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.
A new study finds that complex and unfamiliar sentences generate stronger responses in the brain's language processing centers. Sentences with higher surprisal and linguistic complexity evoke more activation, while extremely simple or nonsensical sequences elicit little response.
A new tool, CellHint, has been developed to unify different single-cell data, creating harmonized datasets. Researchers applied CellHint to reveal underexplored connections between healthy and diseased lung cell states and identified potential interests for future research in adult human hippocampus.
Researchers at Lancaster University find that the 'r' sound is becoming weaker in England, with most young speakers softening it to an elongation of the vowel. This decline is predicted to continue, potentially erasing traditional dialects and linguistic homogenization.
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 NSF-funded project, MABLE, is developing a digital app using crowdsensing, AI, and robotics to empower individuals with responsive maps and turn-by-turn instructions. The app aims to improve accessibility and navigation for persons with visual or mobility impairments, such as those with low vision and wheelchair users.
The EXPLORE toolkit offers interactive visual analytics and machine learning to analyze galaxy data, identify unusual stars, and visualize the lunar surface. Users can create immersive experiences, including 3D models of the Moon and interactive sky maps.
Researchers have developed an AI algorithm that uses people's flavor impressions to make accurate predictions of individual wine preferences. The algorithm combines data from wine labels, user reviews, and sensory tastings to provide personalized recommendations.
The EUDTO-BioFlow project aims to establish a digital twin of the ocean by making critical marine biodiversity data publicly available. This will enable the simulation and study of 'what if' scenarios for effective conservation and management.
Research reviews 98 articles worldwide, finding suicide rates among men increase during and after economic crises. The study highlights the need for governments to fund health services and social support systems to mitigate mental health impact.
Sydney researchers have identified new structural relationships in complex networks like Twitter and political blogs. A 'source-basin' structure plays a crucial role in organizing the flow of information, with influential nodes serving as sources and densely connected active nodes forming basins.
Researchers have combined 14 studies on piglet gut bacteria to uncover common patterns in microbiome development over time. The analysis revealed predictable trajectories and important details at a fine time scale, with an accuracy of 70% in predicting animal age based on microbiomes.
Researchers developed three diffractive deep neural networks using orbital angular momentum to recognize objects in images, achieving accuracy comparable to wavelength and polarization-based models. The technology has potential for real-time processing applications like image recognition and data-intensive tasks.
Virginia Tech researchers analyzed partisan media sentiment toward AI and found that liberal-leaning media tend to have a more negative tone than conservative media. The study suggests that this opposition can be attributed to concerns over AI amplifying existing social biases, such as racial and income disparities.
Researchers created a large-scale remote sensing annotation dataset to support Earth observation research and monitor global land cover changes. The Globe230k dataset provides new insights into the dynamic monitoring of global land cover, enabling high-level semantic understanding of land use.
Researchers developed DIRFA, an AI-based program that generates realistic videos with facial animations synchronized to spoken audio, showcasing improvements over existing approaches. The tool has potential applications in healthcare, education, and entertainment, enhancing user experiences.
Researchers found that dyadic bicultural competence, the ability to navigate both cultural contexts, is associated with relationship quality. Couples with higher levels of this competence tend to experience fewer relationship challenges.
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.
Researchers found that green spaces alleviate extreme heat's negative impacts on human health, while densely packed buildings increase mortality risk. Urban design strategies incorporating different types of greenery are recommended to mitigate heatwave-associated mortality.
A team of researchers applied an unsupervised data-driven analysis method to multiomics dataset, identifying patterns shared across gene expression, DNA methylation, and genetic variation. The study found that these patterns are associated with various diseases and can be used to predict disease onset.
A Dartmouth-led study found that tweets featuring K-pop group BTS generated 111 times more virality than similar tweets without the artist's name. This highlights the power of entertainment in driving public health messages and bridging cultural divides.
A new task group initiative bridges the gap between biodiversity and omics data standards, enabling sustainable interoperability and collaboration. The effort aims to facilitate data reuse, integration, and knowledge generation in biodiversity research.
