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Figure 3. - Phylogenetic relationships among Dicronocephalus species reconstructed with Bayesian inference using 16S rRNA sequences. Numbers above branches indicate ML bootstrap values and Bayesian posterior probabilities. Numbers below branches are bootstrap, symmetric resampling, and jacknife support from parsimony searches, respectively. Scale bar represents 10% nucleotide mutation rate.
Figure 3. - Phylogenetic relationships among Dicronocephalus species reconstructed with Bayesian inference using 16S rRNA sequences. Numbers above branches indicate ML bootstrap values and Bayesian posterior probabilities. Numbers below branches are bootstrap, symmetric resampling, and jacknife support from parsimony searches, respectively. Scale bar represents 10% nucleotide mutation rate.
Figure 1. - Bayesian phylogeny of Euptychia based on one mitochondrial (COI) and one nuclear (EF1-a) gene. Posterior probabilities are listed above and bootstrap values below branches. A dash denotes bootstrap support lower than 50%. (Euptychiaattenboroughi is not included in the analysis – see text for details.)
Figure 1. - Bayesian phylogeny of Euptychia based on one mitochondrial (COI) and one nuclear (EF1-a) gene. Posterior probabilities are listed above and bootstrap values below branches. A dash denotes bootstrap support lower than 50%. (Euptychiaattenboroughi is not included in the analysis – see text for details.)
Figure 10. - Maximum-likelihood phylogeny of Epicephala species based on sequences of the COI, ArgK and EF1α genes. Numbers above nodes are maximum-likelihood bootstrap support values based on 1,000 replications. The Japanese Epicephala species are marked in blue. Symbols right to species names donate ovipositor morphology: inverted U-shape, rounded apically; inverted V-shape, acute apically.
Figure 10. - Maximum-likelihood phylogeny of Epicephala species based on sequences of the COI, ArgK and EF1α genes. Numbers above nodes are maximum-likelihood bootstrap support values based on 1,000 replications. The Japanese Epicephala species are marked in blue. Symbols right to species names donate ovipositor morphology: inverted U-shape, rounded apically; inverted V-shape, acute apically.
Aeolian saltation fieldwork: values for impact and fluid threshold analysis
<p>Excel spreadsheet (.XLSX) containing the following information for the analysis of impact and fluid thresholds presented by Martin and Kok (2017), for averaging interval of 2 seconds and analysis interval of 1 minute. Data are from field deployments at Jericoacoara (Brazil), Rancho Guadalupe (California), and Oceano (California).</p> <p>The spreadsheet contains the following fields:</p> <ul> <li>Date of analysis interval (“Date”).</li> <li>Start time of analysis interval (“StartTime”).</li> <li>End time of analysis interval (“EndTime”).</li> <li>Calculated transport activity (“f_Q”).</li> <li>Calculated effective threshold wind speed (“u_th”) in m/s. This value is undefined (“NaN”) for intervals with f_Q = 0 or f_Q = 1.</li> <li>Fluid threshold hypothesis predicted transport activity (“f_Q_ft”).</li> <li>Impact threshold hypothesis predicted transport activity (“f_Q_it”).</li> <li>Dual threshold hypothesis predicted transport activity (“f_Q_dual”).</li> <li>Stability parameter (“z/L”) obtained from wind speed fluctuations in corresponding 30-minute time interval. This value is sometimes undefined (“NaN”) for intervals of very weak wind.</li> <li>Wind direction (“theta”) in degrees. Value is relative to dominant wind direction at site.</li> </ul> <p>The field measurements from which these values were calculated are described in Martin et al. (2017).</p> <p> </p> <p><strong>References:</strong></p> <p>Martin, R. L. and J. F. Kok (2017), Field evidence for fluid and impact thresholds in aeolian saltation, <em>arXiv:1610.10059v3</em>.</p> <p>Martin, R. L., J. F. Kok, and M. Chamecki (2017), Comprehensive field campaigns illustrate new methods for characterizing high-frequency variability in aeolian saltation flux, <em>arXiv:1609.08707v2</em>.</p>
Aeolian saltation fieldwork: values for impact and fluid threshold analysis
