Articles tagged with Computer Modeling
A recent study suggests that primates and marsupials were among the few tree-dwelling mammals that survived an asteroid impact 66 million years ago. The researchers used computer models and fossil records to find that most surviving mammals did not rely on trees, but some arboreal species may have been versatile enough to adapt.
Researchers study entangled blackworm blobs that show 'intelligent' collective movement when conditions are just right. The model suggests a fine balance between individual movement and clinginess is needed for sustained collective movement.
A team of researchers from the University of Illinois Urbana-Champaign used advanced machine learning to model the physico-chemical properties of a molten salt compound called FLiNaK, enabling accurate atomic-scale reproduction and prediction of behavior under specific reactor conditions. This computational framework can help character...
Researchers developed a novel machine learning algorithm to identify previously unknown air pollutant mixtures linked to poor asthma outcomes in children. The study found that early exposure to individual and mixed pollutants can lead to longer-term problems with asthma, affecting about seven percent of US children.
A $1 million NSF Award supports a project to create an open underground infrastructure map to improve disaster resilience in New York City. The Unification for Underground Resilience Measures (UNUM) project will standardize data sharing and visualization, enabling faster response times and increased safety.
Researchers from McGill University found that unmasked individuals can spread COVID-19 airborne particles up to 70% within a 2-meter radius, highlighting the need for mask-wearing and ventilation. The study suggests that current guidelines relying solely on physical distancing may not be sufficient to prevent transmission.
Researchers have developed patient-specific whole-heart models to predict risk of sudden cardiac death and outcomes of cardiac procedures. These models incorporate individual geometry, structure, and other patient-specific information, enabling personalized diagnosis and treatment.
A team of researchers, led by University of Houston associate professor Ryan Kennedy, has received a $750,000 NSF grant to create an algorithm-accountability benchmark. The project aims to establish general ways of analyzing algorithms and studying their impact on public policy decisions.
Researchers developed a feature selection algorithm that uses boosting to select relevant features from high-dimensional data sets. The algorithm outperforms other methods in terms of accuracy and number of features used, making it more scalable and explainable.
Researchers developed a computational model to optimize the use of additive manufacturing in spare parts supply chains, finding that centralized systems are more efficient for less frequent demand with high variability. The study's findings provide a step forward in understanding how to incorporate AM technologies into supply chains.
A Rice University professor has received a $2.4 million grant from the NIH to develop open-source software for designing personalized treatments for movement impairments using computational modeling and simulation. The software will create customized computer models of individual patients, optimizing treatment solutions.
A team of NTU Singapore scientists developed a predictive computer model called NSGA-II, which proposed strategies to reduce COVID-19 infections and deaths by an average of 72%. The model recommended timely and country-specific advice on interventions such as home quarantines and social distancing measures.
Researchers at MIT and Institut Pasteur have created an efficient method for assembling entire genomes, including the human genome, in minutes using personal computers. This approach uses minimizer-space de Bruijn graphs to store only a small fraction of nucleotides while preserving overall genome structure, enabling faster processing ...
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...
Five innovative research projects tackle fundamental questions of environmental and earth science, including the origins of Earth and life on Mars. The studies aim to advance our understanding and lead to important scientific breakthroughs.
Researchers found that the stability of an amorphous metal alloy's structure is disrupted by mechanical influences, leading to crystalline inclusions. The alloy retains useful properties at pressures below 400 gigapascals before experiencing rapid crystallization and loss of structural integrity.
Researchers developed WebFRIS, a web-based platform to provide socio-economic vulnerability analysis and simplify flood risk information. The tool can help formulate targeted solutions and enhance social capacity and resilience in flood-prone regions.
Researchers developed a new computational procedure to discover functional protein shapes, revealing molecular details of cellular processes. The approach focused on allosteric regulation and applied to adenylate cyclase, a key enzyme in energy metabolism and hormone signaling.
Researchers successfully simulated the capsid disassembly step of hepatitis B viral infection at an unprecedented atomic level, identifying specific regions of the capsid protein that contribute to breakage. This high-accuracy simulation can help design drugs to interrupt these processes and prevent chronic infection.
A new platform called LEARNER allows researchers to share private patient data from multiple institutions while protecting privacy. This enables single institutions to access advanced predictive tools and improve patient outcomes.
