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Categories: Geoscience: Earthquakes, Mathematics: Modeling
Published Scientists use generative AI to answer complex questions in physics
(via sciencedaily.com) Original source Researchers used generative AI to develop a physics-informed technique to classify phase transitions in materials or physical systems that is much more efficient than existing machine-learning approaches.
Published Researchers wrestle with accuracy of AI technology used to create new drug candidates
(via sciencedaily.com) Original source Researchers have determined that a protein prediction technology can yield accurate results in the hunt to efficiently find the best possible drug candidates for many conditions.
Published Wavefunction matching for solving quantum many-body problems
(via sciencedaily.com) Original source Strongly interacting systems play an important role in quantum physics and quantum chemistry. Stochastic methods such as Monte Carlo simulations are a proven method for investigating such systems. However, these methods reach their limits when so-called sign oscillations occur. This problem has now been solved using the new method of wavefunction matching.
Published Century of statistical ecology reviewed
(via sciencedaily.com) Original source A special review examines highly-cited papers in statistical ecology. The review, which covers a century of research, details how models and concepts have evolved alongside increasing computational power.
Published New work extends the thermodynamic theory of computation
(via sciencedaily.com) Original source Physicists and computer scientists have recently expanded the modern theory of the thermodynamics of computation. By combining approaches from statistical physics and computer science, the researchers introduce mathematical equations that reveal the minimum and maximum predicted energy cost of computational processes that depend on randomness, which is a powerful tool in modern computers.
Published New machine learning algorithm promises advances in computing
(via sciencedaily.com) Original source Systems controlled by next-generation computing algorithms could give rise to better and more efficient machine learning products, a new study suggests.
Published AI advancements make the leap into 3D pathology possible
(via sciencedaily.com) Original source Researchers present Tripath: new, deep learning models that can use 3D pathology datasets to make clinical outcome predictions. The research team imaged curated prostate cancer specimens, using two 3D high-resolution imaging techniques. The models were then trained to predict prostate cancer recurrence risk on volumetric human tissue biopsies. By comprehensively capturing 3D morphologies from the entire tissue volume, Tripath performed better than pathologists and outperformed deep learning models that rely on 2D morphology and thin tissue slices.
Published Heavy snowfall and rain may contribute to some earthquakes
(via sciencedaily.com) Original source Episodes of heavy snowfall and rain likely contributed to a swarm of earthquakes over the past several years in northern Japan, researchers find. Their study shows climate conditions could initiate some earthquakes.
Published Pore pressure diffusion led to microseismicity at Illinois basin carbon sequestration site
(via sciencedaily.com) Original source Pore pressure diffusion generated by carbon dioxide injected underground at a carbon storage site in the Illinois Basin is the likely cause of hundreds of microearthquakes that took place at the site between 2011 and 2012, according to a new analysis.
Published An AI leap into chemical synthesis
(via sciencedaily.com) Original source Scientists introduce a large language model-based AI system that revolutionizes chemistry by integrating 18 advanced tools for tasks like organic synthesis and drug discovery.
Published Emergency department packed to the gills? Someday, AI may help
(via sciencedaily.com) Original source Emergency departments nationwide are overcrowded and overtaxed, but a new study suggests artificial intelligence (AI) could one day help prioritize which patients need treatment most urgently.
Published Researchers show that slow-moving earthquakes are controlled by rock permeability
(via sciencedaily.com) Original source A research group explores how the makeup of rocks, specifically their permeability -- or how easily fluids can flow through them -- affects the frequency and intensity of slow slip events. Slow slips' role in the earthquake cycle may help lead to a better model to predict when earthquakes happen.
Published Researchers use foundation models to discover new cancer imaging biomarkers
(via sciencedaily.com) Original source Researchers have harnessed the technology behind foundation models, which power tools like ChatGPT, to discover new cancer imaging biomarkers that could transform how patterns are identified from radiological images. Improved identification of such patterns can greatly impact the early detection and treatment of cancer.
Published Why getting in touch with our 'gerbil brain' could help machines listen better
(via sciencedaily.com) Original source Researchers have debunked a 75-year-old theory about how humans determine where sounds are coming from, and it could unlock the secret to creating a next generation of more adaptable and efficient hearing devices ranging from hearing aids to smartphones.
Published Toxic chemicals can be detected with new AI method
(via sciencedaily.com) Original source Researchers have developed an AI method that improves the identification of toxic chemicals -- based solely on knowledge of the molecular structure. The method can contribute to better control and understanding of the ever-growing number of chemicals used in society, and can also help reduce the amount of animal tests.
Published Do earthquake hazard maps predict higher shaking than actually occurred?
(via sciencedaily.com) Original source A research team studied earthquake hazard maps from five countries and found that all the maps seemed to overpredict the historically observed earthquake shaking intensities. In analyzing the possible causes, the researchers discovered the issue was with the conversion equations used in comparing the maps predicting future quakes with actual shaking data, rather than systemic problems with the hazard modeling itself.
Published New computer algorithm supercharges climate models and could lead to better predictions of future climate change
(via sciencedaily.com) Original source A study describes a new computer algorithm which can be applied to Earth System Models to drastically reduce the time needed to prepare these in order to make accurate predictions of future climate change. During tests on models used in IPCC simulations, the algorithm was on average 10 times faster at spinning up the model than currently-used approaches, reducing the time taken to achieve equilibrium from many months to under a week.
Published Improved AI process could better predict water supplies
(via sciencedaily.com) Original source A new computer model uses a better artificial intelligence process to measure snow and water availability more accurately across vast distances in the West, information that could someday be used to better predict water availability for farmers and others. The researchers predict water availability from areas in the West where snow amounts aren't being physically measured.
Published From disorder to order: Flocking birds and 'spinning' particles
(via sciencedaily.com) Original source Researchers have demonstrated that ferromagnetism, an ordered state of atoms, can be induced by increasing particle motility and that repulsive forces between atoms are sufficient to maintain it. The discovery not only extends the concept of active matter to quantum systems but also contributes to the development of novel technologies that rely on the magnetic properties of particles, such as magnetic memory and quantum computing.
Published AI deciphers new gene regulatory code in plants and makes accurate predictions for newly sequenced genomes
(via sciencedaily.com) Original source Elucidating the relationship between the sequences of non-coding regulatory elements and their target genes is key to understanding gene regulation and its variation between plant species and ecotypes. Now, an international research team developed deep learning models that link gene sequence data with mRNA copy number for several plant species and predicted the regulatory effect of gene sequence variation.