Articles tagged with Mathematical Modeling
Researchers developed a nomogram to predict anal cancer risk in persons with HIV infection, highlighting increased risk among those living with the virus. The model estimates quantitative risk based on patient characteristics, informing screening decisions.
Researchers at Texas A&M University are developing mathematical models to predict and control cellular differentiation. They created a technique using mix-and-read assays, which allow for the detection of key signaling proteins in live tissues. This method enables researchers to gain a deeper understanding of how cells make decisions.
New research suggests that stalling improvements in cardiovascular diseases since 2010 could lead to significant economic costs. The study finds that reduced cardiovascular disease rates would result in £13 billion NHS healthcare costs, £1.5 billion social care costs, and £32 billion lost QALYs between 2020-2029.
An international research team applied a new dynamical model and exceptional historical data to examine major explanations for cultural complexity evolution. The study found little support for many influential theories, including the transition to agriculture and conflict theories.
A mathematical modelling study published in The Lancet Infectious Diseases estimates that COVID-19 vaccines have prevented approximately 19.8 million deaths worldwide in the first year of the vaccination program, a reduction of 63%. This represents nearly 80% of potential deaths that would have occurred without vaccination.
Researchers developed a mathematical model to predict COVID-19 transmission in train carriages, finding that risk is constant regardless of location and that masks are more effective than social distancing in reducing transmission. The study highlights the importance of improving ventilation systems on trains to keep passengers safe.
EpiMoRPH aims to develop locally customized models for decision-making, addressing the limitations of previous disease modeling systems. The project will use two virus-based diseases as case studies and provide a framework for characterizing meta-population disease models.
Researchers at Ohio State University created a mathematical model that assesses the efficacy of immunomodulatory drugs in treating myocardial infarctions. The study found that certain combinations of these drug inhibitors were more efficient at reducing inflammation, offering new possibilities for improving patient outcomes.
The five-year grant will support research on foundational theory and real-world applications, including simulation of optical fibers, weather forecasting, and disease understanding. Postdoctoral researchers and graduate students will work with faculty mentors to develop data acumen and prepare for Ph.D. research.
A new study from the University of Kansas found that a professional development intervention improved an educator's teaching skills and boosted students' abilities to solve word problems, especially for Hispanic English-learning students with math learning disabilities. The program helped develop a 'feedback loop' between educator and ...
Researchers found that wetter pre-growing seasons reduced soil nitrogen through leaching, but applying more fertilizer can mitigate this effect. The model also showed that cold pre-growing season temperatures limited early growth in ways that affected yield potential, making extra fertilizer less effective.
A new study reveals that large-scale hydrological models producing global irrigation water withdrawal estimates are unreliable due to overlooking uncertainties and traditional irrigator practices. The researchers argue that these biases can lead to grave policy misjudgments, devastating consequences and inaccurate water management.
A new study examines mathematical models designed to draw inferences about how evolution operates at the level of populations of organisms. The researchers conclude that such models must be constructed with care, avoiding unwarranted initial assumptions and weighing existing knowledge.
Researchers have developed a new formula for swimming based on their study of odd elasticity, allowing microswimmers to exhibit autonomously directional and deterministic motion. The team used Purcell's swimmer model to demonstrate that any odd elastic micromaterial can spontaneously generate locomotion in a fluid.
A new study from Aarhus University challenges the traditional 'cry curve' pattern of infant crying, which suggests a sharp decline in crying after six weeks. The research, pooling data from 57 studies across 17 countries, reveals that infants continue to cry significantly after six months.
A new distributed learning technique, GD-SEC, reduces communication requirements in wireless architecture, improving efficiency and reducing computational cost. The method employs data compression to transmit only meaningful, usable data, enhancing the impact of machine learning while minimizing its limitations.
Researchers found tree growth not source-limited but rather by cell growth, suggesting forests may not absorb as much carbon as thought. The study's findings challenge current forest growth models and highlight the need for climate change mitigation strategies.
Researchers developed an ensemble model combining multiple individual predictive models to anticipate COVID-19 hospital demand, achieving a significant reduction in prediction error. The study's findings show that incorporating early predictors such as epidemiological data and mobility data leads to better forecasts.
Researchers at H. Lee Moffitt Cancer Center & Research Institute have identified key factors impacting the effectiveness of adaptive therapy in cancer treatment. The study found that spatial organization and competition between drug-resistant cells play a crucial role in determining the success of adaptive therapy.
