Flowchart of the methodology. by Md. Sakib Hasan (20536529)

“…Furthermore, the cooking loss increased non-significantly (<i>p </i>> 0.05) among treated samples due to lower moisture and fat loss. …”

Preparation of fish ball. by Md. Sakib Hasan (20536529)

“…Furthermore, the cooking loss increased non-significantly (<i>p </i>> 0.05) among treated samples due to lower moisture and fat loss. …”

Raw data of this research work. by Md. Sakib Hasan (20536529)

“…Furthermore, the cooking loss increased non-significantly (<i>p </i>> 0.05) among treated samples due to lower moisture and fat loss. …”

Primer sequence of genes. by Wajeeha Komal (17873637)

“…<div><p>Increasing aquaculture production requires high-density farming, which induces stress, necessitating supplements to mitigate its effects and ensure fish health. …”

S1 Data - by Wajeeha Komal (17873637)

“…<div><p>Increasing aquaculture production requires high-density farming, which induces stress, necessitating supplements to mitigate its effects and ensure fish health. …”

Feed formulation with EDTA supplementation. by Wajeeha Komal (17873637)

“…<div><p>Increasing aquaculture production requires high-density farming, which induces stress, necessitating supplements to mitigate its effects and ensure fish health. …”

Primer sequences. by 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. …”

Reusable Amino Acid/<i>N</i>‑Isopropylacrylamide-Based Organogels for Efficient Oil and Solvent Removal from Water by Sandeep K. Sahoo (2891726)

“…Oil spills, waste disposal, synthetic organic compounds (SOCs), volatile organic compounds (VOCs), and other organic pollutants significantly contaminate the food chain and water supply. …”

Reusable Amino Acid/<i>N</i>‑Isopropylacrylamide-Based Organogels for Efficient Oil and Solvent Removal from Water by Sandeep K. Sahoo (2891726)

“…Oil spills, waste disposal, synthetic organic compounds (SOCs), volatile organic compounds (VOCs), and other organic pollutants significantly contaminate the food chain and water supply. …”

Reusable Amino Acid/<i>N</i>‑Isopropylacrylamide-Based Organogels for Efficient Oil and Solvent Removal from Water by Sandeep K. Sahoo (2891726)

“…Oil spills, waste disposal, synthetic organic compounds (SOCs), volatile organic compounds (VOCs), and other organic pollutants significantly contaminate the food chain and water supply. …”

The overall framework of CARAFE. by 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. by 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. by 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. by 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. by 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. by 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. by 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. by 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. by 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. by 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. …”