A new LMU study shows: Three-quarters of the estimated global potential for new forests to capture CO₂ is threatened by significant social and institutional challenges.

Kyushu University researchers have developed an AI-based method to measure how closely corporate disclosures match the ESG issues that matter financially to each industry. Applied to Japan’s food and beverage sector, it showed that companies place greater emphasis on social-related topics, while environmental disclosure remains relatively limited. Priorities also shifted as reporting requirements changed. The study offers insights for investors, firms, and standard setters seeking to evaluate and design effective sustainability reporting regimes.

A new research study in the IEEE Journal of Biomedical and Health Informatics reveals how scientists at Klick Labs created visual maps of sound frequencies (spectrograms) to identify complex, new patterns associated with Type 2 diabetes, using only smartphone recordings of randomly selected short English sentences and participant sex as study criteria. 

In solids, different types of excitations can affect each other. Using a new experimental technique at the X-ray free-electron laser SwissFEL, a team at Paul Scherrer Institute PSI has now been able to uncover the interplay between electronic, magnetic, and lattice excitations. This understanding is important for learning how spin excitations can be controlled for future information technology. The results have been published in the journal Nature Communications. 

Accurate river water level estimation is crucial for flood prevention, disaster mitigation and water resource management, yet strong non-stationarity and nonlinearity in complex plain river-network regions pose significant challenges to conventional approaches.

Deoxyhypusine synthase (DHPS) is a human enzyme required for the replication of a broad range of viruses. Researchers at Korea University have developed an artificial intelligence (AI)-based pipeline for designing DHPS inhibitors. All three compounds predicted to be active showed inhibition in laboratory assays, with two demonstrating measurable potency. The findings demonstrate the feasibility of an AI-guided, host-directed approach to antiviral drug discovery.