Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
15,560
datasets available to search
ShareScore release 0.9.0
Dataset results
15,560 results for “How long”
Raw MS data for "Ligand-specific changes in conformational flexibility mediate long-range allostery in the lac repressor"
<p>These are the raw HDX/MS data for our paper: "Ligand-specific changes in conformational flexibility mediate long-range allostery in the lac repressor."</p>
1805-1898 Census Records of Lausanne : a Long Digital Dataset for Demographic History
<p><strong>Context. </strong>This historical dataset stems from the project of automatic extraction of 72 census records of Lausanne, Switzerland. The complete dataset covers a century of historical demography in Lausanne (1805-1898), which corresponds to 18,831 pages, and nearly 6 million cells.</p> <p><strong>Content.</strong> The data published in this repository correspond to a first release, i.e. a diachronic slice of one register every 8 to 9 years. Unfortunately, the remaining data are currently under embargo. Their publication will take place as soon as possible, and at the latest by the end of 2023. In the meantime, the data presented here correspond to a large subset of 2,844 pages, which already allows to investigate most research hypotheses.</p> <p><strong>Description. </strong>The population censuses, digitized by the <a href="https://www.lausanne.ch/vie-pratique/culture/bibliotheques-et-archives/archives.html">Archives of the city of Lausanne</a>, continuously cover the evolution of the population in Lausanne throughout the 19th century, starting in 1805, with only one long interruption from 1814 to 1831. Highly detailed, they are an invaluable source for studying migration, economic and social history, and traces of cultural exchanges not only with Bern, but also with France and Italy. Indeed, the system of tracing family origin, specific to Switzerland, allows to follow the migratory movements of families long before the censuses appeared. The bourgeoisie is also an essential economic tracer. In addition, censuses extensively describe the organization of the social fabric into family nuclei, around which gravitate various boarders, workers, servants or apprentices, often living in the same apartment with the family.</p> <p><strong>Production. </strong>The structure and richness of censuses have also provided an opportunity to develop automatic methods for processing structured documents. The processing of censuses includes several steps, from the identification of text segments to the restructuring of information as digital tabular data, through Handwritten Text Recognition and the automatic segmentation of the structure using neural networks. Please note that the detailed extraction methodology, as well as the complete evaluation of performance and reliability is published in:</p> <ul> <li>Petitpierre R., Rappo L., Kramer M. (2023). <em>An end-to-end pipeline for historical censuses processing</em>. International Journal on Document Analysis and Recognition (IJDAR). doi: <a href="https://doi.org/10.1007/s10032-023-00428-9">10.1007/s10032-023-00428-9</a></li> </ul> <p><strong>Data structure.</strong> The data are structured in rows and columns, with each row corresponding to a household. Multiple entries in the same column for a single household are separated by vertical bars ⟨|⟩. The center point ⟨·⟩ indicates an empty entry. For some columns (e.g., street name, house number, owner name), an empty entry indicates that the last non-empty value should be carried over. The page number is in the last column.</p> <p><strong>Liability. </strong>The data presented here are not curated nor verified. They are the raw results of the extraction, the reliability of which was thoroughly assessed in the above-mentioned publication. We insist on the fact that for any reuse of this data for research purposes, the implementation of an appropriate methodology is necessary. This may typically include string distance heuristics, or statistical methodologies to deal with noise and uncertainty.</p>
Data of the publication "Transport and entanglement growth in long-range random Clifford circuits"
<p>Conservation laws can constrain entanglement dynamics in isolated quantum systems, manifest in a slowdown of higher Rényi entropies. Here, we explore this phenomenon in a class of long-range random Clifford circuits with U(1) symmetry where transport can be tuned from diffusive to superdiffusive. We unveil that the different<br> hydrodynamic regimes reflect themselves in the asymptotic entanglement growth according to <span class="math-tex">\(S(t) \propto t^{1/z}\)</span> where<br> the dynamical transport exponent z depends on the probability <span class="math-tex">\(\propto r^{-\alpha}\)</span> of gates spanning a distance r. For<br> sufficiently small <span class="math-tex">\(\alpha\)</span>, we show that the presence of hydrodynamic modes becomes irrelevant such that S(t) behaves<br> similarly in circuits with and without conservation law. We explain our findings in terms of the inhibited operator<br> spreading in U(1)-symmetric Clifford circuits where the emerging light cones can be understood in the context<br> of classical Lévy flights. Our Letter sheds light on the connections between Clifford circuits and more generic<br> many-body quantum dynamics.</p>
