Articles tagged with Mathematical Modeling
Comprehensive exploration of living organisms, biological systems, and life processes across all scales from molecules to ecosystems. Encompasses cutting-edge research in biology, genetics, molecular biology, ecology, biochemistry, microbiology, botany, zoology, evolutionary biology, genomics, and biotechnology. Investigates cellular mechanisms, organism development, genetic inheritance, biodiversity conservation, metabolic processes, protein synthesis, DNA sequencing, CRISPR gene editing, stem cell research, and the fundamental principles governing all forms of life on Earth.
Comprehensive medical research, clinical studies, and healthcare sciences focused on disease prevention, diagnosis, and treatment. Encompasses clinical medicine, public health, pharmacology, epidemiology, medical specialties, disease mechanisms, therapeutic interventions, healthcare innovation, precision medicine, telemedicine, medical devices, drug development, clinical trials, patient care, mental health, nutrition science, health policy, and the application of medical science to improve human health, wellbeing, and quality of life across diverse populations.
Comprehensive investigation of human society, behavior, relationships, and social structures through systematic research and analysis. Encompasses psychology, sociology, anthropology, economics, political science, linguistics, education, demography, communications, and social research methodologies. Examines human cognition, social interactions, cultural phenomena, economic systems, political institutions, language and communication, educational processes, population dynamics, and the complex social, cultural, economic, and political forces shaping human societies, communities, and civilizations throughout history and across the contemporary world.
Fundamental study of the non-living natural world, matter, energy, and physical phenomena governing the universe. Encompasses physics, chemistry, earth sciences, atmospheric sciences, oceanography, materials science, and the investigation of physical laws, chemical reactions, geological processes, climate systems, and planetary dynamics. Explores everything from subatomic particles and quantum mechanics to planetary systems and cosmic phenomena, including energy transformations, molecular interactions, elemental properties, weather patterns, tectonic activity, and the fundamental forces and principles underlying the physical nature of reality.
Practical application of scientific knowledge and engineering principles to solve real-world problems and develop innovative technologies. Encompasses all engineering disciplines, technology development, computer science, artificial intelligence, environmental sciences, agriculture, materials applications, energy systems, and industrial innovation. Bridges theoretical research with tangible solutions for infrastructure, manufacturing, computing, communications, transportation, construction, sustainable development, and emerging technologies that advance human capabilities, improve quality of life, and address societal challenges through scientific innovation and technological progress.
Study of the practice, culture, infrastructure, and social dimensions of science itself. Addresses how science is conducted, organized, communicated, and integrated into society. Encompasses research funding mechanisms, scientific publishing systems, peer review processes, academic ethics, science policy, research institutions, scientific collaboration networks, science education, career development, research programs, scientific methods, science communication, and the sociology of scientific discovery. Examines the human, institutional, and cultural aspects of scientific enterprise, knowledge production, and the translation of research into societal benefit.
Comprehensive study of the universe beyond Earth, encompassing celestial objects, cosmic phenomena, and space exploration. Includes astronomy, astrophysics, planetary science, cosmology, space physics, astrobiology, and space technology. Investigates stars, galaxies, planets, moons, asteroids, comets, black holes, nebulae, exoplanets, dark matter, dark energy, cosmic microwave background, stellar evolution, planetary formation, space weather, solar system dynamics, the search for extraterrestrial life, and humanity's efforts to explore, understand, and unlock the mysteries of the cosmos through observation, theory, and space missions.
Comprehensive examination of tools, techniques, methodologies, and approaches used across scientific disciplines to conduct research, collect data, and analyze results. Encompasses experimental procedures, analytical methods, measurement techniques, instrumentation, imaging technologies, spectroscopic methods, laboratory protocols, observational studies, statistical analysis, computational methods, data visualization, quality control, and methodological innovations. Addresses the practical techniques and theoretical frameworks enabling scientists to investigate phenomena, test hypotheses, gather evidence, ensure reproducibility, and generate reliable knowledge through systematic, rigorous investigation across all areas of scientific inquiry.
Study of abstract structures, patterns, quantities, relationships, and logical reasoning through pure and applied mathematical disciplines. Encompasses algebra, calculus, geometry, topology, number theory, analysis, discrete mathematics, mathematical logic, set theory, probability, statistics, and computational mathematics. Investigates mathematical structures, theorems, proofs, algorithms, functions, equations, and the rigorous logical frameworks underlying quantitative reasoning. Provides the foundational language and tools for all scientific fields, enabling precise description of natural phenomena, modeling of complex systems, and the development of technologies across physics, engineering, computer science, economics, and all quantitative sciences.
