Articles tagged with Mathematical Modeling
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.
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.
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 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.
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.
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 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 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 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.
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.
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.
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.
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 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.
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.
A new study models the demography of agricultural transitions, finding that population dynamics played a crucial role in the adoption of farming. The researchers used an ecological model to analyze interactions between farmers and hunter-gatherers, highlighting the impact of factors such as group migration and cultural assimilation.
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.
Three UVA Engineering faculty members, Scott T. Acton, Gustavo Kunde Rohde and Shannon Barker, have been named to the 2025 class of the American Institute for Medical and Biological Engineering (AIMBE) College of Fellows. They are recognized for their contributions to biomedical engineering research, innovation, teaching and leadership.
A new mathematical model reveals that humans played an active role in the transition from hunting and gathering to farming, driven by factors like population growth rates and competition. The study challenges traditional views that focused on environmental factors, providing fresh insight into the rise of farming.
A team of researchers from Osaka University has demonstrated that human tissue can be used to solve complex equations and process information, outperforming traditional computing methods. This breakthrough uses the concept of reservoir computing, where data is input into a complex 'reservoir' that encodes rich patterns.
Researchers developed a new method to include uncertainty in predictive algorithms, ensuring accurate and reliable solutions. The approach uses Markov models to explicitly include uncertainty in specific parameters, allowing for faster predictions and more complete analysis.
Researchers at Kumamoto University have developed a new mathematical modeling technique for linear periodically time-varying systems, enhancing the accuracy of control system models. This breakthrough has profound implications for industries relying on complex control systems, such as autonomous vehicles and aerospace applications, imp...
Researchers discovered that pedestrians form neat lanes in crossing roads only until people start veering off at extreme angles, after which the flow becomes disordered. The team's theory predicts that critical angle of 13 degrees marks the point where crowds collapse from order to disorder.
Researchers studied Aurora Subglacial Basin's subglacial hydrology, finding dynamic rivers that change over time. This new insight may alter predictions of rising sea levels and the role of subglacial water in ice dynamics.
A new model predicts how bacteria navigate obstacles to spread, informing strategies for curbing infections or designing better drug delivery. The model focuses on three surface states: uninterrupted movement, sliding along surfaces, and getting stuck in corners.
Researchers have experimentally confirmed complex synchronisation patterns in oscillatory systems, including leaf-like structures and gaps representing unsynchronised states. This breakthrough builds on previous studies using breathing-soliton lasers to explore nonlinear dynamics.
Researchers from Virginia Tech have published a visionary paper on fusing wireless technologies and AI to create human-like common sense. The team aims to develop a network that can think, plan, and imagine like humans, enabling seamless merging of physical, virtual, and digital dimensions.
The Open Brain Institute launches a groundbreaking platform to simulate and study digital brains, empowering researchers to explore brain complexity and diseases. With its virtual neuroscience laboratories, the OBI enables global collaboration and access to cutting-edge virtual labs.
Researchers discovered how bacterial swarms transition from organized movement to chaotic flow as confinement radius increases. The study reveals intermediate states between order and turbulence through large-scale experiments, computer modeling, and mathematical analysis. These findings provide insights into the universal properties o...
Eliza Michalopoulou is leading a research project to improve ocean floor mapping using sound waves, aiming to understand the seabed's properties and characteristics. The goal is to enhance anti-submarine warfare strategies and contribute to global efforts like Seabed 2030 and Ocean Decade.
Yue Yu, Lehigh University mathematics professor, wins award for pioneering work in data-driven nonlocal models and integrating mathematical analysis into computational model design. The recognition honors her outstanding contributions to the field of computational mechanics at a young age.
A new study found that football teams move as though they are a single person, displaying Lévy walk patterns while hunting for the ball. This collective behavior suggests that individual players complement each other's actions in response to the game.
A new brain-mapping technique identified memory-related brain cells vulnerable to protein buildup, a key factor in Alzheimer's disease. The study found that certain cell types in the hippocampus and cortex were more affected by tau buildup.
A groundbreaking new framework unifies gravity from quantum relative entropy, bridging the gap between quantum mechanics and Einstein's general relativity. The theory predicts a small, positive cosmological constant aligning with experimental observations.
A research team identified simple rules governing decision-making during epidemics, which balance infection costs and social distancing. The guidelines predict population behavior based on disease reproduction number and infection cost, offering a new tool for governments to design intervention strategies.
A deep learning model, CGMformer, leverages large-scale continuous glucose monitoring (CGM) data to extract individual glucose dynamics. The model captures a continuous picture of glucose fluctuations, identifying patterns that may indicate early metabolic dysfunction.
A new mathematical model developed at the University of Waterloo can determine a baby's overall drug exposure when their mother is taking medication, specifically Levetiracetam. The probability of negative effects on a breastfeeding infant is very low for typically prescribed doses.
Researchers at North Carolina State University have developed a new technique to improve the efficiency of food-delivery operations. The technique accounts for key factors such as food supply, location, and vehicle capacity to determine optimized routes that make food delivery faster and more fuel-efficient.