New system eliminates throttle valve losses, extending discharge duration and enhancing grid-scale renewable energy storage capabilities

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective at capturing relationships between nodes and edges in data, but often overlook higher-order, complex connections. To address this challenge, a research team at The Hong Kong Polytechnic University (PolyU) has developed a new heterogeneous graph attention network, revolutionising the modelling of complex relationships in graph-structured data. This innovation is poised to break through AI application limitations in fields such as neuroscience, logistics, computer vision and biology.

A research paper by scientists at University of Electro-Communications explored the long-term clinical outcomes of multi-degree-of-freedom myoelectric prosthetic hands.

The research paper, published on Mar 18, 2025 in the journal Cyborg and Bionic Systems.

Whatever challenges life throws, mothers often know best as they guide offspring through the risky stages of early development.  

Scientists have created a new type of material that could enable common electronic devices to work faster and use less energy, a study suggests.

A University of Missouri researcher has unveiled a safer, smarter way to fight drug-resistant infections.

This review provides a comprehensive overview of the latest advances in droplet microfluidics, with a particular focus on its applications in drug discovery, disease diagnosis, and personalized medicine. The article systematically discusses droplet generation, manipulation, and detection techniques, comparing the advantages and limitations of each method.