Bruce66423 shares a report from the Guardian: New filtration technology developed by Rice University may absorb some Pfas "forever chemicals" at 100 times the rate than previously possible, which could dramatically improve pollution control and speed remediations. Researchers also say they have also found a way to destroy Pfas, though both technologies face a steep challenge in being deployed on an industrial scale. A new peer-reviewed paper details a layered double hydroxide (LDH) material made from copper and aluminum that absorbs long-chain Pfas up to 100 times faster than commonly used filtration systems.

[...] [Michael Wong, director of Rice's Water Institute, a Pfas research center] said Rice's non-thermal process works by soaking up and concentrating Pfas at high levels, which makes it possible to destroy them without high temperatures. The LDH material Rice developed is a variation of similar materials previously used, but researchers replaced some aluminum atoms with copper atoms. The LDH material is positively charged and the long-chain Pfas are negatively charged, which causes the material to attract and absorb the chemicals, Wong said. [...]

Pfas are virtually indestructible because their carbon atoms are bonded with fluoride, but Rice found that the bonds could be broken if the chemicals in the material were heated to 400-500C -- a relatively low temperature. The fluoride gets trapped in the LDH material and is bonded to calcium. The leftover calcium-fluoride material is safe and can be disposed of in a landfill, Wong said. The process works with some long-chain Pfas that are among the most common water pollutants, and it also absorbed some smaller Pfas that are commonplace.

Wong said he is confident the material can be used to absorb a broad array of Pfas, especially if they are negatively charged. Most new Pfas elimination systems fail to work at an industrial scale. Wong said the new material has an advantage because its absorption rate is so strong, it can be used repeatedly and it is in a "drop in material," meaning it can be used with existing filtration infrastructure. That eliminates one of the major cost barriers.

Marcel Bucher, a professor of plant sciences at the University of Cologne in Germany, lost two years of carefully structured academic work in an instant when he temporarily disabled ChatGPT's "data consent" option in August to test whether the AI tool's functions would still work without providing OpenAI his data. All his chats were permanently deleted and his project folders emptied without any warning or undo option, he wrote in a post on Nature.

Bucher, a ChatGPT Plus subscriber paying $20 per month, had used the platform daily to draft grant applications, prepare teaching materials, revise publication drafts and create exams. He contacted OpenAI support, first receiving responses from an AI agent before a human employee confirmed the data was permanently lost and unrecoverable. OpenAI cited "privacy by design" as the reason, telling Nature it does provide a confirmation prompt before users permanently delete a chat but maintains no backups.

Bucher said he had saved partial copies of some materials, but the underlying prompts, iterations, and project folders -- what he describes as the intellectual scaffolding behind his finished work -- are gone forever.

The United States formally withdrew from the World Health Organization on Thursday, making good on an executive order that President Trump issued on his first day in office pledging to leave the international organization that coordinates global responses to public health threats. The New York Times: While the United States is walking away from the organization, a senior official with the Department of Health and Human Services told reporters on Thursday that the Trump administration was considering some type of narrow, limited engagement with W.H.O. global networks that track infectious diseases, including influenza.

As a W.H.O. member, the United States long sent scientists from the Centers for Disease Control and Prevention to participate in international decision-making about which strains to include in the flu vaccine. A W.H.O. meeting on next year's vaccine is scheduled for February. The official said the Trump administration would soon disclose how or whether it will participate.

On Thursday, the administration said that all U.S. government funding to the organization had been terminated, and that all assigned federal employees and contractors had been recalled from its Geneva headquarters and its offices worldwide.

alternative_right shares a report from ScienceAlert: A systematic review of 85 studies has now found good reason to differentiate between 'active' sitting, like playing cards or reading, and 'passive' sitting, like watching TV. [...] "Total sitting time has been shown to be related to brain health; however, sitting is often treated as a single entity, without considering the specific type of activity," explains public health researcher Paul Gardiner from the University of Queensland in Australia. "Most people spend many hours sitting each day, so the type of sitting really matters ... These findings show that small everyday choices -- like reading instead of watching television -- may help keep your brain healthier as you age."

Across numerous studies, Gardiner and colleagues found that active sitting activities, like reading, playing card games, and using a computer, showed "overwhelmingly positive associations with cognitive health, enhancing cognitive functions such as executive function, situational memory, and working memory." Meanwhile, passive sitting was most consistently associated with negative cognitive outcomes, including increased risk of dementia. The study was published in the Journal of Alzheimer's Disease.

Ancient Slashdot reader erice shares the findings from a recent study showing that while AI helped researchers publish more often and boosted their careers, the resulting papers were, on average, less useful. "You have this conflict between individual incentives and science as a whole," says James Evans, a sociologist at the University of Chicago who led the study. From a recent IEEE Spectrum article: To quantify the effect, Evans and collaborators from the Beijing National Research Center for Information Science and Technology trained a natural language processing model to identify AI-augmented research across six natural science disciplines. Their dataset included 41.3 million English-language papers published between 1980 and 2025 in biology, chemistry, physics, medicine, materials science, and geology. They excluded fields such as computer science and mathematics that focus on developing AI methods themselves. The researchers traced the careers of individual scientists, examined how their papers accumulated attention, and zoomed out to consider how entire fields clustered or dispersed intellectually over time. They compared roughly 311,000 papers that incorporated AI in some way -- through the use of neural networks or large language models, for example -- with millions of others that did not.

The results revealed a striking trade-off. Scientists who adopt AI gain productivity and visibility: On average, they publish three times as many papers, receive nearly five times as many citations, and become team leaders a year or two earlier than those who do not. But when those papers are mapped in a high-dimensional "knowledge space," AI-heavy research occupies a smaller intellectual footprint, clusters more tightly around popular, data-rich problems, and generates weaker networks of follow-on engagement between studies. The pattern held across decades of AI development, spanning early machine learning, the rise of deep learning, and the current wave of generative AI. "If anything," Evans notes, "it's intensifying." [...] Aside from recent publishing distortions, Evans's analysis suggests that AI is largely automating the most tractable parts of science rather than expanding its frontiers.