Articles tagged with Computer Modeling
Researchers developed an AI model called OncoNPC that can analyze genetic data to predict cancer type and origin. The model accurately classified at least 40% of tumors with unknown origin, leading to a 2.2-fold increase in eligible patients for targeted treatments.
Researchers find that Acinetobacter baumannii can achieve significant functional modifications in protein complexes over short evolutionary time spans, particularly in hair-like cell appendages. This diversity may affect the pathogen's interaction with its environment and inform personalized therapies.
Researchers developed a computational technique to quickly design and evaluate cellular metamaterial structures with unique properties. The new interface enables users to explore the entire space of potential shapes, allowing for faster development of complex materials.
A new open-source Python toolbox called simpleNomo has been made available, enabling the creation of nomograms directly from logistic regression coefficients. This facilitates the translation of research findings into practical use, particularly in resource-poor settings or areas without internet access.
Researchers developed a generative AI tool, AniFaceDrawing, to assist users in creating high-quality anime portraits. The tool uses a sketch-to-image framework and employs stroke-level disentanglement to match raw sketches with latent vectors of the generative model.
A recent study revealed that attention plays a crucial role in shaping our conscious experience of the world. Researchers found that manipulating attention can modify an individual's ability to consciously perceive visual stimuli, highlighting the intricate relationship between attention and conscious perception. By using advanced neur...
Researchers at the University of Pittsburgh have developed a system that uses fluid mechanics and chemo-mechanical processes to autonomously assemble hierarchical 3D structures. The system utilizes sticky bonds to drive self-organization, allowing for the construction of complex devices with minimal external intervention.
Researchers at UCLA found that GPT-3 performs well on analogy problems, similar to human undergraduates, but struggles with understanding physical space. The AI model's ability to mimic human reasoning is unclear, raising questions about its underlying cognitive processes.
Researchers developed a divide & conquer approach to leads-to model checking, mitigating the state explosion problem and improving performance. The technique, DCA2L2MC, divides the reachable state space into smaller sub-state spaces, making it feasible for large-scale systems.
A study by University of Toronto researchers found that child language development and language evolution share a common cognitive foundation, based on a core knowledge base. The team built a computational model that predicts word meaning extension patterns across languages and time scales, highlighting the role of visual, associative,...
A new open-source software, NMSM Pipeline, enables clinicians and engineers to create personalized computer models of patient movement to optimize treatment designs. The software uses physics-based models to predict and optimize functional outcomes for patients with various mobility impairments.
A University of Central Florida engineer is leading a $3.3 million ARPA-E funded project to develop simulation software for floating offshore wind turbines. The goal is to improve turbine design and increase their use as a renewable energy source. The software will be licensed or commercialized and can be hosted on a university web page.
A team of Lithuanian researchers has created an AI-based system to facilitate the rehabilitation process for stroke patients. The system, which uses wearable equipment and electromyography (EMG) technology, enables patients to track their progress and receive feedback on their exercises.
A new game theory model developed at ISTA finds that both information and ignorance can lead to cooperative outcomes in changing environments. The model, based on stochastic games and algebra, quantifies the benefits of ignorance in around 80-90% cases, highlighting counter-intuitive instances where it is optimal for cooperation.
A new editorial explores the potential of machine learning to enhance early cancer detection in primary care, leveraging extensive patient data and improving risk stratification accuracy. The authors emphasize the need for responsible implementation, collaboration, and validation across diverse populations.
Researchers developed an AI algorithm to predict the properties of new 2D materials with point defects, achieving 3.7 times greater accuracy than other machine learning algorithms. The model operates 1000 times faster than quantum mechanical computations and can handle multiple defects simultaneously.
Researchers create a new privacy metric, Probably Approximately Correct (PAC) Privacy, that enables the addition of minimal noise to protect sensitive data. The algorithm automatically determines the optimal amount of noise needed without requiring knowledge of the inner workings of the model or training process.
A Lehigh University professor has received $4 million in NIH grants to develop an AI-driven approach for precision mental health diagnosis and care. The project aims to identify biomarkers in the brain that can predict treatment response and personalize interventions for patients with depression and other mental disorders.
A new machine learning-based simulation method called Materials Learning Algorithms (MALA) has been developed, enabling accurate electronic structure calculations at large scales. MALA achieves this by utilizing a hybrid approach that combines physics-based approaches with machine learning to predict the electronic structure of materials.
