AI-assisted optical imaging could ease a major bottleneck in breast cancer surgery
Peer-Reviewed Publication
Updates every hour. Last Updated: 27-Oct-2026 09:16 ET (27-Oct-2026 13:16 GMT/UTC)
For many patients with breast cancer, deciding whether cancer has spread to nearby lymph nodes still depends on labor-intensive pathology workflows that require tissue cutting, staining, and expert interpretation.
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.
Electromagnetic waves are extensively utilized in many fields such as communication and medicine. Excessive electromagnetic waves will cause electromagnetic pollution. Electromagnetic pollution may lead to electromagnetic interference (EMI), which will interfere sensitive electronic devices. Furthermore, electromagnetic pollution is harmful to human health and may potentially cause information leakage. The development of lightweight and flexible EMI shielding materials with high mechanical strength and excellent flame retardant properties is currently a hot and difficult research topic.
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.
This study reveals that geographic isolation and Quaternary climatic fluctuations jointly drove genetic differentiation and multiple glacial refugia of the fully mycoheterotrophic herb Burmannia nepalensis, with recent human activity causing population decline.
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.