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  • 125 Shares179 Views

    in Computers Math

    Machine learning used to probe the building blocks of shapes

    Applying machine learning to find the properties of atomic pieces of geometry shows how AI has the power to accelerate discoveries in maths.
    Mathematicians from Imperial College London and the University of Nottingham have, for the first time, used machine learning to expand and accelerate work identifying ‘atomic shapes’ that form the basic pieces of geometry in higher dimensions. Their findings have been published in Nature Communications.
    The way they used artificial intelligence, in the form of machine learning, could transform how maths is done, say the authors. Dr Alexander Kasprzyk from the University of Nottingham said: “For mathematicians, the key step is working out what the pattern is in a given problem. This can be very difficult, and some mathematical theories can take years to discover.”
    Professor Tom Coates, from the Department of Mathematics at Imperial, added: “We have shown that machine learning can help uncover patterns within mathematical data, giving us both new insights and hints of how they can be proved.”
    PhD student Sara Veneziale, from the Department of Mathematics at Imperial, said: “This could be very broadly applicable, such that it could rapidly accelerate the pace at which maths discoveries are made. It’s like when computers were first used in maths research, or even calculators: it’s a step-change in the way we do maths.”
    Defining shapes
    Mathematicians describe shapes using equations, and by analysing these equations can break the shape down into fundamental pieces. These are the building blocks of shapes, the equivalent of atoms, and are called Fano varieties. More

  • 125 Shares109 Views

    in Computers Math

    Birders and AI push bird conservation to the next level

    For the first time, big data and artificial intelligence (AI) are being used to model hidden patterns in nature, not just for one bird species, but for entire ecological communities across continents. And the models follow each species’ full annual life cycle, from breeding to fall migration to nonbreeding grounds, and back north again during spring migration. It begins with the more than 900,000 birders who report their sightings to the Cornell Lab of Ornithology’s eBird program, one of the world’s largest biodiversity science projects. When combined with innovations in technology and artificial intelligence-the same innovations that power self-driving cars and real-time language translation-these sightings are revealing more than ever about patterns of bird biodiversity, and the processes that underlie them.
    The development and application of this revolutionary computational tool is the result of a collaboration between the Cornell Lab of Ornithology and the Cornell Institute for Computational Sustainability. This work is now published in the journal Ecology.
    “This method uniquely tells us which species occur where, when, with what other species, and under what environmental conditions,” said lead author Courtney Davis, a researcher at the Cornell Lab. “With that type of information, we can identify and prioritize landscapes of high conservation value — vital information in this era of ongoing biodiversity loss.”
    “This model is very general and is suitable for various tasks, provided there’s enough data,” Gomes said. “This work on joint bird species distribution modeling is about predicting the presence and absence of species, but we are also developing models to estimate bird abundance — the number of individual birds per species. We’re also aiming to enhance the model by incorporating bird calls alongside visual observations.”
    Cross-disciplinary collaborations like this are necessary for the future of biodiversity conservation, according to Daniel Fink, researcher at the Cornell Lab and senior author of the study.
    “The task at hand is too big for ecologists to do on their own-we need the expertise of our colleagues in computer science and computational sustainability to develop targeted plans for landscape-scale conservation, restoration, and management around the world.”
    This work was funded by the National Science Foundation, The Leon Levy Foundation, The Wolf Creek Foundation, the Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship — a Schmidt Future program, the Air Force Office of Scientific Research, and the U.S. Department of Agriculture’s National Institute of Food and Agriculture. More

  • 88 Shares99 Views

    in Computers Math

    Could future AI crave a favorite food?

