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ScienceDaily

Enormous planet quickly orbiting a tiny, dying star

Thanks to a bevy of telescopes in space and on Earth — and even a pair of amateur astronomers in Arizona — a University of Wisconsin-Madison astronomer and his colleagues have discovered a Jupiter-sized planet orbiting at breakneck speed around a distant white dwarf star. The system, about 80 light years away, violates all common conventions about stars and planets. The white dwarf is the remnant of a sun-like star, greatly shrunken down to roughly the size of Earth, yet it retains half the sun’s mass. The massive planet looms over its tiny star, which it circles every 34 hours thanks to an incredibly close orbit. In contrast, Mercury takes a comparatively lethargic 90 days to orbit the sun. While there have been hints of large planets orbiting close to white dwarfs in the past, the new findings are the clearest evidence yet that these bizarre pairings exist. That confirmation highlights the diverse ways stellar systems can evolve and may give a glimpse at our own solar system’s fate. Such a white dwarf system could even provide a rare habitable arrangement for life to arise in the light of a dying star.

“We’ve never seen evidence before of a planet coming in so close to a white dwarf and surviving. It’s a pleasant surprise,” says lead researcher Andrew Vanderburg, who recently joined the UW-Madison astronomy department as an assistant professor. Vanderburg completed the work while an independent NASA Sagan Fellow at the University of Texas at Austin.

The researchers published their findings Sept. 16 in the journal Nature. Vanderburg led a large, international collaboration of astronomers who analyzed the data. The contributing telescopes included NASA’s exoplanet-hunting telescope TESS and two large ground-based telescopes in the Canary Islands.

Vanderburg was originally drawn to studying white dwarfs — the remains of sun-sized stars after they exhaust their nuclear fuel — and their planets by accident. While in graduate school, he was reviewing data from TESS’s predecessor, the Kepler space telescope, and noticed a white dwarf with a cloud of debris around it.

“What we ended up finding was that this was a minor planet or asteroid that was being ripped apart as we watched, which was really cool,” says Vanderburg. The planet had been destroyed by the star’s gravity after its transition to a white dwarf caused the planet’s orbit to fall in toward the star.

Ever since, Vanderburg has wondered if planets, especially large ones, could survive the journey in toward an aging star.

By scanning data for thousands of white dwarf systems collected by TESS, the researchers spotted a star whose brightness dimmed by half about every one-and-a-half days, a sign that something big was passing in front of the star on a tight, lightning-fast orbit. But it was hard to interpret the data because the glare from a nearby star was interfering with TESS’s measurements. To overcome this obstacle, the astronomers supplemented the TESS data from higher-resolution ground-based telescopes, including three run by amateur astronomers.

“Once the glare was under control, in one night, they got much nicer and much cleaner data than we got with a month of observations from space,” says Vanderburg. Because white dwarfs are so much smaller than normal stars, large planets passing in front of them block a lot of the star’s light, making detection by ground-based telescopes much simpler.

The data revealed that a planet roughly the size of Jupiter, perhaps a little larger, was orbiting very close to its star. Vanderburg’s team believes the gas giant started off much farther from the star and moved into its current orbit after the star evolved into a white dwarf.

The question became: how did this planet avoid being torn apart during the upheaval? Previous models of white dwarf-planet interactions didn’t seem to line up for this particular star system.

The researchers ran new simulations that provided a potential answer to the mystery. When the star ran out of fuel, it expanded into a red giant, engulfing any nearby planets and destabilizing the Jupiter-sized planet that orbited farther away. That caused the planet to take on an exaggerated, oval orbit that passed very close to the now-shrunken white dwarf but also flung the planet very far away at the orbit’s apex.

Over eons, the gravitational interaction between the white dwarf and its planet slowly dispersed energy, ultimately guiding the planet into a tight, circular orbit that takes just one-and-a-half days to complete. That process takes time — billions of years. This particular white dwarf is one of the oldest observed by the TESS telescope at almost 6 billion years old, plenty of time to slow down its massive planet partner.

While white dwarfs no longer conduct nuclear fusion, they still release light and heat as they cool down. It’s possible that a planet close enough to such a dying star would find itself in the habitable zone, the region near a star where liquid water can exist, presumed to be required for life to arise and survive.