Researchers at The Hebrew University of Jerusalem have developed a new deep learning artificial infrastructure inspired by individual neurons. Their approach uses complex mathematical modeling to replicate the brain's electrical processes and create more intelligent AI systems.
A deep learning-based method developed by Kaunas University of Technology researchers can predict the possible onset of Alzheimer's disease from brain images with an accuracy of over 99%. The algorithm was trained on functional MRI images from 138 subjects and performed better than previously developed methods.
Researchers at Technical University of Munich have developed a new machine learning algorithm that can analyze complex markets and their equilibrium strategies. This breakthrough has potential applications in auction theory, wireless spectrum auctions, and more.
A simple stock assessment model applied to 500 years of catch data shows that northern Atlantic cod biomass is currently around 2% of its earlier level. Annual catches could have been sustained at around 200,000 tonnes if authorities had allowed rebuilding in the 1980s.
A study estimates that 103 million Americans had COVID-19 by the end of 2020, accounting for 31% of the population. Undocumented cases accounted for three-quarters of infections, which were often mild or asymptomatic.
Researchers from Binghamton University and Harvard Medical School are using computer modeling and advanced imaging to study brain folding and growth in fetuses. They hope to understand the underlying mechanism of how brains form and how early weeks affect later life.
Student researchers at the University of Cincinnati developed artificial intelligence to train robots to work together to move a couch around obstacles and through a narrow door. The robots successfully completed the task 95% of the time in simulations, with nearly equal success without re-training.
A new digital study has found that Tyrannosaurus rex's jaw had nerve sensors enabling it to better detect and eat its prey. The researchers used computed tomography to analyze the distribution of neurovascular canals in a fossil mandible, revealing complex branching patterns similar to those of modern-day crocodiles and birds.
A University of Missouri researcher is using a grant from the National Science Foundation to explore how time can factor in a building collapse. She's conducting thousands of hours of laboratory tests to determine the breaking points of reinforced concrete building materials.
Phasecraft's new research improves Hamiltonian simulation for near-term quantum computers by five orders of magnitude, making it possible to simulate complex materials and chemistry applications within 2-3 years. The breakthrough algorithm can run on noisy, intermediate-scale quantum hardware, accelerating the pace of real-world impact.
The deployment of thousands of autonomous robots called BGC-Argo floats is transforming our understanding of marine primary productivity on a global scale. By measuring oxygen production over time, researchers can estimate net primary productivity and shed light on the ocean's role in storing carbon.
Researchers at South Ural State University used computer modeling to identify a substance that can block the spread of coronavirus. The study found that ligands must match RNA polymerase as closely as possible to be effective, and scientists have developed an equation to test other ligands' effectiveness on receptors.
Researchers at KAUST developed a new method to simulate the spread of wildfires through forests, capturing complex dynamics involved. The model accurately predicts fire behavior at forest scale and can be used to optimize firebreaks and improve wildfire management.
Scientists aim to develop computer models that can forecast earthquake chances and impact, like weather forecasting. The project will also train students and researchers from diverse backgrounds to work on computational geoscience.
A recent study modelled social, economic, and personal factors influencing voters and parties to identify four key levers that tip the balance towards political extremes. Social contagion and macro-economic factors such as employment and economic growth play a significant role in driving polarization.
Slow slips, or silent earthquakes, are fractures of the Earth's crust that propagate slowly without producing seismic waves. The new database sheds light on the mechanisms behind these events and their potential to trigger regular earthquakes.
Researchers at OIST Graduate University develop robots capable of conducting complex experiments and analyzing data. The 'Nobel Turing Challenge' achieves significant advancements in scientific discovery by leveraging AI-driven robotics.
A new model incorporates human behavior and fears to predict multiple waves of COVID-19 infections. The 'Triple Contagion' model shows how fear can drive disease resurgence, as people may abandon protective measures prematurely or avoid vaccines due to misinformation.
Researchers found that large asteroids from the outer half of the main asteroid belt strike Earth at least 10 times more often than previously calculated
Researchers developed a novel computer model called CODYM to analyze conversational dynamics in seriously ill patients and their families. The model uses Markov Models to capture information flow patterns, providing concise summaries of dependencies in speaker turn lengths.
The spread of infections requires collaboration between biology and physics to understand superspreaders, who account for 80% of transmission. Researchers develop computer models considering family context, work context, and random contexts, highlighting the importance of time in modeling disease behavior.
