Articles tagged with Computational Science
Cleveland Clinic researchers successfully tested quantum computing's ability to simulate proton affinity, a fundamental chemical process critical to life. The study used machine learning applications on quantum hardware, achieving higher accuracy than classical computing in predicting proton affinity.
A new brain-like computer uses analog computing to process and store information in the same location as biological neurons, reducing power consumption by 0.25%. The device, called a memristor network, is more efficient than conventional transistor-based computers and has implications for autonomous vehicles and drones.
A team of researchers from Osaka University has demonstrated that human tissue can be used to solve complex equations and process information, outperforming traditional computing methods. This breakthrough uses the concept of reservoir computing, where data is input into a complex 'reservoir' that encodes rich patterns.
UTA's expansion of its undergraduate research program has enabled students to present their work at major symposiums, including the American Institute of Aeronautics and Astronautics conference. The program has strengthened students' commitment to pursuing graduate studies in various fields.
A Microsoft team led by UC Santa Barbara physicists has developed an eight-qubit topological quantum processor, opening the door to a more stable and robust quantum computer. The chip utilizes Majorana zero modes for error correction, promising a fault-tolerant system.
The Heidelberg Laureate Forum Foundation offers journalist travel grants to cover the 12th HLF from September 14-19, 2025. Journalists can apply until March 31, 2025, and will have exclusive access to interview renowned laureates and young researchers.
The 'equity by design' framework proposed by Daryl Lim aims to maximize AI benefits while minimizing harm, particularly for underrepresented individuals. The approach embeds equity principles throughout the AI lifecycle, addressing biases and increasing inequality.
A new study by the University of Granada's DaSCI institute uses deep generative vision models to create highly realistic satellite images of future climate-related events. The model outperforms pure deep learning and manual solutions, reducing prediction errors and improving image reliability.
The new startup, AQSolotl, has developed a quantum controller that enables users to control quantum computers easily using laptops and desktops. The technology, developed by NTU and NUS researchers, is designed to be scalable, adaptable, and cost-efficient.
The authors introduce advanced methodologies for integrating maintenance strategies and structural health monitoring to extend infrastructure service life. Topics include data-driven decision-making, multi-objective optimization, cost-benefit analysis, and the role of data analytics in managing uncertainties.
A new study by University of Michigan researchers introduces a framework to compare and analyze competitive interactions across various fields, from sports to social hierarchies. The 'depth of competition' model reveals that human games and sports are surprisingly shallow, while animal competitions exhibit much deeper stratification.
The NSF-Simons AI Institute for the Sky (SkAI), led by Northwestern University, will develop innovative AI tools capable of handling vast data from astronomical surveys. Funded by a $20 million grant, Argonne National Laboratory will help drive this revolution in astronomy.
A new generative AI tool called Theseus is being developed to reduce time and labor in computational modeling, suggesting and running simulations to accelerate research and discovery. The AI assistant aims to enhance the work of computational scientists by providing scientific intuition, checking code for bugs and making suggestions.
Chris Van de Walle, a distinguished professor at UCSB, has been awarded the American Physical Society's 2025 Aneesur Rahman Prize for Computational Physics. He was recognized for his development and application of first-principles methods to compute structural, electronic, and optoelectronic properties of point defects and interfaces.
Scientists have developed a new method using artificial intelligence to design thousands of DNA switches that can activate or repress genes in specific cell types. This approach could revolutionize gene therapy and biotechnology by allowing precise control over gene expression in the body.
The U.S. Department of Energy has selected Kate Petersen Mace as the project director for the High Performance Data Facility (HPDF), a first-of-its-kind project providing resources for data-intensive science. Mace will lead the team in developing transformational capabilities to serve the DOE community.
A study reveals that the gender gap in physics has remained stable for over a century due to established scientists' adoption patterns and network inclusion. The gap can be closed by adjusting parameters, but interventions such as funding and promotion opportunities are more challenging.
A new AI model generates detailed images of cancer tissue that imitate what its staining would look like, reducing the need for resource-intensive lab analyses. The VirtualMultiplexer uses contrastive unpaired translation to create accurate virtual pictures of diagnostic tissue colorations.
A new AI-based digital platform has been developed to analyze tissue sections from lung cancer patients, making diagnosis faster and more accurate. The platform uses algorithms that enable fully automated analysis of digitized tissue samples, allowing for personalized therapy based on molecularly specific genetic changes.
Researchers at Tokyo Institute of Technology have developed a novel strategy to increase the efficiency of photopolymerization reactions by leveraging dynamic UV lighting. This technique produces heavier polymer chains with reduced energy consumption, offering potential for sustainable industrial processes and polymeric materials.
