Counteranions reshape molecular packing to tune magnetism
Peer-Reviewed Publication
Updates every hour. Last Updated: 20-Oct-2026 03:16 ET (20-Oct-2026 07:16 GMT/UTC)
To simulate event cameras, which can capture brightness changes at microsecond-scale speeds, conventional methods render numerous frames from 3D scenes, resulting in high computational costs. Researchers from Japan developed an efficient method using physically based path tracing to precisely determine event timings. The efficient implementation using GPUs reduces computation time to as little as one-third of a naïve implementation, enabling more efficient training-data generation for event camera applications, including healthcare monitoring, autonomous driving, and robotics.
Researchers from the Institute of Industrial Science at The University of Tokyo used advanced instruments to watch small crystals on a scale of about one millionth of a meter as they soaked up chloroform. Parts of these crystals were found to work together to change shape, and some crystals began to move. Understanding these effects could lead to the design of new high-tech devices, such as sensors for pollutants.
KANAZAWA, Japan — Spatial transcriptomics can reveal where thousands of genes are active across a tissue, creating molecular maps at single-cell resolution. But comparing two such maps is difficult: thin slices of tissue may be rotated, stretched, or otherwise distorted, so equivalent regions do not automatically line up.
Researchers at Kanazawa University and Sapienza University of Rome have developed a computational method that aligns these maps directly from the individual measurement locations and their gene-activity values. Called Domain Elastic Transform (DET), it smoothly reshapes one digital map to match another without first converting the measurements into a regular grid of pixels.
The research, led by Osamu Hirose of Kanazawa University in collaboration with Emanuele Rodolà of Sapienza University of Rome, was published online in IEEE Transactions on Pattern Analysis and Machine Intelligence on September 15, 2026.