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364 results on '"Wang, Wenyao"'

1. Improving Formability of Titanium Bipolar Plate via Hot Stamping

Author

Zhang, Xianglu, Guo, Nan, Wang, Wenyao, Yan, Zhuoqi, Yang, Daijun, Min, Junying, Ming, Pingwen, Zhang, Cunman, Chaari, Fakher, Series Editor, Gherardini, Francesco, Series Editor, Ivanov, Vitalii, Series Editor, Haddar, Mohamed, Series Editor, Cavas-Martínez, Francisco, Editorial Board Member, di Mare, Francesca, Editorial Board Member, Kwon, Young W., Editorial Board Member, Trojanowska, Justyna, Editorial Board Member, Xu, Jinyang, Editorial Board Member, Mocellin, Katia, editor, Bouchard, Pierre-Olivier, editor, Bigot, Régis, editor, and Balan, Tudor, editor

Published
2024
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2. CLeBPI: Contrastive Learning for Bug Priority Inference

Author

Wang, Wenyao, Wu, Chenhao, and He, Jie

Subjects
Computer Science - Software Engineering
Abstract

Automated bug priority inference can reduce the time overhead of bug triagers for priority assignments, improving the efficiency of software maintenance. Currently, there are two orthogonal lines for this task, i.e., traditional machine learning based (TML-based) and neural network based (NN-based) approaches. Although these approaches achieve competitive performance, our observation finds that existing approaches face the following two issues: 1) TML-based approaches require much manual feature engineering and cannot learn the semantic information of bug reports; 2) Both TML-based and NN-based approaches cannot effectively address the label imbalance problem because they are difficult to distinguish the semantic difference between bug reports with different priorities. In this paper, we propose CLeBPI (Contrastive Learning for Bug Priority Inference), which leverages pre-trained language model and contrastive learning to tackle the above-mentioned two issues. Specifically, CLeBPI is first pre-trained on a large-scale bug report corpus in a self-supervised way, thus it can automatically learn contextual representations of bug reports without manual feature engineering. Afterward, it is further pre-trained by a contrastive learning objective, which enables it to distinguish semantic differences between bug reports, learning more precise contextual representations for each bug report. When finishing pre-training, we can connect a classification layer to CLeBPI and fine-tune it for bug priority inference in a supervised way. To verify the effectiveness of CLeBPI, we choose four baseline approaches and conduct comparison experiments on a public dataset. The experimental results show that CLeBPI outperforms all baseline approaches by 23.86%-77.80% in terms of weighted average F1-score, showing its effectiveness., Comment: 22 pages, 5 figures

Published
2022

5. The application of large language models in medicine: A scoping review

Author

Meng, Xiangbin, Yan, Xiangyu, Zhang, Kuo, Liu, Da, Cui, Xiaojuan, Yang, Yaodong, Zhang, Muhan, Cao, Chunxia, Wang, Jingjia, Wang, Xuliang, Gao, Jun, Wang, Yuan-Geng-Shuo, Ji, Jia-ming, Qiu, Zifeng, Li, Muzi, Qian, Cheng, Guo, Tianze, Ma, Shuangquan, Wang, Zeying, Guo, Zexuan, Lei, Youlan, Shao, Chunli, Wang, Wenyao, Fan, Haojun, and Tang, Yi-Da

Published
2024
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13. Human Perception-based Evaluation Criterion for Ultra-high Resolution Cell Membrane Segmentation

Author

Shi, Ruohua, Wang, Wenyao, Li, Zhixuan, He, Liuyuan, Sheng, Kaiwen, Ma, Lei, Du, Kai, Jiang, Tingting, and Huang, Tiejun

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Computer vision technology is widely used in biological and medical data analysis and understanding. However, there are still two major bottlenecks in the field of cell membrane segmentation, which seriously hinder further research: lack of sufficient high-quality data and lack of suitable evaluation criteria. In order to solve these two problems, this paper first proposes an Ultra-high Resolution Image Segmentation dataset for the Cell membrane, called U-RISC, the largest annotated Electron Microscopy (EM) dataset for the Cell membrane with multiple iterative annotations and uncompressed high-resolution raw data. During the analysis process of the U-RISC, we found that the current popular segmentation evaluation criteria are inconsistent with human perception. This interesting phenomenon is confirmed by a subjective experiment involving twenty people. Furthermore, to resolve this inconsistency, we propose a new evaluation criterion called Perceptual Hausdorff Distance (PHD) to measure the quality of cell membrane segmentation results. Detailed performance comparison and discussion of classic segmentation methods along with two iterative manual annotation results under existing evaluation criteria and PHD is given., Comment: submitted to ICLR 2021

Published
2020

24. SARS‐CoV‐2 spike protein acts as a β‐adrenergic receptor agonist: A potential mechanism for cardiac sequelae of long COVID.

