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A Cornell-led research team has developed an artificial intelligence-powered ring equipped with micro-sonar technology that can continuously—and in real time—track fingerspelling in American Sign Language (ASL).

In its current form, SpellRing could be used to enter text into computers or smartphones via fingerspelling, which is used in ASL to spell out words without corresponding signs, such as proper nouns, names and technical terms. With further development, the device—believed to be the first of its kind—could revolutionize ASL translation by continuously tracking entire signed words and sentences.

The research is published on the arXiv preprint server.

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Korean researchers have succeeded in developing a key technology for all-solid-state secondary batteries, known as next-generation lithium-ion batteries due to their high safety. The work was published online as a cover study in Small at the end of last year.

Electronics and Telecommunications Research Institute (ETRI) developed a separation membrane based on a material that easily becomes fibrillized when subjected to mechanical shearing (force applied) through a mixing process with solid electrolyte powder without using a solvent. This solid electrolyte membrane is simple and fast to manufacture and is extremely thin and robust.

In general, in research on all-solid-state secondary batteries, the thickness is set to several hundred micrometers (µm) to 1 millimeter (mm) to increase the durability of the membrane when using a hard solid electrolyte in the manufacturing process. However, this has the disadvantage of being too thick compared to conventional polymer separation membranes, resulting in a very large loss of energy density.

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It may someday be possible to listen to a favorite podcast or song without disturbing the people around you, even without wearing headphones. In a new advancement in audio engineering, a team of researchers led by Yun Jing, professor of acoustics in the Penn State College of Engineering, has precisely narrowed where sound is perceived by creating localized pockets of sound zones, called audible enclaves.

In an enclave, a listener can hear sound, while others standing nearby cannot, even if the people are in an enclosed space, like a vehicle, or standing directly in front of the audio source.

In a study published in the Proceedings of the National Academy of Sciences, the researchers explain how emitting two nonlinear ultrasonic beams creates audible enclaves, where sound can only be perceived at the precise intersection point of two ultrasonic beams.

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We move thanks to coordination among many skeletal muscle fibers, all twitching and pulling in sync. While some muscles align in one direction, others form intricate patterns, helping parts of the body move in multiple ways.

In recent years, scientists and engineers have looked to muscles as potential actuators for “biohybrid” robots—machines powered by soft, artificially grown . Such bio-bots could squirm and wiggle through spaces where traditional machines cannot. For the most part, however, researchers have only been able to fabricate artificial muscle that pulls in one direction, limiting any robot’s range of motion.

Now MIT engineers have developed a method to grow artificial muscle tissue that twitches and flexes in multiple coordinated directions. As a demonstration, they grew an artificial, muscle-powered structure that pulls both concentrically and radially, much like how the iris in the human eye acts to dilate and constrict the pupil.

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For cattle fattened in fields instead of feedlots, the grass may be greener, but the carbon emissions are not.

A study out Monday in the Proceedings of the National Academy of Sciences finds that even in the most optimistic scenarios, grass-fed beef produces no less planet-warming than industrial beef. The finding calls into question the frequent promotion of grass-fed beef as a more environmentally friendly option. Still, other scientists say grass-fed beef wins out on other factors like or local environmental pollution, complicating the choice for conscientious consumers.

“I think that there is a large portion of the population who really do wish their purchasing decisions will reflect their values,” said Gidon Eshel, a research professor of environmental physics at Bard College and one of the study’s authors. “But they are being misled, essentially, by the wrong information.”

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International Iberian Nanotechnology Laboratory (INL) researchers have developed a neuromorphic photonic semiconductor neuron capable of processing optical information through self-sustained oscillations. Exploring the use of light to control negative differential resistance (NDR) in a micropillar quantum resonant tunneling diode (RTD), the research indicates that this approach could lead to highly efficient light-driven neuromorphic computing systems.

Neuromorphic computing seeks to replicate the information-processing capabilities of biological neural networks. Neurons in rely on rhythmic burst firing for sensory encoding, , and network synchronization, functions that depend on oscillatory activity for signal transmission and processing.

Existing neuromorphic approaches replicate these processes using electrical, mechanical, or thermal stimuli, but optical-based systems offer advantages in speed, energy efficiency, and miniaturization. While previous research has demonstrated photonic synapses and artificial afferent nerves, these implementations require additional circuits that increase power consumption and complexity.

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For decades, atomic clocks have been the pinnacle of precision timekeeping, enabling GPS navigation, cutting-edge physics research, and tests of fundamental theories. But researchers at JILA, led by JILA and NIST Fellow and University of Colorado Boulder physics professor Jun Ye, in collaboration with the Technical University of Vienna, are pushing beyond atomic transitions to something potentially even more stable: a nuclear clock.

This clock could revolutionize timekeeping by using a uniquely low-energy transition within the nucleus of a thorium-229 atom. This transition is less sensitive to environmental disturbances than modern atomic clocks and has been proposed for tests of fundamental physics beyond the Standard Model.

This idea isn’t new in Ye’s laboratory. In fact, work in the lab on nuclear clocks began with a landmark experiment, the results of which were published as a cover article of Nature last year, where the team made the first frequency-based, quantum-state-resolved measurement of the thorium-229 nuclear transition in a thorium-doped host crystal. This achievement confirmed that thorium’s nuclear transition could be measured with enough precision to be used as a timekeeping reference.

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The use of artificial intelligence (AI) scares many people as neural networks, modeled after the human brain, are so complex that even experts do not understand them. However, the risk to society of applying opaque algorithms varies depending on the application.

While AI can cause great damage in democratic elections through the manipulation of social media, in astrophysics it at worst leads to an incorrect view of the cosmos, says Dr. Jonas Glombitza from the Erlangen Center for Astroparticle Physics (ECAP) at Friedrich-Alexander Universität Erlangen-Nürnberg (FAU).

The astrophysicist uses AI to accelerate the analysis of data from an observatory that researches cosmic radiation.

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Researchers at Ruhr University Bochum, Germany, have shed light on the structure of supercritical water. In this state, which exists at extreme temperatures and pressures, water has the properties of both a liquid and a gas at the same time. According to one theory, the water molecules form clusters, within which they are then connected by hydrogen bonds.

The Bochum-based team has now disproven this hypothesis using a combination of terahertz spectroscopy and molecular dynamics simulations. The results are published in the journal Science Advances.

The experimentalists Dr. Katja Mauelshagen, Dr. Gerhard Schwaab and Professor Martina Havenith from the Chair of Physical Chemistry II collaborated with Dr. Philipp Schienbein and Professor Dominik Marx from the Chair of Theoretical Chemistry.

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About 100 million metric tons of high-density polyethylene (HDPE), one of the world’s most commonly used plastics, are produced annually, using more than 15 times the energy needed to power New York City for a year and adding enormous amounts of plastic waste to landfills and oceans.

Cornell chemistry researchers have found ways to reduce the environmental impact of this ubiquitous —found in milk jugs, shampoo bottles, playground equipment and many other things—by developing a machine-learning model that enables manufacturers to customize and improve HDPE materials, decreasing the amount of material needed for various applications. It can also be used to boost the quality of recycled HDPE to rival new, making recycling a more practical process.

“Implementation of this approach will facilitate the design of next-generation commodity materials and enable more efficient polymer recycling, lowering the overall impact of HDPE on the environment,” said Robert DiStasio Jr., associate professor of chemistry and chemical biology in the College of Arts and Sciences (A&S).

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