يعرض 1,061 - 1,080 نتائج من 9,330 نتيجة بحث عن 'significantly ((((((less decrease) OR (we decrease))) OR (mean decrease))) OR (teer decrease))', وقت الاستعلام: 0.80s تنقيح النتائج
  1. 1061

    Table 7_Absolute abundance calculation enhances the significance of microbiome data in antibiotic treatment studies.xlsx حسب Stefanie Wagner (743707)

    منشور في 2025
    "…Here, GCN correction additionally uncovered significant decreases of Lactobacillus and Faecalibacterium. …"
  2. 1062

    Table 9_Absolute abundance calculation enhances the significance of microbiome data in antibiotic treatment studies.xlsx حسب Stefanie Wagner (743707)

    منشور في 2025
    "…Here, GCN correction additionally uncovered significant decreases of Lactobacillus and Faecalibacterium. …"
  3. 1063

    Analytical framework and statistical methods. حسب Na Chen (153323)

    منشور في 2024
    "…Our findings reveal significant variations in income insecurity and social protection responses across these groups. the pandemic had a significant impact on household incomes globally, with lower-middle-income countries experiencing the most significant income reductions. …"
  4. 1064

    Theoretical frameworks of social protection. حسب Na Chen (153323)

    منشور في 2024
    "…Our findings reveal significant variations in income insecurity and social protection responses across these groups. the pandemic had a significant impact on household incomes globally, with lower-middle-income countries experiencing the most significant income reductions. …"
  5. 1065

    Image 3_Absolute abundance calculation enhances the significance of microbiome data in antibiotic treatment studies.tif حسب Stefanie Wagner (743707)

    منشور في 2025
    "…Here, GCN correction additionally uncovered significant decreases of Lactobacillus and Faecalibacterium. …"
  6. 1066

    Image 1_Absolute abundance calculation enhances the significance of microbiome data in antibiotic treatment studies.tif حسب Stefanie Wagner (743707)

    منشور في 2025
    "…Here, GCN correction additionally uncovered significant decreases of Lactobacillus and Faecalibacterium. …"
  7. 1067

    Image 2_Absolute abundance calculation enhances the significance of microbiome data in antibiotic treatment studies.tif حسب Stefanie Wagner (743707)

    منشور في 2025
    "…Here, GCN correction additionally uncovered significant decreases of Lactobacillus and Faecalibacterium. …"
  8. 1068

    Image 4_Absolute abundance calculation enhances the significance of microbiome data in antibiotic treatment studies.tif حسب Stefanie Wagner (743707)

    منشور في 2025
    "…Here, GCN correction additionally uncovered significant decreases of Lactobacillus and Faecalibacterium. …"
  9. 1069

    Structure diagram of ensemble model. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…By developing and validating both empirical and machine learning prediction models, we unravel the evolution of thermal conductivity in response to these factors: within the range of influencing variables, thermal conductivity exhibits an exponential or linear increase with rising water content and dry density, while it decreases exponentially with increasing freeze-thaw cycles. …"
  10. 1070

    Fitting formula parameter table. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…By developing and validating both empirical and machine learning prediction models, we unravel the evolution of thermal conductivity in response to these factors: within the range of influencing variables, thermal conductivity exhibits an exponential or linear increase with rising water content and dry density, while it decreases exponentially with increasing freeze-thaw cycles. …"
  11. 1071

    Test plan. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…By developing and validating both empirical and machine learning prediction models, we unravel the evolution of thermal conductivity in response to these factors: within the range of influencing variables, thermal conductivity exhibits an exponential or linear increase with rising water content and dry density, while it decreases exponentially with increasing freeze-thaw cycles. …"
  12. 1072

    Fitting surface parameters. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…By developing and validating both empirical and machine learning prediction models, we unravel the evolution of thermal conductivity in response to these factors: within the range of influencing variables, thermal conductivity exhibits an exponential or linear increase with rising water content and dry density, while it decreases exponentially with increasing freeze-thaw cycles. …"
  13. 1073

    Model generalisation validation error analysis. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…By developing and validating both empirical and machine learning prediction models, we unravel the evolution of thermal conductivity in response to these factors: within the range of influencing variables, thermal conductivity exhibits an exponential or linear increase with rising water content and dry density, while it decreases exponentially with increasing freeze-thaw cycles. …"
  14. 1074

    Empirical model prediction error analysis. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…By developing and validating both empirical and machine learning prediction models, we unravel the evolution of thermal conductivity in response to these factors: within the range of influencing variables, thermal conductivity exhibits an exponential or linear increase with rising water content and dry density, while it decreases exponentially with increasing freeze-thaw cycles. …"
  15. 1075

    Fitting curve parameters. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…By developing and validating both empirical and machine learning prediction models, we unravel the evolution of thermal conductivity in response to these factors: within the range of influencing variables, thermal conductivity exhibits an exponential or linear increase with rising water content and dry density, while it decreases exponentially with increasing freeze-thaw cycles. …"
  16. 1076

    Test instrument. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…By developing and validating both empirical and machine learning prediction models, we unravel the evolution of thermal conductivity in response to these factors: within the range of influencing variables, thermal conductivity exhibits an exponential or linear increase with rising water content and dry density, while it decreases exponentially with increasing freeze-thaw cycles. …"
  17. 1077

    Empirical model establishment process. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…By developing and validating both empirical and machine learning prediction models, we unravel the evolution of thermal conductivity in response to these factors: within the range of influencing variables, thermal conductivity exhibits an exponential or linear increase with rising water content and dry density, while it decreases exponentially with increasing freeze-thaw cycles. …"
  18. 1078

    Model prediction error trend chart. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…By developing and validating both empirical and machine learning prediction models, we unravel the evolution of thermal conductivity in response to these factors: within the range of influencing variables, thermal conductivity exhibits an exponential or linear increase with rising water content and dry density, while it decreases exponentially with increasing freeze-thaw cycles. …"
  19. 1079

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

    منشور في 2024
    "…By developing and validating both empirical and machine learning prediction models, we unravel the evolution of thermal conductivity in response to these factors: within the range of influencing variables, thermal conductivity exhibits an exponential or linear increase with rising water content and dry density, while it decreases exponentially with increasing freeze-thaw cycles. …"
  20. 1080

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

    منشور في 2024
    "…By developing and validating both empirical and machine learning prediction models, we unravel the evolution of thermal conductivity in response to these factors: within the range of influencing variables, thermal conductivity exhibits an exponential or linear increase with rising water content and dry density, while it decreases exponentially with increasing freeze-thaw cycles. …"