Articles tagged with Experimental Data
Researchers have developed a novel optical neural network architecture that achieves nonlinear optical computation by precisely controlling ultrashort pulse propagation in multimode fibers. This approach streamlines the need for energy-intensive digital processes, achieving comparable accuracy with significantly reduced parameters.
A team from Tokyo Institute of Technology has developed a method to remotely monitor nuclear reactors using antineutrinos. The approach, published in the Journal of Nuclear Science and Technology, could help prevent the manufacturing of materials for nuclear weapons.
Researchers have developed a thermal management technique for photonic packages using glass substrates and thermoelectric vias, enabling precise temperature control. The technology, termed SimTEC, combines through glass vias partially filled with copper and thermoelectric materials to reduce thermal resistance between chips.
The study analyzed 16 years of data from the American Board of Plastic Surgery and found an increased rate of outpatient abdominoplasty without overnight hospital stays. Concomitant liposuction was also more commonly performed in recent years. Despite changes, abdominoplasty remains a safe and reliable procedure.
A recent study using AI to analyze registry data on people's residence, education, income, health, and working conditions can predict life events such as personality and time of death. The model outperforms other advanced neural networks and provides precise answers despite ethical concerns about sensitive data and bias.
A study by Carnegie Mellon University found that using alternative data from smartphones is more effective in improving financial inclusion (23% better) and business profitability (42% better) compared to social media data. This approach can help microloan companies adopt cost-effective solutions and offset potential economic loss.
The study found that 3D integration can lead to significant heat spreading and crosstalk, reducing heater efficiency by up to -43.3% and increasing thermal crosstalk by up to +44.4%. However, optimizing design variables, such as spacing between µbumps and interconnect linewidth, can minimize the thermal penalty of 3D integration.
Researchers at West Virginia University are using artificial intelligence to analyze habanero peppers and develop new methods for predicting genetic traits. The goal is to improve crop yields and prevent genetic diseases, with potential applications in human health.
A team led by Lehigh University's Yahong Rosa Zheng is developing an Autonomous Observatory Node that can collect and transmit data from underwater sensors wirelessly, without the need for expensive subsea cables. The prototype aims to operate at depths of up to 1000 meters, enabling researchers to study extreme environments and detect...
Researchers developed a deep convolutional neural network to pinpoint cardiac catheter tip locations in photoacoustic images, achieving high precision and recall. The approach has the potential to replace fluoroscopy during cardiac interventions, leading to safer procedures.
A new anti-clotting medication, abelacimab, has significantly reduced bleeding among people with atrial fibrillation who are at risk of stroke. The AZALEA-TIMI 71 trial found that abelacimab substantially reduced bleeding compared to the current standard of care use of direct-acting oral anticoagulants.
Researchers at Oak Ridge National Laboratory used quantum biology and artificial intelligence to sharpen the CRISPR Cas9 genome editing tool, improving its efficiency on microbes. The new model revealed key features about nucleotides that enable better guide RNA selection.
A new study found that people's reported media preferences often don't match their actual news consumption, highlighting the need for more accurate measurement. The researchers also discovered that those with divergent media preferences tend to visit similar online news outlets, challenging common assumptions about media polarization.
A new study by the University of Exeter found that increasing human input in AI systems improves citizens' acceptance and perception of fairness. Citizens prefer more accurate and cost-effective systems, with human involvement being a key factor in their acceptance.
A new model predicts the evolution of SARS-CoV-2 variants by analyzing massive data on infections and vaccinations. Human immunity now drives the virus's evolution, with continued surveillance crucial to inform future vaccines.
The development of a new photonic technique enables the precise control of photonic angular momentum, allowing for the efficient recognition and real-time control of total angular momentum modes. The technique, which involves the symmetrical cascading of two units, has been experimentally demonstrated to recognize up to 42 individual T...
Researchers at Argonne National Laboratory have developed an autonomous microscopy technique that uses AI to selectively target points of interest for scanning, speeding up the experimental process and allowing for greater efficiency in facilities with limited beam time. This innovative approach has the potential to accelerate scientif...
Researchers developed a precise historical reconstruction of the Red Sea circulation using fine-grained regional data. The new analysis reveals new characteristics of current circulation, temperature, salinity, and oceanic behavior, improving decision-making for megadevelopments like those in Saudi Arabia.
