Researchers at University of Limerick in Ireland have developed a new method of growing organic crystals that can be used for energy-harvesting applications.

The energy that is being harvested as part of this research is being generated by squeezing amino acid molecules, the building blocks of proteins that exist in the human body.

Piezoelectricity, which translates from Greek to mean pressing electricity, usually found in ceramics or polymers, is also present in human biomolecules.

The research team from the Actuate Lab in the Department of Chemical Sciences and Bernal Institute at UL has previously utilized predictive computer models that allow them to identify how much electricity a biological material will generate when you squeeze it—maki...

Astronomers at the University of Toronto (U of T) have discovered the first pairs of white dwarf and main sequence stars—”dead” remnants and “living” stars—in young star clusters. Described in a new study published in The Astrophysical Journal, this breakthrough offers new insights into an extreme phase of stellar evolution, and one of the biggest mysteries in astrophysics.

Scientists can now begin to bridge the gap between the earliest and final stages of binary star systems—two stars that orbit a shared center of g...

A research team from the Nagoya University Graduate School of Medicine has discovered a promising way to slow the progression of heart failure in mice. They fed mice a diet rich in the soybean protein, β-conglycinin (β-CG), which can support heart health by influencing gut bacteria. Their analysis revealed that the soybean protein rich diet increased the production of the short-chain fatty acids (SCFAs) in the intestine that play a role in protecting the heart. Their findings were published in Clinical Nutrition.

Many people with heart problems try to eat a nutritious diet to reduce their risk of disease. As part of a healthy diet, soybeans have long been recognized for their antioxidant and anti-inflammatory properties...

Large language models (LLMs) are increasingly automating tasks like translation, text classification and customer service. But tapping into an LLM’s power typically requires users to send their requests to a centralized server—a process that’s expensive, energy-intensive and often slow.

Now, researchers have introduced a technique for compressing an LLM’s reams of data, which could increase privacy, save energy and lower costs. Their findings are published on the arXiv preprint server.

The new algorithm, developed by engineers at Princeton and Stanford Engineering, works by trimming redundancies and reducing the precision of an LLM’s layers of information...