Articles tagged with Data Sets
Comprehensive exploration of living organisms, biological systems, and life processes across all scales from molecules to ecosystems. Encompasses cutting-edge research in biology, genetics, molecular biology, ecology, biochemistry, microbiology, botany, zoology, evolutionary biology, genomics, and biotechnology. Investigates cellular mechanisms, organism development, genetic inheritance, biodiversity conservation, metabolic processes, protein synthesis, DNA sequencing, CRISPR gene editing, stem cell research, and the fundamental principles governing all forms of life on Earth.
Comprehensive medical research, clinical studies, and healthcare sciences focused on disease prevention, diagnosis, and treatment. Encompasses clinical medicine, public health, pharmacology, epidemiology, medical specialties, disease mechanisms, therapeutic interventions, healthcare innovation, precision medicine, telemedicine, medical devices, drug development, clinical trials, patient care, mental health, nutrition science, health policy, and the application of medical science to improve human health, wellbeing, and quality of life across diverse populations.
Comprehensive investigation of human society, behavior, relationships, and social structures through systematic research and analysis. Encompasses psychology, sociology, anthropology, economics, political science, linguistics, education, demography, communications, and social research methodologies. Examines human cognition, social interactions, cultural phenomena, economic systems, political institutions, language and communication, educational processes, population dynamics, and the complex social, cultural, economic, and political forces shaping human societies, communities, and civilizations throughout history and across the contemporary world.
Fundamental study of the non-living natural world, matter, energy, and physical phenomena governing the universe. Encompasses physics, chemistry, earth sciences, atmospheric sciences, oceanography, materials science, and the investigation of physical laws, chemical reactions, geological processes, climate systems, and planetary dynamics. Explores everything from subatomic particles and quantum mechanics to planetary systems and cosmic phenomena, including energy transformations, molecular interactions, elemental properties, weather patterns, tectonic activity, and the fundamental forces and principles underlying the physical nature of reality.
Practical application of scientific knowledge and engineering principles to solve real-world problems and develop innovative technologies. Encompasses all engineering disciplines, technology development, computer science, artificial intelligence, environmental sciences, agriculture, materials applications, energy systems, and industrial innovation. Bridges theoretical research with tangible solutions for infrastructure, manufacturing, computing, communications, transportation, construction, sustainable development, and emerging technologies that advance human capabilities, improve quality of life, and address societal challenges through scientific innovation and technological progress.
Study of the practice, culture, infrastructure, and social dimensions of science itself. Addresses how science is conducted, organized, communicated, and integrated into society. Encompasses research funding mechanisms, scientific publishing systems, peer review processes, academic ethics, science policy, research institutions, scientific collaboration networks, science education, career development, research programs, scientific methods, science communication, and the sociology of scientific discovery. Examines the human, institutional, and cultural aspects of scientific enterprise, knowledge production, and the translation of research into societal benefit.
Comprehensive study of the universe beyond Earth, encompassing celestial objects, cosmic phenomena, and space exploration. Includes astronomy, astrophysics, planetary science, cosmology, space physics, astrobiology, and space technology. Investigates stars, galaxies, planets, moons, asteroids, comets, black holes, nebulae, exoplanets, dark matter, dark energy, cosmic microwave background, stellar evolution, planetary formation, space weather, solar system dynamics, the search for extraterrestrial life, and humanity's efforts to explore, understand, and unlock the mysteries of the cosmos through observation, theory, and space missions.
Comprehensive examination of tools, techniques, methodologies, and approaches used across scientific disciplines to conduct research, collect data, and analyze results. Encompasses experimental procedures, analytical methods, measurement techniques, instrumentation, imaging technologies, spectroscopic methods, laboratory protocols, observational studies, statistical analysis, computational methods, data visualization, quality control, and methodological innovations. Addresses the practical techniques and theoretical frameworks enabling scientists to investigate phenomena, test hypotheses, gather evidence, ensure reproducibility, and generate reliable knowledge through systematic, rigorous investigation across all areas of scientific inquiry.
Study of abstract structures, patterns, quantities, relationships, and logical reasoning through pure and applied mathematical disciplines. Encompasses algebra, calculus, geometry, topology, number theory, analysis, discrete mathematics, mathematical logic, set theory, probability, statistics, and computational mathematics. Investigates mathematical structures, theorems, proofs, algorithms, functions, equations, and the rigorous logical frameworks underlying quantitative reasoning. Provides the foundational language and tools for all scientific fields, enabling precise description of natural phenomena, modeling of complex systems, and the development of technologies across physics, engineering, computer science, economics, and all quantitative sciences.
