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Antarctic glacier retreating rapidly

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Antarctic glacier retreating rapidly


Scientists are warning that apparently stable glaciers in the Antarctic can “switch very rapidly” and lose large quantities of ice as a result of warmer oceans.

Their finding comes after a research team led by Benjamin Wallis, a glaciologist at the University of Leeds, used satellites to track the Cadman Glacier, which drains into Beascochea Bay, on the west Antarctic peninsula.

Between November 2018 and May 2021, the glacier retreated eight kilometres as the ice shelf at the end of the glacier — where ice extends out into the sea and is anchored onto the sea floor at what is known as the grounding zone — collapsed. (See image 1)

The ice shelf would have acted as a buttress, slowing the movement of the glacier towards the sea.

Surrounded by warmer ocean waters, the scientists believe the ice shelf thinned and became ungrounded, and the ice shelf was no longer able to hold back the glacier.

As a result, the speed at which the glacier was flowing rapidly accelerated — doubling its speed — increasing the amount of ice it discharges into the sea as icebergs, through a process known as iceberg calving.

Wallis said: “We were surprised to see the speed at which Cadman went from being an apparently stable glacier to one where we see sudden deterioration and significant ice loss.

“What was also curious was that the neighbouring glaciers on this part of the west Antarctic Peninsula did not react in the same way, which may hold important lessons for the way we can better project how climate change will continue to affect this important and sensitive polar region.

“Our study brought together data from three decades, nine different satellite missions, and in-situ oceanographic measurements to understand the changes happening in Antarctica. This demonstrates how important it is to have long term monitoring of the Earth’s polar regions with a range of sensors which all tell us a different piece of the story.”

According to the scientists, the Cadman Glacier is now in a state of “substantial dynamic imbalance.” The ice on the glacier has continued to thin, with elevation being lost at a rate of around 20 metres a year. That is equivalent to a loss in height of a five-storey building each year.

And around 2.16 billion tonnes of ice are draining from the Cadman Glacier into the ocean each year.

The researchers have published their analysis — Ocean warming drives rapid dynamic activation of marine-terminating glacier on the west Antarctic Peninsula — today (November 28) in the scientific journal Nature Communications.

Why the Cadman Glacier became so unstable

Unusually high ocean water temperatures in early 2018/19 around the west Antarctic peninsula are believed to have triggered the rapid dynamic change on the Cadman Glacier system.

By analysing historic satellite data, the scientists believe warmer ocean waters gradually thinned the glacier’s ice shelf from the early 2000s and possibly since the 1970s.

The warmer water was not carried on the surface of the ocean but deep in the water column. This warmer water may have reached the ice shelf where it is grounded on the sea floor. The result is the ice shelf begins to melt from the bottom up.

In 2018/19, the ice shelf was so thin that it broke free from the grounding zone and started to float, in effect slipping anchor and enabling the Cadman Glacier to drain more ice into the seas.

But the scientific team still faced one big question. Why had the Cadman Glacier collapsed when the neighbouring Funk and Lever Glaciers remained relatively stable?

Subsea ridges protect some glaciers

By analysing subsea oceanographic data, they believe a series of subsea rock structures called ridges or sills, at a depth of 200 metres and 230 metres, acts as a defensive barrier, deflecting channels of warmer water from reaching the glaciers. Although they warn that a rise in ocean warming could compromise the ability of the ridges to protect some glaciers.

Professor Michael Meredith, from the British Antarctic Survey and one of the authors of the paper, said: “We have known for some time that the ocean around Antarctica is heating up rapidly, and that this poses a significant threat to glaciers and the ice sheet, with consequences for sea level rise globally.

“What this new research shows is that apparently stable glaciers can switch very rapidly, becoming unstable almost without warning, and then thinning and retreating very strongly. This emphasises the need for a comprehensive ocean observing network around Antarctica, especially in regions close to glaciers that are especially hard to make measurements.”

Writing in the paper, the researchers say what has happened to the Cadman Glacier can be seen as an example of a “glaciological tipping point,” where a system in a steady state can take one or two paths based on a change in an environmental parameter.

A tipping point was reached in 2018 caused by the arrival of unusually warm ocean water, which caused the ice shelf to unground. Reaching this tipping point caused the Cadman Glacier to increase its ice discharge by 28% in 13 months.

The researchers say other glaciers on the Antarctic Peninsula may be vulnerable to similar sudden changes because of subsea geology.