Researchers from Imperial College London and the University of Nottingham used machine learning to identify 'atomic shapes' that form basic pieces of geometry in higher dimensions. The findings reveal unexpected patterns in these shapes and demonstrate the potential for machine learning to accelerate mathematical discoveries.
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.
Using data from Mass General Brigham’s electronic health records, researchers found that SARS-CoV-2 accounted for approximately 1 in 6 cases of sepsis during the COVID-19 pandemic. The mortality rate for patients with SARS-CoV-2-associated sepsis was initially high but declined over time.
The Keck School of Medicine of USC has launched a five-year, $50.3 million multi-omics study to better understand the causes and prevention of various diseases, including NAFLD, in underrepresented racial and ethnic groups.
A study analyzed millions of tweets by Republican and Democratic US politicians over a decade, finding that Republicans were more likely to share untrustworthy information. The researchers identified linguistic signals associated with low-quality information and suggested potential solutions for the public to recognize these signals
Researchers analyzed data from 2005-2020 and found that 10-year conditional survival was similar between biventricular and most single-ventricle CHD patients. Biventricular CHD patients also showed better 10-year survival compared to non-CHD heart transplant recipients.
A new study published in Nature Human Behaviour shows that socio-economic factors play a larger role than climate in driving net-migration patterns worldwide. The researchers created a high-resolution dataset of net-migration over the past two decades to inform policy-making and fuel further research.
A study by Brigham researchers reveals a 37% increase in out-of-state residents seeking abortion care in Massachusetts after Dobbs, with an estimated 45 additional abortions. Non-profit funding for out-of-state residents increased by nearly ten percent, while in-state residents' use of funding remained relatively stable.
Researchers created a comprehensive molecular tree of camel spiders, revealing two main groups in the Americas and their relationships. The study also found that camel spiders began evolving around 250-300 million years ago during the Permian period.
A new study examines racial and socioeconomic differences in US preterm birth and mortality rates over 25 years. Despite improvements, disparities persist, with Black infants 1.4 times more likely to die from preterm birth than White and Hispanic infants.
Augusta University researcher Arni S.R. Srinivasa Rao calls for updating the UN's traditional approach to measuring population replacement levels. He proposes a new formula that allows for more timely and accurate measurement, which is essential for understanding emerging global demographics.
A comprehensive study reveals a stagnation in European freshwater biodiversity recovery, highlighting the need for intensified mitigation strategies. The analysis of 1,816 time series of freshwater invertebrate communities between 1968 and 2020 shows promising increases until the 2010s, but a significant slowdown since then.
A new study by the University of Illinois and USDA-Agricultural Research Service has identified the key factors influencing sweet corn yield. The analysis found that seed source is a significant variable, with processors having a choice over which hybrids to use, and high nighttime temperatures also impact yield.
A new R package, lydemapr, has been developed to track the spread of the invasive Spotted Lanternfly in the US. The dataset contains detailed information on the pest's presence, establishment status, and population density across over 650,000 observations.
A new dictionary provides a comprehensive overview of Shakespeare's language, revealing words with reduced mental ability and plant hybrids. The Arden Encyclopedia of Shakespeare's Language offers insights into the linguistic thumbprints of plays and characters, as well as the networks of character interaction.
The University of Missouri is launching a five-year, $3 million doctoral training program to prepare the next generation of scientists and engineers for emerging fields like materials science and data science. The program aims to empower future workers with both technical expertise and data-driven insights.
Researchers from the University of Kansas have created a powerful dataset to facilitate drug development against gram-negative bacteria. The dataset reveals over 270,000 previously unidentified outer-membrane proteins with potential as vaccine targets.
Researchers developed a deep-learning model to assess CXR images for probable COVID-19 severity. The model achieved an area under the receiver operating characteristic curve of 0.78 when predicting intensive care need within 24 hours.
Biased AI can limit climate predictions and misguide governments due to missing information from under-represented communities. Human-in-the-loop design can fill these 'data holes' by offering a sense check on used data and context.
