يعرض 5,781 - 5,800 نتائج من 18,392 نتيجة بحث عن 'significantly ((mean decrease) OR (((((we decrease) OR (a decrease))) OR (nn decrease))))', وقت الاستعلام: 0.62s تنقيح النتائج
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  9. 5789

    Initial transport rate of [<sup>3</sup>H]-hypoxanthine of PhZ mutants (V%). حسب Mariana Barraco-Vega (19996318)

    منشور في 2024
    "…Different letters (a, b, c, d) represent significant differences at p < 0.05 probability level, according to ANOVA and Tukey´s test.…"
  10. 5790

    Data_Sheet_2_Urolithin A alleviates cell senescence by inhibiting ferroptosis and enhances corneal epithelial wound healing.docx حسب Xiao-Xiao Guo (6092141)

    منشور في 2024
    "…The results of RNA-seq of HS-induced corneal epithelial cells showed that the ferroptosis pathway was significantly dysregulated. Further investigation revealed that UA decreased the level of oxidative stress in HCE-T cells, including the levels of LPO and MDA (p < 0.05). …"
  11. 5791

    Data_Sheet_1_Urolithin A alleviates cell senescence by inhibiting ferroptosis and enhances corneal epithelial wound healing.zip حسب Xiao-Xiao Guo (6092141)

    منشور في 2024
    "…The results of RNA-seq of HS-induced corneal epithelial cells showed that the ferroptosis pathway was significantly dysregulated. Further investigation revealed that UA decreased the level of oxidative stress in HCE-T cells, including the levels of LPO and MDA (p < 0.05). …"
  12. 5792

    Combination of intraperitoneal and intratumoral administration of vitamin D3 is more effective in reducing the EAC tumor volume compared to just i.p. administration: حسب Vidya G. Bettada (22208808)

    منشور في 2025
    "…Ki67 on the other hand showed a significant reduction in the expression in the i.p & i.t treated vitamin D3 group. 7D. …"
  13. 5793

    Testing set error. حسب Xiangjuan Liu (618000)

    منشور في 2025
    "…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …"
  14. 5794

    Internal structure of an LSTM cell. حسب Xiangjuan Liu (618000)

    منشور في 2025
    "…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …"
  15. 5795

    Prediction effect of each model after STL. حسب Xiangjuan Liu (618000)

    منشور في 2025
    "…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …"
  16. 5796

    The kernel density plot for data of each feature. حسب Xiangjuan Liu (618000)

    منشور في 2025
    "…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …"
  17. 5797

    Analysis of raw data prediction results. حسب Xiangjuan Liu (618000)

    منشور في 2025
    "…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …"
  18. 5798

    Flowchart of the STL. حسب Xiangjuan Liu (618000)

    منشور في 2025
    "…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …"
  19. 5799

    SARIMA predicts season components. حسب Xiangjuan Liu (618000)

    منشور في 2025
    "…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …"
  20. 5800

    BWO-BiLSTM model prediction results. حسب Xiangjuan Liu (618000)

    منشور في 2025
    "…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …"