Articles tagged with Computer Simulation
A new approach enables computers and machines to capture images at higher resolution and faster speed, making it impervious to reflective surfaces. The technology uses a virtual screen created by repurposing the surroundings of specular objects.
Researchers developed genESOM, a generative AI that can expand dataset volume and simulate larger animal numbers while maintaining reliability. This allows for 30-50% reduction in animal experiments without compromising results.
Researchers developed a fleet of cooperative robots that, like ants, can spontaneously organize to build and dismantle structures without central control. They identified key parameters needed for excavation and building performance using simple local rules.
Researchers at Kyushu University developed a new mathematical model that simulates oxygen transport by red blood cells through tiny blood vessels and their delivery to surrounding tissues. The findings show that RBCs can naturally adjust the amount of oxygen released based on local requirements.
A team of researchers from The University of Osaka used supercomputer simulations to study how vortices generated by dolphin kicks power fast swimming. They found that large, powerful vortices created by the movement of the dolphin's tail are responsible for most of the propulsion, while smaller ones contribute little to forward motion.
Researchers propose new method to capture complex human movement in public spaces, addressing limitations of traditional approaches. By standardizing data measurement, they aim to improve crowd safety predictions and design safer spaces.
A new computational model developed by researchers at Chalmers University of Technology shows that onshore wind is likely to supply around 25% of global electricity by 2050 and solar reaching about 20%, aligning with the 2°C target. However, this falls short of what is required for a 1.5°C goal.
Researchers at Chalmers University of Technology have demonstrated that several qubits can share the same cable without significantly increasing computation time. This breakthrough technique could enable large-scale quantum computers with thousands of well-functioning qubits, revolutionizing fields like drug development and logistics.
The University of Michigan's new solar particle forecasting technology has been integrated into NASA's Artemis II mission to provide situational awareness of impending harmful radiation released during solar flares and eruptions. The machine-learning model uses satellite images of the sun and corona to forecast solar particle storms up...
Researchers have created a new AI model that can simulate molecules under extreme conditions, allowing for reliable discoveries in fields like drug development and sustainable chemistry. The model's stability opens up new opportunities for simulations in areas where long-term accuracy is essential.
Researchers developed an AI model to create highly photorealistic 3D reconstructions of ground-level damage after earthquakes. The LoRA-Enhanced Ground-view Generation diffusion model can recognize complex visual patterns and predict where structures may be damaged, even in densely populated urban areas.
A new study reveals that the hippocampus represents emotion concepts in a structured hierarchy of pleasantness and bodily reaction, while the ventromedial prefrontal cortex tracks relationships between these nodes. This map-like representation may help in the treatment of mental illnesses, such as depression and anxiety.
Researchers from CASUS at HZDR developed a reliable computational framework to study polyheptazine imides' electronic and optical properties. This work confirms the potential of these materials for photocatalytic reactions, including water splitting and carbon dioxide reduction.
A new AI model can predict moderate heat stress on Florida reefs up to six weeks ahead of time. The model is accurate within one week and provides site-specific predictions, helping coral scientists and restoration practitioners with local reef management and emergency response planning.
Researchers at OIST found that combining inner speech with working memory enhances AI learning, enabling easier adaptation to new situations. This discovery holds promise for developing more human-like AI systems capable of handling complex, dynamic environments.
Researchers have developed a GNSS-only method that consistently outperforms existing methods in dense urban areas, enabling safer and more reliable autonomous navigation. The approach uses a probabilistic framework to estimate position without relying on carrier-phase integer ambiguity resolution.
Researchers at the University of Groningen developed an atomistic model that predicts the driving force for microstructural twinning in shape memory alloys. This discovery can lead to the creation of new crystalline materials with improved reversible deformations, vibration damping, and impact absorption.
New research demonstrates neuromorphic computing's ability to solve complex mathematical problems, including partial differential equations. This technology has the potential to revolutionize energy-efficient computing and tackle real-world challenges.
Researchers developed a portfolio optimization framework to maximize offshore energy production by identifying optimal locations for wind turbines and marine hydrokinetic technologies. The study found that combining these technologies in suitable locations can significantly reduce costs and increase energy stability.
A team of researchers used innovative approaches, including public data and machine learning models, to create more accurate predictions of coastal erosion and infrastructure damage. The project aims to improve storm preparedness and timeliness.
The UC3M's new supercomputer is a state-of-the-art facility designed to support research and development projects requiring high-performance computing. The system features over 11,500 CPU cores and 42 GPUs, enabling the processing of large volumes of data and complex numerical simulations.
This study investigates how environmental variability and human migration influence the evolution of cooperation among humans. Simulation results reveal that cooperation is more likely to evolve when these factors are sufficiently high, hindering non-cooperative groups and encouraging cooperative groups.
A new study used deep learning and large-scale computer simulations to identify structural differences in synthetic cannabinoid molecules that cause them to bind to human brain receptors differently from classical cannabinoids. Researchers found that these substances often trigger the beta arrestin pathway, leading to more severe psych...
Researchers at MBL propose a model for how properties of individual molecules emerge to form liquid droplets called condensates. By combining imaging and computer simulations, they reveal the importance of linker DNA in determining condensate structure.
The new LimbNET platform enables direct simulation of complex biological growth processes, empowering researchers to test and compare hypotheses. The project aims to enhance collaboration, transparency, and knowledge building in the limb development community.
A Kobe University team has introduced a new method using deep learning for creating tailored simulations that respect physical laws while being computationally efficient. The approach shows superior accuracy in simulating diverse physical systems, including those with chaotic behavior.
An international team led by Lehigh University researcher Hannah Dailey is building predictive models to understand and eventually prevent bone healing complications. The team aims to incorporate biological differences into the model, using a library of imaging data from Switzerland's AO Research Institute Davos.
