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1,940 results for “data sample”
Data from: Low-cost automated flight intercept trap for the temporal sub-sampling of flying insects attracted to artificial light at night
<p>Sampling methods are selected depending on the targeted species or the spatial and temporal requirements of the study. However, most methods for passive sampling of flying insects have poor temporal resolution because it is time consuming, costly and/or logistically difficult. Effective sampling of flying insects attracted to artificial light at night (ALAN) requires sampling at user-defined time points (nighttime only) across well-replicated sites resulting in major time and labor-intensive survey effort or expensive automated technologies. Described here is a low-cost automated intercept trap that requires no specialist equipment or skills to construct and operate, making it a viable option for studies that require temporal sub-sampling across multiple sites. The trap can be used to address a wide range of other ecological questions that require a greater temporal and spatial scale than is feasible with previous trap technology.</p>
Raw data of sequencing results of our study: Bovine milk microbiota: Evaluation of different DNA extraction protocols in challenging samples
<p>Clean reads of the repeated milk samples with used Primer Pairs V1V2 and V3V4</p> <p>Raw data of sequencing results (amplicon single variants)</p>
Chemical compositions data for "Space weathering of the Chang'e-5 lunar sample from a mid-high latitude region on the Moon"
<p>Data for “Space weathering of the Chang’e-5 lunar sample from a mid-high latitude region on the Moon”</p>
Experimental data for "sampling Configurations From Software Product Lines Via Probability-aware Diversification and SAT Solving"
<p>Experimental data for "sampling Configurations From Software Product Lines Via Probability-aware Diversification and SAT Solving" submitted to ASE. </p> <p>1. rSATJ4, PaD+rSATJ4, ProbSAT and PaD+ProbSAT are data for RQs1-2;</p> <p>2. NSbS and PaD+NSbS are data for RQ3;</p> <p>3. SATVaEA, PaD+SATVaEA, ProbSATVaEA, PaD+ProbSATVaEA are data for RQ4.</p> <p> </p> <p> </p>
Supplementary material 1 from: Gutiérrez EE, Helgen KM, McDonough MM, Bauer F, Hawkins MTR, Escobedo-Morales LA, Patterson BD, Maldonado JE (2017) A gene-tree test of the traditional taxonomy of American deer: the importance of voucher specimens, geographic data, and dense sampling. ZooKeys 697: 87-131. https://doi.org/10.3897/zookeys.697.15124
Gazetteer : Authors: Eliécer E. Gutiérrez, Kristofer M. Helgen, Molly M. McDonough, Franziska Bauer, Melissa T. R. Hawkins, Luis A. Escobedo-Morales, Bruce D. Patterson, Jesús E. Maldonado
Supplementary material 3 from: Gutiérrez EE, Helgen KM, McDonough MM, Bauer F, Hawkins MTR, Escobedo-Morales LA, Patterson BD, Maldonado JE (2017) A gene-tree test of the traditional taxonomy of American deer: the importance of voucher specimens, geographic data, and dense sampling. ZooKeys 697: 87-131. https://doi.org/10.3897/zookeys.697.15124
Supplementary information figure : Authors: Eliécer E. Gutiérrez, Kristofer M. Helgen, Molly M. McDonough, Franziska Bauer, Melissa T. R. Hawkins, Luis A. Escobedo-Morales, Bruce D. Patterson, Jesús E. Maldonado
Supplementary material 2 from: Gutiérrez EE, Helgen KM, McDonough MM, Bauer F, Hawkins MTR, Escobedo-Morales LA, Patterson BD, Maldonado JE (2017) A gene-tree test of the traditional taxonomy of American deer: the importance of voucher specimens, geographic data, and dense sampling. ZooKeys 697: 87-131. https://doi.org/10.3897/zookeys.697.15124
Name and DNA sequences of pairs of primers used for amplification and sequencing of the CYTB gene : Data type: molecular data
Sampling campaign data - Lake Geneva
<p>Physico-chemical data from the sampling campaigns in Lake Geneva: profiles and discrete samples</p>
VPAIR - Sample Data
<p>Subset of VPAIR for reviewing purposes. </p>
WESTPA 2.0 haMSM restarting tutorial sample data
<p>Sample dataset for use with the WESTPA-2.0 haMSM restarting plugin tutorial.</p>
Raw data for the samples collected from Hole B of the ICDP DSeis project at the Moab Khotsong Gold Mine in South Africa
<p>This data set is corresponding to the Miyamoto, T. et al. "Characteristics of Seismogenic Fault Rock Related to the 2014 Orkney Earthquake (M5.5) Beneath the Moab Khotsong Gold Mine, South Africa" Geophysical Research Letters, 2022. This data set shows physical property, magnetic susceptibility, mineral assemblage, and element composition of all Hole B subsamples, and frictional properties of 5 Hole B subsamples.</p>
Sample data for showyourwork
<p>Data used in the showyourwork test-zenodo unit test.</p>
