Articles tagged with Experimental Data
A new mechanical model simulates how whiskers bend within follicles in response to external forces, shedding light on the process of sensing touch signals. The model suggests an 'S' shaped deformation and predicts how whiskers interact with mechanoreceptors, influencing tactile sensitivity.
A new virtual diagnostic approach uses machine learning to analyze beam quality in electron microscopes, X-ray lasers, and medical accelerators. The method provides accurate information that conventional diagnostics cannot, enabling operators to optimize device performance.
A team of researchers at the University of Illinois replicated hypersonic flow conditions in a NASA Langley Mach 6 wind tunnel using a numerical simulation. The study aimed to better understand the complexities of hypersonic flows, including pressure, temperature, and fluid velocity.
Scientists at Samara Center for Theoretical Materials Science (SCTMS) developed methods to simplify crystal structures, enabling the understanding of material properties. By analyzing simplified structures, researchers can identify patterns and hidden information in original complex structures.
Researchers have developed a method that connects experimental data from synchrotron sources like BESSY II to quantum chemical simulations, reducing computing times for complex molecules. This allows for faster analysis and interpretation of RIXS data, enabling scientists to simulate more complex systems.
The BioAFMviewer software allows for the computational emulation of AFM scanning on any biomolecular structure, generating simulated graphics and movies. This facilitates the comparison of high-resolution structural data with AFM results, aiding in the analysis and interpretation of experimental outcomes.
The University of Göttingen has been awarded a new Collaborative Research Centre (CRC) to analyze experimental data using mathematical modelling and analysis. The CRC will focus on extracting meaningful information from noisy data in various natural sciences fields.
Researchers have proposed a new approach using neural networks and omics data to predict Z-DNA regions in the human genome. DeepZ, a recurrent neural network, achieved higher accuracy than existing algorithms, allowing for the mapping of potential Z-DNA sites across the entire genome.
Berkeley Lab researchers have developed a machine learning model that can design structures with desired optical properties, speeding up the process by at least two to three orders of magnitude. The CUORE experiment has collected a record-breaking dataset for a 'neutrinoless' experiment, surpassing previous experiments by about 10 times.
Researchers developed a new method to distinguish between small earthquakes and low-yield nuclear explosions in the US West. By comparing local magnitude and coda duration magnitude measurements, seismologists can identify seismic events caused by human activity more accurately.
The world's largest informal settlement fire experiment found that fires can spread at an alarming rate, destroying homes in just five minutes. The study, published in Fire Technology, used advanced instrumentation and analysis to simulate the spread of flames through densely-packed settlements.
A new model describes optical properties of high-density plasma, accurately predicting experimental results and outperforming previous models. The generalized Quasi Independent Particle (QUIP) model takes into account plasma microfield inhomogeneity, making it suitable for high-density plasma.
Researchers developed ODiNPred, a machine learning tool using experimental NMR data for hundreds of proteins, to predict regions of rigidity and flexibility. This helps understand the biological role and regulation of intrinsically disordered proteins.
Scientists developed an integrated approach to track energy-transporting ions in ultra-thin materials, potentially leading to faster charging and longer-lasting devices. The study focused on MXenes, a class of two-dimensional materials with promising energy-storing capabilities.
A new study by an international team of researchers found that biodiversity experiment findings are reliable and applicable to the real world. The study analyzed data from two large-scale experiments and compared them with equivalent 'real-world' sites, showing that previous conclusions were supported.
An international team of physicists has analyzed comprehensive data from over a dozen subatomic experiments to investigate right-handed neutrinos. The analysis reveals significant challenges in detecting these particles, but also suggests a possible connection to dark matter.
Researchers at Ben-Gurion University have developed an AI system that can accurately identify the location of malicious drone operators by analyzing their flight paths. The system achieved an accuracy rate of 78% in simulated tests, paving the way for further research and potential real-world applications.
The new FOCI system allows for high-resolution ocean and climate modelling over centuries to millennia, enabling researchers to study natural climate fluctuations and anthropogenic climate change. With its modular design, FOCI can be configured to investigate various research questions and improve the accuracy of model simulations.
The researchers developed a technology called Artificial Chemist, which combines AI and robotics to conduct autonomous R&D and manufacturing of commercially desirable materials. It can identify the best material for any suite of measurable properties in 15 minutes or less.
The article introduces a new theory of detonation-driven hypervelocity shock tunnels, covering three aspects: special features, detonation driver concept, and interface-matching problem. It demonstrates the successful application of this theory in developing large-scale hypersonic test facilities.