Regional disparities exist in responses of secondary pollutants to emission reductions, especially fine particulate matter and ozone. Ozone shows rising signals in most areas, but declining signal exists in North America despite reduced nitrogen oxides.
A new study found that the revised concussion guidelines led to a significant reduction in symptom duration among young athletes. The adoption of active rest, recognizing pre-existing conditions, and educating athletes about recovery improved outcomes, with male athletes experiencing a median duration drop from 11 to 5 days and female ...
A newly merged global surface temperature dataset, including reconstructed land and marine measurements, reveals a consistent increased warming trend compared to previous estimations. The study provides evidence that the globe has warmed at a significantly faster rate than previously thought, with improved coverage of the Earth's surface.
Researchers used 'Neuropixels' probes to capture electrical signals from hundreds of neurons, revealing how visual information flows across the brain. The study found a hierarchy of neural activity, with lower areas representing simpler concepts and higher levels capturing complex ideas.
Computational materials scientists at Ames Laboratory have created an algorithm that uses a hybrid approach inspired by cuckoo birds' nesting habits to find novel high-entropy alloys. The new method significantly reduces the search time for these materials, which are highly sought after for their unique properties and applications.
Researchers at UCLA have developed Diffractive Deep Neural Networks (D2NNs) for all-optical object classification, achieving higher accuracy than individual constituent D2NNs and digital AI models. The success of the ensemble learning approach demonstrates the power of combining multiple predictions to obtain a more accurate prediction.
A new study by Dr Andrea Baronchelli and colleagues reveals a connection between cryptocurrency coding and market behavior. The researchers found that 4% of developers contribute to the code of two or more cryptocurrencies, questioning the transparency surrounding the coding process.
A team of researchers has found evidence that UV radiation from sunlight significantly affects COVID-19 transmission. By analyzing daily COVID-19 cases and environmental conditions, they discovered a correlation between UV exposure and the growth rate of new cases.
Researchers provide a 4D image of an active linkage zone between two major faults, offering insights into fault behavior and implications for seismic hazard assessment. The study highlights the importance of reevaluating 'silent' seismogenic sources in assessing earthquake risk.
A comprehensive study reveals that Germany's plant diversity has been declining steadily over the past decade, affecting both archaeophytes and neophytes. The decline in species diversity averages around two percent per decade, with many common species being affected.
A Purdue University research team uncovered flaws in a prominent dataset used to study brain activity and decode visual perception. The findings challenge previous conclusions on the possibility of reading minds through electric brain signals.
A new method, nnU-Net, has been developed to configure self-learning algorithms for a large number of different imaging datasets, enabling the interpretation of three-dimensional imaging data and distinguishing between tumor and non-tumor tissue.
An international team of researchers has connected specific genetic signals with specific areas of the face, identifying 203 genomic regions that play a role in human facial development. The study sheds light on craniofacial malformations such as cleft lip and palate, as well as evolutionary differences between various populations.
The Leipzig Catalogue of Vascular Plants (LCVP) is the largest and most comprehensive list of scientific names for all known plant species. With over 1.3 million entries, it vastly expands global knowledge of plant diversity and provides a reliable reference for researchers worldwide.
Researchers analyzed a massive dataset of seasonal events across the former Soviet Union and found that species' activities fail to keep up with their cues due to past evolution. Local adaptation patterns result in a massive imprint on nature's calendar, making geographic variation in seasonal timing more pronounced in spring and less ...
A new paper offers a framework for studying online hate and counter speech, analyzing millions of Twitter interactions. Researchers found that organized movements are more effective than individuals in countering hate speech.
A new USC study reveals that AI models lack common sense to generate plausible sentences, despite advances in natural language processing. The research challenges the effectiveness of current benchmark tests and finds that even the strongest models can make silly mistakes.
A new disaster database, DesignSafe, is changing how planners prepare for and respond to natural disasters. The database features over 293 published data sets, including insights on earthquake impact, hurricane damage, and more.
Georgia State University researchers have developed a software tool called COINSTAC, which allows for local data analysis and sharing of results, protecting patient privacy and anonymity. The platform is designed to be compatible with deep learning models, enabling the training of analyses on decentralized databases.
Researchers developed a new method to optimize materials exhibiting metal-insulator transitions (MIT) using Bayesian optimization and latent-variable Gaussian processes. The approach identified 12 previously unidentified MIT materials with optimal functionality and synthesizability.