Researchers at Imperial College London have developed nanocapsules that target specific blood clots, potentially reducing the risk of life-threatening bleeding and increasing the effectiveness of a clot-dissolving drug. The new nanocapsules are designed to attach to activated platelets and release tPA, which dissolves clots.
A research team created a computer model that can simulate the impact of individual receptor types on brain activity. The model uses data from three imaging techniques to quantify receptor-specific modulations of brain states. By predicting changes in brain dynamics after receptor activation, the researchers hope to develop new diagnos...
Scientists Simin Wang and Witold Nazarewicz develop a computer model to reconstruct protons inside the nucleus based on detector data, enabling predictions about nuclear behavior. The model helps understand rare nuclei decay by emitting pairs of particles.
A computer model has been developed to potentially improve bionic eye technology by enhancing clarity and granting color vision to future retinal prosthetic devices. The model, which replicates the shapes and positions of millions of nerve cells in the eye, identifies ways to increase signal transmission and processing efficiency.
A Skoltech researcher has discovered a new model of quantum computation, the variational model, which enables universal computation using limited control over a quantum simulator. This breakthrough bridges the gap between traditional quantum simulators and quantum computers.
Researchers at Northwestern University have created data-driven movies of how RNA folds in the cell, revealing unexpected mechanisms and dynamics. These findings could lead to breakthroughs in understanding and treating RNA-related diseases.
A new machine learning model uses computer algorithms to measure poverty in different countries, providing a more holistic and multi-dimensional approach. The model can predict future poverty levels and plan interventions to alleviate the problem.
Researchers have developed a new computational method called Wasserstein-induced flux (WIF) to validate the accuracy of images in scientific research. WIF provides statistical confidence that specific data points in an image are accurate, enabling scientists to evaluate model performance and improve their models.
Researchers used computer models to analyze COVID-19 pandemic-related changes in human activity and its impact on air pollution. The study found that global nitrogen dioxide concentrations decreased by nearly 20%, with significant reductions observed in 50 of the analyzed cities, including Wuhan, China, Milan, and New York.
A Stanford-led team created a computer model that accurately predicted the spread of COVID-19 in 10 major cities by analyzing three factors: daily destinations, duration, and crowd density. The model reveals that most infections occur at 'superspreader' sites and disproportionately affect minority and low-income populations.
Researchers study insect brain computation to develop faster, more efficient machine learning algorithms. The fruit fly's ability to generalize experiences in complex environments informs the creation of an AI model capable of rapid adaptation.
A holistic causal model is being developed to improve software traceability, leveraging evolutionary histories and intelligent agents for accurate link evaluation. The goal is to enhance trace link quality and facilitate causal reasoning.
Researchers at Princeton University developed a tool to uncover potential biases in visual data sets, such as stereotypical images and underrepresentation. The tool, REVISE, uses statistical methods to inspect data sets for object-based, gender-based, and geography-based biases.
Researchers at UTA are working on a framework to share sensor data through the cloud, reducing costs for businesses and individuals. The sensing-as-a-service model provides incentives for data holders to participate, allowing flexibility and preserving anonymity.
A team of Penn State researchers suggests that simpler models may be a better choice for determining some climate risk due to their ability to better sample uncertainties. This approach can help decision-makers quantify risks more effectively, even if it means sacrificing some detail in the model.
Swiss Center for Electronics and Microtechnology engineers developed an approach to overcome the initial trial-and-error phase of reinforcement learning. This allows computers to quickly find the right path without extreme fluctuations, slashing energy use by over 20% in complex systems.
A new approach to evaluating bridge strength and remaining life is being developed by a University of Texas at Arlington engineer, combining non-destructive evaluation (NDE) techniques with computer modeling and full-scale load testing. The method aims to prioritize repairs without closing roads.
A new open-source computer model is being developed to simulate production and quantify the environmental effects of management decisions on dairy farms. The Ruminant Farms Systems Model project aims to address limitations of current farm management models and provide tools for economic and environmentally balanced decision-making.
A team at the University of Bath has developed Touche, a data-driven computer model that generates responsive animations against attacks and eliminates non-reactive behavior from characters. This framework simplifies the necessary technical work to achieve a convincing simulation, resulting in more realistic results for game developers.