A new artificial intelligence (AI) framework offers a more reliable way to restore partially hidden objects in satellite imagery. 

Starting from syringic acid, a natural phenolic acid with favorable safety and biodegradability features, Prof. Runjiang Song's team at the State Key Laboratory of Green Pesticide, Guizhou University, designed a series of derivatives by combining the syringic acid scaffold with an allicin-inspired disulfide unit and a 1,3,4-oxadiazole moiety. Among 34 derivatives, compound C31 emerged as the most potent anti-Xoo molecule, with an EC₅₀ of 0.86 μg/mL. In rice pot experiments, C31 achieved 59.37% control efficacy against bacterial leaf blight, outperforming syringic acid and the commercial reference thiodiazole copper in this study.

A research team led by Professors Jiafu Wang and Jue Qu has jointly developed an eye-tracking-driven, polarization-agile, and beam-programmable metasurface. This system integrates high-precision eye-tracking technology with advanced programmable metasurface design, enabling real-time 3D beam focusing and adaptive reconfiguration of polarization modes for wireless communication signals. This achievement was published in Research under the title "Eye-Tracking-Driven Programming Metasurface System for Adaptive Beam Focusing and Polarization-agile Communication".