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188 results for “Big data”
Data from: Contextualizing macroecological laws: A big data analysis on electrofishing and allometric scalings in Ohio, USA
We investigated the influence of different electrofishing methods on allometric scaling features of fish assemblages in lotic environments. The ultimate aim was to elucidate to which extent the structure of fish assemblages is predictable by the three-quarter power law theory. Water bodies across the state of Ohio, USA, provided a suitable data set to analyze the size–biomass spectra of 2051 fish assemblages. For the first time, 41,070 allometric field observations were screened according to sampling methods (i.e., longline, tote barge, boat) adopted for sampling collection. Allometric patterns varied considerably in relation with the sampling method, in turn imposed by the local hydrology and morphology of the investigated water courses, as shown by the lowering of scalings from boatable to wadeable systems. There are several lines of evidence indicating that the chosen type of electrofishing acts as a pitfall for size spectra. Using individually weighted body-mass values as independent predictor of spectra we show that the specific sampling methodology required by the physical characteristics of different lotic habitats influence the allometric outcomes, a novel result that makes universality of community power laws not as straightforward as supposed until now.
Data from: Using big data to assess prescribing patterns in Greece: the case of chronic obstructive pulmonary disease
Introduction: Chronic Obstructive Pulmonary Disease (COPD) is one of the top leading causes of death and disability, and its management is focused on reducing risk factors, relieving symptoms, and preventing exacerbations. The study aim was to describe COPD prescribing patterns in Greece by using existing health administrative data for outpatients. Methods: This is a retrospective cross-sectional study based on prescriptions collected by the largest social insurance fund, during the first and last trimester of 2012. Selection criteria were the prescription of specific active substances and a COPD diagnosis. Extracted information included active substance, strength, pharmaceutical form and number of packages prescribed, diagnosis, time of dispensing, as well as insurees' age, gender, percentage of co-payment and social security unique number. Statistical analysis included descriptive statistics and logistic regression. Results: 174,357 patients received medicines for COPD during the study period. Patients were almost equally distributed between male and female, and age above 55 years was strongly correlated with COPD. Most patients received a long-acting beta agonist plus inhaled corticosteroid combination (LABA +ICS), followed by long-acting muscarinic agonist (LAMA). 63% patients belonging in the 35-54 age received LABA+ICS. LAMA was prescribed more frequently among males and was strongly correlated with COPD. Conclusion: The study provides big data analysis of Greek COPD prescribing patterns. It highlights the need for appropriate COPD classification in primary care illustrating the role of electronic prescribing in ensuring appropriate prescribing. Moreover, it indicates possible gender differences in treatment response or disease severity, and the impact of statutory co-payments on prescribing.
Data from: How big is it really? Assessing the efficacy of indirect estimates of body size in Asian elephants
Information on an organism's body size is pivotal in understanding its life history and fitness, as well as helping inform conservation measures. However, for many species, particularly large-bodied wild animals, taking accurate body size measurements can be a challenge. Various means to estimate body size have been employed, from more direct methods such as using photogrammetry to obtain height or length measurements, to indirect prediction of weight using other body morphometrics or even the size of dung boli. It is often unclear how accurate these measures are because they cannot be compared to objective measures. Here, we investigate how well existing estimation equations predict the actual body weight of Asian elephants Elephas maximus, using body measurements (height, chest girth, length, foot circumference and neck circumference) taken directly from a large population of semi-captive animals in Myanmar (n = 404). We then define new and better fitting formulas to predict body weight in Myanmar elephants from these readily available measures. We also investigate whether the important parameters height and chest girth can be estimated from photographs (n = 151). Our results show considerable variation in the ability of existing estimation equations to predict weight, and that the equations proposed in this paper predict weight better in almost all circumstances. We also find that measurements from standardised photographs reflect body height and chest girth after applying minor adjustments. Our results have implications for size estimation of large wild animals in the field, as well as for management in captive settings.
