Showing 14,081 - 14,100 results of 101,459 for search '(( 5 w decrease ) OR ( 5 ((((ng decrease) OR (a decrease))) OR (mean decrease)) ))', query time: 1.45s Refine Results
  1. 14081

    Liquid Crystalline Features in a Polyolefin of Poly(methylene-1,3-cyclopentane) by Naofumi Naga (2084077)

    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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  6. 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 by Jiawen Zhou (2323381)

    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. …”
  7. 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 by Jiawen Zhou (2323381)

    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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  11. 14091

    Data cleaning and preparation algorithm. by Ayana Ablayeva (22103708)

    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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  17. 14097

    Training set data expansion. by Qingjun Yu (1649473)

    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. …”
  18. 14098

    Structural plane recognition effect. by Qingjun Yu (1649473)

    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. …”
  19. 14099

    Structural plane classification. by Qingjun Yu (1649473)

    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. …”
  20. 14100

    Mixup data expansion. by Qingjun Yu (1649473)

    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. …”