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To understand complex objects, humans are known to mentally transform them and represent them as a combination of simpler elements. This ability, known as compositionality, was so far assumed to require fluency in language, thus emerging in childhood after humans have learned to speak and understand others.

Researchers at Aix-Marseille University-CNRS and PSL University École des Hautes Études en Sciences Sociales-CNRS recently explored the possibility that compositionality is based on simple processes and might therefore already be present in infants. Their paper, published in Communications Psychology, provides evidence that infants as young as 1-year-old already possess basic compositional abilities.

“We are generally interested in understanding what is in place before language takes off in an infant’s mind,” Isabelle Dautriche, first author of the paper, told Medical Xpress. “One of the central properties of language is compositionality, which is a long word that simply means the capacity to put words together to understand sentences.

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The CMS collaboration at CERN has observed an unexpected feature in data produced by the Large Hadron Collider (LHC), which could point to the existence of the smallest composite particle yet observed. The result, reported at the Rencontres de Moriond conference in the Italian Alps this week, suggest that top quarks—the heaviest and shortest lived of all the elementary particles—can momentarily pair up with their antimatter counterparts to produce an object called toponium.

Other explanations cannot be ruled out, however, as the existence of toponium was thought too difficult to verify at the LHC, and the result will need to be further scrutinized by CMS’s sister experiment, ATLAS.

High-energy collisions between protons at the LHC routinely produce top quark–antiquark pairs (tt-bar). Measuring the probability, or cross section, of tt-bar production is both an important test of the Standard Model of particle physics and a powerful way to search for the existence of new particles that are not described by the 50-year-old theory. Many of the open questions in particle physics, such as the nature of dark matter, motivate the search for new particles that may be too heavy to have been produced in experiments so far.

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The gene encoding an enzyme from a firefly, discovered at the Sorocaba campus of the Federal University of São Carlos (UFSCar) in Brazil, has given rise to a biosensor capable of detecting pH changes in mammalian cells—which could be useful, for example, in studying diseases and assessing the toxicity of a drug candidate.

The luciferase from the species Amydetes vivianii changes color from bluish-green to yellow and red as acidity decreases in fibroblasts, the most common cell type in connective tissue. It does so with great intensity and stability, something that had not been achieved with other luciferases tested by the research group.

The work is published in the journal Biosensors.

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A team of physicists have discovered a new approach that redefines the conception of a black hole by mapping out their detailed structure, as shown in a research study recently published in Journal of High Energy Physics.

The study details new theoretical structures called “supermazes” that offer a more universal picture of to the field of theoretical physics. Based in , supermazes are pivotal to understanding the structure of black holes on a microscopic level.

“General relativity is a powerful theory for describing the large-scale structure of black holes, but it is a very, very blunt instrument for describing black-hole microstructure,” said Nicholas Warner, co-author of the study and professor of physics, astronomy and mathematics at the USC Dornsife College of Letters, Arts and Sciences. In a framework of theories extending beyond Einstein’s equations, supermazes provide a detailed portrait of the microscopic structure of brane black holes.

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Scientists at Oak Ridge National Laboratory have developed the first-ever method of detecting ribonucleic acid, or RNA, inside plant cells using a technique that results in a visible fluorescent signal. The technology can help researchers detect and track changes in RNA and gene expression in real time, providing a powerful tool for the development of hardier bioenergy and food crops and for the detection of unwanted plant modifications, pathogens and pests.

RNA is a signaling molecule inside cells that is used to read the deoxyribonucleic, or DNA, code and convert it into functional parts such as proteins that are essential for and . The ORNL-developed biosensor continuously monitors RNA levels in live plants, replacing a traditional destructive, time-consuming method used by scientists for collecting, processing and analyzing tissue.

“With this biosensor, scientists gain real-time insights into how cells reprogram themselves at a molecular level under changing environmental conditions such as drought or disease,” said Xiaohan Yang, lead for the project at ORNL. The approach streamlines traditional methods used to verify in modified plants and can better detect plant physiology related to disease or nutrient stress, accelerating the development of better crops.

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Research by physicists at The City College of New York is being credited for a novel discovery regarding the interaction of electronic excitations via spin waves. The finding by the Laboratory for Nano and Micro Photonics (LaNMP) team headed by physicist Vinod Menon could open the door to future technologies and advanced applications such as optical modulators, all-optical logic gates, and quantum transducers. The work is reported in the journal Nature Materials.

The researchers showed the emergence of interaction between electronic excitations (excitons—electron hole pairs) mediated via spin waves in atomically thin (2D) magnets. They demonstrated that the excitons can interact indirectly through magnons (), which are like ripples or waves in the 2D material’s magnetic structure.

“Think of magnons as tiny flip-flops of atomic magnets inside the crystal. One exciton changes the local magnetism, and that change then influences another nearby. It’s like two floating objects pulling toward each other by disturbing water waves around them,” said Menon.

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Twisted moiré photonic crystals—an advanced type of optical metamaterial—have shown enormous potential in the race to engineer smaller, more capable and more powerful optical systems. How do they work?

Imagine you have two pieces of fabric with regular patterns, like stripes or checkers. When you lay the two pieces of fabric directly on top of each other, you can see each pattern clearly. But if you slightly shift one piece of fabric or twist it, new patterns that weren’t in either of the original fabrics emerge.

In twisted moiré photonic crystals, how the layers twist and overlap can change how the material interacts with light. By changing the twist angle and the spacing between layers, these materials can be fine-tuned to control and manipulate different aspects of light simultaneously—meaning the multiple optical components typically needed to simultaneously measure light’s phase, polarization, and wavelength could be replaced with one device.

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An invention from Twente improves the quality of light particles (photons) to such an extent that building quantum computers based on light becomes cheaper and more practical. The researchers published their research in the journal Physical Review Applied.

Quantum computers are at a tipping point: tech giants and governments are investing billions, but there are two fundamental obstacles: the quantity of qubits and the quality of these qubits. UT researchers have invented a component for a photonic quantum computer that exchanges quantity for quality, and have shown that this exchange yields more computing power.

“Our discovery brings a future with a lot closer. That means improved medicines, new materials and safer communications. But also applications that we cannot yet imagine today,” says lead researcher Jelmer Renema. “This technology is an essential part of any future photonic quantum computer.”

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AI has created a sea change in society; now, it is setting its sights on the sea itself. Researchers at Osaka Metropolitan University have developed a machine learning-powered fluid simulation model that significantly reduces computation time without compromising accuracy.

Their fast and precise technique opens up potential applications in offshore power generation, ship design and real-time ocean monitoring. The study was published in Applied Ocean Research.

Accurately predicting fluid behavior is crucial for industries relying on wave and tidal energy, as well as for the design of maritime structures and vessels.

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Monash University researchers have extended Descartes’ Circle Theorem by finding a general equation for any number of tangent circles, using advanced mathematical tools inspired by physics. A centuries-old geometric puzzle dating back to the 17th century has finally been solved by mathematicians

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