    Can artificial intelligence (AI) get hungry? Develop a taste for certain foods? Not yet, but a team of Penn State researchers is developing a novel electronic tongue that mimics how taste influences what we eat based on both needs and wants, providing a possible blueprint for AI that processes information more like a human being.
    Human behavior is complex, a nebulous compromise and interaction between our physiological needs and psychological urges. While artificial intelligence has made great strides in recent years, AI systems do not incorporate the psychological side of our human intelligence. For example, emotional intelligence is rarely considered as part of AI.
    “The main focus of our work was how could we bring the emotional part of intelligence to AI,” said Saptarshi Das, associate professor of engineering science and mechanics at Penn State and corresponding author of the study published recently in Nature Communications. “Emotion is a broad field and many researchers study psychology; however, for computer engineers, mathematical models and diverse data sets are essential for design purposes. Human behavior is easy to observe but difficult to measure and that makes it difficult to replicate in a robot and make it emotionally intelligent. There is no real way right now to do that.”
    Das noted that our eating habits are a good example of emotional intelligence and the interaction between the physiological and psychological state of the body. What we eat is heavily influenced by the process of gustation, which refers to how our sense of taste helps us decide what to consume based on flavor preferences. This is different than hunger, the physiological reason for eating.
    “If you are someone fortunate to have all possible food choices, you will choose the foods you like most,” Das said. “You are not going to choose something that is very bitter, but likely try for something sweeter, correct?”
    Anyone who has felt full after a big lunch and still was tempted by a slice of chocolate cake at an afternoon workplace party knows that a person can eat something they love even when not hungry.
    “If you are given food that is sweet, you would eat it in spite of your physiological condition being satisfied, unlike if someone gave you say a hunk of meat,” Das said. “Your psychological condition still wants to be satisfied, so you will have the urge to eat the sweets even when not hungry.”
    While there are still many questions regarding the neuronal circuits and molecular-level mechanisms within the brain that underlie hunger perception and appetite control, Das said, advances such as improved brain imaging have offered more information on how these circuits work in regard to gustation. More

  • 150 Shares159 Views

    in Computers Math

    These robots helped explain how insects evolved two distinct strategies for flight

    Robots built by engineers at the University of California San Diego helped achieve a major breakthrough in understanding how insect flight evolved, described in the Oct. 4, 2023 issue of the journal Nature. The study is a result of a six-year long collaboration between roboticists at UC San Diego and biophysicists at the Georgia Institute of Technology.
    The findings focus on how the two different modes of flight evolved in insects. Most insects use their brains to activate their flight muscles each wingstroke, just like we activate the muscles in our legs every stride we take. This is called synchronous flight. But some insects, such as mosquitoes, are able to flap their wings without their nervous system commanding each wingstroke. Instead, the muscles of these animals automatically activate when they are stretched. This is called asynchronous flight. Asynchronous flight is common in some of the insects in the four major insect groups, allowing them to flap their wings at great speeds, allowing some mosquitoes to flap their wings more than 800 times a second, for example.
    For years, scientists assumed the four groups of insects-bees, flies, beetles and true bugs (hemiptera)- all evolved asynchronous flight separately. However, a new analysis performed by the Georgia Tech team concludes that asynchronous flight actually evolved together in one common ancestor. Then some groups of insect species reverted back to synchronous flight, while others remained asynchronous.
    The finding that some insects such as moths have evolved from synchronous to asynchronous, and then back to synchronous flight led the researchers down a path of investigation that required insect, robot, and mathematical experiments. This new evolutionary finding posed two fundamental questions: do the muscles of moths exhibit signatures of their prior asynchrony and how can an insect maintain both synchronous and asynchronous properties in their muscles and still be capable of flight?
    The ideal specimen to study these questions of synchronous and asynchronous evolution is the Hawkmoth. That’s because moths use synchronous flight, but the evolutionary record tells us they have ancestors with asynchronous flight.
    Researchers at Georgia Tech first sought to measure whether signatures of asynchrony can be observed in the Hawkmoth muscle. Through mechanical characterization of the muscle they discovered that Hawkmoths still retain the physical characteristics of asynchronous flight muscles-even if they are not used.
    How can an insect have both synchronous and asynchronous properties and still fly? To answer this question researchers realized that using robots would allow them to perform experiments that could never be done on insects. For example, they would be able to equip the robots with motors that could emulate combinations of asynchronous and synchronous muscles and test what transitions might have occurred during the millions of years of evolution of flight. More

  • 150 Shares99 Views

    in Physics

    The development of quantum dots wins the 2023 Nobel prize in chemistry

    Work on tiny dots that light up TV screens and help doctors see the blood vessels that feed tumors has earned three scientists the 2023 Nobel Prize in chemistry.  

