Showing 8,661 - 8,680 results of 17,946 for search 'significantly ((((larger decrease) OR (a decrease))) OR (teer decrease))', query time: 0.65s Refine Results
  1. 8661

    Image 7_Inflammation mediated brain damage and cytokine expression in a maternally derived murine model for preterm hypoxic-ischemic encephalopathy.tiff by Tyler C. Hillman (13030476)

    Published 2025
    “…MAP2 expression was significantly decreased (p < 0.05) between 1.5–6.0 mm of the brain compared to Saline-Hypoxia and Naïve animals. …”
  2. 8662

    Image 6_Inflammation mediated brain damage and cytokine expression in a maternally derived murine model for preterm hypoxic-ischemic encephalopathy.tiff by Tyler C. Hillman (13030476)

    Published 2025
    “…MAP2 expression was significantly decreased (p < 0.05) between 1.5–6.0 mm of the brain compared to Saline-Hypoxia and Naïve animals. …”
  3. 8663

    Image 1_Inflammation mediated brain damage and cytokine expression in a maternally derived murine model for preterm hypoxic-ischemic encephalopathy.tiff by Tyler C. Hillman (13030476)

    Published 2025
    “…MAP2 expression was significantly decreased (p < 0.05) between 1.5–6.0 mm of the brain compared to Saline-Hypoxia and Naïve animals. …”
  4. 8664

    Image 13_Inflammation mediated brain damage and cytokine expression in a maternally derived murine model for preterm hypoxic-ischemic encephalopathy.tiff by Tyler C. Hillman (13030476)

    Published 2025
    “…MAP2 expression was significantly decreased (p < 0.05) between 1.5–6.0 mm of the brain compared to Saline-Hypoxia and Naïve animals. …”
  5. 8665

    Image 8_Inflammation mediated brain damage and cytokine expression in a maternally derived murine model for preterm hypoxic-ischemic encephalopathy.tiff by Tyler C. Hillman (13030476)

    Published 2025
    “…MAP2 expression was significantly decreased (p < 0.05) between 1.5–6.0 mm of the brain compared to Saline-Hypoxia and Naïve animals. …”
  6. 8666

    Table_1_Fasting mimicking diet during neo-adjuvant chemotherapy in breast cancer patients: a randomized controlled trial study.DOCX by Alireza Bahrami (11597663)

    Published 2024
    “…There was a significant increase in median glucose and median insulin levels (p = 0.01 and p = 0.005, respectively) in the control group between baseline and after cycle 8. …”
  7. 8667

    Image 2_Inflammation mediated brain damage and cytokine expression in a maternally derived murine model for preterm hypoxic-ischemic encephalopathy.tiff by Tyler C. Hillman (13030476)

    Published 2025
    “…MAP2 expression was significantly decreased (p < 0.05) between 1.5–6.0 mm of the brain compared to Saline-Hypoxia and Naïve animals. …”
  8. 8668

    Image 3_Inflammation mediated brain damage and cytokine expression in a maternally derived murine model for preterm hypoxic-ischemic encephalopathy.tiff by Tyler C. Hillman (13030476)

    Published 2025
    “…MAP2 expression was significantly decreased (p < 0.05) between 1.5–6.0 mm of the brain compared to Saline-Hypoxia and Naïve animals. …”
  9. 8669

    Image 9_Inflammation mediated brain damage and cytokine expression in a maternally derived murine model for preterm hypoxic-ischemic encephalopathy.tiff by Tyler C. Hillman (13030476)

    Published 2025
    “…MAP2 expression was significantly decreased (p < 0.05) between 1.5–6.0 mm of the brain compared to Saline-Hypoxia and Naïve animals. …”
  10. 8670

    Trends of HIV/AIDS in Ethiopia (1990-2021). by Tegene Atamenta Kitaw (17930374)

    Published 2025
    “…Statistical analyses included Joinpoint regression to identify trend shifts and calculate the Annual and Average Annual Percentage Change over time, with significance determined at a p-value of 0.05. Geographic variations were visualized using ArcGIS Pro, highlighting regions with varying HIV burdens. …”
  11. 8671

    The overall framework of CARAFE. by Zhongjian Xie (4633099)

    Published 2025
    “…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. 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. …”
  12. 8672

    KPD-YOLOv7-GD network structure diagram. by Zhongjian Xie (4633099)

    Published 2025
    “…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. 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. …”
  13. 8673

    Comparison experiment of accuracy improvement. by Zhongjian Xie (4633099)

    Published 2025
    “…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. 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. …”
  14. 8674

    Comparison of different pruning rates. by Zhongjian Xie (4633099)

    Published 2025
    “…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. 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. …”
  15. 8675

    Comparison of experimental results at ablation. by Zhongjian Xie (4633099)

    Published 2025
    “…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. 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. …”
  16. 8676

    Result of comparison of different lightweight. by Zhongjian Xie (4633099)

    Published 2025
    “…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. 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. …”
  17. 8677

    DyHead Structure. by Zhongjian Xie (4633099)

    Published 2025
    “…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. 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. …”
  18. 8678

    The parameters of the training phase. by Zhongjian Xie (4633099)

    Published 2025
    “…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. 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. …”
  19. 8679

    Structure of GSConv network. by Zhongjian Xie (4633099)

    Published 2025
    “…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. 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. …”
  20. 8680

    Comparison experiment of accuracy improvement. by Zhongjian Xie (4633099)

    Published 2025
    “…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. 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. …”