Data for: Detecting Long-Term Balancing Selection Using Allele Frequency Correlation
<p>Genome-wide and top 1% scores for 1KG project data output from BetaScan reported in:</p> <p><a href="https://pubmed.ncbi.nlm.nih.gov/28981714/">Detecting Long-Term Balancing Selection Using Allele Frequency Correlation.</a></p> <p>Siewert KM, Voight BF. Mol Biol Evol. 2017 Nov 1;34(11):2996-3005. doi: 10.1093/molbev/msx209.</p> <p>PMID: 28981714</p> <p>Code available at: https://github.com/ksiewert/BetaScan</p>
Low-level mixed-phase clouds at the high Arctic site of Ny-Ålesund: A comprehensive long-term dataset of remote sensing observations
<p>This dataset contains a comprehensive set of quality-controlled remote sensing observations of low-level mixed-phase clouds collected at the high Arctic site of Ny-Ålesund, between 10 October 2021 and 31 December 2022. Cornerstones of the dataset are observations from a 35-GHz polarimetric scanning Doppler cloud radar and a 94-GHz zenith-pointing Doppler cloud radar. Radar data are complemented with thermodynamic retrievals from a microwave radiometer, liquid base height from a ceilometer and wind fields from large-eddy simulations. All data have undergone extensive quality control, especially the cloud radar data, which are accurately calibrated, matched, and corrected for gas and liquid-hydrometeor attenuation, ground clutter and range folding. This dataset is especially suited for cloud microphysical studies, and the high number of events included allows for the compiling of robust statistics. The dataset is accompanied by a data descriptor article, which is available at <a href="https://doi.org/10.5194/essd-15-5427-2023" target="_blank" rel="noopener">doi.org/10.5194/essd-15-5427-2023</a>.</p> <p> </p> <p><strong>Dataset overview</strong><br>The files include only low-level mixed-phase cloud (LLMPC) events, as well as the 2 hours preceding and following events. Each file contains an individual event, unless multiple events are less than 4 hours apart, in which case they are combined into the same file. LLMPC events are detected by requiring that ice and liquid phase coexist in a cloud layer with top below 2500 m for at least one hour. All radar variables observed in zenith (Doppler moments at 35 and 94 GHz, linear depolarization ratio (LDR) at 35 GHz), as well as microwave radiometer retrievals (temperature (T), liquid water path (LWP), integrated water vapor (IWV)), liquid base height from the ceilometer, and model data (horizontal wind speed and direction) are brought to the same time and range grids (respectively named ‘time_zen’ and ‘range_zen’ in the files). Off-zenith radar variables (reflectivity, differential reflectivity (ZDR), maximum spectral ZDR (sZDRmax), correlation coefficient (RhoHV), differential phase shift (PhiDP), and specific differential phase (KDP)) are stored on separate coordinates (named ‘time_slant’ and ‘range_slant’). All derived corrections are already applied to the data, and stored in the files, in case the user is interested in reconstructing the original data. A number of flags have been included in the files: in particular ‘MPC_detected’ indicates whether a LLMPC event was detected, and ‘liquid_attenuation_correction_flag_zen’ and ‘liquid_attenuation_correction_flag_slant’ indicate whether radar reflectivities were corrected for attenuation due to liquid hydrometeors. Liquid attenuation corrections should be especially taken into account when computing the dual-wavelength ratio (i.e., the difference between reflectivity at 35 GHz and at 94 GHz, both expressed in dBZ), and performing quantitative analyses of reflectivity fields.</p>
Morphological cladogenesis and terminal dwarfing in extinct Late Miocene through Pliocene menardiform globorotalids: New complementary data to «Evolutionary prospection in the Neogene planktic foraminifer Globorotalia menardii and related forms from ODP Hole 925B (Céara Rise, western tropical Atlantic): evidence for gradual evolution superimposed by long distance dispersal ?, Swiss J. Palaeontology, 135:205-248»
