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Materials Genomics: Using supercomputers in the hunt for novel alloys and compounds

Materials Genomics: Using supercomputers in the hunt for novel alloys and compounds | Amazing Science | Scoop.it

In a new study, researchers from Duke University’s Pratt School of Engineering used computational methods to identify dozens of platinum-group alloys that were previously unknown to science but could prove beneficial in a wide range of applications.


Platinum is expensive, but it’s used to transform toxic fumes leaving a car’s engine into more benign gasses, to produce high octane gasoline, plastics and synthetic rubbers, and to fight the spread of cancerous tumors.


“We’re looking at the properties of ‘expensium’ and trying to develop ‘cheapium,’” said Stefano Curtarolo, director of Duke’s Center for Materials Genomics. “We’re trying to automate the discovery of new materials and use our system to go further faster.”


The research is part of the Materials Genome Initiative launched by President Barack Obama in 2011. The initiative’s goal is to support centers, groups and researchers in accelerating the pace of discovery and deployment of advanced material systems crucial to achieving global competitiveness in the 21st century.


The identification of the new platinum-group compounds hinges on databases and algorithms that Curtarolo and his group have spent years developing. Using theories about how atoms interact to model chemical structures from the ground up, Curtarolo and his group screened thousands of potential materials for high probabilities of stability.


After nearly 40,000 calculations, the results identified 37 new binary alloys in the platinum-group metals, which include osmium, iridium ruthenium, rhodium, platinum and palladium.


These metals are prized for their catalytic properties, resistance to chemical corrosion and performance in high-temperature environments, among other properties. Commercial applications for the group include electrical components, corrosion-resistance apparatus, fuel cells, chemotherapy and dentistry. And because of their worldwide scarcity, each metal fetches a premium price.


Now it is up to experimentalists to produce these new materials and discover their physical properties. In addition to identifying unknown alloys, the study also provides detailed structural data on known materials. For example, there are indications that some may be structurally unstable at low temperatures. This isn’t readily apparent because creating such materials is difficult, requiring high temperatures or pressures and very long equilibration processes.


“We hope providing a list of targets will help identify new compounds much faster and more cheaply,” said Curtarolo. “Physically going through these potential combinations just to find the targets would take 200 to 300 graduate students five years. As it is, characterizing the targets we identified should keep the experimentalists busy for 20.” 

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Unlimited, at-home coronavirus testing for your organization

Unlimited, at-home coronavirus testing for your organization | Amazing Science | Scoop.it

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Plastic nurdles are infiltrating our environment and polluting it for hundreds if not thousands of years

Plastic nurdles are infiltrating our environment and polluting it for hundreds if not thousands of years | Amazing Science | Scoop.it

A nurdle is a bead of pure plastic. It is the basic building block of almost all plastic products, like some sort of synthetic ore; their creators call them “pre-production plastic pellets” or “resins.” Every year, trillions of nurdles are produced from natural gas or oil, shipped to factories around the world, and then melted and poured into molds that churn out water bottles and sewage pipes and steering wheels and the millions of other plastic products we use every day. You are almost certainly reading this story on a device that is part nurdle. Most nurdles, being less than 5 millimeters in size, are a form of microplastic from the moment of its creation, something also known as a primary microplastic.

 

Not all nurdles make their way safely to the end of a production line. An estimated 200,000 metric tons of nurdles make their way into oceans annually. The beads are extremely light, around 20 milligrams each. That means, under current conditions, approximately 10 trillion nurdles are projected to infiltrate marine ecosystems around the world each year. Hundreds of fish species — including some eaten by humans — and at least 80 kinds of seabirds eat plastics. Researchers are concerned that animals that eat nurdles risk blocking their digestive tracts and starving to death. Just as concerning is what happens to the beads in the long term: Like most plastics, they do not biodegrade, but they do deteriorate over time, forming the second-largest source of ocean microplastics after tire dust.

 

There’s much we still don’t know about how plastics can harm the bodies of humans and animals alike, but recent research has shown that microplastics can be found in the blood of as much as 80 percent of all adult humans, where they can potentially harm our cells. We may not eat the plastic beads ourselves, but nurdles seem to have a way of finding their way back to us.

 

In most of the United States, the federal and local government respond to nurdle spills big and small in the same way: by doing practically nothing. Nurdles are not classified as pollutants or hazardous materials, so the Coast Guard, which usually handles cleanups of oil or other toxic substances that enter waterways, bears no responsibility for them.

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Unreal Engine 5 - Ultra-realistic video world creation

Neil deGrasse Tyson once said that we are either living in a simulation or on the verge of creating a simulation that others will live in. Imagine we become the agents of that VR into a world like that and interact with AI who might one day realize they aren't real and try to escape into our world.

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Machine-learning model can distinguish antibody targets

Machine-learning model can distinguish antibody targets | Amazing Science | Scoop.it

A new study shows that it is possible to use the genetic sequences of a person's antibodies to predict what pathogens those antibodies will target. Reported in the journal Immunity, the new approach successfully differentiates between antibodies against influenza and those attacking SARS-CoV-2, the virus that causes COVID-19.

 

"Our research is in a very early stage, but this proof-of-concept study shows that we can use machine learning to connect the sequence of an antibody to its function," said Nicholas Wu, a professor of biochemistry at the University of Illinois Urbana-Champaign who led the research with U. of I. biochemistry Ph.D. student Yiquan Wang; and Meng Yuan, a staff scientist at Scripps Research in La Jolla, California.

 

With enough data, scientists should be able to predict not only the virus an antibody will attack, but which features on the pathogen the antibody binds to, Wu said. For example, an antibody may attach to different parts of the spike protein on the SARS-CoV-2 virus. Knowing this will allow scientists to predict the strength of a person's immune defense, as some targets of a pathogen are more vulnerable than others.

 

The new approach was made possible by the abundance of data related to antibodies against SARS-CoV-2, Wu said. "In 20 years, scientists have discovered about 5,000 antibodies against the flu virus," he said. "But in just two years, people have identified 8,000 antibodies for COVID. This provides an opportunity that's never been seen before to study how antibodies work and to do this kind of prediction."

 

The researchers used antibody data from 88 published studies and 13 patents. The datasets were big enough to allow the researchers to train their model to make predictions based on the antibodies' genetic sequence. The model was designed to distinguish whether the sequences coded for antibodies targeting regions on the influenza virus or on the SARS-CoV-2 virus. The researchers then checked the accuracy of those predictions.

 

"The accuracy was close to 85% overall," Wang said. "I was actually quite surprised that it worked so well," Wu said. The team is working to improve its model so that it can more precisely determine which parts of the virus the antibodies attack. "If we can make these predictions based on antibody sequence, we might also be able to go back and design antibodies that bind to specific pathogens," Wu said. "This is not something that we can do now, but those are some implications for future study."

