Search alternatives:
teer decrease » greater decrease (Expand Search)
we decrease » _ decrease (Expand Search), a decrease (Expand Search), use decreased (Expand Search)
nn decrease » _ decrease (Expand Search), a decrease (Expand Search), gy decreased (Expand Search)
teer decrease » greater decrease (Expand Search)
we decrease » _ decrease (Expand Search), a decrease (Expand Search), use decreased (Expand Search)
nn decrease » _ decrease (Expand Search), a decrease (Expand Search), gy decreased (Expand Search)
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721
Fitting curve parameters.
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. …”
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722
Test instrument.
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. …”
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723
Empirical model establishment process.
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. …”
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724
Model prediction error trend chart.
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. …”
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725
Basic physical parameters of red clay.
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. …”
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726
BP neural network structure diagram.
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. …”
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727
Structure diagram of GBDT model.
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. …”
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728
Model prediction error analysis index.
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. …”
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729
Fitting curve parameter table.
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. …”
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730
Model prediction error analysis.
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. …”
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731
Bluetooth beacons with colour coded lanyards.
Published 2025“…During the baseline period, the time to antimicrobials decreased significantly in Kenya (132 and 58 minutes) at control and intervention sites. …”
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732
Table 1_United States military working dogs from 2019 to 2021: analysis of causes of service discharge and decreased service life.docx
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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733
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734
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735
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736
Parvalbumin-positive interneurons (PV-INs) in perilesional tissue respond to optogenetic stimulation and are involved in voluntary movement, but show a decreased firing rate.
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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737
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738
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739
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740