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    Towards more accurate 3D object detection for robots and self-driving cars

    Robotics and autonomous vehicles are among the most rapidly growing domains in the technological landscape, with the potential to make work and transportation safer and more efficient. Since both robots and self-driving cars need to accurately perceive their surroundings, 3D object detection methods are an active area of study. Most 3D object detection methods employ LiDAR sensors to create 3D point clouds of their environment. Simply put, LiDAR sensors use laser beams to rapidly scan and measure the distances of objects and surfaces around the source. However, using LiDAR data alone can lead to errors due to the high sensitivity of LiDAR to noise, especially in adverse weather conditions like during rainfall.
    To tackle this issue, scientists have developed multi-modal 3D object detection methods that combine 3D LiDAR data with 2D RGB images taken by standard cameras. While the fusion of 2D images and 3D LiDAR data leads to more accurate 3D detection results, it still faces its own set of challenges, with accurate detection of small objects remaining difficult. The problem mainly lies in properly aligning the semantic information extracted independently from the 2D and 3D datasets, which is hard due to issues such as imprecise calibration or occlusion.
    Against this backdrop, a research team led by Professor Hiroyuki Tomiyama from Ritsumeikan University, Japan, has developed an innovative approach to make multi-modal 3D object detection more accurate and robust. The proposed scheme, called “Dynamic Point-Pixel Feature Alignment Network” (DPPFA−Net), is described in their paper published in IEEE Internet of Things Journal on 3 November 2023.
    The model comprises an arrangement of multiple instances of three novel modules: the Memory-based Point-Pixel Fusion (MPPF) module, the Deformable Point-Pixel Fusion (DPPF) module, and the Semantic Alignment Evaluator (SAE) module. The MPPF module is tasked with performing explicit interactions between intra-modal features (2D with 2D and 3D with 3D) and cross-modal features (2D with 3D). The use of the 2D image as a memory bank reduces the difficulty in network learning and makes the system more robust against noise in 3D point clouds. Moreover, it promotes the use of more comprehensive and discriminative features.
    In contrast, the DPPF module performs interactions only at pixels in key positions, which are determined via a smart sampling strategy. This allows for feature fusion in high resolutions at a low computational complexity. Finally, the SAE module helps ensure semantic alignment between both data representations during the fusion process, which mitigates the issue of feature ambiguity.
    The researchers tested DPPFA−Net by comparing it to the top performers for the widely used KITTI Vision Benchmark. Notably, the proposed network achieved average precision improvements as high as 7.18% under different noise conditions. To further test the capabilities of their model, the team created a new noisy dataset by introducing artificial multi-modal noise in the form of rainfall to the KITTI dataset. The results show that the proposed network performed better than existing models not only in the face of severe occlusions but also under various levels of adverse weather conditions. “Our extensive experiments on the KITTI dataset and challenging multi-modal noisy cases reveal that DPPFA-Net reaches a new state-of-the-art,” remarks Prof. Tomiyama.
    Notably, there are various ways in which accurate 3D object detection methods could improve our lives. Self-driving cars, which rely on such techniques, have the potential to reduce accidents and improve traffic flow and safety. Furthermore, the implications in the field of robotics should not be understated. “Our study could facilitate a better understanding and adaptation of robots to their working environments, allowing a more precise perception of small targets,” explains Prof. Tomiyama. “Such advancements will help improve the capabilities of robots in various applications.” Another use for 3D object detection networks is the pre-labeling of raw data for deep-learning perception systems. This would greatly reduce the cost of manual annotation, accelerating developments in the field.
    Overall, this study is a step in the right direction towards making autonomous systems more perceptive and assisting us better with human activities. More

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    Climate – Science News

    Climate – Science News


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    Speed bumps under Thwaites Glacier could help slow its flow to the sea
    /article/speed-bumps-thwaites-glacier

    Tue, 19 Dec 2023 13:00:00 +0000

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    SAN FRANCISCO — Most of the news regarding the Thwaites Glacier, a Florida-sized slab of ice that is melting and currently contributing about 4 percent of global sea level rise, is bad. But a bit of good news may have emerged.

    A seismic survey of the bed beneath an upstream section of Thwaites has revealed rough high-rises of earth under the Antarctic glacier, which are comparable in height to the Manhattan skyline, glaciologist Coen Hofstede reported December 12 at a news conference during the American Geophysical Union fall meeting. These rugged rises may be snagging the glacier’s underbelly, slowing its flow toward the ocean and mitigating global sea level rise.

    Glaciers flow somewhat like rivers, but much slower. Where Thwaites outlets into the ocean, it connects to a floating shelf of ice that braces and partially restrains the glacier. That ice shelf was once pinned upon an underwater mountain, which helped stabilize it (SN: 12/13/21). But now the shelf is so deteriorated that it’s basically unhitched, Erin Pettit, a glaciologist at Oregon State University in Corvallis, said at the news event.

    Fortunately, though, the glacier “is not going to suddenly flow off land,” thanks partly to what’s been discovered upstream, said Pettit, who was not involved in the discovery.  

