Articles tagged with Mathematical Modeling
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.
A University of Nebraska-Lincoln researcher has developed a virtual immune system model that can simulate the complex interactions between different components of the human immune system. The goal is to identify more effective drug targets and accelerate the development of new treatments for immune-related diseases.
Researchers at UC3M have developed a mathematical model that analyzes the appearance of oscillations in flow networks, which may help explain how blood circulates in the brain. The model takes into account the size of the network and predicts the frequency of pressure oscillations.
A mathematical modeling study predicts that routine immunization with TCV could avert 46-74% of all typhoid fever cases in 73 countries. Vaccination is also expected to reduce the relative prevalence of antimicrobial-resistant typhoid by 16%, preventing millions of cases and deaths.
Researchers at Pusan National University have developed a new model using 'double Mellin transforms' and the 'method of dimension reduction' to accurately price vulnerable exchange options. The model provides an effective and accurate mathematical solution, enabling quick deployment without long calculations.
A team of researchers from Ritsumeikan University developed an unprecedented stream cipher using chaos theory to create highly secure cryptographic systems. The new system is resistant to statistical attacks and eavesdropping, even against quantum computers, making it a promising solution for post-quantum era cryptosystems.
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 at Boston University developed a real-time method for projecting COVID-19 quarantine needs in congregate housing settings ten days in advance. The team's findings were published in the American Journal of Public Health and can be used as a predictive tool to allocate resources.
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.
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.
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 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.