<p><strong>This dataset replaces the previously published dataset http://doi.org/10.5281/zenodo.321417.</strong></p> <p>Excel spreadsheet (.XLSX) containing the following information for the analysis of impact and fluid thresholds presented by Martin and Kok (2017), for averaging interval of 2 seconds and analysis interval of 1 minute. Data are from field deployments at Jericoacoara (Brazil), Rancho Guadalupe (California), and Oceano (California).</p> <p>The spreadsheet contains the following fields:</p> <ul> <li>Date of analysis interval (“Date”).</li> <li>Start time of analysis interval (“StartTime”).</li> <li>End time of analysis interval (“EndTime”).</li> <li>Calculated transport activity (“f_Q”).</li> <li>Calculated effective threshold wind speed (“u_th”) in m/s. This value is undefined (“NaN”) for intervals with f_Q = 0 or f_Q = 1.</li> <li>Stability parameter (“z/L”) obtained from wind speed fluctuations in corresponding 30-minute time interval. This value is sometimes undefined (“NaN”) for intervals of very weak wind.</li> <li>Wind direction (“theta”) in degrees. Value is relative to dominant wind direction at site.</li> </ul> <p>The field measurements from which these values were calculated are described in Martin et al. (2017).</p>
Dynamic integration of information about salience and value for smooth pursuit eye movements
<p>Dataset from the following publication:</p> <p>Schütz, A. C., Lossin, F., & Gegenfurtner, K. R. (2015). Dynamic integration of information about salience and value for smooth pursuit eye movements. <em>Vision Research, 113</em>, 169-178. <a>doi:10.1016/j.visres.2014.08.009 <span></span></a><a></a> .</p>
IPBES Values Assessment in Linked Open Data format
<p>This dataset contains the Methodological Assessment Report on the Diverse Values and Valuation of Nature of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services in linked open data format.</p> <p>The structure of the file follows the IPBES ontology version 06: <a href="https://github.com/IPBES-Data/IPBES_Ontology">https://github.com/IPBES-Data/IPBES_Ontology</a></p> <p>The report is published in 2022 and consists of 6 chapters and a Summary for Policy Makers. For more information about the report, see: <a href="https://www.ipbes.net/the-values-assessment">https://www.ipbes.net/the-values-assessment</a></p> <p>For any questions and enquiries, please contact the IPBES Data and Knowledge Unit <a href="mailto:aidin.niamir@senckenberg.de">aidin.niamir@senckenberg.de</a></p>
Extracting positive descriptions and exploring landscape value using text analysis in the Cairngorms National Park
<p>The dataset was retrieved August 31, 2023, from <a href="http://data.geograph.org.uk/dumps/">http://data.geograph.org.uk/dumps/</a></p><p>Geograph project require all submitters to adopt a Creative Commons Attribution-ShareAlike licence on their photographic submissions.<br><a href="http://creativecommons.org/licenses/by-sa/2.0/">http://creativecommons.org/licenses/by-sa/2.0/</a></p>
Daily market capitalization values of four stablecoins (USDT, USTC, DAI, FRAX)
<p>Data source provider Gecko Labs Pte. Ltd., 101 Upper Cross Street, #05-16 People's Park Centre, Singapore 058357.</p>
What harms and what hinders de-implementation of low-value care in emergency medicine practice ? A scoping review
<p><span>Low-value care can harm patients and healthcare systems. </span><span>Despite a decade of global endeavours, low-value care has persisted. Identification of barriers and enablers is essential for effective de-implementation of low-value care. This scoping review is an evidence summary of barriers, enablers and features of effective interventions for de-implementation of low-value care in emergency medicine practice worldwide.</span></p>
Residential Value of Lost Load (VOLL) per county in Germany
<h2>Supplementary data for the publication: <i>Trade-offs between system cost and supply security in municipal energy system design: an analysis considering spatio-temporal disparities in the Value of Lost Load</i></h2><p>The contents of the files are as follows:</p><ol><li><a href="https://zenodo.org/api/records/10064429/draft/files/VOLL_hourly_municipal.csv/content">VOLL_hourly_municipal.csv</a> contains the hourly resolved Value of lost Load for each NUTS3 region in Germany.</li><li><a href="https://zenodo.org/api/records/10064429/draft/files/VOLL_municipal_data.csv/content">VOLL_municipal_data.csv </a> contains the data that was used to perform the calculations as described in the Paper.</li><li><a href="https://zenodo.org/api/records/10064429/draft/files/nuts3_bnd_id_cities.csv/content">nuts3_bnd_id_cities.csv</a> contains a mapping of NUTS3 identifier, the German key number for the municipality and the name of the municipality.</li></ol>