Researchers developed a school simulation model that shows how the virus spreads in different settings and calculates the effectiveness of measures against its spread. The model reveals that elementary and lower secondary schools can keep reproduction rates below 1 with classroom ventilation, wearing masks, and class size reduction.
A multidisciplinary team at UNIGE has developed a simple mathematical equation to explain the complex distribution of scales in ocellated lizards. This discovery contributes to a better understanding of skin color pattern evolution and provides an optimal pattern for animal survival.
Researchers developed MonoCon, a new AI technique that enables accurate identification of 3D objects in 2D images. By incorporating auxiliary context, the method improves object detection and estimation accuracy, paving the way for safer and more robust autonomous vehicles.
A mathematical model developed by researchers at Massachusetts General Hospital has identified biological markers that can predict treatment responses in COVID-19 patients. The model reveals differences in patient characteristics and response to therapy, enabling clinicians to provide optimal care for diverse patients.
Mathematical modeling can assess toxicants' impact on river populations without endangering the environment. A new model developed by Peng Zhou and Qihua Huang describes the interactions between a population and a toxicant in an advective environment.
Researchers develop a symmetrized N-center representation that provides a natural, fully equivariant framework for learning properties associated with multiple atoms. The approach gives excellent accuracy for predicting atomic properties despite using only linear or kernel regression.
A recent study found that conventional metrics for detecting audio adversarial examples are unreliable and fail to accurately represent human perception. Researchers proposed a more robust evaluation method, but acknowledge the complexity of modeling auditory perception with mathematical metrics.
New research suggests that ultra-low velocity zones in the deep mantle may be regions made of different rocks than the rest of the mantle, with compositions potentially linked to the early Earth. The study's findings imply the presence of layered structures within these zones, shedding light on their origin and evolution.
Researchers developed a fair-diverse allocation optimization framework to optimize the distribution of COVID-19 vaccines, treatments, and testing supplies. The model aims to get limited resources to the most vulnerable subgroups while ensuring fairness and diversity, independent of demographic background.
The study predicts that the Balearic Islands will lose between 56 and 65% of their beach area permanently due to climate change. This loss is mainly attributed to sea level rise, which will cause devastating inroads on the coastline.
A new study published in PLOS Computational Biology found that the order of COVID-19 symptoms varies depending on the SARS-CoV-2 variant. In the USA, cough was most likely to be the first symptom, while fever and diarrhea were more common third symptoms.
A simplified mathematical model found a 'lag time' between human intervention and an actual decrease in CO2 levels, which could still lead to climate tipping points. The researchers used a system of stochastic delay differential equations to analyze various emission reduction and carbon capture strategies.
Researchers at Linköping University developed a mathematical model to describe global climate target achievement and predict unanimity in climate talks. The model shows how countries influence each other over time, highlighting the importance of inclusive plenary sessions and informed parties.
Researchers at Chalmers University of Technology have developed an algorithm that learns optimal energy usage for electric delivery-vehicles. By focusing on overall energy usage instead of just distance travelled, the vehicles can reduce their energy consumption by up to 20% and minimize battery usage.
Researchers developed a mathematical model to predict mosquito breeding ground temperatures, estimating populations and tracking vector-borne diseases. The model revealed that even in winter, certain breeding grounds can support mosquito growth.
Researchers developed AI that extracts hidden equations of motion from observational data, creating models faithful to the laws of physics. This enables physics-based investigations and simulations for ecosystem sustainability, among other applications.
Researchers found that major COVID-19 models were wrong and not very useful in predicting the pandemic course. They used physics-informed neural networks (PINNs) to capture changing parameters and make predictions with improved accuracy.
New Cornell University research suggests that social connections can distort voting behavior, favoring minority candidates. The study found that complacency and dejectedness – conditions caused by social connections – can skew election outcomes.
A team of researchers at UC Davis Health has developed a novel PET imaging-based tool to detect liver inflammation in non-alcoholic fatty liver disease. The tool uses dynamic PET imaging and mathematical modeling to measure glucose transport from blood to liver tissue, allowing clinicians to quantify liver inflammation.
Mathematicians analysed global COVID-19 data to identify two constants that drastically change a country's rate of infection. Social stress is key to understanding the multi-wave dynamics of COVID-19 outbreaks.