Scientists developed a hybrid approach combining machine learning with nano-indentation techniques to improve the accuracy of material testing. The new method predicts samples' yield strength up to 20 times more accurately than existing methods.
Experiments on a simple model for granular cliffs reveal the mechanism by which these cliffs collapse and create large, tsunami-like waves known as impulse waves. The shape of the granular particles and pile height-to-width ratio were found to be critical in determining the types of waves produced.
A new study reveals that biodiversity increases the efficiency of energy use in grasslands by storing more energy, having greater flow of energy and using energy more efficiently across all trophic levels. Ecosystems with higher plant diversity contain twice as much standing biomass compared to monocultures
Researchers from Mainz physicists reveal that the next generation of neutrino experiments may solve the neutrino mass ordering puzzle within three to seven years. The IceCube Upgrade and JUNO collaboration has demonstrated the effectiveness of a complementary experimental approach.
A recent study by Jackson Lu, Richard Nisbett, and Michael Morris found that East Asians are disproportionately underrepresented in US leadership positions due to relatively lower assertiveness. The research suggests that diverse leadership styles are valuable for organizations and highlights the need for recognition of these differences.
Physicists have produced a new value for the proton's radius in an experiment conducted at Thomas Jefferson National Accelerator Facility, measuring 0.831 fm, smaller than previous results and in agreement with recent muonic atomic spectroscopy results. The new method used electron scattering and novel techniques to improve precision.
A VCU-led team, including professors from several institutions and two companies, is developing an open network for molecular sciences data using AI. The goal is to create a platform for combining and analyzing data from academia, industry, and government, enabling scientists to make predictions and designs with more accuracy.
A UTA study finds that consumers rely on price to judge product quality when local identity is important, suggesting marketers can use this understanding to shape price perceptions. The study also recommends using local flavors and ingredients in products for rural areas where local identity is strong.
Researchers developed an AI-powered decision-making system to streamline experiments, reducing measurement time and improving data quality. The algorithm selects the most uncertain step to measure next, maximizing information gain and ending experiments when additional measurements are unnecessary.
A bioengineering group from the University of Pittsburgh developed a methodology to analyze imaging data, using approximate Bayesian computation to derive useful quantitative information for experimental design. They found that tissue properties such as force production and adhesion are more likely to vary with initial tissue size.
The Argonne team applied Bayesian methods to quantify uncertainties in the thermodynamic properties of hafnium, a key component in computer electronics. They found that traditional models often lacked error bars or uncertainties, leading to inaccurate predictions.
Physicists have confirmed the existence of 'fire streaks' in proton-proton collisions, a phenomenon initially proposed as a theoretical structure. The analysis suggests that the matter arising from these collisions behaves similarly to the fire streaks of quark-gluon plasma.
Researchers have designed a new flash-storage system called LightStore that modifies SSDs to connect directly to a data center's network, enabling more efficient data storage operations. In experiments, the system was found to run twice as efficiently as traditional storage servers and required less than half the physical space.
Researchers used an algorithm to model the decision-making of C. elegans in response to a sensory stimulus, achieving predictions that matched experimental results. The Sir Isaac platform demonstrated improved accuracy compared to prior models, offering insights into the potential of artificial intelligence in scientific discovery.
Researchers from HSE and Yandex developed a method to speed up LHC simulation using Generative Adversarial Networks. The approach accurately predicts the behavior of charged elementary particles, enabling faster analysis of experimental data.
Researchers at Argonne National Laboratory and University of Cambridge used supercomputing and machine learning to identify five high-performing organic dye materials for dye-sensitized solar cells. The study demonstrates the full cycle of data-driven materials discovery, from simulation to laboratory testing.
Scientists have recovered accurate values for precession frequencies of Mercury, Venus, Earth, Mars, and Jupiter using lake sediment data from the Late Triassic and Early Jurassic epochs. The findings provide insights into climate variations driven by Solar System chaos and could constrain models of Solar System evolution.
Scientists at Tokyo Institute of Technology developed a new model to predict nuclear fission reaction products, resolving a long-standing mystery. The 4D Langevin equations model successfully accounts for the effects of fragment shapes on fission products and kinetic energy.
Researchers have developed a faster way to acquire 3D endoscopic optical coherence tomography (OCT) images using 40% less data, which could aid in early detection and classification of various diseases. The new method uses computational approaches that create full 3-D images from incomplete data.
