Lifeboat Foundation: Safeguarding Humanity
Toggle light / dark theme

Blog – Page 2

Get the latest international news and world events from around the world.

Log in for authorized contributors

AI system translates protein sequences into text, helping reveal functions of unknown proteins

In a paper published in Proceedings of the National Academy of Sciences, researchers from Technion and Tel Aviv University present BetaDescribe, an AI system that translates protein sequences into natural-language descriptions, opening a new path toward understanding protein functions and accelerating drug development and material design.

Protein analysis is essential in medicine and biotechnology, as demonstrated by breakthroughs such as Ozempic, a drug whose development was inspired by a peptide found in the saliva of a rare desert lizard and is used to treat obesity, diabetes and other conditions. However, experimental protein characterization remains a lengthy and expensive process, and even large language models (LLMs) have had limited success in performing this task.

This challenge inspired the development of BetaDescribe, an AI system that converts protein sequences into detailed textual descriptions of their functions and other characteristics. In doing so, the system helps bridge the vast gap between the hundreds of thousands of proteins characterized in the lab and the billions or even trillions that actually exist in nature.

New AI add-on helps developers automate everyday programming tasks

Developers are increasingly relying on large language models (LLMs) for everyday computing tasks such as fixing bugs, explaining code and automating text-processing tasks like filtering logs.

However, it’s not as simple as entering or submitting a question and relying on the model to give you the answer. While humans easily understand these tasks and know exactly what they want, it is difficult to translate them into rigid computer code.

Atomic ‘domino effect’ found to drive phase changes in a two-dimensional crystal

Phase transformations—in which a material changes from one crystal structure to another, thereby acquiring dramatically different properties—are ubiquitous in nature. Understanding the microscopic mechanisms of these transformations is essential for controlling material properties and designing functional devices.

A research team led by Profs. Chen Xingqiu and Sun Yan from the Institute of Metal Research (IMR) of the Chinese Academy of Sciences, in collaboration with Prof. Niu Haiyang from Northwestern Polytechnical University, has uncovered a previously unknown phase transformation mechanism in monolayer molybdenum telluride (MoTe2).

The study, published in Proceedings of the National Academy of Sciences on June 29, reveals a phase transformation pathway that is fundamentally distinct from the conventional martensitic model, in which many atoms move together through concerted shear displacements.

Video games might modestly sharpen your memory and other cognitive skills, review suggests

Because video games are a regular part of many people’s everyday lives, researchers have spent a lot of time trying to determine whether they are beneficial or detrimental to brain health. A new study, published in Acta Psychologica, has compiled 20 years of research on how video games affect cognitive abilities into a single systematic review and meta-analysis. This comprehensive study indicates that video games may provide some helpful cognitive benefits to gamers.

On the face of it, it might seem like video games fall into the “brain rot” category of entertainment, similar to endless social media scrolling or watching television. Yet most gamers would agree that video games involve at least some degree of skill, and many researchers would agree, too.

In fact, the interactive nature of video games has positioned them as a potential tool for cognitive training, helping to exercise core mental skills like memory, attention, self-control, spatial reasoning and broader problem-solving.

Electrical imbalances at grain boundaries help explain solid-state battery failure

Next-generation batteries that use new electrolyte materials could achieve far higher energy density than today’s lithium-ion batteries, without many of the safety concerns. But advanced batteries, such as those that use solid or almost-solid electrolytes, have been plagued by the formation of tiny spikes of lithium metal called dendrites that cause the batteries to lose efficiency and fail.

Exactly how those dendrites form is still up for debate. While the interface between the battery’s electrolyte and electrodes has been the focus of most research, another culprit is the boundary where two grains of electrolyte in a solid material meet. Researchers know these boundaries can seed dendrites within electrolytes, although the effects have been difficult to study.

Now researchers at MIT and the Technical University of Munich have uncovered why such boundaries can lead to dendrites: Hidden electrical imbalances across the boundaries affect how the electrolyte conducts electrical charges, which influences how the ions and electrons move through the material during battery operation.

Bioinspired strategy creates complex 3D curved structures via programmed shrinkage

The shape of biological structures, ranging from flower petals to the limbs or organs of animals, is often naturally best suited for performing specific functions. Biological structures also often present curved surfaces with specific functional advantages, such as facilitating the drainage of water, increasing a structure’s strength or aerodynamic efficiency, or supporting heavy loads.

Researchers at Kyoto University recently developed a new method to create three-dimensional (3D) structures with curved surfaces, drawing inspiration from the process through which biological structures grow and acquire specific shapes. Using their proposed fabrication strategy, introduced in a paper published in Journal of the Royal Society Interface, they were able to convert flat sheets into curved structures with various complex shapes.