The University of Houston's CYBER-CARE research center aims to prevent cyberattacks that could compromise the safe movement of people and goods in the US. The center will focus on four goals, including exploring advanced theories to mitigate the impact of large-scale cyberattacks.
The study combines real and robotic insects to understand how they sense forces in their limbs while walking. Campaniform sensilla (CS) are force receptors found in insect limbs that respond to stress and strain, providing critical information for controlling locomotion.
Researchers at Nagoya University developed an AI-based technique to predict crystal orientation in polycrystalline materials, revolutionizing the industry. The method uses optical photographs and reduces measurement time from 14 hours to 1.5 hours, enabling large-area materials analysis.
Researchers at EPFL have found a way to teach quantum computers to learn and process information using principles inspired by quantum mechanics. By training quantum neural networks (QNNs) on a few simple examples called 'product states', the computer can effectively grasp complex dynamics of entangled quantum systems.
A new computer model forecasts yield for four key crops in the southeastern US, drawing on climate, groundwater, and agricultural data. The tool helps farmers and water resource managers identify ways to maximize crop yields while efficiently utilizing water and energy.
A team of researchers at UC Irvine has developed a freely available computer model to estimate the economic costs of hurricanes and typhoons. The model combines data from climate change science and household vulnerability information, providing return periods of asset losses and helping countries better prepare for these disasters.
Research highlights how generative AI models encode biases and negative stereotypes in their users, particularly marginalised groups. This can lead to the mass generation and spread of nonsensical information, influencing human beliefs and perpetuating existing inequalities.
A new study models the spread of African swine fever in US swine farms, finding that control actions can reduce secondary infections by up to 79% but an outbreak could still be persistent and costly. The model suggests that between-farm movements are the primary route of transmission.
Researchers at the University of Washington created an app called FeverPhone that uses existing phone sensors and screens to estimate whether people have fevers. The app was tested on 37 patients in an emergency department and showed accuracy comparable to consumer thermometers, with potential for early intervention in viral outbreaks.
A virtual reality project, Qikiqtaruk: Arctic at Risk, visualizes the impacts of climate change in the Canadian Arctic. The project, created by National Geographic Explorers and local communities, uses immersive technology to transport users to an island experiencing rapid thawing and environmental changes.
Researchers have developed a simulation of how people behave on roads based on cognitive theories, accurately reproducing pedestrian and driver behaviors in common scenarios. The model predicts complex underlying cognitive mechanisms that contribute to the difficulty in creating self-driving vehicles.
The UK is investing £11 million to improve forecast accuracy for extreme weather events like storms, floods and droughts. Scientists are focusing on atmospheric turbulence to create more detailed models.
A team of researchers from Syracuse University and Texas A&M University applied a machine learning model to explore the sources of salinization and alkalinization in U.S. watersheds. The study found that human activities, such as road salt application, were major contributors to salinity, while natural processes dominated alkalinity.
A study by Dartmouth's Geisel School of Medicine found that Medicare fraud in home healthcare billing spread rapidly across U.S. regions between 2002 and 2009, driven by characteristics such as shared patients, high expenditures, and rapid growth in the number of home health agencies. The researchers developed a novel network analysis ...
The study uses neural recordings and computer modeling to show that phonetic information is encoded differently when speech stands out versus being drowned out. This finding could help develop more accurate hearing aids.
A recent study has found that microbes play a crucial role in storing carbon in the soil, with a four-fold greater importance than other processes. This breakthrough could lead to improved soil health and increased food security through targeted farm management practices.
Researchers updated their protein localization prediction model, MULocDeep, to provide more targeted predictions for biological discoveries. The tool helps researchers design more effective experiments and advance scientific discoveries related to drug development and treating diseases like epilepsy.
A new Danish research project, CP-SENS, aims to develop a digital twin platform for the mechanical and construction industries. The project will provide companies with access to intelligent IT systems tailored to their needs, enabling them to adopt digital twins without significant financial investment.
A new research effort aims to provide decision-makers with better information to understand supply chain risks, vulnerabilities, and resilience through visual analytics. The project will create a comprehensive computational and visual analytic environment to identify patterns and interdependencies in supply-demand systems.
A recent study published in the Proceedings of the National Academy of Sciences found that officers' first 45 words during a vehicle stop with a Black driver can indicate how the stop will end. The study discovered a unique 'linguistic signature' that characterizes escalated stops, where officers give an order without stating the reaso...
