Space manipulators play an important role in the on-orbit services and planetary surface operation whose reliability is a key issue. In the extreme environment of space, space manipulators are susceptible to a variety of unknown disturbances. Since it is difficult for the manipulator to be repaired immediately, once it fails, it will mean that it cannot complete the mission as expected, which may cause serious losses and dangers. How to have a resilient guarantee, i.e., the manipulator’s ability to resiliently recover and continue to complete tasks, in failure or disturbance is the core capability of its future development. The motion planning unit is used as the computing terminal of the manipulator’s joint motion trajectory. Compared with traditional motion planning, learning-based motion planning has gradually become a hot spot in current research. However, no matter what kind of research ideas, the single robotic manipulator is studied as an independent agent, making it unable to provide sufficient flexibility under conditions such as external force disturbance, observation noise, and mechanical failure.

Researchers developed DeepMet, a new AI system that sharply improves long-range weather forecasting across the U.S. The model predicts key temperature and humidity patterns up to 45 days ahead with far greater accuracy than current systems, helping identify extreme heat and cold events earlier. DeepMet offers faster, more reliable guidance for climate preparedness and public-health protection.

An Osaka Metropolitan University-led research team conducted a review that examined the theoretical foundations of Artificial Superintelligence and explored how misaligned AI systems could optimize for wrong objectives, leading to patient harm and systemic failures.

Research groups of Professors Weiqi Zhang, Haiyan Xu and Lin Wang from the Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, reported a positively-charged dextran nano-photosensitizer (p-Dex PS) facilitates tumor-associated macrophage (TAM)-mediated delivery and sublethal light-induced metabolic reprogramming, which boosts the TAM polarization and subsequently the anticancer immune effects.

Extracellular vesicles serve as essential mediators of communication between immune cells and tumor cells, and the recent advances in artificial induction strategies offer an adaptable and efficient platform for engineering extracellular vesicles, enabling their application as next-generation strategies in cancer immunotherapy.

The lithium-ion battery is a new energy storage device widely employed in various fields such as mobile power, electric vehicles, unmanned aerial vehicles, and spacecrafts due to its high energy, high efficiency, lightweight, and environmental friendliness. Understanding the internal mechanism of the battery is of utmost importance. The electrochemical model provides detailed insights into the internal mechanism of lithium batteries and encompasses the single-particle model and the P2D model, as well as enhancements such as thermal coupling, mechanical stress coupling, and electric double-layer capacitive coupling. However, the dispersion effect of capacitors in solid electrolyte interface (SEI) film capacitors and porous electrodes has been basically ignored, which is essential for analyzing the internal mechanism and managing energy conversion in lithium batteries experiencing short-term effects. Furthermore, the determination of the dominant order of the Faraday process and non-Faraday process within a short time period is essential for accurately predicting the lifespan of lithium batteries subjected to high-frequency periodic excitation and assessing performance degradation. While the frequency range of these two processes can be roughly delineated through electrochemical impedance spectroscopy (EIS), the precise transition time of their dominant positions remains uncertain.

Monoterpenoids are important plant-derived compounds widely used in fragrances, nutraceuticals, and medicinal applications. 

The rapid expansion of high-throughput sequencing technologies has generated unprecedented amounts of multi-omics data, essential to advancing research in biodiversity, evolution, agriculture, medicine, and environmental science.