Researchers have successfully created an experimental model of a skyrmion particle in a beam of light, providing a real system to demonstrate the behavior of this elusive type of fundamental particle. The study reveals the intricate structure and topological properties of skyrmions, which can be distorted but not broken.
A mathematical model suggests that SARS-CoV-2 Delta-like variants, which combine enhanced transmissibility and partial immune escape, will cause more severe pandemics than variants with either trait alone. Vaccination is predicted to be highly beneficial in these cases, preventing more infections and breakthroughs.
Iowa State University researchers validated the CDC's COVID-19 vaccine rollout strategy, which prioritized frontline essential workers, older age groups, and individuals with underlying health factors. The model showed that this approach was highly effective in curbing mortality while keeping case numbers at bay.
Researchers developed a predictive model that maps electric activity of mouse, rabbit, and human cardiac cells, allowing translation of findings across species. The model is expected to accelerate drug development and improve understanding of disease mechanisms.
Research published in JNeurosci found that children with dyslexia take longer to gather visual evidence, indicating altered motion processing and decision-making. This slowdown corresponds to differences in brain activity, particularly in centro-parietal regions involved in decision making.
A new Illinois study compares performance of static and dynamic nitrogen recommendation tools, finding that complex dynamic tools do not consistently increase profits but offer a 15% reduction in nitrogen leaching. The researchers highlight the need to refine these tools and prioritize environmental outcomes over economic gains.
Researchers developed a mathematical model that can predict the effectiveness of immunotherapy treatment for individual patients based on standard clinical measures. The model showed high sensitivity in predicting treatment response within two months, with minimal false-negative results.
Researchers from academia and industry will converge at Lehigh University to discuss innovative solutions for optimizing efficiency and resiliency in the global supply chain. The workshop aims to leverage machine learning for prescriptive analytics, enabling proactive optimization of supply chain operations.
A team of researchers from Flinders University has developed a single mathematical equation that can accurately model and predict the behavior of ventricular fibrillation, a life-threatening heart rhythm. The equation uses principles from renewal theory to predict the population dynamics of 'rotors' found in the heart during VF.
Researchers develop a more accurate mathematical model to predict solar cell output power, considering degradation and external factors. The new model will aid policymakers in making informed decisions on solar power installations.
A team of researchers has developed an ensemble-based machine learning model that can predict how cancer patients will respond to certain drugs with high accuracy. The model was trained on data from 499 independent cell lines and validated against a clinical dataset containing seven chemotherapeutic drugs.
Researchers applied a physics method to Balinese rice irrigation practices, finding that a balance between water stress and pest stress is crucial for equilibrium. The traditional method, which involves synchronized flooding, can help maintain social harmony and prevent chaos in water schedules.
A new analysis spanning 10,000 years of history and ten major world regions found that world population size, major technological advances, and geographical connectivity are key drivers of military technology evolution. The study's methodology employed a resource called Seshat: Global History Databank to empirically test prior hypotheses.
A team of researchers has developed a novel machine learning model that can identify medication orders requiring pharmacy intervention using provider behavior and contextual features. This approach reduces the risk of exposing sensitive patient data, while alleviating the workload of pharmacists and increasing patient safety.
A new mathematical model suggests that patients with anemia can be effectively treated with transfusions of blood substitutes, which are more readily available than real blood. This approach could reduce the negative effects of blood transfusion and lower costs.
A study of 5,000 simulated undergraduates found that weekly surveillance testing was associated with a substantial reduction in infections. Even at low vaccine effectiveness rates, quarantine protocols were effective in reducing infections by up to 93.6%.
Assistant Professor Kang Hao Cheong and his team discovered that chaotic switching for quantum coin Parrondo's games has similar underlying ideas to encryption. They found that using pre-generated chaotic sequences enhances the work, making it easier to invert the encrypted message to obtain the original state.
A study found that snakes rapidly diversified their diets following the K-Pg mass extinction event, incorporating birds, fish, and small mammals into their diet. This diversification was triggered by ecological opportunities presented by the extinction, with some lineages experiencing further bursts of adaptive evolution.
Researchers find that most countries are not growing wind and solar power fast enough to meet global warming targets of 1.5°C or 2°C. The study analyzes data from 60 countries and finds that only a few countries, like Portugal and Ireland, have seen rapid growth in onshore wind and solar power.
A team of scientists at NAIST successfully used automatic differentiation to accelerate calculations of model parameter extraction, reducing computation time by 3.5 times compared to conventional methods. This breakthrough enables the design of more efficient power converters with increased performance and reduced energy consumption.
