Researchers at OIST develop world-class 'hurricane-in-a-lab' setup to study turbulent Taylor-Couette flows. By re-examining Kolmogorov's framework, they find that the power law predicts universal behavior across all small-scale flows, resolving a long-standing inconsistency.
The Lehigh University team created a computational model to predict the hemodynamic response of patients with AFib, helping tailor neurostimulation dosages. The model validated against clinical data and predicted accurate effects on blood pressure, heart rate, and stroke volume.
A new mathematical framework, STIV, can predict larger-scale effects like proteins unfolding and crystals forming without costly simulations or experiments. The framework solves a 40-year-old problem in phase-field modeling, allowing for the design of smarter medicines and materials.
EPFL researchers have discovered a room-temperature version of the Leidenfrost effect, where oil droplets can bounce for up to five minutes on a vibrating solid surface. The phenomenon is driven by the droplet's own deformations, allowing it to perpetually bounce indefinitely.
A new project aims to develop a computationally efficient model that accurately predicts how additive manufacturing process parameters influence the solidification microstructure of binary alloy solidification. This will enable optimization of additively manufactured parts with confidence in critical industries.
Professor Dan M. Frangopol, Lehigh University's inaugural Fazlur R. Khan Endowed Chair, was recognized for his work on life-cycle civil engineering at the 21st International Probabilistic Workshop in Germany. He is widely credited with establishing this field and has authored over 500 peer-reviewed journal articles.
Researchers from the Institute of Industrial Science, The University of Tokyo, have developed a mathematical theory that can be used to design optimization strategies for dynamical networks, such as those comprising living organisms. They found that tools from information theory provided a way to simplify nonlinear optimization problem...
Researchers at the University of Missouri found that using blockchain to track ingredients through the supply chain reduces consumer uncertainty about food safety and increases willingness to pay premium prices. The technology also provides clear information about the source of ingredients, boosting trust in sustainable foods.
The book provides an overview of agent-based modeling and multi-agent systems, highlighting their application in understanding economic crises. It integrates machine learning to enhance adaptation and behavior of agents in dynamic environments.
The SAGEST Predictive Simulation Center will develop simulation tools to give scientists confidence in exploring extreme physical conditions. The center, led by UVA's Xinfeng Gao, will use high-fidelity and low-fidelity solvers to balance accuracy and efficiency in predictions.
Researchers developed a mathematical model that replicates the muscle movements of the esophagus during swallowing and reveals insights into esophageal motility disorders. The model includes signaling from the brain and nerves, as well as muscle contractions and relaxations, and can simulate various disorders.
Researchers developed a data-driven macroscopic mobility model that relies on simple observations from city planners' routine data collection. The D3M model can accurately represent diverse traffic conditions and simulate complex system-level dynamics.
The European consortium, funded by €4.5M, will recruit and train 15 PhD researchers to develop new models and methods for understanding complex biological systems. The network, coordinated by the University of Edinburgh, aims to create a framework grounded in physics that can be applied systematically.
Researchers are decoding animal decision-making using glass knifefish, exploring the trade-off between gathering information and acting on it. The study, funded by the NIH, aims to understand how animals make decisions in uncertain environments and may lead to breakthroughs in robotics and medicine.
A UMass Amherst kinesiologist has received a $2 million NIH grant to study how myosin molecules work together to drive different processes within cells. His research aims to develop drugs for heart failure, neurological conditions and genetic forms of deafness.
A new theory explains how ideas gain momentum and spread like wildfire. The researchers introduce a mathematical model that takes into account the evolution of ideas as they spread, leading to complex results with unexpected outcomes. This work has implications for understanding belief formation, misinformation, and social contagion.
A new study reveals how Lactococcus lactis regulates the production of a key precursor in vitamin K2 biosynthesis. By tuning substrate supply and genetic architecture, researchers can push production above natural ceilings, opening the door to engineering bacteria for enhanced vitamin K2 production.
A new study from the Complexity Science Hub reveals that innovation can only endure over time if it is balanced with exnovation - the loss or forgetting of older possibilities. The researchers found an interesting trade-off between innovation speed and system stability.
A study published in PLOS Neglected Tropical Diseases has shown that combining country-level information with individual-level variables can improve the identification of soil-transmitted helminth infections among migrant populations. Researchers found that country-level indicators are stronger predictors than individual-level variable...
The book explores foundational and advanced principles of modeling concurrent control systems using Petri nets, focusing on building reliable, verifiable systems where concurrency plays a central role.