Researchers used AI to identify a compound that kills Acinetobacter baumannii, a bacterium responsible for many drug-resistant infections. The new antibiotic shows promise in combating this growing public health threat.
Researchers at MIT have developed a new approach to match 3D shapes by mapping volumes to volumes, resulting in more accurate animations and CAD designs. This method represents shapes as tetrahedral meshes that include the mass inside a 3D object, allowing for better modeling of fine parts and avoiding common artifacts.
Hanna Kokko, a renowned theoretical evolutionary biologist, has been awarded the Alexander von Humboldt Professorship for her groundbreaking research on the interplay between evolutionary and ecological factors. She will receive EUR 3.5 million to establish her research team and obtain necessary equipment and facilities.
Researchers developed AI model QUADL that can create online assessment questions indistinguishable from human-written ones. Instructors found QUADL's questions as effective as those written by humans in assessing student learning objectives. The study suggests QUADL can be a useful tool for instructors and course developers.
Researchers discovered that certain bacterial species, including lactic acid bacteria, correlate with high levels of Candida yeasts in the gut microbiome. This suggests a complex interaction between these microorganisms, where lactic acid bacteria may favor Candida proliferation while making the fungus less virulent.
Researchers develop chitosan-based coating to preserve avocados and create imaging technique to predict shelf life. The coating delays ripening, and the imaging method accurately estimates remaining shelf life, potentially improving avocado quality and availability.
Researchers used AI to analyze speech patterns of patients with Parkinson's disease, finding they spoke in shorter sentences with more verbs and fewer common nouns. The study suggests potential early detection methods for the condition through conversational analysis.
Researchers used AI to study how the hippocampus produces varied replay types efficiently and their purpose. The model showed that sequences are prioritized stochastically according to familiarity and reward positions.
The new model maximizes coverage area and minimizes response time, accounting for hot spots. It outperformed existing techniques in computational testing, improving response times regardless of traffic size.
Researchers at UChicago found a surprising connection between photosynthesis and exciton condensates, a state that allows frictionless energy flow. The discovery could lead to more efficient materials and technologies, such as superconductors.
Researchers identified three novel dual-purpose therapeutic targets using PandaOmics, which could treat both aging and glioblastoma multiforme. The target hypotheses include cyclic nucleotide gated channel subunit alpha 3 (CNGA3), glutamate dehydrogenase 1 (GLUD1) and sirtuin 1 (SIRT1).
A team of researchers from Carnegie Mellon University has developed an AI-based system to help clinicians make decisions quickly and precisely in the ICU. The system, called the AI Clinician Explorer, provides recommendations for treating sepsis based on data from over 18,000 patients.
Researchers at Cedars-Sinai created computational models to bridge the gap between
A study at Kyoto University has demonstrated the computational power of ecological networks, providing a new direction for rapidly developing AI technologies. The researchers developed two types of ecological reservoir computing that efficiently process information and can be utilized as a computational resource.
The new CALANGO software helps untangle genetic factors associated with shared characteristics, such as antibacterial resistance and agricultural improvements. It enables scientists to explore vast amounts of genomic data across thousands of organisms.
Researchers propose a 'state space' approach to reframe farming planning questions, enabling analytics and machine learning to explore optimal crop combinations and simulate different scenarios. This framework allows farmers to design diverse agricultural landscapes based on natural ecosystems, increasing crop yield and sustainability.
Researchers used computational modeling to identify ultrastable MOF structures, which could be useful for gas storage and catalysis. The study found that about 10,000 of the predicted structures were stable enough for these applications, with high deliverable capacities for methane.
Max Planck scientists explore the possibilities of artificial intelligence in materials science, discussing how combining physics-based modeling with AI can unlock complex material designs. The research focuses on overcoming limitations of traditional methods and handling sparse, noisy data.
A new model of DNA flexibility has been developed, providing results of unprecedented quality and characterizing precision and efficiency at the computational level. The study presents a systematic and comprehensive analysis of DNA movement correlations and introduces a new method to capture them.
A WPI-led team used computational modeling to create a detailed picture of the SARS-COV-2 virus envelope, revealing its elliptical shape and changing structure. This discovery could lead to more effective therapies and vaccines, as well as a better understanding of the virus's properties.
Researchers at NIST have developed a new method of digitally simulating hurricanes using AI techniques, accurately representing the trajectory and wind speeds of real storms. The simulations can help develop improved guidelines for building design in hurricane-prone regions.