Fig. 1 in An Overview Of The Ecological Values Of Soumar Wetland On Waterbirds Diversity
Fig. 1. Geographical location of the Soumar wetland (Setif, Northeast Algeria).
Laypeople in Fire Protection: Their Motivation, Their Emotions, Their Value
<p>This online supplement contains a dataset (raw data) collected in a study by the University of Münster, Germany, as well as supplementary study materials, and the online appendix of our paper including additional results. The study is part of a larger research project (<a href="https://www.brawa.ovgu.de/en/">https://www.brawa.ovgu.de/en/</a>) and examined the motivation, emotions, and behavior of laypeople in fire protection.</p><p>Fire events, a specific type of emergency situation, occur regularly and often cost people's lives. Early fire detection and involvement of (trained) laypeople in very early stages is essential, especially in fire-prone historical buildings. In an interview study (N = 25) and a quantification study (N = 238), we examined laypeople's motivation to help, their emotions, and their value – especially regarding behaviors – during fires. In Study 1, based on in-depth interviews using the critical incident technique, we inductively developed three category systems: 1) Key motivators included one's emotional bond to the object, altruism, self-protection, and self-efficacy. 2) Laypeople's emotions, such as stress at first but also calmness, were categorized. 3) We also found that laypeople's primary value during fire incidents was their ability to provide support, e.g., knowledge of the building. In Study 2, we found quantitative support for the findings derived from Study 1. Additionally, we compared laypeople's and experts' assessments and compared reactions depending on fire size. Thus, our research shifts the focus from evacuation to active – and safe – involvement of laypeople. Our results are helpful for executives in emergency management, as they may find value in including laypeople when coping with emergencies.</p><p>The ethics committee of the Faculty of Psychology and Sports Science of the University of Münster approved the studies (under ID 2021-30-MT and ID 2021-14-MT) and we preregistered them with aspredicted.org (available at <a href="https://aspredicted.org/dd2p8.pdf">https://aspredicted.org/dd2p8.pdf</a> and <a href="https://aspredicted.org/m6zh5.pdf">https://aspredicted.org/m6zh5.pdf</a>). The studies were supported by the German Federal Ministry of Education and Research (grant number 13N15416).</p><p><strong>This online supplement includes:</strong></p><ul><li>An online supplement (online appendix) containing additional material and results for Study 1 and Study 2</li><li>One codebook describing all instructions and items in Study 2 (quantification study)</li><li>Raw (anonymized) data set and analysis script for Study 2 (Note: The raw data contains only the information of persons who were included in the analysis and who gave their informed consent. Some demographic information was deleted to ensure anonymity.)</li></ul>
The umbrella value of caribou management strategies for biodiversity conservation in boreal forests under global change
<p><span>Single-species conservation management is often proposed to preserve biodiversity in human-disturbed landscapes. How global change will impact the umbrella value of single-species management strategies remains an open question of critical conservation importance. We assessed the effectiveness of threatened boreal caribou as an umbrella for bird and beetle conservation under global change. We combined mechanistic, spatially explicit models of forest dynamics and predator-prey interactions to forecast the impact of management strategies on the survival of boreal caribou in boreal forest. We then used predictive models of species occupancy to characterize concurrent impacts on bird and beetle