Data from: Comparative support for the expensive tissue hypothesis: big brains are correlated with smaller gut and greater parental investment in Lake Tanganyika cichlids
The brain is one of the most energetically expensive organs in the vertebrate body. Consequently, the energetic requirements of encephalization are suggested to impose considerable constraints on brain size evolution. Three main hypotheses concerning how energetic constraints might affect brain evolution predict covariation between brain investment and i) investment into other costly tissues, ii) overall metabolic rate, and iii) reproductive investment. To date, these hypotheses have mainly been tested in homeothermic animals and the existing data are inconclusive. However, there are good reasons to believe that energetic limitations might play a role in large-scale patterns of brain size evolution also in ectothermic vertebrates. Here we test these hypotheses in a group of ectothermic vertebrates, the Lake Tanganyika cichlid fishes. After controlling for the effect of shared ancestry and confounding ecological variables, we find a negative association between brain size and gut size. Furthermore, we find that the evolution of a larger brain is accompanied by increased reproductive investment into egg size and parental care. Our results indicate that the energetic costs of encephalization may be an important general factor involved in the evolution of brain size also in ectothermic vertebrates.
Data from: Prey size and dietary niche of Rafinesque's big-eared bat (Corynorhinus rafinesquii)
Bats in the genus Corynorhinus possess a suite of morphological characters that permit them to effectively use both gleaning and aerial-hawking foraging strategies to capture Lepidoptera. Consequently, they occupy a specialized feeding niche within North American bat assemblages and are of particular interest for dietary studies. We collected fecal pellets from a colony of C. rafinesquii (Rafinesque's Big-Eared Bat) at Mammoth Cave National Park during August–October 2011 and amplified cytochrome-c oxidase subunit 1 fragments of prey from these pellets. We used the Barcode of Life Database to identify prey, and evaluated the size of prey species based on published values. The mean wingspan of prey we recorded from our samples was smaller than average values reported for Rafinesque's Big-Eared Bat using traditional methods (P ≤ 0.01), suggesting that surveys of culled insect parts beneath roosting sites may lead to biased estimates of the size and breadth of prey species eaten by gleaning bats. Mean wingspan of lepidopteran prey consumed by Rafinesque's Big-Eared Bat in our study was larger (P ≤ 0.01) than values reported for the Myotis septentrionalis (Northern Long-Eared Bat ), which is a smaller, sympatric gleaner in eastern North America. Further, comparisons of our diet data with abundance of prey suggest macrolepidopteran taxa are consistently consumed by Rafinesque's Big-Eared Bat to greater degree than microlepidotera. Our findings suggest that North American Corynorhinus consume a wider range of sizes and species of Lepidoptera than previously reported in studies based solely on identification of culled prey-wings beneath feeding roosts.
Data from: An inordinate fondness for beetles? Variation in seasonal dietary preferences of night roosting big brown bats (Eptesicus fuscus)
Generalist species with numerous food web interactions are thought to provide stability to ecosystem dynamics; however, it is not always clear whether habitat generality translates into dietary diversity. Big brown bats are common across North America and employ a flexible foraging strategy over water, dense forests, forest edges and rural and urban settings. Despite this generalist use of habitat, they are paradoxically characterized as beetle specialists. However, hard carapaces may preferentially survive digestion leading to over-representation during morphological analysis of diet. This specialization has not been evaluated independently using molecular analysis and species-level identification of prey. We used next-generation sequencing to assess the diet of big brown bats. Beetles were consumed in the highest frequency but Lepidoptera species richness was highest among identified prey. The consumption of species showed strong seasonal and annual variation. While Coleoptera consumption varied, Lepidoptera and Ephemeroptera were relatively constant dietary components. Dietary diversity increased in late summer when insect diversity decreases. Our results indicate that big brown bats are dietary generalists and, while beetles are an important component of the diet, Lepidoptera are equally important, and Lepidoptera and Ephemeroptera are the only stable prey resource exploited. As resources become limited, big brown bats may respond by increasing the species richness of prey and thus their connectedness in the ecosystem. This characterization of diet corresponds well with a generalist approach to foraging, making them an important species in encouraging and maintaining ecosystem stability.
