Articles tagged with Computational Science
The UCLA-led team has developed a solution to improve cryo-electron microscopy's imaging capabilities for smaller protein molecules, enabling higher-resolution images. This advance is expected to help researchers identify specific locations on proteins that can be targeted for therapeutic purposes.
Researchers aim to access ocean waters hidden beneath ice shelves, where critical information about climate change is stored. An intelligent mothership and coordinated marine robots will communicate data from under-ice cavities, optimizing sampling and configuration.
GlowTrack, a non-invasive movement tracking method using fluorescent dye markers, improves the capture of diverse movements in laboratories. This technique enables easier comparison of movement data between studies, increasing scientific discovery and advancing fields like biology, robotics, and medicine.
Researchers at MIT have developed a novel superconducting qubit architecture that can perform operations between qubits with high accuracy, exceeding 99.9% for two-qubit gates and 99.99% for single-qubit gates. The new design utilizes fluxonium qubits, which have longer lifespans than traditional transmon qubits.
Scientists have introduced a novel approach to change the shape of azobenzenes using visible light, enabling efficient and practical applications. The new supramolecular complex, called DESC, harnesses the power of red wavelengths to prompt molecular transformations.
Researchers have successfully developed a robot that can autonomously navigate through living lung tissue, avoiding vital structures such as airways and blood vessels. This innovation enables surgeons to reach previously inaccessible small tumors, improving treatment outcomes for patients with lung cancer.
A Tohoku University research team developed a technique to recreate water flow in real-time using only a small amount of data from real water. This technology enables the creation of immersive VR games with lifelike water motion, potentially enhancing online communication and remote interactions.
Researchers from the University of Oldenburg developed a new stochastic method to mitigate sudden swings in wind turbine power output. The study found that control systems are mainly responsible for short-term fluctuations and can be optimized to ensure more consistent energy output.
A new study published in Genome Biology analyzed the genomes of 2000 dogs from 321 breeds, revealing 25 major groups that match expected breed origins. The research found significant genetic variation among breeds, with wolves exhibiting 14% more variation than dogs.
The WVU team evaluated Code Interpreter's features, finding it accessible to students but limited for scientists working with biological data. The plugin breaks down barriers for coding, but lacks internet access and parallel processing capabilities.
MIT researchers developed a new algorithm that can execute complex maneuvers like loops and rolls for tailsitter aircraft, enabling agile trajectories with fast-changing accelerations. The algorithm uses differential flatness to ensure feasibility and planning in real-time.
The team successfully completed the sequencing of the Y chromosome using long-read sequencing technology and innovative computational assembly methods. This achievement adds 41 additional protein-coding genes and provides crucial insight into reproduction, evolution, and population change.
Scientists estimate annual probability of a mass shooting in every US state and public places like schools, using statistical methods and computer simulations. The study finds that mass shootings are low-probability but high-consequence events.
Researchers develop a new model predicting up to twice the original amount of subglacial water may be draining into the ocean, accelerating glacial melt and sea level rise. The theory uses satellite measurements and is a simple equation that can predict exfiltration in a fraction of a second on a laptop.
Researchers propose a hypothesis that astrocytes, non-neuronal cells in the brain, can perform core computation as transformers, providing insights into human brain function and machine learning success. This discovery could spark future neuroscience research and help explain transformer performance across complex tasks.
Researchers successfully created stem-cell derived organoids from human stem cells that secrete three essential enamel proteins. These proteins form a matrix that undergoes mineralization to create a hardened enamel structure. The breakthrough offers hope for developing novel treatments to repair and regenerate teeth.
A new study found that a massive North Atlantic cooling event led to the disruption of early human occupation in Europe, with climate stress changing the course of early human history. The study used observational and modeling evidence to document the unprecedented climate anomaly.
A recent study reveals that past climate changes and vegetation shifts played a key role in determining when and where early human species interbred. The research suggests that the overlap of habitats led to increased encounters and interactions among groups, increasing the chance of interbreeding.
A new machine-learning method, BigMHC, can accurately predict cancer-related protein fragments that may trigger an immune system response. By leveraging massive data through transfer learning, BigMHC enables scientists to develop personalized immunotherapies and vaccines by identifying the most likely to provoke an immune response.
