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.
Researchers analyzed COVID-19 conspiracy theories on Twitter, finding that some peaked at the beginning of the pandemic while others remained persistent throughout. The study suggests that risk perceptions and lack of information from governments and experts contributed to the persistence of these theories.
A new dataset provides an unprecedented insight into the Arctic Ocean's biological life, revealing a year's worth of microbial communities and their responses to climate change. The EcoOmics dataset aims to guide conservation efforts and provide evidence for novel biology that may influence our understanding of evolution on Earth.
A study found that Italian regions with high levels of environmental pollution have higher cancer mortality rates, even after controlling for lifestyle factors. The analysis identified specific sources of pollution associated with certain types of cancer, highlighting the need for environmental reduction and prevention to combat cancer.
A University of Groningen team created two machine learning models to predict app removal risks, achieving accuracy rates of up to 79.2%. The models can help developers avoid bans and users protect their data.
The Keck School of Medicine's Stevens INI has received a nearly $2 million grant to upgrade its storage system, increasing its capacity to handle vast amounts of brain imaging data. This will enable the lab to maximize scientific productivity and fulfill its promise to collaborate with researchers globally.
A new study by Cornell University researchers found that nearly all market research panel participants are at risk of being de-anonymized due to the presence of quasi-identifiers. The reidentification risk can be up to 94% when considering multiple observations per panelist, highlighting the need for improved data privacy measures.
Researchers aim to create a unified database network for battery data, facilitating AI analysis and predictions. The Battery Data Genome will collect data across the entire battery lifecycle, from discovery to deployment, with uniform standards for metadata.
Researchers developed a tool that encodes patient data as DNA sequences to link health databases accurately. The platform uses BLAST and machine learning algorithms to integrate data from multiple administrative databases, overcoming typographical errors and inconsistencies.
Researchers found that 12% of cancer survivors lived in poverty, experiencing negative effects on physical and mental health. Financial burden of cancer care persists years after diagnosis, leading to poor health outcomes and increased mortality.
Researchers found that a common autism screening test consistently excludes more women than men from research studies, creating a 'leaky pipeline' for diagnosis and treatment. This bias is attributed to the test's origins in male-dominated samples, which may not accurately capture female phenotypes.
Researchers at King Abdullah University of Science & Technology (KAUST) have developed a more robust and realistic general method for dealing with wind-driven phenomena in geostatistical modeling, which promises to greatly improve the accuracy of pollutant dispersion prediction.
Researchers from Children's Hospital of Philadelphia used advanced mapping techniques to identify causal genes and target pairings in the pancreas linked to type 2 diabetes. The study revealed alpha and acinar cells play a greater role in disease development than previously thought.
A new study from North Carolina State University shows that soil temperature can be used to predict the spread of the corn earworm, an important pest affecting various crop species. The research reveals three geographic zones where the pest can overwinter, and models suggest that these zones will shift northward due to climate change.
Rice University's ROBE Array algorithm slashes the size of DLRM memory structures, allowing training on 100 megabytes of memory and a single GPU. The method matches state-of-the-art DLRM training methods with improved inference efficiency.
Thirty-eight Chinese cities have reduced their CO2 emissions for at least five years, while 21 cities have cut emissions due to economic decline or population loss. The study recommends individualized emission targets considering cities' resources and development goals.
Mandated PDMP use in US states reduced opioid prescriptions by 6.1% but led to a 50.1% increase in heroin-related deaths, according to researchers from the University of Texas at Dallas.
Researchers developed a digital health system approach to enhance clinical decision-making for low-back pain sufferers. The system combines self-reported pain measures with precise motion-sensing data, revealing functional improvements only after six months of surgery.
A new Harvard-led study reveals that rising global temperatures caused the explosive evolution of early reptiles, challenging previous explanations. The research suggests climate change triggered morphological changes in reptile groups, including those that gave rise to crocodiles and dinosaurs.
Researchers assembled a large biologging dataset to understand how sharks, rays, and skates use the ocean depths. They found that many species migrate vertically in response to food resources, with some diving to extreme depths.
A new study from North Carolina State University reveals no-till farming boosts agricultural land values in the Midwest, with a 1% increase translating to a $7.86 per acre gain. This finding supports the economic and environmental benefits of adopting soil conservation practices like no-till farming.
