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Astronomers discover new type of supernova triggered by black hole-star interaction

Astronomers have discovered what may be a massive star exploding while trying to swallow a black hole companion, offering an explanation for one of the strangest stellar explosions ever seen.

The discovery was made by a team led by the Center for Astrophysics | Harvard & Smithsonian (CfA) and the Massachusetts Institute of Technology (MIT) as part of the Young Supernova Experiment. The results are published in The Astrophysical Journal.

The blast, named SN 2023zkd, was first discovered in July 2023 by the Zwicky Transient Facility. A new AI algorithm designed to scan for unusual explosions in real time first detected the , and that early alert allowed astronomers to begin follow-up observations immediately—an essential step in capturing the full story of the explosion. By the time the explosion was over, it had been observed by a large set of telescopes, both on the ground and from space.

Observations investigate ultraluminous X-ray sources in the galaxy NGC 5813

Using NASA’s Chandra and ESA’s XMM-Newton space observatories, Indian astronomers have explored the population of ultraluminous X-ray sources in the galaxy NGC 5813, which resulted in the detection of a new source of this type. Results of the observational campaign were published August 7 on the pre-print server arXiv.

Researchers track how iron deficiency disrupts photosynthesis in crucial ocean algae

The next time you breathe, consider this: Photosynthesis of algae, powered by iron dust in the ocean, made it possible.

Now, a Rutgers University study published in the Proceedings of the National Academy of Sciences pulls back the curtain on this vital process.

Iron is a critical micronutrient for , the microscopic algae that form the foundation of the ocean’s . It is deposited into the world’s oceans as dust from deserts and arid areas as well as from glacial meltwater.

Agricultural sensor detects crops by their vibrations, offering an alternative approach for farm robots

Farmers might be able to get help tending and harvesting crops using a new sensing technology from Carnegie Mellon University’s Robotics Institute (RI). Researchers have invented a tool called SonicBoom that can find crops like apples based on the sound they make. The novel technology, still in the early stages of development, may someday be used by farm robots for tasks like pruning vines or locating ripe apples hidden among the leaves.

“Even without a camera, this sensing technology could determine the 3D shape of things just by touching,” said Moonyoung (Mark) Lee, a fifth-year Ph.D. student in robotics.

A paper describing this technology appears in IEEE Robotics and Automation Letters.

Sweat-sensitive jacket adjusts its thickness to keep you comfortable when it’s cold

When we are out in cold weather, we wear warm clothes to stay comfortable. But there is a snag. Regular warm clothing can’t adjust to changes in our body temperature. If we start to sweat, we get too hot and sticky, which makes us want to remove layers. This defeats the purpose of wearing them, since we still need to stay warm.

But what if our clothes could adapt? That’s the question Xiuqiang Li at Nanjing University of Aeronautics and Astronautics in China and his colleagues set out to answer. They have developed a jacket with a filling made from a bacterial cellulose membrane that responds to human sweating.

The innovative membrane automatically adjusts its thickness based on humidity. It’s 13 millimeters thick in cool, and shrinks to just 2 millimeters when humidity levels are high, such as when you sweat. This allows the to be thick when you need to stay warm and then get thinner when you want to cool down a little.

BEAST-GB model combines machine learning and behavioral science to predict people’s decisions

A key objective of behavioral science research is to better understand how people make decisions in situations where outcomes are unknown or uncertain, which entail a certain degree of risk.

The ability to predict people’s choices in these situations could be highly advantageous, as it could help to draft effective initiatives aimed at prompting people to make better decisions for themselves and others in their community.

Researchers at Technion (Israel Institute of Technology) and various institutes in the United States recently developed a new computational model called BEAST-GB, which was found to predict people’s decisions in situations that entail risk and uncertainty.

Computational framework sheds light on how the brain’s decision-making is impacted in psychiatric disorders

Scientists from the Icahn School of Medicine at Mount Sinai, working in collaboration with a team from the University of Texas at El Paso, have developed a novel computational framework for understanding how a region of the brain known as the striatum is involved in the everyday decisions we make and, importantly, how it might factor into impaired decision-making by individuals with psychiatric disorders like post-traumatic stress disorder and substance use disorder.

In a study published in Nature Communications, the team reported that modulating activity within the striosomal compartment—a neurochemically discrete area of the striatum—might be an important therapeutic strategy for promoting healthier in people with psychiatric disorders.

“Though it has been established that the striatum is clearly important for cost-benefit decision-making, the precise role of the striosomal compartment has remained elusive,” says Ki Goosens, Ph.D., Associate Professor of Pharmacological Sciences and Psychiatry, at the Icahn School of Medicine at Mount Sinai and co-lead author of the study.

A quantum gas that refuses to heat—physicists observe many-body dynamical localization

In everyday life, continuously doing work on a system is found to heat it up. Rubbing your hands together warms them. Hammering a piece of metal makes it hot. Even without knowing the equations, we learn from experience: driving any system, whether by stirring, pressing, or striking, leads to a rise in the system’s temperature.

The same expectation holds for microscopic quantum systems: when we continuously excite a many-particle system, especially one with strong particle-particle interactions, we expect it to absorb energy and to heat up. But is this always the case, in particular at the ?

No, says an experiment carried out by a team from Hanns-Christoph Nägerl’s group at the Department of Experimental Physics of the University of Innsbruck. The research has been published in Science.

Energy-efficient ultracompact laser reduces light loss in all directions

An international team of scientists led by Nanyang Technological University, Singapore (NTU Singapore) has developed a new type of ultracompact laser that is more energy efficient and consumes less power.

Smaller than a grain of sand, the micrometer-sized laser incorporates a special design that reduces light leakage. Minimizing light loss means less energy is required to operate the laser compared to other highly compact lasers.

The laser emits light in the terahertz region (30 μm—3 mm), a 6G communications frequency, and could pave the way for high-speed wireless communication of the future.

Researchers observe evidence of hyperbolic exciton polaritons

The ability to move electron-hole pairs—called excitons—in desired directions is important for generating electricity and creating fuels. This happens naturally in photosynthesis, making it a source of inspiration to researchers innovating optoelectronic devices.

Strong coupling between light and excitons generates bosonic quasiparticles called polaritons that express unique properties that positively affect device performance.

Researchers observed steady-state hyperbolic polaritons (HEPs)—exotic kinds of exciton polaritons with attractive properties—in the van der Waals magnet, chromium sulfide bromide (CrSBr).

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