<p>A complementary morphometric data set is provided to the study of Knappertsbusch (2016) about the shell evolution of menardiform globorotalids (Neogene planktic foraminifera) at ODP Hole 925B from Céara Rise in the the western tropical Atlantic. The new measurements confirm splitting of extinct <em>Globorotalia multicamerata</em> from the <em>G. menardii</em> stock via the intermediate form <em>G. limbata</em> between about 6 Ma to 5 Ma ago. After splitting both <em>G. limbata</em> and <em>G. multicamerata</em> show gradual divergence from <em>G. menardii</em> in several shell parameters illustrating morphological cladogenesis. Between 2.88 Ma and 2.59 Ma the same parameters show a concerted trend towards reduced values indicating pre-extinction dwarfing. A comparison with published literature data of Delta<sup>18</sup>O trends between species, that populated the mixed layer (<em>Globigerinoides sacculifer</em>) and the thermocline layer (<em>Neogloboquadrina dutertrei</em>) at this location during those times suggests, that both divergence and subsequent dwarfing trends were probably the results of changes in upper watermass stratification.</p> <p>The complementary data set is provided in six zipped archives APPENDIX A, B, C, D, E and F (zipped with free software 7-Zip 22.00 (x64), 2022-06-15 from 1999-2022 Igor Pawlow), together with a description of the data in file Report_925B_suppl_1.pdf.</p>
Open Source and Open Science Sustainability Year-long Study - Pseudonymised
<p>Research software is often abandoned or shut down, for one reason or another. While some reasons may be straightforward, e.g. a sole maintainer has moved on, or grant funding has ceased - some projects are able to withstand these barriers and may remain active and maintained despite adversity.</p> <p>This study monitors open source projects over the period of a year, measuring common performance indicators, to see if any indicators are common to projects that remain sustainable and active.</p> <p>This study uses mixed methods:</p> <ol> <li>Initial survey gathers info about the project age, leadership, and GitHub (or other source control) URLs. Participants are asked to add <a href="https://sustainable-open-science-and-software.github.io/readme_notice">a short notice to their readme</a>.</li> <li>After the initial survey, we gathered information about the GitHub projects such as number of contributors, number of PRs, time taken to close/merge these PRs, and issues closed. Some of this info is gathered using scripts, and other parts are gathered manually. An example of a manual metric is the Code of Conduct - while we can programmatically check for the <em>existence</em> of CodeOfConduct.md, we can’t easily check for enforcement contacts without manual checks.</li> <li>6 months and 12 months after the initial survey, we send follow up surveys, and in month 12 we re-run the GitHub metrics to compare to month 0.</li> </ol> <p> </p> <p>For more study info see: <a href="https://sustainable-open-science-and-software.github.io/">https://sustainable-open-science-and-software.github.io/</a></p> <p> </p>
Functional potential and evolutionary response to long-term heat selection of bacterial associates of coral photosymbionts
<p>Sequencing reads were assembled using the genome assembler pipeline Shovill v1.1.0. Briefly, the Shovill pipeline included read trimming using Trimmomatic v0.39, de novo assembly with SPAdes v3.15.5 and genome polishing with Pilon v1.24. After the pipeline, additional polishing was performed by mapping the reads back to the contigs with BWA v0.7.17 and sorting the resulting SAM/BAM files using SAMtools v1.15.1. Pilon v1.24 was then used to correct bases, fix mis-assemblies and fill gaps. The reformat.sh script from the Bbmap package v38.76 (-minlength=1000) was used to filter out contigs less than 1000bp. The draft genome assemblies were then annotated with Bakta v1.7.0. </p> <p>Single nucleotide polymorphism (SNP) detection between WT (WTref) and SS (SSref) samples were then performed using snippy v4.6.0, where both WT and SS samples were inputted as the reference genome in turn.</p> <p>A subset of the snippy output files are uploaded here and contain all variants found.</p>
Dataset for "Joint optimization of land carbon uptake and albedo can help achieve moderate instantaneous and long-term cooling effects"
<p>Data and Code for 'Joint optimization of land carbon uptake and albedo can help achieve moderate instantaneous and long-term cooling effects' by Graf et al. (Communications Earth and Environment)</p>
Database of a study on long-term land cover changes in Thừa Thien Huế Province, Central Vietnam
<p>Data provided here forms the basis of a study which is published in the journal Land Use Policy (year 2023) under the title 'The nature of a ‘forest transition’ in Thừa Thien Huế Province, Central Vietnam – A study of land cover changes over five decades'. The database contains the image files of the maps (and associated legends) shown in the publication. Further data (currently under use for other related research) will eventually be added to the repository.</p>
The long term series of characteristics of floods that happened to 12 rivers in Finland and northern Russia.