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Stanford scientist models landscape formation on Titan, revealing an Earth-like alien world

Stanford scientist models landscape formation on Titan, revealing an Earth-like alien world | Amazing Science | Scoop.it

Saturn’s moon Titan looks very much like Earth from space, with rivers, lakes, and seas filled by rain tumbling through a thick atmosphere. While these landscapes may look familiar, they are composed of materials that are undoubtedly different – liquid methane streams streak Titan’s icy surface and nitrogen winds build hydrocarbon sand dunes.

 

The presence of these materials – whose mechanical properties are vastly different from those of silicate-based substances that make up other known sedimentary bodies in our solar system – makes Titan’s landscape formation enigmatic. By identifying a process that would allow for hydrocarbon-based substances to form sand grains or bedrock depending on how often winds blow and streams flow, Stanford University geologist Mathieu Lapôtre and his colleagues have shown how Titan’s distinct dunes, plains, and labyrinth terrains could be formed.

 

Titan, which is a target for space exploration because of its potential habitability, is the only other body in our solar system known to have an Earth-like, seasonal liquid transport cycle today. The new model, recently published in Geophysical Research Letters, shows how that seasonal cycle drives the movement of grains over the moon’s surface.

 

“Our model adds a unifying framework that allows us to understand how all of these sedimentary environments work together,” said Lapôtre, an assistant professor of geological sciences at Stanford’s School of Earth, Energy & Environmental Sciences (Stanford Earth). “If we understand how the different pieces of the puzzle fit together and their mechanics, then we can start using the landforms left behind by those sedimentary processes to say something about the climate or the geological history of Titan – and how they could impact the prospect for life on Titan.”

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Turning back time – new technique rewinds the age of skin cells by 30 years

Turning back time – new technique rewinds the age of skin cells by 30 years | Amazing Science | Scoop.it

Research from the Babraham Institute has developed a method to ‘time jump’ human skin cells by 30 years, turning back the aging clock for cells without losing their specialized function. Work by researchers in the Institute’s Epigenetics research program has been able to partly restore the function of older cells, as well as rejuvenating the molecular measures of biological age. The research is published in the journal eLife and whilst at an early stage of exploration, it could revolutionize regenerative medicine.

 

How does it work?

As we age, our cells’ ability to function declines and the genome accumulates marks of aging. Regenerative biology aims to repair or replace cells including old ones. One of the most important tools in regenerative biology is our ability to create ‘induced’ stem cells. The process is a result of several steps, each erasing some of the marks that make cells specialized. In theory, these stem cells have the potential to become any cell type, but scientists aren’t yet able to reliably recreate the conditions to re-differentiate stem cells into all cell types.

 

The new method, based on the Nobel Prize winning technique scientists use to generate stem cells, overcomes the problem of entirely erasing cell identity by halting reprogramming part of the way through the whole process. This allowed researchers to find the precise balance between reprogramming cells, making them biologically younger, while still being able to regain their specialized cell function.

 

In 2007, Shinya Yamanaka was the first scientist to turn normal cells, which have a specific function, into stem cells which have the special ability to develop into any cell type. The full process of stem cell reprogramming takes around 50 days using four key molecules called the Yamanaka factors. The new method, called 'maturation phase transient reprogramming’, exposes cells to Yamanaka factors for just 13 days. At this point, age-related changes are removed and the cells have temporarily lost their identity. The partly reprogrammed cells were given time to grow under normal conditions, to observe whether their specific skin cell function returned. Genome analysis showed that cells had regained markers characteristic of skin cells (fibroblasts), and this was confirmed by observing collagen production in the reprogrammed cells.

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Me and my organoid: a step closer to tailored therapy

Me and my organoid: a step closer to tailored therapy | Amazing Science | Scoop.it

This is the story of the revolutionary development of mini-organs (organoids) and their countless applications on how they help us to develop and implement tailored therapy for each patient. A tale for the future of medicine from a group of scientists in Utrecht that started it all - out of wonder.

 

In 2009, Hans Clevers  external link, a stem cell biologist at Utrecht University, made a discovery that would forever transform healthcare. His lab at the Hubrecht Institute  external link had grown what, under the microscope, looked like a real gut outside the body (made from mouse intestinal cells). It was the first in a series of organs-in-a-dish that would revolutionize personalized medicine in every corner of the world. Today, the possibilities of these mini-organs are enormous: from finding the right treatment to otherwise lethal genetic diseases, numerous cancers and infectious diseases, to understanding furtive neurological disorders such as schizophrenia, bipolar disorder or autism without having to poke one’s brain. We also know deaths from organ donor shortages could soon be a thing of the past.

Welcome the organoids: mini-organs that could save your or your family’s life one day…

 

But how do organoids work exactly? What can you do with organoids now, and which doors will they open for patients and healthcare in the future? They may sound like science fiction to you, but organoids are already transforming patients’ reality.

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Wall of Birds - Evolution and Diversity

Wall of Birds - Evolution and Diversity | Amazing Science | Scoop.it
Interact with the epic mural, spanning 243 birds and 375 million years, at the Cornell Lab of Ornithology

Via Guilhes Damian, Dr. Stefan Gruenwald
Guilhes Damian's curator insight, March 16, 2016 10:40 AM

Wall of Birds - evolution and diversity of birds around the world in a beautiful map

Andreas Maniatis's curator insight, March 17, 2016 5:31 AM

An exemplary Interactive Visual Narration about evolution and diversity in the world of the birds

Julien Tesgui's curator insight, March 17, 2016 8:17 PM

An exemplary Interactive Visual Narration about evolution and diversity in the world of the birds

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Blood-brain barrier–penetrating single CRISPR-Cas9 nanocapsules for effective and safe glioblastoma gene therapy

Blood-brain barrier–penetrating single CRISPR-Cas9 nanocapsules for effective and safe glioblastoma gene therapy | Amazing Science | Scoop.it

A team of scientists designed a unique nanocapsule for efficient single CRISPR-Cas9 encapsulation, noninvasive brain delivery and tumor cell targeting, and was able to demonstrate an effective and safe strategy for glioblastoma gene therapy. Their newly developed CRISPR-Cas9 nanocapsules can easily be produced by encapsulating the single Cas9/sgRNA complex within a glutathione-sensitive polymer shell incorporating a dual-action ligand that facilitates BBB penetration, tumor cell targeting, and Cas9/sgRNA selective release. These nanocapsules provide promising glioblastoma tissue targeting that led to high PLK1 gene editing efficiency in a brain tumor (up to 38.1%) with negligible (less than 0.5%) off-target gene editing in high-risk tissues.

