With the accelerated advancement of lunar and Mars exploration programs, long-term human habitation on extraterrestrial bodies faces the severe challenge of extreme diurnal temperature variations. Phase change materials (PCMs), owing to their ability to store or release substantial latent heat during solid–liquid phase transitions while maintaining a nearly constant temperature, have become an ideal solution for space thermal control systems. However, in the microgravity environment of space, the ground-dominant natural convection tends to disappear, and thermocapillary convection may become the prevailing heat transfer mechanism; in low-gravity environments such as those on the Moon and Mars, the coexistence and competition between these two convective regimes remain unclear. Existing studies have predominantly focused on either Earth's gravity or pure microgravity conditions, with a notable scarcity of research on the coupled effects of thermocapillary and natural convection at intermediate gravity levels. The melting dynamics of two typical organic PCMs, succinonitrile and n-octadecane, under low-gravity conditions have not yet been systematically elucidated. Therefore, clarifying the roles of thermocapillary convection under varying gravity levels and container geometries holds significant engineering guidance for the design of efficient space thermal control systems.

Cognitive impairment, including mild cognitive impairment (MCI) and Alzheimer's disease, is a growing challenge in ageing societies. Early detection is crucial, as timely intervention can improve care planning, monitoring and quality of life. Yet cognitive decline is often identified only after symptoms have become more pronounced, limiting opportunities for support.

High-voltage direct current (HVDC) lines are often described as the power highways of the clean-energy era, carrying large amounts of electricity across long distances with high efficiency. 

Osaka Metropolitan University researchers developed an AI-driven transfer-learning method that refines volume size factor predictions from first-principles calculations, enabling more reliable prediction of properties in previously unexplored alloy systems.

Quantum random number generators play a crucial role in securing high-demand information contexts by producing true random numbers. Nevertheless, the large volume and high cost limit their widespread use. Here, a system on-chip is proposed that fully leverages the advantages of different photonic integrated platforms, where the interference optical paths and photodiodes are integrated on a standard silicon process, while the laser source on-chip is realized on a III–V platform. Using micro-lens coupling package technology with coupling loss lower than 2 dB, the components on different platforms are combined and packaged with the amplifier circuits in a 42 mm × 24 mm footprint in a butterfly form. This miniaturized and cost-effective entropy source enables outputting a vacuum noise signal with a 3-dB bandwidth of over 500 MHz. After sampling and post-processing, a random number generation rate of up to 6.57 Gbps is achieved.

Getting sick can look very different for people with Down syndrome (DS); illnesses that are mild for most people may lead to serious complications, including pneumonia, hospitalization or intensive care.

Scientists have long known that excess hydrogen sulfide — a naturally occurring gas that becomes harmful when it accumulates in cells — has been a contributing factor for susceptibility to infections for people with DS. For years, researchers have believed that a chromosome 21 gene called CBS was largely responsible for this overproduction.

But now, researchers at the Texas A&M University College of Veterinary Medicine and Biomedical Sciences (VMBS) and the Texas A&M Health Institute of Biosciences and Technology (IBT) have identified evidence for a previously unknown pathway that may help explain those immune challenges.