A new study by University of East Anglia reveals ChatGPT's systematic left-wing bias, favoring Democrats in the US and Labour Party in the UK. The platform's responses also lean towards President Lula da Silva of Brazil's Workers' Party.
Research identifies key molecular signatures and pathways contributing to skeletal muscle strength loss in females with estrogen deficiency. The study found parallel patterns of inhibition and activation across various signaling pathways, including AMPK and calcium signaling.
Researchers developed an innovative optical tool, the Schistoscope, to capture microscopy images of urine samples for efficient detection of Schistosoma haematobium eggs. A two-stage diagnostic framework using deep learning accurately identified and counted eggs in field settings with high sensitivity, specificity, and precision.
A team of researchers developed a novel method that leverages temporal characteristics of blood pulse to estimate heart rates with improved accuracy, especially in scenes with ambient light fluctuations. The proposed method showed a 36.5% improvement in estimation accuracy compared to conventional methods.
A Swansea University-led study found that Welsh breastfeeding rates increased during the pandemic, with a significant correlation between mothers' intention to breastfeed and exclusive breastfeeding duration. The study proposes targeted interventions during pregnancy and policies to support families to improve breastfeeding duration.
A sociological study by the University of Zurich confirms that many professionals consider their work to be socially useless. Office jobs were found to be more than twice as likely to feel pointlessness compared to other occupations. The study suggests that factors such as routine work, job autonomy, and management quality also contrib...
Researchers combined linguistics and genetics to propose a new origin theory for the Indo-European languages, suggesting an ultimate homeland south of the Caucasus. The study estimated the family to be approximately 8100 years old, with five main branches split off by around 7000 years ago.
A new study uses machine learning to analyze data from DrugAge, a database of chemical compounds modulating lifespan in model organisms. The researchers create four types of datasets to predict whether or not a compound extends the lifespan of C. elegans, using features such as compound-protein interactions and Gene Ontology terms.
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 new study suggests capping the energy use of the top 20% of consumers could reduce carbon emissions by 11.4%. The strategy would allow those with lower incomes to increase their consumption levels, promoting fairness and delivering climate justice.
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 propose a novel vehicle color recognition method based on Smooth Modulation Neural Network with Multi-Scale Feature Fusion, achieving high accuracy and overcoming class imbalance issues. The proposed method outperforms state-of-the-art VCR methods and meets the requirements for fine classification of vehicle colors.
A recent study by Kyoto University has raised concerns about the authenticity of Big Oil's net-zero emissions claims. The research team found that oil majors are not making sufficient progress in phasing out fossil fuels and transitioning to clean energy, despite their pledges to achieve net-zero by 2050.
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 retrospective analysis of national data found that over 20 million Americans experienced loss of smell or taste after COVID infection, with a large portion never fully recovering these senses. The study estimated that almost 28 million Americans may be left with decreased sense of smell after COVID infection.
Researchers analyzed 692,534 race times to find genetic improvement accounts for 60% of speed increase in short-distance races, while heritability is low across all distances. The study suggests weaker selection or other factors limiting genetic progress, particularly over long distances.
Researchers identified five subtypes of heart failure using machine learning, including early onset and atrial fibrillation related. These subtypes have different mortality risks, with some patients at higher risk of dying within a year after diagnosis.
A team of scientists has developed an automated algorithm to reconstruct the shape of each neuron inside a light microscopy image using deep learning. This breakthrough addresses the challenge of generalizing algorithms across diverse species, brain locations, developmental stages, and microscopy image sets.
A deep learning-based framework called EMGSense enables accurate wearable EMG device usage through AI self-training techniques. It achieves average accuracy of 91.9% in gesture recognition and 81.2% in activity recognition, outperforming state-of-the-art approaches.
Researchers tracked immune cell clusters in the aging mouse prostate using highly multiplexed immune profiling. Early adulthood sees myeloid cells, while between 6-12 months old, there's a profound shift to T and B lymphocyte-dominance. The study reveals new insight into prostatic inflammaging and the window for interventions.