Articles tagged with Computer 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.
A deep learning model achieved up to 98% accuracy in distinguishing autistic from neurotypical participants, providing clear insights into brain regions most influential to its decisions. The model could benefit autistic people and clinicians by offering accurate and explainable results to inform assessment and support.
Researchers developed a fully automated finite element analysis pipeline to transform spine diagnostics and personalized treatment planning. The new approach enables rapid, patient-specific simulations that support preoperative planning, spinal implant optimization, and early detection of degenerative spine conditions.
Researchers will generate maps showing the intensity and extent of an earthquake, helping to identify regions with a higher probability of infrastructure damage. The simulation will recreate a hypothetical scenario of an 8.1 magnitude earthquake in Mexico's Michoacán state.
A new AI model can estimate the long-term risk of over 1,000 diseases and forecast human health changes over a decade. The model was trained on anonymised patient data from 400,000 participants and tested on data from 1.9 million patients in the Danish National Patient Registry.
The Leopoldina Annual Assembly will focus on the progress of artificial intelligence in various fields, including medicine, image creation, medical diagnoses, and decision-making processes. Experts from natural and social sciences will discuss the effects of AI on society, ethics, and democracy.
Five new professors join Goethe University's C3S, focusing on biodiversity modeling, socioeconomic drivers of climate change, data surveillance, critical computational literacy, and the normative constitution of computation. Hagen, Linsenmeier, Akbari, Verständig, and Müller-Mall bring fresh momentum to the center.
A team of scientists has estimated that an average cell line acquires and retains roughly 13 percent of its genes every million years through lateral gene transfer. This process enables microbes to adapt to new environments and access essential nutrients. The study provides the first quantitative analysis of gene transfer rates across ...
Tayfun Tezduyar's space-time computational flow analysis enables accurate modeling of complex systems, from designing parachutes for astronauts to simulating blood flow through heart valves. The approach provides high-fidelity representations in both space and time, allowing for more realistic solutions.
Researchers at Saarland University discovered that molecular dipoles in ice and shoe soles interact to create a disordered, amorphous structure on the ice surface. This interaction causes the ice to become slippery, leading to slips and falls, rather than pressure or friction.
Researchers have developed a new method to accurately measure the acidity of PFAS, finding some to be thousands of times more acidic than previously thought. This breakthrough could help track the persistence and spread of these toxic chemicals in the environment.
Florida Atlantic University's FAU Engineering has received a $827,533 USD grant from the USDA to develop an advanced edge/fog computing-based framework called FogAg. This project aims to revolutionize precision agriculture by enabling real-time sensing and analysis of crop growth and yield.
A study by BSC-CNS analyzed molecular data from over 4,000 patients and 45 diseases using a newly developed computational method. The results show that 64% of medically known connections are related by similarities in gene expression, providing clues about the biological mechanisms linking them.
The study reveals that when physical constraints are removed, human mobility follows a power-law pattern, decreasing steadily with distance. The researchers found this pattern across five orders of magnitude, from 10 meters to hundreds of kilometers.
Researchers at Tohoku University have developed an AI-built materials map that combines experimental data with computational predictions to identify promising materials for thermoelectric waste-heat recovery. The map enables faster development timelines and reduces trial-and-error, accelerating innovation in energy-related technologies.
Simpler, physics-based models can generate more accurate predictions than state-of-the-art deep-learning models for certain climate scenarios. However, simple models are more accurate when estimating regional surface temperatures, while deep-learning approaches excel at local rainfall estimation.
The inaugural AI in Agriculture Symposium will bring together experts from academia and industry to discuss the latest research and real-world applications for agriculture. The symposium will feature a roundtable discussion on multidisciplinary collaborations in agriculture.
A new computational framework has been developed to optimize cellular self-organization, allowing scientists to understand and control how cells grow and interact. The framework uses machine learning tools to extract rules that guide cell behavior, enabling the creation of artificial organs and potential treatments for cancer.
A new AI-assisted model combines MRI, biochemical, and clinical information to predict worsening knee osteoarthritis with high accuracy. The model showed improved accuracy in predicting worsening pain and joint space narrowing, suggesting its potential to enhance care.
The new model can predict how well any given molecule will dissolve in an organic solvent, helping chemists choose the right solvent for reactions. The researchers trained two models on a comprehensive dataset and found that their predictions were two to three times more accurate than the previous best model.
Research at the University of Rochester Medical Center and University College Dublin has revealed key insights into multisensory integration in the brain. The study found that when changes occur in both visual and auditory inputs, auditory and visual decision processes unfold in parallel but come together in the motor system.