Data from: Climate drives adaptive genetic responses associated with survival in big sagebrush (Artemisia tridentata)
A genecological approach was used to explore genetic variation for survival in Artemisia tridentata (big sagebrush). Artemisia tridentata is a widespread and foundational shrub species in western North America. This species has become extremely fragmented, to the detriment of dependent wildlife, and efforts to restore it are now a land management priority. Common garden experiments were established at three sites with seedlings from 55 source-populations. Populations included each of the three predominant subspecies, and cytotype variations. Survival was monitored for five-years to assess differences in survival between gardens and populations. We found evidence of adaptive genetic variation for survival. Survival within gardens differed by source-population and a substantial proportion of this variation was explained by seed climate-of-origin. Plants from areas with the coldest winters had the highest levels of survival, while populations from warmer and drier sites had the lowest levels of survival. Survival was lowest, 36%, in the garden that was prone to the lowest minimum temperatures. These results suggest the importance of climatic driven genetic differences and their effect on survival. Understanding how genetic variation is arrayed across the landscape and its association with climate can greatly enhance the success of restoration and conservation.
Data from: Small RNAs from a big genome: the piRNA pathway and transposable elements in the salamander species Desmognathus fuscus
Most of the largest vertebrate genomes are found in salamanders, a clade of amphibians that includes 686 species. Salamander genomes range in size from 14 to 120 Gb, reflecting the accumulation of large numbers of transposable element (TE) sequences from all three TE classes. Although DNA loss rates are slow in salamanders relative to other vertebrates, high levels of TE insertion are also likely required to explain such high TE loads. Across the Tree of Life, novel TE insertions are suppressed by several pathways involving small RNA molecules. In most known animals, TE activity in the germline is primarily regulated by the Piwi-interacting RNA (piRNA) pathway. In this study, we test the hypothesis that salamanders' unusually high TE loads reflect the loss of the ancestral piRNA-mediated TE-silencing machinery. We characterized the small RNA pool in the female and male adult gonads, testing for the presence of small RNA molecules that bear the characteristics of TE-targeting piRNAs. We also analyzed the amino acid sequences of piRNA pathway proteins from salamanders and other vertebrates, testing whether the overall patterns of sequence divergence are consistent with conserved pathway function across the vertebrate clade. Our results do not support the hypothesis of piRNA pathway loss; instead, they suggest that the piRNA pathway is expressed in salamanders. Given these results, we propose hypotheses to explain how the extraordinary TE loads in salamander genomes could have accumulated, despite the expression of TE-silencing machinery.
Data from: Does my posterior look big in this? The effect of photographic distortion on morphometric analyses
Most geometric morphometric studies are underpinned by sets of photographs of specimens. The camera lens distorts the images it takes, and the extent of the distortion will depend on factors such as the make and model of the lens and camera and user-controlled variation such as the zoom of the lens. Any study that uses populations of geometric data digitized from photographs will have shape variation introduced into the data set simply by the photographic process. We illustrate the nature and magnitude of this error using a 30-specimen data set of Recent New Zealand Mactridae (Mollusca: Bivalvia), using only a single camera and camera lens with four different photographic setups. We then illustrate the use of retrodeformation in Adobe Photoshop and test the magnitude of the variation in the data set using multivariate Procrustes analysis of variance. The effect of photographic method on the variance in the data set is significant, systematic, and predictable and, if not accounted for, could lead to misleading results, suggest clustering of specimens in ordinations that has no biological basis, or induce artificial oversplitting of taxa. Recommendations to minimize and quantify distortion include: (1) that studies avoid mixing data sets from different cameras, lenses, or photographic setups; (2) that studies avoid placing specimens or scale bars near the edges of the photographs; (3) that the same camera settings are maintained (as much as practical) for every image in a data set; (4) that care is taken when using full-frame cameras; and (5) that a reference grid is used to correct for or quantify distortion.
