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Hair Holds Hidden Clues to Children’s Mental Health Crisis

A strand of hair might seem like an unlikely window into a child’s psychological wellbeing, but new research from the University of Waterloo suggests that measuring stress hormones in hair samples could help identify which children with chronic illnesses are most at risk for developing serious mental health problems.

The four-year study of 244 Canadian children reveals a concerning pattern: more than two-thirds of kids living with chronic physical conditions showed persistently elevated levels of cortisol, the body’s primary stress hormone, measured through their hair. These children also displayed more symptoms of depression, anxiety, and behavioral problems compared to peers whose stress levels naturally declined over time.

Doing The Math On CPU-Native AI Inference

A number of chip companies — importantly Intel and IBM, but also the Arm collective and AMD — have come out recently with new CPU designs that feature native Artificial Intelligence (AI) and its related machine learning (ML). The need for math engines specifically designed to support machine learning algorithms, particularly for inference workloads but also for certain kinds of training, has been covered extensively here at The Next Platform.

Just to rattle off a few of them, consider the impending “Cirrus” Power10 processor from IBM, which is due in a matter of days from Big Blue in its high-end NUMA machines and which has a new matrix math engine aimed at accelerating machine learning. Or IBM’s “Telum” z16 mainframe processor coming next year, which was unveiled at the recent Hot Chips conference and which has a dedicated mixed precision matrix math core for the CPU cores to share. Intel is adding its Advanced Matrix Extensions (AMX) to its future “Sapphire Rapids” Xeon SP processors, which should have been here by now but which have been pushed out to early next year. Arm Holdings has created future Arm core designs, the “Zeus” V1 core and the “Perseus” N2 core, that will have substantially wider vector engines that support the mixed precision math commonly used for machine learning inference, too. Ditto for the vector engines in the “Milan” Epyc 7,003 processors from AMD.

All of these chips are designed to keep inference on the CPUs, where in a lot of cases it belongs because of data security, data compliance, and application latency reasons.

Electrical flash method rapidly purifies red mud into strong ceramics, aluminum feedstock

A team of researchers at Rice University has developed a faster and cleaner method for recovering aluminum and removing toxic metals from bauxite residue, or red mud, which is a hazardous by-product of aluminum production.

This new technique, published in ACS Applied Materials and Interfaces, involves a brief electrical pulse lasting under one minute, along with a small amount of chlorine gas. If implemented on a larger scale, it could revolutionize global waste management and materials recovery.

The process uses flash joule heating (FJH), which rapidly heats materials with a short, high-power electrical pulse to vaporize harmful metals, leaving behind a residue rich in aluminum. This aluminum-rich material can then be repurposed into durable ceramic tiles or bricks or resubjected to the normal aluminum production process. The method offers a practical and scalable solution to address a significant pollution problem by transforming it into valuable materials, marking an advancement in industrial waste recovery.

New study sheds light on how exercise helps lose weight

Researchers have provided new insights into how exercise helps lose weight. They discovered a mechanism by which the compound Lac-Phe, which is produced during exercise, reduces appetite in mice, leading to weight loss. The findings appeared in Nature Metabolism.

“Regular exercise is considered a powerful way to lose weight and to protect from obesity-associated diseases, such as diabetes or heart conditions,” said co-corresponding author Dr. Yang He, assistant professor of pediatrics—neurology at Baylor and investigator at the Duncan NRI. “Exercise helps lose weight by increasing the amount of energy the body uses; however, it is likely that other mechanisms are also involved.”

The researchers previously discovered that Lac-Phe is the most increased metabolite—a product of the body’s metabolism—in blood after intense exercise, not just in mice but also in humans and racehorses. The team’s previous work showed that giving Lac-Phe to obese mice reduced how much they ate and helped them lose weight without . But until now, scientists didn’t fully understand how Lac-Phe works to suppress .

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