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Charge your laptop in a minute or your EV in 10? Supercapacitors can help

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Charge your laptop in a minute or your EV in 10? Supercapacitors can help


Imagine if your dead laptop or phone could charge in a minute or if an electric car could be fully powered in 10 minutes.

While not possible yet, new research by a team of CU Boulder scientists could potentially lead to such advances.

Published today in the Proceedings of the National Academy of Sciences, researchers in Ankur Gupta’s lab discovered how tiny charged particles, called ions, move within a complex network of minuscule pores. The breakthrough could lead to the development of more efficient energy storage devices, such as supercapacitors, said Gupta, an assistant professor of chemical and biological engineering.

“Given the critical role of energy in the future of the planet, I felt inspired to apply my chemical engineering knowledge to advancing energy storage devices,” Gupta said. “It felt like the topic was somewhat underexplored and as such, the perfect opportunity.”

Gupta explained that several chemical engineering techniques are used to study flow in porous materials such as oil reservoirs and water filtration, but they have not been fully utilized in some energy storage systems.

The discovery is significant not only for storing energy in vehicles and electronic devices but also for power grids, where fluctuating energy demand requires efficient storage to avoid waste during periods of low demand and to ensure rapid supply during high demand.

Supercapacitors, energy storage devices that rely on ion accumulation in their pores, have rapid charging times and longer life spans compared to batteries.

“The primary appeal of supercapacitors lies in their speed,” Gupta said. “So how can we make their charging and release of energy faster? By the more efficient movement of ions.”

Their findings modify Kirchhoff’s law, which has governed current flow in electrical circuits since 1845 and is a staple in high school students’ science classes. Unlike electrons, ions move due to both electric fields and diffusion, and the researchers determined that their movements at pore intersections are different from what was described in Kirchhoff’s law.

Prior to the study, ion movements were only described in the literature in one straight pore. Through this research, ion movement in a complex network of thousands of interconnected pores can be simulated and predicted in a few minutes.

“That’s the leap of the work,” Gupta said. “We found the missing link.”



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AI headphones let wearer listen to a single person in a crowd, by looking at them just once

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AI headphones let wearer listen to a single person in a crowd, by looking at them just once


Noise-canceling headphones have gotten very good at creating an auditory blank slate. But allowing certain sounds from a wearer’s environment through the erasure still challenges researchers. The latest edition of Apple’s AirPods Pro, for instance, automatically adjusts sound levels for wearers — sensing when they’re in conversation, for instance — but the user has little control over whom to listen to or when this happens.

A University of Washington team has developed an artificial intelligence system that lets a user wearing headphones look at a person speaking for three to five seconds to “enroll” them. The system, called “Target Speech Hearing,” then cancels all other sounds in the environment and plays just the enrolled speaker’s voice in real time even as the listener moves around in noisy places and no longer faces the speaker.

The team presented its findings May 14 in Honolulu at the ACM CHI Conference on Human Factors in Computing Systems. The code for the proof-of-concept device is available for others to build on. The system is not commercially available.

“We tend to think of AI now as web-based chatbots that answer questions,” said senior author Shyam Gollakota, a UW professor in the Paul G. Allen School of Computer Science & Engineering. “But in this project, we develop AI to modify the auditory perception of anyone wearing headphones, given their preferences. With our devices you can now hear a single speaker clearly even if you are in a noisy environment with lots of other people talking.”

To use the system, a person wearing off-the-shelf headphones fitted with microphones taps a button while directing their head at someone talking. The sound waves from that speaker’s voice then should reach the microphones on both sides of the headset simultaneously; there’s a 16-degree margin of error. The headphones send that signal to an on-board embedded computer, where the team’s machine learning software learns the desired speaker’s vocal patterns. The system latches onto that speaker’s voice and continues to play it back to the listener, even as the pair moves around. The system’s ability to focus on the enrolled voice improves as the speaker keeps talking, giving the system more training data.

The team tested its system on 21 subjects, who rated the clarity of the enrolled speaker’s voice nearly twice as high as the unfiltered audio on average.

This work builds on the team’s previous “semantic hearing” research, which allowed users to select specific sound classes — such as birds or voices — that they wanted to hear and canceled other sounds in the environment.

Currently the TSH system can enroll only one speaker at a time, and it’s only able to enroll a speaker when there is not another loud voice coming from the same direction as the target speaker’s voice. If a user isn’t happy with the sound quality, they can run another enrollment on the speaker to improve the clarity.

The team is working to expand the system to earbuds and hearing aids in the future.

