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    Researchers develop real-time lyric generation technology to inspire song writing

    Music artists can find inspiration and new creative directions for their song writing with technology developed by Waterloo researchers.
    LyricJam, a real-time system that uses artificial intelligence (AI) to generate lyric lines for live instrumental music, was created by members of the University’s Natural Language Processing Lab.
    The lab, led by Olga Vechtomova, a Waterloo Engineering professor cross-appointed in Computer Science, has been researching creative applications of AI for several years.
    The lab’s initial work led to the creation of a system that learns musical expressions of artists and generates lyrics in their style.
    Recently, Vechtomova, along with Waterloo graduate students Gaurav Sahu and Dhruv Kumar, developed technology that relies on various aspects of music such as chord progressions, tempo and instrumentation to synthesize lyrics reflecting the mood and emotions expressed by live music.
    As a musician or a band plays instrumental music, the system continuously receives the raw audio clips, which the neural network processes to generate new lyric lines. The artists can then use the lines to compose their own song lyrics. More

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    Windbreaks, surprisingly, could help wind farms boost power output

    Windbreaks may sound like a counterintuitive idea for boosting the performance of a wind turbine. But physicists report that low walls that block wind could actually help wind farms produce more power.

    Scientists already knew that the output of a single wind turbine could be improved with a windbreak. While windbreaks slow wind speed close to the ground, above the height of the windbreak, wind speeds actually increase as air rushes over the top. But for large wind farms, there’s a drawback. A windbreak’s wake slows the flow of air as it travels farther through the rows of turbines. That could suggest that windbreaks would be a wash for wind farms with many turbines.

    But by striking a balance between these competing effects, windbreaks placed in front of each turbine can increase power output, new computer simulations suggest. It comes down to the windbreaks’ dimensions. Squat, wide barriers are the way to go, according to a simulated wind farm with six rows of turbines. To optimize performance, windbreaks should be a tenth the height of the turbine and at least five times the width of the blades, physicists report July 30 in Physical Review Fluids. Such an arrangement could increase the total power by about 10 percent, the researchers found. That’s the equivalent of adding an additional turbine, on average, for every 10 in a wind farm.

    In the simulations, the wind always came from the same direction, suggesting the technique might be useful in locations where wind tends to blow one way, such as coastal regions. Future studies could investigate how this technique might apply in places where wind direction varies.

    In a computer simulation of a wind farm with 24 turbines, scientists found that windbreaks (red) improved the overall power output. Wakes created by the windbreaks appear in dark blue, and wakes of the turbines are light blue.L. Liu and R.J.A.M. Stevens/Physical Review Fluids 2021, Visualizations by Srinidhi N. Gadde More

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    The new UN climate change report shows there’s no time for denial or delay

    The science is unequivocal: Humans are dramatically overhauling Earth’s climate. The effects of climate change are now found everywhere around the globe and are intensifying rapidly, states a sweeping new analysis released August 9 by the United Nations’ Intergovernmental Panel on Climate Change, or IPCC. And the window to reverse some of these effects is closing.

    “There is no room for doubt any longer” about humans’ responsibility for current climate change, says Kim Cobb, a climate scientist at Georgia Tech in Atlanta and an author on the first chapter of the report. “And now we can say quite definitely that a whole class of extreme [events]” is linked to human-caused climate change.

    Climate change is already affecting every region on Earth in multiple ways, from drought and fire conditions in the U.S. West to heat waves in Europe and flooding in Asia, the report notes  (SN: 7/7/21). Each of the past four decades has been the warmest on record since preindustrial times (SN: 5/26/21).

    The study also looks at several different scenarios of greenhouse gas warming, including perhaps the most hopeful scenarios in which by 2050 the world achieves “net zero” carbon emissions, where emitted gases are balanced by carbon removal from the atmosphere.

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    If the world gets down to net-zero emissions, the decades afterward hold “hints of light,” says Baylor Fox-Kemper, an oceanographer at Brown University in Providence, R.I., and the coordinating lead author of the new report’s chapter on oceans and Earth’s icy regions. “Temperatures come back down a little — not all the way back to preindustrial times, but there’s a little recovery.”

    But other changes are irreversible on near-future timescales — that is, the next century or more, Fox-Kemper says. Even in those mid-century net-zero emissions scenarios, “it’s still pretty bad,” he says. Sea levels, for example, will continue to rise until about the year 2300, driven in part by the juggernaut of Greenland’s melting ice sheet (SN: 9/30/20). “We may have already crossed [the] threshold beyond which Greenland’s melting could be stopped,” he says. Still, swift and deep emissions reductions would significantly slow how much sea levels will rise by the end of the century, the report finds.

    The new analysis is the sixth in a series of massive assessment reports undertaken by the IPCC since 1990. In each report, hundreds of scientists from around the world analyze the findings of thousands of studies to form a consensus picture of how Earth’s climate is changing and what role people play in those changes.

    “The key message [of this report] is still the same as was first published in 1990 … human-induced emissions of greenhouse gases pose a threat for humans’ well-being and the biosphere,” said Petteri Taalas, Secretary-General of the World Meteorological Organization, at an event announcing the report’s release August 9.

    But researchers understand climate change far better now than they did in 1990, when the first assessment report was released. In the last three decades, new findings have poured in from tens of thousands more observing stations, from a wealth of satellite instruments, and from dramatically improved climate simulations (SN: 1/7/20).

    The IPCC’s fifth assessment report, released in several parts during 2013 and 2014, was itself a game changer. It was the first to state that greenhouse gas emissions from human activities are driving climate change — a conclusion that set the stage for 195 nations to agree in Paris in 2015 to curb those emissions (SN: 4/13/14; SN: 12/12/15).

    The Paris Agreement set a target of limiting the global average temperature to 2 degrees Celsius above preindustrial times. But many island nations and others most threatened by climate change feared that this target wasn’t stringent enough. So in an unprecedented step, the U.N. commissioned a report by the IPCC to compare how a future Earth might look if warming were limited to just 1.5 degrees Celsius instead.

    The Dixie Fire, the largest individual wildfire in California’s history, started on July 13, 2021 and left the town of Greenville, including its library (shown) in ruins. The IPCC’s sixth assessment report finds that humans are unequivocally responsible for the planet’s rising temperatures since the late 1800s, and links these changes to extreme weather including wildfires, drought, heat waves, extreme precipitation and properties of tropical cyclones. Trevor Bexon/Getty Images

    That special report, released in 2018, revealed in fine detail how just half a degree of extra warming by 2100 could matter, from the increased likelihood of heat waves to higher sea levels (SN: 12/17/18). The one-two punch of those concrete findings and scorching temperatures in 2019 grabbed the attention of public and policy makers alike.

    Scientists were surprised by how hard the 1.5 degree report landed. “Even for me,” says Ko Barrett, vice chair of the IPCC and a senior advisor for climate at the U.S. National Oceanic and Atmospheric Administration, “a person who has dedicated my entire professional career to addressing climate change, the report caused me to rethink my personal contribution to the climate problem. Climate change was not some distant temperature target to be hit in the ethereal future. It was close; it was now.”

    IPCC scientists hope the new report, with its powerful emphasis on the regional and local effects of climate change — fully a third of the report is devoted to outlining those — will have a similar impact. And its timing is significant. Beginning October 31, heads of state from around the world are scheduled to meet in Glasgow, Scotland, to discuss updated — and hopefully increasingly ambitious — plans to reduce emissions to meet the targets of the 2015 Paris Agreement. 

    With previous reports, “the world listened, but it didn’t hear. Or the world listened, but it didn’t act strongly enough,” said Inger Andersen, executive director of the U.N. Environment Programme, at the Aug. 9 event for the report’s release. “We certainly urge them … to listen to the facts on the table now.” More

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    Natural language processing research: Signed languages

