Articles tagged with Data Samples
The world's first open-access battery imaging library has been launched, offering over 4.5 terabytes of experimental data for researchers to advance battery research and AI-driven image analysis. The library provides a wide range of imaging modalities and data types, enabling scientists to get the full picture required for their analysis.
A recent study analyzing 5.8 billion medicines dispensed in England from 2019 to 2024 found significant health disparities, with nearly twice as many medicines prescribed to the most deprived groups as those in the least deprived groups by age 40.
Researchers examined how practice-based research and learning networks approach data governance, identifying the importance of building knowledge of Indigenous data sovereignty. Existing Indigenous governance frameworks provide guidance on incorporating Indigenous data sovereignty principles into PBRLNs.
A global analysis of over 2,300 seawater samples reveals human-made chemicals make up a significant portion of organic matter in coastal oceans. Industrial chemicals, including plastics and consumer products, dominate the anthropogenic chemical signal, persisting even 20 kilometers offshore.
Singapore's breast cancer incidence is rising, but mortality rates are falling, mirroring global trends. The country's strong healthcare system and high-screening participation have contributed to improved survival rates.
Researchers used machine learning to identify conflict labels from data, discovering three archetypes with distinct geographic, demographic, and economic properties. The study emphasizes the limitations of existing conflict classifications and suggests new approaches for predicting conflict severity.
A study by Bielefeld University used anonymized WhatsApp metadata to show that personalized feedback can help people understand their communication habits. Many participants adjusted their views on response speed and chat participation after seeing data-based visualizations.
Researchers have launched a new multimodal medical dataset, Observer, capturing anonymized, real-time interactions between patients and clinicians. The dataset links video, audio, transcripts, and electronic health records to study subtleties like body language and environmental factors affecting care.
The SECURED project aims to provide a secure environment for decentralized, cooperative processing of health data and anonymisation assessment. The consortium is developing AI models to diagnose and treat patients with blood malignancies in a secure way, ensuring patient data protection and compliance with European privacy regulations.
A team of researchers from Binghamton University has created the first-ever high-resolution 3D model of Rano Raraku quarry, revealing over 1,000 moai statues. The model allows users to zoom in and pan across various features, providing a detailed look at the island's quarries and challenging previous theories about its history.
The Global Pathogen Analysis Platform (GPAP) will enable low- and middle-income countries to conduct research and surveillance of infectious diseases independently. The platform aims to prevent disease outbreaks from developing into pandemics by detecting genetic sequences of potential pathogens.
Researchers developed a new method to address the 'anticlustering' problem in medical data analysis, which distorts results due to batch effects. This method enables accurate research on endometriosis by minimizing batch effects and ensuring robust experimental design.
A recent study published in JAMA Otolaryngology–Head & Neck Surgery found an association between cannabis use disorder and benign salivary gland tumors. The researchers call for further prospective research to confirm this association and understand the relationship between cannabis use and these tumors.
Gene coexpression analysis reveals optimal markers of cell types and states, providing opportunities for developing novel biomarkers and targeted treatment strategies for glioma patients. Dr. Oldham's work tackles the reproducibility crisis in science, emphasizing data metadata standardization.
Researchers investigated the efficiency of modern neural network-based generative models, comparing them to traditional sampling techniques. The study found that modern diffusion-based methods may face challenges due to a first-order phase transition, but also exhibit superior efficiency in certain cases.
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.
The study found a steady increase in diagnosed learning disability prevalence among US children and adolescents over two decades, with 8.83% of children ages 6-17 affected between 1997 and 2021. This chronic condition affects about 9 in 100 overall, highlighting its significant impact on the US population.
Researchers from Baylor University studied cortisol levels in leopard seals and found significant variations based on sex, diet, and body mass. The study provides crucial baseline data on this enigmatic Antarctic species.
The project aims to collect core samples and temperature data down to 15,000 feet to test the potential of geothermal energy in the region. Data will also be gathered on underground carbon storage in the Appalachian basin, a scientific first in the state.
A study found that high-quality labeling of images boosts perceptions of training data credibility, leading to increased trust in AI systems. However, biases in the data can reduce trust in certain aspects.
A study published in Lancet Diabetes & Endocrinology found that the incidence of type 1 diabetes among Finnish children increased by 16% during the pandemic. Researchers believe that social isolation and lockdowns rather than SARS-CoV-2 infection may have contributed to this increase.
