Showing 2,201 - 2,220 results of 21,342 for search '(( significant ((time decrease) OR (greater decrease)) ) OR ( significant decrease decrease ))', query time: 0.46s Refine Results
  1. 2201

    Risk of bias summary. by Duc Tran Quang (20564967)

    Published 2025
    “…The observed decrease in body weight could be partially attributed to factors influencing energy balance, as evidenced by the significantly lower mean calorie intake at the end of the intervention (1694.71 kcal/day, 95% CI: 1498.57–1890.85) compared to the baseline intake (2000.64 kcal/day, 95% CI: 1830–2172.98), despite the absence of intentional efforts to restrict energy intake by the participants. …”
  2. 2202

    Criteria for study selection. by Duc Tran Quang (20564967)

    Published 2025
    “…The observed decrease in body weight could be partially attributed to factors influencing energy balance, as evidenced by the significantly lower mean calorie intake at the end of the intervention (1694.71 kcal/day, 95% CI: 1498.57–1890.85) compared to the baseline intake (2000.64 kcal/day, 95% CI: 1830–2172.98), despite the absence of intentional efforts to restrict energy intake by the participants. …”
  3. 2203

    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.…”
  4. 2204

    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.…”
  5. 2205

    Summary of related studies. by Most. Fatematuz Zohora (19429152)

    Published 2024
    “…The DBDAA introduces real-time processing for safety checks, significantly improving system efficiency and reducing the risk of deadlocks. …”
  6. 2206

    Process execution halted due to deadlock. by Most. Fatematuz Zohora (19429152)

    Published 2024
    “…The DBDAA introduces real-time processing for safety checks, significantly improving system efficiency and reducing the risk of deadlocks. …”
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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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  18. 2218

    Testing set error. by Xiangjuan Liu (618000)

    Published 2025
    “…<div><p>This study constructs a multi-stage hybrid forecasting model using hog price time series data and its influencing factors to improve prediction accuracy. …”
  19. 2219

    Internal structure of an LSTM cell. by Xiangjuan Liu (618000)

    Published 2025
    “…<div><p>This study constructs a multi-stage hybrid forecasting model using hog price time series data and its influencing factors to improve prediction accuracy. …”
  20. 2220

    Prediction effect of each model after STL. by Xiangjuan Liu (618000)

    Published 2025
    “…<div><p>This study constructs a multi-stage hybrid forecasting model using hog price time series data and its influencing factors to improve prediction accuracy. …”