Lifeboat Foundation: Safeguarding Humanity
Toggle light / dark theme

Blog – Page 3

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

Log in for authorized contributors

AI-generated nanomaterial images fool even experts, study shows

Black-and-white images of pom-pom–like clusters, semi-translucent fields of tiny dark gray stars on a pale background, and countless other abstract patterns are a familiar sight in scientific papers describing the shapes and properties of newly engineered materials.

So, when research images show particles that resemble puffed popcorn or perfectly smooth “Tic Tacs,” it might not trigger our AI suspicion radar, but researchers in a recent study caution otherwise.

Microscopy images are indispensable in nanomaterials science, as they reveal the hidden intricacies and fascinating shapes that tiny particles assume, which appear to be a pile of dust to the naked eye.

Genetic and behavioral links found between musical rhythm perception and developmental language disorders

In a paper published in Nature Communications, researchers at Vanderbilt University Medical Center’s Department of Otolaryngology–Head and Neck Surgery leveraged two main studies—one focused on behavior and one focused on genetics—to highlight the correlation between participants’ musical rhythm abilities and developmental speech-language disorders.

These disorders include , dyslexia and stuttering, among others.

Evidence showed that deficiency in musical perception is a “modest but consistent risk factor for developmental speech, language and reading disorders,” according to the study’s lead author, Srishti Nayak, Ph.D., assistant professor of Otolaryngology-Head and Neck Surgery.

Could dark energy change over time? Supercomputer simulations challenge ΛCDM assumption

Since the early 20th century, scientists have gathered compelling evidence that the universe is expanding at an accelerating rate. This acceleration is attributed to what is known as dark energy—a fundamental property of spacetime that has a repulsive effect on galaxies.

For decades, the leading cosmological model, known as the Lambda Cold Dark Matter (ΛCDM), has assumed that is a constant entity, unchanging throughout cosmic time. While this simple assumption has served as the bedrock of modern cosmology, it has left a fundamental question unanswered: what if dark energy is not constant, but instead a time-varying property of the universe?

Recent observations have provided some of the first hints that the above-mentioned assumption may not be correct. The Dark Energy Spectroscopic Instrument (DESI), a sophisticated experiment for conducting astronomical surveys of distant galaxies, has produced data suggesting a preference for a dynamic dark energy (DDE) component.

Early intake of the antidepressant fluoxetine alters brain development in rats, study finds

Past neuroscience studies have consistently showed the profound effects of early life experiences on the brain’s wiring, particularly on the formation of the junctions that enable communication between neurons (i.e., synapses). The influence of early life experiences was found to be particularly pronounced during so-called sensitive periods (SPs), windows of time during which the brain’s plasticity (i.e., its ability to form or reorganize neural connections) is heightened.

Experimental evidence suggests that these periods of heightened brain plasticity are regulated by specialized neurons that release the inhibitory neurotransmitter GABA (gamma-aminobutyric acid). So-called parvalbumin-positive (PV+) interneurons have been found to play a central role in the unfolding of SPs, as their gradual enclosure into protective structures was linked to the conclusion of these periods.

Researchers at University of Milan and University of Helsinki recently carried out a study exploring the effects of early exposure to the widely prescribed antidepressant fluoxetine (FLX) on the regulation of SPs in rats. Their findings, published in Molecular Psychiatry, suggest that exposure to fluoxetine during gestation, pregnancy or breastfeeding could influence the and behavior of rat pups later in life.

Floquet Chern insulators based on nonlinear photonic crystals achieved

Over the past few years, engineers and material scientists have been trying to devise new optical systems in which light particles (i.e., photons) can move freely and in useful ways, irrespective of defects and imperfections. Topological phases, unique states of matter that are not defined by local properties, but by non-local and global features, can enable the robust movement of photons despite material defects.

Researchers at the University of Pennsylvania and University of California-Santa Barbara recently demonstrated the realization of Floquet Chern insulators, materials in which the periodic application of an oscillating light field or other external fields give rise to a unique topological phase, in a nonlinear photonic system. The insulators presented in their paper, which was published in Nature Nanotechnology, are based on nonlinear photonic crystals, materials with repeating patterns that can control the and respond differently to light of different intensities.

“Topological photonics explores photonic systems that exhibit robustness against defects and disorder, enabled by protection from underlying ,” wrote Jicheng Jin, Li He and their colleagues in their paper. “These phases are typically realized in linear optical systems and characterized by their intrinsic photonic band structures. We experimentally study Floquet Chern insulators in periodically driven nonlinear photonic crystals, where the topological phase is controlled by the polarization and the frequency of the driving field.”