Research reveals genes that benefit one sex but harm the other can lead to poorer health in women after menopause. Genes that improve late-life male fitness accumulate even if they harm female fitness.
A new device has been developed to perform high-throughput 3D chemotactic assays, revealing diversity and complexity in the chemotactic regulation of neuronal development by various guidance molecules. The platform uses a hydrogel-based microfluidic system to test hundreds of suspended microscale hydrogel cylinders with distinct gradie...
A Columbia-led team has been awarded $16.75 million from the BRAIN Initiative to study the primary visual cortex, a region crucial for making sense of visual information. The five-year project aims to bridge the gap in knowledge between theoretical and experimental neuroscience.
Riffyn has launched Open Access, offering a full-featured Riffyn SDE account to non-profit members. This provides the capability to transform scientific work, increasing reproducibility and reusability of experiments.
A new study from the University of British Columbia and Princeton University found that intense competition fosters pro-social behavior, including sharing, co-operation, and volunteering. This results in higher levels of contribution to collective pools and reported increases in generalized trust among coworkers.
The automatic tool improves both inter-operator and intra-operator reliability, with a peak force sharper than the sliding hammer. Both tools have high learnability, but the automatic tool is 75% more efficient.
A survey of researchers found that scientists of all career stages are prone to jumping to conclusions when interpreting data, similar to undergraduates. Conducting a 'premortem' before new experiments can help identify potential pitfalls and encourage more thoughtful decision-making.
A team of scientists, including a UC Riverside physicist, has imposed conditions on how dark matter interacts with ordinary matter. The study sets constraints that can aid in detecting the elusive dark matter particle and better understand its fundamental properties.
Researchers analyzed data from the MiniBooNE experiment and found thousands of neutrino-nucleus collisions with the same energy, shedding light on neutrino interactions with matter. The discovery could help solve long-standing problems in experimental design and potentially reveal new physics processes.
A study published in Springer's journal Memory & Cognition found that men tend to take shortcuts and navigate more efficiently than women in known environments. Women, on the other hand, follow learned routes and are more likely to wander, leading to slower navigation times.
The Big Bell Test successfully validated Bell inequalities using a participatory science experiment, where 100,000 people generated random bits via a video game. The results confirm the violation of Bell inequalities, opening new avenues for quantum physics applications.
Researchers at Osaka University have identified a carbon isotope with a magic number of six, demonstrating improved stability and understanding of spin-orbit coupling in atomic nuclei. This breakthrough provides new insights into the origin of spin-orbit force and magic numbers of nuclei.
A new study reveals that the regeneration of phosphatidylinositol 4,5 bisphosphate (PIP2) in the fly eye is not as straightforward as previously thought. The researchers found that PIP2 cycle may be an 'open cycle' where breakdown products are siphoned away to other biochemical pathways.
The GAMBIT Collaboration has developed software tools to analyze data from various experiments and compare them with predictions of new theories. This comprehensive analysis narrows the search areas for 'new physics' and eliminates models whose predictions have not been confirmed.
Researchers at Tohoku University have introduced a novel intermolecular surface force that explains the actomyosin driving mechanism. The discovery sheds new light on muscle contraction, highlighting a previously unexplained aspect of the myosin power stroke model.
Research from NC State University reveals that prenatal BPA exposure at levels below the current FDA safety threshold alters hormone receptor expression, synaptic transmission, and neurodevelopment in the developing rat brain. The study found sex-specific differences in sensitivity to BPA exposure, with females appearing more sensitive.
Researchers used CMS open data to analyze jets produced from proton collisions, revealing a universal feature within subatomic particles. The study demonstrates the scientific value of open access in particle physics and provides a stepping stone for future analysis.
Nobuo Sato received a $10,000 grant to apply his knowledge of Quantum Chromodynamics to understand the protons and neutrons in everyday matter. His calculations involve parton distribution functions and transverse momentum distributions.
Physicists from IFJ PAN developed a simple model to describe the complex process of atomic nucleus collisions. The model predicts that hot matter forms streaks along the direction of impact, moving faster with distance from the collision axis.
Researchers modelled midge swarm cohesion and found that the faster individual midges fly, the stronger gravitational-like force they experience. This speed-dependent force increases with distance from the centre of the swarm.
Scientists simulated the structure of fullerite and single crystal diamond to show how fullerite can become ultrahard. The results suggest that part of the fullerite turns into diamond under pressure, while the other part remains compressed within the diamond, increasing its bulk modulus.