Researchers create a technique to model organic objects, creating photorealistic 3D images of complex shapes for autonomous sorting. This method improves robotic systems that sort microscopic marine fossils used in climate research.
A recent study published in Brain reveals that a mathematical model can classify genes into four categories based on their interaction with the brain's network patterns. This classification helps explain why some brain regions deteriorate rapidly while others remain intact, providing new insights into Alzheimer's disease.
Researchers developed a theoretical model that accurately describes the relationship between mechanical stress and chemical reactions, resolving discrepancies in previous studies. The new model helps predict mechanochemical reactions, promising for greener manufacturing and lubricant design.
A mathematical model was developed to calculate the economic and environmental costs of fungicide resistance in agriculture. The study found that yields can increase or decrease depending on the context, and that expensive fungicides can actually reduce costs.
Researchers from The University of Osaka have devised new mathematical models to describe the mechanics of crystal defects. Using differential geometry, they provided a robust and rigorous framework for understanding these phenomena.
A new analytical method reveals overlooked species at risk of extinction, providing a valuable layer of insight for conservationists. The dual-role approach captures both predator and prey interactions, identifying keystone species and vulnerabilities.
A new study reveals that Alzheimer's risk genes influence tau buildup and spread in distinct pathways, challenging traditional views of the disease. Four gene types were identified: Network-Aligned Vulnerability and Resilience, and Network-Independent Vulnerability and Resilience.
A new study published in PNAS Nexus explores how opinions within inner circles influence the perception of social division. The researchers found that consensus within one's circle can exaggerate perceptions of polarization, and that subjective lenses change over time, influencing how individuals perceive societal polarization.
Scientists have developed a new tool named scICE to tackle the stability problem in single-cell RNA sequencing data. The tool provides a way to validate clustering outcomes mathematically, ensuring higher confidence in conclusions drawn from single-cell data.
Researchers analyzed viral loads during early infection to predict disease progression and developed a method to identify patients at risk of severe symptoms. The study suggests that patients with high viral loads are more likely to experience long-lasting skin lesions and severe symptoms.
Researchers found that immunocompromised animals respond better to phage therapy due to depleted alveolar macrophages, which initially seemed to hinder its efficacy. The study highlights the importance of the immune system in phage therapy and may inform personalized treatment strategies.
A team led by L. Mahadevan found that young anacondas can execute a quick, one-off skating movement called the 'S-start' due to their physical attributes. This movement is similar to sidewinding and could inspire new robotic systems.
A research team developed an analytical model to evaluate the performance of grant-free communications schemes in densely populated IoT environments. They found that interference cancellation improved base station throughput but did not resolve the near-far problem, while power control addressed it but led to decreased overall network ...
Advanced computer simulations reveal shear deformations and internal mechanical stresses play a crucial role in grain growth and evolution. This discovery helps explain why real polycrystals behave differently than predicted and offers insights into designing stronger materials.
A UBC Okanagan research team has developed TrajReducer, an AI system that accurately predicts vessel destinations by analyzing ship trajectories and patterns. This technology can help Canadian ports adapt quickly to global supply chain disruptions and improve operational efficiency.
Researchers at Harvard developed link-bots, centimeter-scale robots composed of V-shaped chains with notched links, capable of coordinated movements and emergent collective behavior. The team demonstrated link-bots' ability to move forward, stop, change direction, squeeze through gaps, and cooperate on tasks.
A new study found a universal organizing pattern governing species distribution across biogeographical regions. The research reveals that core areas provide optimal conditions for species survival and diversification, driving biodiversity radiance outward.
Researchers at the University of Maryland Baltimore County have made an important discovery about how cells move through tissues, combining mathematical modeling with advanced imaging to show that physical shape and chemical signals interact. The study's findings could inform new strategies for controlling cell movement via medical tre...
Researchers from The University of Osaka have demonstrated that vision transformers can spontaneously develop human-like visual attention patterns without specific training. This breakthrough showcases the potential of self-supervised learning for advancing AI applications and modeling biological vision.
Aurora, a state-of-the-art machine learning model, delivers high-quality forecasts for key environmental systems like air quality, weather, and tropical cyclones. The model's flexibility enables it to be used for various future scenarios, including flood risks, wildfire spread, and renewable energy output.
Research found that early-life growth plays a significant role in determining final adult height, accounting for about 67% of the variation. Childhood growth also accounted for a substantial proportion of the difference in adult height.
