Showing 261 - 280 results of 850 for search '(( significant decrease decrease ) OR ( significant ((time decrease) OR (mean decrease)) ))~', query time: 0.32s Refine Results
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    The TOR inhibitors Rapamycin and AZD-8055 strongly reduce RPS6 phosphorylation and cell proliferation in Vasa2+/Piwi1+ cells. by Eudald Pascual-Carreras (12115380)

    Published 2025
    “…<i>n</i> = 2–4 biological replicates per condition, with 15 individuals per replicate. Significance levels for Student <i>t</i> test are indicated for adjusted <i>p</i> values: *<i>p</i> < 0.05, ***<i>p</i> < 0.001, ***<i>p</i> < 0.0001. d: day(s), n.s.: non-significant. …”
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    Run times of two algorithms. by Gourab Saha (8987405)

    Published 2025
    “…The LSTM model is used for healthy vegetation area forecasting highlighting the changes of the vegetation area over time. Such analysis helps to decide whether that land is suitable for farming or not. …”
  9. 269

    COVID19 effect on essential services. by Admas Abera (11821659)

    Published 2024
    “…The present study found that the mean number of patients treated for TB declined by 35 patients (β: -34.62; 95%CI: -50.29, -18.95) compared to the pre-COVID-19 era while the number of new patients enrolled for ART decreased by 71 patients (β: -70.62; 95%CI: -107.19, -34.05). …”
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    Detailed information of the observation datasets. by Weidong Ji (129916)

    Published 2025
    “…Generally speaking, there is no clear linear relationship between scores and the other variables. 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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    General technical specification for GW154/6700. by Weidong Ji (129916)

    Published 2025
    “…Generally speaking, there is no clear linear relationship between scores and the other variables. 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.…”