Articles tagged with Data Sets
Researchers analyzed fossil pollen and sedimentary records to study Holocene climate variability's impact on the northeastern US. The findings suggest rapid ecological changes in response to changing climate conditions.
Researchers found that evacuees who returned to their homes after initial evacuation had more children, while those who stayed in western Finland had fewer. Those who intermarried with the host population increased their social status, but were less likely to have children.
Researchers can create synthetic networks that satisfy differential privacy requirements, enabling broader sharing of confidential data for scientific discovery. These altered datasets capture most statistical features from the original network, making them suitable for various researchers.
A new method called FIt-SNE has been developed to speed up the analysis of single-cell gene expression data, reducing rendering time from over three hours to just fifteen minutes. This innovation allows researchers to capture rare cell populations and visualize thousands of genes at the level of single cells simultaneously.
A study suggests that empty homes tax could generate income for local governments and reduce demand from foreign investors to increase housing affordability. Low-use properties are concentrated in desirable areas, where building more homes may not solve the problem.
A new study found Hispanic males are twice as likely to have fatal interactions with the police in areas with high Hispanic populations and agencies with more Hispanic officers. The research suggests reforms within police ranks are needed, even in diverse forces.
Researchers developed a deep-learning model that detects fake news by analyzing language patterns, finding favoritism towards exaggerations in false stories. The model achieved high accuracy in distinguishing fact from fiction, particularly when tested on novel topics.
Researchers developed a new method to identify significant ties in social networks, controlling for individual activity levels. This approach accurately mimics real-life school class clusters and has applications in various complex networks, including interbank markets and face-to-face interactions.
A novel valuation method reveals that stock options granted to women and senior managers are worth more because they hold onto them longer. Options with less frequent vesting dates also cost companies significantly more.
A new AI model has been developed to translate mouse model data to human disease conditions, increasing the accuracy of extrapolation by up to 50%. The model, known as Found In Translation (FIT), has been tested on 28 different human diseases and uncovered novel disease-associated genes.
A new study using crowdsourced field size data shows that smallholder farms contribute substantially to world food production, making up 40% of the global agricultural area. The research provides a detailed map and estimates of field sizes at the global, continental, and national levels.
Researchers identify potential causes of bias in machine learning systems and demonstrate how changing data collection methods can reduce bias without compromising accuracy. They suggest identifying clusters of patients with high disparities in accuracy to inform data collection decisions.
Researchers found that small ParkScore improvements lead to increased physical exercise among residents, with cities like Minneapolis and San Francisco ranking high. The study suggests that investing in park infrastructure can positively impact public health, with a collective effect of improved fitness and well-being.
A recent study from the University of Colorado Boulder found that academic ideas tend to spread faster from highly-ranked universities, even when the quality of the idea is mediocre. This suggests a power imbalance in academia, where elite institutions have an advantage in spreading their research to others.
A study by MIT researchers found that about one-third of Requests for Comments on Wikipedia go unresolved, citing factors such as poor initial arguments and excessive discussion. The researchers developed a machine-learning model to predict when RfCs may go stale, and recommended digital tools to improve deliberation and resolution.
Researchers at KAUST have developed VR apps to visualize and interpret complex datasets in three dimensions. These apps use immersive technologies to allow users to interactively explore features of the data, leading to more accurate statistical models.
A team of researchers has developed a mutual information approach to interpreting atmospheric data collected over an 18-year period, finding strong correlations between new-particle formation and water content, sulfuric acid concentration, temperature, and relative humidity.
A new paper highlights the importance of open and usable data sets in ecology and other field research. By sharing data and code, scientists can save time and effort, as well as foster critical inquiry and new knowledge.
A study published in ACS NSQIP demonstrates a sustained benefit on colorectal surgical outcomes, with significant reductions in complications such as surgical site infections and sepsis. The program's introduction of procedure-targeted datasets also led to improved outcomes, including increased early discharges.
Researchers at Dartmouth College used the Bible to develop an algorithm that can convert written works into different styles for different audiences. The study, published in Royal Society Open Science, trained on over 1.5 million unique pairings of source and target verses from various versions of the sacred texts.
A study led by OHSU has published the largest cancer dataset of its kind, involving hundreds of patient samples and revealing new insights into acute myeloid leukemia (AML). The dataset may help researchers and physicians solve specific questions about AML treatment options.