    To image Thwaites’ underbelly, researchers used a tractorlike vehicle (background, center) to haul a seismic vibrator truck on a sled, as well as a 1.5-kilometer-long chain of seismometers (foreground), across the glacier’s surface. A caboose-train (left) used for cooking, eating and repairs accompanied the vibrator truck across the ice. Coen Hofstede

    More than 70 kilometers inland from Thwaites’ ice shelf, Hofstede and his colleagues conducted a seismic survey to probe the glacier’s underbelly. The team attached a 1.5-kilometer-long daisy-chain of seismometers to a vehicle equipped with a vibrating plate. Then they drove a roughly 200-kilometer-long stretch of the glacier, using the plate to generate seismic waves and the seismometers to record the waves’ reflectance off layers of ice and earth below. “It’s almost like radar,” said Hofstede, of the Alfred Wegener Institute Helmholtz Center for Polar and Marine Research in Bremerhaven, Germany.

    A Pisten Bully (center left), a tracked vehicle able to maneuver on the ice, tows seismic equipment (red) across Thwaites Glacier. A second Pisten Bully (right) hauls the
    accommodation train with the crew’s sleeping tents.Ole Zeising

    The seismic waves revealed rises under Thwaites that are 10 to 20 kilometers long and toothed with blocks of sediment. These blocks stood up to 100 meters tall above the rises and stretched for up to several kilometers horizontally.

    The data showed that the upstream faces of these blocks appear to be under greater pressure than their downstream sides, and that there might be layers of deformed ice within the glacier above the rises. Hofstede hypothesizes that the rises and blocks are slowing Thwaites’ flow as its ice presses against them.

    Using computers to simulate the flow of Thwaites glacier shows that “it gets hung up on tall features,” said glaciologist Ben Smith of the University of Washington in Seattle, who was not involved in the work.

    The rises are probably related to a rift system, an area where tectonic forces have pulled the ground apart, Hofstede said. Under Thwaites, these rifts run roughly perpendicular to the glacier’s ice flow, sort of like speed bumps on a street.

    The findings will allow for more nuanced simulations of the glacier’s evolution, Hofstede said, which are crucial for understanding rates of sea level rise.

    ]] >

    Invisible comet tails of mucus slow sinking flakes of ‘marine snow’
    /article/comet-tails-mucus-marine-snow

    Mon, 18 Dec 2023 18:00:00 +0000

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    WASHINGTON — Tiny, sinking flakes of detritus in the ocean fall more slowly thanks to the goop that surrounds each flake, new observations reveal.

    The invisible mucus makes “comet tails” that surround each flake, physicist Rahul Chajwa of Stanford University reported November 19 at the American Physical Society’s Division of Fluid Dynamics meeting. Those mucus tails slow the speed at which the flakes fall. That could affect the rate at which carbon gets sequestered deep in the oceans, making the physics of this sticky goo important for understanding Earth’s climate.

    Although scientists knew the goo was a component of the “marine snow” that falls in the ocean, they hadn’t previously measured its impact on sinking speed.

    Marine snow is made of dead and living phytoplankton, decaying organic matter, feces, bacteria and other aquatic sundries, all wrapped up in mucus that’s produced by the organisms. Like the gunk known for clogging airways during respiratory virus season, the mucus is what’s called a viscoelastic fluid (SN: 3/17/16). That’s something that flows like a liquid but exhibits elastic behavior as well, springing back after being stretched.

    This underwater blizzard is not easy to study. When observed in the ocean, the particles sink swiftly out of view. In the laboratory, the particles can be viewed for longer periods, but the trek ashore degrades the delicate marine snow and kills the living organisms within it.

    Tiny particles (white dots) within a seawater-filled chamber were used to measure the rate at which fluid flows around this flake of marine snow as it falls. The chamber is designed to keep the sinking snowflake in view of the camera.

    So Chajwa and colleagues built a physics lab at sea. Aboard a research vessel in the Gulf of Maine, the team collected marine snow particles in traps 80 meters below the water’s surface. Then they loaded their catch into a device onboard, designed to observe the particles falling.

    Nicknamed “the gravity machine,” it’s a fluid-filled wheel that rotates in order to keep an individual flake in view of a camera. It’s a bit like a hamster wheel for falling debris. As the flake sinks, the wheel turns so as to move the snow in the opposite direction, allowing the snowfall to be observed indefinitely. The gravity machine was itself mounted on a gimbal designed to stave off sloshing from the rocking of the ship.

    “It’s a very nice compromise between the real marine snow that you get in the ocean versus what you can do practically in the lab,” says biophysicist Anupam Sengupta of the University of Luxembourg, who was not involved with the research.

    To observe how the fluid flowed around the particles, the researchers added tiny beads within the fluid in the gravity machine. That revealed the rate of fluid flow around the particles. The speed of fluid flow was slowed in a comet tail–shaped region around the particle, revealing the invisible mucus that sinks along with the particle.

    Marine snow particles (one shown) are surrounded with invisible mucus. Drag the slider to see how fluid flows around the flake as it falls. Slower speeds (yellow) reveal mucus that trails the flake in a comet tail–shape (red dotted line). Left: Rahul Chajwa and Manu Prakash/PrakashLab/Stanford UniversityRight: Rahul Chajwa and Manu Prakash/PrakashLab/Stanford University

    The particles sank at speeds up to 200 meters per day. The mucus played a big role in sinking speed. “The more the mucus, the slower the particles sink,” Chajwa says. On average, the mucus causes the marine snow particles to linger twice as long in the upper 100 meters of the ocean as they otherwise would, Chajwa and colleagues determined.