 

Treatment with nanocapsules extended the median survival time (68 days versus 24 days) in mice. Thus, this new CRISPR-Cas9 delivery system addresses various delivery challenges to demonstrate safe and tumor-specific delivery of gene editing Cas9 ribonucleoprotein for improved glioblastoma treatment that may potentially be therapeutically useful for several other brain diseases.

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Quantum Computing Algorithm Could Lead to Design of New Materials

Quantum Computing Algorithm Could Lead to Design of New Materials | Amazing Science | Scoop.it

A team of researchers at Columbia University have developed a new algorithm that could help quantum computers calculate molecular energy and lead to the design of new materials. The algorithm uses the most quantum bits to date to calculate ground state energy, which is the lowest-energy state in a quantum mechanical system. 


The new study was published in Nature.


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Hidden Regions Revealed in the First Complete Sequence of a Human Genome

Hidden Regions Revealed in the First Complete Sequence of a Human Genome | Amazing Science | Scoop.it

Parts of the human genome now available to study for the first time are important for understanding genetic diseases, human diversity, and evolution.

The first truly complete sequence of a human genome, covering each chromosome from end to end with no gaps and unprecedented accuracy, is now accessible through the UCSC Genome Browser and is described in six papers published today (March 31, 2022) in Science.

Since the first working draft of a human genome sequence was assembled at UC Santa Cruz in 2000, genomics research has led to enormous advances in our understanding of human biology and disease. Nevertheless, crucial regions accounting for some 8% of the human genome have remained hidden from scientists for over 20 years due to the limitations of DNA sequencing technologies.

Karen Miga, assistant professor of biomolecular engineering at UC Santa Cruz, and Adam Phillippy at the National Human Genome Research Institute (NHGRI) organized an international team of scientists—the Telomere-to-Telomere (T2T) Consortium—to fill in the missing pieces. Their efforts have now paid off.

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Lab creates superfluid circuit using fermions to study electron behavior

Lab creates superfluid circuit using fermions to study electron behavior | Amazing Science | Scoop.it

Researchers at Dartmouth College have built the world's first superfluid circuit that uses pairs of ultracold electron-like atoms, according to a study published in Physical Review Letters. The laboratory test bed gives physicists control over the strength of interactions between atoms, providing a new way to explore the phenomena behind exotic materials such as superconductors.

"Much of modern technology revolves around controlling the flow of electrons around circuits," said Kevin Wright, assistant professor of physics at Dartmouth and senior researcher of the study. "By using electron-like atoms we can test theories in ways that were not possible before."

While conductive materials such as copper are well understood, researchers do not completely understand how electrons move or can be controlled in exotic materials like topological insulators and superconductors that can be useful for building quantum computers.

The new circuit acts as a quantum emulator to explore how electrons work in real materials, offering a way to analyze the movement of electrons in a highly controllable setting.

"Electrons can do things that are far more strange and rich than anyone imagined," said Wright. "We are learning about electrons without using electrons." Atomic particles are either bosons or fermions. Bosons, such as photons, tend to bunch together. Fermions, such as electrons, tend to avoid each other. While superfluid circuits using ultracold boson-like atoms already exist, the Dartmouth circuit is the first to use ultracold atoms that act as fermions.

The circuit operates on the isotope lithium-6. Although lithium-6 is a complete atom, it has properties that make it act like an individual electron. The behavior of the complete atom serves as an analog for individual electrons.

"If we could scale the properties of lithium-6 atoms to electrons, they would be flowing without resistance even above room temperature," said Yanping Cai, the first author of the paper who wrote the paper as a Dartmouth Ph.D. candidate. "Studying these simple circuits might provide insights about high-temperature superconductivity."

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Brain Implant Helps "Locked-In" Paralyzed Man to Communicate Entire Sentences

Brain Implant Helps "Locked-In" Paralyzed Man to Communicate Entire Sentences | Amazing Science | Scoop.it

A completely paralyzed patient can now convey full sentences thanks to electrodes implanted in his brain. Medical research surgically placed brain-computer interfaces (BCIs) into a patient’s brain. The implants tracked electrical activity in the brain and translated the signals to commands to another device.

 

According to a paper published in Nature detailing the procedure, the subject was able to message requests for beer, soup and massages from his nurses. He also asked to watch movies with his son. The participant suffers from Amyotrophic lateral sclerosis, or ALS, and is completely ‘locked-in,’ meaning he can’t use his limbs or make eye movements. In the past, BCIs have helped patients convey ‘yes’ or ‘no’ via thoughts or allowed partially paralyzed patients to move prosthetic limbs.

 

“It’s really remarkable to be able to reestablish communication with someone in a completely locked-in state. To me, that’s a tremendous breakthrough and obviously quite meaningful for the research participant,” said Jaimie Henderson, M.D., a Stanford University neurosurgeon who wasn’t involved in the project.

 

The individual received the innovative treatment through ALS Voice GmbH. A nonprofit that works with noncommunicative participants to incorporate BCIs and other technologies to improve their quality of life. The patient responded well to neurofeedback, which shows brain activity in real time so a patient can control their responses. When brain electrical activity alters, a computer would respond with ascending or descending tones.

 

“Within two days, [the patient] was able to increase and decrease the frequency of a sound tone,” said Ujwal Chaudhary of ALS Voice gGmbH. His team developed software based on a computer system the patient’s family created. One of the patient’s first sentences was, “boys, it works so effortlessly.”

 

In the future, Chaudhary wants to develop software with a word list that has an autocomplete function in the software. “There are many ways in which we could make it faster,” he said.

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Footage of hypersonic metallic UFO revealed by Pentagon officials at historic hearing

Footage of hypersonic metallic UFO revealed by Pentagon officials at historic hearing | Amazing Science | Scoop.it
Pentagon officials speaking at the first public hearing on UFOs since the 1960s have shown previously classified footage of an unidentified aerial phenomenon (UAP).

 

The first well-known UFO sighting occurred in 1947, when businessman Kenneth Arnold claimed to see a group of nine high-speed objects near Mount Rainier in Washington while flying his small plane. Arnold estimated the speed of the crescent-shaped objects as several thousand miles per hour and said they moved “like saucers skipping on water.” In the newspaper report that followed, it was mistakenly stated that the objects were saucer-shaped, hence the term flying saucer.

