Passenger flow anomaly detection in urban rail transit networks with graph convolution network-informer and Gaussian Bayes models.

Passenger flow anomaly detection in urban rail transit networks (URTNs) is critical in managing surging demand and informing effective operations planning and controls in the network. Existing studies have primarily focused on identifying the source of anomalies at a single station by analysing the time-series characteristics of passenger flow. However, they ignored the high-dimensional and complex spatial features of passenger flow and the dynamic behaviours of passengers in URTNs during anomaly detection. This article proposes a novel anomaly detection methodology based on a deep learning framework consisting of a graph convolution network (GCN)-informer model and a Gaussian naive Bayes model. The GCN-informer model is used to capture the spatial and temporal features of inbound and outbound passenger flows, and it is trained on normal datasets. The Gaussian naive Bayes model is used to construct a binary classifier for anomaly detection, and its parameters are estimated by feeding the normal and abnormal test data into the trained GCN-informer model. Experiments are conducted on a real-world URTN passenger flow dataset from Beijing. The results show that the proposed framework has superior performance compared to existing anomaly detection algorithms in detecting network-level passenger flow anomalies. This article is part of the theme issue 'Artificial intelligence in failure analysis of transportation infrastructure and materials'.

Clinical efficacy and safety of nicergoline combined with oxiracetam in the treatment of vascular cognitive impairment.

As a α1-adrenergic receptor antagonist, nicergoline can induce vasodilation and increase arterial blood flow. Its clinical application can effectively prevent and treat cognitive impairment and reduce cognitive decline and comprehensively improve patients' daily living ability and social function. The clinical efficacy of nicergoline combined with oxiracetam in the treatment of vascular cognitive impairment after stroke was analyzed. 120 patients with cognitive impairment after stroke were randomly divided into nicergoline group and Experience group. They were treated with nicergoline and nicergoline combined with oxiracetam respectively. Both groups were treated for one month. Montreal Cognitive Assessment Scale (MoCA) was used to evaluate the cognitive function of the two groups before and after treatment, and the clinical efficacy was compared. The results showed that the average score of MoCA in the combined group was (5.97±2.06), higher than that in the nicergoline group (3.53±1.44). The change of MoCA score was the most significant. There was significant difference between the nicergoline group and the combined group (t=4.21, P<0.01). The combined group had the highest effective rate and the total effective rate was 93.3%. Conclusion: Nicergoline and oxiracetam are effective drugs in the treatment of vascular cognitive impairment (VCI). The combined use of nicergoline and oxiracetam is better than that of nicergoline alone. The combined use of nicergoline and oxiracetam can significantly improve the severity of symptoms and quality of life in patients with vascular cognitive impairment after stroke. The clinical effect is definite.