    Chemist Moungi Bawendi, chemist Louis Brus and physicist Alexei Ekimov split the prize for the discovery and synthesis of quantum dots, the Royal Swedish Academy of Sciences announced October 4.

    Chemist Moungi Bawendi (left), chemist Louis Brus (middle) and physicist Alexei Ekimov (right) have split the 2023 Nobel Prize in chemistry for “the discovery and development of quantum dots, nanoparticles so tiny that their size determines their properties.”MIT, Columbia University, Nexdot

    “Quantum dots are a new class of materials, different from molecules,” said Heiner Linke, a member of the Nobel committee. Just adjusting the size of these nanoparticles, roughly a few billionths of a meter across, can change their properties — optical, electric, magnetic, even melting points — thanks to quantum mechanics (SN: 6/29/15). 

    That’s also true of color. “If you want to make different colors with molecules, you would choose a new molecule, a new set of atoms” arranged in a different structure, Linke said. But quantum dots of different colors have the exact same arrangement of atoms. The only difference is particle size.

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    When quantum dots are irradiated by light, electrons within get energized, eventually releasing that energy as fluorescent light. The smaller the dots are, the more they compress the wave function of an electron, increasing its energy so that the dot appears blue. Larger dots appear red. 

    Dots of the same size made from different materials may also emit slightly different wavelengths of light, says Jean-Marc Pecourt, a chemist at CAS, a division of the American Chemical Society. Quantum dots are usually made from semiconductor materials, such as graphene, selenite or metal sulfides, Pecourt says. So by adjusting materials or the size of quantum dots, chemists can alter their properties for a wide variety of uses.

    The idea that the size of these nanoparticles could alter their properties was predicted nearly a century ago, but at the time it seemed impossible to reproduce that effect in the real world. To do that, researchers would need a perfectly crystalline material, and would need to control the size of the nanomaterial very precisely, sculpting it atom layer by atom layer.  

    Then, in the early 1980s, Ekimov and Brus independently showed that it could be done. Ekimov, now at Nanocrystals Technology, Inc., in Briarcliff Manor, N.Y., demonstrated this in glass, adding copper chloride to produce tiny crystals and revealing that the color of the glass was linked to the size of those crystals. Brus, of Columbia University, made a similar discovery, but in a different context: He demonstrated the link between size and color for nanoparticles floating freely in a solution and in gaseous compounds (SN: 10/3/92). 

    Those discoveries triggered intense interest in how to harness these little dots for a variety of applications. But manufacturing them would require being able to control the size of the particles to precise specifications. 

    A decade later, Bawendi, of MIT, developed a method to precisely control the speed of the crystals’ growth in a solution, figuring out how to stop them right when they reach a desired size. He did this by first injecting chemical reagents into the solution that instantaneously formed the tiny crystals and then promptly adjusting the temperature of the solution, halting their growth. 

    “I’m deeply honored and surprised and shocked by the announcement this morning,” Bawendi said October 4 during an MIT news conference. “I’m especially honored to share this with Lou Brus, who was my postdoctoral mentor [from] whom I learned so much. I tried to emulate his scholarship and his mentoring style as a professor myself when I came to MIT.” 

    Bawendi started working on quantum dots after he met Brus at Nokia Bell Labs, headquartered in Murray Hill, N.J. The researchers needed high quality quantum dots to study the physics of the nanoparticles, Bawendi said. “It wasn’t because I wanted to make the best quantum dots possible for application, it was because we needed to make the best possible quantum dots to study them.” It took years of trial and error to work out the method, he said.

    By making it possible to manufacture quantum dots, Bawendi’s method opened up a world of possible uses for the nanoparticles. Quantum dots make it possible to very precisely change the color of LED lights and dramatically improve their efficiency. Dots that glow with fluorescent light, injected into the body and attached to immune cells that swarm to cancerous tissues, can help surgeons distinguish even hard-to-see tumors (SN: 8/3/04). The ability to be tuned to absorb different wavelengths of light could also allow the manufacture of customized solar cells that are highly efficient in different light conditions. The dots might also be used to build quantum computers, Pecourt says (SN: 2/14/18). 