 

Sightings of unidentified aerial phenomena increased, and in 1948 the U.S. Air Force began an investigation of these reports called Project Sign. The initial opinion of those involved with the project was that the UFOs were most likely sophisticated Soviet aircraft, although some researchers suggested that they might be spacecraft from other worlds, the so-called extraterrestrial hypothesis (ETH). Within a year, Project Sign was succeeded by Project Grudge, which in 1952 was itself replaced by the longest-lived of the official inquiries into UFOs, Project Blue Book, headquartered at Wright-Patterson Air Force Base in DaytonOhio.

 

From 1952 to 1969 Project Blue Book compiled reports of more than 12,000 sightings or events, each of which was ultimately classified as (1) “identified” with a known astronomical, atmospheric, or artificial (human-caused) phenomenon or (2) “unidentified.” The latter category, approximately 6 percent of the total, included cases for which there was insufficient information to make an identification with a known phenomenon.

 

An American obsession with the UFO phenomenon was under way. In the hot summer of 1952 a provocative series of radar and visual sightings occurred near National Airport in Washington, D.C. Although these events were attributed to temperature inversions in the air over the city, not everyone was convinced by this explanation. Meanwhile, the number of UFO reports had climbed to a record high. This led the Central Intelligence Agency to prompt the U.S. government to establish an expert panel of scientists to investigate the phenomena. The panel was headed by H.P. Robertson, a physicist at the California Institute of Technology in PasadenaCalifornia, and included other physicists, an astronomer, and a rocket engineer. The Robertson Panel met for three days in 1953 and interviewed military officers and the head of Project Blue Book. They also reviewed films and photographs of UFOs. Their conclusions were that (1) 90 percent of the sightings could be easily attributed to astronomical and meteorologic phenomena (e.g., bright planets and starsmeteorsauroras, ion clouds) or to such earthly objects as aircraft, balloons, birds, and searchlights, (2) there was no obvious security threat, and (3) there was no evidence to support the ETH. Parts of the panel’s report were kept classified until 1979, and this long period of secrecy helped fuel suspicions of a government cover-up.

 

A second committee was set up in 1966 at the request of the Air Force to review the most interesting material gathered by Project Blue Book. Two years later this committee, which made a detailed study of 59 UFO sightings, released its results as Scientific Study of Unidentified Flying Objects—also known as the Condon Report, named for Edward U. Condon, the physicist who headed the investigation. The Condon Report was reviewed by a special committee of the National Academy of Sciences. A total of 37 scientists wrote chapters or parts of chapters for the report, which covered investigations of the 59 UFO sightings in detail. Like the Robertson Panel, the committee concluded that there was no evidence of anything other than commonplace phenomena in the reports and that UFOs did not warrant further investigation. This, together with a decline in sighting activity, led to the dismantling of Project Blue Book in 1969.

 

Despite the failure of the ETH to make headway with the expert committees, a few scientists and engineers, most notably J. Allen Hynek, an astronomer at Northwestern University in EvanstonIllinois, who had been involved with projects Sign, Grudge, and Blue Book, concluded that a small fraction of the most-reliable UFO reports gave definite indications for the presence of extraterrestrial visitors. Hynek founded the Center for UFO Studies (CUFOS), which continues to investigate the phenomenon. Another major U.S. study of UFO sightings was the Advanced Aviation Threat Identification Program (AATIP), a secret project that ran from 2007 to 2012. When the existence of the AATIP was made public in December 2017, the most newsworthy aspect of it was a report that the U.S. government possessed alloys and compounds purportedly attained from UFOs that were of unidentifiable nature, but many scientists remained skeptical about this claim.

 

Aside from the American efforts, the only other official and fairly complete records of UFO sightings were kept in Canada, where they were transferred in 1968 from the Canadian Department of National Defense to the Canadian National Research Council. The Canadian records comprised about 750 sightings. Less-complete records have been maintained in the United KingdomSwedenDenmarkAustralia, and Greece. In the United States, CUFOS and the Mutual UFO Network in Bellvue, Colorado, continue to log sightings reported by the public.

 

In the Soviet Union, sightings of UFOs were often prompted by tests of secret military rockets. In order to obscure the true nature of the tests, the government sometimes encouraged the public’s belief that these rockets might be extraterrestrial craft but eventually decided that the descriptions themselves might give away too much information. UFO sightings in China have been similarly provoked by military activity that is unknown to the public.

 

UFO reports have varied widely in reliability, as judged by the number of witnesses, whether the witnesses were independent of each other, the observing conditions (e.g., foghaze, type of illumination), and the direction of sighting. Typically, witnesses who take the trouble to report a sighting consider the object to be of extraterrestrial origin or possibly a military craft but certainly under intelligent control. This inference is usually based on what is perceived as formation flying by sets of objects, unnatural—often sudden—motions, the lack of sound, changes in brightness or colour, and strange shapes.

 

That the unaided eye plays tricks is well known. A bright light, such as the planet Venus, often appears to move. Astronomical objects can also be disconcerting to drivers, as they seem to “follow” the car. Visual impressions of distance and speed of UFOs are also highly unreliable because they are based on an assumed size and are often made against a blank sky with no background object (cloudsmountains, etc.) to set a maximum distance. Reflections from windows and eyeglasses produce superimposed views, and complex optical systems, such as camera lenses, can turn point sources of light into apparently saucer-shaped phenomena. Such optical illusions and the psychological desire to interpret images are known to account for many visual UFO reports, and at least some sightings are known to be hoaxes. Radar sightings, while in certain respects more reliable, fail to discriminate between artificial objects and meteor trails, ionized gas, rain, or thermal discontinuities in the atmosphere.

 

“Contact events,” such as abductions, are often associated with UFOs because they are ascribed to extraterrestrial visitors. However, the credibility of the ETH as an explanation for abductions is disputed by most psychologists who have investigated this phenomenon. They suggest that a common experience known as “sleep paralysis” may be the culprit, as this causes sleepers to experience a temporary immobility and a belief that they are being watched.

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NASA’s James Webb Space Telescope's Sharper View Hints at New Possibilities for Science

NASA’s James Webb Space Telescope's Sharper View Hints at New Possibilities for Science | Amazing Science | Scoop.it

NASA’s James Webb Space Telescope is aligned across all four of its science instruments, as seen in a previous engineering image showing the observatory’s full field of view. Now, we take a closer look at that same image, focusing on Webb’s coldest instrument: the Mid-Infrared Instrument, or MIRI. The MIRI test image (at 7.7 microns) shows part of the Large Magellanic Cloud. This small satellite galaxy of the Milky Way provided a dense star field to test Webb’s performance.

 

Here, a close-up of the MIRI image is compared to a past image of the same target taken with NASA’s Spitzer Space Telescope’s Infrared Array Camera (at 8.0 microns). The retired Spitzer telescope was one of NASA’s Great Observatories and the first to provide high-resolution images of the near- and mid-infrared universe. Webb, with its significantly larger primary mirror and improved detectors, will allow us to see the infrared sky with improved clarity, enabling even more discoveries.