Researchers from FAU and the Sensing Institute created a detailed computer model of the mouse brain's vasculature, simulating how brain blood vessels respond to hemodynamics and vasodynamics. The model shows that transitional vessels play a critical role in regulating flow and protecting the brain during increased activity.
PhyNetPy aims to create a unified framework for phylogenetic networks, enabling widespread use of complex models of evolutionary history. The project seeks to bridge the gap between phylogenetics and population genetics communities.
Andreas Papaefstathiou's research will help elevate the study of particle physics in nuclear collisions at Kennesaw State University. The grant will also contribute to the development of a new particle collider in the US, strengthening partnerships between universities.
New research finds that wildfire smoke substantially increases ozone concentrations, even in remote areas with few human emission sources. The study suggests that removing anthropogenic NOx emissions would not eliminate ozone problems, as fires can still produce ozone.
A large-scale modeling study led by MIT researchers reveals that dynamically adjusting vehicle speeds can cut annual city-wide intersection carbon emissions by 11-22%. Implementing eco-driving measures could also result in a 25-50% reduction in CO2 emissions if only 10% of vehicles adopt the technology.
Researchers are developing an AI imaging approach to distinguish between tumor progression and treatment effects in glioblastoma patients, promising to improve care and outcomes. The AI approach has already shown accuracy rates of up to 74% in initial testing.
Researchers found that bat boxes can reach lethal temperatures if not designed properly. Simulations showed that adding insulation, light colors, and thoughtful orientations can make the boxes safer. The study's code is publicly available, allowing conservationists to tailor their solutions to specific climates.
Researchers developed a customized parametric insurance system using Probabilistic Tsunami Risk Assessment (PTRA) to quantify tsunami losses and payouts. The proposed framework reduces overpayment by 60.9% while maintaining risk reduction, potentially saving lives and money.
A research team developed an innovative unsupervised model for industrial anomaly detection using paired well-lit and low-light images. The model leverages feature maps, Low-pass Feature Enhancement, and Illumination-aware Feature Enhancement to detect anomalies while remaining lightweight and memory-efficient.
This book provides a beginner-friendly resource on the impact and evolution of decentralized networks, highlighting their applications in healthcare, supply chains, agriculture, climate monitoring, and education. The authors emphasize sustainability, data security, and ethical tech adoption.
Researchers create a technique to model organic objects, creating photorealistic 3D images of complex shapes for autonomous sorting. This method improves robotic systems that sort microscopic marine fossils used in climate research.
The team aims to deliver AI power directly to devices, improving resilience and speed in constrained environments. By processing data step-by-step across a network of devices, they can create a safe and adaptable system that can withstand attacks and extreme conditions.
Researchers developed a hybrid approach combining molecular dynamics simulations and Helfrich theory to evaluate bending rigidities of graphene nanosheets with lattice defects. The study reveals insights for designing novel materials with tailored mechanical properties.
Zhuoran Qiao's AI-driven tool, NeuralPLexer, enables researchers to quickly model biomolecular interactions and predict drug binding pockets. This breakthrough accelerates the development of new drugs and healthcare.
Scientists use human-AI collaboration to tackle complex questions in condensed matter physics, leveraging machine learning algorithms to identify patterns in simulation data. This approach successfully models the behavior of frustrated magnets and sheds light on quantum computing and gravity.
The Hong Kong Polytechnic University has secured funding from the Research Grants Council to develop a cost-effective and sustainable collaborative Generative AI (Co-GenAI) model. The project aims to democratize AI development by reducing centralized computational demand and enabling broader participation in GenAI research and deployment.
Stanford researchers introduce a cost-effective way to evaluate AI language models, accounting for question difficulty to ensure fair comparisons. The new approach reduces costs by half and enables rapid progress in the field of artificial intelligence.
Researchers are creating generalized digital twins for machines, aiming to improve coordination up and down the production line. The center also plans to develop digital twins for human-robot collaboration and use software for simulation and analysis.
Researchers found that LLMs are better at representing non-sensorimotor concepts but struggle with sensory and motor concepts. Incorporating sensory input improves LLM performance and leads to more human-like representation, consistent with previous human studies on multimodal learning.
Hypergraph research aims to improve network resilience by analyzing multi-way relationships, enabling more accurate representations of complex systems. By modeling projects within Texas A&M University as hypergraphs, researchers can depict interconnectedness and how individual work affects the entire system.
A new design method, SPADE, evaluates UAV video surveillance system quality without real-world manipulations. It assesses the impact of image resolution on object detection performance., The SPADE method can be applied to various UAV systems and will aid in designing complex large-scale systems involving multiple UAVs.
