When a research team from Eurac Research entered the warehouses of the National Archaeological Museum in La Paz a couple of years ago, they were stunned to find more than 50 mummified individuals and over 500 pre-Columbian skulls, preserved with good intentions but in conditions that put them at risk of contamination by fungi and bacteria. This is a situation that often occurs in countries that cannot devote large sums of money to the conservation of cultural heritage, but also in countries such as Italy, where the heritage is so vast that it is difficult to take care of everything. The problem of protecting organic cultural heritage also arises when it needs to be transported or studied. Environmental conditions can have a significant impact on the most sensitive items, such as mummified human remains, textiles, paper, and wood. A research team coordinated by Eurac Research has been experimenting with conservation techniques and materials for years and has now developed an innovative, versatile, and inexpensive system called the Conservation Soft Box. It was recently presented in an article in the Journal of Cultural Heritage and at the 11th World Congress of Mummy Studies in Cuzco, Peru.

Zebrafish midline tissues coordinate their growth during embryonic development using a leader-follower strategy described by formation control, as reported by researchers from Japan and the USA. The notochord leads elongation, while adjacent tissues grow and migrate with it in response to fibroblast growth factor gradients, cadherin-2-mediated cell adhesion, and mechanosensory Yap signaling. The researchers could replicate this behavior using a mathematical model, revealing a control theory-based principle for harmonized tissue development in embryos.

Choosing how to live in a way that truly helps our overburdened planet can be difficult. Researchers at DTU have calculated the impact of a wide range of everyday activities to help consumers lighten their impact on the environment.

Researchers have shown for the first time how hidden motions could control how granular materials such as soil and snow slip and slide, confirming a long-suspected hypothesis. The knowledge could help in understanding how landslides and avalanches work and even help the construction industry in the future.

Shanghai, August 21, 2025 — Nuclear energy is widely recognized as one of the most promising clean energy sources for the future, but its safe and efficient use depends critically on the development of robust nuclear fuels and structural materials that can endure extreme environments. A newly published review in AI & Materials highlights how machine learning (ML) is transforming this field, enabling scientists to accelerate discoveries, optimize performance, and overcome long-standing challenges in nuclear materials research.

The article, titled “Machine learning in research and development of advanced nuclear materials: a systematic review for continuum-scale modelling,” was authored by Chaoyue Jin and Professor Shurong Ding from the Institute of Mechanics and Computational Engineering at Fudan University. It provides an in-depth systematic review of how ML has been applied to nuclear fuels and structural materials, particularly at the continuum scale.