A research paper by scientists from Beijing University of Posts and Telecommunications designed a multimodal controller termed the tactile, kinesthetic, and electromyography (EMG) bionic gripping controller (TKE-BGC).

The new research paper, published on May. 13 in the journal Cyborg and Bionic Systems, developed a bioinspired control framework that dramatically improves prosthetic hand stability during such dynamic tasks.

A research paper by scientists from Capital Medical University proposed a diffusion tensor imaging (DTI)-based DenseNet to identify SVCI from subcortical ischemic vascular disease (SIVD) and to profile multidomain cognitive risks.

The new research paper, published on May. 13 in the journal Cyborg and Bionic Systems, developed a deep‑learning framework that uses routine diffusion tensor imaging to both identify SVCI and profile an individual’s domain‑specific cognitive weaknesses.

Semiconductors are a crucial component of devices such as smartphones, computers, LEDs, and solar cells. New generation solar cells which use perovskite and organic semiconductors  are gaining attention for applications in flexible electronics, light-emitting devices, and high-efficiency solar cells. This technology becomes crucial for helping reduce reliance on fossil fuels.

A major challenge in bettering existing semiconductor technology is the process of electronic doping. Conventional doping techniques often rely on metal salts, chemical additives, and slow processing methods that can leave residues, reduce long-term stability, and depend heavily on trial-and-error optimization.

Pabitra Nayak and colleagues have developed a new approach called in situ regenerative adduct-assisted (IRAA) doping, demonstrated in halide perovskite solar cells, which makes the process of doping cleaner, faster, and more efficient.

Flaky tests—automated checks that produce inconsistent results—are a persistent issue in software development, wasting time and computational resources. Researchers from Kyushu University analyzed 649 projects in the OpenStack ecosystem and found that over half were affected by flakiness that often spreads across projects. They identified cross-project flakiness caused by an unstable test affecting multiple projects and inconsistent flakiness as key phenomena.