A recent study by GEOMAR researchers found that fluctuations in the Labrador Sea can significantly influence the strength of sinking processes east of Greenland. This phenomenon affects the Atlantic Meridional Overturning Circulation (AMOC), a crucial climate system that brings warm water from the Gulf of Mexico to Europe.
Astronomers have created the first computer simulations showing how convection in the cores of massive stars generates waves that result in flickering starlight. The effect is different from the visible twinkling of stars in the night sky and could be observed with improved telescopes.
Researchers created a digital replica of patients' hearts to inform arrhythmogenic right ventricular cardiomyopathy (ARVC) diagnosis and treatment. The 'genotype-specific digital-twin' strategy could tailor therapies based on individual genetics, improving precision healthcare in other diseases.
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 at Michigan State University have discovered a way to utilize vibrations in quantum computing to prevent information loss. By tuning the vibrations experienced by qubits and understanding their impact on fidelity, the team can create more stable quantum states.
Researchers identify at least 10,000 novel foldable αβ-folds, expanding our understanding of the protein universe. The discovery has significant implications for fields like drug development and enzyme design.
Researchers created artificial allosteric sites in protein complexes using computational design to regulate concerted functions. This breakthrough holds promise for industry, biology, medicine, and agriculture.
Researchers created a detailed analysis of the domestic cat's nasal airway, revealing two distinct regions of air flow during inhalation. The study suggests that the cat nose functions as an efficient dual-purposed gas chromatograph, capable of detecting and separating chemicals quickly and efficiently.
Scientists at Argonne National Laboratory discovered a new fluoride electrolyte that can protect lithium metal batteries against performance decline. The electrolyte maintains a robust protective layer on the anode surface for hundreds of cycles, enabling the battery to last longer.
Researchers at the University of Waterloo discovered a method to bypass voice authentication security systems with high accuracy. They found that malicious actors can generate convincing copies of a victim's voice using deepfake software, evading existing spoofing countermeasures.
Researchers propose GREENER framework to promote sustainable research practices, reducing greenhouse gas emissions and maximizing benefits to humanity and environment. Key considerations include estimating energy consumption of algorithms, tackling embodied impacts through new collaborations, and relocating computations to low-carbon s...
BioAutoMATED is an all-in-one AutoML platform designed for biologists, enabling easy analysis and interpretation of biological sequences. The platform uses three existing AutoML tools to generate models that can predict biological functions from sequence information.
A new machine learning algorithm analyzed high-resolution digital images of herbarium specimens, revealing that factors other than climate have a strong effect on leaf size within a plant species. The study also demonstrates how AI can be used to transform static specimen collections and quickly document climate change effects.
African Superplume is responsible for rift-parallel deformation and seismic anisotropy in the East African Rift System, contradicting previous theories on plate-driving forces. The study uses 3D thermomechanical modeling to explain this phenomenon.
Researchers have made significant progress in reprogramming cells to supply the ribosome with building blocks other than alpha-amino acids. The ultimate goal is to make the translation system fully programmable, allowing for the production of an unlimited variety of new molecular chains with unique properties.
Researchers developed MOVA to evaluate the pathogenicity of missense variants based on their structural position. The new method showed superior performance in predicting pathogenicity, especially for hotspot mutations in ALS-causing genes like TARDBP and FUS.
Researchers at MIT have designed a computational model that can predict other people's emotions, including joy, gratitude, and regret. The model uses insights into human intuition, incorporating factors such as desires, expectations, and observation of actions to make predictions.
Researchers found that people divide complex tasks into simpler subtasks by balancing utility and computational cost. This approach is consistent with a new computational theory, suggesting a fundamental principle underlying human decision-making.
Researchers developed high-performance culture media using machine learning to predict superior medium compositions that yield higher cellular activity. The optimized medium promoted higher cell growth than commercial medium.
A new MIT study shows that lawyers prefer plain English contracts, which they find easier to understand and more appealing than traditional legal documents. The researchers found that while lawyers excel at reading and writing complex legalese, the style can be a barrier for non-lawyers.