McMaster and Pittsburgh researchers have developed a soft material that can perform a NAND logic operation using only three beams of visible light. The breakthrough paves the way for autonomous systems with computation capabilities without traditional electronics.
Researchers at RIKEN successfully simulated the Milky Way Galaxy with over 100 billion individual stars, far surpassing previous state-of-the-art models. This achievement demonstrates the power of AI-accelerated simulations in tackling complex multi-scale problems in astrophysics and beyond.
A new report from Earth4All argues that Brazil's vast forests and renewable energy potential are complemented by the power of trust and social cohesion in tackling the climate crisis. The study identifies five areas for coordinated reforms to accelerate decarbonisation and build resilience, including poverty reduction and inclusive gov...
The Stowers Institute has appointed its first AI Fellow, Sumner Magruder, to harness the potential of artificial intelligence in biological research. He will collaborate with researchers to design new algorithms and unlock insights from large datasets.
Researchers at Washington State University found that early planting to avoid heat damage may actually hinder spring wheat productivity due to other growth issues. The study used computer modeling to show that moving crop plantings earlier in the season can expose crops to elevated heat or cold stress in later growth stages.
Marmar Moussa's project aims to bridge the gap between single-cell technologies and spatial tissue analysis, creating a more complete picture of disease development. The new algorithms will enable scientists to study tumor progression, extracellular matrix remodeling, and other dynamic processes in cancer and beyond.
A solar sail probe could provide a new vantage point for detecting space tornadoes, also known as flux ropes, which can disrupt Earth's magnetic field. These smaller features are too small for typical simulations, but a solar sail probe can help scientists see them and predict potential hazards.
A recent study used Japan's Fugaku supercomputer to simulate the effects of time-varying dark energy on cosmic evolution. The results show that a higher matter density creates stronger gravitational forces, leading to earlier and more efficient formation of massive galaxy clusters.
A research team has discovered the structural origins of mechanical softness in amorphous materials like glass, attributing it to hierarchical ring structures that coexist with medium-range order and local disorder. This finding will accelerate the design of flexible and strong amorphous solids.
Biomedical engineers at Duke University developed a platform combining automated wet lab techniques and AI to design nanoparticles for drug delivery. The TuNa-AI platform resulted in a 42.9% increase in successful nanoparticle formation compared to standard approaches.
Researchers at FAU have developed a smarter AI framework that can manage complex systems with unequal levels of authority and adapt to imperfect information. The framework, based on reinforcement learning and game theory, reduces unnecessary computation while maintaining system stability and optimal strategy outcomes.
University of Michigan researchers have made significant progress in developing a more accurate simulation approach for density functional theory, a widely used method in fundamental chemistry and materials science studies. The new approach has improved the calculation of exchange-correlation functionals, which describe how electrons i...
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.
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.
Researchers developed a two-phase simulation model incorporating air-water interactions, representing eddies and aerosols more realistically. The hybrid method balances computing power and precision, conserving resources in less active areas.
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.
Researchers at Penn State have simulated a new class of protein misfolding using atomic-scale models, revealing a type of entanglement that disrupts protein function and persists in cells. The findings support the existence of this long-lasting type of misfolding, which is thought to contribute to aging and disease.
Researchers developed a novel framework using generative AI and musculoskeletal simulation to create synthetic gait data. This approach enables more robust and generalizable gait analysis across various patient populations and clinical environments.
Researchers developed a software fueled by genomics to predict cancer cell behavior, combining genomics technologies with computational modeling. The new 'grammar' enables communication between biology and code, allowing scientists to build digital representations of multicellular biological systems and simulate diseases like cancer.
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.
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 at Tohoku University developed a new framework for simulating nonlinear quantum dynamics, making it easier to understand and study complex quantum systems. The method uses time-evolution data to extract nonlinear response functions without requiring explicit multipoint correlations.
A team of Penn engineers and materials scientists have developed a biomineral-infused concrete that captures up to 142% more CO2 than conventional mixes while using less cement. The new material is stronger, lighter, and uses fewer materials like cement.
A Cochrane review found that virtual reality (VR) can help stroke survivors regain arm movement and increase therapy time. VR may also improve balance and reduce activity limitations, but effects on mobility and quality of life are uncertain.
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 from The University of Osaka have demonstrated that vision transformers can spontaneously develop human-like visual attention patterns without specific training. This breakthrough showcases the potential of self-supervised learning for advancing AI applications and modeling biological vision.
Researchers at Rice University have developed a novel personalized medicine approach for addressing movement impairments. The Neuromusculoskeletal Modeling (NMSM) Pipeline software allows clinicians to work in collaboration to construct personalized computer models of individual patients, leading to more effective orthopedic surgery, p...
TIFRH researchers found that imparting additional motility to poorly annealed glass components can induce further annealing, transforming a ductile material into a brittle one. This discovery provides insights into how cells might regulate glassiness and aids in designing new metamaterials.
Researchers developed T2IRay, a VR input method with precise object pointing, and ChoreoCraft, a virtual reality tool supporting choreographers' creativity. These technologies received Honorable Mention awards at CHI 2025 for their contributions to human-computer interaction.
A new computer model simulates magnetism and turbulence in the interstellar medium, providing unprecedented detail on the Milky Way Galaxy's overall magnetic field. The model also helps understand star formation and the propagation of cosmic rays, offering insights into astrophysical phenomenon.
The study models ASFV outbreaks in densely populated US swine states, highlighting the need for enhanced sampling strategies and laboratory capacity to prevent delays and contamination. The model suggests that a minimum of 136-367 sample collectors are needed in non-epidemic scenarios, increasing to 833-3115 in large outbreak scenarios.