Mapping RNA-protein ‘chats’ could uncover new treatments for cancer and brain disease

Bioengineers at the University of California San Diego have developed a powerful new technology that can map the entire network of RNA-protein interactions inside human cells—an achievement that could offer new strategies for treating diseases ranging from cancer to Alzheimer’s.

RNA-protein interactions regulate many essential processes in cells, from turning genes on and off to responding to stress. But until now, scientists could only capture small subsets of these interactions, leaving much of the cellular “conversation” hidden.

“This technology is like a wiring map of the cell’s conversations,” said Sheng Zhong, professor in the Shu Chien-Gene Lay Department of Bioengineering at the UC San Diego Jacobs School of Engineering, who led the study published in Nature Biotechnology.

Silver-nanoring coating points to ‘self-regulating’ smart windows—without power or tinting

A new Danish research breakthrough could make buildings far more energy-efficient in the future. Researchers from Aarhus University’s Interdisciplinary Nanoscience Center (iNANO) have developed a light-responsive hybrid material based on so-called silver nanorings that automatically responds to solar intensity and regulates how much heat penetrates through windows.

The microscopic silver rings increasingly block near-infrared light as sunlight becomes stronger—without making the glass less transparent.

The technology functions without the use of power, sensors, or electronics—and could potentially be applied as a window coating in, for example, and modern residential buildings where large glass areas are common and heat radiation from the sun can be a challenge. This makes the solution particularly relevant at a time when for cooling exceeds the need for heating in large parts of the world.

Designing random nanofiber networks, optimized for strength and toughness

In nature, random fiber networks such as some of the tissues in the human body, are strong and tough with the ability to hold together but also stretch a lot before they fail. Studying this structural randomness—that nature seems to replicate so effortlessly—is extremely difficult in the lab and is even more difficult to accurately reproduce in engineering applications.

Recently, researchers at The Grainger College of Engineering, University of Illinois Urbana-Champaign and the Rensselaer Polytechnic Institute devised a method to repeatedly print random polymer nanofiber networks with desired characteristics and use to tune the random network characteristics for improved strength and toughness.

“This is a big leap in understanding how nanofiber networks behave,” said Ioannis Chasiotis, a professor in the Department of Aerospace Engineering. “Now, for the first time, we can reproduce randomness with desirable underlying structural parameters in the lab, and with the companion computer model, we can optimize the to find the network parameters, such as nanofiber density, that produce simultaneously higher network strength, stiffness and toughness.”

Molecular qubits can communicate at telecom frequencies

A team of scientists from the University of Chicago, the University of California Berkeley, Argonne National Laboratory, and Lawrence Berkeley National Laboratory has developed molecular qubits that bridge the gap between light and magnetism—and operate at the same frequencies as telecommunications technology. The advance, published today in Science, establishes a promising new building block for scalable quantum technologies that can integrate seamlessly with existing fiber-optic networks.

Because the new molecular qubits can interact at telecom-band frequencies, the work points toward future quantum networks—sometimes called the “.” Such networks could enable ultra-secure communication channels, connect quantum computers across long distances, and distribute quantum sensors with unprecedented precision.

Molecular qubits could also serve as highly sensitive quantum sensors; their tiny size and chemical flexibility mean they could be embedded in unusual environments—such as —to measure magnetic fields, temperature, or pressure at the nanoscale. And because they are compatible with silicon photonics, these molecules could be integrated directly into chips, paving the way for compact quantum devices that could be used for computing, communication, or sensing.

AI techniques excel at solving complex equations in physics, especially inverse problems

Differential equations are fundamental tools in physics: they are used to describe phenomena ranging from fluid dynamics to general relativity. But when these equations become stiff (i.e. they involve very different scales or highly sensitive parameters), they become extremely difficult to solve. This is especially relevant in inverse problems, where scientists try to deduce unknown physical laws from observed data.

To tackle this challenge, the researchers have enhanced the capabilities of Physics-Informed Neural Networks (PINNs), a type of artificial intelligence that incorporates physical laws into its .

Their approach, reported in Communications Physics, combines two innovative techniques: Multi-Head (MH) training, which allows the neural network to learn a general space of solutions for a family of equations—rather than just one specific case—and Unimodular Regularization (UR), inspired by concepts from differential geometry and , which stabilizes the learning process and improves the network’s ability to generalize to new, more difficult problems.

/* */