Researchers have developed new algorithms to enhance the reliability of data center networks (DCNs) by constructing fault-tolerant paths and maximum disjoint paths in augmented cube-based architectures. These breakthroughs address critical challenges in handling node failures and improving data transmission efficiency, which are vital as cloud computing and big data continue to drive DCN expansion. The findings were published on 15 June 2026 in Frontiers of Computer Science, a journal co-published by Higher Education Press and Springer Nature.

Osaka Metropolitan University researchers used GPS trajectory data and quasi-experimental methods to evaluate how the opening of ONIKURU affected citizens’ stay behavior.

In almost half of all fatal electric scooter crashes in Sweden, the rider has been under the influence of alcohol. These fatal crashes occur mainly in the evenings or through the night, and in all cases, no helmet has been worn. This is shown by a new study from Chalmers University of Technology, in Sweden, and the Swedish Transport Administration. The study also states that most fatal crashes occur with private electric scooters, rather than rentals.

Researchers developed a two-step simulation framework to predict rail-induced vibrations in a hotel planned near Changsha Huanghua Airport Terminal 3, where subway and high-speed railway infrastructure intersect. The study found that some train operations could make floor vibrations perceptible and exceed vibration limits, while a combined track-based mitigation strategy could bring all evaluated indicators within relevant standards.

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.

Seoul National University College of Engineering announced that a joint research team led by Prof. Ho-Young Kim of the Department of Mechanical Engineering at SNU, together with Ph.D. candidate Seungjoo Lee and Dr. Junhee Choi, and Prof. Sung Jae Kim of the Department of Electrical and Computer Engineering, in collaboration with Prof. Wonjung Kim of Yonsei University, Prof. Sohyuni Jung of DGIST, and Dr. Wonseok Kim of Harvard Medical School, has, for the first time, uncovered the physical mechanism by which the desert horned lizard (Phrynosoma platyrhinos) drinks water. The team also developed an innovative biomimetic water-harvesting system capable of extracting clean drinking water from contaminated soil.

This interdisciplinary study, involving researchers from multiple institutions in Korea and abroad, has been recognized for its excellence and published in PNAS (Proceedings of the National Academy of Sciences), one of the world’s leading multidisciplinary scientific journals. Notably, the study was selected as a highlighted paper in PNAS’s “In This Issue” section, where the journal’s editor-in-chief and editorial board handpick the most noteworthy papers published each week, drawing significant global attention.

Researchers from the South Dakota School of Mines and Technology have developed a smart detection system that automatically identifies surface defects on aluminum gas meter lids. By combining three different deep learning models, the ensemble approach achieved over 97% accuracy in detecting cracks and cold flows, offering a faster, more reliable alternative to manual inspection that could improve safety and reduce waste in manufacturing.

Researchers developed a photonic spiking hashing framework that uses a DFB-SA laser to generate robust binary codes for similarity retrieval. By introducing a hardware-aware quantization margin loss, the system reduces noise-induced bit flips near the threshold boundary. Hardware-in-the-loop experiments on image and text datasets produced error-free binary outputs in the tested queries while maintaining high retrieval accuracy.