A joint international research team has challenged the traditional 'pollution haven' hypothesis—which suggests that companies relocate production to countries with lax environmental regulations—by proposing a new strategy that companies should seek a 'green haven' instead. This finding is attracting attention.

As recent Artificial Intelligence (AI) models’ capacity to understand and process long, complex sentences grows, the necessity for new semiconductor technologies that can simultaneously boost computation speed and memory efficiency is increasing. Amidst this, a joint research team featuring KAIST researchers and international collaborators has successfully developed a core AI semiconductor 'brain' technology based on a hybrid Transformer and Mamba structure, which was implemented for the first time in the world in a form capable of direct computation inside the memory, resulting in a four-fold increase in the inference speed of Large Language Models (LLMs) and a 2.2-fold reduction in power consumption.

A research team, affiliated with South Korea's Ulsan National Institute of Science and Technology (UNIST) discovered a hidden "reset button" in rotations—showing that by simply doubling and rescaling the forces involved, any spin, from atomic nuclei to quantum bits, can be brought perfectly brought back to its original state.

Led by Professor Junya Wang at Huazhong University of Science and Technology, the team has pushed the envelope by introducing a method inspired by human visual “gaze” behavior. Instead of hardware upgrades, their solution dynamically adjusts the MEMS scanning trajectory so that, within a fixed sampling budget, more attention is directed toward regions of interest (ROIs).

Osaka Metropolitan University researchers developed yeast that efficiently adsorbs targeted rare earth elements.

University of Otago – Ōtākou Whakaihu Waka researchers have developed algorithms that improve the precision of location tracking in smartwatches, a world-first development.

Soybeans grown alongside maize often face shading stress that reduces yield, yet some cultivars can thrive under low light. Scientists have now uncovered a comprehensive genetic network that controls this shade tolerance, moving beyond the traditional single-gene perspective. By integrating forward genome-wide association and reverse transcriptomic analyses, researchers identified more than 200 causal genes and over 7,800 expressed genes involved in soybean’s shade response. These genes function in a coordinated sequence—from light signal detection to metabolic adaptation—forming a multilayered regulatory system. The findings open a new pathway toward breeding high-yield, shade-tolerant soybeans for intercropping systems worldwide.