For example, Webb’s MIRI image shows the interstellar gas in unprecedented detail. Here, you can see the emission from “polycyclic aromatic hydrocarbons,” or molecules of carbon and hydrogen that play an important role in the thermal balance and chemistry of interstellar gas. When Webb is ready to begin science observations, studies such as these with MIRI will help give astronomers new insights into the birth of stars and proto-planetary systems.

 

In the meantime, the Webb team has begun the process of setting up and testing Webb’s instruments to begin science observations this summer. Today at 11 a.m., Webb experts will preview these next two months of instrument preparations in a teleconference for media. Listen to the audio stream live at nasa.gov/live.

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NASA’s InSight Records Monster Quake on Mars

NASA’s InSight Records Monster Quake on Mars | Amazing Science | Scoop.it
Estimated to be magnitude 5, the quake is the biggest ever detected on another planet.

 

NASA’s InSight Mars lander has detected the largest quake ever observed on another planet: an estimated magnitude 5 temblor that occurred on May 4, 2022, the 1,222nd Martian day, or sol, of the mission. This adds to the catalog of more than 1,313 quakes InSight has detected since landing on Mars in November 2018. The largest previously recorded quake was an estimated magnitude 4.2 detected Aug. 25, 2021.

 

InSight was sent to Mars with a highly sensitive seismometer, provided by France’s Centre National d’Études Spatiales (CNES), to study the deep interior of the planet. As seismic waves pass through or reflect off material in Mars’ crust, mantle, and core, they change in ways that seismologists can study to determine the depth and composition of these layers. What scientists learn about the structure of Mars can help them better understand the formation of all rocky worlds, including Earth and its Moon.

 

A magnitude 5 quake is a medium-size quake compared to those felt on Earth, but it’s close to the upper limit of what scientists hoped to see on Mars during InSight’s mission. The science team will need to study this new quake further before being able to provide details such as its location, the nature of its source, and what it might tell us about the interior of Mars.

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Hubble Sheds Light on How Supermassive Black Holes Form

Hubble Sheds Light on How Supermassive Black Holes Form | Amazing Science | Scoop.it

Astronomers have identified a rapidly growing black hole in the early universe that is considered a crucial "missing link" between young star-forming galaxies and the first supermassive black holes. They used data from NASA's Hubble Space Telescope to make this discovery. Until now, the monster, nicknamed GNz7q, had been lurking unnoticed in one of the best-studied areas of the night sky, the Great Observatories Origins Deep Survey-North (GOODS-North) field.

 

 

Archival Hubble data from Hubble's Advanced Camera for Surveys helped the team determine that GNz7q existed just 750 million years after the big bang. The team obtained evidence that GNz7q is a newly formed black hole. Hubble found a compact source of ultraviolet (UV) and infrared light. This couldn't be caused by emission from galaxies, but is consistent with the radiation expected from materials that are falling onto a black hole. Rapidly growing black holes in dusty, early star-forming galaxies are predicted by theories and computer simulations, but had not been observed until now.

 

"Our analysis suggests that GNz7q is the first example of a rapidly growing black hole in the dusty core of a starburst galaxy at an epoch close to the earliest supermassive black hole known in the universe," explained Seiji Fujimoto, an astronomer at the Niels Bohr Institute of the University of Copenhagen and lead author of the Nature paper describing this discovery. "The object's properties across the electromagnetic spectrum are in excellent agreement with predictions from theoretical simulations."

 

One of the outstanding mysteries in astronomy today is: How did supermassive black holes, weighing millions to billions of times the mass of the Sun, get to be so huge so fast? Current theories predict that supermassive black holes begin their lives in the dust-shrouded cores of vigorously star-forming "starburst" galaxies before expelling the surrounding gas and dust and emerging as extremely luminous quasars. While extremely rare, both these dusty starburst galaxies and luminous quasars have been detected in the early universe.

 

The team believes that GNz7q could be a missing link between these two classes of objects. GNz7q has exactly both aspects of the dusty starburst galaxy and the quasar, where the quasar light shows the dust reddened color. Also, GNz7q lacks various features that are usually observed in typical, very luminous quasars (corresponding to the emission from the accretion disk of the supermassive black hole), which is most likely explained that the central black hole in GN7q is still in a young and less massive phase. These properties perfectly match with the young, transition phase quasar that has been predicted in simulations, but never identified at similarly high-redshift universe as the very luminous quasars so far identified up to a redshift of 7.6.

 

 

"GNz7q provides a direct connection between these two rare populations and provides a new avenue toward understanding the rapid growth of supermassive black holes in the early days of the universe," continued Fujimoto. "Our discovery provides an example of precursors to the supermassive black holes we observe at later epochs."

 
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Ocean water samples yield treasure trove of RNA virus data

Ocean water samples yield treasure trove of RNA virus data | Amazing Science | Scoop.it

Ocean water samples collected around the world have yielded a treasure trove of new data about RNA viruses, expanding ecological research possibilities and reshaping our understanding of how these small but significant submicroscopic particles evolved.

 

Combining machine-learning analyses with traditional evolutionary trees, an international team of researchers has identified 5,500 new RNA virus species that represent all five known RNA virus phyla and suggest there are at least five new RNA virus phyla needed to capture them.

 

The most abundant collection of newly identified species belong to a proposed phylum researchers named Taraviricota, a nod to the source of the 35,000 water samples that enabled the analysis: the Tara Oceans Consortium, an ongoing global study onboard the schooner Tara of the impact of climate change on the world's oceans.

 

"There's so much new diversity here -- and an entire phylum, the Taraviricota,were found all over the oceans, which suggests they're ecologically important," said lead author Matthew Sullivan, professor of microbiology at The Ohio State University. "RNA viruses are clearly important in our world, but we usually only study a tiny slice of them -- the few hundred that harm humans, plants and animals. We wanted to systematically study them on a very big scale and explore an environment no one had looked at deeply, and we got lucky because virtually every species was new, and many were really new."

 

The study appears online today (April 7, 2022) in Science. While microbes are essential contributors to all life on the planet, viruses that infect or interact with them have a variety of influences on microbial functions. These types of viruses are believed to have three main functions: killing cells, changing how infected cells manage energy, and transferring genes from one host to another. Knowing more about virus diversity and abundance in the world's oceans will help explain marine microbes' role in ocean adaptation to climate change, the researchers say. Oceans absorb half of the human-generated carbon dioxide from the atmosphere, and previous research by this group has suggested that marine viruses are the "knob" on a biological pump affecting how carbon in the ocean is stored.

