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Your search keyword '"YIN, WEIWEI"' showing total 262 results
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262 results on '"YIN, WEIWEI"'

1. Targeting pro-inflammatory T cells as a novel therapeutic approach to potentially resolve atherosclerosis in humans

Author

Fan, Lin, Liu, Junwei, Hu, Wei, Chen, Zexin, Lan, Jie, Zhang, Tongtong, Zhang, Yang, Wu, Xianpeng, Zhong, Zhiwei, Zhang, Danyang, Zhang, Jinlong, Qin, Rui, Chen, Hui, Zong, Yunfeng, Zhang, Jianmin, Chen, Bing, Jiang, Jun, Cheng, Jifang, Zhou, Jingyi, Gao, Zhiwei, Liu, Zhenjie, Chai, Ying, Fan, Junqiang, Wu, Pin, Chen, Yinxuan, Zhu, Yuefeng, Wang, Kai, Yuan, Ying, Huang, Pintong, Zhang, Ying, Feng, Huiqin, Song, Kaichen, Zeng, Xun, Zhu, Wei, Hu, Xinyang, Yin, Weiwei, Chen, Wei, and Wang, Jian’an

Published
2024
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2. Author Correction: Targeting pro-inflammatory T cells as a novel therapeutic approach to potentially resolve atherosclerosis in humans

Author

Fan, Lin, Liu, Junwei, Hu, Wei, Chen, Zexin, Lan, Jie, Zhang, Tongtong, Zhang, Yang, Wu, Xianpeng, Zhong, Zhiwei, Zhang, Danyang, Zhang, Jinlong, Qin, Rui, Chen, Hui, Zong, Yunfeng, Zhang, Jianmin, Chen, Bing, Jiang, Jun, Cheng, Jifang, Zhou, Jingyi, Gao, Zhiwei, Liu, Zhenjie, Chai, Ying, Fan, Junqiang, Wu, Pin, Chen, Yinxuan, Zhu, Yuefeng, Wang, Kai, Yuan, Ying, Huang, Pintong, Zhang, Ying, Feng, Huiqin, Song, Kaichen, Zeng, Xun, Zhu, Wei, Hu, Xinyang, Yin, Weiwei, Chen, Wei, and Wang, Jian’an

Published
2024
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11. Sand Erosion Behaviors and Mechanism of Pseudoelastic TiNi Shape Memory Alloy

Author

Yin, Weiwei, Liu, Xiaoguang, Pan, Peidao, Wang, Lielong, Ceccarelli, Marco, Series Editor, Agrawal, Sunil K., Advisory Editor, Corves, Burkhard, Advisory Editor, Glazunov, Victor, Advisory Editor, Hernández, Alfonso, Advisory Editor, Huang, Tian, Advisory Editor, Jauregui Correa, Juan Carlos, Advisory Editor, Takeda, Yukio, Advisory Editor, and Tan, Jianrong, editor

Published
2022
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28. An Integrated Transformer with Collaborative Tokens Mining for Fine-Grained Recognition

Author

Yin, Weiwei Yang and Jian

Subjects
fine-grained recognition, transformer, image patches, tokens
Abstract

Fine-grained recognition mainly classifies subclass images into hundreds of subcategorical labels by locating the discriminative regions (e.g., Cape May warbler or Magnolia warbler bird). Due to the high complexity and non-differentiation of region locations through the traditional backbone architecture, most existing approaches utilize multi-level reinforcement learning to distinguish the similar appearance among sub-categories. These methods explore incomplete information through only the intra-class informative regions in one image or the inter-class and intra-class relationship in pairwise images, leading to the tendency for overlapped region locations. Since the inter-class correlations and new backbone with complete contextual semantic information play important roles in distinguishing fine-grained classes, we propose a novel transformer with the collaborative token mining (TCTM) scheme by fully exploiting the relationships between inter-class and intra-class regions. The proposed TCTM scheme with a new transformer backbone consists of two modules that collaboratively explore the spatially aware tokens: the Pyramid Tokens Multiplication (PTM) module which exploits the integrated multi-stage inter-class and intra-class correlations from new transformer architecture and the Tokens Proposals Generation (TPG) module which captures two groups of top-four discriminative tokens. The two PTMs extract contrastive tokens for each image and learn to rank these tokens, assuming that those from the same class and the same module should have smaller distances. The TPGs further sort and update the candidate tokens from the extracted attention tokens by ranking their probabilities with ground truth subcategorical labels. Through the collaboration between the PTM and TPG, our TCTM scheme can take the integrated correlations into account and mine the discriminative tokens for final fine-grained classification. Extensive experiments on four popular benchmarks show that our proposed TCTM outperforms the state-of-the-art methods by a large margin.

Published
2023
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34. Additional file 10 of Single-cell analysis reveals HBV-specific PD-1+CD8+ TRM cells in tumor borders are associated with HBV-related hepatic damage and fibrosis in HCC patients

Author

Liu, Lulu, Liu, Junwei, Li, Pan, Luo, Jijun, Qin, Rui, Peng, Qiao, Li, Bin, Wei, Xuyong, Wang, Tian, Shi, Hongyu, Wang, Ming-Da, Li, Chao, Fang, Weijia, Chen, Wei, Xu, Xiao, Yang, Tian, Yin, Weiwei, and Zeng, Xun

Abstract

Additional file 10: FigureS3.Correlation of HBV clinical features with immune features. (A) Comparisons ofthe frequencies of major immune subsets across HBV infection and HCC tissues.(B and C) Comparisons of the frequencies of selected meta-clusters between HBV+and HBV- samples in INT (B) and TB (C) tissues. (D) The heatmap of the Spearmancorrelation coefficients between HBV clinical features and immune features inTB tissues, colored by correlation coefficients and for pairs with p-value morethan 0.1 were set to zero. E, The correlation plots between selected HBVclinical features and immune features as in (D). Two-way ANOVA test was used in(A), with *p < 0.05, **p < 0.01, and ***p < 0.001.