    Advancements in natural language processing (NLP) enable computers to understand what humans say and help people communicate through tools like machine translation, voice-controlled assistants and chatbots.
    But NLP research often only focuses on spoken languages, excluding the more than 200 signed languages around the world and the roughly 70 million people who might rely on them to communicate.
    Kayo Yin, a master’s student in the Language Technologies Institute, wants that to change. Yin co-authored a paper that called for NLP research to include signed languages.
    “Signed languages, even though they are a significant part of the languages used in the world, aren’t included,” Yin said. “There is a demand and an importance in having technology that can handle signed languages.”
    The paper, “Including Signed Languages in Natural Language Processing,” won the Best Theme Paper award at this month’s 59th Annual Meeting of the Association for Computational Linguistics. Yin’s co-authors included Amit Moryossef of Bar-Ilan University in Israel; Julie Hochgesang of Gallaudet University; Yoav Goldberg of Bar-Ilan University and the Allen Institute for AI; and Malihe Alikhani of the University of Pittsburgh’s School of Computing and Information.
    The authors wrote that communities relying on signed language have fought for decades both to learn and use those languages, and for them to be recognized as legitimate. More

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    Physical activity protects children from the adverse effects of digital media on their weight later in adolescence

    Children’s heavy digital media use is associated with a risk of being overweight later in adolescence. Physical activity protects children from the adverse effects of digital media on their weight later in adolescence.
    A recently completed study shows that six hours of leisure-time physical activity per week at the age of 11 reduces the risk of being overweight at 14 years of age associated with heavy use of digital media.
    Obesity in children and adolescents is one of the most significant health-related challenges globally. A study carried out by the Folkhälsan Research Center and the University of Helsinki investigated whether a link exists between the digital media use of Finnish school-age children and the risk of being overweight later in adolescence. In addition, the study looked into whether children’s physical activity has an effect on this potential link.
    The results were published in the Journal of Physical Activity and Health.
    More than six hours of physical activity per week appears to reverse adverse effects of screen time
    The study involved 4,661 children from the Finnish Health in Teens (Fin-HIT) study. The participating children reported how much time they spent on sedentary digital media use and physical activity outside school hours. The study demonstrated that heavy use of digital media at 11 years of age was associated with a heightened risk of being overweight at 14 years of age in children who reported engaging in under six hours per week of physical activity in their leisure time. In children who reported being physically active for six or more hours per week, such a link was not observed.
    The study also took into account other factors potentially impacting obesity, such as childhood eating habits and the amount of sleep, as well as the amount of digital media use and physical activity in adolescence. In spite of the confounding factors, the protective role of childhood physical activity in the connection between digital media use in childhood and being overweight later in life was successfully confirmed.
    Activity according to recommendations
    “The effect of physical activity on the association between digital media use and being overweight has not been extensively investigated in follow-up studies so far,” says Postdoctoral Researcher Elina Engberg.
    Further research is needed to determine in more detail how much sedentary digital media use increases the risk of being overweight, and how much physical activity is needed, and at what intensity, to ward off such a risk. In this study, the amount of physical activity and use of digital media was reported by the children themselves, and the level of their activity was not surveyed, so there is a need for further studies.
    “A good rule of thumb is to adhere to the physical activity guidelines for children and adolescents, according to which school-aged children and adolescents should be physically active in a versatile, brisk and strenuous manner for at least 60 minutes a day in a way that suits the individual, considering their age,” says Engberg. In addition, excessive and extended sedentary activity should be avoided.
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    Overcoming the limitations of scanning electron microscopy with AI

    What if a super-resolution imaging technique used in the latest 8K premium TVs is applied to scanning electron microscopy, essential equipment for materials research?
    A joint research team from POSTECH and the Korea Institute of Materials Science (KIMS) applied deep learning to the scanning electron microscopy (SEM) to develop a super-resolution imaging technique that can convert a low-resolution electron backscattering diffraction (EBSD) microstructure images obtained from conventional analysis equipment into super-resolution images. The findings from this study were recently published in the npj Computational Materials.
    In modern-day materials research, SEM images play a crucial role in developing new materials, from microstructure visualization and characterization, and in numerical material behavior analysis. However, acquiring high-quality microstructure image data may be exhaustive or highly time-consuming due to the hardware limitations of the SEM. This may affect the accuracy of subsequent material analysis, and therefore, it is paramount to overcome the technical limitations of the equipment.
    To this, the joint research team developed a faster and more accurate microstructure imaging technique using deep learning. In particular, by using a convolutional neural network, the resolution of the existing microstructure image was enhanced by 4 times, 8 times, and 16 times, which reduces the imaging time up to 256 times compared to the conventional SEM system.
    In addition, super-resolution imaging verified that the morphological details of the microstructure can be restored with high accuracy through microstructure characterization and finite element analysis.
    “Through the EBSD technique developed in this study, we anticipate the time it takes to develop new materials will be drastically reduced,” explained Professor Hyoung Seop Kim of POSTECH who led the research.
    This research was conducted with the support from the Mid-career Researcher Program of the National Research Foundation of Korea, the AI Graduate School Program of the Institute for Information & Communications Technology Promotion (IITP), and Phase 4 of the Brain Korea 21 Program of the Ministry of Education, and with the support from the Korea Materials Research Institute.
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    Unlocking the AI algorithm ‘black box’ – new machine learning technology to find out what makes plants and humans tick

