A research paper by scientists at Sichuan University presented a water-responsive self-curling adhesive conduit to achieve adaptive wrapping and suture-free repair for peripheral nerve injury.

The research paper, published on Mar 27, 2026 in the journal Cyborg and Bionic Systems.

The stress concentration and damage evolution of ultra-high performance concrete (UHPC) under long-term dynamic loading are difficult to monitor in real time, as conventional sensors suffer from poor durability, high cost, and incompatibility with matrix deformation. Recently, a team from the University of Shanghai for Science and Technology developed a machine learning framework that significantly improves dynamic compressive stress prediction in high-sensitivity ultra-high performance concrete (HS-UHPC) by incorporating electrical resistivity as a key input parameter. Using three machine learning algorithms—double-layer neural network, boosting tree, and squared exponential Gaussian process regression (SE-GPR)—the team demonstrated that adding resistivity measurements alongside traditional displacement data enhances predictive accuracy, with the SE-GPR model achieving an R² of 0.85 and reducing mean absolute error by 41.1% compared to displacement-only models. The core innovation is using electrical resistivity to directly capture load‑induced microstructural changes, overcoming the damage‑detection limitations of traditional strain or displacement measurements. This provides a new theoretical basis for intelligent monitoring of self‑sensing concrete.

A research team investigated how high-volume fly ash replacement affects concrete’s early-age characteristics and hardening properties. Tests with 0%–60% fly ash replacing cement show that fly ash improves flowability but delays early hydration. While early strength drops with higher fly ash, 10%–40% replacement delivers superior long-term mechanical performance. The team recommends 40% fly ash as the optimal cement replacement, balancing environmental sustainability, cost efficiency, and structural performance for green concrete engineering.

Climate extremes are adversely affecting cacao production. A recent study by Hasanuddin University highlights the potential of multistrata shade structures in addressing these challenges. Researchers show how a mix of shade trees—such as coconut, banana, and Gliricidia sepium—can help cacao plants grow better and become more resilient. These trees can improve soil fertility and help cacao plants cope with environmental variability—offering a pathway toward more resilient and sustainable smallholder agriculture.