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776 results on '"MA Zhichao"'

1. Decreased BIRC5-206 promotes epithelial–mesenchymal transition in nasopharyngeal carcinoma through sponging miR-145-5p

Author

Xu Weihua, Hu Junjie, Ma Zhichao, Feng Wanyi, Gong Wei, Fu Shengmiao, and Chen Xinping

Subjects
nasopharyngeal carcinoma, birc5-206, epithelial–mesenchymal transition, mir-145-5p, cd40, Medicine
Abstract

Metastasis significantly contributes to the poor prognosis of advanced nasopharyngeal carcinoma (NPC). Our prior studies have demonstrated a decrease in BIRC5-206 expression in NPC, which promotes disease progression. However, the role of BIRC5-206 in the invasion and metastasis of NPC has not been fully elucidated. In this study, our objective was to explore the biological function and underlying mechanisms of BIRC5-206 in NPC. Additionally, we established an NPC mouse model of lung invasiveness using C666 cells to assess the impact of BIRC5-206 on NPC metastasis. Our results revealed that silencing BIRC5-206 inhibited apoptosis and enhanced the invasion of NPC cells, whereas its overexpression reversed these effects. Moreover, decreased BIRC5-206 expression significantly increased N-cadherin and Vimentin expression while reducing E-cadherin and occludin levels, both in vivo and in vitro. Additionally, silencing BIRC5-206 markedly augmented the formation of invasive foci in lung tissues. Rescue experiments further confirmed that decreased BIRC5-206 expression facilitates NPC metastasis via modulation of the miR-145-5p/CD40 signaling pathway. In summary, our study suggests that BIRC5-206 may serve as a potential prognostic biomarker and therapeutic target in the diagnosis and treatment of NPC.

Published
2024
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2. Probing-Enhanced Stochastic Programming

Author

Ma, Zhichao, Kim, Youngdae, Linderoth, Jeff, Luedtke, James R., and Matthews, Logan R.

Subjects
Mathematics - Optimization and Control
Abstract

We consider a two-stage stochastic decision problem where the decision-maker has the opportunity to obtain information about the distribution of the random variables $\xi$ that appear in the problem through a set of discrete actions that we refer to as \emph{probing}. Probing components of a random vector $\eta$ that is jointly-distributed with $\xi$ allows the decision-maker to learn about the conditional distribution of $\xi$ given the observed components of $\eta$. We propose a three-stage optimization model for this problem, where in the first stage some components of $\eta$ are chosen to be observed, and decisions in subsequent stages must be consistent with the obtained information. In the case that $\eta$ and $\xi$ have finite support, Goel and Grossmann gave a mixed-integer programming (MIP) formulation of this problem whose size is proportional to the square of cardinality of the sample space of the random variables. We propose to solve the model using bounds obtained from an information-based relaxation, combined with a branching scheme that enforces the consistency of decisions with observed information. The branch-and-bound approach can naturally be combined with sampling in order to estimate both lower and upper bounds on the optimal solution value and does not require $\eta$ or $\xi$ to have finite support. We conduct a computational study of our method on instances of a stochastic facility location and sizing problem with the option to probe customers to learn about their demands before building facilities. We find that on instances with finite support, our approach scales significantly better than the MIP formulation and also demonstrate that our method can compute statistical bounds on instances with continuous distributions that improve upon the perfect information bounds.

Published
2024

7. Routing Optimization of LEO Satellite Network Based on Genetic Ant Colony Algorithm

Author

Miao, Jingyu, Ma, Zhichao, Liu, Bin, Hu, Shaohua, Zhang, Limin, An, Guolong, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, 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, 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, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, 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, Tan, Kay Chen, Series Editor, Dong, Jian, editor, Zhang, Long, editor, and Cheng, Deqiang, editor

Published
2024
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8. An UAVs-Assisted Edge Computing Network with Multi-agent Reinforcement Learning

Author

Ma, Zhichao, Miao, Jingyu, Peng, Liang, Liu, Bin, Zhang, Limin, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, 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, 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, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, 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, Tan, Kay Chen, Series Editor, Dong, Jian, editor, Zhang, Long, editor, and Cheng, Deqiang, editor

Published
2024
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9. Denoised Temporal Relation Network for Temporal Action Segmentation

Author

Ma, Zhichao, Li, Kan, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Liu, Qingshan, editor, Wang, Hanzi, editor, Ma, Zhanyu, editor, Zheng, Weishi, editor, Zha, Hongbin, editor, Chen, Xilin, editor, Wang, Liang, editor, and Ji, Rongrong, editor

Published
2024
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17. Know Your Customer: Balancing Innovation and Regulation for Financial Inclusion

Author

Elliott, Karen, Coopamootoo, Kovila, Curran, Edward, Ezhilchelvan, Paul, Finnigan, Samantha, Horsfall, Dave, Ma, Zhichao, Ng, Magdalene, Spiliotopoulos, Tasos, Wu, Han, and van Moorsel, Aad

Subjects
Computer Science - Computers and Society, Computer Science - Cryptography and Security, Computer Science - Human-Computer Interaction
Abstract

Financial inclusion depends on providing adjusted services for citizens with disclosed vulnerabilities. At the same time, the financial industry needs to adhere to a strict regulatory framework, which is often in conflict with the desire for inclusive, adaptive, and privacy-preserving services. In this article we study how this tension impacts the deployment of privacy-sensitive technologies aimed at financial inclusion. We conduct a qualitative study with banking experts to understand their perspectives on service development for financial inclusion. We build and demonstrate a prototype solution based on open source decentralized identifiers and verifiable credentials software and report on feedback from the banking experts on this system. The technology is promising thanks to its selective disclosure of vulnerabilities to the full control of the individual. This supports GDPR requirements, but at the same time, there is a clear tension between introducing these technologies and fulfilling other regulatory requirements, particularly with respect to 'Know Your Customer.' We consider the policy implications stemming from these tensions and provide guidelines for the further design of related technologies., Comment: Published in the Journal Data & Policy

Published
2021
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