<p>The dataset of flood’s characteristics (annual and spring): the volume of spring flood (in mm of the depth of runoff), the dates of spring flood begin and end, the length of spring flooding period, the yearly maximum daily discharge and its date were estimated for each year from the daily series of water discharges observed at the hydrometric sites. To define the dates of spring flood begin and end we applied the semi-empirical method given in Shevnina (2013). The yearly maximum water discharges have been obtained in Gudmundsson et al. (2018) for the period until 2017; this dataset gives a good agreement in the estimations for the overlapping periods. The series of volume of spring flood (in mm of the depth of runoff), the dates of spring flood begin and end, the length of spring flooding period, the yearly maximum daily discharge and its date are given in the dataset supplementing the study submitted to the Water resource research journal (<a href="https://agupubs.onlinelibrary.wiley.com/journal/19447973">https://agupubs.onlinelibrary.wiley.com/journal/19447973</a> ). </p> <p>The daily series of water river discharges at the sites located in Finland were extracted from (a) the Global runoff database <a href="https://portal.grdc.bafg.de/">https://portal.grdc.bafg.de/</a> (for the period from beginning of the observations to 2017); (b) the archive of the Finnish Environmental Institute <a href="https://www.syke.fi/">https://www.syke.fi</a> (for the period 2018–2020) and these series can be obtained after its representatives’ permission from the author. The daily series of water discharges at the sites located in the Russian Federation were extracted from (a) the yearly hydrological books published by the State Hydrological Institute <a href="http://www.hydrology.ru/en">http://www.hydrology.ru/en</a> (for the period from the beginning of observation to 2007); (b) the automated information system for state monitoring of water bodies <a href="https://gmvo.skniivh.ru/">https://gmvo.skniivh.ru/</a> (for the period 2008–2020) and these series are available from its web-site after a registration. </p> <p>The dataset consists of the CSV/TXT files, each file contains the long term series of the characteristics listed in the header: "year", "DFB" (date when a spring flooding period begins, day of year, DOY),"DFE" (date when the spring flooding period ends, DOY),"Length" (length of the spring flooding period, days), "DFMax" (date when the yearly maximum water discharge is recorded, DOY), "Qmax" (the yearly maximum water discharge, cubic m per second), "FRD" (the volume of spring flood expressed in mm per flooding period), "YRD" (volume of annual flow, expressed in mm per year),"Ftype" (the source of annual flood equaling to 1 of the yearly maximum water discharge is recorded in the spring flooding period or 0 if it is not). </p> <p>The dataset was obtained in the study funded by the Academy of Finland under the contract number 317999. It will become freely available once the manuscript is published. </p> <p>References</p> <p>Gudmundsson, L., Do, H. X., Leonard, M., & Westra, S. (2018), The Global Streamflow Indices and Metadata Archive (GSIM) – Part 2: Quality control, time-series indices and homogeneity assessment, Earth Syst. Sci. Data, 10, 787–804, https://doi.org/10.5194/essd-10-787-2018.</p> <p>Shevnina E. (2013), Method to calculate characteristics of spring flood from daily water discharges, Problems of the Arctic and Antarctic, 1(95), pp. 12-21. In Russian</p>
Data of the publication "Hydrodynamics in long-range interacting systems with center-of-mass conservation"
<p>In systems with a conserved density, the additional conservation of the center of mass (dipole moment) has been shown to slow down the associated hydrodynamics. At the same time, long-range interactions generally lead to faster transport and information propagation. Here, we explore the competition of these two effects and develop a hydrodynamic theory for long-range center-of-mass-conserving systems. We demonstrate that these systems can exhibit a rich dynamical phase diagram containing subdiffusive, diffusive, and superdiffusive behaviors, with continuously varying dynamical exponents. We corroborate our theory by studying quantum lattice models whose emergent hydrodynamics exhibit these phenomena.</p>
