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Categories: Energy: Fossil Fuels, Mathematics: Modeling

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Researchers suggest how scientists can circumvent the need for massive data sets to forecast extreme events with the combination of an advanced machine learning system and sequential sampling techniques.

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Researchers analyzed the effects of decarbonization strategies by linking global resource inventories with demographic systems to generate a matrix showing the risks and benefits. The research suggests that increased demand for energy transition metals (ETMs) could be more disruptive to some communities than winding back production of thermal coal. The team calculated that while a complete phase-out of coal could disrupt mine-town systems with a minimum of 33.5 million people, an additional 115.7 million would be at risk from disruption by ETMs.

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Researchers have developed an AI based neural network to detect an early knee osteoarthritis from x-ray images. AI was able to match a doctors' diagnosis in 87% of cases. The result is important because x-rays are the primary diagnostic method for early knee osteoarthritis. An early diagnosis can save the patient from unnecessary examinations, treatments and even knee joint replacement surgery.

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A new study shows machine-learning models trained using simple symptoms, demographic features are effective in predicting COVID-19 infections.

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Using a novel modeling method, a team of researchers gained new insights into how hummingbirds produce wing movement, which could lead to design improvements in flying robots.

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Mathematical analysis identifies a vortex structure that is impervious to decay.

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The reliability of data storage and writing speed in advanced magnetic devices depend on drastic, complex changes in microscopic magnetic domain structures. However, it is extremely challenging to quantify these changes, limiting our understanding of magnetic phenomena. To tackle this, researchers developed, using machine learning and topology, an analysis method that quantifies the complexity of the magnetic domain structures, revealing hidden features of magnetization reversal that are hardly seen by human eyes.

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In a laboratory experiment, researchers have succeeded in realizing an effective spacetime that can be manipulated. In their research on ultracold quantum gases, they were able to simulate an entire family of curved universes to investigate different cosmological scenarios and compare them with the predictions of a quantum field theoretical model.

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With the theory that for every action, even those seemingly complex and random, there is a math problem that describes it, a researcher is publishing a new formula that helps find that equation quickly. Yes, he's speeding up science.

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Researchers used a unique coupled computer modeling approach to accurately recreate the coastal flooding that occurred during Hurricane Florence, demonstrating that it is more accurate than traditional modeling approaches.

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A new study finds that the health benefits associated with wind power could more than quadruple if operators turned down output from the most polluting fossil-fuel-based power plants when energy from wind is available. However, compared to wealthier communities, disadvantaged communities would reap a smaller share of these benefits.

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An interdisciplinary team of researchers has developed a potential breakthrough in green aviation: a recipe for a net-zero fuel for planes that will pull carbon dioxide (CO2) out of the air.

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Microscopic image data is key to developing low-power, high-speed electronic devices. However, the complex interactions in nanoscale magnetic materials are difficult to understand. A research group has now realized a new functional design theory called 'extended Landau free energy model' that combines topology and AI with free energy to automate the interpretation of the microscopic image. This model illustrates the physical mechanism and critical location of magnetization reversal and proposes a device structure with low energy consumption.

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Research finds using a large collection of simple, un-curated synthetic image generation programs to pretrain a computer vision model for image classification yields greater accuracy than employing other pretraining methods that are more costly and time consuming, and less scalable.

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A new study has revealed how the glass-like shells of diatoms help these microscopic organisms perform photosynthesis in dim conditions. A better understanding of how these phytoplankton harvest and interact with light could lead to improved solar cells, sensing devices and optical components.

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New research shows a pathway toward full decarbonization of U.S. aviation fuel use by substituting conventional jet fuel with sustainably produced biofuels. The study found that planting the grass miscanthus on 23.2 million hectares of existing marginal agricultural lands -- land that often lays fallow or is poor in soil quality -- across the United States would provide enough biomass feedstock to meet the liquid fuel demands of the U.S. aviation sector fully from biofuels, an amount expected to reach 30 billion gallons/year by 2040.

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Computational scientists adopt new framework for making AI models more findable, accessible, interoperable and reusable.

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Researchers have discovered a new process that uses fuel to control non-living materials, similar to what living cells do. The reaction cycle can easily be applied to a wide range of materials and its rate can be controlled -- a breakthrough in the emerging field of such reactions. The discovery is a step towards soft robotics; soft machines that can sense what is happening in their environment and respond accordingly.

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Researchers have developed a proof-of-concept system to autonomously detect compressed air leaks on trains and relay the location of the leaks to mechanical personnel for repair. The automated system could reduce the time, costs and labor needed to find and repair air leaks, and it could lower the locomotive industry's overall fuel consumption and exhaust emissions.

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A simple material can separate carbon dioxide from other gases that fly out of the smokestacks of coal-fired power plants. It lacks the shortcomings that other proposed carbon filtration materials have, rivaling designer compounds in its simplicity, overall stability and ease of preparation.