The model shows viral outbreaks can be prevented if at least 60% of a population complies with both measures
Artificial intelligence could be one of the keys for limiting the spread of infection in future pandemics. In a new study, researchers at the University of Gothenburg have investigated how machine learning can be used to find effective testing methods during epidemic outbreaks, thereby helping to better control the outbreaks.
Studies show wearing masks and social distancing can contain the spread of the COVID-19 virus, but their combined effectiveness is not precisely known. In Chaos, researchers at New York University and Politecnico di Torino in Italy developed a network model to study the effects of these two measures on the spread of airborne diseases like COVID-19. The model shows viral outbreaks can be prevented if at least 60% of a population complies with both measures.
The number of SEC inquiries about potential terrorist ties has grown substantially in recent years, and according to new research from Duke University's Fuqua School of Business, the increase could reduce the quality of the agency's financial reporting oversight.
Researchers from Singapore-MIT Alliance for Research and Technology (SMART) and National University of Singapore (NUS) have developed a new multifaceted method that can directly observe compositional fluctuations in indium gallium nitride, a semiconductor material used in LEDs. The method can be adapted and applied in other materials science studies to investigate compositional fluctuations.
Optimizing network communication accelerates training in large-scale machine-learning models.
Researchers from Tokyo Metropolitan University have shown that a quantity known as "thermoelectric conductivity" is an effective measure for the dimensionality of newly developed thermoelectric nanomaterials. Studying films of semiconducting single-walled carbon nanotubes and atomically thin sheets of molybdenum sulfide and graphene, they found clear distinctions in how this number varies with conductivity, in agreement with theoretical predictions in 1D and 2D materials. Such a metric promises better design strategies for thermoelectric materials.
Researchers have developed a new algorithm capable of identifying features of male zebra finch songs that may underlie the distinction between a short phrase sung during courtship, and the same phrase sung in a non-courtship context. Sarah Woolley of McGill University in Montreal, Canada, and colleagues present these findings in the open-access journal PLOS Computational Biology.
In a new article published in Proceedings of the National Academy of Sciences of the United States of America, Moffitt Cancer Center researchers demonstrate how an important defect in STING gene expression in melanoma cells contributes to their evasion from immune cell detection and destruction.
Powerful algorithms used by Netflix, Amazon and Facebook can 'predict' the biological language of cancer and neurodegenerative diseases like Alzheimer's, scientists have found. Big data produced during decades of research was fed into a computer language model to see if artificial intelligence can make more advanced discoveries than humans.