Supplement to "Low-level mixed-phase clouds at the high Arctic site of Ny-Ålesund: A comprehensive long-term dataset of remote sensing observations"
<p>This dataset is a supplement to "Low-level mixed-phase clouds at the high Arctic site of Ny-Ålesund: A comprehensive long-term dataset of remote sensing observations", available at <a href="http://doi.org/10.5281/zenodo.7803064">doi.org/10.5281/zenodo.7803064</a>. The additional variables here included are: slow edge velocity, fast edge velocity, and eddy dissipation rate (EDR). All variables are stored on the same time and range grids adopted for the main dataset. Similarly, the event selection and file structure are identical to those of the main dataset.<br><br>Slow and fast edge velocities are derived from Doppler spectra recorded by the zenith-pointing 94-GHz cloud radar. The slow (fast) edge velocity is calculated as the velocity associated with the slowest (fastest) Doppler bin above the peak noise level, belonging to a spectral cluster whose width is at least 5 Doppler bins.<br><br>The EDR is retrieved following the approach by Borque et al. (2016; <a href="http://doi.org/10.1002/2015JD024543">doi.org/10.1002/2015JD024543</a>), using as input the slow edge velocity, and model horizontal wind speed from the main dataset. EDR is retrieved in 5 minute intervals, up to a maximum range of 3 km.<br><br>The detailed documentation of the variables here included can be found in the Supporting Information to the following publication: <a href="https://doi.org/10.1029/2023GL106599" target="_blank" rel="noopener">doi.org/10.1029/2023GL106599</a>.</p>
IRIDIA-AF, a large paroxysmal atrial fibrillation long-term electrocardiogram monitoring database
<h2>Abstract</h2><p>Atrial fibrillation (AF) is the most common sustained heart arrhythmia in adults. Holter monitoring, a long-term 2-lead electrocardiogram (ECG), is a key tool available to cardiologists for AF diagnosis. Machine learning (ML) and deep learning (DL) models have shown great capacity to automatically detect AF in ECG and their use as medical decision support tool is growing. Training these models rely on a few open and annotated databases. We present a new Holter monitoring database from patients with paroxysmal AF with 167 records from 152 patients, acquired from an outpatient cardiology clinic from 2006 to 2017 in Belgium. AF episodes were manually annotated and reviewed by an expert cardiologist and a specialist cardiac nurse. Records last from 19 hours up to 95 hours, divided into 24-hour files. In total, it represents 24 million seconds of annotated Holter monitoring, sampled at 200 Hz. This dataset aims at expanding the available options for researchers and offers a valuable resource for advancing ML and DL use in the field of cardiac arrhythmia diagnosis.</p><h2>Article</h2><p><a href="https://www.nature.com/articles/s41597-023-02621-1">https://www.nature.com/articles/s41597-023-02621-1</a></p><h2>Repository</h2><p><a href="https://github.com/cedricgilon/iridia-af">https://github.com/cedricgilon/iridia-af</a></p><h2>Versions history</h2><ul><li>2023-10-04: v1.0.1 – remove hidden files from .zip archive</li><li>2023-07-26: v1.0.0 – initial release</li></ul><h2>Keywords</h2><p>Paroxysmal Atrial Fibrillation, AF, long-term electrocardiogram, ECG, Holter monitoring, Database, Dataset, IRIDIA, IRIDIA-AF</p>
Ensemble Machine Learning Prediction of Potential FAPAR: Monthly time-series 2021 and Long-Term Comparison with Actual FAPAR
<p><strong>General Description</strong></p> <p>The dataset contains composites at 250 m spatial resolution of (1) monthly potential FAPAR for the year 2021 from ensemble ML model predictions, (2) the model deviance for each prediction, (3) the yearly average of potential FAPAR, (4) the yearly average of actual FAPAR and (5) the yearly average of the difference between actual and potential (actual minus potential) FAPAR. The dataset is based on the <a href="https://zenodo.org/record/8392976">95th percentile of the monthly aggregated FAPAR</a> derived from <a href="http://glass.umd.edu/Overview.html">250 m 8 d GLASS V6 FAPAR</a>. Potential FAPAR was predicted by fitting an ensemble ML model using globally distributed training points (cca 3 Mio) and a set of 52 biophysical covariates including several layers related to human pressure. The code for modeling potential FAPAR is