 

By taking on the challenge of classifying RNA viruses, the team entered waters still rippling from earlier taxonomy categorization efforts that focused mostly on RNA viral pathogens. Within the biological kingdom Orthornavirae, five phyla were recently recognized by the International Committee on Taxonomy of Viruses (ICTV).

 

Though the research team identified hundreds of new RNA virus species that fit into those existing divisions, their analysis identified thousands more species that they clustered into five new proposed phyla: Taraviricota, Pomiviricota, Paraxenoviricota, Wamoviricota and Arctiviricota,which, like Taraviricota, features highly abundant species -- at least in climate-critical Arctic Ocean waters, the area of the world where warming conditions wreak the most havoc.

 

Sullivan's team has long cataloged DNA virus species in the oceans, growing the numbers from a few thousand in 2015 and 2016 to 200,000 in 2019. For those studies, scientists had access to viral particles to complete the analysis. In these current efforts to detect RNA viruses, there were no viral particles to study. Instead, researchers extracted sequences from genes expressed in organisms floating in the sea, and narrowed the analysis to RNA sequences that contained a signature gene, called RdRp, which has evolved for billions of years in RNA viruses, and is absent from other viruses or cells.

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Flying dinosaurs (pterosaurs) could change the color of their feathers, research study finds

Flying dinosaurs (pterosaurs) could change the color of their feathers, research study finds | Amazing Science | Scoop.it

An international team of paleontologists has discovered remarkable new evidence that pterosaurs, the flying relatives of dinosaurs, were able to control the color of their feathers using melanin pigments.The new study is based on analyses of a new 115 million year old fossilized headcrest of the pterosaur Tupandactylus imperator from north-eastern Brazil. Pterosaurs lived side by side with dinosaurs, 230 to 66 million years ago.  This species of pterosaur is famous for its bizarre huge headcrest. The team discovered that the bottom of the crest had a fuzzy rim of feathers, with short wiry hair-like feathers and fluffy branched feathers. 

 

“We didn’t expect to see this at all”, said Dr Cincotta. “For decades paleontologists have argued about whether pterosaurs had feathers. The feathers in our specimen close off that debate for good as they are very clearly branched all the way along their length, just like birds today”.  The team then studied the feathers with high-powered electron microscopes and found preserved melanosomes – granules of the pigment melanin. Unexpectedly, the new study shows that the melanosomes in different feather types have different shapes. 

 

“In birds today, feather color is strongly linked to melanosome shape.” said Prof. McNamara. “Since the pterosaur feather types had different melanosome shapes, these animals must have had the genetic machinery to control the colors of their feathers. This feature is essential for color patterning and shows that coloration was a critical feature of even the very earliest feathers.”

 

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Artificial neurons go quantum with photonic circuits

Artificial neurons go quantum with photonic circuits | Amazing Science | Scoop.it

In recent years, artificial intelligence has become ubiquitous, with applications such as speech interpretation, image recognition, medical diagnosis, and many more. At the same time, quantum technology has been proven capable of computational power well beyond the reach of even the world’s largest supercomputer.

 

Quantum physicists at the University of Vienna have now demonstrated a new device, called quantum memristor, which may allow to combine these two worlds, thus unlocking unprecedented capabilities. The experiment, carried out in collaboration with the National Research Council (CNR) and the Politecnico di Milano in Italy, has been realized on an integrated quantum processor operating on single photons. The work is published in the current issue of the journal "Nature Photonics".

 

At the heart of all artificial intelligence applications are mathematical models called neural networks. These models are inspired by the biological structure of the human brain, made of interconnected nodes. Just like our brain learns by constantly rearranging the connections between neurons, neural networks can be mathematically trained by tuning their internal structure until they become capable of human-level tasks: recognizing our face, interpreting medical images for diagnosis, even driving our cars. Having integrated devices capable of performing the computations involved in neural networks quickly and efficiently has thus become a major research focus, both academic and industrial.

 

One of the major game changers in the field was the discovery of the memristor, made in 2008. This device changes its resistance depending on a memory of the past current, hence the name memory-resistor, or memristor. Immediately after its discovery, scientists realized that (among many other applications) the peculiar behavior of memristors was surprisingly similar to that of neural synapses. The memristor has thus become a fundamental building block of neuromorphic architectures.

 

By using single photons, i.e. single quantum particles of lights, and exploiting their unique ability to propagate simultaneously in a superposition of two or more paths, the physicists have overcome the challenge. In their experiment, single photons propagate along waveguides laser-written on a glass substrate and are guided on a superposition of several paths. One of these paths is used to measure the flux of photons going through the device and this quantity, through a complex electronic feedback scheme, modulates the transmission on the other output, thus achieving the desired memristive behavior. Besides demonstrating the quantum memristor, the researchers have provided simulations showing that optical networks with quantum memristor can be used to learn on both classical and quantum tasks, hinting at the fact that the quantum memristor may be the missing link between artificial intelligence and quantum computing.

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How Do Gene Drives Work?

How Do Gene Drives Work? | Amazing Science | Scoop.it

Synthetic gene drive technology is a method of genetic engineering through which certain desired traits can be introduced to almost all individuals in a population. Researchers can either eliminate a species or alter the genetic makeup of living organisms through gene drive technology. Most gene drives are genetic elements that can quickly spread through populations of organisms and have nearly a 100% chance of passing the genes they carry to the next generation. 


How are gene drives generated?

Naturally occurring gene drives are found in almost all animals, including humans, plants, fungi and bacteria. They are selfish genetic elements that spread through inheritance from one generation to another. For example, homing endonuclease genes (HEGs) are site-specific selfish genes that spread by cleaving a homologous wild-type chromosome and copying themselves into the cut site through homology-directed repair (HDR). Meiotic drive is an intragenomic mechanism that interferes with meiotic processes so that the transmission of one or more alleles is favored over another. Manipulation of transposable elements, i.e., small DNA sequences that can move from one location in the genome to another, can also generate gene drives.

 

Earlier attempts to generate synthetic gene drives involved gene-editing techniques such as zinc-finger nucleases (ZFNs) and transcription activator-like effector nucleases (TALENs). However, mutations occurring in the repetitive elements limited the use of these technologies for the generation of gene drives, as they were often inactivated before being passed on to the next generation.

How do CRISPR-Cas9 gene drives work?

