Complex protein interactions at synapses are essential for memory formation in our brains, but the mechanisms behind these processes remain poorly understood. Now, researchers from Japan have developed a computational model revealing new insights into the unique droplet-inside-droplet structures that memory-related proteins form at synapses. They discovered that the shape characteristics of a memory-related protein are crucial for the formation of these structures, which could shed light on the nature of various neurological disorders.

Multicolored optical switching is essential for potential advancements in telecommunication and optical computing. However, most materials typically exhibit only single-colored optical nonlinearity under intense laser illumination. To address this, researchers have demonstrated that exciting the multivalley semiconductor germanium with a single-color pulse laser enables ultrafast transparency switching across multiple wavelengths. This breakthrough could drive the development of ultrafast optical switches for future multiband communication and optical computing.

Kyoto, Japan -- There's a sensation that you experience -- near a plane taking off or a speaker bank at a concert -- from a sound so total that you feel it in your very being. When this happens, not only do your brain and ears perceive it, but your cells may also.

Technically speaking, sound is a simple phenomenon, consisting of compressional mechanical waves transmitted through substances, which exists universally in the non-equilibrated material world. Sound is also a vital source of environmental information for living beings, while its capacity to induce physiological responses at the cell level is only just beginning to be understood.

Following on previous work from 2018, a team of researchers at Kyoto University have been inspired by research in mechanobiology and body-conducted sound -- the sound environment in body tissues -- indicating that acoustic pressure transmitted by sound may be sufficient to induce cellular responses.

Development of ShotgunCSP: a crystal structure prediction algorithm combining machine learning and first-principles calculations.Achieved world-leading performance in crystal structure prediction benchmarks.A machine learning algorithm for predicting crystal symmetry dramatically improves the performance of structural predictions for complex and large-scale crystal systems.

Developed the machine learning algorithm E2T and its software for learning to learn for extrapolative prediction.Achieved outstanding extrapolative prediction performance in material property prediction tasks across diverse material systems.Demonstrated that models exposed to extensive extrapolative tasks can acquire the ability to rapidly adapt to new tasks.

An Osaka Metropolitan University researcher has developed an autonomous driving algorithm for agricultural robots used for greenhouse cultivation and other farm work.

Recent studies have revealed that electrons passing through chiral molecules exhibit significant spin polarization--a phenomenon known as Chirality-Induced Spin Selectivity (CISS). This effect stems from a nontrivial coupling between electron motion and spin within chiral structures, yet quantifying it remains challenging.

To address this, researchers at the Institute for Molecular Science (IMS) /SOKENDAI investigated an organic superconductor with chiral symmetry. They focused on nonreciprocity related to spin-orbit coupling and observed an exceptionally a large nonreciprocal transport in the superconducting state, far exceeding theoretical predictions. Remarkably, this was found in an organic material with inherently weak spin-orbit coupling, suggesting that chirality significantly enhances charge current-spin coupling with inducing mixed spin-triplet Cooper pairs.

Why does dementia affect more women than men? To help solve this mystery, researchers uncovered a new risk factor: age of menopause onset.