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Climbing the social ladder: A clear understanding of connections matters more than popularity, study suggests

Climbing the social ladder isn’t simply a matter of popularity. Rather, people in positions of influence are particularly adept at forming “maps” of their social connections, which they navigate to become prominent in their social network, new research shows.

It’s like having a “social superpower,” according to study author Oriel FeldmanHall, an associate professor of cognitive and psychological sciences at Brown University who is affiliated with the University’s Carney Institute for Brain Science.

“People vary considerably in how accurately they understand the structure of their communities,” FeldmanHall said. “Our research establishes for the first time that people who excel at mapping out their social network—determining who belongs to which communities and cliques—are the ones who will go on to become the most influential in the social network.”

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Scientists demonstrate unconditional exponential quantum scaling advantage using two 127-qubit computers

Quantum computers have the potential to speed up computation, help design new medicines, break codes, and discover exotic new materials—but that’s only when they are truly functional.

One key thing that gets in the way: noise or the errors that are produced during computations on a quantum machine—which in fact makes them less powerful than —until recently.

Daniel Lidar, holder of the Viterbi Professorship in Engineering and Professor of Electrical & Computer Engineering at the USC Viterbi School of Engineering, has been iterating on , and in a new study along with collaborators at USC and Johns Hopkins, has been able to demonstrate a quantum exponential scaling advantage, using two 127-qubit IBM Quantum Eagle processor-powered quantum computers, over the cloud.

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Brain organizes visuomotor associations into structured graph-like mental schemes, study finds

Graphs, visual representations outlining the relationships between different entities, concepts or variables, can be very effective in summarizing complex patterns and information. Past psychology studies suggest that the human brain stores memories and experiences following graph-like and structured patterns, specifically as a network of associations, also referred to as cognitive graphs.

These cognitive graphs are hypothesized to represent different concepts as “nodes” and the relationships between these concepts as edges connecting these nodes. By organizing information in a structured way, they can allow people to apply knowledge they have acquired in the past to new situations and draw conclusions about what is happening based on previous experiences.

The role of cognitive graphs has been widely investigated in the past, with most studies focusing on their contribution to the storage and retrieval of facts and knowledge (i.e., declarative memories). In contrast, the extent to which they influence the planning and control of movements remains poorly understood.

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Embryos can eliminate bacterial infections before forming their immune system, new research shows

Research led by scientists from the Institute of Molecular Biology of Barcelona (IBMB) of the CSIC and the Bellvitge Biomedical Research Institute (IDIBELL) has managed to film how a few days-old embryos defend themselves from a potential infection by bacteria. The work is published this week in the journal Cell Host and Microbe.

Specifically, they have been able to see how use cells present on their surface, known as , to ingest and destroy bacteria through a process called phagocytosis, similar to that carried out by white blood cells. Crucially, scientists could observe that this ability to eliminate bacteria is also present in .

Using state-of-the-art microscopy techniques, the research shows how cells capture Escherichia coli and Staphylococcus aureus bacteria through small protrusions of their membrane, in which the protein Actin is involved. “Our research shows that, at the beginning of development—before implantation in the uterus and before the formation of organs—embryos already have a defense system that allows them to eliminate bacterial infections,” says Esteban Hoijman, researcher at IBMB-CSIC and IDIBELL, leader of the research.

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Advanced algorithm to study catalysts on material surfaces could lead to better batteries

A new algorithm opens the door for using artificial intelligence and machine learning to study the interactions that happen on the surface of materials.

Scientists and engineers study the that happen on the surface of materials to develop more energy efficient batteries, capacitors, and other devices. But accurately simulating these fundamental interactions requires immense computing power to fully capture the geometrical and chemical intricacies involved, and current methods are just scratching the surface.

“Currently it’s prohibitive and there’s no supercomputer in the world that can do an analysis like that,” says Siddharth Deshpande, an assistant professor in the University of Rochester’s Department of Chemical Engineering. “We need clever ways to manage that large data set, use intuition to understand the most important interactions on the surface, and apply data-driven methods to reduce the sample space.”

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Scale of how chronic fatigue syndrome affects patients’ blood shown for first time

People with ME/CFS (myalgic encephalomyelitis/chronic fatigue syndrome) have significant differences in their blood compared with healthy individuals, a new study reveals, suggesting a path toward more reliable diagnosis of the long-term debilitating illness. The paper is published in the journal EMBO Molecular Medicine.

The largest ever biological study of ME/CFS has identified consistent blood differences associated with chronic inflammation, insulin resistance, and liver disease.

Significantly, the results were mostly unaffected by patients’ activity levels, as low activity levels can sometimes hide the biological signs of illness, experts say.

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Rewriting a century-old physics law on thermal radiation to unlock the potential of energy, sensing and more

A research team from Penn State has broken a 165-year-old law of thermal radiation with unprecedented strength, setting the stage for more efficient energy harvesting, heat transfer and infrared sensing.

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Magically reducing errors in quantum computers: Researchers invent technique to decrease overhead

For decades, quantum computers that perform calculations millions of times faster than conventional computers have remained a tantalizing yet distant goal. However, a new breakthrough in quantum physics may have just sped up the timeline.

In an article titled “Efficient Magic State Distillation by Zero-Level Distillation” published in PRX Quantum, researchers from the Graduate School of Engineering Science and the Center for Quantum Information and Quantum Biology at the University of Osaka devised a method that can be used to prepare high-fidelity “magic states” for use in quantum computers with dramatically less overhead and unprecedented accuracy.

Quantum computers harness the fantastic properties of quantum mechanics such as entanglement and superposition to perform calculations much more efficiently than classical computers can. Such machines could catalyze innovations in fields as diverse as engineering, finance, and biotechnology. But before this can happen, there is a significant obstacle that must be overcome.

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AI image models gain creative edge by amplifying low-frequency features

Recently, text-based image generation models can automatically create high-resolution, high-quality images solely from natural language descriptions. However, when a typical example like the Stable Diffusion model is given the text “creative,” its ability to generate truly creative images remains limited.

KAIST researchers have developed a technology that can enhance the creativity of text-based image generation models such as Stable Diffusion without additional training, allowing AI to draw creative chair designs that are far from ordinary.

Professor Jaesik Choi’s research team at KAIST Kim Jaechul Graduate School of AI, in collaboration with NAVER AI Lab, developed this technology to enhance the creative generation of AI generative models without the need for additional training. The work is published on the arXiv preprint server the code is available on GitHub.

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Phonon-mediated heat transport across materials visualized at the atomic level

Gao Peng’s research group at the International Center for Quantum Materials, School of Physics, Peking University, has developed a breakthrough method for visualizing interfacial phonon transport with sub-nanometer resolution. Leveraging fast electron inelastic scattering in electron microscopy, the team directly measured temperature fields and thermal resistance across interfaces, unveiling the microscopic mechanism of phonon-mediated heat transport at the nanoscale.

The study is published in Nature under the title “Probing transport dynamics across an interface by .”

Phonons are central to heat conduction, electrical transport, and light interactions. In modern semiconductor devices, phonon mismatches at material interfaces create significant thermal resistance, limiting performance. Yet, existing methods lack the spatial resolution needed for today’s sub-10 nm technologies.

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