openly available at <a href="http://github.com/Open-Earth-Monitor/Global_FAPAR_250m">https://github.com/Open-Earth-Monitor/Global_FAPAR_250m</a>. The dataset can be used in many applications like land degradation modeling, land productivity mapping, and land potential mapping. </p> <p><strong>Data Details</strong></p> <ul> <li><strong>Time period:</strong> January 2021 - December 2021</li> <li><strong>Type of data: </strong>Fraction of Absorbed Photosynthetically Active Radiation (FAPAR)</li> <li><strong>How the data was collected or derived:</strong> Derived from 250m 8 d GLASS V6 FAPAR</li> <li><strong>Statistical methods used: </strong>Ensemble machine learning</li> <li><strong>Limitations or exclusions in the data: </strong>The dataset does not include data for Antarctica.</li> <li><strong>Coordinate reference system:</strong> EPSG:4326</li> <li><strong>Bounding box (Xmin, Ymin, Xmax, Ymax):</strong> (-180.00000, -62.0008094, 179.9999424, 87.37000)</li> <li><strong>Spatial resolution:</strong> 1/480 d.d. = 0.00208333 (250m)</li> <li><strong>Image size: </strong>172,800 x 71,698</li> <li><strong>File format: </strong>Cloud Optimized Geotiff (COG) format.</li> </ul> <p><strong>Support</strong></p> <p>If you discover a bug, artifact, or inconsistency, or if you have a question please raise a GitHub issue: <a href="https://github.com/Open-Earth-Monitor/Global_FAPAR_250m/issues">https://github.com/Open-Earth-Monitor/Global_FAPAR_250m/issues</a></p> <p><strong>Reference</strong></p> <p>Hackländer, J., Parente, L., Ho, Y.-F., Hengl, T., Simoes, R., Consoli, D., Şahin, M., Tian, X., Herold, M., Jung, M., Duveiller, G., Weynants, M., Wheeler, I., (2023?) "Land potential assessment and trend-analysis using 2000–2021 FAPAR monthly time-series at 250 m spatial resolution", submitted to PeerJ, preprint available at: <a href="https://doi.org/10.21203/rs.3.rs-3415685/v1">https://doi.org/10.21203/rs.3.rs-3415685/v1</a></p> <p> </p> <p><strong>Name convention</strong></p> <p>To ensure consistency and ease of use across and within the projects, we follow the standard Open-Earth-Monitor file-naming convention. The convention works with 10 fields that describes important properties of the data. In this way users can search files, prepare data analysis etc, without needing to open files. The fields are:</p> <ol> <li><strong>generic variable name:</strong> pot.fapar = Potential Fraction of Absorbed Photosynthetically Active Radiation</li> <li><strong>variable procedure combination: </strong>eml = ensemble machine learning</li> <li><strong>Position in the probability distribution / variable type:</strong> m = mean</li> <li><strong>Spatial support:</strong> 250m</li> <li><strong>Depth reference: </strong>s = surface</li> <li><strong>Time reference begin time:</strong> 20210101 = 2021-01-01</li> <li><strong>Time reference end time:</strong> 20211231 = 2021-12-31</li> <li><strong>Bounding box: </strong>go = global (without Antarctica)</li> <li><strong>EPSG code:</strong> epsg.4326 = EPSG:4326</li> <li><strong>Version code:</strong> v20230924 = 2023-09-24 (creation date)</li> </ol>
Self-consistent models of Earth's mantle and core from long-period seismic and tidal constraints
<p>This dataset consists of a collection of self-consistent radial seismic Earth models. The models are derived by inverting a large set of normal-mode centre-frequencies, quality factors, and geodetic data, including mass, moment of inertia, and tidal response.</p><p>The dataset is accompanied by a research paper titled "Self-consistent models of Earth's mantle and core from long-period seismic and tidal constraints" (DOI: <a href="https://doi.org/10.1093/gji/ggad254">10.1093/gji/ggad254</a>). The paper presents the methodology and findings related to the development of the models.</p><p>This version (V0.2) of the dataset replaces the previous version (V0.1). </p><p><strong>Dataset Details</strong></p><p>The dataset includes confidence intervals (CIs) for these parameters at 25%, 50%, and 75% levels that are representative of the uncertainty of the sampled model parameters. For example, the files <a href="https://zenodo.org/api/files/fa9f19f0-bf6a-41a8-8ca7-489a5b1b9c49/screm-25p-high.dat?versionId=b3b349c2-0a0b-48cc-b1f3-90137b8d1dcb">screm-25p-high.dat</a> and <a href="https://zenodo.org/api/files/fa9f19f0-bf6a-41a8-8ca7-489a5b1b9c49/screm-25p-low.dat?versionId=81db34f2-29f4-48aa-95c4-bb73b050a47f">screm-25p-low.dat</a> contain the upper and lower bound of the 25% CI sampled model range. A python plotting script is available, which plots the CIs.