Liquid marbles' unique hydrophobic outer layer allows for faster evaporation than bare water droplets due to particle-particle and liquid-particle interactions. The team's mathematical model accurately predicts evaporation behavior, providing insights into these tiny biological structures.
Using observations, lab experiments, theory, and computation, researchers have developed a simple theory to explain the form and growth of apples' cusp-like features. The team found that mechanical instability and underlying fruit anatomy play joint roles in giving rise to multiple cusps in fruits.
Researchers from MIT have developed a way to use carbon dioxide monitors to estimate indoor COVID-19 risk in near real-time. The model takes into account various factors such as ventilation, mask usage, and activity levels to provide an indoor reproductive number that represents the virus's transmission rate.
A new study by University of Cambridge researchers proposes abandoning the R rate for tracking pandemics in favor of nowcasts, which forecast daily new cases and deaths based on growth rates. The Harvey-Kattuman model has already proved accurate and effective in predicting COVID-19 waves and spikes worldwide.
Researchers developed a mathematical model to study the action of SARS-CoV-2, enabling the examination of individual virus particles and their spikes. This analysis can help fine-tune prevention and treatment by providing insights into viral load, spike distribution, and cell infection potential.
Mathematical modeling suggests that contact-tracing apps can help achieve herd immunity by identifying individuals with greater exposure to others and targeting them for vaccination. The approach, known as 'hot-spotting,' could reduce the number of vaccine doses needed by up to half.
Researchers at Rice University have been awarded a four-year, $1.2 million National Institutes of Health grant to advance the art and science of creating custom-designed microbial colonies. The grant will enable the development of technologies like synthetic tissues that enhance soils or gut microbiomes.
A team of scientists from Incheon National University developed a programmable DNA-based microfluidic chip that can perform complex mathematical calculations, such as Boolean logic operations. The chip uses a motor-operated valve system to execute a series of reactions in rapid and convenient manner.
Researchers suggest that protecting the microbiome is crucial in preventing and fighting off infections with harmful, drug-resistant bacteria. By preserving a healthy balance of beneficial microorganisms, individuals can reduce their susceptibility to these types of infections.
Researchers developed a mathematical model to predict the angle of repose of sand hills, which is influenced by particle size and gravity. The model was validated using simulations and has potential applications in space exploration, additive manufacturing, and planetary science.
A mathematical model developed at Linköping University predicts that many species in polar regions will become extinct due to global warming, with ecosystems already showing signs of strain. The model simulates the impact of climate change on species interactions and diversity, highlighting the importance of considering ecological proc...
The UMass Amherst Reich Lab, led by biostatistician Nicholas Reich, will continue to advance real-time forecasting methods during infectious disease outbreaks thanks to a five-year NIH grant renewal. The lab's flu forecasting collaborative has been designated as one of two national Influenza Forecasting Centers of Excellence.
A new study by the ICTA-UAB establishes that populations of hunter-gatherer groups with strong seasonal dependence on meat had fewer people per square kilometer than those relying on abundant plant foods. This result is based on a complex set of calculations showing how diet composition influenced population density.
QUT researchers developed a new mathematical model to enable faster solutions for complicated problems in agriculture, ecology and medicine. The method improves how to determine the 'best' intervention strategies, balancing benefits and side effects, and can be applied to farming practices and chemotherapy.
Researchers analyzed 1.4 million field observations and 73,000 museum records to find a strong correlation between species abundance in nature and their presence in museum collections. This method enables scientists to study species decline and estimate past abundances, providing insights into conservation efforts.
A new study proposes that protocells, the putative ancestors of modern living cells, used temperature differences to divide. This simple mechanism could underlie the growth and self-replication of these early cells.
Scientists have discovered that geckos use their tails to recover from head-first crashes into rainforest trees, with implications for the design of agile robots. This versatile behavior allows geckos to stabilize themselves after impact and maintain control during gliding maneuvers.
Researchers develop novel models to investigate the impact of drug-eluting stents on arterial tissue permeability and blood flow. The study identifies key factors contributing to restenosis near stent edges, highlighting potential avenues for design improvements.
Researchers created a model to estimate viral population variability using epidemiological data, predicting the emergence of novel variants. The study suggests that lack of vaccination increases mutation frequency and spread.
A new study found that global marine ecosystem models differ widely in their representation of key processes, leading to underestimation of climate change impacts. Marine ecosystem models generally agree on biomass decline but disagree on magnitude and location across the world's oceans through the 21st century.