Additional co-authors on the paper were Bandhav Veluri, Malek Itani and Tuochao Chen, UW doctoral students in the Allen School, and Takuya Yoshioka, director of research at AssemblyAI. This research was funded by a Moore Inventor Fellow award, a Thomas J. Cabel Endowed Professorship and a UW CoMotion Innovation Gap Fund.



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Theory and experiment combine to shine a new light on proton spin

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Theory and experiment combine to shine a new light on proton spin


Nuclear physicists have long been working to reveal how the proton gets its spin. Now, a new method that combines experimental data with state-of-the-art calculations has revealed a more detailed picture of spin contributions from the very glue that holds protons together. It also paves the way toward imaging the proton’s 3D structure.

The work was led by Joseph Karpie, a postdoctoral associate in the Center for Theoretical and Computational Physics (Theory Center) at the U.S. Department of Energy’s Thomas Jefferson National Accelerator Facility.

He said that this decades-old mystery began with measurements of the sources of the proton’s spin in 1987. Physicists originally thought that the proton’s building blocks, its quarks, would be the main source of the proton’s spin. But that’s not what they found. It turned out that the proton’s quarks only provide about 30% of the proton’s total measured spin. The rest comes from two other sources that have so far proven more difficult to measure.

One is the mysterious but powerful strong force. The strong force is one of the four fundamental forces in the universe. It’s what “glues” quarks together to make up other subatomic particles, such as protons or neutrons. Manifestations of this strong force are called gluons, which are thought to contribute to the proton’s spin. The last bit of spin is thought to come from the movements of the proton’s quarks and gluons.

“This paper is sort of a bringing together of two groups in the Theory Center who have been working toward trying to understand the same bit of physics, which is how do the gluons that are inside of it contribute to how much the proton is spinning around,” he said.

He said this study was inspired by a puzzling result that came from initial experimental measurements of the gluons’ spin. The measurements were made at the Relativistic Heavy Ion Collider, a DOE Office of Science user facility based at Brookhaven National Laboratory in New York. The data at first seemed to indicate that the gluons may be contributing to the proton’s spin. They showed a positive result.

But as the data analysis was improved, a further possibility appeared.

“When they improved their analysis, they started to get two sets of results that seemed quite different, one was positive and the other was negative,” Karpie explained.

While the earlier positive result indicated that the gluons’ spins are aligned with that of the proton, the improved analysis allowed for the possibility that the gluons’ spins have an overall negative contribution. In that case, more of the proton spin would come from the movement of the quarks and gluons, or from the spin of the quarks themselves.

This puzzling result was published by the Jefferson Lab Angular Momentum (JAM) collaboration.

Meanwhile, the HadStruc collaboration had been addressing the same measurements in a different way. They were using supercomputers to calculate the underlying theory that describes the interactions among quarks and gluons in the proton, Quantum Chromodynamics (QCD).

To equip supercomputers to make this intense calculation, theorists somewhat simplify some aspects of the theory. This somewhat simplified version for computers is called lattice QCD.

Karpie led the work to bring together the data from both groups. He started with the combined data from experiments taken in facilities around the world. He then added the results from the lattice QCD calculation into his analysis.

“This is putting everything together that we know about quark and gluon spin and how gluons contribute to the spin of the proton in one dimension,” said David Richards, a Jefferson Lab senior staff scientist who worked on the study.

“When we did, we saw that the negative things didn’t go away, but they changed dramatically. That meant that there’s something funny going on with those,” Karpie said.

Karpie is lead author on the study that was recently published in Physical Review D. He said the main takeaway is that combining the data from both approaches provided a more informed result.

“We’re combining both of our datasets together and getting a better result out than either of us could get independently. It’s really showing that we learn a lot more by combining lattice QCD and experiment together in one problem analysis,” said Karpie. “This is the first step, and we hope to keep doing this with more and more observables as well as we make more lattice data.”

The next step is to further improve the datasets. As more powerful experiments provide more detailed information on the proton, these data begin painting a picture that goes beyond one dimension. And as theorists learn how to improve their calculations on ever-more powerful supercomputers, their solutions also become more precise and inclusive.

The goal is to eventually produce a three-dimensional understanding of the proton’s structure.

“So, we learn our tools do work on the simpler one-dimension scenario. By testing our methods now, we hopefully will know what we need to do when we want to move up to do 3D structure,” Richards said. “This work will contribute to this 3D image of what a proton should look like. So it’s all about building our way up to the heart of the problem by doing this easier stuff now.”



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