Showing 10,541 - 10,560 results of 48,561 for search '(( a ((mean decrease) OR (linear decrease)) ) OR ( a ((greatest decrease) OR (largest decrease)) ))', query time: 0.73s Refine Results
  1. 10541

    Axial forces in the tension zone. by Maogang Tian (21485116)

    Published 2025
    “…Furthermore, parametric studies reveal that the pile base displacement exhibits a non-linear trend of initially decreasing and then increasing with larger inclination angles of the inclined piles. …”
  2. 10542

    VPF and VIPF. by Maogang Tian (21485116)

    Published 2025
    “…Furthermore, parametric studies reveal that the pile base displacement exhibits a non-linear trend of initially decreasing and then increasing with larger inclination angles of the inclined piles. …”
  3. 10543

    Rabbit length of stay data. by Ashley Sum Yin U. (18437434)

    Published 2024
    “…The median LOS of rabbits was 29 days, highlighting the pressing need to improve their time to adoption. A linear model was constructed to identify predictors of LOS of adopted rabbits (n = 1203) and revealed that intake year, intake month, source of intake, age, cephalic type, and breed size significantly predicted time to adoption for rabbits (F(37, 1165) = 7.95, <i>p</i> < 2.2e-16, adjusted R<sup>2</sup> = 0.18). …”
  4. 10544

    Surrender reasons (n = 649). by Ashley Sum Yin U. (18437434)

    Published 2024
    “…The median LOS of rabbits was 29 days, highlighting the pressing need to improve their time to adoption. A linear model was constructed to identify predictors of LOS of adopted rabbits (n = 1203) and revealed that intake year, intake month, source of intake, age, cephalic type, and breed size significantly predicted time to adoption for rabbits (F(37, 1165) = 7.95, <i>p</i> < 2.2e-16, adjusted R<sup>2</sup> = 0.18). …”
  5. 10545

    R script. by Ashley Sum Yin U. (18437434)

    Published 2024
    “…The median LOS of rabbits was 29 days, highlighting the pressing need to improve their time to adoption. A linear model was constructed to identify predictors of LOS of adopted rabbits (n = 1203) and revealed that intake year, intake month, source of intake, age, cephalic type, and breed size significantly predicted time to adoption for rabbits (F(37, 1165) = 7.95, <i>p</i> < 2.2e-16, adjusted R<sup>2</sup> = 0.18). …”
  6. 10546

    Surrender reasons and descriptions. by Ashley Sum Yin U. (18437434)

    Published 2024
    “…The median LOS of rabbits was 29 days, highlighting the pressing need to improve their time to adoption. A linear model was constructed to identify predictors of LOS of adopted rabbits (n = 1203) and revealed that intake year, intake month, source of intake, age, cephalic type, and breed size significantly predicted time to adoption for rabbits (F(37, 1165) = 7.95, <i>p</i> < 2.2e-16, adjusted R<sup>2</sup> = 0.18). …”
  7. 10547

    Number of rabbit intakes by intake year. by Ashley Sum Yin U. (18437434)

    Published 2024
    “…The median LOS of rabbits was 29 days, highlighting the pressing need to improve their time to adoption. A linear model was constructed to identify predictors of LOS of adopted rabbits (n = 1203) and revealed that intake year, intake month, source of intake, age, cephalic type, and breed size significantly predicted time to adoption for rabbits (F(37, 1165) = 7.95, <i>p</i> < 2.2e-16, adjusted R<sup>2</sup> = 0.18). …”
  8. 10548

    Rabbit intake data. by Ashley Sum Yin U. (18437434)

    Published 2024
    “…The median LOS of rabbits was 29 days, highlighting the pressing need to improve their time to adoption. A linear model was constructed to identify predictors of LOS of adopted rabbits (n = 1203) and revealed that intake year, intake month, source of intake, age, cephalic type, and breed size significantly predicted time to adoption for rabbits (F(37, 1165) = 7.95, <i>p</i> < 2.2e-16, adjusted R<sup>2</sup> = 0.18). …”
  9. 10549
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  11. 10551

    Conceptual framework (Adapted from Abidin, 1995). by Rachel Brathwaite (767994)

    Published 2023
    “…Secondly, focal correlates were included in the cross-fit partialing out lasso linear/logistic regression (double machine-learning) model. …”
  12. 10552

    Study dataset. by Rachel Brathwaite (767994)

    Published 2023
    “…Secondly, focal correlates were included in the cross-fit partialing out lasso linear/logistic regression (double machine-learning) model. …”
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  20. 10560