A research paper by scientists at The Chinese University of Hong Kong presented a new robotic bimodal palpation technique utilizing circumferential and sliding B-scan modes along with Bayesian optimization for precise lesion center and boundary detection..

The research paper, published on Sept. 2, 2025 in the journal Cyborg and Bionic Systems.

Synchronization abounds in nature and now researchers at UC San Diego have unlocked the mathematics that govern oscillators operating at similar frequencies in the intestine that create a staircase effect. 

A research paper by scientists at Nanyang Technological University presents wearable devices with headgear and abdominal buckle that address these challenges using hooking mechanisms, multimaterial 3-dimensional printing, and selective electroless plating.

The new research paper, published on Sep. 22, 2025 in the journal Cyborg and Bionic Systems, reported wearable devices, such as headgear and abdominal buckles with surface stimulators, designed for cyborg insect preparation and navigation.

A research team proposes a three-dimensional quantum anomalous Hall effect (3D QAHE) in Weyl semimetals (WSMs) by introducing Rashba spin-orbit coupling. This new state supports chiral surface and hinge states along different spatial directions, with Hall resistance switching between 0, h/e², and ±h/e², offering potential for energy-efficient devices and in-memory computing.

Researchers from SANKEN at The University of Osaka have successfully developed a groundbreaking “self-evolving” edge AI technology that enables real-time learning and forecasting capabilities directly within compact devices. This innovation, termed MicroAdapt, achieves unprecedented speed and accuracy. It processes data up to 100,000 times faster and achieves up to 60% higher accuracy compared to conventional state-of-the-art deep learning methods. This achievement represents a major advance toward next-generation real-time AI applications across manufacturing, automotive IoT, and medical wearables, addressing critical limitations of existing cloud-dependent AI.