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1,372 results on '"Chen, Xiaoyong"'

1. Cathepsin B Nuclear Flux in a DNA-Guided Antinuclear Missile Cancer Therapy.

Author

Cao, Fei, Tang, Caroline, Chen, Xiaoyong, Tu, Zewei, Jin, Ying, Turk, Olivia, Nishimura, Robert, Ebens, Allen, Dubljevic, Valentina, Campbell, James, Zhou, Jiangbing, and Hansen, James

Abstract

Some antinuclear antibodies (ANAs) bind extracellular nucleic acids released into tumor environments and are pulled into the nuclei of live cancer cells through nucleoside salvage pathways, independent of tumor-specific surface antigens. Here we show that ANA nuclear penetration induces nuclear flux by the lysosomal protease cathepsin B and leverage this mechanism to design an antinuclear antibody-drug conjugate (ANADC) with cathepsin B-labile drug linker. The ANADC targets nucleic acid exhaust from necrotic tumors and crosses membrane barriers through nucleoside salvage as a DNA-seeking and tumor agnostic antinuclear missile cancer therapy.

Published
2024

2. Benchmarking the Robustness of Temporal Action Detection Models Against Temporal Corruptions

Author

Zeng, Runhao, Chen, Xiaoyong, Liang, Jiaming, Wu, Huisi, Cao, Guangzhong, and Guo, Yong

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Temporal action detection (TAD) aims to locate action positions and recognize action categories in long-term untrimmed videos. Although many methods have achieved promising results, their robustness has not been thoroughly studied. In practice, we observe that temporal information in videos can be occasionally corrupted, such as missing or blurred frames. Interestingly, existing methods often incur a significant performance drop even if only one frame is affected. To formally evaluate the robustness, we establish two temporal corruption robustness benchmarks, namely THUMOS14-C and ActivityNet-v1.3-C. In this paper, we extensively analyze the robustness of seven leading TAD methods and obtain some interesting findings: 1) Existing methods are particularly vulnerable to temporal corruptions, and end-to-end methods are often more susceptible than those with a pre-trained feature extractor; 2) Vulnerability mainly comes from localization error rather than classification error; 3) When corruptions occur in the middle of an action instance, TAD models tend to yield the largest performance drop. Besides building a benchmark, we further develop a simple but effective robust training method to defend against temporal corruptions, through the FrameDrop augmentation and Temporal-Robust Consistency loss. Remarkably, our approach not only improves robustness but also yields promising improvements on clean data. We believe that this study will serve as a benchmark for future research in robust video analysis. Source code and models are available at https://github.com/Alvin-Zeng/temporal-robustness-benchmark., Comment: Accepted by CVPR2024

Published
2024

22. Research on Leakage Recognition Method of Photovoltaic Connected to Distribution Network Based on NCA and SSA-KELM

Author

Wang, Zihu, Liu, Zhengsheng, Liu, Yuanhong, Qu, Hongqing, Han, Xiaohui, Chen, Xiaoyong, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Li, Jian, editor, Xie, Kaigui, editor, Hu, Jianlin, editor, and Yang, Qingxin, editor

Published
2023
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