Collection of pXRF Data Corresponding to Study Spectral Samples | Southwest Australia Acid Saline Sediments | Radwin 2022
<p>This file contains pXRF data from a portable Bruker XRF instrument using mudrock calibration settings, where each sample was scanned for 90 seconds to alternate through energy spectrums. This data has at tab displaying associated file numbers that correspond to sample ID's. These sample ID's all correspond to spectra of the same sample location used for the pXRF measurements. This data was collected for the completion of a masters thesis at the University of Utah Department of Geology & Geophysics. </p>
Audio Rendered Using Symbolic Music Data Sampled From DMelodies
<p>This is a dataset of audio files rendered using a subset of symbolic music data from <a href="https://github.com/ashispati/dmelodies_dataset">DMelodies</a>.</p>
Dataset for paper: How Twitter Data Sampling Biases U.S. Voter Behavior Characterizations
<p>This repository contains the data and code for the paper "How Twitter Data Sampling Biases U.S. Voter Behavior Characterizations."</p>
HARMONIOUS Sele River UAS Sample Data
<p>This dataset has been produced during a field campaign along the Sele River, Italy during 22-23 March 2022 within the framework of the <a href="http://www.costharmonious.eu">HARMONIOUS COST Action</a></p> <p>The area interest has a size of ~0.27 hectares. </p> <p>The dataset consists of two main data types:</p> <ol> <li>Thermal Infrared mosaic</li> <li>Multispectral mosaic</li> </ol> <p>The data acquisition was performed using a DJI Matrice M210 UAS and two main sensor systems:</p> <ol> <li>Zenmuse XT2 radiometric</li> <li>MicaSense RedEdge-MX Dual system</li> </ol> <p>The raw data were processed using Pix4D Mapper. Georeferencing was provided by using Ground Control Points (UTM33N)</p> <p><em>Data owner:<br> Dr. László Bertalan,<br> University of Debrecen, Hungary<br> <a href="https://sites.google.com/view/laszlobertalangeo">Website</a></em></p>
Kenya heel prick and cord blood sample data
<div> <p><span>Using data from Ontario Canada, we previously developed machine learning-based algorithms incorporating newborn screening metabolites to estimate gestational age (GA). The objective of this study was to evaluate the use of these algorithms in a population of infants born in Siaya county, Kenya.</span> </p> </div> <div> <p><span>Cord and heel prick samples were collected from newborns in Kenya and metabolic analysis was carried out by Newborn Screening Ontario in Ottawa, Canada. Postnatal GA estimation models were developed with data from Ontario with multivariable linear regression using ELASTIC NET regularization. Model performance was evaluated by applying the models to the data collected from Kenya and comparing model-derived estimates of GA to reference estimates from early pregnancy ultrasound.</span> </p> </div> <div> <p><span>Heel prick samples were collected from 1,039 newborns from Kenya. Of these, 8.9% were born preterm and 8.5% were small for GA. Cord blood samples were also collected from 1,012 newborns. In data from heel prick samples, our best-performing model estimated GA within 9.5 days overall of reference GA [mean absolute error (MAE) 1.35 (95% CI 1.27, 1.43)]. In preterm infants and those small for GA, MAE was 2.62 (2.28, 2.99) and 1.81 (1.57, 2.07) weeks, respectively. In data from cord blood, model accuracy slightly decreased overall (MAE 1.44 (95% CI 1.36, 1.53)). Accuracy was not impacted by maternal HIV status and improved when the dating ultrasound occurred between 9 and 13 weeks of gestation, in both heel prick and cord blood data (overall MAE 1.04 (95% CI 0.87, 1.22) and 1.08 (95% CI 0.90, 1.27), respectively).</span></p> <p>Compared to internal validation performance using Ontario data and to our previously published external validations, model performance was diminished in the Kenya cohort, suggesting that reference ultrasound timing is an important factor in model performance. Our study highlights the challenges in reliably estimating GA in low resource settings, even those with access to dating ultrasound, given that the timing of dating ultrasound is critical to develop algorithms for accurate estimation of GA based on metabolic analysis of blood obtained at birth.</p> </div>
Sample data
<p>Sequential multi-echo bSSFP data (ETL3_1x1_sl3_FA30_meas20_BW1002_LR_FID1701.mat) and single-echo bSSFP (reference) data (ETL1_1x1_sl3_FA30_meas20_BW1002_LR_FID1698.mat).</p>
Missing data in sea turtle population monitoring: a Bayesian statistical framework accounting for incomplete sampling