Now that research has confirmed these systems exist, they offer a tantalizing opportunity for searching for other forms of life. The unique structure of white dwarf-planet systems provides an ideal opportunity to study the chemical signatures of orbiting planets’ atmospheres, a potential way to search for signs of life from afar.

“I think the most exciting part of this work is what it means for both habitability in general — can there be hospitable regions in these dead solar systems — and also our ability to find evidence of that habitability,” says Vanderburg.

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ScienceDaily

Using artificial intelligence to smell the roses

A pair of researchers at the University of California, Riverside, has used machine learning to understand what a chemical smells like — a research breakthrough with potential applications in the food flavor and fragrance industries.

“We now can use artificial intelligence to predict how any chemical is going to smell to humans,” said Anandasankar Ray, a professor of molecular, cell and systems biology, and the senior author of the study that appears in iScience. “Chemicals that are toxic or harsh in, say, flavors, cosmetics, or household products can be replaced with natural, softer, and safer chemicals.”

Humans sense odors when some of their nearly 400 odorant receptors, or ORs, are activated in the nose. Each OR is activated by a unique set of chemicals; together, the large OR family can detect a vast chemical space. A key question in olfaction is how the receptors contribute to different perceptual qualities or percepts.

“We tried to model human olfactory percepts using chemical informatics and machine learning,” Ray said. “The power of machine learning is that it is able to evaluate a large number of chemical features and learn what makes a chemical smell like, say, a lemon or a rose or something else. The machine learning algorithm can eventually predict how a new chemical will smell even though we may initially not know if it smells like a lemon or a rose.”

According to Ray, digitizing predictions of how chemicals smell creates a new way of scientifically prioritizing what chemicals can be used in the food, flavor, and fragrance industries.

“It allows us to rapidly find chemicals that have a novel combination of smells,” he said. “The technology can help us discover new chemicals that could replace existing ones that are becoming rare, for example, or which are very expensive. It gives us a vast palette of compounds that we can mix and match for any olfactory application. For example, you can now make a mosquito repellent that works on mosquitoes but is pleasant smelling to humans.”

The researchers first developed a method for a computer to learn chemical features that activate known human odorant receptors. They then screened roughly half a million compounds for new ligands — molecules that bind to receptors — for 34 odorant receptors. Next, they focused on whether the algorithm that could estimate odorant receptor activity could also predict diverse perceptual qualities of odorants.

“Computers might help us better understand human perceptual coding, which appears, in part, to be based on combinations of differently activated ORs,” said Joel Kowalewski, a student in the Neuroscience Graduate Program working with Ray and the first author of the research paper. “We used hundreds of chemicals that human volunteers previously evaluated, selected ORs that best predicted percepts on a portion of chemicals, and tested that these ORs were also predictive of new chemicals.”

Ray and Kowalewski showed the activity of ORs successfully predicted 146 different percepts of chemicals. To their surprise, few rather than all ORs were needed to predict some of these percepts. Since they could not record activity from sensory neurons in humans, they tested this further in the fruit fly (Drosophila melanogaster) and observed a similar result when predicting the fly’s attraction or aversion to different odorants.

“If predictions are successful with less information, the task of decoding odor perception would then become easier for a computer,” Kowalewski said.

Ray explained that many items available to consumers use volatile chemicals to make themselves appealing. About 80% of what is considered flavor in food actually stems from the odors that affect smell. Fragrances for perfuming cosmetics, cleaning products, and other household goods play an important role in consumer behavior.

“Our digital approach using machine learning could open up many opportunities in the food, flavor, and fragrance industries,” he said. “We now have an unprecedented ability to find ligands and new flavors and fragrances. Using our computational approach, we can intelligently design volatile chemicals that smell desirable for use and also predict ligands for the 34 human ORs.”

The study was partially funded by UCR and the National Science Foundation.

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IEEE Spectrum

Submarine Cable Repairs Underway in South Africa

A clock in South Africa is counting down the seconds until a pair of broken cables are expected to go back in service. Every few hours, the service provider TENET, which keeps South Africa’s university and research facilities connected to the global Internet, tweets updates.

The eight-year-old West Africa Cable System (WACS) submarine cable, which runs parallel to Africa’s west coast, broke at two points early on 16 January. That same day, an 18-year-old cable called SAT-3 that runs along the same route also broke.

