Lifeboat Foundation: Safeguarding Humanity
Toggle light / dark theme

Blog – Page 5,179

Astronomers report the detection of a new brown dwarf as part of the Ophiuchus Disk Survey Employing ALMA (ODISEA) program. The newfound object, designated SSTc2d J163134.1–24006, appears to be experiencing a quasi-spherical mass loss. The discovery was detailed in a paper published September 2 on the arXiv pre-print repository.

Brown dwarfs are intermediate objects between planets and stars, occupying the mass range between 13 and 80 Jupiter masses (0.012 and 0.076 ). They can burn deuterium but are unable to burn regular hydrogen, which requires a minimum mass of at least 80 Jupiter masses and a core temperature of about 3 million K.

A team of led by Dary Ruiz-Rodriguez of the National Radio Astronomy Observatory (NRAO) in Charlottesville, Virginia, have investigated SSTc2d J163134.1–24006, initially identified as a faint stellar object, under the ODISEA project, which is dedicated to study the entire population of protoplanetary disks in the Ophiuchus Molecular Cloud. They found that SSTc2d J163134.1–24006 is most likely a brown dwarf with a mass of about 0.05 solar masses, and an elliptical shell of carbon monoxide (CO).

Read more | >

An alzheimer’s-proof brain: a groundbreaking case.

In a groundbreaking case researchers from the Massachusetts General Hospital have discovered a gene variant that seems to have disrupted the pathology of Tau Protein. The case of Aliria Rosa Piedrahita de Villegas.

Abstract: Distinct tau neuropathology and cellular profiles of an APOE3 Christchurch homozygote protected against autosomal dominant Alzheimer’s dementia.

https://link.springer.com/article/10.1007/s00401-022-02467-8

Nature’s Lab Teaches Alzheimer’s Prevention:

Continue reading “Groundbreaking Alzheimer’s Case: Gene APOE3” | >

Or so goes the theory. Most CIM chips running AI algorithms have solely focused on chip design, showcasing their capabilities using simulations of the chip rather than running tasks on full-fledged hardware. The chips also struggle to adjust to multiple different AI tasks—image recognition, voice perception—limiting their integration into smartphones or other everyday devices.

This month, a study in Nature upgraded CIM from the ground up. Rather than focusing solely on the chip’s design, the international team—led by neuromorphic hardware experts Dr. H.S. Philip Wong at Stanford and Dr. Gert Cauwenberghs at UC San Diego—optimized the entire setup, from technology to architecture to algorithms that calibrate the hardware.

The resulting NeuRRAM chip is a powerful neuromorphic computing behemoth with 48 parallel cores and 3 million memory cells. Extremely versatile, the chip tackled multiple AI standard tasks—such as reading hand-written numbers, identifying cars and other objects in images, and decoding voice recordings—with over 84 percent accuracy.

Read more | >

Strange diamonds from an ancient dwarf planet in our solar system may have formed shortly after the dwarf planet collided with a large asteroid about 4.5 billion years ago, according to scientists.

The research team says they have confirmed the existence of lonsdaleite, a rare hexagonal form of diamond, in ureilite meteorites from the mantle of the dwarf planet.

Lonsdaleite is named after the famous British pioneering female crystallographer Dame Kathleen Lonsdale, who was the first woman elected as a Fellow to the Royal Society.

Read more | >

A study co-led by physicists at UC Riverside and UC Irvine has found that dark matter halos of ultra-diffuse galaxies are very odd, raising questions about physicists’ understanding of galaxy formation and the structure of the universe.

Ultra-diffuse galaxies are so called because of their extremely low luminosity. The distribution of baryons—gas and stars—is much more spread out in ultra-diffuse galaxies compared to “normal” galaxies with similar masses.

In the following Q&A, Hai-Bo Yu, an associate professor of physics and astronomy at UCRhis thoughts on the findings he and UCI’s Manoj Kaplinghat, his long-term collaborator, have published in The Astrophysical Journal about newly discovered ultra-diffuse galaxies and their halos.

Read more | >

Not everything needs to be seen to be believed; certain things are more readily heard, like a train approaching its station. In a recent paper, published in Physical Review Letters, researchers have put their ears to the rail, discovering a new property of scattering amplitudes based on their study of sound waves through solid matter.

Be it light or sound, physicists consider the likelihood of particle interactions (yes, sound can behave like a particle) in terms of probability curves or scattering amplitudes. It is common lore that when the momentum or energy of one of the scattered particles goes to zero, scattering amplitudes should always scale with integer powers of momentum (i.e., p1, p2, p3, etc.). What the research team found however, was that the can be proportional to a fractional power (i.e., p1/2, p1/3, p1/4, etc.).

Why does this matter? While quantum field theories, such as the Standard Model, allow researchers to make predictions about particle interactions with extreme accuracy, it is still possible to improve upon current foundations of fundamental physics. When a new behavior is demonstrated—such as fractional-power scaling—scientists are given an opportunity to revisit or revise existing theories.

Read more | >

A new device has been fabricated that can demonstrate the quantum anomalous Hall effect, in which tiny, discrete voltage steps are generated by an external magnetic field. This work may enable extremely low-power electronics, as well as future quantum computers.

If you take an ordinary wire with running through it, you can create a new electrical voltage perpendicular to the flow of current by applying an . This so-called Hall effect has been used as part of a simple magnetic sensor, but the sensitivity can be low.

There is a corresponding quantum version, called the quantum anomalous Hall effect that comes in defined increments, or quanta. This has raised the possibility of using the quantum anomalous Hall effect for the purpose of constructing new highly conductive wires or even quantum computers. However, the physics that leads to this phenomenon is still not completely understood.

Read more | >

A matter-wave interferometer can probe the magnetism of a broad range of species, from single atoms to very large, weakly magnetic molecules.

This year marks the centenary of the ground-breaking experiment of Otto Stern and Walther Gerlach that demonstrated the quantization of the spin angular momentum of an atom [1]. The evidence came from the observation that a beam of silver atoms, upon traversing a spatially varying magnetic field, split into two beams. The spatial splitting of the spin-up and spin-down atoms corresponded to an atomic magnetic moment of 1 Bohr magneton—the magnetic moment of a single spinning electron. The deflection of particle beams in a spatially varying magnetic field remains the basis of techniques for characterizing the magnetic properties of isolated atoms and molecules. Such techniques, however, aren’t sufficiently sensitive to study very large, weakly magnetic molecules, including many biological molecules.

Read more | >

Understanding how the brain organizes and accesses spatial information — where we are, what’s around the corner, how to get there — remains an exquisite challenge. The process involves recalling an entire network of memories and stored spatial data from tens of billions of neurons, each connected to thousands of others. Neuroscientists have identified key elements such as grid cells, neurons that map locations. But going deeper will prove tricky: It’s not as though researchers can remove and study slices of human gray matter to watch how location-based memories of images, sounds and smells flow through and connect to each other.

Artificial intelligence offers another way in. For years, neuroscientists have harnessed many types of neural networks — the engines that power most deep learning applications — to model the firing of neurons in the brain. In recent work, researchers have shown that the hippocampus, a structure of the brain critical to memory, is basically a special kind of neural net, known as a transformer, in disguise. Their new model tracks spatial information in a way that parallels the inner workings of the brain. They’ve seen remarkable success.

“The fact that we know these models of the brain are equivalent to the transformer means that our models perform much better and are easier to train,” said James Whittington, a cognitive neuroscientist who splits his time between Stanford University and the lab of Tim Behrens at the University of Oxford.

Read more | >