يعرض 141 - 160 نتائج من 7,622 نتيجة بحث عن 'significantly ((((((less decrease) OR (teer decrease))) OR (we decrease))) OR (greater decrease))', وقت الاستعلام: 0.65s تنقيح النتائج
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    S1 File - حسب Ingmar Lundquist (46422)

    منشور في 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. …"
  3. 143

    Ethogram describing all outcome measures. حسب Sara Hintze (3216885)

    منشور في 2024
    الموضوعات:
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    Medicare clozapine data analysis. حسب Luke R. Cavanah (19022435)

    منشور في 2025
    "…We observed a steady decrease in clozapine use adjusted for population (−18.0%) and spending (−24.9%) over time. …"
  17. 157

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

    منشور في 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. …"
  18. 158

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

    منشور في 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. 159

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

    منشور في 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. 160

    Results of RF algorithm screening factors. حسب Jintao Li (448681)

    منشور في 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. …"