A study led by Washington University in St. Louis found that nonlethal parasitic infections reduce herbivory rates and trigger trophic cascades impacting plant communities. The research used a mathematical model and global meta-analysis to highlight the ecological consequences of common parasitic infections in wild animals.
Researchers at DTU Compute and DIKU have developed a machine learning model that can map the potential of proteins, enabling the biotech industry to accelerate the development of new proteins. The model generates a picture of how proteins are linked, allowing for the identification of closely related proteins with desirable properties.
A new mathematical model suggests that wearing masks could drastically slow the spread of COVID-19, reducing severe cases and pressure on healthcare systems. The study's findings are potentially applicable to any respiratory infection transmitted by inhaling infectious particles.
A new study published in PLOS Global Public Health found that shielding vulnerable populations while allowing the virus to spread through the rest of the population would have failed. The research reveals that even with perfect shielding, healthcare capacity would have been overwhelmed, and tens of thousands more deaths would have occu...
A mathematical model reveals that spontaneous symmetry breaking in chemical reactions leads to homochirality, optimizing energy harvesting from the environment. This phenomenon could explain how life developed on primordial Earth and has implications for the synthesis of chiral drug molecules.
The study reveals the sing saw uses a surprising effect to create its distinct tone: when curved into an S-shape, energy vibrates in a confined area producing a clear, long-lasting sound. This principle can be applied to design high-quality resonators for various applications.
Researchers are studying moths to understand agile decision-making in complex environments, aiming to develop autonomous bio-inspired systems. Meanwhile, a team is exploring origami- and kirigami-inspired flexible structures for multifunctional applications.
A study by Tokyo University of Science researchers has demonstrated that a computationally-light model can simulate complex brain cell responses, including periodic and quasi-periodic responses. The Izhikevich neuron model was found to be capable of reproducing both types of responses at lower computational cost.
The new computational tool, AF2Complex, predicts the structure of protein complexes and their interactions, offering insights into biomolecular mechanisms. The model is based on AlphaFold 2 and performs well in predicting protein structures and complex formations.
A new KAUST study uses machine learning to predict disease spread with high accuracy, dynamically incorporating latest data without human bias. This approach offers a promising alternative to conventional models, providing a more accurate story of the underlying epidemic data.
A team of researchers, led by L. Mahadevan, developed a mathematical model to understand the mechanics of combing and detangling. They found that using short strokes starting from the free end can effectively remove tangles, with an optimal minimum length for each stroke identified.
A new mathematical model predicts a significant shift in US public opinion on moral issues, with abortion rights expected to dominate. Within 15 years, a majority of Americans will support equal parental leave.
Researchers used mathematical modeling to characterize the interplay between immune suppression, immune blockade and antigenicity in pre-cancerous cells. They found that an immunosuppressive environment is crucial for colorectal cancer progression.
Researchers have discovered an elegant equation to approximate the coherence time of materials hosting spin qubits. The team can now estimate coherence times in seconds using just five material properties, facilitating a rapid exploration of new candidate materials.
A novel 'rational' neural network reveals underlying mathematical equations through Green's functions, enabling humans to understand machine-generated findings. This breakthrough in partial differential equation learning holds promise for advancing scientific exploration of weather systems, climate change, and more.
New research suggests the brain uses multiple strategies to process smells, employing both snapshot-like and evolving ensemble approaches. The study provides new tools for scientists to quantify and interpret brain activity patterns.
A new study used a virtual population to simulate a clinical trial examining kidney damage in Black Americans. The model predicted kidney damage and showed that adding drug therapy and reducing salt intake could stop the damage, improving heart sizes as well.
The project will develop a better understanding of nuclear radiation by integrating recent mathematical developments into radiation transport modelling. This will lead to improved nuclear safety, cancer radiotherapy, and shielding for astronauts from cosmic rays.
Researchers have developed a new forecasting approach using machine learning and anonymized datasets from Facebook that significantly outperforms conventional models for projecting COVID trends at the county level. The model captures shifting trends in numbers reflecting lockdowns, waning immunity, or masking policies.
Researchers at Ural Federal University have developed a method to significantly accelerate the synthesis of aluminum-based alloys using computer modeling. The new approach allows for control over the internal structure and physical properties of the alloy, enabling the creation of materials with desired characteristics.
Researchers suggest that asteroid Ryugu could be a relic of an ancient comet due to its high organic content and spinning top shape. The study proposes a simple physical model that fits the observed data, suggesting that comets can leave behind rocky debris in the inner solar system.
