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. …”

Improved model distillation 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. …”

Image 2_Case report: Significant lesion reduction and neural structural changes following ibogaine treatments for multiple sclerosis.jpeg by David Qixiang Chen (8198265)

“…We present two case studies of MS patients who underwent a novel ibogaine treatment, highlighting significant neuroimaging changes and clinical improvements. …”

Image 1_Case report: Significant lesion reduction and neural structural changes following ibogaine treatments for multiple sclerosis.jpeg by David Qixiang Chen (8198265)

“…We present two case studies of MS patients who underwent a novel ibogaine treatment, highlighting significant neuroimaging changes and clinical improvements. …”

Table 1_Dual variants of uncertain significance in a case of hyper-IgM syndrome: implications for diagnosis and management.docx by Nourhen Agrebi (14151222)

“…Background<p>Hyper-IgM syndrome (HIGM) is a genetic immunodeficiency characterized by elevated to normal IgM levels and decreased IgG, IgA, and IgE. The overlapping clinical presentations of different gene mutations complicate diagnosis and management.…”

Cyclosporin A significantly reduces the survival rate and completely inhibits the formation of multicellular aggregates in tolerant strains under caspofungin stress. by Yongqin Wu (272012)

“…<p>(A) Cyclosporin A decreases the survival rate of tolerant strains under caspofungin. …”

DataSheet1_Significant nocturnal wakefulness after sleep onset in metabolic dysfunction–associated steatotic liver disease.PDF by Sofia Schaeffer (20379954)

“…HC 45.4 min vs. 21.3 min, p = 0.0004), and decreased sleep efficiency (MASLD vs. HC 86.5% vs. 92.8%, p = 0.0008) compared with HC despite comparable sleep duration. …”

DataSheet3_Significant nocturnal wakefulness after sleep onset in metabolic dysfunction–associated steatotic liver disease.PDF by Sofia Schaeffer (20379954)

“…HC 45.4 min vs. 21.3 min, p = 0.0004), and decreased sleep efficiency (MASLD vs. HC 86.5% vs. 92.8%, p = 0.0008) compared with HC despite comparable sleep duration. …”

DataSheet2_Significant nocturnal wakefulness after sleep onset in metabolic dysfunction–associated steatotic liver disease.PDF by Sofia Schaeffer (20379954)

“…HC 45.4 min vs. 21.3 min, p = 0.0004), and decreased sleep efficiency (MASLD vs. HC 86.5% vs. 92.8%, p = 0.0008) compared with HC despite comparable sleep duration. …”

DataSheet4_Significant nocturnal wakefulness after sleep onset in metabolic dysfunction–associated steatotic liver disease.PDF by Sofia Schaeffer (20379954)

“…HC 45.4 min vs. 21.3 min, p = 0.0004), and decreased sleep efficiency (MASLD vs. HC 86.5% vs. 92.8%, p = 0.0008) compared with HC despite comparable sleep duration. …”

Discovery of Dual-Acting Biofilm Inhibitors against Pseudomonas aeruginosa by the Coupling of 3‑Hydroxypyridin-4(1<i>H</i>)‑ones with <i>N</i>‑Phenylamide QS Inhibitors by Hao-Zhong Long (19685972)

“…The hit compound <b>19l</b> (IC₅₀ = 0.33 ± 0.06 μM) demonstrated significant biofilm inhibition compared to previously reported 3-hydroxypyridin-4(1<i>H</i>)-one derivatives <i>in vitro</i>. …”

Table 1_Predicted habitat and areas of ecological significance shifts of top predators in the South Shetland Islands under climate changes.docx by Yufei Dai (621612)

“…Key findings include: 1) The spatial distribution of top predators in the South Shetland Islands is predominantly influenced by bathymetry, mixed layer thickness (Mlotst), and sea ice concentration (SIC). 2) The highly suitable habitats for the Gentoo Penguin (Pygoscelis papua), Humpback Whale (Megaptera novaeangliae), and Light-mantled Albatross (Phoebetria palpebrata) are expected to decrease under various future scenarios. 3) The AES in the South Shetland Islands are predominantly concentrated along the southern coastal areas. 4) The AES on the western side of the islands are projected to undergo significant fluctuations, while those on the eastern side are likely to exhibit minor changes, with the central area remaining relatively stable.…”