    Biomedical engineer and chemist Warren Chan says the prize is well deserved. “They’re the ones who built the foundation,” says Chan, of the University of Toronto. “I’m really happy that the field is getting credit for really changing the world, not just in quantum dots, but in a lot of different areas.” 

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    One of the first applications came in the late 1990s when Chan and colleagues used quantum dots to tag cells in the lab, he says. “The surface modifications that were used for integrating quantum dots for applications were then also adapted for other types of nanoparticles.”

    The Nobel committee looks not only at past contributions, but also the effect a discovery may have on the future, Chan says. The ability to tune nanoparticles by changing their size or surface properties could open a wide variety of possibilities that have not yet been explored. Chan and colleagues are now using quantum dots to detect infectious diseases, including HIV, influenza and hepatitis B.

    “I was absolutely thrilled to see this,” says Judith Giordan, president of the American Chemical Society. “We have three people recognized who brought this technology from a dream, a hope, a theoretical construct … all the way through synthesis and manufacture.”

    Earlier this week, the development of mRNA vaccines — widely speculated as a candidate for the 2023 chemistry Nobel Prize — received the Nobel in medicine or physiology instead (SN: 10/2/23). 

    “Sometimes chemistry gets a bad rap,” Giordan says. “But here are two magnificent examples of how chemistry has solved problems in the world.”

    The three winners will share the prize of 11 million Swedish kronor, or about $1 million. More

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    A global report finds amphibians are still in peril. But it’s not all bad news

    Nearly 20 years ago, the first global assessment of amphibians found the animals facing widespread declines. Now, a second, updated report shows that many amphibians are still in trouble, but with some silver linings, researchers report October 4 in Nature.

    “We are realistic and hopeful at the same time,” says Jennifer Luedtke, a conservationist at the International Union for Conservation of Nature, which tracks extinction risk trends for species around the world.

    In particular, the wealth of data in the new report, which includes about 8,000 amphibian species, could help focus conservation efforts for years to come, says Luedtke, who also works from Washington, D.C., for Re:wild, a conservation organization based in Austin, Texas. That’s what happened after the first Global Amphibian Assessment in 2004, which brought awareness to the amphibian crisis and galvanized researchers to coordinate efforts.

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    Having two assessments that can be compared is a big deal, experts say. “It’s important not just to have a picture, but actually to have a sequence of pictures … where you can see what’s happening over time,” says conservation ecologist Ana Rodrigues of CNRS in Montpelier, France, who worked on the first assessment but was not involved in the second. “I’m really happy to see this done.”

    Here are five big takeaways from the new report.

    1. Amphibians remain more threatened with extinction than any other vertebrate group.

    About 41 percent of amphibian species, which include frogs, toads and salamanders, are threatened with extinction, Luedtke and her colleagues found. That’s more than any other group of vertebrates, beating out sharks and rays (37 percent), mammals (27 percent), reptiles (21 percent) and birds (13 percent).

    Amphibians held this title in 2004 too, when 39 percent of species were threatened. As part of the 2022 update, researchers also used data to reconstruct the situation in 1980. They found that even in 1980, that number was already high, at 38 percent. Basically, amphibians have been really threatened for a really long time, Luedtke says.

    The most common threat that affects amphibians is habitat loss and degradation, with agriculture affecting as many as 77 percent of the studied species. Other threats include climate change and disease, each affecting 29 percent of species. Of course, “these things are never completely isolated,” says Rodrigues, and each threat may increase the likelihood of other threats.

    2. Many of the worst amphibian declines are being caused by climate change now, instead of disease.

    Luedtke and colleagues also wanted to know which threats were most responsible for driving the worst declines. So they looked at a subset of 788 species that, between 1980 and 2022, moved down an IUCN Red List status level — for instance, from vulnerable to endangered. They found that, in 2004, disease was the primary driver behind the drop in conservation status for 58 percent of that species subset. At the time, the fungal pathogen chytrid was devastating frog populations around the world (SN: 8/23/02). Climate change, on the other hand, was a significant contributor to declines in only 1 percent of species.

    Now, less than 20 years later, climate change is behind a status drop for 39 percent of species. That makes it the most common primary driver of declines across the amphibian group, the researchers found. And still the finding is probably an underestimate, Luedtke says, as studies continue to emerge detailing how climate change–related temperature increases, changes in precipitation, extreme weather events and wildfires impact amphibians.