Two types of flash drought have been identified in China, Type I driven by high temperatures and evapotranspiration, while Type II is initiated by rainfall deficiency. Both types have increased significantly over the past 30 years, with a two-fold greater increase for Type I.
Researchers at the University of Sussex have created a large dataset that can be used to develop smartphone apps that detect transportation modes, predict road conditions, and offer route recommendations. The dataset has achieved high accuracy rates in recognizing modes of transport, paving the way for innovative mobile applications
A deep learning approach can identify nuanced mammographic imaging features specific to recalled but benign (false-positive) mammograms, distinguishing them from those identified as malignant or negative. The study achieved an area under the curve (AUC) of 0.76-0.91, indicating high performance in detecting false recalls.
The new global marine environmental forecasting system will provide accurate predictions of ocean temperature, salinity, velocity, and tidal currents with a horizontal resolution of 10 km. The system's accuracy is expected to reach an advanced international level, enabling clear identification of ocean mesoscale phenomena.
A new MIT model has been developed to reduce false positives in credit card fraud detection, achieving a 54% reduction in incorrect flagging of legitimate transactions. By extracting more than 200 detailed features for each individual transaction, the model can better pinpoint unusual spending habits and improve accuracy.
Researchers at Northwestern University have identified four clusters of personality types using comprehensive data from over 1.5 million questionnaire respondents. The findings challenge existing paradigms in psychology and provide new insights into human behavior.
Researchers at MIT develop Temporal Relation Network (TRN) module to help CNNs recognize activities by observing key frames. The module achieves top accuracy of 95% in activity recognition on Jester dataset, outperforming existing models.
Researchers found that overconfident CEOs are 33% more likely to be sued by shareholders. A shareholder lawsuit can curb future risk-taking behavior, leading to lower confidence and more prudent actions. This study highlights the importance of shareholder power in regulating CEO behavior.
A Lehigh research team is developing a 'Google for research data' that can assist scientists in locating datasets across various disciplines. The team aims to create a domain-agnostic search engine that utilizes user-centric methods to develop dataset search tools and novel indexing techniques.
Researchers from the Santa Fe Institute developed a new algorithm called SpringRank that analyzes wins and losses in networks to predict outcomes. The algorithm outperformed others in efficiency and accuracy, even when applied to diverse datasets such as NCAA basketball teams and animal social behaviors.
The DeepLesion database is the largest publicly available medical image dataset, containing over 32,000 annotated lesions from 10,000 case studies. It has tremendous potential to jump-start the field of computer-aided detection and diagnosis.
A Massachusetts-based study found that opioid overdose events decreased during pregnancy but increased in the postpartum period, particularly when fewer resources were available to mothers with substance use disorder. The research team developed a unique dataset linking statewide resources and found that women with opioid use disorder ...
A new approach uses machine learning to generate computer-generated X-rays to supplement real images, increasing the size of training sets for AI systems. This method improves classification accuracy for common and rare conditions by up to 40%, overcoming a challenge in applying artificial intelligence to medicine.
A new study by Queen Mary University of London found that 58% of online video piracy is concentrated in just two locations, making them susceptible to detection by copyright enforcers. The research also revealed a global network of streaming cyberlockers and third-party indexing services facilitating piracy.
The GA4GH Large Scale Genomics Work Stream introduces the htsget protocol, a standard for accessing large-scale genomic sequencing data online without file transfers. This enables global sharing and collaboration, addressing the growing need for big-data cloud-based approaches in genomics.
A new study by North Carolina State University researchers found that companies incorporated in tax haven countries with weak governance are more likely to engage in practices benefiting executives at the cost of their shareholders. These companies paid an average of 83% less in dividends to shareholders, compared to those in well-regu...
Researchers developed a robust model for general causality that identifies multiple causal connections without time-sequence data. The Multivariate Additive Noise Model (MANM) works on simulated real-world datasets, offering opportunities to analyze complex phenomena in areas like economics and disease outbreaks.
Researchers developed a computational framework to analyze large-scale single-cell gene expression levels, enabling the study of unprecedented cellular heterogeneity in rare cell populations. The BigSCale tool successfully processed 1.3 million individual cells from a mouse brain dataset.
A new study by the University of Waterloo confirms that mergers create value for investors, improving shareholder value and market share. The research found that firms realize synergies from mergers, benefiting all stakeholders, including consumers who do not face higher prices.
