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Your search keyword '"Li, Chentao"' showing total 14 results
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14 results on '"Li, Chentao"'

10. Identifying Key Barriers to Green Transition Development in China's Express Industry Based on the Fuzzy DEMATEL Method.

Author

Xu, Xuan, Huang, Yifan, Hu, Bo, Li, Chentao, and Gong, Kenan

Abstract

The "green transformation of the express" delivery industry in this study primarily refers to the adoption of green energy and environmentally friendly technologies in express delivery packaging, transportation, and recycling systems. This transformation can significantly enhance energy efficiency and reduce emissions in the express system, promoting the sustainable development of the entire industry. However, the progress of green transformation in China's express delivery industry has been impeded by various barriers. To address this, we propose a barrier analysis framework based on the Fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL) methodology to explore key obstacles to green transformation in the express industry. Our research aims to answer three main questions: (1) What are the key barriers to green transformation in China's express delivery industry? (2) How do these barriers interact and influence each other? (3) What strategic measures can be implemented to overcome these barriers? We first compile a list of barriers, innovatively proposing two new ones: "inadequate green standards in the express industry" and "suboptimal green packaging technology". Considering the ambiguity in expert input and the complex interactions among barriers, we employ fuzzy DEMATEL within an Interval Type 2 Fuzzy Sets (IT2FSs) environment to investigate the significance and causality of these barriers. This approach distinguishes our study from previous research by providing a more nuanced understanding of barrier interactions in the specific context of China's express delivery industry. Based on our analysis, we identify eight critical barriers and propose corresponding strategic measures. [ABSTRACT FROM AUTHOR]

Published
2024
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13. LA-ViT: A Network With Transformers Constrained by Learned-Parameter-Free Attention for Interpretable Grading in a New Laryngeal Histopathology Image Dataset

Author

Huang, Pan, Xiao, Hualiang, He, Peng, Li, Chentao, Guo, Xiaodong, Tian, Sukun, Feng, Peng, Chen, Hu, Sun, Yuchun, Mercaldo, Francesco, Santone, Antonella, and Qin, Jing

Abstract

Grading laryngeal squamous cell carcinoma (LSCC) based on histopathological images is a clinically significant yet challenging task. However, more low-effect background semantic information appeared in the feature maps, feature channels, and class activation maps, which caused a serious impact on the accuracy and interpretability of LSCC grading. While the traditional transformer block makes extensive use of parameter attention, the model overlearns the low-effect background semantic information, resulting in ineffectively reducing the proportion of background semantics. Therefore, we propose an end-to-end network with transformers constrained by learned-parameter-free attention (LA-ViT), which improve the ability to learn high-effect target semantic information and reduce the proportion of background semantics. Firstly, according to generalized linear model and probabilistic, we demonstrate that learned-parameter-free attention (LA) has a stronger ability to learn highly effective target semantic information than parameter attention. Secondly, the first-type LA transformer block of LA-ViT utilizes the feature map position subspace to realize the query. Then, it uses the feature channel subspace to realize the key, and adopts the average convergence to obtain a value. And those construct the LA mechanism. Thus, it reduces the proportion of background semantics in the feature maps and feature channels. Thirdly, the second-type LA transformer block of LA-ViT uses the model probability matrix information and decision level weight information to realize key and query, respectively. And those realize the LA mechanism. So, it reduces the proportion of background semantics in class activation maps. Finally, we build a new complex semantic LSCC pathology image dataset to address the problem, which is less research on LSCC grading models because of lacking clinically meaningful datasets. After extensive experiments, the whole metrics of LA-ViT outperform those of other state-of-the-art methods, and the visualization maps match better with the regions of interest in the pathologists' decision-making. Moreover, the experimental results conducted on a public LSCC pathology image dataset show that LA-ViT has superior generalization performance to that of other state-of-the-art methods.

Published
2024
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14. Synthetic Cells and Molecules in Cellular Immunotherapy.

Author

Lin H, Li C, Zhang W, Wu B, Wang Y, Wang S, Wang D, Li X, and Huang H

Subjects
Humans, Neoplasms therapy, Neoplasms immunology, Animals, Artificial Cells immunology, Receptors, Chimeric Antigen immunology, T-Lymphocytes immunology, Immunotherapy, Adoptive methods, Immunotherapy methods
Abstract

Cellular immunotherapy has emerged as an exciting strategy for cancer treatment, as it aims to enhance the body's immune response to tumor cells by engineering immune cells and designing synthetic molecules from scratch. Because of the cytotoxic nature, abundance in peripheral blood, and maturation of genetic engineering techniques, T cells have become the most commonly engineered immune cells to date. Represented by chimeric antigen receptor (CAR)-T therapy, T cell-based immunotherapy has revolutionized the clinical treatment of hematological malignancies. However, serious side effects and limited efficacy in solid tumors have hindered the clinical application of cellular immunotherapy. To address these limitations, various innovative strategies regarding synthetic cells and molecules have been developed. On one hand, some cytotoxic immune cells other than T cells have been engineered to explore the potential of targeted elimination of tumor cells, while some adjuvant cells have also been engineered to enhance the therapeutic effect. On the other hand, diverse synthetic cellular components and molecules are added to engineered immune cells to regulate their functions, promoting cytotoxic activity and restricting side effects. Moreover, novel bioactive materials such as hydrogels facilitating the delivery of therapeutic immune cells have also been applied to improve the efficacy of cellular immunotherapy. This review summarizes the innovative strategies of synthetic cells and molecules currently available in cellular immunotherapies, discusses the limitations, and provides insights into the next generation of cellular immunotherapies., Competing Interests: Competing Interests: The authors have declared that no competing interest exists., (© The author(s).)

Published
2024
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