Showing 2,701 - 2,720 results of 2,767 for search '(( significant decrease decrease ) OR ( significant ((mean decrease) OR (a decrease)) ))~', query time: 0.31s Refine Results
  1. 2701

    Assembly process of machine recognition form. by Zhe Hu (787283)

    Published 2025
    “…Then, the LSTM model is trained using this sliding window approach, achieving a root mean square error(RMSE) of 0.03 on the test set. …”
  2. 2702

    Process of steel truss incremental launching. by Zhe Hu (787283)

    Published 2025
    “…Then, the LSTM model is trained using this sliding window approach, achieving a root mean square error(RMSE) of 0.03 on the test set. …”
  3. 2703

    CGAN and AutoML stacking device. by Zhe Hu (787283)

    Published 2025
    “…Then, the LSTM model is trained using this sliding window approach, achieving a root mean square error(RMSE) of 0.03 on the test set. …”
  4. 2704

    Comprehensive prediction process of shape errors. by Zhe Hu (787283)

    Published 2025
    “…Then, the LSTM model is trained using this sliding window approach, achieving a root mean square error(RMSE) of 0.03 on the test set. …”
  5. 2705

    Shape error manual calculation process. by Zhe Hu (787283)

    Published 2025
    “…Then, the LSTM model is trained using this sliding window approach, achieving a root mean square error(RMSE) of 0.03 on the test set. …”
  6. 2706

    U-wave estimates versus R-matrix noise variance. by Zhe Hu (787283)

    Published 2025
    “…Then, the LSTM model is trained using this sliding window approach, achieving a root mean square error(RMSE) of 0.03 on the test set. …”
  7. 2707

    Sliding window process. by Zhe Hu (787283)

    Published 2025
    “…Then, the LSTM model is trained using this sliding window approach, achieving a root mean square error(RMSE) of 0.03 on the test set. …”
  8. 2708

    Original record form of error matrix. by Zhe Hu (787283)

    Published 2025
    “…Then, the LSTM model is trained using this sliding window approach, achieving a root mean square error(RMSE) of 0.03 on the test set. …”
  9. 2709

    Form for machine recognition. by Zhe Hu (787283)

    Published 2025
    “…Then, the LSTM model is trained using this sliding window approach, achieving a root mean square error(RMSE) of 0.03 on the test set. …”
  10. 2710

    RMSE versus architectural parameters. by Zhe Hu (787283)

    Published 2025
    “…Then, the LSTM model is trained using this sliding window approach, achieving a root mean square error(RMSE) of 0.03 on the test set. …”
  11. 2711

    Kalman process. by Zhe Hu (787283)

    Published 2025
    “…Then, the LSTM model is trained using this sliding window approach, achieving a root mean square error(RMSE) of 0.03 on the test set. …”
  12. 2712

    Attention mechanism. by Zhe Hu (787283)

    Published 2025
    “…Then, the LSTM model is trained using this sliding window approach, achieving a root mean square error(RMSE) of 0.03 on the test set. …”
  13. 2713

    Shape error measurement results statistics. by Zhe Hu (787283)

    Published 2025
    “…Then, the LSTM model is trained using this sliding window approach, achieving a root mean square error(RMSE) of 0.03 on the test set. …”
  14. 2714

    Broader frequency tuning in auditory cortex of <i>Fmr1</i> KO rats despite unaltered subcortical tuning properties. by D. Walker Gauthier (21637726)

    Published 2025
    “…Boxplots dots represent individual multiunit clusters. All other values are means ± SEM. **<i>p</i> < 0.01, ***<i>p</i> < 0.0001, ns = not significant. …”
  15. 2715

    Table 1_Waning neutralizing antibodies through 180 days after homologous and heterologous boosters of inactivated COVID-19 vaccine.docx by Zhifei Chen (1740625)

    Published 2025
    “…Participants were recruited from December 2021 to June 2022, with a follow-up period of 180 days. We evaluated humoral immune responses and their longevity by measuring the geometric mean titers (GMTs) of neutralizing antibodies against the SARS-CoV-2 virus at various time points post-boost. …”
  16. 2716

    Fig 4 - by Nehal Shawky Nagy (17721213)

    Published 2024
    “…Values are expressed as mean ± SEM; n = 3 rats for each group. Different superscripts on the columns are significantly different at p≤0.05.…”
  17. 2717

    Effects of vidarabine, V2E, V3E and V5E on cardiac fibrosis. by Kenji Suita (750993)

    Published 2025
    “…(B) Chronic ISO infusion significantly increased the area of fibrosis in cardiac muscle but this increase was significantly decreased by Vida, V2E, V3E and V5E. …”
  18. 2718

    Data Sheet 1_Effect of high intakes of protein-only and carbohydrate-only on plasma metabolites and hormones, in addition to nitrogen excretion.xlsx by Matthieu Clauss (9769343)

    Published 2025
    “…Additionally, we measured urinary nitrogen excretion as a marker of protein degradation.</p>Methods<p>Fourteen young, healthy, moderate-to-well-trained participants (VO<sub>2max</sub> 50.6 ± 2.9 mL·kg<sup>-1</sup>·min<sup>-1</sup>; mean ± SEM) reported in the morning after an overnight fast. …”
  19. 2719

    Outcomes of Corticosteroids Combined with 15 Mg/Week Methotrexate as Initial Treatment for Acute Vogt-Koyanagi-Harada Disease by Yao Lu (185912)

    Published 2025
    “…All the eyes had retinal reattachment and the choroidal thickness significantly decreased. Sun-set glow fundus was identified in 18 eyes (23.1%). …”
  20. 2720

    Table 1_Unveiling the global impact of hypertensive heart disease among individuals aged ≥ 65 years: metabolic risk factors and future projections for 2050.xlsx by Ning An (618997)

    Published 2025
    “…Metabolic risks, particularly high systolic blood pressure, were significant contributors to HHD-related mortality and DALYs, with a pronounced impact in high-SDI regions. …”