Articles tagged with Computational Science
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.
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.
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 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 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 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 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.
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.
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.
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.
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.
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.
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.
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.
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 ...
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.
Researchers create lab-grown brain organoids as biological hardware to drive computing forward. These three-dimensional cultures can process information faster and more efficiently than current silicon computers.
A new study by Dartmouth College researchers finds that sanctions on wealth managers would be more effective than asset seizure in crippling Russia's oligarchs. The research uses network science to map the connections between wealthy individuals and their financial experts, revealing a vulnerable network that can be disrupted with targ...
A Berkeley Lab-led team has designed a new type of solid electrolyte consisting of a mix of various metal elements, resulting in a more conductive and less dependent material. The new design could advance solid-state batteries with high energy density and superior safety, potentially overcoming long-standing challenges.
Two new papers demonstrate the use of Outbreak.info as a standardized source for COVID-19 data, tracking daily variant reports and a Research Library with aggregated research publications. The platform provides essential tools for researchers to track virus evolution and improve diagnostics.
Researchers developed a wireless communication system that enables quantum computers to send and receive data using high-speed terahertz waves, reducing power consumption and error-causing heat. The system uses a transceiver chip and tiny mirrors to transmit data wirelessly, making it suitable for large-scale quantum systems.
Researchers used a high-performance computer simulation to study the impact of soil subsidence on permafrost thawing in the Arctic tundra. They found that uneven land subsidence leads to a drier landscape, which limits the process's acceleration through the end of the century.
The Heidelberg Laureate Forum Foundation offers journalist travel grants to cover the 10th HLF from September 24-29, 2023. Recipients of prestigious awards in mathematics and computer science will gather with young researchers for a week of interdisciplinary dialogue.
Researchers and industry leaders from around the world will gather in Sydney to discuss key areas of quantum computing, communications, sensing, training, entrepreneurship, and policy. The three-day event is expected to feature insights on cyber security, sustainability, and commercialization, with over 700 attendees.
Researchers at MIT developed a technique to improve machine-learning models' reliability without requiring additional data or extensive computing resources. The method uses a simpler companion model to estimate uncertainty, enabling more effective uncertainty quantification.
Researchers are exploring how a kind of clay can soak up carbon dioxide and store it, potentially reducing the impact of climate change. The study found that carbon dioxide is more stable in wet clay nanopores than in plain water.
Researchers tested three common techniques to make algorithms fairer and found that one approach didn't reduce social norm bias at all. They proposed a new technique: a formula to directly measure social norm bias in an algorithm so it can be corrected. This bias can persist even after overt discrimination is removed.
The Human Brain Project Summit 2023 will highlight the scientific achievements of the project at the interface of neuroscience and technology. Researchers will present cutting-edge research on European advances in neuroscience and applications in medicine and brain-derived technologies.
Researchers have developed a sophisticated AI algorithm, SPHINKS, that can refine omics datasets and pinpoint protein kinases responsible for tumor growth in glioblastoma. The algorithm has the potential to provide personalized treatments for patients with aggressive brain cancer.
Researchers developed BirdFlow, a predictive model that utilizes eBird data and machine learning to forecast migratory patterns. The model was tested on 11 species of North American birds and found to outperform other models in tracking migration flows.
Dr. Nico Spiller to develop new analysis methods using machine learning to analyze complex brain data related to memory, decision making, and movement. The fellowship aims to provide insights into neurodegenerative diseases such as Alzheimer's and Parkinson's disease.
A new Swedish quantum computer is being made available to the industry, accompanied by a test bed and a quantum helpdesk. The test bed will allow companies and researchers to solve problems using quantum technology at a significantly lower cost than existing commercial options.
Researchers at Brookhaven National Laboratory have successfully discovered new materials using artificial intelligence and self-assembly. The AI-driven technique led to the discovery of three new nanostructures, expanding the scope of self-assembly's applications in microelectronics and catalysis.
A study by NTU Singapore found that mental health chatbots engage users in empathetic conversations and offer support and guidance through psychotherapeutic exercises. The chatbots displayed a 'coach-like' personality, but were not able to deliver personalised advice.
Researchers from Brown and MIT developed a new framework that uses machine learning and sequential sampling to predict rare disasters like earthquakes and pandemics with less data. The framework, called DeepOnet, has been shown to outperform traditional modeling efforts in predicting scenarios, probabilities and timelines of rare events.
Researchers developed a new computer model, quantitative fate mapping, to trace the origin of cells in fully grown organisms. The model helps spot which cells acquire alterations during development that change an organism's fate from healthy to disease states.
USTC scientists made a significant breakthrough in ab initio computing simulation of complex metallic heterostructures with 2.5 million atoms. This achievement is expected to be applied in the construction of 2D-materials-based transistors.
Researchers at Aalto University have developed a new optical computing approach that uses circularly polarized light to operate logic gates, resulting in ultrafast processing speeds. The technology operates about one million times faster than existing technologies and can be integrated into a single device.
Researchers at Johns Hopkins Medicine discovered that regulating the electrical charge on the inner side of the cell membrane can activate pathways responsible for cell movement. This finding has potential implications for understanding cancer cell migration and immune cell function.
A KAUST research team studied the interaction between nitrogen gas and hydrocarbons in oil reservoirs. They found a direct correlation between nitrogen solubility and oil swelling, enhancing oil recovery. The study also sheds light on CO2 storage with impurities like methane and nitrogen.
A team of researchers proposes an intelligent routing scheme to optimize link load balancing in software-defined networks, achieving significant performance improvements. Their algorithms outperform traditional methods, reducing maximum bandwidth by 24.6 percent in real-world topologies.
A team of researchers from the University of Pennsylvania has developed a new algorithm, metadynamics, that can navigate high-dimensional energy landscapes to find low-energy configurations. This breakthrough has the potential to revolutionize fields such as protein folding and machine learning.
A team of quantum engineers at UNSW Sydney has developed a method to reset a quantum computer using a fast digital voltmeter to watch the temperature of an electron, reducing preparation errors from 20% to 1%. This innovation represents a modern twist on Maxwell's demon, a thought experiment that dates back to 1867.
Researchers at MIT have developed a new architecture for optical neural networks, which can perform complex linear algebra operations using light signals. The new design eliminates uncorrectable errors that limited the scalability of earlier systems, enabling larger networks with improved accuracy.
Researchers at the University of Texas at Dallas have developed a computer-based platform for drug discovery using topological data analysis. The approach allows for virtual screening of thousands of compound candidates, narrowing them down to the most promising ones for laboratory and clinical testing.
Researchers have identified over 300 genome regions that contribute to an individual's chemical fingerprint, influencing susceptibility to diseases and response to drugs. The study's findings can help tailor treatment decisions and improve disease outcomes.