بدائل البحث:
significant decrease » significant increase (توسيع البحث), significantly increased (توسيع البحث)
greater decrease » greatest decrease (توسيع البحث), greater increase (توسيع البحث), greater disease (توسيع البحث)
nn decrease » _ decrease (توسيع البحث), a decrease (توسيع البحث), mean decrease (توسيع البحث)
significant decrease » significant increase (توسيع البحث), significantly increased (توسيع البحث)
greater decrease » greatest decrease (توسيع البحث), greater increase (توسيع البحث), greater disease (توسيع البحث)
nn decrease » _ decrease (توسيع البحث), a decrease (توسيع البحث), mean decrease (توسيع البحث)
-
3981
-
3982
-
3983
-
3984
-
3985
-
3986
-
3987
-
3988
Interventions for Psychological Stress in Pregnant African American Women: A Scoping Review
منشور في 2025الموضوعات: -
3989
-
3990
-
3991
-
3992
-
3993
-
3994
Top 10 significant functional annotations of up-regulated DEGs.
منشور في 2025"…Functional annotations are ordered by decreasing significance, with color indicating significance according to the legend’s color scale, the ratio of genes on the horizontal axis, and DEG count represented by circle size.…"
-
3995
Top 10 significant functional annotations of down-regulated DEGs.
منشور في 2025"…Functional annotations are ordered by decreasing significance, with color indicating significance level based on the legend’s color scale, the ratio of genes on the horizontal axis, and DEG count represented by circle size.…"
-
3996
-
3997
-
3998
-
3999
-
4000
Major hyperparameters of RF-SVR.
منشور في 2024"…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R<sup>2</sup> value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …"