Metro Passenger-Flow Representation via Dynamic Mode Decomposition and Its Application.

Passenger-flow anomaly detection and prediction are essential tasks for intelligent operation of the metro system. Accurate passenger-flow representation is the foundation of them. However, spatiotemporal dependencies, complex dynamic changes, and anomalies of passenger-flow data bring great challenges to data representation. Taking advantage of the time-varying characteristics of data, we propose a novel passenger-flow representation model based on low-rank dynamic mode decomposition (DMD), which also integrates the global low-rank nature and sparsity to explore the spatiotemporal consistency of data and depict abrupt data, respectively. The model can detect anomalies and predict short-term passenger flow conveniently and flexibly. For anomaly detection, we further introduce a strong temporal Toeplitz regularization to characterize the temporal periodic change of data, so as to more accurately detect anomalies. We conduct experiments with smart card transaction data from the Beijing metro system to assess the performance of the model in two use cases. In terms of anomaly detection, the experimental results demonstrate that our method can detect anomalies efficiently, especially for time sequence anomalies. As for short-term prediction, our model is superior to other methods in most cases.

Genome-wide identification of PYL gene family in wheat: Evolution, expression and 3D structure analysis.

Here, 38 wheat PYL genes (TaPYLs) belonging to 13 homoeologous groups were identified using the genome-search method, with 26 and 12 PYL genes identified in Triticum dicoccoides and Aegilops tauschii, respectively. Phylogenetic relationship, conserved domain and molecular evolution analysis revealed that PYL genes showed highly conservative between wheat and theprogenitors. Interaction network and miRNA target prediction found that TaPYLs could interact with the important components of ABA signaling pathway and Tae-miR966b-3p might be a hub regulator mediating wheat ABA signal network. Furthermore, the tissue-specific and stress-responsive TaPYLs were detected through RNA-seq analysis. Expressions of 10 TaPYLs were validated by QPCR analysis and the homoeologous genes showed significantly differential expression, suggesting subfunctionalization of them has occurred. Finally, 3D structures of the TaPYL proteins were predicted by homology modeling. This study lays the foundation for further functional study of PYL genes for development and stress tolerance improvement in wheat and beyond.