Unraveling the regulatory network of miRNA expression in Potato Y virus-infected of using integrated small RNA and transcriptome sequencing.

Potato virus Y (PVY) disease is a global problem that causes significant damage to crop quality and yield. As traditional chemical control methods are ineffective against PVY, it is crucial to explore new control strategies. MicroRNAs (miRNAs) play a crucial role in plant and animal defense responses to biotic and abiotic stresses.

DCFF-MTAD: A Multivariate Time-Series Anomaly Detection Model Based on Dual-Channel Feature Fusion.

The detection of anomalies in multivariate time-series data is becoming increasingly important in the automated and continuous monitoring of complex systems and devices due to the rapid increase in data volume and dimension. To address this challenge, we present a multivariate time-series anomaly detection model based on a dual-channel feature extraction module. The module focuses on the spatial and time features of the multivariate data using spatial short-time Fourier transform (STFT) and a graph attention network, respectively.