Author

Deng, Xiangning, Cui, Hongtu, Liang, Hao, Wang, Xinyu, Yu, Haiyi, Wang, Jingjia, Wang, Wenyao, Liu, Dongyang, Zhang, Youyi, Dong, Erdan, Tang, Yida, and Xiao, Han

Subjects
POST-acute COVID-19 syndrome, ALLOSTERIC proteins, CYCLIC adenylic acid, BLOOD proteins, MOLECULAR docking
Abstract

Background: Currently, pathophysiological mechanisms of post‐acute sequelae of coronavirus disease‐19‐cardiovascular syndrome (PASC‐CVS) remain unknown. Methods and results: Patients with PASC‐CVS exhibited significantly higher circulating levels of severe acute respiratory syndrome‐coronavirus‐2 spike protein S1 than the non‐PASC‐CVS patients and healthy controls. Moreover, individuals with high plasma spike protein S1 concentrations exhibited elevated heart rates and normalized low frequency, suggesting cardiac β‐adrenergic receptor (β‐AR) hyperactivity. Microscale thermophoresis (MST) assay revealed that the spike protein bound to β1‐ and β2‐AR, but not to D1‐dopamine receptor. These interactions were blocked by β1‐ and β2‐AR blockers. Molecular docking and MST assay of β‐AR mutants revealed that the spike protein interacted with the extracellular loop 2 of both β‐ARs. In cardiomyocytes, spike protein dose‐dependently increased the cyclic adenosine monophosphate production with or without epinephrine, indicating its allosteric effects on β‐ARs. Conclusion: Severe acute respiratory syndrome‐coronavirus‐2 spike proteins act as an allosteric β‐AR agonist, leading to cardiac β‐AR hyperactivity, thus contributing to PASC‐CVS. [ABSTRACT FROM AUTHOR]

Published
2024
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28. An Experimental Study on the Frictional Behavior of Ultrathin Metal Sheets at Elevated Temperatures.

Author

Xia, Yuhang, Hou, Zeran, Tan, Jinjun, Wang, Wenyao, Guo, Nan, and Min, Junying

Subjects
SHEET metal, HIGH temperatures, FERRITIC steel, METAL formability, STAINLESS steel, PSEUDOPLASTIC fluids
Abstract

Hot forming is an effective approach for improving the formability of ultrathin metal sheets, such as those made of stainless steel and pure titanium. However, the increased friction coefficient between the tool and the high-temperature metal sheet negatively affects material flow during hot forming, potentially resulting in severe local thinning or even cracking. This study explores the frictional behavior of 0.1 mm thick ferritic stainless steel (FSS) and commercially pure titanium (CP-Ti) sheets at elevated temperatures. A friction testing apparatus was developed to measure the friction coefficients of these metal sheets from room temperature (25 °C) up to 600 °C. The friction coefficient of the FSS sheet increased monotonically with temperature, whereas that of the CP-Ti sheet first increased and then decreased. Post-friction testing microscopic examination demonstrated that built-up edges formed on the surfaces of the friction blocks when rubbed against the stainless steel, contributing to the higher friction coefficients. This study provides a foundation for understanding frictional behavior during the hot forming of ultrathin metal sheets. [ABSTRACT FROM AUTHOR]

Published
2024
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41. Additional file 6 of Assessment of redundant randomized clinical trials among patients with ST segment elevation myocardial infarction

Author

Jia, Yuanxi, Liang, Jun, Wang, Wenyao, Wei, Xin, Xiao, Shaoming, and Robinson, Karen A.

Abstract

Additional file 6: Figure A4. Cumulative Meta-Analysis for Statins. This figure shows the result of a cumulative meta-analysis for RCTs assessing statins conducted in mainland China. Only the first 50 RCTs were analyzed due to the limit of Stata.

Published
2023
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43. Additional file 5 of Association between liver fibrosis and thrombotic or bleeding events in acute coronary syndrome patients

Author

Liu, Yupeng, Song, Jingjing, Wang, Wenyao, Zhang, Kuo, Yang, Jie, Wen, Jun, Meng, Xiangbin, Gao, Jun, Wang, Jingjia, Shao, Chunli, and Tang, Yi-Da

Abstract

Additional file 5: Supplementary Table 1. Univariable and multivariable Cox regression analysis of MACCE. Supplementary Table 2. Baseline characteristics according to the absence and presence of MACCE

Published
2023
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46. Additional file 5 of Assessment of redundant randomized clinical trials among patients with ST segment elevation myocardial infarction

Author

Jia, Yuanxi, Liang, Jun, Wang, Wenyao, Wei, Xin, Xiao, Shaoming, and Robinson, Karen A.

Abstract

Additional file 5: Figure A3. Cumulative Meta-Analysis for P2Y12 Receptor Inhibitors. This figure shows the result of a cumulative meta-analysis for RCTs assessing P2Y12 receptor inhibitors conducted in mainland China. Only the first 50 RCTs were analyzed due to the limit of Stata.

Published
2023
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47. Additional file 4 of Assessment of redundant randomized clinical trials among patients with ST segment elevation myocardial infarction

Author

Jia, Yuanxi, Liang, Jun, Wang, Wenyao, Wei, Xin, Xiao, Shaoming, and Robinson, Karen A.

Abstract

Additional file 4: Figure A2. Cumulative Meta-Analysis for Reperfusion. This figure shows the result of a cumulative meta-analysis for RCTs assessing reperfusion conducted in mainland China. Only the first 50 RCTs were analyzed due to the limit of Stata.

Published
2023
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