    If it falls deep enough, marine snow can sequester carbon away from the atmosphere. That’s because living phytoplankton, like plants, take in carbon dioxide and release oxygen. When phytoplankton form marine snow, they take that carbon along with them as they sink. If a flake reaches the ocean floor, it can settle into a scum at the bottom that caches that carbon over long time periods. The faster the particles sink, the more likely they are to make it to the abyss before being eaten by critters (SN: 6/23/22).

    Knowing how fast the particles sink is important for calculating the ocean’s impact on Earth’s climate, and how that might change as the climate warms, the researchers say. The oceans are major players in the planet’s carbon cycle (SN: 12/2/21), and scientists estimate that oceans have taken up roughly 30 percent of the carbon dioxide released by humans since industrialization. Chajwa and colleagues hope that their results can be used to refine climate models, which currently do not take the mucus into account.

    So this mucus is nothing to sneeze at. “We’re talking about microscopic physics,” says Stanford physicist Manu Prakash, a coauthor of the work, which is also reported in a paper submitted October 3 at arXiv.org. “But multiply that by the volume of the ocean … that’s what gives you the scale of the problem.”

    ]] >

    3 Antarctic glaciers show rapidly accelerated ice loss from ocean warming
    /article/3-antarctic-glaciers-rapid-loss-climate-change

    Mon, 18 Dec 2023 12:00:00 +0000

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    SAN FRANCISCO — Several Antarctic glaciers are undergoing dramatic acceleration and ice loss. Hektoria Glacier, the worst affected, has quadrupled its sliding speed and lost 25 kilometers of ice off its front in just 16 months, scientists say.

    The rapid retreat “is really unheard of,” says Mathieu Morlighem, a glaciologist at Dartmouth College who was not part of the team reporting these findings.

    The collapse was triggered by unusually warm ocean temperatures, which caused sea ice to retreat. This allowed a series of large waves to hit a section of coastline that is normally shielded from them. “What we’re seeing here is an indication of what could happen elsewhere” in Antarctica, says Naomi Ochwat, a glaciologist at the University of Colorado Boulder who presented the findings December 11 at the American Geophysical Union meeting.

    Hektoria Glacier, Green Glacier, and Crane Glacier sit near the tip of the Antarctic Peninsula, which reaches up toward South America. The crescent moon–shaped bay, called the Larsen B Embayment, once seemed stable. As these glaciers oozed off the coastline, their ice used to merge into a floating slab around 200 meters thick. This slab, called the Larsen B Ice Shelf, was about the size of Rhode Island and filled the entire bay.

    Having existed for over 10,000 years, this ice shelf buttressed and stabilized the glaciers flowing into it. But during a warm summer in 2002, it suddenly fragmented into thousands of skinny icebergs (SN: 3/27/02).

    Hektoria, Green, and Crane glaciers — no longer contained by the ice shelf —  began to flow into the ocean several times faster than they had before, shedding billions of tons of ice over the next decade.

    Then starting in 2011, the hemorrhaging slowed down. The thin veneer of sea ice that forms over the bay each winter began to persist year round, preserved by a series of cold summers. This “landfast ice,” attached firmly to the coastline, grew five to 10 meters thick, stabilizing the glaciers. Their floating tongues gradually advanced back into the bay. But things changed abruptly in early 2022. On January 19 and 20, the landfast ice disintegrated into fragments, which drifted away.

    Satellite images taken just 10 days apart reveal the dramatic breakup of sea ice in Antarctica’s Larsen B Embayment. On January 16, 2022, sea ice filled the bay (left). By January 26 (right), the ice had fractured and was drifting away following a series of powerful waves that struck the bay several days earlier. Left: Joshua Stevens, MODIS/LANCE/EOSDIS/NASA, WORLDVIEW/GIBS/NASARight: Joshua Stevens, MODIS/LANCE/EOSDIS/NASA, WORLDVIEW/GIBS/NASA

    Using data from ocean buoys farther north, Ochwat and colleagues determined that a series of powerful waves, higher than 1.5 meters, had swept in from the northeast — cracking apart the landfast ice. Those waves were highly unusual for this area.

    The Southern Ocean, which encircles Antarctica, holds some of the world’s roughest waters. The Antarctic Peninsula extends up into this turbulent region, but its east side, where the Larsen B Embayment sits, rarely feels the waves. It is normally protected by several hundred kilometers of pack ice — floes of sea ice, pressed together by ocean currents — that dampen the waves, leaving the waters near Larsen as flat as a mirror.

    In 2022, water temperatures near the surface of the Southern Ocean rose several tenths of a degree Celsius higher than normal, causing pack ice to shrink and peel away from the peninsula. This exposed the area to waves, which then broke up the landfast sea ice.

    The glaciers accelerated as their floating tongues, no longer held in place, fragmented into bergs. Crane Glacier lost 11 kilometers of ice, nearly erasing its floating tongue; Green Glacier lost 18 kilometers, encompassing all of its floating ice.

    Hektoria lost all 15 kilometers of its floating ice — followed by another 10 kilometers of ice that is normally more stable, because it rests on the seafloor. That “is faster than any tidewater glacier retreat that we know of,” Ochwat says.

    The previous standout, Alaska’s Columbia Glacier, had lost 20 kilometers of ice in 30 years, records show. But Hektoria lost its 10 kilometers of nonfloating ice in just five months — including 2.5 kilometers that crumbled in a 3-day period.

