A5064554105- Privacy-Preserving Technologies in Data
- Cryptography and Data Security
- Graph theory and applications
- VLSI and Analog Circuit Testing
- Viral-associated cancers and disorders
- Cytomegalovirus and herpesvirus research
- Software Engineering Research
- Internet Traffic Analysis and Secure E-voting
- Stochastic Gradient Optimization Techniques
- Advanced Steganography and Watermarking Techniques
- Computational Drug Discovery Methods
- Digital and Cyber Forensics
- Biometric Identification and Security
- Physical Activity and Education Research
- HIV Research and Treatment
- Machine Learning and ELM
- Soil Moisture and Remote Sensing
- Advanced Technologies in Various Fields
- Software Reliability and Analysis Research
- Digital Media Forensic Detection
- Manufacturing Process and Optimization
- Access Control and Trust
- History and advancements in chemistry
- Generative Adversarial Networks and Image Synthesis
- Advanced Sensor and Control Systems
Guangzhou University
2021-2025
Wuhan University
2024-2025
Zhongnan Hospital of Wuhan University
2024-2025
Anhui University
2025
State Key Laboratory of Virology
2024
Chang'an University
2024
Institute of Art
2021
Henan University of Science and Technology
2021
Nuclear and Radiation Safety Center
2020
Savannah State University
2018-2019
Deubiquitinases (DUBs) remove ubiquitin from substrates and play crucial roles in diverse biological processes. However, our understanding of deubiquitination viral replication remains limited. Employing an oncogenic human herpesvirus Kaposi’s sarcoma-associated (KSHV) to probe the role protein deubiquitination, we found that Ovarian tumor family deubiquitinase 4 (OTUD4) promotes KSHV reactivation. OTUD4 interacts with transcription activator (K-RTA), a key factor controls reactivation,...
How to achieve distributed differential privacy (DP) without a trusted central party is of great interest in both theory and practice. Recently, the shuffle model has attracted much attention. Unlike local DP which users send randomized data directly collector/analyzer, an intermediate untrusted shuffler introduced randomly permute data, have already been by users, before they reach analyzer. The most appealing aspect that while shuffling does not explicitly add more noise it can make...
The development of effective and broad-spectrum antiviral therapies remains an unmet need. Current virus-targeted strategies are often limited by narrow spectrum activity the rapid emergence resistance. As a result, there is increasing interest in alternative approaches that target host cell factors critical for viral replication. One promising strategy targeting deubiquitinases (DUBs), enzymes regulate key proteins involved reactivation In this study, we explore potential DUB complex...
The shuffle model of differential privacy provides promising privacy-utility balances in decentralized, privacy-preserving data analysis. However, the current analyses amplification via shuffling lack both tightness and generality. To address this issue, we propose variation-ratio reduction as a comprehensive framework for single-message multi-message protocols. It leverages two new parameterizations: total variation bounds local messages probability ratio blanket messages, to determine...
Taking the steganalytic discriminators as adversaries, existing Generative Adversarial Networks (GAN)-based steganographic approaches learn implicit cost functions to measure embedding distortion for steganography. However, in these are trained by stego-samples with insufficient diversity, and their network structures offer very limited representational capacity. As a result, will not exhibit robustness various patterns, which causes learning suboptimal functions, thus compromising...
In many mobile applications, user-generated data are presented as set-valued data. To tackle potential privacy threats in analyzing these valuable data, local differential has been attracting substantial attention. However, existing approaches only provide sub-optimal utility and expensive computation communication for distribution estimation heavy-hitter identification. this paper, we propose a utility-optimal efficient publication method (i.e., <italic...
Numerical vector aggregation has numerous applications in privacy-sensitive scenarios, such as distributed gradient estimation federated learning, and statistical analysis on key-value data. Within the framework of local differential privacy, this work gives tight minimax error bounds O(d s/(n epsilon^2)), where d is dimension numerical s number non-zero entries. An attainable mechanism then designed to improve from existing approaches suffering rate O(d^2/(n epsilon^2)) or s^2/(n...
A numeric number which represents a complete shape of the chemical graph is said to be topological index. In this paper, we study 2D-lattice three-layered single- walled Titania nanotubes (SWTNT) and investigate their M-polynomial. Mainly, compute certain indices (TI’s) relates degree-based by help addition, give first as well second Zagreb polynomials aforesaid nanotubes. At end, draw comparison for better understanding computed results.
Locating and fixing software faults is a time-consuming resource-intensive task in development. Traditional fault localization methods, such as Spectrum-Based Fault Localization (SBFL), rely on statistical analysis of test coverage data but often suffer from lower accuracy. Learning-based techniques, while more effective, require extensive training can be computationally expensive. Recent advancements Large Language Models (LLMs) offer promising improvements by enhancing code comprehension...
Large Language Models (LLMs) show great promise in software engineering tasks like Fault Localization (FL) and Automatic Program Repair (APR). This study examines how input order context size affect LLM performance FL, a key step for many downstream tasks. We test different orders methods using Kendall Tau distances, including "perfect" (where ground truths come first) "worst" last). Our results strong bias order, with Top-1 accuracy falling from 57\% to 20\% when we reverse the code order....
Wang, X.; Wei, G.; S.; Yang, Y.; Du, F., and B., 2020. Impact of large cooling tower on atmospheric dispersion effluent from coastal nuclear power plant. In: Mi, C.; Zhao, L., Lam, S. (eds.), Global Topics New Trends in Coastal Research: Port, Ocean Engineering. Journal Research, Special Issue No. 103, pp. 474–478. Coconut Creek (Florida), ISSN 0749-0208.In order to improve the simulation quality plant, computational fluid dynamics (CFD) method was used simulate impact diffusion gaseous The...
With the rapid development of science and technology, more advanced technology can be applied in power plant, include centralized control system.The automation level plant continuously improved by application operation which played a very important role saving resources decreasing energy consumption.However, as operation, some problems were also increasingly appeared, order to ensure safe scientific measures need formulated.
Numerical vector aggregation plays a crucial role in privacy-sensitive applications, such as distributed gradient estimation federated learning and statistical analysis of key-value data. In the context local differential privacy, this study provides tight minimax error bound <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$O(\frac{ds}{n\epsilon ^{2}})$</tex-math></inline-formula> , where...
The reduced reciprocal Randic (RRR) index is a molecular structure descriptor (or more precisely, topological index), which useful for predicting the standard enthalpy of formation and normal boiling point isomeric octanes. In this paper, mathematical aspect RRR explored, or specifically, graph(s) having minimum is/are identified from collection all n–vertex connected bicyclic graphs n≥5. As consequence, best possible lower bound on index, obtained when