To simulate blood flow inside brain aneurysms, researchers from Japan developed a computational method that combines 4D flow MRI, computational fluid dynamics, and data assimilation, which provides greater accuracy and efficiency. By focusing only on the aneurysm region, this approach significantly reduces computational cost while improving flow estimation. When validated on patient data, it outperforms conventional models—offering a practical tool for patient-specific risk assessment and treatment strategies.

Researchers from the Faculty of Physics at the University of Warsaw and the University of British Columbia have described how a so-called lone spinon - an exotic quantum excitation that is a single unpaired spin - can arise in magnetic models. The discovery deepens our understanding of the nature of magnetism and could have implications for the development of future technologies such as quantum computers and new magnetic materials. The findings were published in the renowned journal “Physical Review Letters”.

Forest fires cause irreversible ecological and economic losses worldwide, often exacerbated by delayed or inefficient rescue efforts. A new study presents a groundbreaking data-driven framework to revolutionize aviation emergency networks. By integrating fire probability predictions with multi-objective optimization, the research enables faster, cost-effective rescue planning tailored to real-world fire risks. Tested in China’s Hainan Province, the model reduces response times while balancing ecological and operational costs—offering a scalable solution for global forest protection.