Rubber additives and relevant oxidation products in groundwater in a central China region: Levels, influencing factors and exposure.

This study investigated the presence of rubber additives and relevant oxidation products (RAROPs) in groundwater in central China's aboveground river region. Seven RAROPs were detected, and their levels in shallow groundwater showed a mild decreasing trend from the area near the Yellow River (Avg: 8.49 ng L) to the area on the far bank of the Yellow River (Avg: 5.

ADSTGCN: A Dynamic Adaptive Deeper Spatio-Temporal Graph Convolutional Network for Multi-Step Traffic Forecasting.

Multi-step traffic forecasting has always been extremely challenging due to constantly changing traffic conditions. Advanced Graph Convolutional Networks (GCNs) are widely used to extract spatial information from traffic networks. Existing GCNs for traffic forecasting are usually shallow networks that only aggregate two- or three-order node neighbor information.

BHGAttN: A Feature-Enhanced Hierarchical Graph Attention Network for Sentiment Analysis.

Recently, with the rise of deep learning, text classification techniques have developed rapidly. However, the existing work usually takes the entire text as the modeling object and pays less attention to the hierarchical structure within the text, ignoring the internal connection between the upper and lower sentences. To address these issues, this paper proposes a Bert-based hierarchical graph attention network model (BHGAttN) based on a large-scale pretrained model and graph attention network to model the hierarchical relationship of texts.