The metaverse has the potential to make scientists more effective by removing barriers, improving teaching and learning, and enabling new experimental environments. Researchers must also plan well and avoid potential pitfalls, such as ownership and privacy issues.
A Texas A&M team is studying the impact of cryptocurrency mining on the state's power grid, revealing a potential for demand flexibility during times of peak energy usage. The research suggests that when the grid is stressed due to heatwaves or other factors, cryptocurrency miners can shut down, providing a buffer against strain.
Researchers used computational tools and medical record analysis to investigate the effects of statin drugs on COVID-19 patients. They found that only certain statins, including simvastatin and atorvastatin, reduced mortality risk in COVID-19 patients, while others had no effect.
Researchers develop innovative data compression scheme to facilitate multispeckle diffuse correlation spectroscopy with high pixel resolutions, enabling non-invasive measurement of brain blood flow. The scheme uses field-programmable gate array compression to alleviate computational burdens and expand the use of SPAD cameras in biomedi...
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.
A team of scientists created a mathematical model that accurately describes microstructures by integrating data from highly magnified images taken during experiments. The findings provide insight into how microstructures change at high temperatures and have implications for the development of new materials.
Scientists have successfully mapped the landscape of m6A modification in mouse embryos, revealing intriguing patterns of gene activity and distribution in transposable elements. This study fills a gap in the transcriptome field, providing new insights into the function of m6A during development.
Researchers identify potential application of quantum compression in edge computing, which could save storage space and network bandwidth. Quantum compression, a new concept, is being explored as an enabling tool for edge applications, with classical techniques compared to quantum approaches.
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 evaluate ChatGPT's potential in assisting computational materials science tasks, including building atomic structures and running DFT calculations. While the tool shows promise, it still faces limitations and ethical concerns.
Researchers have derived a formula predicting the effects of environmental noise on quantum computing. By incorporating redundancy in quantum messages, scientists can now quantify how much redundancy is needed to protect against dephasing noise.
The POSTECH team developed a multifunctional tip-enhanced spectroscopy that dynamically controls the physical properties of quasiparticles in 2D materials. This technology increases interlayer excitons' luminous efficiency by 9,000 times and modulates their energy.
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.
Rice University's assistant professor of computer science, Todd Treangen, has been awarded a $599,943 National Science Foundation CAREER Award to develop a comprehensive computational platform for detecting yet-unseen microbial pathogens. The project aims to characterize previously unseen pathogens that could pose a risk to humans.
A team of researchers has observed nanoparticles self-assembling and crystalizing into solid materials in real time, revealing the growth process at nanometer resolution. The findings have implications for designing new materials, including thin films for electronic applications.
Researchers at King Abdullah University of Science & Technology (KAUST) successfully integrated two-dimensional materials on silicon microchips, achieving high integration density, electronic performance, and yield. The resulting hybrid devices exhibit special electronic properties that enable low-power consumption artificial neural ne...
Researchers have created a high-resolution, single-cell model of the human hippocampus CA1 area using data from the BigBrain Atlas. The model replicates the structure and architecture of the neurons, as well as their connectivity. This advancement in neuroscience has potential applications for modeling other brain regions.
The new architecture reduces physical qubits required for error correction to 10% of conventional architectures, enabling better performance than classical computers. This breakthrough accelerates progress toward practical quantum computing, with the aim of applying quantum computing applications to various societal issues.
Richard McIndoe is leading a national research initiative to advance understanding of diabetes and obesity through the National Centers for Metabolic Phenotyping in Live Models of Obesity and Diabetes (MPMOD). The MPMOD initiative provides access to advanced testing services, including bariatric surgery on mice, to enable new insights ...
The new technology enables compact, low-power, fast, and energy-efficient devices for fibre-optical communications, sensors, and future quantum computers. This breakthrough could lead to advancements in applications such as 3D imaging for autonomous vehicles and photonic-assisted computing.
Researchers explore how AI language models like ChatGPT understand and respond to user input, mirroring their users' intelligence. The Reverse Turing Test reveals that chatbots reflect the intelligence level of their interviewers, incorporating their biases into responses.