    All of this suggests that people trying to predict sea level rise need to consider sea ice, Morlighem says. Up until now, “its role in [glacier] dynamics has been completely ignored.”

    Ochwat is waiting to see what will happen as the current Antarctic summer heats up between December and March. Hektoria and the other glaciers have been retreating only during summer months, when sea ice is absent; they pause during winter, when the surface of the bay freezes for a few months.

    If Antarctic sea ice continues to shrink, as it has since 2022, it could spell trouble, says study coauthor Ted Scambos, a glaciologist also at UC Boulder. “You’re going to have a longer section of coastline where wave action can act on the front of ice shelves and glaciers,” potentially accelerating glacial retreat.

    ]] >

    COP28 nations agreed to ‘transition’ from fossil fuels. That’s too slow, experts say
    /article/cop28-fossil-fuels-climate-change

    Fri, 15 Dec 2023 15:30:00 +0000

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    Days of contentious wrangling in Dubai at the United Nations’ 28th annual climate summit ended December 13 with a historic agreement to “transition away” from fossil fuels and accelerate climate action over the next decade. The organization touted the agreement as a moment of global solidarity, marking “the beginning of the end” of the fossil fuel era.

    But the final agreement reached at COP28, signed by nearly 200 nations, did not include language that explicitly mandated phasing out fossil fuel energy, deeply frustrating many nations as well as climate scientists and activists.

    The agreement is considered the world’s first “global stocktake,” an inventory of climate actions and progress made since the 2015 Paris Agreement to limit global warming to “well below” 2 degrees Celsius above the preindustrial average (SN: 12/12/15).

    It acknowledges the conclusions of scientific research that greenhouse gas emissions will need to be cut by 43 percent by 2030 compared with 2019 levels, in order to limit global warming to 1.5 degrees Celsius by the end of the century. It then calls on nations to speed up climate actions before 2030 so as to reach global net zero by 2050 — in which greenhouse gases entering the atmosphere are balanced by their removal from the atmosphere. Among the actions called for are increasing global renewable energy generation, phasing down coal power and phasing out fossil fuel subsidies.

    But among many scientists gathered in San Francisco at the American Geophysical Union’s annual meeting to discuss climate change’s impacts to Earth’s atmosphere, polar regions, oceans and biosphere, the reaction to the language in the agreement was more frustrated than celebratory.

    “The beginning of the end? I wish it was the middle of the end,” says climate scientist Luke Parsons of the Nature Conservancy, who is based in Durham, N.C. “But you have to start somewhere, I guess.”

    It is a step forward, says Ted Scambos, a glaciologist at the University of Colorado Boulder. “Saying it out loud, that we are aiming to phase out fossil fuels, is huge.”

    It’s not a moment too soon: The globe is already experiencing many climate change–linked extreme weather events, including the hottest 12 months ever recorded (SN: 11/9/23). Still, Scambos says, “it’s a tribute to the science and the negotiators that we can take this step now, before the disastrous global impacts truly get underway.” But, he added, “I fear that the pace [of future climate action] will … still be driven by impacts arriving at our collective doors.”

    Other researchers had a grimmer take.

    “It was weak sauce,” says climate scientist Michael Mann of the University of Pennsylvania. “What we really need is a commitment to phase out fossil fuels, on a very specific timeline: We’re going to reduce carbon emissions by 50 percent this decade, bring them down to zero mid-century. Instead, they agreed to transition away from fossil fuels — the analogy that I use is, you’re diagnosed with diabetes, and you tell your doctor you’re going to transition away from doughnuts. That’s not going to cut it. It didn’t meet the moment.”

    Eric Rignot, a glaciologist at the University of California, Irvine, called the agreement “deeply disappointing and misleading,” noting that it didn’t include any language specifically calling for phasing out fossil fuels. Furthermore, he says, “COP28 keeps entertaining the idea that 1.5 degrees Celsius may be achievable, but everyone is offtrack to meet that goal. [And] for ice sheets and glaciers, even 1.5 degrees is not sustainable.”  There already are fears, for instance, that the melting of Greenland’s ice sheet can’t be stopped (SN: 8/9/21).

    Even if the world stays close to that average temperature, “the ice sheets are going to be retreating,” says Rob DeConto, a glaciologist at the University of Massachusetts at Amherst. “But you start getting out toward the end of the century, and all hell is going to break loose if we go much above 1.5. You’re talking about actually exceeding the limits of adaptation around so much of our coastlines.”  

    On December 12, the eighth anniversary of the signing of the Paris Agreement, the European Union’s Copernicus Climate Change Service noted that the world has, in effect, “lost” 19 years by delaying action to reduce fossil fuel emissions. Back in 2015, climate projections suggested that Earth’s average temperature would reach the 1.5 degrees C threshold by the year 2045 — then 30 years away. Now, projections show that the planet may reach that benchmark by 2034, just 11 years in the future.

    “We’ve got a shrinking window of opportunity,” Mann says. “And that window of opportunity will close if we don’t make dramatic and immediate reductions to our carbon emissions.”