The European Platform for Neurodegenerative Diseases has launched its Cohort Catalogue, featuring an extensive list of international cohorts across the neurodegeneration disease spectrum. Researchers can search and filter cohorts by metadata characteristics to discover relevant studies and initiate new collaborations.
Researchers identified 7 key symptoms of long COVID, including heart issues and joint pain, in a study of 52,461 patients. The findings could help healthcare providers diagnose and treat the condition more effectively.
Researchers at Kyoto University have found that the Tohoku earthquake may have occurred upon a complete stress release, with data suggesting normal faults in both sedimentary formations above and below the plate boundary fault. This discovery provides insights into how fault slipping contributed to the devastating tsunami.
A new study urges regulators to take a closer look at the health and safety risks of the growing medicinal and recreational cannabis market. The research team found that many pesticides in cannabis cultivation were highly unlikely to be used, but still detected, highlighting the need for stricter regulations.
Researchers from the Institute of Atmospheric Physics develop a correction method for Nansen cast temperature profiles, addressing a depth bias affecting global ocean warming assessments. The new approach has significant implications for understanding ocean warming rates and achieving better climate understanding.
Researchers developed a mobile phone app using AI to accurately detect COVID-19 infection in people's voices, outperforming lateral flow tests. The app achieved an accuracy of 89% and can be used for remote testing, enabling rapid screening of populations.
A new study suggests that members of the public want to know if their health information or samples from their bodies will be used in research or to help develop new biomedical products. The study found that patients are more likely to want notification about research use of their health information than biospecimens.
A study by West Virginia University found that over 7% of junior high and high school students in rural Appalachia identified as gender-diverse, including nonbinary or transgender identities. This exceeds previous estimates and highlights the need for support services in these areas.
CoVaRR-Net is investing $6.9 million in 15 research projects focused on understanding Omicron subvariants and finding solutions to curb their spread. The studies will explore various aspects of variants, including viral transmission between animals and people, new variant mutations, and the impact of social factors on Indigenous Peoples.
A novel single-cell RNA sequencing technique, TAS-Seq, has been developed to provide higher-precision data than current methods. The new method detects more genes and identifies highly variable genes, making it a sensitive high-throughput scRNA method.
A new study published in Microbiology Spectrum found that nasopharyngeal swabs were the most effective method for detecting COVID-19, with detection rates ranging from 92 to 100%. Saliva and anterior nares tests had lower detection rates, particularly in asymptomatic patients.
Researchers developed a system to estimate the probability of a majority response being wrong, eliminating unnecessary task assignments and increasing efficiency in crowdsourcing projects. This method can be applied to various binary classification tasks, reducing labor and improving accuracy.
A new screening tool has been developed to identify pregnant women at risk of eating disorders, allowing for early intervention and treatment. The Prenatal Eating Behaviors Screening (PEBS) tool, created by WVU researchers, uses a 12-question screener to assess symptoms and emotions associated with eating disorders.
Researchers have trained sniffer dogs to detect SARS-CoV-2 in airport passengers with high accuracy, comparable to PCR swab tests. The dogs' performance was found to be robust across various scenarios, including low prevalence populations, suggesting their potential for widespread use in screening.
Researchers developed an AI system using swarm learning to predict cancer from medical images of tissue samples without accessing patient data. The technique improved the detection of genetic changes in colon tumors with high accuracy.
A team of researchers has made a large collection of coffee samples' NMR data freely available to assess the variety under which coffee is sold. The dataset can be interactively explored using software called NMRium-browser, allowing users to visualize the molecular structure of coffee beans from different origins.
A recent study published in mBio discovered that the SARS-CoV-2 viral gene ORF8 plays a crucial role in the severity and spread of COVID-19. Researchers found that mutations in ORF8 contribute to inflammation and disease outcomes, suggesting new treatment options for patients with severe cases.
Researchers develop a new method to reconstruct the states of complex nonlinear systems based on time series data. The approach optimizes reconstruction parameters by focusing on the geometric structure of attractors, resulting in improved accuracy.
A crowdsourcing campaign has compiled data on the drivers of tropical forest loss between 2008 and 2019, resulting in a high-resolution dataset. The analysis found that agriculture expansion, road construction, and wood extraction are major contributors to deforestation.
A National Jewish Health-led study found that over a third of identified genetic risk factors for asthma are associated with altered function of airway epithelium. The research discovered genetic changes in genes related to mucus production and type 2 inflammatory pathways, increasing asthma risk.