Researchers at Nagoya University discovered that combining two tiny vibrating elements can amplify their signal up to 100 million times, enabling the transmission of clear signals over long distances. This finding could innovate long-distance communications and remote medical devices without requiring high energy consumption.
Researchers found that a fertility rate of at least 2.7 children per woman is needed to reliably avoid eventual extinction in small populations. A female-biased birth ratio can reduce extinction risk, helping more lineages survive over time.
SourcePLOS·JournalPLOS One·TypeComputational simulation/modeling·DateApr 30, 2025
Researchers developed a new method to predict the effectiveness of mangroves in protecting coastlines against extreme weather events. The HU method uses wave non-linearity and can calculate wave height attenuation with ease, saving billions of dollars worldwide.
Mathematical modeling research from University of Utah Health suggests that treating moderate cases with antibiotics could limit the spread of cholera and reduce the likelihood of antibiotic resistance. In areas where cholera spreads slowly, aggressive antibiotic use may even stop outbreaks entirely.
A University of Ottawa-led study reveals that serotonin neurons are connected and interact with each other, controlling serotonin release in specific regions of the brain. This complex system has implications for understanding decision-making and developing targeted therapeutics for mood disorders.
Researchers developed a new method to determine optimal threshold time for restricted mean survival time analysis, improving statistical power in clinical and epidemiological studies. The method outperformed traditional statistical analysis methods in real-world scenarios, revealing clear differences between treatment groups.
Machine learning (ML) techniques can identify materials with high synthesis feasibility and suggest suitable experimental conditions. Computational models derived from thermodynamics and kinetics enhance predictive performance and interpretability of ML models, optimizing experimental design and increasing synthesis efficiency.
Researchers Ana Ivonne Vazquez-Armendariz and Jan Hasenauer are using their prize money to study the functions of scavenger cells in the lungs, combining mathematics and medicine. Their new models aim to understand how these immune cells behave in the lung, potentially unlocking better defense mechanisms.
Researchers analyzed massive audio recordings to create a dictionary of short melodies in English-language prosody, assigning functions and meanings. They discovered hundreds of basic patterns with linguistic functions, including conveying attitudes such as curiosity or surprise, and identified syntactic rules governing their order.
A mathematical modeling study suggests that sustained HIV remission or eradication could consistently reduce new HIV infections among men who have sex with men (MSM) in the Netherlands. However, transient remission with a risk of rebound may increase new infections if not closely monitored.
Researchers propose universe may rotate with one rotation every 500 billion years, resolving Hubble tension paradox and explaining discrepancies in astronomical measurements. The theory is compatible with current models and doesn't break any known laws of physics.
A Lehigh University team developed a novel machine learning method to predict abnormal grain growth in materials, enabling the creation of stronger, more reliable materials. The model successfully predicted abnormal grain growth in 86% of cases, with predictions made up to 20% of the material's lifetime.
Researchers developed a new modeling method that estimates customer interest beyond completed transactions and traditional forecasting techniques, providing a more precise way to understand demand. The approach helps businesses optimize operations and improve decision-making by reconstructing missing pieces of the demand picture.
Increasing dietary potassium and reducing sodium can effectively regulate blood pressure, according to a new mathematical model developed by the University of Waterloo. The study suggests that a higher ratio of potassium to sodium intake may be more effective for lowering blood pressure than simply reducing sodium intake.
The study reveals that frustrated assemblies can lead to materials with desirable properties like strength and toughness. By understanding the relationship between structure and property, researchers aim to design advanced materials for medical devices and sustainable construction.
A study reveals widespread overlap between feeding grounds for seabirds, marine mammals, and regions with high wind potential. Researchers propose developing risk maps to predict conflicts and recommend expanding marine protected areas and strengthening spatial planning tools.
Researchers developed a machine learning-powered fluid simulation model that significantly reduces computation time without compromising accuracy. The new surrogate model maintains the same level of accuracy as traditional particle-based simulations while reducing computation time from approximately 45 minutes to just three minutes.
A project aims to understand how temperature, light pollution, and bird abundance affect West Nile virus transmission in mosquitoes. The goal is to advise health departments on the best time to kill bugs and limit transmission.
A new framework developed by MIT researchers allows large language models (LLMs) to break down complex planning problems into manageable parts and find optimal solutions using software optimization tools. The framework achieves an 85% success rate on nine complex challenges, outperforming the best baseline.