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Categories: Ecology: Trees, Mathematics: Statistics

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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.

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Computational tools are indispensable in almost all scientific disciplines. Especially in cases where large amounts of research data are generated and need to be quickly processed, reliable, carefully developed software is crucial for analyzing and correctly interpreting such data. Nevertheless, scientific software can have quality quality deficiencies. To evaluate software quality in an automated way, computer scientists have designed the SoftWipe tool.

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Researchers have developed a new software tool to detect, evaluate and quantify off-target editing activity, including adverse translocation events that can cause cancer. The software is based on input taken from a standard measurement assay, involving multiplexed PCR amplification and Next-Generation Sequencing (NGS).

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The latest generation of personal alcohol breath testing devices pair with smartphones. While some of these devices were found to be relatively accurate, others may mislead users into thinking that they are fit to drive, according to a new study.

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Like conductors of a spooky symphony, researchers have 'entangled' two small mechanical drums and precisely measured their linked quantum properties. Entangled pairs like this might someday perform computations and transmit data in large-scale quantum networks.

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Inspired by a theoretical model of particles moving around on a chessboard, new robot swarm research shows that, as magnetic interactions increase, dispersed 'dumb robots' can abruptly gather in large, compact clusters to accomplish complex tasks. Researchers report that these 'BOBbots' (behaving, organizing, buzzing bots) are also capable of collectively clearing debris that is too heavy for one alone to move, thanks to a robust algorithm.

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The "three-body problem," the term coined for predicting the motion of three gravitating bodies in space, is essential for understanding a variety of astrophysical processes as well as a large class of mechanical problems, and has occupied some of the world's best physicists, astronomers and mathematicians for over three centuries. Their attempts have led to the discovery of several important fields of science; yet its solution remained a mystery.

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A reproducibility crisis is ongoing in scientific research, where many studies may be difficult or impossible to replicate and thereby validate, especially when the study involves a very large sample size. Now researchers have developed a statistical tool that can accurately estimate the replicability of a study, thus eliminating the need to duplicate the work and effectively mitigating the reproducibility crisis.

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A new study demonstrates that machine-learning strategies can be applied to routinely collected physiological data, such as heart rate and blood pressure, to provide clues about pain levels in people with sickle cell disease.