Radiative cooling fabric creates a thermally comfortable environment without energy input, providing a sustainable approach to personal thermal management. However, most currently reported fabrics mainly focus on outdoor cooling, ignoring to achieve simultaneous cooling both indoors and outdoors, thereby weakening the overall cooling performance. Herein, a full-scale structure fabric with selective emission properties is constructed for simultaneous indoor and outdoor cooling. The fabric achieves 94% reflectance performance in the sunlight band (0.3–2.5 µm) and 6% in the mid-infrared band (2.5–25 µm), effectively minimizing heat absorption and radiation release obstruction. It also demonstrates 81% radiative emission performance in the atmospheric window band (8–13 µm) and 25% radiative transmission performance in the mid-infrared band (2.5–25 μm), providing 60 and 26 W m⁻² net cooling power outdoors and indoors. In practical applications, the fabric achieves excellent indoor and outdoor human cooling, with temperatures 1.4–5.5 °C lower than typical polydimethylsiloxane film. This work proposes a novel design for the advanced radiative cooling fabric, offering significant potential to realize sustainable personal thermal management.

In a recent study, Medical University of South Carolina researchers compared two ways to help kids to get effective trauma therapy: training therapists vs. training therapists plus child protective services’ workers, juvenile justice professionals, school guidance counselors and others to spot struggling kids and refer them. Both approaches reduced kids’ posttraumatic stress and depression. The second method identified more kids who had experienced trauma and needed help and increased the number who finished treatment.

Recent research shows that using custom 3D-printed models tailored to each patient can help surgeons remove oral cancers more accurately. 

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.