A research paper by scientists at Capital Medical University proposed a diffusion tensor imaging (DTI)-based DenseNet to identify SVCI from subcortical ischemic vascular disease (SIVD) and to profile multidomain cognitive risks.

The research paper, published on May 13, 2026 in the journal Cyborg and Bionic Systems.

A research paper by scientists at Wuhan University of Science and Technology presented a prosthetic control framework developed through human skill transfer..

The research paper, published on May 13, 2026 in the journal Cyborg and Bionic Systems.

Rhodoliths may look like small rocks on the seafloor, but they're actually living algae that create habitats for marine life and contribute to long-term carbon storage.  A new study found that the deeper ‘low-light’ waters off Japan's Tanegashima Island harbor a surprisingly distinct and diverse community of these ‘living pink rocks,’ including four species completely new to science. Researchers identified at least 12 species in a small patch of seafloor 35–38 meters deep, but only three were also found in nearby shallow waters, suggesting the deeper habitat is not simply a continuation of the one near the surface.

Xiaowei Yue and colleagues propose a physical-mechanism-aided, transformer-based model capable of producing reliable predictions of wind shear. Wind shear, a sudden change in wind speed or direction, is a major cause of aviation incidents; it was responsible for 18% of aviation accidents in 2022. Predicting wind shear events is a priority for aviation safety, as it would allow pilots to avoid areas where wind shear is likely. 

Artificial intelligence increasingly helps providers achieve more robustness for their grids, provide better forecasts of electricity prices, and make energy use more efficient. In critical infrastructures, such as the energy system, AI should not be a black box – its decisions need to be understandable at any time. Researchers at the Karlsruhe Institute of Technology (KIT) have developed a new method for a more transparent analysis of AI-based predictions for energy systems. The results of their study have been published in Nature Communications.  (DOI: 10.1038/s41467-026-73243-5)