Showing 21 - 40 results of 328 for search '(( significantly ((we decrease) OR (a decrease)) ) OR ( significantly linear decrease ))~', query time: 0.38s Refine Results
  1. 21

    Basic physical parameters of red clay. by Hongqi Wang (2208238)

    Published 2024
    “…Furthermore, we quantitatively analyze the specific influence of water content and other factors on the thermal conductivity of stabilized soil and construct a comprehensive prediction model encompassing BP neural network, gradient boosting decision tree, and linear regression models. …”
  2. 22

    BP neural network structure diagram. by Hongqi Wang (2208238)

    Published 2024
    “…Furthermore, we quantitatively analyze the specific influence of water content and other factors on the thermal conductivity of stabilized soil and construct a comprehensive prediction model encompassing BP neural network, gradient boosting decision tree, and linear regression models. …”
  3. 23

    Structure diagram of GBDT model. by Hongqi Wang (2208238)

    Published 2024
    “…Furthermore, we quantitatively analyze the specific influence of water content and other factors on the thermal conductivity of stabilized soil and construct a comprehensive prediction model encompassing BP neural network, gradient boosting decision tree, and linear regression models. …”
  4. 24

    Model prediction error analysis index. by Hongqi Wang (2208238)

    Published 2024
    “…Furthermore, we quantitatively analyze the specific influence of water content and other factors on the thermal conductivity of stabilized soil and construct a comprehensive prediction model encompassing BP neural network, gradient boosting decision tree, and linear regression models. …”
  5. 25

    Fitting curve parameter table. by Hongqi Wang (2208238)

    Published 2024
    “…Furthermore, we quantitatively analyze the specific influence of water content and other factors on the thermal conductivity of stabilized soil and construct a comprehensive prediction model encompassing BP neural network, gradient boosting decision tree, and linear regression models. …”
  6. 26

    Model prediction error analysis. by Hongqi Wang (2208238)

    Published 2024
    “…Furthermore, we quantitatively analyze the specific influence of water content and other factors on the thermal conductivity of stabilized soil and construct a comprehensive prediction model encompassing BP neural network, gradient boosting decision tree, and linear regression models. …”
  7. 27

    Geometric manifold comparison visualization by Eloy Geenjaar (21533195)

    Published 2025
    “…In this work, we propose to use a generative non-linear deep learning model, a disentangled variational autoencoder (DSVAE), that factorizes out window-specific (context) information from timestep-specific (local) information. …”
  8. 28

    Hyperparameter ranges by Eloy Geenjaar (21533195)

    Published 2025
    “…In this work, we propose to use a generative non-linear deep learning model, a disentangled variational autoencoder (DSVAE), that factorizes out window-specific (context) information from timestep-specific (local) information. …”
  9. 29

    Convolutional vs RNN context encoder by Eloy Geenjaar (21533195)

    Published 2025
    “…In this work, we propose to use a generative non-linear deep learning model, a disentangled variational autoencoder (DSVAE), that factorizes out window-specific (context) information from timestep-specific (local) information. …”
  10. 30

    Association of covariates and COPD risk. by Yushan Shi (16440272)

    Published 2024
    “…Stratified analyses revealed no significant differences or interactions.</p><p>Conclusion</p><p>Our findings suggest a potential link between increased dietary niacin intake and a decreased prevalence of COPD.…”
  11. 31

    Design of the D-trial. by Torsten Schober (20485754)

    Published 2024
    “…An increase in PD led to a linear decrease in inflorescence yield per plant (<i>p</i> = 0.02), whereas a positive linear relationship was found for inflorescence yield (<i>p</i> = 0.0001) and CBD yield (<i>p</i> = 0.0002) per m<sup>2</sup>. …”
  12. 32

    Estimated mean values for light interception. by Torsten Schober (20485754)

    Published 2024
    “…An increase in PD led to a linear decrease in inflorescence yield per plant (<i>p</i> = 0.02), whereas a positive linear relationship was found for inflorescence yield (<i>p</i> = 0.0001) and CBD yield (<i>p</i> = 0.0002) per m<sup>2</sup>. …”
  13. 33

    Raw data V-trial. by Torsten Schober (20485754)

    Published 2024
    “…An increase in PD led to a linear decrease in inflorescence yield per plant (<i>p</i> = 0.02), whereas a positive linear relationship was found for inflorescence yield (<i>p</i> = 0.0001) and CBD yield (<i>p</i> = 0.0002) per m<sup>2</sup>. …”
  14. 34

    Raw data D-trial. by Torsten Schober (20485754)

    Published 2024
    “…An increase in PD led to a linear decrease in inflorescence yield per plant (<i>p</i> = 0.02), whereas a positive linear relationship was found for inflorescence yield (<i>p</i> = 0.0001) and CBD yield (<i>p</i> = 0.0002) per m<sup>2</sup>. …”
  15. 35

    Study-related adverse events. by Benjamin R. Lewis (22279166)

    Published 2025
    “…In a linear mixed model analysis (LMM), the MBSR + PAP arm evidenced a significantly larger decrease in QIDS-SR-16 score than the MBSR-only arm from baseline to 2-weeks post-intervention (between-groups effect = 4.6, 95% CI [1.51, 7.70]; <i>p</i> = 0.008). …”
  16. 36

    Study flow chart. by Benjamin R. Lewis (22279166)

    Published 2025
    “…In a linear mixed model analysis (LMM), the MBSR + PAP arm evidenced a significantly larger decrease in QIDS-SR-16 score than the MBSR-only arm from baseline to 2-weeks post-intervention (between-groups effect = 4.6, 95% CI [1.51, 7.70]; <i>p</i> = 0.008). …”
  17. 37

    Study CONSORT diagram. by Benjamin R. Lewis (22279166)

    Published 2025
    “…In a linear mixed model analysis (LMM), the MBSR + PAP arm evidenced a significantly larger decrease in QIDS-SR-16 score than the MBSR-only arm from baseline to 2-weeks post-intervention (between-groups effect = 4.6, 95% CI [1.51, 7.70]; <i>p</i> = 0.008). …”
  18. 38

    Threading Behavior and Dynamics of Ring-Linear Polymer Blends under Poiseuille Flow by Deyin Wang (6028850)

    Published 2024
    “…We investigate the ring-linear polymer blends under Poiseuille flow across a range of flow intensities. …”
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  20. 40

    BMI groups by SES. by Krystal Hunter (6820052)

    Published 2025
    “…BMI was a significant factor in PTB for lower socioeconomic status (LSES) women. …”