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Experts consider glass nanoparticles kept inside extreme vacuum layers as potential platforms for examining the quantum world’s limits. However, a question in the field of quantum theory remains unanswered: at which size does an object start being described by quantum physics laws rather than classical physics laws?

Achieving Quantum-State Cooling in More Than One Direction Is Challenging

SciTechDaily reports that a research team attempted to precisely answer the question through the ERC-Synergy project Q-Xtreme. The team comprised Lukas Novotny from ETH Zurich, Markus Aspelmeyer from the University of Vienna, Oriol Romero-Isart from the University of Innsbruck, and Romain Quidant from Zurich.

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Computer models are an important tool for studying how the brain makes and stores memories and other types of complex information. But creating such models is a tricky business. Somehow, a symphony of signals—both biochemical and electrical—and a tangle of connections between neurons and other cell types creates the hardware for memories to take hold. Yet because neuroscientists don’t fully understand the underlying biology of the brain, encoding the process into a computer model in order to study it further has been a challenge.

Now, researchers at the Okinawa Institute of Science and Technology (OIST) have altered a commonly used computer model of called a Hopfield network in a way that improves performance by taking inspiration from biology. They found that not only does the new network better reflect how neurons and other cells wire up in the , it can also hold dramatically more memories.

The complexity added to the network is what makes it more realistic, says Thomas Burns, a Ph.D. student in the group of Professor Tomoki Fukai, who heads OIST’s Neural Coding and Brain Computing Unit. “Why would biology have all this complexity? Memory capacity might be a reason,” Mr. Burns says.

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National University of Singapore (NUS) pharmaceutical scientists have developed synthetic peptide nanonets for treating infections by bacteria strains resistant to last-resort antibiotics.

In nature, trap-and-kill is a common immune defense mechanism employed by various species, including humans. In response to the presence of pathogens, peptides are released from host cells and they promptly self-assemble in solution to form cross-linked nanonets, which then entrap the bacteria and render them more vulnerable to antimicrobial components.

Several research groups have explored synthetic biomimetics of nanonets as an avenue for addressing the global healthcare challenge of widespread . However, most prominent studies in the field only yielded disjointed short nanofibrils restricted to the bacterial surfaces and are incapable of physically immobilizing the bacteria. Additionally, these designs were lacking in control over the initiation of the self-assembly process.

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Optical computing has been gaining wide interest for machine learning applications because of the massive parallelism and bandwidth of optics. Diffractive networks provide one such computing paradigm based on the transformation of the input light as it diffracts through a set of spatially-engineered surfaces, performing computation at the speed of light propagation without requiring any external power apart from the input light beam. Among numerous other applications, diffractive networks have been demonstrated to perform all-optical classification of input objects.

Researchers at the University of California, Los Angeles (UCLA), led by Professor Aydogan Ozcan, have introduced a “time-lapse” scheme to significantly improve the accuracy of diffractive optical networks on complex input objects. The findings are published in the journal Advanced Intelligent Systems.

In this scheme, the object and/or the diffractive network are moved relative to each other during the exposure of the output detectors. Such a “time-lapse” scheme has previously been used to achieve super-resolution imaging, for example, in , by capturing multiple images of a scene with lateral movements of the camera.

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Wearable devices such as smartwatches, fitness trackers, and virtual reality headsets are becoming commonplace. They are powered by flexible electronics that consist of electrodes with plastic or metal foil as substrates. However, both of these come with their own drawbacks. Plastics suffer from poor adhesion and low durability, while metal foils make the devices bulky and less flexible.

In light of this, paper is a promising alternative. It is porous, light, thin, foldable, and flexible. Moreover, paper has randomly distributed fibers that provide a large surface area for depositing active electrode material, making for excellent electrochemical properties.

Accordingly, researchers have developed various paper-based supercapacitors, devices that store electric charge and energy, by stacking multiple sheets, acting as positive and negative electrodes and separators. However, such an arrangement increases device size and resistance. In addition, they tend to form creases, peel off, and slip over each other, which further deteriorate device performance.

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This larger-than-expected result shows the change in Dimorphos’ orbit was not just from the impact of the DART spacecraft. The larger part of the change was due to a recoil effect from all the ejected material flying off into space, which Ariel Graykowski of the SETI Institute and colleagues estimated as between 0.3 percent and 0.5 percent of the asteroid’s total mass.

A First Success

The success of NASA’s DART mission is the first demonstration of our ability to protect Earth from the threat of hazardous asteroids.

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Over time, clumps of dark matter began to gravitationally pull in regular matter, forming recognizable structures, such as galaxies. Galaxies, in turn, coalesced together into massive galaxy clusters that are linked across huge stretches of space by filaments of dark matter, creating what is now known as the cosmic web.

For years, scientists have speculated that magnetic fields within the cosmic web would help to produce shocks that might glow dimly in radio light. Now, for the first time, astronomers have captured this “predicted emission from the formation and growth of the large-scale structure of the Universe,” according to a recent study in Science Advances.

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As COVID has demonstrated, when pathogens are moving through the population, we adjust, limiting interactions, even isolating, and generally changing the way we associate with one other. Humans are not alone. New research from Harvard scientists provides some insight into how pathogens change animal social behaviors.

“Extreme environmental conditions have a very strong influence on all animals,” said Yun Zhang, a professor in the Department of Organismic and Evolutionary Biology. But while this behavior has been seen in animals from simple fruit flies all the way up to primates, researchers have not understood what happens inside an individual animal’s brain that leads to infection-induced changes in .

In their new paper, published in Nature, Zhang and colleagues studied the small roundworm C. elegans, which exists in nature with two sexes: hermaphrodites that produce both eggs and sperm, and males. Under normal conditions, the hermaphrodites are loners, preferring to self-reproduce over mating with males. However, Zhang’s team found that the hermaphrodite worms infected by a pathogenic strain of the bacterium Pseudomonas aeruginosa became more interested in one another and increased their mating with males.

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Determining the passage of time in our world of ticking clocks and oscillating pendulums is a simple case of counting the seconds between ‘then’ and ‘now’.

Down at the quantum scale of buzzing electrons, however, ‘then’ can’t always be anticipated. Worse still, ‘now’ often blurs into a haze of vagueness. A stopwatch simply isn’t going to work for some scenarios.

A potential solution could be found in the very shape of the quantum fog itself, according to a 2022 study by researchers from Uppsala University in Sweden.

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