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Categories: Energy: Nuclear, Mathematics: Statistics

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Engineers are working to develop a new, economically viable and safe source of low carbon electricity through nuclear fusion.

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Data stored in spin states of ytterbium atoms can be transferred to surrounding atoms in a crystal matrix.

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A research team has developed a large-area suspended graphene and irradiated the thinnest graphene target with an ultra-intense laser to realize high-energy ion acceleration. Their findings will be applied to the development of compact, efficient ion accelerators used for cancer treatment, nuclear fusion and so on.

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Despite being among the most researched topics on supercomputers, a fundamental understanding of the effects of turbulent motion on fluid flows still eludes scientists. A new approach aims to change that.

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Researchers have developed a system based on computer vision techniques that allows automatic analysis of biomedical videos captured by microscopy in order to characterize and describe the behavior of the cells that appear in the images.

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Community structure, including relationships between and within groups, is foundational to our understanding of the world around us.

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Asymptomatic COVID-19 cases are the bane of computer modelers' existences -- they throw off the modeling data to an unknown degree. A new approach explores using historic epidemic data from eight different countries to estimate the transmission rate and fraction of under-reported cases.

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Researchers have built a machine learning framework that can define the mathematical equations describing a cell's trajectory from one state to another, such as its development from a stem cell into one of several different types of mature cell. The framework, called dynamo, can also be used to figure out the underlying mechanisms -- the specific cocktail of gene activity -- driving changes in the cell.

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Retrieving an accurate picture of what a tagged animal does as it journeys through its environment requires statistical analysis, especially when it comes to animal movement, and the methods statisticians use are always evolving to make full use of the large and complex data sets that are available. A recent study by researchers at the Institute for the Oceans and Fisheries (IOF) and the UBC department of statistics has taken us a step closer to understanding the behaviours of northern resident killer whales by improving statistical tools useful for identifying animal behaviours that can't be observed directly.

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Mathematicians created a statistical model that can be used to detect misinformation in social posts.

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Novel software for grouping immunological T-cell receptors may enable the identification of shared patterns that could be used to determine if a person has previously been infected or vaccinated against a given pathogen.

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By observing how strange particles called anyons dissipate heat, researchers have shown that they can probe the properties of these particles in systems that could be relevant for topological quantum computing.

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Scientists are using a new mathematical tool to predict how combinations of genetic mutations cause different types of tumors.

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Mathematical modeling of disease spread suggests that herd immunity could be achieved with fewer vaccine doses by using Bluetooth-based contact-tracing apps to identify people who have more exposure to others -- and targeting them for vaccination.

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Archaeologists have long had a dating problem. The radiocarbon analysis typically used to reconstruct past human demographic changes relies on a method easily skewed by radiocarbon calibration curves and measurement uncertainty. And there's never been a statistical fix that works -- until now.

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The COVID-19 pandemic may be the deadliest viral outbreak the world has seen in more than a century. But statistically, such extreme events aren't as rare as we may think, asserts a new analysis of novel disease outbreaks over the past 400 years. A newly assembled record of past outbreaks was used to estimate the probability of a pandemic with similar impact to COVID-19 is about 2 percent in any year. And that probability is growing.

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A new method could lead to more accurate predictions of how new materials behave at the atomic scale.

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Researchers have modeled COVID-19 completion versus cessation in clinical trials using machine learning algorithms and ensemble learning.

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A major challenge in cancer therapy is the adaptive response of cancer cells to targeted therapies. Although this adaptive response is theoretically reversible, such a reversal is hampered by numerous molecular mechanisms that allow the cancer cells to adapt to the treatment. A team has used information theory, in order to objectify in vivo the molecular regulations at play in the mechanisms of the adaptive response and their modulation by a therapeutic combination.

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It may only be a matter of time until the growing problem of 'deep fakes' converges with geographical information science (GIS). A research team are doing what they can to get ahead of the problem.