<p>Monitoring how populations respond to sustained conservation measures is essential to detect changes in their population status and determine the effectiveness of any interventions. In the case of sea turtles, their populations are difficult to assess because of their complicated life histories. Ground-derived clutch counts are most often used as an index of population size for sea turtles; however, data are often incomplete with varying sampling intensity within and among sites and seasons. To address these issues, we: (1) develop a Bayesian statistical modelling framework that can be used to account for sampling uncertainties in a robust probabilistic manner within a given site and season; and (2) apply this to a previously unpublished long-term sea turtle dataset (n = 17 years) collated for the Republic of the Congo, which hosts two sympatrically nesting species of sea turtle (leatherback turtle [<em>Dermochelys coriacea</em>] and olive ridley turtle [<em>Lepidochelys olivacea</em>]). The results of this analysis suggest that leatherback turtle nesting levels dropped initially and then settled into quasi-cyclical levels of interannual variability, with an average of 573 (mean, 95% prediction interval: 554–626) clutches laid annually between 2012 and 2017. In contrast, nesting abundance for olive ridley turtles has increased more recently, with an average of 1,087 (mean, 95% prediction interval: 1,057–1,153) clutches laid annually between 2012 and 2017. These findings highlight the regional and global importance of this rookery with the Republic of the Congo, hosting the second largest documented populations of olive ridley and the third largest for leatherback turtles in Central Africa; and the fourth largest non-arribada olive ridley rookery globally. Furthermore, whilst the results show that Congo's single marine and coastal national park provides protection for over half of sea turtle clutches laid in the country, there is scope for further protection along the coast. Although large parts of the African coastline remain to be adequately monitored, the modelling approach used here will be invaluable to inform future status assessments for sea turtles given that most datasets are temporally and spatially fragmented. </p>
Neuronal data sample from PMd of non-human primates (Macaca Mulatta) performing a countermanding reaching task
<p>Brief presentation of the subjects and task performed</p> <p>Two adult male rhesus macaque monkeys (Macaca mulatta; P, C) performed a countermanding reaching task. All experimental procedures, animal care, housing, and surgical procedures conformed with European (Directive 86/609/ECC and 2010/63/UE) and Italian (D.L. 116/92 and D.L. 26/2014) laws on the use of nonhuman primates in scientific research and were approved by the Italian Ministry of Health. In both monkeys a 96 channels Utah arrays (BlackRock Microsystem, USA) was employed to record neuronal activity from the dorsal premotor cortex (PMd) contralateral to the arm employed during the task.</p> <p>Behavioral task</p> <p>Monkeys performed a countermanding reaching task interacting with visual stimuli presented on a touch-screen. Each trial started with the presentation of a central stimulus (red dot) that they had touch with their finger and hold (400-900ms). Thereafter the central stimulus disappeared and, simultaneously, a target appeared (go signal) randomly at one of two opposite positions (left or right). In no-stop trials to perform a correct trial, monkeys had to move their hand form the central target, touch peripheral target and to maintain their fingers on it for a random time (400-800 ms). In stop trials at a variable delay (Stop signal delay, SSD) after the go signal was presented, the central stimulus reappeared (Stop signal) instructing the monkey to keep the hand on the starting position (additional holding time; 400-1000 ms) to perform a correct-stop trial. If the monkey moved the hand during stop trials, the trial was considered a wrong-stop trial. No-stop and stop trials were randomly intermingled in such a way that the no-stop trials were more frequent.</p> <p>Recordings</p> <p>The neuronal activity from each electrode was recorded by employing a Tucker Davies Technologies RZ2 system (sampling rate at 24.4 Khz). Single unit activity was then isolated by using Kilosort (Pachitariu, et al. in Advances in Neural information processing systems (2016) 4448-4456).</p> <p>Data and code reproduce and are linked the main figures and results of the paper "Neuronal population dynamics during motor plan cancellation in non-human primates" , <em>Proceedings of the National Academy of Sciences</em> (<em>PNAS</em>)</p> <p>For further inquiry please contact: stefano.ferraina@uniroma1.it or pierpaolo.pani@uniroma1.it</p> <p> </p>
ScienceDex guides
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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.