Researchers from University of Toronto, MIT, and University of British Columbia published a new paper on quasi-experimental methods in marketing. The study describes the underlying logic and actions that make this method convincing, highlighting its use in explaining changes in consumer behavior, firm behavior, and market-level outcome...
A new cloud-based data resource has been developed to help identify new subtypes of amyotrophic lateral sclerosis (ALS), a fatal neurological disorder. The tool, part of the Answer ALS collaborative effort, uses biological and clinical data from over 1,000 patients to better understand the disease.
A new study published in Clinical Nutrition found that drinking less than the UK's recommended 14 units of alcohol per week increases the risk of cardiovascular events. Moderate alcohol consumption is associated with a 23% increased risk of suffering a cardiovascular event for every additional 1.5 pints of beer consumed.
A Rutgers study found measurable airborne SARS-CoV-2 RNA in the air of most homes where COVID-19 infected individuals were isolating, suggesting airborne transmission beyond isolation rooms poses a risk to other occupants. The study also showed that infected individuals often did not strictly adhere to self-isolation protocols.
The Nutrition for Precision Health study will use data from 10,000 participants to develop algorithms predicting individual responses to food and dietary routines. The goal is to create more personalized nutrition recommendations and reduce health disparities.
A longitudinal survey of over 3,000 adolescents aged 11-14 found that supportive relationships with family and friends, physical activity, and better sleep helped shield against the pandemic's negative impact on mental health. Girls were more likely than boys to experience psychological distress during the pandemic.
Researchers at Skoltech developed an algorithm that aggregates and maps environmental data to predict and visually map the quality of water, soil, or air. The solution uses interpolation to fill gaps in data and produces detailed maps with high resolution.
A new study by the University of Plymouth has demonstrated the potential of gait authentication to protect smartphones from cyber crime. The system achieved an average accuracy rate of around 85% in recognizing individuals' stride patterns, with rates rising to almost 90% when participants were walking normally and fast.
A team of international researchers has developed a globally-applicable ethical code for ancient human DNA research, aiming to address social and cultural implications. The code proposes cooperation with stakeholders, minimal damage to human remains, and respect for indigenous communities' perspectives.
Researchers will assess potential effects on individuals with pre-existing conditions and measure toxin levels in blood, urine, and nasal mucosa. The study aims to understand the long-term health impacts of exposure to harmful algal blooms and develop tools for measuring concentrations of toxins in the environment.
A team of researchers led by Maurizio Porfiri found that counties with fewer COVID-19 cases voted more for Joe Biden than Donald Trump. The study used a spatial data modeling approach to analyze county-level data and determine the influence of epidemiological and economic processes on voting behavior.
Researchers from University of Copenhagen discover a protein analysis that can predict COVID-19 patient death or hospitalization with high accuracy, predicting 78.7% of hospitalizations and 93.9% of non-serious infections. This discovery has the potential to save lives by identifying high-risk individuals.
Researchers found that males and females have different heat-sensing systems, which may be related to reproduction and offspring care. This difference leads to segregation between the sexes at certain periods during breeding cycles.
Researchers used radiokrypton dating to study the origin and flow of freshwater and saltwater in the Floridan Aquifer. The study found that some samples contained 40,000-year-old saltwater from just before the last glacial maximum, highlighting the impact of rising sea levels on coastal aquifers.
An Australian study found that trust in government approval of safe COVID-19 vaccines is the primary driver of vaccine uptake. Perceived effectiveness in protecting others was also a significant factor. The study revealed lower rates of vaccine uptake among younger, unemployed individuals and those with lower altruistic beliefs.
A team of NTU Singapore scientists developed a predictive computer model called NSGA-II, which proposed strategies to reduce COVID-19 infections and deaths by an average of 72%. The model recommended timely and country-specific advice on interventions such as home quarantines and social distancing measures.
Researchers analyzed genome sequences and mobile phone data to track Covid-19 spread in Bangladesh. A three-day window between lockdown announcements and enforcement led to increased infections as citizens traveled to other areas.
Researchers successfully detected local mammals and birds by collecting 18 litres of water from a two-kilometre stretch along the river Mulde. The team identified 50% of fish species, 22% of mammal species, and 7.4% of breeding bird species in the region.
A new model developed by Stanford researchers provides a more accurate baseline for tracking methane emissions from oil and gas operations. The model, which uses bottom-up approach with component-level data, closely approximates top-down inventories and highlights specific activities that should be targeted for remediation or regulation.