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Superconductivity, which entails an electrical resistance of zero at very low temperatures, is a highly desirable and thus widely studied quantum phenomenon. Typically, this state is known to arise following the formation of bound electron pairs known as Cooper pairs, yet identifying the factors contributing to its emergence in quantum materials has so far proved more challenging.

Researchers at Princeton University, the National High Magnetic Field Laboratory, Beijing Institute of Technology and the University of Zurich recently carried out a study aimed at better understanding the superconductivity observed in CsV₃Sb₅, a superconductor with a Kagome lattice (i.e., in which atoms form a hexagonal pattern that resembles that of Kagome woven baskets).

Their paper, published in Nature Physics, identifies two distinct superconducting regimes in this material, which were found to be linked to different transport and thermodynamic properties.

The X-37B is a reusable robotic space plane operated by the US Space Force. It resembles a miniature space shuttle at just under 9 metres long with a 4.5 metre wingspan and is an uncrewed vehicle designed for long-duration missions in low Earth orbit.

The craft launches vertically atop a rocket, lands horizontally like a conventional aircraft and serves as a testbed for new technologies and experiments that can be returned to Earth for analysis.

It’s development was a collaborative effort between NASA, Boeing, and the US Department of Defence. It was originally conceived by NASA in the late 1990s to explore reusable spaceplane technologies but transitioned to the US Air Force in 2004 for military purposes.

Shanghai Jiao Tong University along with multiple collaborating institutions including the University of Copenhagen and Lawrence Berkeley National Laboratory, have conducted an extensive investigation into microbial ecosystems in the deep ocean hadal zone.

Findings reveal an unprecedented level of taxonomic novelty, with 89.4% of identified microbial species previously unreported. The study demonstrated that selection pressures, favoring either streamlined or versatile adaptation strategies, dominate over neutral drift in shaping these extreme .

Hadal environments, located at depths exceeding 6,000 meters below sea level, remain among the least explored ecosystems on Earth. Manned submersibles capable of reaching full-ocean depth have been rare, with less than a dozen individuals visiting the deepest point of the Mariana Trench before 2019.

Sulfate-reducing bacteria break down a large proportion of the organic carbon in the oxygen-free zones of Earth, and in the seabed in particular. Among these important microbes, the Desulfobacteraceae family of bacteria stands out because its members are able to break down a wide variety of compounds—including some that are poorly degradable—to their end product, carbon dioxide (CO2).

A team of researchers led by Dr. Lars Wöhlbrand and Prof. Dr. Ralf Rabus from the University of Oldenburg, Germany, has investigated the role of these microbes in detail and published the findings of their comprehensive study in the journal Science Advances.

The team reports that the bacteria are distributed across the globe and possess a complex metabolism that displays modular features. All the studied strains possess the same central metabolic architecture for harvesting energy, for example.

Yale University, Dartmouth College, and the University of Cambridge researchers have developed MindLLM, a subject-agnostic model for decoding functional magnetic resonance imaging (fMRI) signals into text.

Integrating a neuroscience-informed attention mechanism with a large language model (LLM), the model outperforms existing approaches with a 12.0% improvement in downstream tasks, a 16.4% increase in unseen subject generalization, and a 25.0% boost in novel task adaptation compared to prior models like UMBRAE, BrainChat, and UniBrain.

Decoding into has significant implications for neuroscience and brain-computer interface applications. Previous attempts have faced challenges in predictive performance, limited task variety, and poor generalization across subjects. Existing approaches often require subject-specific parameters, limiting their ability to generalize across individuals.

To fuel the future advancement of the electronics industry, engineers will need to develop batteries that can be charged quickly, have higher energy densities (i.e., can store more energy) and last longer. Among the most promising alternatives to lithium-ion (Li-ion) batteries, which power most devices on the market today, are lithium-metal batteries (LMBs).

As suggested by their name, LMBs have an anode (i.e., negative electrode) made of Li metal. Compared to Li-ion batteries, which have graphite or silicon-based anodes, LMBs can exhibit significantly higher energy densities.

Despite their potential, LMBs have been found to exhibit slow redox kinetics and poor cycling reversibility. These limitations tend to adversely impact their performance, reducing their charging speed and their efficiency over time.

Organolithium compounds, molecules containing a carbon–lithium bond, are excellent precursors for building new carbon–carbon and other carbon–heteroatom bonds. They are widely utilized in both academia and industry for their applications in polymer synthesis, pharmaceuticals, and general organic synthesis.

A conventional method for generating organolithium compounds is done by reacting organohalide compounds, molecules containing a carbon–halogen bond, with lithium metal in an organic solvent. For example, a reaction between 1-bromobutane and lithium metal produces n-butyllithium.

Organolithiums are typically unstable and are therefore rapidly converted into a new product in situ after generating them.

The Automated Intimate Partner Violence Risk Support System (AIRS) utilizes clinical history and radiologic data to pinpoint patients seen in the emergency room who may be at a risk for intimate partner violence (IPV). Developed over the past five years, AIRS has been rolled out to the Brigham and Women’s Hospital’s Emergency Rooms in Boston as well as surrounding primary care sites. Currently, the tool has been validated at the University of California-San Francisco Medical Center and is being evaluated by the Alameda Health System for its role in clinical workflow.

“Data labeling quality is a huge concern—not just with intimate partner violence care, but in machine learning for healthcare and machine learning, broadly speaking,” says cofounder Irene Chen. “Our hope is that with training, clinicians can be taught how to spot intimate partner violence—we are hoping to find a set of cleaner labels.”

In 1989, political scientist Francis Fukuyama predicted we were approaching the end of history. He meant that similar liberal democratic values were taking hold in societies around the world. How wrong could he have been? Democracy today is clearly on the decline. Despots and autocrats are on the rise.

You might, however, be thinking Fukuyama was right all along. But in a different way. Perhaps we really are approaching the end of history. As in, game over humanity.

Now there are many ways it could all end. A global pandemic. A giant meteor (something perhaps the dinosaurs would appreciate). Climate catastrophe. But one end that is increasingly talked about is (AI). This is one of those potential disasters that, like climate change, appears to have slowly crept up on us but, many people now fear, might soon take us down.

Scientists have recorded the first-ever brain scan of a dying human.

A man suddenly died during a routine brain scan, revealing intriguing insights into what happens in our final moments.

An 87-year-old man undergoing a routine EEG for epilepsy suffered a fatal heart attack. Researchers found that in the 30 seconds before and after his heart stopped, his brain waves resembled those seen during dreaming, memory recall, and meditation.

This suggests that the commonly reported phenomenon of “life flashing before your eyes” may have a neurological basis. However, since this is a single case study, more research is needed to confirm how common this experience may be.

The findings, published by Dr. Ajmal Zemmar and his team, showed a surge in gamma waves — high-frequency neural oscillations linked to memory and consciousness — just before and after death.

These waves are typically observed when people recall memories, adding weight to the idea that the brain may replay key life events in its final moments. While this discovery cannot fully explain the mysteries of death, it offers a fascinating glimpse into the brain’s last activity and opens the door for further research on human consciousness at the end of life.