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3D Printing Industry

Precht and Mamou-Mani unveil ‘Sandwaves’ and ‘Pixel Gate’ 3D printed installations in Saudi Arabia

Architectural design studios Precht and Mamou-Mani Architects have constructed a pair of installations in Saudi Arabia using 3D printing. The first installation, named Sandwaves, uses a sand 3D printing method and features lattice structures woven in a ribbon-like formation. The second piece comprises a set of stacked cubes, named Pixel Gate, 3D printed using a […]

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Author: Anas Essop

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Hackster.io

A Pair of AI-Powered E.D.I.T.H Smart Glasses

In the movie Spider-Man: Far from Home, Peter Parker gets a pair of glasses that give him access to a wide range of useful information. In true sci-fi fashion, they are nearly indistinguishable from normal corrective glasses, yet incredibly powerful. YouTuber JLaservideo decided to construct his own version of this wearable tech, and while they’re not quite as subtle as the ones in film, they do have some impressive abilities.

The main feature of this device is a small see-through OLED screen that is mounted on one of the glasses lenses. This allows the user to see through the display while reading text, generated by a computer, then passed along using an Arduino over serial. Any text can be shown, but since that’s not really useful the controlling computer takes pictures with a webcam, then extracts any visible text using OpenCV. Text is then sent to WolframAlpha, which searches the Internet and returns (potentially)useful information, or returns the answer to math problems that it sees.

The glasses require a number of wires that are attached to a notebook computer to operate, so it’s still a long way from Spider-Man’s functionality. However, as seen toward the end of the video, it can still be used (literally) on the road, and JLaservideo demonstrates this capability by letting it analyze a stop sign for him!

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Author: Jeremy S. Cook

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Hackster.io

Web-Enabled Unicorn Boots Warn You of Product Recalls

What do you do if you have a pair of recalled children’s rain boots? Of course, you should return them to wherever is required for a refund, but depending on how much money you’re getting back, this might not be worth the effort. Artist Andrew Kleindolph has another idea for such footwear: an Internet-connected display for other recalled products. While these rainbow-unicorn boots might not have properly fulfilled their purpose, at least they can now warn you of other impending dangers.

The main element to this build is Adafruit’s new PyPortal, a CircuitPython-powered Internet display. The device is perfect for this type of zany boot display, with an ATSAMD51J20 and ESP32 WiFi module onboard, along with a 3.2” 320×240 color TFT screen. This allows das boot to pull data from the web, in this case live data from the United States Consumer Product Safety Commission (USCPSC), to inform you about exciting new product recalls. It’s a very strange thing to see in front of a unicorn boot backdrop.

With its embedded battery, you can even take it on the road, showing data on non-child resistant packaging, burners that fail to turn off, corroding aerosol containers and more, anywhere you see fit to take it!

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Author: Jeremy S. Cook

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Hackster.io

Psychedelic Smart Glasses with WS2812 Rings

Like many hacked projects, this pair of “smart glasses” started out as what creator Facelesstech describes as “a stupid idea” that he followed through on to see if it was possible. The build consists of a pair of eight NeoPixel-style LED rings embedded on the inside of sunglasses, obscuring a large part of your view, but making you look oh-so-cool… or at least very noticeable at night.

The NeoPixel rings are driven by an ATtiny85 chip on a small custom PCB, manufactured in a way that it sits nearly flush with the right arm. This board also features a set of DIP switches to change between different visible modes. These appear to be: single-color, rainbow, fading, and chase — though one could certainly reprogram it for special occasions, if so desired.

While there’s no programming port per se, the ATtiny85 is arranged so that it can be accessed with a spring loaded “chip clip” programmer, which came in handy after Facelesstech everything together without a bootloader installed. Power is provided by an AAAA LiPo scavenged from a disposable e-cigarrette. It’s small enough to be embedded in that glasses’ rather substantial left arm, and is held in place there with heat shrink.

Facelesstech notes that he wishes he’d had something like this “back when I used to go out.” The good news though is that he’s put code and board files up on GitHub, and the project is also described in the video below. Perhaps you can make a pair yourself and put the glasses to use in their proper environment!

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Author: Jeremy S. Cook