Recently, micro/nanosatellites have become a significant trend in space with the rapid development of space technology, microelectromechanical systems, and commercial off-the-shelf components. However, most traditional micro/nanosatellites have poor reliability and real-time performance. The implementation of a real-time operating system (RTOS) can effectively prevent system crashes due to untimely responses, thereby enhancing the real-time performance and reliability of the micro/nanosatellite attitude determination system. The Dalian-1 Lianli satellite, a 17-kg 12U high-resolution remote sensing CubeSat, was developed to validate a series of innovative technologies, including submeter high-resolution remote sensing imaging, the high-reliability OpenHarmony real-time operating system (RTOS), and the nontoxic hydroxylamine nitrate propulsion system. The satellite first uses the free, high-reliability OpenHarmony RTOS in the world. Launched on 2023 May 10, aboard the Tianzhou-VI cargo spacecraft, the satellite was successfully deployed into orbit on 2024 January 18, following 253 d of in-orbit storage at the China Space Station.

This study systematically elucidates the drug resistance mechanisms of five highly pathogenic viruses, proposes five innovative anti-resistance strategies, and integrates artificial intelligence technology to establish a next-generation antiviral drug research and development framework, thereby providing critical theoretical support and transformative pathways for addressing clinical challenges associated with drug resistance.

New research from Fujita Health University reveals that talking can subtly delay the eyes’ ability to detect and stabilize on visual information. In experiments comparing talking, listening, and control conditions, only talking caused slower reaction, movement, and fixation times during rapid eye-movement tasks. Because driving depends heavily on fast gaze shifts, these delays may impair hazard detection and slow physical responses. The findings highlight the hidden risks of engaging in conversation while driving.

A research team developed a fully automated, drone-based phenotyping workflow that can measure key peanut canopy and architecture traits at scale—without the usual manual plot tracing and time-consuming image cleanup.

A research team has developed a new hybrid artificial intelligence framework that can accurately estimate leaf nitrogen content without relying on labor-intensive field measurements.

A research team has developed a new model, PlantIF, that addresses one of the most pressing challenges in agriculture: the accurate and timely diagnosis of plant diseases.

A research team has developed CornPheno, a smartphone-based tool designed to revolutionize corn phenotyping.