A multi-modal attention neural network for traffic flow prediction by capturing long-short term sequence correlation.

Accurate traffic flow prediction information can help traffic managers and drivers make more rational decisions and choices. To make an effective and accurate traffic flow prediction, we need to consider not only the spatio-temporal dependencies between data, but also the temporal correlation between data. However, most existing methods only consider temporal continuity and ignore temporal correlation. In this paper, we propose a multi-modal attention neural network for traffic flow prediction by capturing long-short term sequence correlation (LSTSC). In the model, we employed attention mechanisms to capture the spatio-temporal correlations of the sequences, and the model based on multiple decision forms demonstrated higher accuracy and reliability. The superiority of the model is demonstrated on two datasets, PeMS08 and PeMSD7(M), particularly for long-term predictions.

MD-GCN: A Multi-Scale Temporal Dual Graph Convolution Network for Traffic Flow Prediction.

The spatial-temporal prediction of traffic flow is very important for traffic management and planning. The most difficult challenges of traffic flow prediction are the temporal feature extraction and the spatial correlation extraction of nodes. Due to the complex spatial correlation between different roads and the dynamic trend of time patterns, traditional forecasting methods still have limitations in obtaining spatial-temporal correlation, which makes it difficult to extract more valid information. In order to improve the accuracy of the forecasting, this paper proposes a multi-scale temporal dual graph convolution network for traffic flow prediction (MD-GCN). Firstly, we propose a gated temporal convolution based on a channel attention and inception structure to extract multi-scale temporal dependence. Then, aiming at the complexity of the traffic spatial structure, we develop a dual graph convolution module including the graph sampling and aggregation submodule (GraphSAGE) and the mix-hop propagation graph convolution submodule (MGCN) to extract the local correlation and global correlation between neighbor nodes. Finally, extensive experiments are carried out on several public traffic datasets, and the experimental results show that our proposed algorithm outperforms the existing methods.

Pulse transit time reveals drug kinetics on vascular changes affected by propofol.

Pulse transit time (PTT) is the duration in which a pulse wave travels between two arterial sites within the same cardiac cycle. The aim of our study is to use PTT to examine propofol's effects on the vascular system. Methods. We collected data from 50 healthy women, between 28 and 51 years old, who underwent gynaecological surgery under general anaesthesia. The general anaesthesia was induced with propofol injection (2 mg/kg). PTT measurements were obtained from the R-wave of electrocardiogram and the pulse wave of photoplethysmograph. Two PTT values were obtained; one before (the control) and the other after propofol injection. The results were analysed by Student's t-test. Results. After propofol injection, the PTT was prolonged. The change in the PTT value from that of baseline was significant statistically (P < 0.05, by Student's t-test). The PTT change over time correlated with the degree of vasodilatation over time. Monitoring of PTT not only revealed the magnitude of vascular changes but also demonstrated the onset of vascular dilation, its peak and duration. We conclude that PTT is a useful guide in monitoring the drug kinetics of propofol.

Management of catheter-induced pulmonary artery perforation during weaning from cardiopulmonary bypass--a case report.

We report a case of pulmonary artery perforation induced by Swan-Ganz catheter. Brisk massive airway hemorrhage occurred after withdrawl of the Swan-Ganz catheter post cardiopulmonary bypass. Early recognition, immediate re-establishment of cardiopulmonary bypass, lobectomy of the sanguineous lobe subsequent to rupture of the involved pulmonary artery, and thorough bronchial toilet were the major determinants contributing to successfully rescuing the patient's life. She was discharged uneventfully in spite of high mortality rate of the catheter-induced pulmonary artery perforation.

Left atrial infective endocarditis with giant vegetation without involvement of the mitral valve--a case report of transesophageal echocardiography in diagnosis.

Cardiac valves are the most commonly victimized sites of infective endocarditis. The vegetations migrating outside the valves are quite rare. Echocardiography is a sensitive method for detecting these lesions. We report a case of unusual echocardiographic presentation of infective endocarditis. Transesophageal echocardiography showed a giant tonguelike echogenic mass, which attached to the posterior wall of left atrium without involving the mitral valve. Also, we discuss the differential diagnosis of infective endocarditis and myxoma, as well as the considerations of anesthetic management of intracardiac mass.