A recent study published in Journal of Advertising sheds light on the effects of in-stream video advertising on ad information encoding. The research found that mid-roll ads elicit negative emotions but do not affect viewers' purchase intention. In contrast, pre- and post-roll ads have a significant impact on memory formation, highligh...
Scientists at the Max Planck Institute present a method for training artificial intelligence using physical processes, reducing energy consumption and computing time. The new approach relies on non-linear processes, such as optics, to mimic the human brain's parallel processing, potentially leading to more efficient neural networks.
A recent study suggests that higher intake of ultraprocessed foods, particularly those with artificial sweeteners, may be associated with an increased risk of depression. The exact mechanism is unknown, but researchers believe that artificial sweeteners could play a role in the development of depression.
A new approach for coupling different light modes enables unprecedented data transfer rates in an MDM system. By using a gradient-index metamaterial waveguide, researchers achieved a high coupling coefficient and created a 16-channel MDM communication system with a data transfer rate of 2.162 Tbit/s.
A new method can detect drivers' attention levels from their eye movements, enabling the development of more effective takeover signals. The study found that drivers who are engrossed in on-screen activities take longer to respond to warnings, highlighting a potential safety concern.
Researchers at NTU Singapore have developed a method to read data stored in antiferromagnets, allowing for potential energy-efficient and high-speed computing. This breakthrough could lead to the creation of new memory chips with improved performance and capacity.
Scientists at Max-Planck-Institut für Eisenforschung developed a machine learning model that enhances predictive accuracy in alloy design, uncovering new corrosion-resistant compositions. The model combines numerical and textual data, enabling the identification of optimal alloy formulas.
A new AI model, dubbed the 'ChatGPT Chemistry Assistant,' extracts relevant information from scientific papers on MOF syntheses. The tool predicts crystalline states of MOFs based on conditions extracted from texts.
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 new study using MINDWATCH brain-monitoring technology reveals that listening to music and drinking coffee can measurably alter brain arousal, improving performance in working memory tasks. Perfume had a modest positive effect as well.
A new diagnostic method assesses electrical and mechanical activity in the heart during atrial fibrillation, providing personalized assessment of atrial remodeling. This can help predict disease progression and guide treatment.
A recent study revealed that attention plays a crucial role in shaping our conscious experience of the world. Researchers found that manipulating attention can modify an individual's ability to consciously perceive visual stimuli, highlighting the intricate relationship between attention and conscious perception. By using advanced neur...
A new open-source software, NMSM Pipeline, enables clinicians and engineers to create personalized computer models of patient movement to optimize treatment designs. The software uses physics-based models to predict and optimize functional outcomes for patients with various mobility impairments.
A new complex-domain neural network enhances large-scale coherent imaging by exploiting latent coupling information between amplitude and phase components. The technique reduces exposure time and data volume significantly while maintaining high-quality reconstructions.
Researchers have developed a computational tool to compare large datasets and predict immune responses to disease, potentially leading to better vaccines. The new algorithm, designed by La Jolla Institute for Immunology scientists, uses machine learning to identify underlying patterns in immune system data.
A University of Central Florida engineer is leading a $3.3 million ARPA-E funded project to develop simulation software for floating offshore wind turbines. The goal is to improve turbine design and increase their use as a renewable energy source. The software will be licensed or commercialized and can be hosted on a university web page.
Peter Hurck, the 2023 JSA Postdoctoral Prize winner, is conducting data analyses to identify strange particles and learn about their properties. He hopes to improve data analysis methods for these particles using high-quality data from GlueX experiments.
A team of researchers at Texas A&M University is developing a new method for understanding metal behavior under extreme conditions using metal cutting, a traditional manufacturing tool. The process involves shearing or deforming the metal to extreme levels under high rates and can provide fundamental information on material strength an...
A new AI technology has been developed to generate artificial scientific data, allowing for faster and more efficient detection of material features. The AI uses generative adversarial networks to incorporate background noise and experimental imperfections into the generated data, making it virtually indistinguishable from real data.
Researchers from West Virginia University have made a groundbreaking discovery by detecting evidence of low-frequency gravitational waves, which can only be perceived with a detector much larger than the Earth. The signal was detected using pulsar timing arrays and has significant implications for understanding spacetime dynamics.
New measurements from RHIC's STAR detector suggest the shape of small quark-gluon plasma drops is influenced by the substructure of smaller projectile nuclei. This contradicts previous findings from PHENIX detector, which attributed QGP shape to larger-scale positions of nucleons. The results may deepen understanding of properties and ...
