Articles tagged with Computational Science
A study using anonymized patient records from UC health centers found over 600 correlations between endometriosis and other conditions, including infertility, autoimmune disease, and certain cancers. The research supports the growing understanding of endometriosis as a multi-system disorder.
A new book introduces a structure that balances efficiency and fairness in optimization models, examining real-world effects of different approaches. It suggests that truly optimal results are fair ones, promoting informed and ethical choices in algorithm-driven world.
A combination of two approved cancer medications may slow or reverse Alzheimer's symptoms by reversing gene expression changes in neurons and brain cells. Researchers analyzed public data from deceased donors and found a link between these drugs and reduced risk of developing the disease.
A national pilot program led by UTA faculty is helping take the mystery out of quantum physics for students and educators. The program, Quantum for All, provides hands-on curriculum and classroom strategies to equip high school science teachers with the tools they need to teach quantum science.
A team of researchers has successfully described warm dense matter, a state of matter combining solid, liquid, and gaseous phases, using a new computational method. This breakthrough advances laser fusion research and helps in the synthesis of new high-tech materials.
Researchers from OIST develop new quantum AI method for image recognition based on boson sampling, achieving highly accurate results without complex training. The approach uses a linear optical network and preserves information, outperforming classical methods in various datasets.
The Human Exposome Moonshot initiative aims to map the physical, chemical, biological and psychosocial exposures driving 80% of chronic diseases. The exposome project integrates advanced technologies to create a comprehensive understanding of environmental influences on health.
Researchers at Harvard developed link-bots, centimeter-scale robots composed of V-shaped chains with notched links, capable of coordinated movements and emergent collective behavior. The team demonstrated link-bots' ability to move forward, stop, change direction, squeeze through gaps, and cooperate on tasks.
A team led by Kenneth Merz used IBM Quantum System One to run Sample-Based Quantum Diagonalization, a new method for simulating molecules in solvent. The approach achieved high chemical accuracy and demonstrated the ability to predict molecular energies and solvation free energy in aqueous solutions.
Prof. AU Man Ho Allen has been recognized with the prestigious Hong Kong Engineering Science and Technology (HKEST) Award 2024-25 for his outstanding contributions to the Web3 ecosystem and the digital economy. His research focuses on developing practical, secure, and privacy-preserving cryptographic solutions.
The fifth annual Quantum Science Center Summer School at Purdue University welcomed its largest group of students, with a focus on introductory presentations and technical talks. Graduate students and doctoral candidates led the program, which covered topics such as quantum materials, devices, and algorithms.
Researchers at Caltech successfully controlled the motion of individual atoms, encoding quantum information, and demonstrated hyper-entanglement in massive particles. This experiment could lead to advancements in quantum computation and precision clocks.
Researchers at U of A create a transistor that operates at speeds over 1,000 times faster than modern computer chips. The breakthrough uses quantum effects to manipulate electrons in graphene, enabling ultrafast processing for applications in space research, chemistry, and healthcare.
The Human Exposome is a global scientific effort to understand the environmental factors that underpin disease and health. The Exposome Moonshot Forum aims to chart this exposome, providing usable metrics and data points for targeted public health interventions.
Skia identifies and decodes shadow branches, storing them in a memory area to alleviate bottlenecks and improve throughput. The technique can lead to quicker performance and less power consumption for data centers.
Researchers at the University of Bristol have discovered a novel way to accelerate accurate quantum measurements by trading space for time using additional qubits. This method enables faster and more confident measurements without sacrificing accuracy, with potential applications in leading quantum hardware platforms.
ACM has joined India's ONOS initiative, providing 6,500 government-funded institutions with Premium Access to the ACM Digital Library. This enables authors to publish unlimited Open Access articles without APCs, increasing global visibility and reach of Indian research.
A Lehigh University team developed a novel machine learning method to predict abnormal grain growth in materials, enabling the creation of stronger, more reliable materials. The model successfully predicted abnormal grain growth in 86% of cases, with predictions made up to 20% of the material's lifetime.
Researchers at ETH Zurich developed a method to measure frictional forces between single particles in suspensions. By understanding these microscopic interactions, they can optimize suspension flow characteristics and prevent dramatic thickening.
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 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.
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.
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.
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.