Researchers establish objective standards for defining and identifying binary tropical cyclones (BTCs), which can bring extreme precipitation and cause serious disasters. The study analyzed two best-track datasets and provides a main standard for defining BTCs, based on separation distance and coexistence time.
A new open-source dataset has been created to provide county-level exposure numbers for tropical cyclones and human health. This tool will enable scientists to analyze multiple storms in different places and time periods, drilling down to see what happens in different health outcomes for people.
For the first time, astronomers have surveyed over 250 million stars in the Milky Way's bulge, measuring their chemical composition and gaining new insights into the galaxy's formation. The data will help scientists understand how the Milky Way formed its central bulge and gain a better understanding of other galaxies.
Recent research shows that chimpanzees, like humans, increasingly prioritize mutual and equitable friendships with others as they get older. Younger adults tend to form lopsided relationships, while older chimpanzees focus on maintaining smaller, fulfilling networks of close friends.
A new data set provides high-resolution daily temperatures from around the globe to study human health impacts from heat waves, risks to agriculture, droughts, and food insecurity. The CHIRTS-daily dataset offers accurate estimates of air temperatures for 1983-2016, supporting efforts to monitor, understand, and mitigate climate hazards.
Researchers have developed machine learning algorithms to predict which RNA-based toehold switches function well, enabling the identification and optimization of these tools. The algorithms analyzed a massive dataset of over 100,000 toehold switch sequences and predicted their behavior with high accuracy.
A novel method for automated pollen analysis has been developed by combining imaging flow cytometry with deep learning, allowing for accurate species identification and quantitative findings in just 20 minutes. The new tool was tested on 35 plant species and achieved an accuracy rate of 96%, outperforming traditional microscopy methods.
Researchers at Princeton University developed a tool to uncover potential biases in visual data sets, such as stereotypical images and underrepresentation. The tool, REVISE, uses statistical methods to inspect data sets for object-based, gender-based, and geography-based biases.
A global study maps areas with high carbon returns from natural forest regrowth, highlighting climate's role in carbon storage. Climate change mitigation strategy: restoring degraded woody vegetation could store substantial amounts of CO2.
Researchers at Mount Sinai Hospital developed a COVID-19 mortality prediction model based on patient's age, minimum oxygen saturation, and type of encounter. The model showed high accuracy (AUC=0·91) in predicting mortality among patients with COVID-19, offering potential for improved prognostication and management.
Regional differences in Russia's alcohol consumption patterns reveal a complex relationship between government measures and unlicensed alcohol sales. Studies have shown that regions with stricter policies exhibit reduced registered alcohol consumption, but unregistered alcohol remains a significant issue.
Researchers developed a machine learning model that analyzes molecular structure to predict enthalpy of formation with better accuracy than traditional approaches. The model's accuracy improves with more data, enabling the development of fully automated algorithms for predicting complex chemical phenomena.
A machine learning study conducted at Princeton University found that the meaning of words is shaped by culture, history, and geography. The researchers analyzed over 1,000 words in 41 languages and discovered that many everyday words have varying meanings across cultures.
Carnegie Mellon researchers create large dataset capturing interaction between sound, action, and vision to improve robotic perception. The study found that sounds can help robots differentiate between objects and predict physical properties of new objects.
A new study published in the Journal of Transport and Health found that walking to work can significantly improve a person's self-rated health compared to casual strolls. People who walked primarily for utilitarian purposes, such as commuting to work, reported better health than those who walked mostly for leisure.
A new study by Cornell researchers uses machine learning to assess the effectiveness of mathematical tools in predicting financial markets. The model can also predict future market movements, a task considered extraordinarily difficult due to markets' massive amounts of information and high volatility.
A new study from Stanford University's Immigration Policy Lab found that many refugees in the US move to different states soon after arrival, primarily seeking better job markets and social networks. Refugees are more likely to leave high-unemployment states and join those with booming economies.
Experts have developed a platform for self-testing AI medical services, allowing for automated validation and improvement. The platform provides an opportunity to fine-tune algorithms with unlimited access to data instances, minimizing human factor manipulation.
A new study by scientists at the University of Cambridge's Autism Research Centre found that transgender and gender-diverse adults are three to six times more likely to be diagnosed as autistic. The research used data from over 600,000 adult individuals and confirmed previous smaller scale studies.
