Lifeboat Foundation

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 gravity—to further our understanding of how stars form, how galaxies evolve, and how most elements on the periodic table were created. This discovery could also help explain cosmic events like supernova explosions and gravitational waves, since binaries containing one or more of these compact dead stars are thought to be the origin of such phenomena.

Most stars exist in binary systems. In fact, nearly half of all stars similar to our sun have at least one companion star. These paired stars usually differ in size, with one star often being more massive than the other. Though one might be tempted to assume that these stars evolve at the same rate, more massive stars tend to live shorter lives and go through the stages of stellar evolution much faster than their lower mass companions.

Cognitive neuroscientists at Trinity College Dublin have published new research describing a brand new approach to making habit change achievable and lasting.

This innovative framework has the potential to significantly improve approaches to personal development, as well as the clinical treatment of compulsive disorders (for example obsessive compulsive disorder, addiction, and eating disorders).

The research was led by Dr. Eike Buabang, Postdoctoral Research Fellow in the lab of Professor Claire Gillan in the School of Psychology, has been published as a paper titled “Leveraging cognitive neuroscience for making and breaking real-world habits” in the journal Trends in Cognitive Sciences.

Life is a series of small events: making morning coffee, letting the dog out, opening a laptop, letting the dog back in. Add them all up and you have a full day. Our brains are committed to observing and processing the events that make up our daily lives, said Jeff Zacks, the Edgar James Swift Professor in Arts & Sciences and chair of the Department of Psychological & Brain Sciences. “Knowing where events begin and where they end is crucial to understanding the world,” Zacks said.

In a pair of new papers, Zacks and other researchers in Arts & Sciences and the McKelvey School of Engineering explore this key process of human cognition.

Zacks led a study that trained computer models to observe more than 25 hours of video of people performing simple, everyday tasks such as cleaning a kitchen or cooking a meal before making predictions about what happens next. The study came to a surprising conclusion: The computer models were most accurate when they responded to uncertainty. When the model was especially unsure about what would happen next, it would reset and reassess the scene, an approach that improved its overall comprehension.

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.

New research from the University of Kent has demonstrated that quantum information could eventually be used to coordinate the actions of devices that can move, such as drones or autonomous vehicles. This could lead to more efficient logistics, which could make deliveries cheaper, and better use of limited bandwidth for the likes of self-driving cars.

By carrying out “real world” experiments on a quantum computer, the team of quantum physicists (led by Ph.D. student Josh Tucker in the University of Kent’s School of Physics and Astronomy), found that if the two devices share a pair of quantum coins (qubits), the devices can continue to influence each other even after they have been separated and can no longer communicate.

The experiments simulated the phenomenon using real qubits inside a quantum computer developed by IBM. The qubits are made of superconducting material and kept at temperatures colder than the interstellar void. This allows them to behave according to the laws of quantum physics that defy common sense—including the ability to influence each other without coming into contact and without sending signals.

A new study demonstrates that even simple single-cell organisms, such as ciliates and amoebae, exhibit habituation, a basic form of learning previously thought to be exclusive to more complex beings.

This revelation not only changes our understanding of cellular capabilities but also opens up possibilities for applications in cancer immunology, suggesting that our immune cells might be reprogrammed to better recognize and attack cancer cells.

A dog learns to sit on command. A person tunes out the steady hum of a washing machine while engrossed in a book. The ability to learn and adapt is a cornerstone of evolution and survival.

Scientists have developed a novel technique using high-energy particle collisions at the Relativistic Heavy Ion Collider (RHIC), a U.S. Department of Energy (DOE) Office of Science user facility for nuclear physics research located at DOE’s Brookhaven National Laboratory. Detailed in a newly published paper in Nature, this method complements lower-energy approaches for studying nuclear structure. It offers deeper insights into the shapes of atomic nuclei, enhancing our understanding of the building blocks of visible matter.

“In this new measurement, we not only quantify the overall shape of the nucleus — whether it’s elongated like a football or squashed down like a tangerine — but also the subtle triaxiality, the relative differences among its three principle axes that characterize a shape in between the ‘football’ and ‘tangerine,’” said Jiangyong Jia, a professor at Stony Brook University (SBU) who has a joint appointment at Brookhaven Lab and is one of the principal authors on the STAR Collaboration publication.

Deciphering nuclear shapes has relevance to a wide range of physics questions, including which atoms are most likely to split in nuclear fission, how heavy atomic elements form in collisions of neutron stars, and which nuclei could point the way to exotic particle decay discoveries. Leveraging improved knowledge of nuclear shapes will also deepen scientists’ understanding of the initial conditions of a particle soup that mimics the early universe, which is created in RHIC’s energetic particle smashups. The method can be applied to analyzing additional data from RHIC as well as data collected from nuclear collisions at Europe’s Large Hadron Collider (LHC). It will also have relevance to future explorations of nuclei at the Electron-Ion Collider, a nuclear physics facility in the design stage at Brookhaven Lab.

Researchers have linked the origins of fast radio bursts to magnetars, highly magnetized neutron stars, which often arise from the mergers of massive stars in star-forming galaxies.

By utilizing the Deep Synoptic Array-110, they’ve localized 70 FRBs, discovering that these bursts are more frequent in massive, metal-rich galaxies. This suggests that the environmental conditions conducive to FRB occurrence are also ideal for magnetar formation.

Unveiling the mystery of fast radio bursts.

Amid heated debates about the potential pitfills of artificial intelligence, the technology has finally taken a form we can probably all get behind — an “AI granny” created expressly to waste scammers’ time.

British telecom company Virgin Media O₂ on Thursday introduced Daisy, a custom-made human-like chabot that answers calls in real time, keeping fraudsters on the phone as long as possible in a bid to annoy and frustrate them, just as they do to consumers worldwide. Daisy (that’s “dAIsy”) automates the practice of “scambaiting,” which involves people posing as potential victims to squander scammers’ time and resources, publicly expose their wily ways, gather information useful to law enforcement and even confuse the con artists’ devices.

Daisy, newly dubbed O2’s “head of scammer relations,” impersonates an older adult, making her part of a demographic that’s particularly vulnerable to scams. Unlike human scambaiters who need to sleep and shower once in a while, Daisy can spend all day and night on the phone with swindlers. “While they’re busy talking to me they can’t be scamming you, and let’s face it, dear, I’ve got all the time in the world,” Daisy says in the introductory video from O₂ embedded below. The video personifies her as a photorealistic AI-generated woman with gray hair, glasses and pearls talking on a pink landline.