news, journals and articles from all over the world.
Argonne scientists are working around the clock to analyze the virus to find new treatments and cures, predict how it will propagate through the population, and make sure that our supply chains remain intact.
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Argonne scientists and engineers are looking toward AI — specifically, machine learning — to help us better understand the mechanics that govern nuclear reactors.
Read moreResearchers have used artificial intelligence to detect Vietnam War-era bomb craters in Cambodia from satellite images – with the hope that it can help find unexploded bombs.
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In a machine learning challenge dubbed the 2020 Large Hadron Collider Olympics, a team of cosmologists from Berkeley Lab developed a code that best identified a mock signal hidden in simulated particle-collision data.
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Proteins are the building blocks of life and scientists have long studied how to improve them or design new ones. Traditionally, new proteins are created by mimicking existing proteins or manually editing their amino acids. This process is time-consuming, and it is difficult to predict the impact of changing an amino acid. In APL Bioengineering, researchers explore how to create new proteins by using machine learning to translate protein structures into musical scores, presenting an unusual way to translate physics concepts across domains.
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In a study, the researchers used a machine learning algorithm to classify more than 110 types of plastics, including commercial and lab-made varieties, to better understand how they might degrade in the ocean.
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Astrophysicists supported by the Department of Energy’s Office of Science are developing these guides in the form of computer models that rely on machine learning to examine the LSST data.
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Applying deep learning to seismic data has revealed tremor and slip occur at all times—before and after known large-scale slow-slip earthquakes—rather than intermittently in discrete bursts, as previously believed.
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Scientists may be a step closer to solving some of anthropology’s biggest mysteries thanks to a machine learning algorithm that can scour through remote sensing data, such as satellite imagery, looking for signs of human settlements, according to an international team of researchers.
Read moreMachine learning is helping Penn Medicine researchers identify the size and shape of brain networks in individual children, which may be useful for understanding psychiatric disorders. In a new study published in Neuron, a multidisciplinary team showed how brain networks unique to each child can predict cognition. The study is the first to show that functional neuroanatomy can vary greatly among kids, and is refined during development.
Read moreArgonne scientists are combining one-of-a-kind x-ray experiments with novel computer simulations to help engineers at aerospace and defense companies save time and money.
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