A new study found that 'gaps' within DNA protein and sequence alignments can provide valuable information about nucleotide and amino acid substitutions. The finding is particularly relevant for studying distantly related species.
Researchers at Cedars-Sinai created complex computer models of individual brain cells using artificial intelligence. These models capture the electrical signals that neurons fire to communicate with each other, allowing researchers to replicate brain activity at the single-cell level.
Researchers aim to uncover information on blotchy bass syndrome's prevalence, distribution, and potential risks through data collected by citizens. The study will help determine which bass species are susceptible and which seem immune.
The new database offers improved estimations of Potential Evapotranspiration and Aridity Index for the entire world at a high spatial resolution. This allows for a finer description of water needs in different regions, enabling better resource management and land-use planning.
Researchers have centralized over 300 key figures in the Human Impacts Database, providing information on global plastic production, standing livestock population, and sea level rise. The database aims to promote collective quantitative literacy of the Anthropocene.
The new AI system uses associative learning to detect similarities in datasets, reducing processing time and computational cost. By leveraging optical parallel processing and light signals, the system can identify patterns and associations more efficiently than conventional machine learning algorithms.
A new study by researchers at the University of Oxford found that ageing female wild red deer on the Isle of Rum in Scotland tend to adopt a life of solitude as they grow older. They interact with fewer other individuals within their home ranges and shift to less populated areas of their habitat.
A new study uses machine learning models to predict cancer patients' responses to immunotherapy based on their gut microbiome features. The research identifies common gut bacterial taxa associated with responders versus non-responders, providing a potential tool for distinguishing and predicting immunotherapy responders.
A comprehensive global dataset of lakes and reservoirs has been published, offering new information on land and fresh water use. The research provides a better understanding of the impact of changing climate and human actions on global freshwater resources.
Provincial health ministries hold COVID-19 vaccination data but have been reluctant to share it with researchers. Establishing partnerships between provinces and the Health Data Research Network would enable timely data transfer and support research into vaccine effectiveness.
Researchers developed a novel convolutional neural network for facial expression recognition, outperforming conventional models while being computationally less expensive. The new model achieved an accuracy of 72.4% using only 58,000 parameters.
A comprehensive dataset of over 1000 shark-human interactions in Australia helps scientists identify patterns linking environmental, biological, or social factors to shark bites. The database can inform decision-making on mitigation measures, such as wetsuit design and shark deterrent devices.
A University of Washington study found that Pacific salmon in larger groups have lower predation risk, but may trade safety for food. The researchers analyzed historical data on fish catches and predator wounds to estimate group size and predation risk, revealing the benefits and costs of schooling in marine fish.
A new study shows that community science activities can produce high-quality taxonomic data sets, empowering community scientists and supporting biodiversity discovery. Thousands of microscopic liverwort leaves were measured by community scientists over two years, with surprising accuracy.
A newly expanded data set of brain scans from stroke patients called ATLAS now includes 1,271 MRI images with manually segmented lesions, facilitating large-scale stroke recovery research. Researchers hope to develop algorithms to automate lesion segmentation, enabling clinicians to predict patient responses to therapies.
A new study reveals that population declines have been greatest among species that migrate to areas with more human infrastructure, habitat degradation, and climate change. The research identified 16 human-induced threats to migratory birds, including infrastructure associated with bird disturbance and collisions.
Researchers have developed an app to help doctors identify patients with chronic lymphocytic leukemia (CLL) at risk of developing infections, allowing for earlier treatment. The app uses blood test results and genetic data to predict patient risk, improving treatment outcomes and reducing pressure on the healthcare system.
The American College of Cardiology and the American Heart Association have released a comprehensive data standard to standardize definitions for COVID-19-related cardiovascular conditions. This framework will help pool or compare data from various sources to assess its applicability to clinical practice and research endeavors.
A new report highlights the nation's race and ethnicity data shortcomings, recommending federal leadership on standardizing demographic data collection and reporting across critical issue areas. The report aims to help policymakers craft solutions that take into account where resources should be concentrated to address racial disparities.
Feminicide, a worldwide problem resulting in 87,000 intentional killings of women in 2017, has incomplete data due to undercounting and narrow legislation. Researchers using counterdata aim to enact alternative epistemological approaches centering care, memory, and justice.
A massive dataset from Binghamton University tracks public health government responses to COVID-19 at all levels of government worldwide. The dataset provides insights into the effectiveness of different types of government in responding to global crises.