A study using data science and mathematical models identifies the most suitable rehabilitation method for each patient with osteoarthritis. The research aims to provide personalized treatment recommendations for healthcare professionals, ultimately leading to more effective care for patients.
Scientists developed an AI approach to model and map the Earth's natural features in greater detail and accuracy. The new system can recognise intricate features and aspects of the terrain far beyond traditional methods, generating enhanced-quality environmental maps.
A new mathematical model reveals high risk of cross-species disease spread on farms with multiple types of livestock. Targeting top 3% of most networked farms can significantly reduce transmission and protect other species.
Researchers at Tel Aviv University have developed a unique detector using compressed xenon gas to detect axion-like particles, promising a breakthrough in finding dark matter. The new technology enables the exploration of previously inaccessible masses, constraining the properties of axion-like particles.
Researchers developed a mathematical model to predict how antibodies generated by COVID-19 vaccines confer protection against symptomatic infections. The study found that vaccine efficacy is linked to the level of neutralization titre and could enable testing of future vaccines before clinical trials.
A team led by City University of Hong Kong researcher Dr Zhang Qingpeng found that donating 46% to 80% of COVID-19 vaccines to low- and middle-income countries can significantly reduce infection rates and mortality. The study suggests prioritizing vaccines for countries with high incidence, prevalence, and mortality rates.
Researchers from the University of Illinois have revamped the popular crop growth simulation software BioCro, allowing modelers to use the technology more easily. The updated version includes faster and more accurate algorithms, enabling researchers to try new simulations more easily and link to other models.
Researchers from Washington University in St. Louis have discovered that the pore size of a battery separator plays a crucial role in determining the stability and safety of a battery. The study reveals that smaller pores can lead to localized metal ion penetration and increased risk of short circuits.
A new UNSW-led study reveals that global warming has amplified the water cycle, with an estimated 46,000-77,000 cubic kilometers of freshwater transported from the equator to the poles since 1970. This finding suggests broader changes to the global water cycle and highlights the need for improved climate models.
GIST researchers propose a new strategy for crime prevention using artificial intelligence, trained on a large-scale dataset of deviant incident reports and corresponding images. The model, called DevianceNet, can accurately classify and detect deviant places, making it a useful tool in urban safety development.
Researchers from NIST have developed a mathematical model that predicts the strength and timing of changes in velocity required for crane operators to apply when transporting heavy loads. This equation can be applied to various situations, including moving a load with initial rest and large distances.
Researchers found that the master clock and slave clock operate via distinct molecular mechanisms, allowing for robustness and flexibility in regulating bodily rhythms. The master clock's ability to adapt to environmental changes enables quick adjustment to new time zones after international flights.
Researchers developed patient surrogates to evaluate potential prostate cancer treatments, identifying genes that could be targeted with drugs. The models predicted synergistic effects of treatments and identified promising drug combinations.
A Harvard T.H. Chan School of Public Health study suggests that US elementary schools should only remove masks when local COVID-19 case rates are below a certain threshold to avoid increased transmission. The study provides a framework for school decision-makers to estimate the level of mitigation needed to meet their goals.
Researchers at RIT have created a biophysical model that can predict changes in cartilage mechanics and function during disease pathways. The model, informed by experimental data, enables noninvasive predictions using MRI scans, potentially reducing the need for invasive procedures.
In a recent study, Dalla Torre and his team ran a collaborative mathematical game on different technologies to evaluate the systems' ability to demonstrate quantum mechanical properties. The Quantinuum System Model H1-1 outperformed classical results by returning correct answers 97% of the time.
Mathematicians at the University of Leicester have developed a new mathematical model that could greatly increase the efficiency of pest control. The model uses field data and computer simulations to predict the distribution of slugs in arable fields, accounting for individual creature movements.
A study published in AGU Advances found that water depletion from rivers and lakes accelerates near urban centers due to factors like increased evaporation and groundwater exploitation. Researchers analyzed satellite imagery of the US from 1984 to 2018 and developed a model predicting surface water loss proximity to cities.
Researchers at the University of Pennsylvania found that changing social strategies between settings can lead to more cooperative behavior in a society. In a model with spillover between domains, cooperation is favored when actors can observe and imitate each other's behaviors in different contexts.
Researchers at Tel Aviv University found that a specific type of bacteria, Weissella, becomes dominant in the gut microbiomes of locusts when they form swarms. This change may provide the bacteria with an evolutionary advantage, allowing them to spread and infect more locusts.