diversity. Landscapes were simulated based on three scenarios of climate change and four of forest management. We found that strategies that best mitigate human impact on boreal caribou were an effective umbrella for maintaining bird and beetle assemblages. While we detected a stronger effect of land-use change compared to climate change, the umbrella value of management strategies for caribou habitat conservation were still impacted by the severity of climate change. Our results showed an interplay among changes in forest attributes, boreal caribou mortality, as well as bird and beetle species assemblages. The conservation status of some species mandates the development of recovery strategies, highlighting the importance of our study which shows that single-species conservation can have important umbrella benefits despite global change.</span></p>
Beaumont numbers and associated values of several mountain belts on Earth
<p>This file contains the data shown in table 1 in the Article: Tectonics or Surface Processes during orogenesis - the Beaumont number: II. Application to orogens on Earth.</p><p>Variable definitions:<br>NAndes are the Northern Andes, CAndes are the central Andes, EurAlps are the European Alps, Him is Himalaya-Tibet, Pyr are the Pyrenees, SANZ are the Southern Alps of New Zealand, TW is Taiwan, TS is the Tian Shan, Zag is the Zagros. <br>Bm is the Beaumont number (mean value), Kf is the fluvial erodibility (mean value), vc is the convergence or shortening rate (mean value), Fint is the integrated crustal strength of the orogen foreland (mean value), and AvgPrecip is the mean annual precipitation (mean value). BmVar, KfVar, vcVar, and FintVar are the variability of the respective mean values. AvgPrecipSTD is the standard deviation of AvgPrecip.</p>
Stable oxygen and hydrogen isotope values for permafrost ice, rain, and snow collected near Fairbanks, Alaska and a summary of all age dates from the CRREL Permafrost Tunnel
<p>Stable oxygen and hydrogen isotope values for permafrost ice, rain, and snow collected near Fairbanks, Alaska as well as a summary of all age dates from the CRREL Permafrost Tunnel</p><p>Please contact me for more information or to use the data.</p><p>thomas.a.douglas@usace.army.mil</p>
Stability (similarity) values of output maps generated using different background point sampling strategies
<p>These tables represent the model settings and similarity values of Species Distribution Models generated using different background pointssampling strategies. The similarity values are our own newly designed way to investigate model stability and were determined by comparing an output map of an SDM fitted using real data (original map) with an output map of an SDM fitted using virtual occurrences generated from the original map.</p>
Consumer value data for water quality improvement depending on the gap between perceived and expected condition
<p>This CSV file provides data from a survey of consumers about the gap between current and expected tap water quality. The WTP analysis of consumers' expectations for improved tap water quality was estimated with the R program. The R program is available at https://www.r-project.org.</p>
Dataset for the paper "TestDossier: A Dataset of Tested Values Automatically Extracted from Test Execution"
<p><strong>Dataset for the paper "TestDossier: A Dataset of Tested Values Automatically Extracted from Test Execution".</strong></p><p>We store values of the basic build-in Python types: numeric (int, float, and complex), boolean (bool), and text sequence (str). We also store values of the types: sequence (list, tuple, and range), set (frozenset and set), and mapping (dict) that include only basic types. To create the dataset, we monitored the test suites of 15 Python Standard Libraries. TestDossier contains 1,234 distinct argument/variable names and 133,169 dis- tinct values, leading to a total of 12,9M individual values.</p>
Value of water level class observations for parameter set selection in hydrological modelling
<p>Data corresponding to the study "<span>Value of water level class observations for parameter set selection in hydrological modelling</span>", published in the Hydrological Sciences Journal.</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.