A study by WVU researcher Ednilson Bernardes found that supplier pool pressure contributed to the oversupply of prescription opioids like oxycodone and hydrocodone. The researchers analyzed transactions from 2006-2012, revealing that over 90% of supply came from just three generics manufacturers.
A recent study published in Big Data & Society found that Democrats and Republicans in the US surveyed agree on the mathematical features of COVID-19 graphs, such as line slopes, but differ in their subjective interpretations. The researchers suggest that political affiliations may moderate how people interpret data, highlighting the i...
The INCLUDE Data Hub provides centralized access to large-scale research resources, including biospecimen libraries and clinical datasets, for the study of Down syndrome. With over 8,000 study participants and 30,000 biospecimens, researchers can accelerate discoveries that benefit people with Down syndrome.
The study collected sensor data and conducted surveys to understand the conditions people experience as they move about their daily life. The dataset provided a granular picture of temperature exposure, revealing that participants were well-situated to maintain low temperatures, but still faced dangerously hot environments.
Researchers developed a methodological framework to ensure web data validity in marketing studies. The study provides recommendations for addressing challenges in collecting and using web data via web scraping and APIs.
Researchers at MIT found that explanation methods used to aid human decision-makers in high-stakes situations often have lower accuracy for minoritized subgroups. The fidelity of these explanations varies dramatically between subgroups, with the quality often significantly lower for women and Black people.
A significant overestimation of arterial oxygen saturation by pulse oximetry was found in Asian, Black and Hispanic patients compared to non-Hispanic white patients. This discrepancy led to unrecognized and delayed recognition of COVID-19 treatment eligibility among these groups.
A WHO-supported series has collected 13,700 new database records on mosquito-borne diseases, providing valuable resource for studying and containing infectious diseases. The data can be used to train machine-learning models for vector detection and classification, improving global human health.
A Kyoto University study shows that even though biodiversity increases with more interactions, mean interaction strength decreases. The interaction capacity hypothesis proposes that this weakening of interspecific interactions may be due to increased community diversity.
A new tool called DeepSqueak uses deep learning to identify marine mammal calls with high accuracy, even in noisy environments. The tool was originally developed for rodent ultrasound signals but has been adapted to detect sounds at other frequencies, including humpback whales and delphinids.
A new analysis found that citizen science data from apps like eBird can be a valuable resource for researchers and managers, offering insights into wild bird populations. By comparing publicly-produced data with officially tracked numbers, researchers have identified patterns and potential areas for improvement.
Scientists have developed a machine learning algorithm that can accurately predict the lifetimes of different battery chemistries using as little as a single cycle of experimental data. The technique could reduce costs and accelerate the development of new battery materials, enabling researchers to quickly evaluate and test multiple ma...
A new study published in Animal Behaviour found that newborn African savannah elephants can keep up with their mothers' daily movements, contrary to previous assumptions. This remarkable ability allows the calves to benefit from protection against predators and integration into the herd's social structure.
A new study found that valbenazine, a VMAT2 inhibitor, is safe and effective in treating chorea in patients with Huntington's disease. Chorea is a common symptom of the disease, causing involuntary and irregular movements.
A recent study by the University of Rochester found that mobility patterns can be predicted with surprising accuracy based on data collected from acquaintances, even if individual users turn off their own location tracking. The researchers discovered that up to 95% of an individual's movement pattern can be inferred from people they ar...
A new study by University of Warwick researchers finds that the adoption of cereal crops is the key factor in the emergence of complex hierarchies and states. Contrary to conventional theory, high land productivity does not lead to the development of tax-levying states.
A recent study combining climate data with fossil records of large mammals in Africa found that times of erratic climate change do not lead to major evolutionary changes. The research, published in the Proceedings of the National Academy of Sciences, suggests that environmental variability and species turnover may not be closely related.
Researchers at NYU Tandon School of Engineering propose a paradigm to solve the problem of inferring collective size from individual behaviors. By observing self-propelled Vicsek particles, they show that the time rate of growth of mean square heading is sufficient to predict the number of particles under particular parameters.
A machine learning model has been trained to accurately identify individuals with post-traumatic stress disorder (PTSD) by analyzing text data. The model achieved an 80% accuracy rate in distinguishing between those with and without PTSD. This breakthrough could lead to the development of a cost-effective screening tool for health prof...