Search alternatives:
linear decrease » linear increase (Expand Search)
nn decrease » _ decrease (Expand Search), gy decreased (Expand Search), b1 decreased (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
linear decrease » linear increase (Expand Search)
nn decrease » _ decrease (Expand Search), gy decreased (Expand Search), b1 decreased (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
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6841
Income satisfaction measure.
Published 2025“…In this paper, we apply a novel approach to try and address this issue. …”
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6842
Marginal effect of HTD on income and SWB.
Published 2025“…In this paper, we apply a novel approach to try and address this issue. …”
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6843
Estimation procedure flow-chart.
Published 2025“…In this paper, we apply a novel approach to try and address this issue. …”
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6844
Structural model outline.
Published 2025“…In this paper, we apply a novel approach to try and address this issue. …”
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6845
Amino acid metabolic pathways are influenced by the NC1 POM cycle over expression.
Published 2025“…Box and whisker plots of selected metabolites that displayed significant increase or decrease in the NC1 POM cycle producing strain (NC), red boxes, or empty vector producing strain (YC) green boxes. …”
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6846
Direct Observation of Liquid–Liquid Phase Separation and Core–Shell Morphology of PM<sub>2.5</sub> Collected from Three Northeast Asian Cities and Implications for N<sub>2</sub>O<s...
Published 2025“…As the shell becomes more viscous, the diffusivity of N<sub>2</sub>O<sub>5</sub> decreases, thereby lowering the N<sub>2</sub>O<sub>5</sub> uptake coefficient by 1–3 orders of magnitude and significantly restricting N<sub>2</sub>O<sub>5</sub> uptake. …”
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6847
Direct Observation of Liquid–Liquid Phase Separation and Core–Shell Morphology of PM<sub>2.5</sub> Collected from Three Northeast Asian Cities and Implications for N<sub>2</sub>O<s...
Published 2025“…As the shell becomes more viscous, the diffusivity of N<sub>2</sub>O<sub>5</sub> decreases, thereby lowering the N<sub>2</sub>O<sub>5</sub> uptake coefficient by 1–3 orders of magnitude and significantly restricting N<sub>2</sub>O<sub>5</sub> uptake. …”
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6848
Direct Observation of Liquid–Liquid Phase Separation and Core–Shell Morphology of PM<sub>2.5</sub> Collected from Three Northeast Asian Cities and Implications for N<sub>2</sub>O<s...
Published 2025“…As the shell becomes more viscous, the diffusivity of N<sub>2</sub>O<sub>5</sub> decreases, thereby lowering the N<sub>2</sub>O<sub>5</sub> uptake coefficient by 1–3 orders of magnitude and significantly restricting N<sub>2</sub>O<sub>5</sub> uptake. …”
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6849
Direct Observation of Liquid–Liquid Phase Separation and Core–Shell Morphology of PM<sub>2.5</sub> Collected from Three Northeast Asian Cities and Implications for N<sub>2</sub>O<s...
Published 2025“…As the shell becomes more viscous, the diffusivity of N<sub>2</sub>O<sub>5</sub> decreases, thereby lowering the N<sub>2</sub>O<sub>5</sub> uptake coefficient by 1–3 orders of magnitude and significantly restricting N<sub>2</sub>O<sub>5</sub> uptake. …”
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6850
Direct Observation of Liquid–Liquid Phase Separation and Core–Shell Morphology of PM<sub>2.5</sub> Collected from Three Northeast Asian Cities and Implications for N<sub>2</sub>O<s...
Published 2025“…As the shell becomes more viscous, the diffusivity of N<sub>2</sub>O<sub>5</sub> decreases, thereby lowering the N<sub>2</sub>O<sub>5</sub> uptake coefficient by 1–3 orders of magnitude and significantly restricting N<sub>2</sub>O<sub>5</sub> uptake. …”
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6851
Direct Observation of Liquid–Liquid Phase Separation and Core–Shell Morphology of PM<sub>2.5</sub> Collected from Three Northeast Asian Cities and Implications for N<sub>2</sub>O<s...
Published 2025“…As the shell becomes more viscous, the diffusivity of N<sub>2</sub>O<sub>5</sub> decreases, thereby lowering the N<sub>2</sub>O<sub>5</sub> uptake coefficient by 1–3 orders of magnitude and significantly restricting N<sub>2</sub>O<sub>5</sub> uptake. …”
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6852
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6853
Prediction of transition readiness.
Published 2025“…In most transition domains, help needed did not decrease with age and was not affected by function. …”
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6854
Dataset visualization diagram.
Published 2025“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”
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6855
Dataset sample images.
Published 2025“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”
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6856
Performance comparison of different models.
Published 2025“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”
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6857
C2f and BC2f module structure diagrams.
Published 2025“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”
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6858
YOLOv8n detection results diagram.
Published 2025“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”
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6859
YOLOv8n-BWG model structure diagram.
Published 2025“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”
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6860
BiFormer structure diagram.
Published 2025“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”