    “It’s very worrying,” Rodrigues says. “We’re at the beginning of climate change.… What’s ahead of us?”

    Amphibian species in the tepuis, or tabletop mountains, of Venezuela, like this Chimantá poison frog (Anomaloglossus rufulus), are particularly vulnerable to climate change, as they are unable to shift much higher in altitude to escape warming temperatures.F.J.M. ROJAS-RUNJAIC

    3. It’s bad around the world. But amphibians are doing worse in some regions than others.

    Each region faces its own set of threats. The chytrid outbreak, for example, has affected much of the world, but it hit Central and South America especially hard from the 1970s to the 2000s. That likely explains why that region contains the largest proportion of species in the IUCN Red List categories of highest concern, the researchers say. New Guinea and Africa were spared much of the devastation, though the pathogen has recently started to emerge in sub-Saharan Africa.

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    Across Europe and East Asia, habitat loss is the leading cause of decline, followed by a newly emerging fungal pathogen in Europe called Batrachochytrium salamandrivorans, this time that affects salamanders (SN: 9/3/13). It hasn’t yet spread to North America, which would be disastrous, Rodrigues says. The continent is home to more than 200 types of salamanders, over a quarter of the world’s salamander species.

    For now, North America’s amphibian declines are most associated with climate change, the report found. South and Southeast Asia are seeing an improving trend among their species’ extinction risk, probably due to better management of protected areas.

    4. Scientists know a lot more about amphibians now than they did in 2004.

    One of the assessment’s few bright spots is its sheer amount of data. The update includes more than 2,000 additional species — all newly described since 2004. There was also a decrease in species labeled as “data deficient” by the IUCN, from 23 percent in 2004 to only 11 percent in 2022. By comparison, though, less than 1 percent of bird species are listed as data deficient.

    While there’s still a long way to go for amphibians, researchers are thrilled by the new amount of information. “It’s like, wow, all the knowledge!” Rodrigues says. “So that’s absolutely good news.” With more data, she says, conservation efforts can be better focused.

    This indigo bush frog (Raorchestes indigo) has moved from critically endangered to vulnerable thanks to habitat protection efforts in the Kudremukh Massif mountain range of India.Saurabh Sawant

    5. Some amphibian species have improved since 2004.

    The new report didn’t just find declines — 120 species saw their IUCN conservation status improve.

    About half of those species recovered unaided. Many of those had suffered declines due to chytrid and are now bouncing back, possibly as frogs become resistant to the pathogen (SN: 3/29/18). It’s a source of hope that “we have these little frogs evolving, in front of our eyes, resistance to chytridiomycosis,” Luedtke says.

    The other half improved thanks to conservation efforts, the report found. One of those species is India’s indigo bush frog (Raorchestes indigo), which was classified as critically endangered in 2004. A couple years later, a legal battle led to the end of all mining in the Kudremukh Massif mountain range, and the species’ IUCN status has since improved to vulnerable.

    Stories like that are evidence that effective habitat protection can make a noticeable difference, the researchers say, and yet, with most amphibians still facing declines, it’s clear that current efforts are not enough. The assessment’s accompanying State of the World’s Amphibians Report focuses on action steps based on the new findings. Among other things, it identifies 50 target conservation areas around the world — including Jamaica, Brazil’s Atlantic Forest and the Central Annamite Highlands in Vietnam — that feature a high density of threatened species.

    “Yes, the number of threatened amphibians continues to increase, but our understanding is improving,” Luedtke says. “And because we understand them better, we can act in a more accurate and effective way.” More

