بدائل البحث:
greatest decrease » treatment decreased (توسيع البحث), greater increase (توسيع البحث)
linear decrease » linear increase (توسيع البحث)
we decrease » _ decrease (توسيع البحث), nn decrease (توسيع البحث), mean decrease (توسيع البحث)
a decrease » _ decrease (توسيع البحث), _ decreased (توسيع البحث), _ decreases (توسيع البحث)
greatest decrease » treatment decreased (توسيع البحث), greater increase (توسيع البحث)
linear decrease » linear increase (توسيع البحث)
we decrease » _ decrease (توسيع البحث), nn decrease (توسيع البحث), mean decrease (توسيع البحث)
a decrease » _ decrease (توسيع البحث), _ decreased (توسيع البحث), _ decreases (توسيع البحث)
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5841
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5842
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5843
RICTOR silencing inhibits cell proliferation via UGCG regulation.
منشور في 2025"…(<b>C</b>) Cell proliferation studies show a decrease in the proliferation of MCF-7_RICTOR<sup>SH</sup> cells (mean ± SEM, <i>n</i> = 4) compared to MCF-7_SCRAM<sup>SH</sup> cells. …"
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5844
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5845
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5846
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5847
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5848
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5849
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5850
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5851
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5852
Trends in spatial beta diversity over time.
منشور في 2025"…A lack of significant trend is shown in blue. The average linear trend across surveys (black line with 95% confidence interval in gray) is also plotted from a linear mixed effect model with a random slope and intercept for survey. …"
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5853
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. …"
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5854
Pseudo code for coupling model execution process.
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. …"
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5855
Major hyperparameters of RF-MLPR.
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. …"
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5856
Results of RF algorithm screening factors.
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. …"
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5857
Schematic diagram of the basic principles of 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. …"
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5858
Related to Fig 3.
منشور في 2025"…(<b>O</b>, <b>P</b>) Cell proliferation assay confirms an increase in cell proliferation of BT-474_ZFX<sup>OE</sup> cells (mean ± SEM, <i>n</i> = 5) (O), whereas BT-474_ZFX<sup>SL</sup> cells (mean ± SEM, <i>n</i> = 3) show decreased cell proliferation (P). (<b>Q</b>) Tumor growth kinetics recorded a significantly higher growth of BT-474_ZFX<sup>OE</sup> (mean ± SEM, <i>n</i> = 5) than BT-474_VECT<sup>OE</sup> tumors. …"
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5859
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5860
RICTOR regulates UGCG expression via transcription factor Zinc Finger X-linked (ZFX).
منشور في 2025"…<b>(T)</b> Tumor growth kinetics recorded a significantly higher growth of MCF-7_ZFX<sup>OE</sup> (mean ± SEM, <i>n</i> = 4-6) than MCF-7_VECT<sup>OE</sup> tumors. …"