Showing 921 - 940 results of 9,062 for search 'significant ((((gap decrease) OR (((we decrease) OR (greatest decrease))))) OR (mean decrease))', query time: 0.68s Refine Results
  1. 921

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

    Published 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. …”
  2. 922

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

    Published 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. …”
  3. 923

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

    Published 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. …”
  4. 924

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

    Published 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. …”
  5. 925

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

    Published 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. …”
  6. 926

    Fitting curve parameter table. by Hongqi Wang (2208238)

    Published 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. …”
  7. 927

    Model prediction error analysis. by Hongqi Wang (2208238)

    Published 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. …”
  8. 928

    Bluetooth beacons with colour coded lanyards. by J Mark Ansermino (13958512)

    Published 2025
    “…During the baseline period, the time to antimicrobials decreased significantly in Kenya (132 and 58 minutes) at control and intervention sites. …”
  9. 929

    Table 1_United States military working dogs from 2019 to 2021: analysis of causes of service discharge and decreased service life.docx by Dakota Discepolo (16804191)

    Published 2025
    “…ANOVA analysis comparing mean service life resulted in significant differences of mean overall service with main effects of breed (p = 0.0252), outcome (p = 0.0004), service discharge category (p < 0.0001), and subpopulation (p < 0.0001).…”
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    Parvalbumin-positive interneurons (PV-INs) in perilesional tissue respond to optogenetic stimulation and are involved in voluntary movement, but show a decreased firing rate. by Livia Vignozzi (22430567)

    Published 2025
    “…<b>E</b>, Quantification of the average firing rate of the recorded PV-INs in response to optogenetic stimulation. A significant decrease in firing activity is evident in stroke animals (Two-tailed <i>T</i> Test *** <i><i>P</i></i> < 0.001). …”
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