    ]] >

    Ocean heat waves often lurk out of sight
    /article/ocean-heat-waves-below-surface-common

    Thu, 14 Dec 2023 19:30:00 +0000

    /?p=3134157 More

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    New soft robots roll like tires, spin like tops and orbit like moons

    Researchers have developed a new soft robot design that engages in three simultaneous behaviors: rolling forward, spinning like a record,and following a path that orbits around a central point. The device, which operates without human or computer control, holds promise for developing soft robotic devices that can be used to navigate and map unknown environments.
    The new soft robots are called twisted ringbots. They are made of ribbon-like liquid crystal elastomers that are twisted — like a rotini noodle — and then joined together at the end to form a loop that resembles a bracelet. When the robots are placed on a surface that is at least 55 degrees Celsius (131 degrees Fahrenheit), which is hotter than the ambient air, the portion of the ribbon touching the surface contracts, while the portion of the ribbon exposed to the air does not. This induces a rolling motion; the warmer the surface, the faster the robot rolls.
    “The ribbon rolls on its horizontal axis, giving the ring forward momentum,” says Jie Yin, corresponding author of a paper on the work and an associate professor of mechanical and aerospace engineering at North Carolina State University.
    The twisted ringbot also spins along its central axis, like a record on a turntable. And as the twisted ringbot moves forward it travels in an orbital path around a central point, essentially moving in a large circle. However, if the twisted ringbot encounters a boundary — like the wall of a box — it will travel along the boundary.
    “This behavior could be particularly useful for mapping unknown environments,” Yin says.
    The twisted ringbots are examples of devices whose behavior is governed by physical intelligence, meaning their actions are determined by their structural design and the materials they are made of, rather than being directed by a computer or human intervention.
    The researchers are able to fine-tune the behavior of the twisted ringbot by engineering the geometry of the device. For example, they can control the direction that the twisted ringbot spins by twisting the ribbon one way or the other. Speed can be influenced by varying the width of the ribbon, the number of twists in the ribbon, and so on.

    In proof-of-concept testing, the researchers showed that the twisted ringbot was able to follow the contours of various confined spaces.
    “Regardless of where the twisted ringbot is introduced to these spaces, it is able to make its way to a boundary and follow the boundary lines to map the space’s contours — whether it’s a square, a triangle and so on,” says Fangjie Qi, first author of the paper and a Ph.D. student at NC State. “It also identifies gaps or damage in the boundary.
    “We were also able to map the boundaries of more complex spaces by introducing two twisted ringbots into the space, with each robot rotating in a different direction,” Qi says. “This causes them to take different paths along the boundary. And by comparing the paths of both twisted ringbots, we’re able to capture the contours of the more complex space.”
    “In principle, no matter how complex a space is, you would be able to map it if you introduced enough of the twisted ringbots to map the whole picture, each one giving part of it,” says Yin. “And, given that these are relatively inexpensive to produce, that’s viable.
    “Soft robotics is still a relatively new field,” Yin says. “Finding new ways to control the movement of soft robots in a repeatable, engineered way moves the field forward. And advancing our understanding of what is possible is exciting.”
    The paper, “Defected Twisted Ring Topology For Autonomous Periodic Flip-Spin-Orbit Soft Robot,” will be published the week of January 8 in Proceedings of the National Academy of Sciences. The paper was co-authored by Yanbin Li and Yao Zhao, postdoctoral researchers at NC State; Yaoye Hong, a recent Ph.D. graduate of NC State; and Haitao Qing, a Ph.D. student at NC State.
    The work was done with support from the National Science Foundation under grants 2005374 and 2126072. More

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    New AI tool accurately detects COVID-19 from chest X-rays

    Researchers have developed a groundbreaking Artificial Intelligence (AI) system that can rapidly detect COVID-19 from chest X-rays with more than 98% accuracy. The study results have just been published in Nature Scientific Reports.
    Corresponding author Professor Amir H Gandomi, from the University of Technology Sydney (UTS) Data Science Institute, said there was a pressing need for effective automated tools to detect COVID-19, given the significant impact on public health and the global economy.
    “The most widely used COVID-19 test, real time polymerase chain reaction (PCR), can be slow and costly, and produce false-negatives. To confirm a diagnosis, radiologists need to manually examine a CT scans or X-rays, which can be time consuming and prone to error,” said Professor Gandomi.
    “The new AI system could be particularly beneficial in countries experiencing high levels of COVID-19 where there is a shortage of radiologists. Chest X-rays are portable, widely available and provide lower exposure to ionizing radiation than CT scans,” he said.
    Common symptoms of COVID-19 include fever, cough, difficulty breathing and a sore throat, however it can be difficult to distinguish COVID-19 from Flu and other types of pneumonia.
    The new AI system uses a deep learning-based algorithm called a Custom Convolutional Neural Network (Custom-CNN) that is able to quickly and accurately distinguish between COVID-19 cases, normal cases, and pneumonia in X-ray images.
    “Deep learning offers an end-to-end solution, eliminating the need to manually search for biomarkers. The Custom-CNN model streamlines the detection process, providing a faster and more accurate diagnosis of COVID-19,” said Professor Gandomi.