Data from: The cost of being big: local competition, importance of dispersal and experimental evolution of reversal to unicellularity
Multicellularity provides multiple benefits. Nonetheless, unicellularity is ubiquitous and there have been multiple cases of evolutionary reversal to a unicellular organization. In this paper, we explore some of the costs of multicellularity as well as the possibility and dynamics of evolutionary reversals to unicellularity. We hypothesize that recently evolved multicellular organisms would face a high cost of increased competition for local resources in spatially structured environments because of larger size and increased cell densities. To test this hypothesis we conducted competition assays, computer simulations, and selection experiments using isolates of Saccharomyces cerevisiae that recently evolved multicellularity. In well-mixed environments, multicellular isolates had lower growth rates relative to their unicellular ancestor due to limitations of space and resource acquisition. In structured environments with localized resources, cells in both multicellular and unicellular isolates grew at a similar rate. Despite similar growth, higher local density of cells in multicellular groups led to increased competition and higher fitness costs in spatially structured environments. In structured environments all of the multicellular isolates rapidly evolved a predominantly unicellular life cycle, while in well-mixed environments reversal was more gradual. Taken together, these results suggest that a lack of dispersal, leading to higher local competition, might have been one of the main constraints in the evolution of early multicellular forms.
USHAP: Big Data Seamless 1 km Ground-level Black Carbon Dataset for the United States
<p>USHAP (USHighAirPollutants) is one of the series of long-term, full-coverage, high-resolution, and high-quality datasets of ground-level air pollutants for the United States. It is generated from the big data (e.g., ground-based measurements, satellite remote sensing products, atmospheric reanalysis, and model simulations) using artificial intelligence by considering the spatiotemporal heterogeneity of air pollution. </p><p>This is the big data-derived seamless (spatial coverage = 100%) daily, monthly, and yearly 1 km (i.e., D1K, M1K, and Y1K) ground-level Black Carbon (BC) dataset in the United States from 2000 to 2020. Our daily BC estimates agree well with ground measurements with an average cross-validation coefficient of determination (CV-R2) of 0.80 and normalized root-mean-square error (NRMSE) of 0.60, respectively.</p><p>All the data will be made public online once our paper is accepted, and if you want to use the USHighBC dataset for related scientific research, please contact us (Email: weijing_rs@163.com; weijing@umd.edu).</p><ul><li>Wei, J., Wang, J., Li, Z., Kondragunta, S., Anenberg, S., Wang, Y., Zhang, H., Diner, D., Hand, J., Lyapustin, A., Kahn, R., Colarco, P., da Silva, A., and Ichoku, C. <a href="https://weijing-rs.github.io/publications/Wei_et_al-LPH-2023.pdf">Long-term mortality burden trends attributed to black carbon and PM2.5 from wildfire emissions across the continental USA from 2000 to 2020: a deep learning modelling study</a>. <i>The Lancet Planetary Health</i>, 2023, 7, e963–e975. https://doi.org/10.1016/S2542-5196(23)00235-8</li></ul><p><strong>More air quality datasets of different air pollutants can be found at: </strong><a href="https://weijing-rs.github.io/product.html"><strong>https://weijing-rs.github.io/product.html</strong></a></p>
Using big sequencing data to identify chronic SARS-Coronavirus-2 infections
<p>This dataset supports the "Using big sequencing data to identify chronic SARS-Coronavirus-2 infections" publication in Nature Communications. </p><p>It contains the following files and folders:<br> </p><ul><li>Readme.txt - detailed information on all folders and files.</li><li>Supplementary Dataset 1</li><li>Supplementary Dataset 2</li><li>Supplementary Dataset 3</li><li>Supplementary Dataset 4</li><li>Supplementary Dataset 5</li><li>Supplementary Dataset 6</li><li>Supplementary Dataset 7</li></ul>
A Big Data Analysis Algorithm for Massive Sensor Medical Images
<p><span>The smart sensor based big data analysis recommendation system has significant privacy and security concerns when it comes to using sensor medical images for suggestions and monitoring. The danger of security breaches and unauthorized access which might lead to identity theft and privacy violations increases when sending and storing sensitive medical data on the cloud. Insufficient or erroneous patient data can lead to poor treatment decisions, misdiagnoses, and unreliable recommendations. By creating an anomaly detection system based on machine learning specifically for medical image and providing timely treatments and notifications, our effort will improve patient care and well-being. We infer the feature extraction, feature selection, attack detection, and data collection data processing procedures in order to anticipate the anomaly in patient data. We transfer the data, take care of any missing values, and sanitize it using the data pre-processing mechanism. We employed the RFE and DPCA algorithms for feature selection and extraction, respectively. In addition, we applied the AGRNN approach to identify abnormalities. Data arrival rate, resource consumption, propagation delay, transaction epoch, true positive rate, false alarm rate, and RMSE are some of the metrics used to evaluate the proposed task.</span></p>