Researchers at Texas A&M University are using advanced machine-learning analysis to reveal the evolution of cracks in rock and concrete. By combining data from multiple sources, including sound waves, electromagnetics, and pressure measurements, they aim to improve our understanding of crack damage and development.
Researchers developed a computational tool called PolyA-miner to analyze alternative polyadenylation (APA) sites in RNA strands. The tool precisely identifies novel APA sites that were not detected by traditional analytical approaches, revealing new insights into gene regulation.
Tong and collaborators are developing a model-ready emission dataset for CAM-CMAQ's wildfire forecasting system, aiming to improve accuracy and mitigate adverse fire effects. The dataset will also incorporate aerosol attenuation of photolysis in smoke plumes.
A team of researchers has quantified human activity across Antarctica, revealing that almost every area has been visited. Biodiversity is not well-represented within these areas, highlighting the need for swift action to declare new protected areas.
A major loss of grassland has occurred in Great Britain since 1990, with a net reduction of 7,668 km2 or 1.9 million acres, as woodland area increased by 5,236 km2 and urban areas expanded by 3,376 km2 between 1990 and 2015. The majority of this loss and increase occurred in Scotland and England respectively.
Researchers from Caltech and institutions like Northwestern University used deep learning and supercomputing to identify Nyx, a product of a long-ago galaxy merger. The discovery provides the first indication that a dwarf galaxy merged with the Milky Way disk.
Researchers at Cornell University used AI to investigate how reflection changes images, discovering clues like facial features and beards that can differentiate originals from reflections. The study has implications for training machine learning models and detecting faked images.
A team of researchers at Carnegie Mellon University has developed an automated method for making communications more polite, using a large dataset of labeled sentences. The system can restructure nonpolite directives or add words to make them more well-mannered, while maintaining the original meaning.
Researchers developed a new set of computational tools to identify cell-type specific methylation patterns, known as molecular barcodes, in complex cell mixtures. These new methods can distinguish between different cell types in tissues made up of multiple cell types.
A large-scale database of ground reaction force data from over 2,000 patients has been made publicly available for research purposes. The GAITREC database includes information on patients with joint transplants, fractures, and ligament injuries, providing a valuable resource for clinicians and researchers.
A team has devised deep-learning and other computational approaches that dramatically reduce image-analysis time by orders of magnitude. They report their results in Nature Biotechnology, accelerating image analysis in three major ways: deconvolution, 3D registration, and complex deconvolution.
By extending available data, researchers developed a method to estimate mass concentrations of particulate matter from humidity and visibility measurements. This approach has the potential to provide broader understanding of how particulate matter evolves and improve visibility in daily life.
Researchers have created a new map revealing the Earth's mantle at a depth of 3,000 kilometers by analyzing thousands of seismic waves collected over 30 years. The map shows hot and dense regions below Hawaii and French Polynesia.
A multivariate analysis of sea level data reveals that barystatic and steric contributions drive most interannual variability in GMSL, with ENSO playing a significant role. The study highlights the magnitude of these contributions associated with ENSO events.
Researchers at King Abdullah University of Science & Technology devised a new analytical tool to predict flood risk by adapting a classical statistical model for analyzing extreme rainfall in large datasets. The model demonstrated potential in capturing observed patterns in northeast America, promising improved prediction capabilities.
Using air conditioners increases electricity bills on average by 42%, particularly affecting poorer households. Climate change amplifies this impact, especially in Europe and North America.
The gnomAD Consortium has published its first major studies of human genetic variation, revealing new insights into rare types of genetic variation. The research provides better tools for clinical geneticists to diagnose patients with rare genetic diseases and evaluate proposed drug targets.
A new methodology for assessing the credibility of historical global land use/cover datasets has been proposed, addressing temporal and spatial changes. The approach evaluates accuracy, rationality, and likelihood assessments through five case studies, providing a framework for improving data quality.
A study found significant gender imbalance in medical imaging datasets used to train classifiers, leading to biased AI-based diagnostic systems. The analysis showed that underrepresented groups were misclassified more frequently than the majority group.
A new soil moisture product has been developed for mainland China, utilizing a dual-pass data assimilation system that auto-calibrates model parameters. The product provides gridded soil moisture data with a spatial resolution of 0.25° over China, showing consistent patterns with precipitation and evaporation.
A Tel Aviv University-led study published in Nature found that complexity in analytical methods contributes to variability in research outcomes. Researchers analyzed the same dataset using different analysis methods, resulting in varying conclusions. The study highlights the need for improved methodology and data sharing to advance sci...