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"So far, all lifeforms on Earth have a phosphorous-based chemistry, particularly as the backbone of DNA," writes longtime Slashdot reader bshell. "In 2010, a paper was published in Science claiming that arsenic-based bacteria were living in a California lake (in place of phosphorous). That paper was finally retracted by the journal Science the other day." From a report: : Some scientists are celebrating the move, but the paper's authors disagree with it -- saying that they stand by their data and that a retraction is not merited. In Science's retraction statement, editor-in-chief Holden Thorp says that the journal did not retract the paper when critics published take-downs of the work because, back then, it mostly reserved retractions for cases of misconduct, and "there was no deliberate fraud or misconduct on the part of the authors" of the arsenic-life paper. But since then, Science's criteria for retracting papers have expanded, he writes, and "if the editors determine that a paper's reported experiments do not support its key conclusions," as is the case for this paper, a retraction is now appropriate. "It's good that it's done," says microbiologist Rosie Redfield, who was a prominent critic of the study after its publication in 2010 and who is now retired from the University of British Columbia in Vancouver, Canada. "Pretty much everybody knows that the work was mistaken, but it's still important to prevent newcomers to the literature from being confused." By contrast, one of the paper's authors, Ariel Anbar, a geochemist at Arizona State University in Tempe, says that there are no mistakes in the paper's data. He says that the data could be interpreted in a number of ways, but "you don't retract because of a dispute about data interpretation." If that's the standard you were to apply, he says, "you'd have to retract half the literature."

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alternative_right shares a report from Phys.org: Driven by high temperatures in the Gulf, Hurricane Ian rapidly intensified from a Category 3 to Category 5 before making landfall in Southwest Florida on September 28, 2022. The deadly storm caught many by surprise and became the costliest hurricane in state history. Now, researchers from the University of South Florida say they've identified what may have caused Ian to develop so quickly. A strong ocean current called the Loop Current failed to circulate water in the shallow region of the Gulf. As a result, subsurface waters along the West Coast of Florida remained unusually warm during the peak of hurricane season. [...] The researchers found that if the Loop Current reaches an area near the Dry Tortugas, which they call the "pressure point," it can flush warm waters from the West Florida Shelf and replace it with cold water from deeper regions of the Gulf. This pressure point is where the shallow contours of the seafloor converge, forcing cold water to the surface in a process known as upwelling. In the months leading up to Hurricane Ian, the Loop Current did not reach the pressure point, leaving the waters on the shelf unmixed, which caused both the surface and subsurface waters on the West Florida Shelf to remain warm throughout summer. The findings have been published in Geophysical Research Letters.

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An anonymous reader quotes a report from Popular Science: On the early evening of June 22, 2010, American tennis star John Isner began a grueling Wimbledon match against Frenchman Nicolas Mahut that would become the longest in the sport's history. The marathon battle lasted 11 hours and stretched across three consecutive days. Though Isner ultimately prevailed 70-68 in the fifth set, some in attendance half-jokingly wondered at the time whether the two men might be trapped on that court for eternity. A similarly endless-seeming skirmish of rackets is currently unfolding just an hour's drive south of the All England Club -- at Google DeepMind. Known for pioneering AI models that have outperformed the best human players at chess and Go, DeepMind now has a pair of robotic arms engaged in a kind of infinite game of table tennis. The goal of this ongoing research project, which began in 2022, is for the two robots to continuously learn from each other through competition. Just as Isner eventually adapted his game to beat Mahut, each robotic arm uses AI models to shift strategies and improve. But unlike the Wimbledon example, there's no final score the robots can reach to end their slugfest. Instead, they continue to compete indefinitely, with the aim of improving at every swing along the way. And while the robotic arms are easily beaten by advanced human players, they've been shown to dominate beginners. Against intermediate players, the robots have roughly 50/50 odds -- placing them, according to researchers, at a level of "solidly amateur human performance." All of this, as two researchers involved noted this week in an IEEE Spectrum blog, is being done in hopes of creating an advanced, general-purpose AI model that could serve as the "brains" of humanoid robots that may one day interact with people in real-world factories, homes, and beyond. Researchers at DeepMind and elsewhere are hopeful that this learning method, if scaled up, could spark a "ChatGPT moment" for robotics -- fast-tracking the field from stumbling, awkward hunks of metal to truly useful assistants. "We are optimistic that continued research in this direction will lead to more capable, adaptable machines that can learn the diverse skills needed to operate effectively and safely in our unstructured world," DeepMind senior staff engineer Pannag Sanketi and Arizona State University Professor Heni Ben Amor write in IEEE Spectrum.

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