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significant application » significant applications (Expand Search), significant implications (Expand Search), significant association (Expand Search)
application graphs » application rates (Expand Search), application rate (Expand Search), application range (Expand Search)
non decrease » point decrease (Expand Search), note decreased (Expand Search), fold decrease (Expand Search)
nn decrease » _ decrease (Expand Search), a decrease (Expand Search), mean decrease (Expand Search)
Showing 41 - 60 results of 12,885 for search '(( significant application graphs ) OR ( significant ((non decrease) OR (nn decrease)) ))', query time: 0.37s Refine Results
  1. 41
    A random graph configuration.

    A random graph configuration. by Md. Rafiqul Islam (403453)

    Published 2024
    “…Although it is an elementary graph partitioning problem, it is one of the most challenging combinatorial optimization-based problems, and tons of application areas make this problem highly admissible. …”
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  2. 42
    Significant repeated measurements sEMG outcomes.

    Significant repeated measurements sEMG outcomes. by María Benito-de-Pedro (22057468)

    Published 2025
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  3. 43
    Significant single measurement sEMG outcomes.

    Significant single measurement sEMG outcomes. by María Benito-de-Pedro (22057468)

    Published 2025
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  4. 44
    Study case in 4-regular graph.

    Study case in 4-regular graph. by Yeftanus Antonio (11608060)

    Published 2021
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  5. 45
    Scatterplot of data with the averaged data values (first averaged over days by month, and then averaged over the monthly averages by year) with the non-significant decreasing trend from the model superimposed.

    Scatterplot of data with the averaged data values (first averaged over days by month, and then averaged over the monthly averages by year) with the non-significant decreasing trend from the model superimposed. by Rachel Tennant (18196081)

    Published 2024
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  6. 46
    Revisiting the Application of Machine Learning Approaches in Predicting Aqueous Solubility

    Revisiting the Application of Machine Learning Approaches in Predicting Aqueous Solubility by Tianyuan Zheng (19265176)

    Published 2024
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  7. 47
    Revisiting the Application of Machine Learning Approaches in Predicting Aqueous Solubility

    Revisiting the Application of Machine Learning Approaches in Predicting Aqueous Solubility by Tianyuan Zheng (19265176)

    Published 2024
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  8. 48
    Shoot-to-root translocation of GmNN1/FT2a regulates soybean nodulation.

    Shoot-to-root translocation of GmNN1/FT2a regulates soybean nodulation. by Xinxin Li (281237)

    Published 2022
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  9. 49
    Functions of <i>GmNN1/FT2a</i> in nitrogen nutrition and nodulation.

    Functions of <i>GmNN1/FT2a</i> in nitrogen nutrition and nodulation. by Xinxin Li (281237)

    Published 2022
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  10. 50
    Application of the short fixed intervals significantly improved primary data analysis.

    Application of the short fixed intervals significantly improved primary data analysis. by Alex A. Gutsol (6719063)

    Published 2019
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  11. 51
    A Graph Neural Network Model with a Transparent Decision-Making Process Defines the Applicability Domain for Environmental Estrogen Screening

    A Graph Neural Network Model with a Transparent Decision-Making Process Defines the Applicability Domain for Environmental Estrogen Screening by Fan Fan (341438)

    Published 2023
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  12. 52
    Four methods used for GraphMHC model validation: Intra-validation, inter-validation, clinical application, and extra-validation.

    Four methods used for GraphMHC model validation: Intra-validation, inter-validation, clinical application, and extra-validation. by Hoyeon Jeong (18264791)

    Published 2024
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  13. 53
    Feasible solutions for the graph of Fig 1.

    Feasible solutions for the graph of Fig 1. by Md. Rafiqul Islam (403453)

    Published 2024
    “…Although it is an elementary graph partitioning problem, it is one of the most challenging combinatorial optimization-based problems, and tons of application areas make this problem highly admissible. …”
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  14. 54
    CFU-Mk is significantly decreased by GATA1s overexpression in <i>GATA1s</i> strains.

    CFU-Mk is significantly decreased by GATA1s overexpression in <i>GATA1s</i> strains. by Shiori Matsuo (10492159)

    Published 2021
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  15. 55
    Both MRI and SR-PCI demonstrated significant decreases in clinically-relevant articular cartilage parameters.

    Both MRI and SR-PCI demonstrated significant decreases in clinically-relevant articular cartilage parameters. by Suranjan Bairagi (17087667)

    Published 2023
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  16. 56
    Applicability Domains Based on Molecular Graph Contrastive Learning Enable Graph Attention Network Models to Accurately Predict 15 Environmental End Points

    Applicability Domains Based on Molecular Graph Contrastive Learning Enable Graph Attention Network Models to Accurately Predict 15 Environmental End Points by Haobo Wang (2529424)

    Published 2023
    “…By introducing molecular graph (MG) contrastive learning, MG-based ρ<sub>s</sub> and molecular inconsistency in activities (<i>I</i><sub>A</sub>) were calculated and employed for characterizing the structure–activity landscape (SAL)-based applicability domain AD<sub>SAL</sub>{ρ<sub>s</sub>, <i>I</i><sub>A</sub>}. …”
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  17. 57
    Plant growth, nodulation, and N content as affected by manipulating of GmNN1/FT2a.

    Plant growth, nodulation, and N content as affected by manipulating of GmNN1/FT2a. by Xinxin Li (281237)

    Published 2022
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  18. 58
    Expression of <i>GmNN1/FT2a</i> in various tissues of soybean plants.

    Expression of <i>GmNN1/FT2a</i> in various tissues of soybean plants. by Xinxin Li (281237)

    Published 2022
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  19. 59
    GmNN1/FT2a interacted with GmNYFA-C in the BiFC assay.

    GmNN1/FT2a interacted with GmNYFA-C in the BiFC assay. by Xinxin Li (281237)

    Published 2022
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  20. 60
    Error boxplot and violin graphs for the previously published and proposed GPR models.

    Error boxplot and violin graphs for the previously published and proposed GPR models. by Fahd Saeed Alakbari (10701871)

    Published 2025
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