    “If a PCR test or rapid antigen test shows a negative or inconclusive result, due to low sensitivity, patients may require further examination via radiological imaging to confirm or rule out the virus’s presence. In this situation the new AI system could prove beneficial.
    “While radiologists play a crucial role in medical diagnosis, AI technology can assist them in making accurate and efficient diagnoses,” said Professor Gandomi.
    The performance of the Custom-CNN model was evaluated via a comprehensive comparative analysis, with accuracy as the performance criterion. The results showed that the new model outperforms the other AI diagnostic models.
    Fast and accurate diagnosis of COVID-19 can ensure patients get the correct treatment, including COVID-19 antivirals, which work best if taken within five days of the onset of symptoms. It could also help them isolate and protect others from getting infected, reducing pandemic outbreaks.
    This breakthrough represents a significant step in combatting the ongoing challenges posed by the pandemic, potentially transforming the landscape of COVID-19 diagnosis and management. More

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    Researchers develop algorithm to determine how cellular ‘neighborhoods’ function in tissues

    Researchers from Children’s Hospital of Philadelphia (CHOP) have developed a new AI-powered algorithm to help understand how different cells organize themselves into particular tissues and communicate with one another. This new tool was tested on two types of cancer tissues to reveal how these “neighborhoods” of cells interact with one another to evade therapy, and more studies could reveal more information about the function of these cells in the tumor microenvironment.
    The findings were published online today by the journal Nature Methods.
    To understand how different cells organize themselves to support the functions of a tissue, researchers proposed the concept of tissue cellular neighborhoods (TCNs) to describe functional units in which different, recurrent cell types work together to support specific tissue functions. Across individuals, the functions of these TCNs would remain the same. However, translating the huge amount of information in spatial omics data into models and hypotheses that can be interpreted and tested by researchers requires advanced AI algorithms.
    “It is very difficult to study the tissue microenvironment, how certain cells organize, behave and communicate with one another,” said senior study author Kai Tan, PhD, an investigator in the Center for Childhood Cancer Research at CHOP and a professor in the Department of Pediatrics and the Perelman School of Medicine at the University of Pennsylvania. “Until recent advances in so-called spatial omics technology, it was impossible to spatially characterize more than 100 proteins or hundreds or even thousands of genes across a piece of tissue, which might be home to hundreds of thousands of cells and their respective genes.”
    In this study, researchers developed the deep-learning-based CytoCommunity algorithm to identify TCNs based on cell identities of a tissue sample, their spatial distributions as well as patient clinical data, which can help researchers better understand how these neighborhoods of cells are organized and are associated with certain clinical outcomes. In this study, tissue samples from breast and colorectal tumors were used because of a high volume of data available, enough to train the algorithm to identify TCNs associated with high-risk disease subtypes.
    By using CytoCommunity for breast and colorectal cancer data, the algorithm revealed new fibroblast-enriched TCNs and granulocyte-enriched TCNs specific to high-risk breast cancer and colorectal cancer, respectively.
    “Since we were able to prove the effectiveness of CytoCommunity, the next step is to apply this algorithm to both healthy and diseased tissue data generated by research consortia such as HuBMAP (Human BioMolecular Atlas Program) and HTAN (Human Tumor Atlas Network)” Tan said. “For instance, using data from childhood cancers such as leukemia, neuroblastoma and high-grade gliomas, we hope to find tissue cellular neighborhoods that might be associated with responses to certain therapies and combine our findings with genetic data to help determine which genetic pathways may be involved at the cellular and molecular levels.”
    This study was supported by National Institutes of Health grant CA233285, HL165442 and HL156090, a grant from the Chan Zuckerberg Initiative (AWD-2021-237920), a grant from the Leona M. and Harry B Helmsley Charitable Trust (no. 2008-04062), a National Natural Science Foundation of China grant no. 62002277, a grant from the Young Talent Fund of University Association for Science and Technology in Shaanxi (no. 20210101), a grant from the Fundamental Research Funds for the Central Universities (no. QTZX23051), and National Natural Science Foundation of China grant nos. 62132015 and U22A2037. More

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    Soft robotic, wearable device improves walking for individual with Parkinson’s disease

    Freezing is one of the most common and debilitating symptoms of Parkinson’s disease, a neurodegenerative disorder that affects more than 9 million people worldwide. When individuals with Parkinson’s disease freeze, they suddenly lose the ability to move their feet, often mid-stride, resulting in a series of staccato stutter steps that get shorter until the person stops altogether. These episodes are one of the biggest contributors to falls among people living with Parkinson’s disease.
    Today, freezing is treated with a range of pharmacological, surgical or behavioral therapies, none of which are particularly effective.
    What if there was a way to stop freezing altogether?
    Researchers from the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) and the Boston University Sargent College of Health & Rehabilitation Sciences have used a soft, wearable robot to help a person living with Parkinson’s walk without freezing. The robotic garment, worn around the hips and thighs, gives a gentle push to the hips as the leg swings, helping the patient achieve a longer stride.
    The device completely eliminated the participant’s freezing while walking indoors, allowing them to walk faster and further than they could without the garment’s help.
    “We found that just a small amount of mechanical assistance from our soft robotic apparel delivered instantaneous effects and consistently improved walking across a range of conditions for the individual in our study,” said Conor Walsh, the Paul A. Maeder Professor of Engineering and Applied Sciences at SEAS and co-corresponding author of the study.
    The research demonstrates the potential of soft robotics to treat this frustrating and potentially dangerous symptom of Parkinson’s disease and could allow people living with the disease to regain not only their mobility but their independence.