A new study by an international team, including MIT and CNRS, observed that similarities exist between the behavior of birds in flight and physical systems. The research suggests that the transition from disorder to coordination is not as different between particles and biological elements as previously thought.
Researchers found that children's immune systems attacked their own tissues after latching onto a coronavirus protein resembling one found in multiple organs. Early intervention was crucial to prevent death in these cases, and the study has implications for understanding other autoimmune diseases.
A new open-source platform, Nova-ST, is transforming gene expression profiling in tissue samples by offering affordable and high-resolution spatial analysis. This approach allows scientists to map gene expression across a tissue section with a spatial context, enabling the study of complex biological processes.
Scientists used AI to identify genes that can convert brain cancer cells into immune cells, increasing survival chances by up to 75% in mouse models. The approach bypasses the blood-brain barrier, offering new hope for aggressive cancers.
Researchers measured dielectric properties of 11 polyimides to establish correlation between molecular structure and dielectric behavior. The study revealed that higher fluorine content resulted in lower dielectric constant values, enabling potential applications for 6G technologies.
Researchers developed a crystalline solid that can adsorb and release ammonia, making it easy to recover. The material's high density and ease of desorption make it a promising solution for efficient hydrogen storage.
A groundbreaking approach inspired by bio-inspired neuromorphic imaging and speckle correlography has unveiled a revolutionary technique for optical image encryption. This method leverages computational neuromorphic imaging to encrypt images into event-stream ciphertexts, significantly enhancing security and complexity.
A new study reveals that data on popular community science platforms is biased towards easily identifiable and attractive species. Researchers found that iNaturalist's reliance on photos creates a personal bias, underreporting certain species and overreporting others.
Researchers at USC developed a new method to accurately predict wildfire spread using satellite data and artificial intelligence. The model offers a potential breakthrough in wildfire management and emergency response, providing more precise and timely data for firefighters and evacuation teams battling wildfires.
Researchers at Argonne National Laboratory have developed biodegradable and recyclable luminescent polymers that can break down under heat or mild acid. The material showed a tenfold increase in light-emitting efficiency, making it suitable for applications such as displays and medical imaging.
Researchers developed a method to assess the reliability of foundation models, enabling users to choose the best model for their task without testing it on real-world data. The approach measures consensus among multiple models and aligns representations to compare consistency.
Researchers created a new cortical surface template called 'OpenNeuro Average' that provides greater accuracy and efficiency in analyzing neuroimaging data. The template is based on the geometric shape of the brain and can be used for studies on cognition, clinical neuroscience, autism, and neurodegenerative diseases.
A recent study predicts that lakes worldwide will experience unprecedented surface and subsurface warming, leading to severe disruptions in ecosystems. Tropical lakes are expected to be the first to emerge from natural temperature bounds, while high-latitude lakes may shield their subsurface layers from surface warming.
Scientists from Trinity College Dublin created a computer program that visualizes molecular structure in the style of Piet Mondrian. The program uses blocks of color to represent symmetry and shape, making it easier to understand complex molecular interactions.
Scientists developed customized AI tools, including ChatGPT, to provide accurate responses on digital pathology. The tools help pathologists without extensive coding experience analyze tissue samples, bridging the gap between pathology and digital pathology skills.
A deep metagenomic sequencing study in Berlin wastewater reveals common viruses like RSV and flu, seasonal visitors like asparagus-infecting viruses, and astroviruses with potential for gastrointestinal tract infections. The analysis also identifies novel enzymes with biotechnological potential, expanding our knowledge of viral diversity.
A team of researchers developed EMOKINE software to measure the objective kinematic features of movements that express emotions. The software provides movement parameters from data sets at the touch of a button, allowing scientists to analyze emotional expression and intentions.
A new imaging technique allows scientists to visualize the Earth's rocky interior using GPS data, revealing details about the planet's crust and mantle. This method has the potential to improve earthquake predictions by combining it with other techniques.
Researchers have discovered that gallium's bonds disappear at melting point but reappear at higher temperatures, leading to a new explanation for its low melting point. This breakthrough has important implications for advances in nanotechnology and materials science.
A new model developed by Flatiron Institute researchers proposes that individual neurons exert more control over their surroundings, which could be replicated in artificial neural networks. This updated model treats neurons as tiny 'controllers' and may lead to better AI performance and efficiency.
A platform called Open-ST enables scientists to reconstruct gene expression in cells within a tissue in three dimensions, capturing molecular and (sub)cellular structures. The platform was used to study cell types at subcellular resolution in tissues from mice brains, tumor tissue, and healthy lymph nodes, providing insights into cance...
