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Mathematical Modeling News
June 26, 2022

Top Headlines
 

New Theory of Decision-Making Seeks to Explain Why Humans Don't Make Optimal Choices

A new theory of economic decision-making offers an explanation as to why humans, in general, make decisions that are simply adequate, not ...

Bumps Could Smooth Quantum Investigations

Materials theorists model a contoured surface overlaid with 2D materials and find it possible to control their electronic and magnetic properties. The discovery could simplify research into many-body ...

Great Timing, Supercomputer Upgrade Lead to Successful Forecast of Volcanic Eruption

In the fall of 2017, a team of geologists had just set up a new volcanic forecasting modeling program on the Blue Waters and iForge supercomputers. ...

Traveling Wave of Light Sparks Simple Liquid Crystal Microposts to Perform Complex Dance

Mastering control over the dynamic interplay among optical, chemical and mechanical behavior in single-material, liquid crystalline elastomers, ...
Latest Headlines
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Earlier Headlines
 

A New Model Sheds Light on How We Learn Motor Skills

Researchers have developed a mathematical model of motor learning that reflects the motor learning process in the human brain. Their findings suggest that motor exploration -- that is, increased ...

Math Model Predicts Efficacy of Drug Treatments for Heart Attacks

Researchers used mice to develop a mathematical model of a myocardial infarction. The new model predicts several useful new drug combinations that may one day help treat heart attacks, according to ...

Estimating Tumor-Specific Total mRNA Level Predicts Cancer Outcomes

Researchers have developed a mathematical tool to estimate tumor-specific RNA levels from tumor samples with mixed cell types. Using this technique on thousands of samples found that higher mRNA ...

Human Behavior Is Key to Building a Better Long-Term COVID Forecast

From extreme weather to another wave of COVID-19, forecasts give decision-makers valuable time to prepare. When it comes to COVID, though, long-term forecasting is a challenge, because it involves ...

Accelerating the Pace of Machine Learning

Machine learning happens a lot like erosion. Data is hurled at a mathematical model like grains of sand skittering across a rocky landscape. Some of those grains simply sail along with little or no ...

New Model Could Improve Matches Between Students and Schools

Simultaneous and uncoordinated school admissions in situations where students have multiple options can lead to unfilled seats and a lot of stress for families and administrators. To create a fairer, ...

How Cells Correct Errors Under Time Pressure

How does a cell balance risk and speed when dividing? Scientists have developed and experimentally tested the first mathematical theory that describes the cell's best strategy for dividing ...

Machine Learning Framework IDs Targets for Improving Catalysts

Chemists have developed a new machine-learning (ML) framework that can zero in on which steps of a multistep chemical conversion should be tweaked to improve productivity. The approach could help ...

Computational Sleuthing Confirms First 3D Quantum Spin Liquid

Computational detective work by physicists has confirmed cerium zirconium pyrochlore is a 3D quantum spin liquid, a solid material in which quantum entanglement and the geometric arrangement of atoms ...

Development of an Ensemble Model to Anticipate Short-Term COVID-19 Hospital Demand

Scientists identified the most relevant predictive variables for anticipating hospital demand and proposed using an ensemble model based on the average of the predictions of several individual ...

'Digital Twins,' an Aid to Give Individual Patients the Right Treatment at the Right Time

An international team of researchers have developed advanced computer models, or 'digital twins', of diseases, with the goal of improving diagnosis and treatment. They used one such model ...

Deep Learning Model to Predict Adverse Drug-Drug Interactions

The intake of multiple drugs can result in adverse health effects due to unexpected drug-drug interactions (DDIs). Now, researchers have developed a deep learning model that predicts DDIs based on ...

Plug-and-Play Organ-on-a-Chip Can Be Customized to the Patient

Researchers have developed a model of human physiology in the form of a multi-organ chip consisting of engineered human heart, bone, liver, and skin that are linked by vascular flow with circulating ...

COVID-19 Lockdown Measures Affect Air Pollution from Cities Differently

Seizing on a natural experiment created by restricted travel, researchers combine a network model with air pollution data before and during ...

Sending out Bacteria-Carrying Mosquitoes to Protect People from Dengue

Researchers developed a model to spatially distribute mosquitoes infected with Wolbachia bacteria, which reduce the transmission of the dengue virus. The researchers use real data on human and vector ...

Researchers Create 3D Model for Rare Neuromuscular Disorders, Setting Stage for Clinical Trial

Scientists have created a bioengineered 3-D model that mimics the biology of two rare diseases. The researchers used the 'tissue chip' model to show how a drug could potentially treat the ...

Study Shows Simple, Computationally-Light Model Can Simulate Complex Brain Cell Responses

Studying how brain cells respond to signals from their neighbors can aid the understanding of cognition and development. However, experimentally measuring the brain's activity is complicated. ...

Tear-Free Hair Brushing? All You Need Is Math

Scientists explore the mathematics of combing and explain why the brushing technique used by so many is the most effective method to detangle a bundle of ...

Layered Controls Can Significantly Curb Exposure to COVID-19

Using a new computational model that simulates the life cycle of pathogen-laden particles, researchers found that a combination of distancing of six feet, universal mask-wearing, and increased room ...

Machine Learning Model Could Better Measure Baseball Players' Performance

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 ...

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