Showing 14,161 - 14,180 results of 105,884 for search '(( 2 de decrease ) OR ( 5 ((((ng decrease) OR (a decrease))) OR (mean decrease)) ))', query time: 1.70s Refine Results
  1. 14161

    Table_5_H2S Regulation of Metabolism in Cucumber in Response to Salt-Stress Through Transcriptome and Proteome Analysis.xls by Jinglong Jiang (9256409)

    Published 2020
    “…Here, an integrated transcriptomic and proteomic analysis based on RNA-seq and 2-DE was used to investigate the global mechanism underlying H<sub>2</sub>S-regulated salt-stress tolerance. …”
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    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. …”
  4. 14164

    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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  7. 14167

    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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  13. 14173

    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. …”
  14. 14174

    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. …”
  15. 14175

    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. …”
  16. 14176

    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. …”
  17. 14177

    Marking example. 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. 14178

    Image_1_Maternal exposure to air pollution alters energy balance transiently according to gender and changes gut microbiota.jpg by Olivia Pizetta Zordão (15181675)

    Published 2023
    “…This group showed a slight increase in food intake. In female offspring from FA/PM<sub>2.5</sub>, BW, and leptin levels were elevated. …”
  19. 14179

    DataSheet_1_Maternal exposure to air pollution alters energy balance transiently according to gender and changes gut microbiota.pdf by Olivia Pizetta Zordão (15181675)

    Published 2023
    “…This group showed a slight increase in food intake. In female offspring from FA/PM<sub>2.5</sub>, BW, and leptin levels were elevated. …”
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