Critical Transition Theory Shows Flickering in Heart Before Atrial Fibrillation

Atrial fibrillation ranks among the most common heart conditions, and episodes are difficult to predict. Researchers have proposed a way to define cardiac state and have studied the dynamics before the cardiac rhythm changes from normal sinus to AF rhythm and vice versa. The work, appearing in Chaos and based on critical transition theory, looks to provide an early warning for those with paroxysmal atrial fibrillation with potential implications for future wearable devices.

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Modeling COVID-19 Data Must Be Done With Extreme Care

As the virus causing COVID-19 began its devastating spread, an international team of scientists was alarmed by the lack of uniform approaches by various countries’ epidemiologists. Data modeling to predict the numbers of likely infections varied widely and revealed a high degree of uncertainty. In the journal Chaos, the group describes why modeling and extrapolating the evolution of COVID-19 outbreaks in near real time is an enormous scientific challenge that requires a deep understanding of the nonlinearities underlying the dynamics of epidemics.

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Correlations in COVID-19 Growth Point to Universal Strategies for Slowing Spread

Many months since the first COVID-19 outbreak, countries continue to explore solutions to manage the spread of the virus. Chaos theory researchers analyzed the growth of confirmed cases across four continents to better characterize the spread and examine which strategies are effective in reducing it, and their results, published in Chaos, found the virus commonly grows along a power law curve.

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Simulations Show Extreme Opinions Can Lead to Polarized Groups

In this week’s Chaos, researchers use a theoretical model to examine what effect extreme views have on making the entire system more polarized. The group’s network-based model extends a popular approach for studying opinion dynamics, called the Cobb model, and is based on the hypothesis that those with opinions farther from the middle of a political spectrum are also less influenced by others, a trait known to social scientists as “rigidity of the extreme.”

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Duchenne Muscular Dystrophy Diagnosis Improved by Simple Accelerometers

Testing for Duchenne muscular dystrophy can require specialized equipment, invasive procedures and high expense, but measuring changes in muscle function and identifying compensatory walking gait could lead to earlier detection. This week in Chaos, researchers present a relative coupling coefficient, which can be used to quantify the factors involved in the human gait and more accurately screen for the disorder. They measured movements of different parts of the body in test subjects, viewing the body as a kinematic chain.

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Researchers Discover Method to Detect Motor-Related Brain Activity

Motor-related brain activity is of great interest to researchers looking for a better way to improve neurorehabilitation, and one factor to consider is the suppression of the specific rhythmic activity of neurons within the sensorimotor cortex of the brain. Studies indicate this feature suffers from variability when using traditional methods to explore it. In the journal Chaos, scientists in Russia are approaching the problem from a different angle to search for a more robust feature of brain activity associated with accomplishing motor tasks.

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From Firearms to Fish — Following Patterns to Discover Causality

Mathematicians have successfully applied a new, pictorial approach to answer complex questions that puzzle analysts, such as, do media stories on firearm legislation influence gun sales? Cause-and-effect queries like this pop up in various fields, from finance to neuroscience, and objective methods are needed to deliver reliable answers.

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