Showing 41 - 50 results of 50 for search '(( significant decrease decrease ) OR ( significance ((set decrease) OR (step decrease)) ))~', query time: 0.31s Refine Results
  1. 41

    Raw Data by Kevin Gries (21956942)

    Published 2025
    “…Utilizing a crossover design, subjects (n=9 [7M, 2F], 24±1y) exercised at 65% VO2max for 60-minutes following a day of reduced activity (IN; 3,581±1,185 steps) and normal activity (A; 11,069±3,631 steps). …”
  2. 42

    Supplemental Tables S1-S5 by Kevin Gries (21956942)

    Published 2025
    “…Utilizing a crossover design, subjects (n=9 [7M, 2F], 24±1y) exercised at 65% VO2max for 60-minutes following a day of reduced activity (IN; 3,581±1,185 steps) and normal activity (A; 11,069±3,631 steps). …”
  3. 43

    Table 1_Laboratory comparison of consumer-grade and research-established wearables for monitoring heart rate, body temperature, and physical acitivity in sub-Saharan Africa.docx by Stefan Mendt (834379)

    Published 2025
    “…These technologies hold significant promise for advancing digital medicine, particularly in remote and rural areas in low-income settings like sub-Saharan Africa, where climate change is exacerbating health risks. …”
  4. 44

    Image 4_Impact of DRG policy on the performance of tertiary hospital inpatient services in Chongqing, China: an interrupted time series study, 2020–2023.png by Yunyu Liu (11739052)

    Published 2025
    “…Background<p>Implementing the diagnosis-related groups (DRG) payment policy in 2021 marked a significant step in increasing the capacity and efficiency of public hospital services in Chongqing, China. …”
  5. 45

    Image 1_Impact of DRG policy on the performance of tertiary hospital inpatient services in Chongqing, China: an interrupted time series study, 2020–2023.png by Yunyu Liu (11739052)

    Published 2025
    “…Background<p>Implementing the diagnosis-related groups (DRG) payment policy in 2021 marked a significant step in increasing the capacity and efficiency of public hospital services in Chongqing, China. …”
  6. 46

    Image 2_Impact of DRG policy on the performance of tertiary hospital inpatient services in Chongqing, China: an interrupted time series study, 2020–2023.png by Yunyu Liu (11739052)

    Published 2025
    “…Background<p>Implementing the diagnosis-related groups (DRG) payment policy in 2021 marked a significant step in increasing the capacity and efficiency of public hospital services in Chongqing, China. …”
  7. 47

    Image 3_Impact of DRG policy on the performance of tertiary hospital inpatient services in Chongqing, China: an interrupted time series study, 2020–2023.png by Yunyu Liu (11739052)

    Published 2025
    “…Background<p>Implementing the diagnosis-related groups (DRG) payment policy in 2021 marked a significant step in increasing the capacity and efficiency of public hospital services in Chongqing, China. …”
  8. 48

    Ambient Air Pollutant Dynamics (2010–2025) and the Exceptional Winter 2016–17 Pollution Episode: Implications for a Uranium/Arsenic Exposure Event by Thomas Clemens Carmine (19756929)

    Published 2025
    “…Mean Imputation Fallback for Predictors:</i> Any remaining gaps in these non-PM₂.₅ pollutant columns (after linear interpolation) were filled using the overall column mean (sklearn.impute.SimpleImputer(strategy='mean')) to ensure a complete predictor set for the subsequent step. Values imputed via this method do not receive a distinct flag but retain their flag from the previous step (0 or 2); the Imputation_Stats sheet reports the count affected.XGBoost</p><p><br></p><p dir="ltr"><i>3. …”
  9. 49

    PDLB - Balance Sheet by Nguyen Linh (19516642)

    Published 2024
    “…</p><p><br></p><p dir="ltr">On the expense side, there was significant concern into the 2023 results about non-interest expense. …”
  10. 50

    Reinforcement Learning for Assessing Route Instruction Usability in Complex Indoor Spaces by Reza Arabsheibani (14244716)

    Published 2025
    “…Our results show that RL agents successfully learn to navigate even with incomplete instructions, significantly outperforming random agents. Agents trained on diverse environments generalize well to novel settings, although performance decreases with higher environmental complexity and finer-grained instruction grammars when instructions are incomplete. …”