    The inner 24-hour cycles — or circadian rhythms — are key to maintaining human, plant and animal health, which could provide valuable insight into how broken clocks impact health.
    Circadian rhythms, such as the sleep-wake cycle, are innate to most living organisms and critical to life on Earth. The word circadian originates from the Latin phrase ‘circa diem’ which means ‘around a day’.
    Biologically, the circadian clock temporally orchestrates physiology, biochemistry, and metabolism across the 24-hour day-night cycle. This is why being out of kilter can affect our fitness levels, our health, or our ability to survive. For example, experiencing jet lag is a chronobiological problem — our body clocks are out of sync because the normal external cues such as light or temperature have changed.
    The circadian clock isn’t unique to humans. In plants, an accurate clock helps to regulate flowering and is crucial to synchronising metabolism and physiology with the rising and setting sun. Understanding circadian rhythms can help to improve plant growth and yields, not to mention revealing new avenues for tackling human diseases.
    Beyond plants
    For this latest research, the team applied ML to predict complex temporal circadian gene expression patterns in model plant Arabidopsis thaliana. Taking newly generated datasets, published temporal datasets, and Arabidopsis genomes, the team of scientists trained ML models to make predictions about circadian gene regulation and expression patterns. More

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    Brain connectivity can build better AI

    A new study shows that artificial intelligence networks based on human brain connectivity can perform cognitive tasks efficiently.
    By examining MRI data from a large Open Science repository, researchers reconstructed a brain connectivity pattern, and applied it to an artificial neural network (ANN). An ANN is a computing system consisting of multiple input and output units, much like the biological brain. A team of researchers from The Neuro (Montreal Neurological Institute-Hospital) and the Quebec Artificial Intelligence Institute trained the ANN to perform a cognitive memory task and observed how it worked to complete the assignment.
    This is a unique approach in two ways. Previous work on brain connectivity, also known as connectomics, focused on describing brain organization, without looking at how it actually performs computations and functions. Secondly, traditional ANNs have arbitrary structures that do not reflect how real brain networks are organized.By integrating brain connectomics into the construction of ANN architectures, researchers hoped to both learn how the wiring of the brain supports specific cognitive skills, and to derive novel design principles for artificial networks.
    They found that ANNs with human brain connectivity, known as neuromorphic neural networks, performed cognitive memory tasks more flexibly and efficiently than other benchmark architectures. The neuromorphic neural networks were able to use the same underlying architecture to support a wide range of learning capacities across multiple contexts.
    “The project unifies two vibrant and fast-paced scientificdisciplines,” says Bratislav Misic, a researcher at The Neuro and the paper’s senior author. “Neuroscience and AI share common roots, but have recently diverged. Using artificial networks will help us to understand how brain structure supports brain function. In turn, using empirical data to make neural networks will reveal design principles for building better AI. So, the two will help inform each other and enrich our understanding of the brain.”
    This study, published in the journal Nature Machine Intelligence on Aug. 9, 2021, was funded with the help of the Canada First Research Excellence Fund, awarded to McGill University for the Healthy Brains, Healthy Lives initiative, the Natural Sciences and Engineering Research Council of Canada, Fonds de Recherche du Quebec — Santé, Canadian Institute for Advanced Research, Canada Research Chairs, Fonds de Recherche du Quebec — Nature et Technologies, and Centre UNIQUE (Union of Neuroscience and Artificial Intelligence).
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