Interview Data on Challenges in big data based communication amid C19
<p><strong>Transcriptions of Interview Data that follows the Semi-Structured Interview Guide</strong></p> <p>Introduction</p> <p>Prior to beginning the interview, the research participant is given the option to accept or decline the interview being recorded. The interviewers then explained that the interview is entirely confidential and any references to company names, colleague names, or product names will be redacted from the transcripts and kept anonymous. The research participant’s name will not be used or recorded in the transcript or in the final manuscript. </p> <p>Background</p> <ol> <li> <p>Can you tell us about your education and professional background?</p> </li> </ol> <p>Current role and responsibilities</p> <ol> <li> <p>What is your current role/position? </p> </li> <li> <p>What industry is your company part of?</p> </li> <li> <p>What department are you part of? </p> </li> <li> <p>What area of the business do you support? </p> </li> <li> <p>What types of communications are you creating (e.g. communications channels, deliverables, platforms, etc.)?</p> </li> <li> <p>Are you utilizing RPA, AI, or data visualizations tools to communicate data? If so, how? </p> </li> <li> <p>Who are your stakeholders (who is the audience)?</p> </li> </ol> <p>Data and communications</p> <ol> <li> <p>When communicating data, what are the communication objectives/goals?</p> <ol> <li> <p>What communications problems are seeking to solve?</p> </li> </ol> </li> <li> <p>What type of data do you use in your role? </p> </li> <li> <p>How do you determine which datasets to use and communicate? </p> <ol> <li> <p>How do you assess the datasets for variety, volume, velocity, veracity?</p> </li> </ol> </li> <li> <p>How do you use it? (To describe, predict, diagnose, or make recommendations?)</p> </li> <li> <p>What has been the outcome or impact of using data in communications?</p> </li> <li> <p>How do you measure the impact of your communications?</p> </li> <li> <p>What are the challenges in communicating data?</p> </li> <li> <p>Do you use these communications across regions and international markets?</p> <ol> <li> <p>What are the challenges in communicating data across regions and international markets?</p> </li> <li> <p>What adjustments are required or what factors are taken into consideration when communicating data across countries? </p> </li> </ol> </li> <li> <p>Are these communications shared or utilized across business units, functions, and departments?</p> </li> </ol> <p>Conclusion </p> <ol> <li> <p>What value do your communications add to achieving business objectives? </p> </li> </ol>
Intervista sui Big Data de "Le Scienze" - Festival della Scienza Medica di Bologna, 2017
<p><strong>Videointervista</strong> La scienza oggi ha a disposizione oggi una quantità di dati che offre enormi possibilità ma che allo stesso tempo minaccia di far pagare un prezzo salato ai ricercatori. Enrico Bucci spiega come padroneggiare questi strumenti e verificare la validità dei risultati ottenuti</p>
Integrating Data Quality in Industrial Big Data Architectures: an Action Design Research Study
<p>This dataset includes the results of the ATAM analysis and the summary of the ADR process. </p>
Convergent evolution of the army ant syndrome and congruence in big-data phylogenetics
<p>Data for project entitled "Convergent evolution of the army ant syndrome and congruence in big-data phylogenetics" by Marek L. Borowiec</p>
Data to "Distinguishing mirror from glass: A 'big data' approach to material perception"
<p>This record contains images, models, and analysis scripts written in MATLAB.</p> <p>Tamura, Prokott, Fleming. "Distinguishing mirror from glass: A ‘big data’ approach to material perception." in preparation.</p>
SPSS data file and output file for study "Relationship Between Big Five Personality Traits and Attitudes Towards Artificial Intelligence".
<p>The SPSS data file and output file for the study "Relationship Between Big Five Personality Traits and Attitudes Towards Artificial Intelligence".</p>
Unsupervised detection of semantic correlations in big data
<p>simulated spin configurations from statistical mechanics models at thermal equilibrium. Further details are in our manuscript with the same title. </p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.