    The research is published in Nature Medicine.
    For over a decade, Walsh’s Biodesign Lab at SEAS has been developing assistive and rehabilitative robotic technologies to improve mobility for individuals’ post-stroke and those living with ALS or other diseases that impact mobility. Some of that technology, specifically an exosuit for post-stroke gait retraining, received support from the Wyss Institute for Biologically Inspired Engineering, and was licensed and commercialized by ReWalk Robotics.
    In 2022, SEAS and Sargent College received a grant from the Massachusetts Technology Collaborative to support the development and translation of next-generation robotics and wearable technologies. The research is centered at the Move Lab, whose mission is to support advances in human performance enhancement with the collaborative space, funding, R&D infrastructure, and experience necessary to turn promising research into mature technologies that can be translated through collaboration with industry partners.
    This research emerged from that partnership.
    “Leveraging soft wearable robots to prevent freezing of gait in patients with Parkinson’s required a collaboration between engineers, rehabilitation scientists, physical therapists, biomechanists and apparel designers,” said Walsh, whose team collaborated closely with that of Terry Ellis, Professor and Physical Therapy Department Chair and Director of the Center for Neurorehabilitation at Boston University.
    The team spent six months working with a 73-year-old man with Parkinson’s disease, who — despite using both surgical and pharmacologic treatments — endured substantial and incapacitating freezing episodes more than 10 times a day, causing him to fall frequently. These episodes prevented him from walking around his community and forced him to rely on a scooter to get around outside.

    In previous research, Walsh and his team leveraged human-in-the-loop optimization to demonstrate that a soft, wearable device could be used to augment hip flexion and assist in swinging the leg forward to provide an efficient approach to reduce energy expenditure during walking in healthy individuals.
    Here, the researchers used the same approach but to address freezing. The wearable device uses cable-driven actuators and sensors worn around the waist and thighs. Using motion data collected by the sensors, algorithms estimate the phase of the gait and generate assistive forces in tandem with muscle movement.
    The effect was instantaneous. Without any special training, the patient was able to walk without any freezing indoors and with only occasional episodes outdoors. He was also able to walk and talk without freezing, a rarity without the device.
    “Our team was really excited to see the impact of the technology on the participant’s walking,” said Jinsoo Kim, former PhD student at SEAS and co-lead author on the study.
    During the study visits, the participant told researchers: “The suit helps me take longer steps and when it is not active, I notice I drag my feet much more. It has really helped me, and I feel it is a positive step forward. It could help me to walk longer and maintain the quality of my life.”
    “Our study participants who volunteer their time are real partners,” said Walsh. “Because mobility is difficult, it was a real challenge for this individual to even come into the lab, but we benefited so much from his perspective and feedback.”
    The device could also be used to better understand the mechanisms of gait freezing, which is poorly understood.
    “Because we don’t really understand freezing, we don’t really know why this approach works so well,” said Ellis. “But this work suggests the potential benefits of a ‘bottom-up’ rather than ‘top-down’ solution to treating gait freezing. We see that restoring almost-normal biomechanics alters the peripheral dynamics of gait and may influence the central processing of gait control.”
    The research was co-authored by Jinsoo Kim, Franchino Porciuncula, Hee Doo Yang, Nicholas Wendel, Teresa Baker and Andrew Chin. Asa Eckert-Erdheim and Dorothy Orzel also contributed to the design of the technology, as well as Ada Huang, and Sarah Sullivan managed the clinical research. It was supported by the National Science Foundation under grant CMMI-1925085; the National Institutes of Health under grant NIH U01 TR002775; and the Massachusetts Technology Collaborative, Collaborative Research and Development Matching Grant. More

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    Using berry phase monopole engineering for high-temperature spintronic devices

    Spintronic devices are electronic devices that utilize the spin of electrons (an intrinsic form of angular momentum possessed by the electron) to achieve high-speed processing and low-cost data storage. In this regard, spin-transfer torque is a key phenomenon that enables ultrafast and low-power spintronic devices. Recently, however, spin-orbit torque (SOT) has emerged as a promising alternative to spin-transfer torque.
    Many studies have investigated the origin of SOT, showing that in non-magnetic materials, a phenomenon called the spin Hall effect (SHE) is key to achieving SOT. In these materials, the existence of a “Dirac band” structure, a specific arrangement of electrons in terms of their energy, is important to achieving large SHE. This is because the Dirac band structure contains “hot spots” for the Berry phase, a quantum phase factor responsible for the intrinsic SHE. Thus, materials with suitable Berry phase hot spots are key to engineering the SHE.
    In this context, the material tantalum silicide (TaSi2) is of great interest as it has several Dirac points near the Fermi level in its band structure, suitable for practicing Berry phase engineering. To demonstrate this, a team of researchers, led by Associate Professor Pham Nam Hai from the Department of Electrical and Electronic Engineering at Tokyo Institute of Technology (Tokyo Tech), Japan, recently investigated the influence of Dirac band hot spots on the temperature dependence of SHE in TaSi2. “Berry phase monopole engineering is an interesting avenue of research as it can give rise to efficient high-temperature SOT spintronic devices such as the magneto-resistive random-access memory,” explains Dr. Hai about the importance of their study. Their findings were published in the journal Applied Physics Letters.
    Through various experiments, the team observed that the SOT efficiency of TaSi2 remained almost unchanged from 62 K to 288 K, which was similar to the behavior of conventional heavy metals. However, upon increasing the temperature further, the SOT efficiency suddenly increased and nearly doubled at 346 K. Moreover, the corresponding SHE also increased in a similar fashion. Notably, this was quite different from the behavior of conventional heavy metals and their alloys. Upon further analysis, the researchers attributed this sudden increase in SHE at high temperatures to Berry phase monopoles.
    “These results provide a strategy to enhance the SOT efficiency at high temperatures via Berry phase monopole engineering,” highlights Dr. Hai.
    Indeed, their study highlights the potential of Berry phase monopole engineering to effectively use the SHE in non-magnetic materials, and provides a new pathway for the development of high-temperature, ultrafast, and low-power SOT spintronic devices. More

