Molecular Characterization and Pathogenicity Analysis of Porcine Rotavirus A.

Porcine rotavirus A (RVA) is one of the major etiological agents of diarrhea in piglets and constitutes a significant threat to the swine industry. A molecular epidemiological investigation was conducted on 2422 diarrhea samples from Chinese pig farms to enhance our understanding of the molecular epidemiology and evolutionary diversity of RVA. The findings revealed an average RVA positivity rate of 42% (943/2422), and the study included data from 26 provinces, primarily in the eastern, southern and southwestern regions.

Challenges and New Directions in Therapeutic Cancer Vaccine Development.

Tumor vaccine is a promising immunotherapy for solid tumors. Therapeutic tumor vaccines aim at inducing tumor regression, establishing durable antitumor memory, and avoiding non-specific or adverse reactions. However, tumor-induced immune suppression and immune resistance pose challenges to achieving this goal.

HKAN: A Hybrid Kolmogorov-Arnold Network for Robust Fabric Defect Segmentation.

Currently, fabric defect detection methods predominantly rely on CNN models. However, due to the inherent limitations of CNNs, such models struggle to capture long-distance dependencies in images and fail to accurately detect complex defect features. While Transformers excel at modeling long-range dependencies, their quadratic computational complexity poses significant challenges.

Empowering Privacy Through Peer-Supervised Self-Sovereign Identity: Integrating Zero-Knowledge Proofs, Blockchain Oversight, and Peer Review Mechanism.

Frequent user data breaches and misuse incidents highlight the flaws in current identity management systems. This study proposes a blockchain-based, peer-supervised self-sovereign identity (SSI) generation and privacy protection technology. Our approach creates unique digital identities on the blockchain, enabling secure cross-domain recognition and data sharing and satisfying the essential users' requirements for SSI.

Identification Method for Railway Rail Corrugation Utilizing CEEMDAN-PE-SPWVD.

Rail corrugation intensifies wheel-rail vibrations, often leading to damage in vehicle-track system components within affected sections. This paper proposes a novel method for identifying rail corrugation, which combines Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), permutation entropy (PE), and Smoothed Pseudo Wigner-Ville Distribution (SPWVD). Initially, vertical acceleration data from the axle box are decomposed using CEEMDAN to extract intrinsic mode functions (IMFs) with distinct frequencies.