Fig 10 - EC. حسب Curtis Chepsiror (21368103)

Construction and efficacy evaluation of nomogram model related to risk score. حسب Jiaxin Jiang (10656134)

Raw data. حسب Ji Min Kim (9154816)

"…</p><p>Results</p><p>Mig-6 expression was significantly reduced in the adipose tissue of obese mice and humans. …"

Western blot raw data for PCNA. حسب Minjun Kim (1588486)

"…</p><p>Results</p><p>Diabetic rats exhibited significantly accelerated gastric emptying (liquid GE AUC: + 45.2%; solid GE: + 23.1%, p < 0.01) and elevated blood glucose (327.4 ± 22.8 mg/dL vs. 96.2 ± 10.1 mg/dL in controls, p < 0.001), accompanied by increased oxidative stress markers and expression of c-Kit, ERK1/2, and PCNA. …"

Immunostain of c-Kit. حسب Minjun Kim (1588486)

"…</p><p>Results</p><p>Diabetic rats exhibited significantly accelerated gastric emptying (liquid GE AUC: + 45.2%; solid GE: + 23.1%, p < 0.01) and elevated blood glucose (327.4 ± 22.8 mg/dL vs. 96.2 ± 10.1 mg/dL in controls, p < 0.001), accompanied by increased oxidative stress markers and expression of c-Kit, ERK1/2, and PCNA. …"

Western blot raw data for p-ERK. حسب Minjun Kim (1588486)

"…</p><p>Results</p><p>Diabetic rats exhibited significantly accelerated gastric emptying (liquid GE AUC: + 45.2%; solid GE: + 23.1%, p < 0.01) and elevated blood glucose (327.4 ± 22.8 mg/dL vs. 96.2 ± 10.1 mg/dL in controls, p < 0.001), accompanied by increased oxidative stress markers and expression of c-Kit, ERK1/2, and PCNA. …"

Western blot raw data for c-Kit. حسب Minjun Kim (1588486)

"…</p><p>Results</p><p>Diabetic rats exhibited significantly accelerated gastric emptying (liquid GE AUC: + 45.2%; solid GE: + 23.1%, p < 0.01) and elevated blood glucose (327.4 ± 22.8 mg/dL vs. 96.2 ± 10.1 mg/dL in controls, p < 0.001), accompanied by increased oxidative stress markers and expression of c-Kit, ERK1/2, and PCNA. …"

Primer sequences. حسب Koichi Yoshimoto (9298643)

"…We examined the mRNA expression of <i>Ddit3</i> (CHOP) and <i>Casp3</i> (caspase-3) on day one after the surgery; mRNA expression of both genes appeared to decrease in the KUS121 group, as compared with the control group, although differences between groups were not significant. …"

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

"…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. …"

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

"…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. …"

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

"…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. …"

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

"…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. …"

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

"…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. …"

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

"…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. …"

DyHead Structure. حسب Zhongjian Xie (4633099)

"…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. …"

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

"…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. …"

Structure of GSConv network. حسب Zhongjian Xie (4633099)

"…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. …"

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

"…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. …"

Improved model distillation structure. حسب Zhongjian Xie (4633099)

"…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. …"

Surgical changes through ISIW implantation. حسب Sayaka Kimura-Uchida (22793666)

"…Pre- and postoperative data are compared by Tukey’s HSD test and asterisks mean statistical significance (p < 0.05). IOP decreases significantly from 3 to 12 months after surgery whereas GMS decreases from one day to 12 months after surgery. …"