“The starting point for our study was the idea that the 3D forms of living organisms might be explained by spatial patterns of growth-rate differences,” Kentaro Morikawa, first author of the paper, told Tech Xplore.

Quantum computing: Laser-optical system offers full control over 2,000 trapped Rydberg atoms

Fraunhofer ILT in Aachen has developed a highly complex laser-optical system for a quantum computer currently under construction at the 5th Institute of Physics at the University of Stuttgart. This system enables 2,000 Rydberg atoms to be positioned with submicrometer precision in the computer’s highly compact vacuum chamber. To do this, the system projects an array of 2,000 individually controllable laser beams into the chamber. These beams act as optical tweezers and hold the trapped Rydberg atoms precisely at the distance required for them to interact with each other. The computer’s quantum logic processes are based on these interactions.

The task was formidable: to develop a system capable of controlling 2,000 trapped strontium atoms using optical tweezers and positioning them with an accuracy of less than 100 nanometers (nm) within the vacuum chamber of a Rydberg quantum computer. The vacuum chamber is the computer’s processing unit, where two adjacent atoms are brought into a state through laser excitation in which they interact with one another. These interactions can be controlled and measured. Scientists refer to them as two-qubit logic gates; they are the building blocks of quantum logic in a Rydberg quantum computer.

Rydberg atoms are particularly well suited for quantum computing. In their laser-excited state, they are more than one micrometer (µm) in size because, as a result of the excitation, their outermost electron briefly moves to an orbital far from the atomic nucleus, where it nevertheless remains bound. However, due to the weak binding of the outer electron, the atoms are highly sensitive to electric fields, which can also originate from neighboring atoms. Scientists are leveraging this property for the highly precise electromagnetic control of quantum operations.

Detecting neutron sources by borrowing inference tools from cosmology

Neutron sources can be directly identified from measured spectra rather than proxies using inference tools adapted from cosmology, according to a University of Michigan Engineering study published in Physical Review Applied. The method can improve nuclear security by helping intercept materials at ports or borders or guide first responders during emergency response.

Directly detecting and characterizing a neutron source remains a challenge because most nuclear materials emit neutrons with energy patterns, called neutron spectra, that look similar to one another—whether from a benign industrial isotope or fissile material.

“This problem sits at the intersection of fundamental physics, statistics and real-world nuclear security. There is a very practical need to identify unknown neutron-emitting materials, but there is also a deep scientific challenge: How do you extract reliable information from signals that are weak, noisy and highly similar?” said David Breitenmoser, a postdoctoral research fellow of nuclear engineering and radiological sciences at U-M and lead author of the study.

Earth’s deepest rocks help define upper limit for viscosity beyond which materials effectively become rigid

Viscosity is one of the most fundamental physical properties used to describe how materials flow. It governs the movement of liquids, molten rocks and even slowly deforming regions deep inside the Earth. While scientists have long studied materials with low or moderate viscosities, a simple but important question has remained largely unexplored: Is there a physically meaningful upper limit to viscosity?

Extremely high-viscosity materials are usually composed of rock-forming minerals, which are rarely discussed within the traditional framework of fluid dynamics, leaving this question largely unanswered.

To address this question, a study by Professor Masaki Yoshida from the Department of Physical Sciences, College of Science and Engineering, Ritsumeikan University, Japan, investigated whether the Earth’s interior could provide a natural constraint on the highest physically meaningful viscosity over finite timescales.

Controlling magnetic chirality could help memory pack in more data

Magnetic storage devices, like a computer’s hard disk drive, utilize magnets to represent binary data. However, as these devices are downsized, stray magnetic fields generated by individual magnetic components can interact with neighboring elements to cause operational malfunctions, limiting how much data we can densely pack into memory devices.

A joint research team led by Hidetoshi Masuda and Yoshinori Onose from Tohoku University’s Institute for Materials Research—in collaboration with CROSS, J-PARC, Keio University, and Kyoto University—has successfully demonstrated precise, deterministic control over the spiral-handedness (magnetic chirality) in a metallic helimagnet, a material that inherently avoids malfunction-causing crosstalk. Details of their findings were published in the Proceedings of the National Academy of Sciences on June 16, 2026.

A helimagnet features microscopic atomic magnets arranged in a twisted, spiral pattern. Utilizing its chirality (right-or left-handed mirror images) to represent binary data (“0” and “1”) could enable ultra-high-density storage. While some experiments suggested that this chirality could be controlled by simultaneously applying an electric current and a magnetic field, previous confirmations relied on indirect, macroscopic electrical measurements highly susceptible to experimental artifacts.

/* */