A joint research team from Saitama University and the Institute of Microbial Chemistry (BIKAKEN) has developed a polymerizable monomer from 4-trehalosamine, a biologically stable and chemically modifiable analog of trehalose, and used it to prepare water-soluble polyacrylamides with tunable compositions. By taking advantage of the uniquely reactive amino group of 4-trehalosamine, the approach provides a new route for incorporating this sugar into synthetic polymers at controlled levels. Unlike conventional carbohydrate-containing polymers that often require complex protection and deprotection chemistry, the new approach exploits the naturally occurring amino group of 4-trehalosamine to introduce polymerizable functionality selectively and efficiently. The resulting platform may facilitate the design of carbohydrate-containing polymers for biotechnology and advanced functional materials.

A research team from the Vision and Action Laboratory, Visual Perception and Cognition Laboratory, and Cognitive Neurotechnology Unit in the Department of Computer Science and Engineering at Toyohashi University of Technology, led by Associate Professor Hideki Tamura, has demonstrated that, even when an object moves at the same physical speed, its approach is perceived as faster when it comes from behind than when it approaches from the front. Across five experiments using both a real autonomous mobile robot (AMR) and immersive virtual reality (VR), 92% of the participants consistently exhibited this perceptual bias, perceiving approaches from behind as faster than frontal approaches. The results further suggest that this phenomenon is unlikely to be explained by factors such as object appearance or motor noise, but is instead associated with vision-dependent factors that arise when observers turn around to view an approaching object from behind. Furthermore, by incorporating the experimentally observed perceptual bias into a robot navigation model, the researchers simulated a robot overtaking a pedestrian from behind. The simulation suggested that accounting for human perceptual characteristics results in avoidance trajectories that begin earlier while maintaining a greater distance from pedestrians than conventional navigation models.

The study was published in IEEE Robotics and Automation Letters on September 10, 2026.

https://doi.org/10.1109/LRA.2026.3732839

“My job is to collect and clean data,” says Associate Professor Tazro Ohta of Chiba University’s Institute for Advanced Academic Research, Graduate School of Medicine, and Data Science Core (DSC). As human genetic information has become easier to obtain as digitized data, analyzing it now requires advanced expertise and high-performance computing. By making his research products available as freely accessible open-source software and databases, Dr. Ohta is contributing to the development of data science. “I believe that data science needs a place where people can interact,” he told us, speaking about the importance and excitement of making databases open to the public.

Novel framework enables fine control over the intensity and expressiveness of AI-generated human motion, as reported by researchers from Science Tokyo. The “Motion Style Slider” framework enables animators to control the style and adjust a virtual character’s motion, from subtle to overly exaggerated, based on only two motion samples. The proposed approach achieves consistent style control and smooth transitions without the need for extensive motion-capture datasets.

Researchers found that carefully balancing metallic cobalt and cobalt oxide enables highly selective electrocatalytic hydrogenation of nitrogen-containing compounds. The catalyst converted pyridine to piperidine with a more than 99% yield, while intermittent electrolysis maintained its optimal chemical state, offering a potential route toward sustainable chemical manufacturing without use of scarce precious metals.

Researchers at Tohoku University and collaborators have demonstrated key technologies for controlling and measuring electrons in zinc oxide quantum dots, an important step toward developing spin-based quantum devices. Their results provide a new platform for exploring how electron spins behave in this promising material.

Researchers at the University of Osaka found that simultaneous stimulation of the primary somatosensory cortex and insular cortex may produce richer artificial bodily sensations than stimulating either region alone. In three patients, dual-site stimulation evoked sensations including gentle touch and combined numbness and warmth. These preliminary findings suggest that multisite stimulation may influence how sensory qualities are integrated, with potential applications in sensory neuroprosthetics and functional brain mapping in humans.

The valence-electron concentration has been conventionally used to identify and classify magnetic ground states in various intermetallic compounds. In quasicrystal approximants, the predictive power of valence-electron concentration is found to be limited across different alloy families and constituent elements. Now, researchers establish the lattice parameter as an experimentally accessible, unified structural descriptor for magnetic ground state selection in Tsai-type icosahedral compounds. This breakthrough will help identify novel quasicrystals and approximant crystals with emergent magnetic properties. 

A team of researchers led by the National Astronomical Observatory of Japan discovered unexpectedly intricate magnetic structures above quiet-Sun regions, by observing the Sun with the balloon-borne solar observatory Sunrise-III.

Correlation does not imply causation. Using AI to discover new materials is becoming more common, but data-driven approaches sometimes rely heavily on correlations and make testing AI-based predictions difficult. A new perspective paper published by Tohoku University researchers developed a framework for incorporating physics-based principles into AI to generate more interpretable, testable, and meaningful predictions.