arXiv subjects

Caiyun Huang

Publications and source records attributed to Caiyun Huang.

3 recordsLinked to original sources

arXiv2026

Finite difference methods for three kinds of reaction-diffusion equations with free boundaries

This work considers to numerically solve three kinds of reaction-diffusion equations with free boundaries. First, the popular front-fixing method is used to transform the considered free boundary problems into fixed boundary problems. Then, by employing the finite difference method, numerical schemes with $\mathrm{M}$-matrices as their coefficient matrices are developed for these transformed fixed-boundary problems. Next, for the developed numerical schemes, we establish numerical theory involving positivity preservation, monotonicity preservation, and stability. It is noteworthy that, unlike some existing works that impose tight restrictions on the time step-size to discuss the numerical theory, the proposed numerical schemes require only a mild restriction. Finally, numerical examples are provided to test the developed numerical schemes and to confirm the theoretical results.

math.NA↗

arXiv2024

Artificial Intelligence for Central Dogma-Centric Multi-Omics: Challenges and Breakthroughs

With the rapid development of high-throughput sequencing platforms, an increasing number of omics technologies, such as genomics, metabolomics, and transcriptomics, are being applied to disease genetics research. However, biological data often exhibit high dimensionality and significant noise, making it challenging to effectively distinguish disease subtypes using a single-omics approach. To address these challenges and better capture the interactions among DNA, RNA, and proteins described by the central dogma, numerous studies have leveraged artificial intelligence to develop multi-omics models for disease research. These AI-driven models have improved the accuracy of disease prediction and facilitated the identification of genetic loci associated with diseases, thus advancing precision medicine. This paper reviews the mathematical definitions of multi-omics, strategies for integrating multi-omics data, applications of artificial intelligence and deep learning in multi-omics, the establishment of foundational models, and breakthroughs in multi-omics technologies, drawing insights from over 130 related articles. It aims to provide practical guidance for computational biologists to better understand and effectively utilize AI-based multi-omics machine learning algorithms in the context of central dogma.

q-bio.GN↗

arXiv2017

SFCSD: A Self-Feedback Correction System for DNS Based on Active and Passive Measurement

Domain Name System (DNS), one of the important infrastructure in the Internet, was vulnerable to attacks, for the DNS designer didn't take security issues into consideration at the beginning. The defects of DNS may lead to users' failure of access to the websites, what's worse, users might suffer a huge economic loss. In order to correct the DNS wrong resource records, we propose a Self-Feedback Correction System for DNS (SFCSD), which can find and track a large number of common websites' domain name and IP address correct correspondences to provide users with a real-time auto-updated correct (IP, Domain) binary tuple list. By matching specific strings with SSL, DNS and HTTP traffic passively, filtering with the CDN CNAME and non-homepage URL feature strings, verifying with webpage fingerprint algorithm, SFCSD obtains a large number of highly possibly correct IP addresses to make an active manual correction in the end. Its self-feedback mechanism can expand search range and improve performance. Experiments show that, SFCSD can achieve 94.3% precision and 93.07% recall rate with the optimal threshold selection in the test dataset. It has 8Gbps processing speed stand-alone to find almost 1000 possibly correct (IP, Domain) per day for the each specific string and to correct almost 200.

cs.NI↗