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)

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

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)

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

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

“…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. …”

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)

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

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)

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

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)

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

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

“…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. …”

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

“…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. …”

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

“…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. …”

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

“…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. …”

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

“…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. …”

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

“…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. …”

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

“…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. …”

DyHead Structure. by Zhongjian Xie (4633099)

“…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. …”

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

“…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. …”

Structure of GSConv network. by Zhongjian Xie (4633099)

“…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. …”

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

“…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. …”

Improved model distillation structure. by Zhongjian Xie (4633099)

“…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. …”

Table 2_Unsupervised machine learning revealed a correlation between low-dose statins and favorable outcomes in ICH patients.docx by Chaohua Cui (1793155)

“…The low-dose statin group exhibited reduced mortality (p = 0.001), a decreased rate of unfavorable functional outcomes (p < 0.001), and fewer cerebrovascular events (p < 0.001). …”

Table 1_Unsupervised machine learning revealed a correlation between low-dose statins and favorable outcomes in ICH patients.docx by Chaohua Cui (1793155)

“…The low-dose statin group exhibited reduced mortality (p = 0.001), a decreased rate of unfavorable functional outcomes (p < 0.001), and fewer cerebrovascular events (p < 0.001). …”