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Categories: Environmental: Wildfires, Mathematics: Modeling
Published Rectifying AI's usage in the quest for thermoelectric materials
(via sciencedaily.com) Original source AI is revolutionizing the way researchers seek to identify new materials, but it still has some shortcomings. Now, a team of researchers has navigated AI's pitfalls to identify a thermoelectric material that boasts remarkable properties.
Published Unintended consequences of fire suppression
(via sciencedaily.com) Original source A new study reveals how fire suppression ensures that wildfires will burn under extreme conditions at high severity, exacerbating the impacts of climate change and fuel accumulation.
Published Physicists develop modeling software to diagnose serious diseases
(via sciencedaily.com) Original source Researchers have recently published FreeDTS -- a shared software package designed to model and study biological membranes at the mesoscale -- the scale 'in between' the larger macro level and smaller micro level. This software fills an important missing software among the available biomolecular modeling tools and enables modeling and understanding of many different biological processes involving the cellular membranes e.g. cell division.
Published Powerful new AI can predict people's attitudes to vaccines
(via sciencedaily.com) Original source A powerful new tool in artificial intelligence is able to predict whether someone is willing to be vaccinated against COVID-19.
Published New technique helps AI tell when humans are lying
(via sciencedaily.com) Original source Researchers have developed a new training tool to help artificial intelligence (AI) programs better account for the fact that humans don't always tell the truth when providing personal information. The new tool was developed for use in contexts when humans have an economic incentive to lie, such as applying for a mortgage or trying to lower their insurance premiums.
Published Vac to the future
(via sciencedaily.com) Original source Scientists recently published the results of a competition that put researchers to the test. For the competition, part of the NIH-funded Computational Models of Immunity network, teams of researchers from different institutions offered up their best predictions regarding B. pertussis (whooping cough) vaccination.
Published AI for astrophysics: Algorithms help chart the origins of heavy elements
(via sciencedaily.com) Original source The origin of heavy elements in our universe is theorized to be the result of neutron star collisions, which produce conditions hot and dense enough for free neutrons to merge with atomic nuclei and form new elements in a split-second window of time. Testing this theory and answering other astrophysical questions requires predictions for a vast range of masses of atomic nuclei. Scientists are using machine learning algorithms to successfully model the atomic masses of the entire nuclide chart -- the combination of all possible protons and neutrons that defines elements and their isotopes.
Published Researchers develop a new control method that optimizes autonomous ship navigation
(via sciencedaily.com) Original source Existing ship control systems using Model Predictive Control for Maritime Autonomous Surface Ships (MASS) do not consider the various forces acting on ships in real sea conditions. Addressing this gap, researchers developed a novel time-optimal control method, that accounts for the real wave loads acting on a ship, enabling effective planning and control of MASS at sea.
Published How do neural networks learn? A mathematical formula explains how they detect relevant patterns
(via sciencedaily.com) Original source Neural networks have been powering breakthroughs in artificial intelligence, including the large language models that are now being used in a wide range of applications, from finance, to human resources to healthcare. But these networks remain a black box whose inner workings engineers and scientists struggle to understand. Now, a team has given neural networks the equivalent of an X-ray to uncover how they actually learn.
Published Balancing training data and human knowledge makes AI act more like a scientist
(via sciencedaily.com) Original source When you teach a child how to solve puzzles, you can either let them figure it out through trial and error, or you can guide them with some basic rules and tips. Similarly, incorporating rules and tips into AI training -- such as the laws of physics --could make them more efficient and more reflective of the real world. However, helping the AI assess the value of different rules can be a tricky task.
Published Method rapidly verifies that a robot will avoid collisions
(via sciencedaily.com) Original source A new safety-check technique can prove with 100 percent accuracy that a planned robot motion will not result in a collision. The method can generate a proof in seconds and does so in a way that can be easily verified by a human.
Published Running performance helped by mathematical research
(via sciencedaily.com) Original source A new mathematical model has shown, with great precision, the impact that physiological and psychological parameters have on running performance and provides tips for optimized training.
Published New AI model draws treasure maps to diagnose disease
(via sciencedaily.com) Original source Researchers have developed an artificial intelligence model that can accurately identify tumors and diseases in medical images. The tool draws a map to explain each diagnosis, helping doctors follow its line of reasoning, check for accuracy, and explain the results to patients.
Published 2020 extreme weather event that brought fires and snow to western US
(via sciencedaily.com) Original source The same weather system that led to the spread of the devastating Labor Day wildfires in 2020 brought record-breaking cold and early-season snowfall to parts of the Rocky Mountains. Now, new research is shedding light on the meteorology behind what happened and the impacts of such an extreme weather event.
Published Study finds drought fuels invasive species after wildfires
(via sciencedaily.com) Original source Scientists uncover the intricate dance between drought, wildfires and invasive species in Southern California's coastal sage scrub ecosystems.
Published What math tells us about social dilemmas
(via sciencedaily.com) Original source Human coexistence depends on cooperation. Individuals have different motivations and reasons to collaborate, resulting in social dilemmas, such as the well-known prisoner's dilemma. Scientists now present a new mathematical principle that helps to understand the cooperation of individuals with different characteristics.
Published Cooler, wetter parts of Pacific Northwest likely to see more fires, new simulations predict
(via sciencedaily.com) Original source Forests in the coolest, wettest parts of the western Pacific Northwest are likely to see the biggest increases in burn probability, fire size and number of blazes as the climate continues to get warmer and drier.
Published Improving efficiency, reliability of AI medical summarization tools
(via sciencedaily.com) Original source Medical summarization, a process that uses artificial intelligence (AI) to condense complex patient information, is currently used in health care settings for tasks such as creating electronic health records and simplifying medical text for insurance claims processing. While the practice is intended to create efficiencies, it can be labor-intensive, according researchers who created a new method to streamline the way AI creates these summaries, efficiently producing more reliable results.
Published Plasma scientists develop computer programs that could reduce the cost of microchips and stimulate American manufacturing
(via sciencedaily.com) Original source Fashioned from the same element found in sand and covered by intricate patterns, microchips power smartphones, augment appliances and aid the operation of cars and airplanes. Now, scientists are developing computer simulation codes that will outperform current simulation techniques and aid the production of microchips using plasma, the electrically charged state of matter also used in fusion research. These codes could help increase the efficiency of the manufacturing process and potentially stimulate the renaissance of the chip industry in the United States.
Published Accelerating the discovery of single-molecule magnets with deep learning
(via sciencedaily.com) Original source Single-molecule magnets (SMMs) are exciting materials. In a recent breakthrough, researchers have used deep learning to predict SMMs from 20,000 metal complexes. The predictions were made solely based on the crystal structures of these metal complexes, thus eliminating the need for time-consuming experiments and complex simulations. As a result, this method is expected to accelerate the development of functional materials, especially for high-density memory and quantum computing devices.