Scientists from the University of Groningen in the Netherlands have developed a soft polymer hydrogel that can conduct electricity as well as metal can. This finding has the potential for a large numbers of applications, for example in biocompatible sensors and in wound healing.

Researchers have developed a new algorithm that combines two processes for personalizing robotic prosthetic devices to both optimize the movement of the prosthetic limb and – for the first time – also help a human user’s body engage in a more natural walking pattern. The new approach can be used to help restore and maintain various aspects of user movement, with the goal of addressing health challenges associated with an amputation.

Paper packaging is a sustainable alternative to plastic. However, as it is permeable to air, food packaged in paper loses its flavour over time, and undesirable substances such as solvents can penetrate the packaging. Up to now, extensive tests were necessary for each type of paper to determine to what extent and how quickly this happens. A research team led by Karin Zojer from the Institute of Solid State Physics at Graz University of Technology (TU Graz) has now developed an AI-based prediction system that calculates how permeable different types of paper are to volatile organic substances. This significantly speeds up the development of new packaging materials. The prediction tool, which was developed as part of the CD Laboratory for Mass Transport through Paper, is already being used by a paper manufacturer.

Dance is a form of cultural expression that has endured all of human history, channeling a seemingly innate response to the recognition of sound and rhythm. A team at the University of Tokyo and collaborators demonstrated distinct fMRI activity patterns in the brain related to a specific audience’s level of expertise in dance. The findings were born from recent breakthroughs in dance motion-capture datasets and AI generative models, facilitating a cross-modal study characterizing the art form’s complexity.

Researchers from Aalto University used network theory to develop a method for measuring the impact of individuals on societal division. While the method can be applied to any case around which social media data can be gathered, the initial study utilised Twitter data collected before Finland’s 2019 and 2023 parliamentary elections. The results reveal how a relatively small elite can have a disproportionately large influence on shaping polarizing environments.