Researchers at UT Dallas developed a tool to identify inconsistencies in cosmological data, revealing potential errors in current models. The findings suggest that either systematic errors need to be removed or the underlying model is incomplete, leading to questions about Albert Einstein's theory of gravity.
The NIMS inorganic material database AtomWork-Adv has been made available to the public with enhanced features. The database contains a vast amount of crystal structure, X-ray diffraction, material properties, and phase diagram data collected from literature up to 2014.
A study found a significant link between low birth weight and left-handedness in two large sets of Japanese and Dutch newborn children. Left-handers averaged lower birth weights, with differences observed even within families.
The USGS and DOE have released a comprehensive dataset of U.S. wind turbine locations and characteristics, enabling accurate planning and research. The database contains over 57,000 turbines and allows users to search and sort the wind fleet by various criteria.
Researchers used synthetic-aperture radar data from four satellites to analyze the Lake Urmia Causeway in Iran, finding accelerated deformation due to soil consolidation and human activity. They also developed a predictive model for future deformation, highlighting the potential of space-based monitoring for critical structures.
Researchers developed a new method to train computers to better recognize objects in the real world by using virtual reality. A virtual dataset called ParallelEye was created, allowing for diverse and realistic images of various scenes, which significantly improved performance on object detection tasks.
Researchers analyzed 136 million keystrokes from 168,000 volunteers to identify what makes a faster typist. The study found that the fastest typists use rollover typing, where they press the next key before the previous one is released, and display different typing styles.
A team of computational biologists developed an algorithm to integrate multiple sequencing datasets at single-cell resolution. This approach enables the comparison of single-cell datasets and dissects differences between them.
Researchers have created a massive 13 million-person family tree using genealogy data, revealing trends in marriage, migration, and longevity. The study found that people are more likely to marry fourth cousins than seventh cousins, and that women in Europe and North America have migrated more than men.
A new study finds that over 99% of Chicagoland wetlands are home to non-native plant species, with reed canary grass dominating many sites. The research highlights the importance of considering ecosystem function and functional values in restoration efforts in urban areas.
The Clinical Epidemiology Database aims to facilitate collaboration among researchers by providing a standardized platform for accessing and exploring complex clinical data. The database, launched by the University of Pennsylvania, introduces an intuitive interface and provides documentation of study design and background.
The USC-led ATLAS project has compiled a large dataset of brain scans from stroke patients, which is now available for download. Researchers are using this dataset to develop and test algorithms that can automatically process MRI images from stroke patients, aiming to identify biological markers for personalized treatment plans.
LMIC researchers face concerns over national ownership and unequal publishing opportunities when sharing open datasets. To address these issues, increased investment in LMIC data management infrastructure and international policy frameworks are proposed.
Researchers have developed a new method that can accurately estimate biodiversity at a global scale, up to 10 orders of magnitude. The study used the 1999 Great Britain Countryside Survey dataset and tested over a dozen methods, with one model providing estimates within 10% of the true value.
Researchers used a combination of conventional and remotely-sensed climate measurements to model the future distributions of bamboo species in southwestern China. This approach increased confidence in model results, providing valuable guidance for conservation planning and nuanced decision-making.
Researchers developed codes MENNDL and RAVENNA to efficiently design and train neural networks, generating and training up to 18,600 networks simultaneously. This enables the training of highly accurate networks in a fraction of the time, with applications in self-driving cars, intelligent robots, and scientific experiments.
The CARICOMP program found significant decreases in water quality at 42% of the monitoring stations across the Caribbean basin. Despite expected increases in water temperature due to global warming, no such changes were detected in the data set.
A computational study by Queen Mary University of London has identified Botswana as the country with the most distinct musical recordings globally. The researchers found that China has the most spatial outliers compared to its neighboring countries, highlighting unique timbral characteristics such as the butterfly harp string instrument.
Scientists at Vrije Universiteit Amsterdam found that averaging all estimates yields significant accuracy gains, especially when considering multiple people. Taking the average of estimates from different individuals is a more effective approach for good decision-making than relying on personal expertise.
Scientists analyze NASA data to investigate solar storm impact on cetaceans' internal compasses. While space weather is not primary driver of strandings, it may be one factor among several contributing to the phenomenon.