Search alternatives:
ng decrease » nn decrease (Expand Search), _ decrease (Expand Search), we decrease (Expand Search)
w decrease » we decrease (Expand Search), _ decrease (Expand Search), _ decreased (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
5 w » 5 wt (Expand Search)
ng decrease » nn decrease (Expand Search), _ decrease (Expand Search), we decrease (Expand Search)
w decrease » we decrease (Expand Search), _ decrease (Expand Search), _ decreased (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
5 w » 5 wt (Expand Search)
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14081
Liquid Crystalline Features in a Polyolefin of Poly(methylene-1,3-cyclopentane)
Published 2008“…A liquid crystalline phase has been discovered in a polyolefin of poly(methylene-1,3-cyclopentane) (PMCP) having low molecular weight, which was obtained with cyclization polymerization of 1,5-hexadiene (HD) using a zirconocene catalyst in the presence of chain transfer reagents. …”
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14082
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14083
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14084
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14085
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14086
Data_Sheet_5_P16INK4a Deletion Ameliorates Damage of Intestinal Epithelial Barrier and Microbial Dysbiosis in a Stress-Induced Premature Senescence Model of Bmi-1 Deficiency.docx
Published 2021“…P16<sup>INK4a</sup> deletion could maintain barrier function and microbiota balance in Bmi-1<sup>–/–</sup> mice through strengthening formation of TJ and decreasing macrophages-secreted TNF-α induced by Desulfovibrio entering the intestinal epithelium. …”
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14087
Data_Sheet_5_P16INK4a Deletion Ameliorates Damage of Intestinal Epithelial Barrier and Microbial Dysbiosis in a Stress-Induced Premature Senescence Model of Bmi-1 Deficiency.docx
Published 2021“…P16<sup>INK4a</sup> deletion could maintain barrier function and microbiota balance in Bmi-1<sup>–/–</sup> mice through strengthening formation of TJ and decreasing macrophages-secreted TNF-α induced by Desulfovibrio entering the intestinal epithelium. …”
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14088
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14089
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14090
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14091
Data cleaning and preparation algorithm.
Published 2025“…</p><p>Results</p><p>Over the decade, age-standardized incidence rates decreased from 5.55 to 5.40 per 100,000, while mortality rates rose from 3.75 to 4.75 per 100,000. …”
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14092
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14093
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14094
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14095
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14096
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14097
Training set data expansion.
Published 2024“…Based on the PyTorch deep learning framework, the initial U<sup>2</sup>-Net network weights were set, the learning rate was set to 0.001, the training batch was 4, and the Adam optimizer adaptively adjusted the learning rate during the training process. A dedicated network model for segmenting structural planes was obtained, and the model achieved a maximum F-measure value of 0.749 when the confidence threshold was set to 0.7, with an accuracy rate of up to 0.85 within the range of recall rate greater than 0.5. …”
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14098
Structural plane recognition effect.
Published 2024“…Based on the PyTorch deep learning framework, the initial U<sup>2</sup>-Net network weights were set, the learning rate was set to 0.001, the training batch was 4, and the Adam optimizer adaptively adjusted the learning rate during the training process. A dedicated network model for segmenting structural planes was obtained, and the model achieved a maximum F-measure value of 0.749 when the confidence threshold was set to 0.7, with an accuracy rate of up to 0.85 within the range of recall rate greater than 0.5. …”
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14099
Structural plane classification.
Published 2024“…Based on the PyTorch deep learning framework, the initial U<sup>2</sup>-Net network weights were set, the learning rate was set to 0.001, the training batch was 4, and the Adam optimizer adaptively adjusted the learning rate during the training process. A dedicated network model for segmenting structural planes was obtained, and the model achieved a maximum F-measure value of 0.749 when the confidence threshold was set to 0.7, with an accuracy rate of up to 0.85 within the range of recall rate greater than 0.5. …”
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14100
Mixup data expansion.
Published 2024“…Based on the PyTorch deep learning framework, the initial U<sup>2</sup>-Net network weights were set, the learning rate was set to 0.001, the training batch was 4, and the Adam optimizer adaptively adjusted the learning rate during the training process. A dedicated network model for segmenting structural planes was obtained, and the model achieved a maximum F-measure value of 0.749 when the confidence threshold was set to 0.7, with an accuracy rate of up to 0.85 within the range of recall rate greater than 0.5. …”