يعرض 2,181 - 2,200 نتائج من 4,823 نتيجة بحث عن 'significant ((((((gap decrease) OR (greater decrease))) OR (nn decrease))) OR (mean decrease))', وقت الاستعلام: 0.58s تنقيح النتائج
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    Flow chart of research object screening. حسب Wenyao Xie (21567889)

    منشور في 2025
    "…Notably, these associations were significant only in non-cancer populations (testosterone: OR=0.97, P < 0.001; estradiol: OR=1.64, P < 0.001), and generally absent in cancer patients except for older cancer patients (≥60 years) where testosterone maintained a significant negative correlation with ALI (OR=0.96, P = 0.020). …"
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    The loss of bone in the femoral distal epiphysis is affected by housing type and weightlessness conditions in microgravity. حسب Rukmani Cahill (20939813)

    منشور في 2025
    "…(F) Conn.D is decreased in FL. Data shown are the mean ±  standard deviation with a scatter plot (ns: non-significant, * : p <  0.033, **: p <  0.002, ***: p <  0.0002). …"
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    The overall framework of CARAFE. حسب Zhongjian Xie (4633099)

    منشور في 2025
    "…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …"
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    KPD-YOLOv7-GD network structure diagram. حسب Zhongjian Xie (4633099)

    منشور في 2025
    "…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …"