Showing 201 - 220 results of 7,971 for search 'significantly ((((((less decrease) OR (larger decrease))) OR (greater decrease))) OR (we decrease))', query time: 0.61s Refine Results
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    S1 File - by Ingmar Lundquist (46422)

    Published 2025
    “…<div><p>The impact of islet neuronal nitric oxide synthase (nNOS) on glucose-stimulated insulin secretion (GSIS) is less understood. We investigated this issue by performing simultaneous measurements of the activity of nNOS <i>versus</i> inducible NOS (iNOS) in GSIS using isolated murine islets. …”
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    Medicare clozapine data analysis. by Luke R. Cavanah (19022435)

    Published 2025
    “…We observed a steady decrease in clozapine use adjusted for population (−18.0%) and spending (−24.9%) over time. …”
  18. 218

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

    Published 2024
    “…This narrow approach overlooks the multifaceted variables influencing runoff, resulting in incomplete and less reliable predictions. To address these challenges, we selected and integrated Random Forest (RF), Support Vector Regression (SVR), and Multilayer Perceptron Regression (MLPR) to develop two coupled intelligent prediction models—RF-SVR and RF-MLPR—due to their complementary strengths. …”
  19. 219

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

    Published 2024
    “…This narrow approach overlooks the multifaceted variables influencing runoff, resulting in incomplete and less reliable predictions. To address these challenges, we selected and integrated Random Forest (RF), Support Vector Regression (SVR), and Multilayer Perceptron Regression (MLPR) to develop two coupled intelligent prediction models—RF-SVR and RF-MLPR—due to their complementary strengths. …”
  20. 220

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

    Published 2024
    “…This narrow approach overlooks the multifaceted variables influencing runoff, resulting in incomplete and less reliable predictions. To address these challenges, we selected and integrated Random Forest (RF), Support Vector Regression (SVR), and Multilayer Perceptron Regression (MLPR) to develop two coupled intelligent prediction models—RF-SVR and RF-MLPR—due to their complementary strengths. …”