Published
2023
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35. Additional file 8 of Single-cell analysis reveals HBV-specific PD-1+CD8+ TRM cells in tumor borders are associated with HBV-related hepatic damage and fibrosis in HCC patients

Author

Liu, Lulu, Liu, Junwei, Li, Pan, Luo, Jijun, Qin, Rui, Peng, Qiao, Li, Bin, Wei, Xuyong, Wang, Tian, Shi, Hongyu, Wang, Ming-Da, Li, Chao, Fang, Weijia, Chen, Wei, Xu, Xiao, Yang, Tian, Yin, Weiwei, and Zeng, Xun

Abstract

Additional file 8: FigureS1.CyTOF data analyses of immune cells from HCC and HH tissues.(A) Thegating strategy of CyTOF data for live and singleton immune cells. (B) The tSNEplots of selected markers as in (Figure 1B). (C) The heatmap of 100 SOMsubclusters, major immune cell subtypes, and cluster frequencies were labeledon the top.

Published
2023
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36. Additional file 9 of Single-cell analysis reveals HBV-specific PD-1+CD8+ TRM cells in tumor borders are associated with HBV-related hepatic damage and fibrosis in HCC patients

Author

Liu, Lulu, Liu, Junwei, Li, Pan, Luo, Jijun, Qin, Rui, Peng, Qiao, Li, Bin, Wei, Xuyong, Wang, Tian, Shi, Hongyu, Wang, Ming-Da, Li, Chao, Fang, Weijia, Chen, Wei, Xu, Xiao, Yang, Tian, Yin, Weiwei, and Zeng, Xun

Abstract

Additional file 9: FigureS2. The clinical-related immunealterations in TB tissues. (A) Comparisons of the frequencies of selectedmeta-clusters between INT and TB tissues. (B) The heatmap of the comparisons ofmeta-cluster frequencies across patients grouped by defined clinical featuresin TB tissues, colored by the signed -log10(p-value). (C)Comparisons of the meta-cluster frequencies in TB tissues between early-stageand advanced-stage patients classified as in (B). Unpaired student’s t-test wasused in (A-C), with *p < 0.05, **p < 0.01, and ***p < 0.001.

Published
2023
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43. Development of a predictive model for identifying previously undetected vertical root fractures.

Author

Cao, Dantong, Zhang, Peng, Gao, Antian, Gulibire, Aihemaiti, Xie, Xin, Liang, Jiahao, Hu, Ziyang, Yin, Weiwei, and Lin, Zitong

Subjects
DENTAL pulp cavities, PREDICTION models, PERIAPICAL diseases, CONE beam computed tomography, TOOTH fractures
Abstract

This study aimed to develop a predictive model to screen for undetected vertical root fractures (VRFs) in root canal treated teeth. We included 95 root canal treated teeth with suspected VRFs; 77 for training and 18 for validation. Following clinical and cone‐beam CT parameters were recorded: sex, tooth type, coronal restoration, time interval from completion of endodontic treatment to definitive diagnosis (TI), type of bone loss (BL), apical extent of root filling (AR) and the ratio of root filling diameter to the actual diameter in the coronal (1/3TA) and middle (2/3TA) root thirds. A predictive model p = 1/(1 – e−x) was generated, where x = −7.433 + 1.977BL + 1.479 (2/3TA) + 1.102 AR; the sensitivity and specificity were 0.852 and 0.875 for training and 0.917 and 0.833 for validation. VRF teeth were more likely to have vertical bone loss and overfilled root canals. This model had a high diagnostic efficacy for VRFs. [ABSTRACT FROM AUTHOR]

Published
2023
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44. Effect of Pre-Heat-Treatment on the Oxidation Resistance of MCrAlY Coatings: A Review.

Author

Zhang, Bangyan, Zheng, Shijie, Dong, Jiajian, Yin, Weiwei, Wu, Hongbin, Tian, Lixi, and Liu, Guangming

Subjects
THERMAL barrier coatings, SURFACE coatings, DIFFUSION coatings, AIRPLANE motors, GAS turbines, CERAMIC coating
Abstract

High-performance gas turbines and aircraft engines necessitate MCrAlY (M = Ni, Co, or Ni/Co) coatings with exceptional oxidation resistance. Pre-heat-treatment can enhance the performance of MCrAlY bond coatings in the following ways: First, it reduces the porosity of the bond coating and promotes the diffusion of elements within it. Second, pre-heat-treatment allows for the formation of a continuous, dense, and moderately thick layer of pure Al2O3 scale, which helps to delay the formation of mixed oxides. Lastly, proper pre-heat-treatment can increase the grain size of the Al2O3 scale, leading to a lower growth rate of the oxide scale. Additionally, this article proposes new directions for developing more reasonable and effective pre-heat-treatment methods, laying the foundation for the creation of thermal barrier coatings (TBCs) with greater durability and higher performance. [ABSTRACT FROM AUTHOR]

Published
2023
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47. Modelling and Sampling Ramified Objects with Substructure-Based Method

Author

Yin, Weiwei, Jaeger, Marc, Teng, Jun, Hu, Bao-Gang, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Sunderam, Vaidy S., editor, van Albada, Geert Dick, editor, Sloot, Peter M. A., editor, and Dongarra, Jack J., editor

Published
2005
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