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Categories: Computer Science: Quantum Computers, Mathematics: Statistics

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A new statistical method provides a more efficient way to uncover biologically meaningful changes in genomic data that span multiple conditions -- such as cell types or tissues.

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America was unprepared for the magnitude of the pandemic, which overwhelmed many counties and filled some hospitals to capacity. A new study suggests there may have been a mathematical method, of sorts, to the madness of those early COVID days.

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People often wonder why one nutritional study tells them that eating too many eggs, for instance, will lead to heart disease and another tells them the opposite. The answer to this and other conflicting food studies may lie in the use of statistics, according to a new report.

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Researchers followed the birth and death of tens of thousands of nematode worms using the 'Lifespan Machine', which collects lifespan data at unprecedented statistical resolution. They found that worms have at least two distinct 'biological ages', and that these have consistent correlations between each other, suggesting the existence of an invisible hierarchical structure that regulates the ageing process. The findings challenge the idea of living organisms having a single, universal biological age. It also means mean that biomarkers used to assess biological age can be changed by interventions such as diet, exercise, or drug treatments without actually turning a 'fast ager' into a 'slow ager'. The study calls into question the use of ageing biomarkers -- what exactly are they measuring?

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The contact.engineering platform enables users to create a digital twin of a surface and thus to help predict, for example, how quickly it wears out, how well it conducts heat, or how well it adheres to other materials.

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A commentary advocates the proper application of artificial intelligence in healthcare and warns of the dangers when machine learning algorithms are misused.

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Scientists have developed a method to identify symmetries in multi-dimensional data using Bayesian statistical techniques. Bayesian statistics has been in the spotlight in recent years due to improvements in computer performance and its potential applications in artificial intelligence. However, this statistical approach requires complex calculations of integrals, which are often considered approximations only. In their new study, the research team successfully derived new exact integral formulas. Their findings contribute to improving the accuracy of methods to identify data symmetries, possibly extending their applications to wider areas of interest, such as genetic analysis.

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A groundbreaking Bayesian method and new statistical analyses of genomic data from geckos in the Philippines shows that during the ice ages, the timing of gecko diversification gives strong statistical support for the first time to the Pleistocene aggregate island complex (PAIC) model of diversification, or 'species pump.'

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Fine-tuning the thermal conductivity of amorphous silicon used in technologies such as solar cells and image sensors should become much easier thanks to the computational topology and machine-learning-assisted discovery of the relationship between nano-scale structures and physical properties.

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A quantum system with only 51 charged atoms can take on more than two quadrillion different states. Calculating the system's behavior is child's play for a quantum simulator. But verifying the result is almost impossible, even with today's supercomputers. A research team has now shown how these systems can be verified using equations formulated in the 18th century.

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The famous double slit experiment shows that particles can travel on two paths at the same time -- but only by looking at a lot of particles and analysing the results statistically. Now a two-path-interference experiment has been designed that only has to measure one specific particle to prove that it travelled on two paths.

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Mathematicians have developed statistical methods that lay the framework for the crucial first step of determining whether there are any linkages between exposures and health outcomes from the 2010 Deepwater Horizon oil spill, which is considered the largest marine oil spill in the history of the U.S.

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Researchers have developed a machine learning model that could better measure baseball players' and teams' short- and long-term performance, compared to existing statistical analysis methods for the sport. Drawing on recent advances in natural language processing and computer vision, their approach would completely change, and could enhance, the way the state of a game and a player's impact on the game is measured.

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Professional organizations in science, technology, engineering and mathematics (STEM) fields could more effectively collect data on underrepresented groups in their fields, according to a new survey. With more robust information, STEM organizations could better target efforts to recruit and retain a more diverse membership.

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Power functional theory is a new approach that makes it possible to describe precisely the dynamics of many-particle systems over time.

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An artificial intelligence (AI)-based computer algorithm accurately predicted a person's likelihood of suffering heart problems related to clogged arteries based on voice recordings alone.

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Researchers have developed an algorithm that uses the most quantum bits to date to calculate ground state energy, the lowest-energy state in a quantum mechanical system. The discovery could make it easier to design new materials.

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A quantum ensemble -- a set of quantum states with their corresponding probabilities -- is essential to the encoding of classical information for transmission over quantum channels. But receivers must be able to 'guess' the transmitted quantum state, incurring a cost called 'guesswork.' Recently, researchers have derived analytical solutions of the guesswork problem for when the ensemble is subject to a finite set of conditions. The results constitute a first step towards future algorithms for quantum software.

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Scientists are evaluating machine-learning models using transfer learning principles.

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A new data analysis tool has revealed the specific immune cell types associated with increased risk of death from COVID-19.