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    Functional semiconductor made from graphene

    Researchers at the Georgia Institute of Technology have created the world’s first functional semiconductor made from graphene, a single sheet of carbon atoms held together by the strongest bonds known. Semiconductors, which are materials that conduct electricity under specific conditions, are foundational components of electronic devices. The team’s breakthrough throws open the door to a new way of doing electronics.
    Their discovery comes at a time when silicon, the material from which nearly all modern electronics are made, is reaching its limit in the face of increasingly faster computing and smaller electronic devices. Walter de Heer, Regents’ Professor of physics at Georgia Tech, led a team of researchers based in Atlanta, Georgia, and Tianjin, China, to produce a graphene semiconductor that is compatible with conventional microelectronics processing methods — a necessity for any viable alternative to silicon.
    In this latest research, published in Nature, de Heer and his team overcame the paramount hurdle that has been plaguing graphene research for decades, and the reason why many thought graphene electronics would never work. Known as the “band gap,” it is a crucial electronic property that allows semiconductors to switch on and off. Graphene didn’t have a band gap — until now.
    “We now have an extremely robust graphene semiconductor with 10 times the mobility of silicon, and which also has unique properties not available in silicon,” de Heer said. “But the story of our work for the past 10 years has been, ‘Can we get this material to be good enough to work?'”
    A New Type of Semiconductor
    De Heer started to explore carbon-based materials as potential semiconductors early in his career, and then made the switch to exploring two-dimensional graphene in 2001. He knew then that graphene had potential for electronics.
    “We were motivated by the hope of introducing three special properties of graphene into electronics,” he said. “It’s an extremely robust material, one that can handle very large currents, and can do so without heating up and falling apart.”
    De Heer achieved a breakthrough when he and his team figured out how to grow graphene on silicon carbide wafers using special furnaces. They produced epitaxial graphene, which is a single layer that grows on a crystal face of the silicon carbide. The team found that when it was made properly, the epitaxial graphene chemically bonded to the silicon carbide and started to show semiconducting properties.

    Over the next decade, they persisted in perfecting the material at Georgia Tech and later in collaboration with colleagues at the Tianjin International Center for Nanoparticles and Nanosystems at Tianjin University in China. De Heer founded the center in 2014 with Lei Ma, the center’s director and a co-author of the paper.
    How They Did It
    In its natural form, graphene is neither a semiconductor nor a metal, but a semimetal. A band gap is a material that can be turned on and off when an electric field is applied to it, which is how all transistors and silicon electronics work. The major question in graphene electronics research was how to switch it on and off so it can work like silicon.
    But to make a functional transistor, a semiconducting material must be greatly manipulated, which can damage its properties. To prove that their platform could function as a viable semiconductor, the team needed to measure its electronic properties without damaging it.
    They put atoms on the graphene that “donate” electrons to the system — a technique called doping, used to see whether the material was a good conductor. It worked without damaging the material or its properties.
    The team’s measurements showed that their graphene semiconductor has 10 times greater mobility than silicon. In other words, the electrons move with very low resistance, which, in electronics, translates to faster computing. “It’s like driving on a gravel road versus driving on a freeway,” de Heer said. “It’s more efficient, it doesn’t heat up as much, and it allows for higher speeds so that the electrons can move faster.”
    The team’s product is currently the only two-dimensional semiconductor that has all the necessary properties to be used in nanoelectronics, and its electrical properties are far superior to any other 2D semiconductors currently in development.

    “A long-standing problem in graphene electronics is that graphene didn’t have the right band gap and couldn’t switch on and off at the correct ratio,” said Ma. “Over the years, many have tried to address this with a variety of methods. Our technology achieves the band gap, and is a crucial step in realizing graphene-based electronics.”
    Moving Forward
    Epitaxial graphene could cause a paradigm shift in the field of electronics and allow for completely new technologies that take advantage of its unique properties. The material allows the quantum mechanical wave properties of electrons to be utilized, which is a requirement for quantum computing.
    “Our motivation for doing graphene electronics has been there for a long time, and the rest was just making it happen,” de Heer said. “We had to learn how to treat the material, how to make it better and better, and finally how to measure the properties. That took a very, very long time.”
    According to de Heer, it is not unusual to see yet another generation of electronics on its way. Before silicon, there were vacuum tubes, and before that, there were wires and telegraphs. Silicon is one of many steps in the history of electronics, and the next step could be graphene.
    “To me, this is like a Wright brothers moment,” de Heer said. “They built a plane that could fly 300 feet through the air. But the skeptics asked why the world would need flight when it already had fast trains and boats. But they persisted, and it was the beginning of a technology that can take people across oceans.” More