Researchers have developed a world-first method to simulate specific types of error-corrected quantum computations, a significant leap forward in the quest for robust quantum technologies. The new algorithm tackles a long-standing challenge in quantum research and enables accurate simulation using conventional computers.
Researchers at the Wyss Institute have identified vorinostat as a promising treatment for Rett Syndrome using an AI-driven drug discovery process and innovative disease modeling. The findings demonstrate disease-modifying abilities across multiple tissues, offering hope for a potentially curative treatment.
Scientists have developed a new multiscale modeling approach that can simulate how microscopic changes affect macroscale brain activity. The framework successfully predicted the effects of anesthesia on synaptic receptors, bridging the gap between molecular and whole-brain levels.
Researchers at Cornell University have developed a process that transforms short videos of rooms into highly accurate, interactable 3D simulations. The technology can be used to create more realistic video games and train robots to operate within specific real-world spaces.
A novel 3D modeling method accurately quantifies the shading potential of over 800 microalgal species, affecting underwater light conditions and ecosystem balance. The study provides a comprehensive Projected Area Database for freshwater microalgae, enabling researchers to estimate the ecological impact of algal blooms.
Researchers developed an AI tool called AAnet to characterize cancer cell diversity, identifying five distinct cell groups with different gene expression profiles. This could lead to more targeted therapies and improved patient outcomes.
Researchers at ETH Zurich have created a living material that can absorb CO2 from the air through photosynthesis and store it in a stable mineral form. The material, made with cyanobacteria, can be shaped using 3D printing and requires sunlight, water, and nutrients to grow.
Researchers Mostafa Bedewy and Ahmed Aziz Ezzat are advancing nanomanufacturing by using machine learning to control the formation of nanoparticles and grow carbon nanotubes. The team aims to reveal which nanoparticles act as seeds for growing nanotubes, a key step towards creating ideal high-density structures.
A new study published in Frontiers in Robotics and AI explores the use of artificial intelligence to detect live oysters. While the AI model ODYSSEE shows promise, it lags behind humans in accuracy, correctly identifying live oysters at a rate of 63% compared to 74% for expert annotators.
A new AI tool predicts infectious disease risk using large language modeling, consistently outperforming existing methods. The model uses real-time information to predict disease patterns and hospitalization trends, filling a gap in pandemic prediction tools.
A newly developed AI model, crossNN, accurately diagnoses brain tumors in 99.1% of cases and differentiates between over 170 tumor types from all organs with 97.8% accuracy. This technology enables non-invasive diagnostics using cerebrospinal fluid samples, providing a stress-free alternative to traditional biopsy methods.
A new AI tool developed by University of Missouri researchers can predict the 3D shape of chromosomes inside individual cells, providing a new view of how genes work. The tool helps identify unique differences in chromosome folding between cells, which controls gene activity and can lead to diseases like cancer.
Researchers have successfully modeled the synaptic vesicle cycle with unprecedented detail, shedding new light on how our brains function. The model predicts parameters of synaptic function that could not be tested experimentally, opening new avenues for neuroscience investigations.
Researchers propose therapeutic robots exhibit autonomy, responding only when users are calm and emotionally regulated, to foster trust, empathy, and fine-tuning. This approach has the potential to transform robotic therapy and human-robot interaction in fields like social skills development and emotional coaching.
Researchers have developed an image-analysis tool called SeaSplat that cuts through the ocean's optical effects and generates images of underwater environments with accurate colors. The team paired SeaSplat with a computational model to convert images into three-dimensional underwater worlds, allowing for virtual exploration.
Researchers created over 3,800 anatomically accurate digital hearts to investigate how age, sex, and lifestyle affect heart disease. They found that age and obesity cause changes in the heart's electrical properties, which could explain why these factors are linked to a higher risk of heart disease.
Kobe University researchers uncover a new phenomenon in bismuth that masks its surface conductivity, relevant to topological materials suitable for quantum computing and spintronics. The study breaks the principle of bulk-edge correspondence, suggesting 'topological blocking' in other systems.
Researchers at Texas A&M University developed a new AI model to speed up building damage assessments and predict recovery times after a tornado. The model uses remote sensing, deep learning, and restoration models to generate damage assessments in under an hour, providing actionable intelligence for first responders and policymakers.
A new AI-driven tool can forecast acute child malnutrition in Kenya up to six months in advance with high accuracy, enabling timely interventions. The model integrates clinical data and satellite information to identify emerging risk areas, providing a game-changing solution to address public health emergency in the country.