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    in Computers Math

    AI drones to help farmers optimize vegetable yields

    For reasons of food security and economic incentive, farmers continuously seek to maximize their marketable crop yields. As plants grow inconsistently, at the time of harvesting, there will inevitably be variations in quality and size of individual crops. Finding the optimal time to harvest is therefore a priority for farmers. A new approach making heavy use of drones and artificial intelligence demonstrably improves this estimation by carefully and accurately analyzing individual crops to assess their likely growth characteristics.
    Some optimistic science fiction stories talk about a post-scarcity future, where human needs are catered for and hard labor is provided by machines. There are some ways in which this vision appears to predict some elements of current technological progress. One such area is in agricultural research, where automation has been making an impact. For the first time, researchers, including those from the University of Tokyo, have demonstrated a largely automated system to improve crop yields, which can benefit many and may help pave the way for future systems that could one day harvest crops directly.
    “The idea is relatively simple, but the design, implementation and execution is extraordinarily complex,” said Associate Professor Wei Guo from the Laboratory of Field Phenomics. “If farmers know the ideal time to harvest crop fields, they can reduce waste, which is good for them, for consumers and the environment. But optimum harvest times are not an easy thing to predict and ideally require detailed knowledge of each plant; such data would be cost and time prohibitive if people were employed to collect it. This is where the drones come in.”
    Guo has a background in both computer science and agricultural science, so is ideally suited to finding ways cutting-edge hardware and software could aid agriculture. He and his team have demonstrated that some low-cost drones with specialized software can image and analyze young plants — broccoli in the case of this study — and accurately predict their expected growth characteristics. The drones carry out the imaging process multiple times and do so without human interaction, meaning the system requires little in terms of labor costs.
    “It might surprise some to know that by harvesting a field as little as a day before or after the optimal time could reduce the potential income of that field for the farmer by 3.7% to as much as 20.4%,” said Guo. “But with our system, drones identify and catalog every plant in the field, and their imaging data feeds a model that uses deep learning to produce easy-to-understand visual data for farmers. Given the current relative low costs of drones and computers, a commercial version of this system should be within reach to many farmers.”
    The main challenge the team faced was in the image analysis and deep learning aspects. Collecting the image data itself is relatively trivial, but given the way plants move in the wind and how the light changes with time and the seasons, the image data contains a lot of variation that machines often find hard to compensate for. So, when training their system, the team had to invest a huge amount of time labeling various aspects of images the drones might see, in order to help the system learn to correctly identify what it was seeing. The vast data throughput was also challenging — image data was often of the order of trillions of pixels, tens of thousands of times larger than even a high-end smartphone camera.
    “I’m inspired to find more ways that plant phenotyping (measuring of plant growth traits) can go from the lab to the field in order to help solve the major problems we face,” said Guo. More

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    in Computers Math

    Insect cyborgs: Towards precision movement

    Insect cyborgs may sound like science fiction, but it’s a relatively new phenomenon based on using electrical stimuli to control the movement of insects. These hybrid insect computer robots, as they are scientifically called, herald the future of small, high mobile and efficient devices.
    Despite significant progress being made, however, further advances are complicated by the vast differences between different insects’ nervous and muscle systems.
    In a recent study published in the journal eLife, an international research group has studied the relationship between electrical stimulation in stick insects’ leg muscles and the resultant torque (the twisting force that makes the leg move).
    They focused on three leg muscles that play essential roles in insect movement: one for propulsion, one for joint stiffness, and one for transitioning between standing and swinging the leg. The experiments involved the researchers keeping the body of the stick insects fixed, and electrically stimulating one out of the three leg muscles to produce walking-like movements.
    The research was led by Dai Owaki, associate professor at the Department of Robotics at Tohoku University’s Graduate School of Engineering. Experiments were conducted at Bielefeld University, Germany, in a lab run by Professors Volker Dürr and Josef Schmitz.
    “Based on our measurements, we could generate a model that predicted the created torque when different patterns of electrical stimulation were applied to a leg muscle,” points out Owaki. “We also identified a nearly linear relationship between the duration of the electrical stimulation and the torque generated, meaning we could predict how much twisting force we would generate by just looking at the length of the applied electrical pulse.”
    Using only a few measurements, Owaki and his collaborators could apply this to each individual insect. As a result of these findings, scientists will be able to refine the motor control of tuned biohybrid robots, making their movements more precise.
    While the team knows their insights could lead to adaptable and highly mobile devices with various applications, they still cite some key challenges that need to be addressed. “First, model testing needs to be implemented in free-walking insects, and the electrical stimuli must be refined to mimic natural neuromuscular signals more closely,” adds Owaki. More