CRISPR-Cas9 gene drives consist of a drive allele, i.e., a genetic construct carrying genes encoding the desired trait, Cas9, and a guide RNA (gRNA), as well as flanking arms homologous to the sequences surrounding the target site in the wild type chromosome. When a homozygous gene drive-modified individual mates with an unmodified individual, the resulting offspring inherits one drive allele from the gene drive-modified parent and one non-modified version of the corresponding allele from the wild-type parent. The gRNA and the Cas9 genes are subsequently expressed in the cell, and the gRNA guides Cas9 to make a double-strand break in the wild-type chromosome at the target site. The drive allele then acts as a template for HDR, and the entire drive allele - including the gene of interest - is inserted into the wild-type chromosome. The cell is now homozygous for the drive allele, which will be passed to all gametes after meiosis, thus spreading the desired trait in the population.

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Scientists create an algorithm to assign a label to every pixel in the world, without human supervision

Scientists create an algorithm to assign a label to every pixel in the world, without human supervision | Amazing Science | Scoop.it

Labeling data can be a chore. It's the main source of sustenance for computer-vision models; without it, they'd have a lot of difficulty identifying objects, people, and other important image characteristics. Yet producing just an hour of tagged and labeled data can take a whopping 800 hours of human time. Our high-fidelity understanding of the world develops as machines can better perceive and interact with our surroundings. But they need more help.

 

Scientists from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL), Microsoft, and Cornell University have attempted to solve this problem plaguing vision models by creating "STEGO," an algorithm that can jointly discover and segment objects without any human labels at all, down to the pixel.

 

STEGO learns something called "semantic segmentation"—fancy speak for the process of assigning a label to every pixel in an image. Semantic segmentation is an important skill for today's computer-vision systems because images can be cluttered with objects. Even more challenging is that these objects don't always fit into literal boxes; algorithms tend to work better for discrete "things" like people and cars as opposed to "stuff" like vegetation, sky, and mashed potatoes. A previous system might simply perceive a nuanced scene of a dog playing in the park as just a dog, but by assigning every pixel of the image a label, STEGO can break the image into its main ingredients: a dog, sky, grass, and its owner.

 

Assigning every single pixel of the world a label is ambitious—especially without any kind of feedback from humans. The majority of algorithms today get their knowledge from mounds of labeled data, which can take painstaking human-hours to source. Just imagine the excitement of labeling every pixel of 100,000 images. To discover these objects without a human's helpful guidance, STEGO looks for similar objects that appear throughout a dataset. It then associates these similar objects together to construct a consistent view of the world across all of the images it learns from.

 

Seeing the world

Machines that can "see" are crucial for a wide array of new and emerging technologies like self-driving cars and predictive modeling for medical diagnostics. Since STEGO can learn without labels, it can detect objects in many different domains, even those that humans don't yet understand fully.

 

"If you're looking at oncological scans, the surface of planets, or high-resolution biological images, it's hard to know what objects to look for without expert knowledge. In emerging domains, sometimes even human experts don't know what the right objects should be," says Mark Hamilton, a Ph.D. student in electrical engineering and computer science at MIT, research affiliate of MIT CSAIL, software engineer at Microsoft, and lead author on a new paper about STEGO. "In these types of situations where you want to design a method to operate at the boundaries of science, you can't rely on humans to figure it out before machines do."

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First Covid-19 Breath Test Authorized by FDA

First Covid-19 Breath Test Authorized by FDA | Amazing Science | Scoop.it

The US Food and Drug Administration has granted emergency use authorization to the first Covid-19 test that spots chemical compounds associated with the coronavirus in breath, the agency said Thursday.  The FDA said the InspectIR Covid-19 Breathalyzer, which is about the size of a piece of carry-on luggage, can be used in medical offices and mobile testing sites. It can give results in less than three minutes. The system separates and identifies chemical mixtures to detect five compounds associated with SARS-CoV-2 infection.

 

A study of the InspectIR Breathalyzer found that it accurately identified more than 91% of positive samples and nearly 100% of negative samples. Similar sensitivity was found in another study that focused on the Omicron coronavirus variant. However, a positive result should be confirmed with a PCR test, the FDA said. "It's another tool, and the FDA announcement suggests it's reasonably accurate and a relatively user-friendly tool," Dr. Emily Volk, president of the College of American Pathologists, a board-certified anatomic and clinical pathologist, said Friday. "It waits to be seen how widely this will be adopted," Volk said. "That could rely on how expensive it is." In an email to CNN on Friday, InspectIR Systems said it is not releasing the price of the machine or when it will be available. 

 

The agency's authorization "is yet another example of the rapid innovation occurring with diagnostic tests for COVID-19," Dr. Jeff Shuren, director of the FDA's Center for Devices and Radiological Health, said in a statement. "The FDA continues to support the development of novel COVID-19 tests with the goal of advancing technologies that can help address the current pandemic and better position the U.S. for the next public health emergency."

 

FDA Press Release (April 14, 2022):

https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-authorizes-first-covid-19-diagnostic-test-using-breath-samples 

 

FDA Letter of Authorization (April 14, 2022):

https://www.fda.gov/media/157720/download?utm_medium=email&utm_source=govdelivery 


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Astronomers just discovered a new type of stellar explosion, the micronova

Astronomers just discovered a new type of stellar explosion, the micronova | Amazing Science | Scoop.it
They're like novas, just smaller in scale and more localized on a white dwarf's surface.

 

Astronomers have discovered highly localized thermonuclear blasts coming from the surface of three white dwarf stars—unusually short-lived events they have dubbed "micronovae." They're similar to novas, except these blasts can burn through a tremendous amount of material in just a few hours, roughly equivalent to 3.5 billion Great Pyramids of Giza. According to the authors of a new paper published in the journal Nature, micronovae could be common in the Universe; they're just difficult to detect because they don't last very long.

 

“The phenomenon challenges our understanding of how thermonuclear explosions in stars occur,' said co-author Simone Scaringi, an astronomer at Durham University in the UK. "We thought we knew this, but this discovery proposes a totally new way to achieve them. It just goes to show how dynamic the Universe is."

 

Astronomers have known about novas for centuries. The 16th-century astronomer Tycho Brahe coined the term after witnessing a supernova in 1572, describing it in his treatise De nova stella ("concerning the new star"). The terms were used interchangeably until the 1930s when scientists began distinguishing between the events, since their causes and energies seemed quite different. Novas typically are the result, not of new stars, as the name implies, but the remnants of ancient stars known as white dwarfs. The process begins with a binary system, in which one of the two stars turns into a red giant, leaving just a white dwarf remnant core still in orbit with the other star in the system. A white dwarf is small and incredibly dense because it collapses so tightly that its electrons are smashed together, forming "electron-degenerate matter." Eventually the electrons provide enough of an outward-pressing force to halt the star's collapse.

