Showing 2,301 - 2,320 results of 18,571 for search 'significantly ((((we decrease) OR (greater decrease))) OR (((mean decrease) OR (a decrease))))', query time: 0.78s Refine Results
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    Top 10 significant functional annotations of up-regulated DEGs. by Meitner Cadena (22216261)

    Published 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.…”
  7. 2307

    Top 10 significant functional annotations of down-regulated DEGs. by Meitner Cadena (22216261)

    Published 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.…”
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    Major hyperparameters of RF-SVR. by Jintao Li (448681)

    Published 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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    Pseudo code for coupling model execution process. by Jintao Li (448681)

    Published 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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    Major hyperparameters of RF-MLPR. by Jintao Li (448681)

    Published 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. …”
  12. 2312

    Results of RF algorithm screening factors. by Jintao Li (448681)

    Published 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. …”
  13. 2313

    Schematic diagram of the basic principles of SVR. by Jintao Li (448681)

    Published 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. …”
  14. 2314

    Colored Gold Ions Enabled High-Transparent and Low-Haze Cellulose Films with Excellent Flame-Retardant and UV to Blue Light-Blocking Performance by Qiu Fu (10830823)

    Published 2025
    “…Herein, we reported a facile and green process for fabricating biodegradable and flexible gold ion (Au<sup>3+</sup>)-coordinated cellulose-based light filters with diverse UV- and HEBL-screening capacities via adsorption of Au<sup>3+</sup>. …”
  15. 2315

    Colored Gold Ions Enabled High-Transparent and Low-Haze Cellulose Films with Excellent Flame-Retardant and UV to Blue Light-Blocking Performance by Qiu Fu (10830823)

    Published 2025
    “…Herein, we reported a facile and green process for fabricating biodegradable and flexible gold ion (Au<sup>3+</sup>)-coordinated cellulose-based light filters with diverse UV- and HEBL-screening capacities via adsorption of Au<sup>3+</sup>. …”
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    Colored Gold Ions Enabled High-Transparent and Low-Haze Cellulose Films with Excellent Flame-Retardant and UV to Blue Light-Blocking Performance by Qiu Fu (10830823)

    Published 2025
    “…Herein, we reported a facile and green process for fabricating biodegradable and flexible gold ion (Au<sup>3+</sup>)-coordinated cellulose-based light filters with diverse UV- and HEBL-screening capacities via adsorption of Au<sup>3+</sup>. …”
  17. 2317

    Colored Gold Ions Enabled High-Transparent and Low-Haze Cellulose Films with Excellent Flame-Retardant and UV to Blue Light-Blocking Performance by Qiu Fu (10830823)

    Published 2025
    “…Herein, we reported a facile and green process for fabricating biodegradable and flexible gold ion (Au<sup>3+</sup>)-coordinated cellulose-based light filters with diverse UV- and HEBL-screening capacities via adsorption of Au<sup>3+</sup>. …”
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