A new study found that animals use a wide range of strategies to accomplish tasks, many of which are just as effective as the optimal solution but require less brain power. The research provides a theoretical framework for understanding these 'good enough' strategies and their potential applications in animal behavior.
A new system named SQUID, a computational tool created by Cold Spring Harbor Laboratory scientists, helps interpret how AI models analyze the genome. It reduces background noise and leads to more accurate predictions about genetic mutations.
Researchers create special language Phenoscript to describe traits in a way that both humans and computers can understand. This allows for large-scale studies of organismal traits, boosting the emerging field of phenomics. The new language is being tested and aims to integrate semantic species descriptions with nanopublications.
Researchers from MIT develop a new technique called Natural Language Embedded Programs (NLEPs) to enable large language models to solve numerical, analytical, and language-based tasks. NLEPs achieved greater than 90 percent accuracy on symbolic reasoning tasks and showed 30 percent greater accuracy than task-specific prompting methods.
Researchers developed a quantum annealing approach to accelerate data assimilation, significantly reducing computational cost. The method achieves comparable accuracy to conventional approaches but in a fraction of the time.
Researchers at NCCR MARVEL have discovered a chain of copper and carbon atoms that forms the thinnest metallic nanowire stable at 0K. CuC2 has promising properties for flexible electronics, including its ability to be bent without losing its metallic behavior.
A new study by a global consortium provides insight into how tumors evolve, shedding light on the intricate processes underlying cancer evolution. The findings define optimal algorithms to analyze tumor evolution, enhancing diagnostic accuracy and treatment planning.
A new method developed by researchers at Florida Atlantic University and the Smithsonian Environmental Research Center improves the accuracy of acoustic tracking in marine animals. The method uses a movement model to reconstruct animal tracks, even in regions with uneven receiver coverage.
A new system developed by Boyce Thompson Institute makes affordable, mobile and high-throughput phenotyping tools accessible worldwide. This allows researchers to conduct data-driven studies on plant growth and responses over time, accelerating breeding of more resilient crop varieties.
Researchers at La Jolla Institute for Immunology developed a computational method to link gene activity to molecular marks on DNA, potentially aiding in the detection of solid tumors and more accurate cancer diagnoses. This new approach utilizes machine learning tools to identify connections between genes and enhancers in the genome.
Portland State University has secured a nearly $1 million grant from the National Science Foundation's Campus Cyberinfrastructure program to establish the Oregon Regional Computing Accelerator (Orca) cluster. The cluster will provide free-of-cost computing resources and cyberinfrastructure to colleges in rural, regional, and minority-s...
A novel approach to training AI systems uses information about spatial position to identify objects and navigate surroundings, inspired by children's visual development. The method improves contrastive learning models' effectiveness by incorporating simulated spatial context information, outperforming base models in various tasks.
The study enhances shape-from-shading technique to create detailed models of lunar terrain with higher resolutions and faster production speeds. Researchers use advanced computer algorithms to automate the process, resulting in more accurate maps that show subtle features and variations of lunar surface terrain.
Researchers at Lancaster University and Radboud University Nijmegen have discovered a novel pathway to modulate and amplify spin waves at the nanoscale, paving the way for dissipation-free quantum information technologies. The study's findings could lead to the development of fast and energy-efficient computing devices.
Cleveland Clinic and IBM researchers develop a hybrid framework combining quantum and classical computing methods for protein structure prediction. This approach overcomes limitations of current classical methods and demonstrates improved accuracy in predicting protein structures.
Elastic turbulence, a chaotic fluid motion in non-Newtonian fluids, exhibits universal power-law decay of energy and intermittent behavior. This study reveals its unexpected similarity to classical Newtonian turbulence, paving the way for developing a complete mathematical theory and predicting flow patterns.
Researchers from the University of Bath have created a deformable screen called DeformIO, which can be deformed through finger pressure. The surface becomes softer or stiffer in direct response to force applied, allowing users to interact with digital objects in a more tactile way.
Researchers in Portugal have developed an innovative open-source platform called DL4MicEverywhere, providing life scientists with easy access to advanced artificial intelligence for the analysis of microscopy images. The platform enables researchers to easily train and use deep learning models on their own data, regardless of their com...
A novel multifunctional catalyst has been developed to convert methane into valuable hydrocarbons, reducing greenhouse gas emissions and energy consumption. The catalyst's spatial distribution of Cu and acid sites determines the final products, with uniform distribution leading to stable and efficient methanol production.