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1,778 results on '"Mu, Yu"'

17. Comparison of the Three-Generation Numerical Models for Proton Exchange Membrane Fuel Cell Multi-physics Prediction

Author

Bai, Fan, He, Pu, Mu, Yu-Tong, Tao, Wen-Quan, 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, Tolio, Tullio A. M., Editorial Board Member, Trojanowska, Justyna, Editorial Board Member, Schmitt, Robert, Editorial Board Member, Xu, Jinyang, Editorial Board Member, Benim, Ali Cemal, editor, Bennacer, Rachid, editor, Mohamad, Abdulmajeed A., editor, Ocłoń, Paweł, editor, Suh, Sang-Ho, editor, and Taler, Jan, editor

Published
2024
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18. Tuning Electrode Reactivity through Organometallic Complexes

Author

Shen, Yi, Mu, Yu, Wang, Dunwei, Liu, Chong, and Diaconescu, Paula L

Subjects
Affordable and Clean Energy, functionalized electrode, surface functionalization, organometallic complex, electrode surface, switchable catalysis, electrocatalysis, electricfield-assisted catalysis, integrated catalysis, electric field-assisted catalysis, Chemical Sciences, Engineering, Nanoscience & Nanotechnology
Abstract

The use of molecularly modified electrodes in catalysis heralds a new paradigm in designing chemical transformations by allowing control of catalytic activity. Herein, we provide an overview of reported methods to develop electrodes functionalized with organometallic complexes and a summary of commonly used techniques for characterizing the electrode surface after immobilization. In addition, we highlight the implications of surface functionalization in catalysis to emphasize the key aspects that should be considered during the development and optimization of functionalized electrodes. Particularly, surface-molecule electronic coupling and electrostatic interactions within a hybrid system are discussed to present effective handles in tuning catalytic activity. We envision that this emerging type of hybrid catalytic system has the potential to combine the advantages of homogeneous catalysis and heterogeneous supports and could be applied to an expanded range of transformations beyond energy conversion.

Published
2023

21. Polarization effects on fluorescence emission of zebrafish neurons using light-sheet microscopy

Author

Ye, Hong, Xu, Xin, Wang, Jixiang, Wang, Jing, He, Yi, Mu, Yu, and Shi, Guohua

Subjects
Physics - Biological Physics, Quantitative Biology - Neurons and Cognition
Abstract

Light-sheet fluorescence microscopy (LSFM) makes use of a thin plane of light to optically section and image transparent tissues or organisms {\it{in vivo}}, which has the advantages of fast imaging speed and low phototoxicity. In this paper, we have employed light-sheet microscopy to investigate the polarization effects on fluorescence emission of zebrafish neurons via modifying the electric oscillation orientation of the excitation light. The intensity of the fluorescence emission from the excited zebrafish larvae follows a cosine square function with respect to the polarization state of the excitation light and reveals a 40$\%$ higher fluorescence emission when the polarization orientation is orthogonal to the illumination and detection axes. Through registration and subtraction of fluorescence images under different polarization states, we have demonstrated that most of the enhanced fluorescence signals are from the nerve cells rather than the extracellular substance. This provides us a way to distinguish the cell boundaries and observe the organism structures with improved contrast and resolution.

Published
2022

22. Spatiotemporal control for integrated catalysis

Author

Deng, Shijie, Jolly, Brandon J, Wilkes, James R, Mu, Yu, Byers, Jeffery A, Do, Loi H, Miller, Alexander JM, Wang, Dunwei, Liu, Chong, and Diaconescu, Paula L

Subjects
Engineering, Organic Chemistry, Chemical Sciences, Affordable and Clean Energy
Published
2023

39. Morphological changes and hub genes screening in rats with anorectal malformations during hindgut development

Author

Si Ying Li, Chen Yi Wang, Mu Yu Li, Xiao Bing Tang, Zheng Wei Yuan, and Yu Zuo Bai

Subjects
Anorectal malformations, Protein-protein interaction, Gene set enrichment analysis, Differentially expressed genes, High-throughput sequencing, Pediatrics, RJ1-570, Surgery, RD1-811
Abstract

Background: Anorectal malformations (ARMs) are among the most common congenital digestive tract malformations worldwide. Although there have been extensive efforts for elucidating their pathogenesis, the specific molecular mechanisms underlying ARMs remain unclear. Methods: We generated ARM Wistar rat models using ethylenethiourea. Nine pregnant rats were allocated to the ARM and control groups, respectively. Hindgut tissue was isolated from embryos collected on gestational days 14, 15, and 16, representing the key timepoints of anorectal development. High-throughput sequencing was used to identify differentially expressed genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed on the obtained genes. Module analysis was performed via Search Tool for the Retrieval of Interacting Genes (STRING), and a protein-protein interaction (PPI) network was constructed using Cytoscape software. Gene Set Enrichment Analysis (GSEA) was conducted to verify the enrichment of development/apoptosis/epithelium/morphogenesis/Wnt pathway-related core gene sets and identify ARM hub genes. Reverse transcription-quantitative polymerase chain reaction assay was employed to verify mRNA levels of hub genes. Results: 313 GSEA core genes form ten core gene sets were selected. Based on the 281 differentially expressed circRNAs (|Fc| > 2, FDR < 0.05), 42 PPI core genes were obtained. According to the integration of GSEA analysis and PPI network, three hub genes (Cul1, Gli3, and Osr2) highly associated with ETU-induced ARMs were identified. The qRT-PCR validation data were consistent with the sequencing results. Conclusions: These results provide a theoretical basis for the further identification of potential diagnostic and therapeutic targets in ARMs.

Published
2024
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44. Robust Estimation Method against Poisoning Attacks for Key-Value Data with Local Differential Privacy

Author

Hikaru Horigome, Hiroaki Kikuchi, Masahiro Fujita, and Chia-Mu Yu

Subjects
LDP, key-value data, expectation maximization, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999
Abstract

Local differential privacy (LDP) protects user information from potential threats by randomizing data on individual devices before transmission to untrusted collectors. This method enables collectors to derive user statistics by analyzing randomized data, thereby presenting a promising avenue for privacy-preserving data collection. In the context of key–value data, in which discrete and continuous values coexist, PrivKV has been introduced as an LDP protocol to ensure secure collection. However, this framework is susceptible to poisoning attacks. To address this vulnerability, we propose an expectation maximization (EM)-based algorithm combined with a cryptographic protocol to facilitate secure random sampling. Our LDP protocol, known as emPrivKV, exhibits two key advantages: it improves the accuracy of statistical information estimation from randomized data, and enhances resilience against the manipulation of statistics, that is, poisoning attacks. These attacks involve malicious users manipulating the analysis results without detection. This study presents the empirical results of applying the emPrivKV protocol to both synthetic and open datasets, highlighting a notable improvement in the precision of statistical value estimation and robustness against poisoning attacks. As a result, emPrivKV improved the frequency and the mean gains by 17.1% and 25.9%, respectively, compared to PrivKV, with the number of fake users being 0.1 of the genuine users. Our findings contribute to the ongoing discourse on refining LDP protocols for key–value data in scenarios involving privacy-sensitive information.

Published
2024
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