A recent study published in Science of the Total Environment found a scarcity of studies on microbial and chemical drinking water contamination in Appalachia and associated health outcomes. Only 85 publications met the criteria, with many gaps remaining to be filled.
A new study by CNIC researchers reveals that low-grade systemic inflammation triggered by subclinical atherosclerosis accelerates epigenetic aging in otherwise healthy young individuals. The study found a strong association between atherosclerosis progression and accelerated biological age, with potential reversibility through lifestyl...
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 publication by the PHENIX Collaboration at RHIC's Relativistic Heavy Ion Collider provides definitive evidence that gluon spins are aligned in the same direction as the spin of the proton they're in. This result, known as the 'golden measurement,' allows theorists to calculate how much gluons contribute to a proton's spin.
Researchers ran survey experiments to assess the effectiveness of microtargeting in politics, finding that targeted ads can be 70% more persuasive than general campaigns. However, using multiple attributes for targeting did not add further benefit, suggesting a 'one ad does not fit all' approach.
A University of Essex-led study found that fast-oscillating brain waves linked to brief pain and touch differ widely in scans, with individual patterns stable across time. The research challenges previous findings on the relationship between pain and gamma oscillations.
Researchers found female babies with CDH have a 32% higher risk of dying within 30 to 60 days of birth compared to males. The study, using medical records from an international registry, suggests that lower birth weights for females may be linked to the disparity in survival rates.
Researchers discuss how AI can adapt and reinvent social science research practices to harness the power of large language models. The study explores novel opportunities for testing theories and hypotheses about human behavior at great scale and speed.
The latest DESI data release provides a precise 3D map of the universe with high certainty. The data also sheds new light on cosmic acceleration and the nature of gravity at large scales.
A decade-long study reveals that warmer temperatures lead to significant loss of organic compounds in deep forest soils, affecting carbon sequestration. This finding has implications for natural carbon sinks and soil management practices.
Researchers developed a new spectropolarimetric imaging technique called DIP-SP, which integrates a passive polarization modulator into an imaging spectrometer. This approach enables high-dimensional information capture from incomplete measurements and significantly improves image quality.
The MOLLER experiment has been granted Critical Decision-3A, allowing it to begin procurement of key components and make a precise measurement of the electron's weak charge, which will compare to the Standard Model's prediction.
Researchers used large language models to generate open-ended answers, which were often more convincing than real responses. This approach may help gather data quickly and at low cost but also raises concerns about the authenticity of online user data.
The CHEP2023 conference will address computing, networking, and software issues for leading data-intensive science experiments. Key trends and solutions in computing as it applies to research in nuclear and high energy physics will be discussed.
A mobile application utilizing Python and a single-element ultrasound transducer has been developed for photoacoustic tomography (PAT) image reconstruction. The application successfully reconstructs high-quality images with signal-to-noise ratio values above 30 decibels, making it suitable for point-of-care diagnosis in low-resource se...
A recent study by Sara Valentini and colleagues at Bocconi University found that consistency between online content and the values associated with a brand increases rebroadcasting frequency. Posts containing price promotions also perform well when aligned with the brand's identity, with followers being 109% more likely to share them.
Researchers have made the first-ever observations of how lambda particles, a form of strange matter, are produced by a specific process called semi-inclusive deep inelastic scattering (SIDIS). The study reveals that diquarks, pairs of quarks and gluons, can march through atomic nuclei, contributing to the formation of lambdas.
Researchers analyzed 2,571 patients treated with monoclonal antibodies and found a 39% reduced risk of hospitalization or death compared to non-treated peers. The study also showed greater benefit in patients with immunocompromising conditions and those treated earlier during the pandemic.
The UTSA ScooterLab will collect data on riders' mobility, context and environment to improve sustainable transportation solutions. The project aims to transform the way we think about micro-mobility.
The ExPaNDS project is holding four topic-based webinars showcasing how efficient management of data can increase its value through sharing and reuse. The webinars cover Life Sciences, Cultural Heritage Science, Tomography/Imaging, and Industry topics.
Astronomers have cataloged over 51,863 Lyman-alpha-emitting galaxies, 123,891 star-forming galaxies, and 4,976 active galactic nuclei using HETDEX's spectroscopic data. The survey is a non-targeted, moon-sized survey that collects spectra from 35,000 fiber optic cables, providing a unique dataset for future galaxy mapping.