 

One of the first white dwarf stars discovered, dubbed 40 Eridani B, had a density over 25,000 times that of the Sun, packed into a much smaller volume (roughly the size of Earth)—an observational deduction that astronomers initially deemed impossible. A second white dwarf, Sirius B (orbiting the star Sirius), was discovered soon after and appeared incredibly dense. And it's the unique properties of white dwarf stars that give rise to novas. If a white dwarf is close enough to its companion star, it begins siphoning off matter (usually hydrogen) from its companion star's outer atmosphere. The hydrogen falls onto the white dwarf's very hot surface, and its atoms fuse into helium in a thermonuclear explosion. For a nova, this occurs across the entire surface of the star, producing an intense, bright light that can be observed for several weeks.

 

So Scaringi and his fellow astronomers were surprised to find bright flashes of light, akin to a nova, that only lasted for just a few hours while analyzing data from NASA's Transiting Exoplanet Survey Satellite (TESS). Launched in 2018, TESS's mission is to hunt for planets outside our Solar System by looking for periodic dips in light from stars—evidence that an exoplanet might be orbiting such a star.

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Further investigation revealed two more similar events, which the astronomers dubbed micronovae. Two of those events were observed on stars already known to be white dwarfs. The team relied on additional observations from the European Southern Observatory's Very Large Telescope to confirm the third was also a white dwarf.

 

But why were these thermonuclear explosions so strangely localized? A follow-up paper published in the Monthly Notices of the Royal Astronomical Society proposes that micronovae could be triggered by magnetic confinement of material on an accreting white dwarf. The star's powerful magnetic fields funnel matter toward the magnetic poles, triggering a thermonuclear explosion confined by those same magnetic fields.

 

“For the first time, we have now seen that hydrogen fusion can also happen in a localized way. The hydrogen fuel can be contained at the base of the magnetic poles of some white dwarfs, so that fusion only happens at these magnetic poles,” said co-author Paul Groot, an astronomer at Radboud University in the Netherlands. “This leads to micro-fusion bombs going off, which have about one-millionth of the strength of a nova explosion, hence the name micronova.”

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World Quantum Day: How to Make Silicon Qubits

World Quantum Day: How to Make Silicon Qubits | Amazing Science | Scoop.it

Full-scale quantum computers require the integration of millions of qubits, and the potential of using industrial semiconductor manufacturing to meet this need has driven the development of quantum computing in silicon quantum dots. However, fabrication has so far relied on electron-beam lithography and, with a few exceptions, conventional lift-off processes that suffer from low yield and poor uniformity.

 

Now a group of quantum scientists report quantum dots that are hosted at a 28Si/28SiO2 interface and fabricated in a 300 mm semiconductor manufacturing facility using all-optical lithography and fully industrial processing. With this approach, they were able to achieve nanoscale gate patterns with excellent yield. In the multi-electron regime, the quantum dots allow good tunnel barrier control—a crucial feature for fault-tolerant two-qubit gates. Single-spin qubit operation using magnetic resonance in the few-electron regime reveals relaxation times of over 1 s at 1 T and coherence times of over 3 ms.

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Faces, Bodies, Spiders, and Radios: How the Brain Represents Visual Objects

Faces, Bodies, Spiders, and Radios: How the Brain Represents Visual Objects | Amazing Science | Scoop.it
 
Machine learning and neuroscience discover the mathematical system used by the brain to organize visual objects. When Plato set out to define what made a human a human, he settled on two primary characteristics: We do not have feathers, and we are bipedal (walking upright on two legs). Plato's characterization may not encompass all of what identifies a human, but his reduction of an object to its fundamental characteristics provides an example of a technique known as principal component analysis.

 

Now, Caltech researchers have combined tools from machine learning and neuroscience to discover that the brain uses a mathematical system to organize visual objects according to their principal components. The work shows that the brain contains a two-dimensional map of cells representing different objects. The location of each cell in this map is determined by the principal components (or features) of its preferred objects; for example, cells that respond to round, curvy objects like faces and apples are grouped together, while cells that respond to spiky objects like helicopters or chairs form another group.

 

The research was conducted in the laboratory of Doris Tsao (BS '96), professor of biology, director of the Tianqiao and Chrissy Chen Center for Systems Neuroscience and holder of its leadership chair, and Howard Hughes Medical Institute Investigator. A paper describing the study appears in the journal Nature on June 3, 2022.

 

The researchers took the set of thousands of images they had shown primates and passed them through a deep network. They then examined activations of units found in the eight different layers of the deep network. Because there are thousands of units in each layer, it was difficult to discern any patterns to their firing.

 

The lead researcher, Bao, decided to use principal component analysis to determine the fundamental parameters driving activity changes in each layer of the network. In one of the layers, Bao noticed something oddly familiar: one of the principal components was strongly activated by spiky objects, such as spiders and helicopters, and was suppressed by faces. This precisely matched the object preferences of the cells Bao had recorded from earlier in the no man's land network.

 

What could account for this coincidence? One idea was that IT cortex might actually be organized as a map of object space, with x- and y-dimensions determined by the top two principal components computed from the deep network. This idea would predict the existence of face, body, and no man's land regions, since their preferred objects each fall neatly into different quadrants of the object space computed from the deep network. But one quadrant had no known counterpart in the brain: stubby objects, like radios or cups.

 

Bao decided to show primates images of objects belonging to this "missing" quadrant as he monitored the activity of their IT cortexes. Astonishingly, he found a network of cortical regions that did respond only to stubby objects, as predicted by the model. This means the deep network had successfully predicted the existence of a previously unknown set of brain regions. Why was each quadrant represented by a network of multiple regions? Earlier, Tsao's lab had found that different face patches throughout IT cortex encode an increasingly abstract representation of faces. Bao found that the two networks he had discovered showed this same property: cells in more anterior regions of the brain responded to objects across different angles, while cells in more posterior regions responded to objects only at specific angles.

 

This shows that the temporal lobe contains multiple copies of the map of object space, each more abstract than the preceding. Finally, the team was curious how complete the map was. They measured the brain activity from each of the four networks comprising the map as the primates viewed images of objects and then decoded the brain signals to determine what the primates had been looking at. The model was able to accurately reconstruct the images viewed by the primates.

 

"We now know which features are important for object recognition," says Bao. "The similarity between the important features observed in both biological visual systems and deep networks suggests the two systems might share a similar computational mechanism for object recognition. Indeed, this is the first time, to my knowledge, that a deep network has made a prediction about a feature of the brain that was not known before and turned out to be true. I think we are very close to figuring out the how the primate brain solves the object recognition problem."

 

The research paper is titled "A map of object space in primate inferotemporal cortex."

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