</p><p>The dataset files are provided in comma-separated values (CSV) format, containing the following columns:</p><ol><li><strong>Radius (km)</strong>: Radial distance from the center of the Earth.</li><li><strong>Depths (km)</strong>: Depth from the surface of the Earth.</li><li><strong>Density (g/cm³)</strong>: Radial density structure.</li><li><strong>P-wave velocity (vp) (km/s)</strong>: Radial compressional (P) wave velocity structure</li><li><strong>S-wave velocity (vs) (km/s)</strong>: Radial shear (S) wave velocity structure.</li><li><strong>Qkappa</strong>: Radial bulk attenuation structure.</li><li><strong>Qmu</strong>: Radial shear wave attenuation structure.</li><li><strong>Bulk Modulus (K) (GPa)</strong>: Radial bulk modulus structure.</li><li><strong>Shear Modulus (Mu) (GPa)</strong>: Radial shear modulus structure.</li><li><strong>Pressure (GPa)</strong>: Radial pressure profile.</li><li><strong>Temperature (K)</strong>: Radial geothermal profile.</li></ol><p><strong>Citation</strong></p><p>If you use this dataset in your research or refer to the models, please cite the following paper:</p><p><strong>Title:</strong> Self-consistent models of Earth's mantle and core from long-period seismic and tidal constraints<br><strong>Authors:</strong> J. Kemper, A. Khan, G. Helffrich, M. van Driel, D. Giardini<br><strong>Journal:</strong> Geophysical Journal International<br><strong>Year: </strong>2023<br><strong>DOI:</strong> <a href="https://doi.org/10.1093/gji/ggad254">10.1093/gji/ggad254</a></p><p>Please also acknowledge the dataset by providing a link to the Zenodo repository and its DOI.</p><p>Bibtex:<br>@article{Kemper_etal23,<br>author = {Kemper, J and Khan, A and Helffrich, G and van Driel, M and Giardini, D},<br>title = "{Self-consistent models of Earth's mantle and core from long-period seismic and tidal constraints}",<br>journal = {Geophysical Journal International},<br>pages = {ggad254},<br>year = {2023},<br>month = {06},<br>issn = {0956-540X},<br>doi = {10.1093/gji/ggad254},<br>url = {https://doi.org/10.1093/gji/ggad254},<br>} </p><p> </p>
Long-term response of wetland plant communities to management intensity, grazing abandonment, and prescribed fire
Isolated, seasonal wetlands within agricultural landscapes are important ecosystems. However, they are currently experiencing direct and indirect effects of agricultural management surrounding them. Because wetlands provide important ecosystem services, it is crucial to determine how these factors affect ecological communities. Here, we studied the long-term effects of land use intensification, cattle grazing, prescribed fires, and their interactions on wetland plant diversity, community dynamics, and functional diversity. To do this, we used vegetation and trait data from a 14-year-old experiment on 40 seasonal wetlands located within semi-natural and intensively managed pastures in Florida. These wetlands were allocated different grazing and prescribed fire treatments (grazed vs. ungrazed; burned vs. unburned). Our results showed that wetlands within intensively managed pastures have lower native plant diversity, floristic quality, evenness, higher non-native species diversity, and exhibited the most resource-acquisitive traits. Wetlands embedded in intensively managed pastures were also characterized by lower species turnover over time. We found that 14 years of cattle exclusion reduced species diversity in both pasture management intensities and had no effect on floristic quality. Fenced wetlands exhibited lower functional diversity and experienced a higher rate of community change both due to an increase in tall, clonal, and palatable grasses. The effects of prescribed fires were often dependent on grazing treatment. For instance, prescribed fires increased functional diversity in fenced wetlands but not in grazed wetlands. Our study suggests that cattle exclusion and prescribed fires are not enough to restore wetlands in intensively managed pastures and further highlights the importance of not converting semi-natural pastures to intensively managed pastures. Our study also suggests that grazing levels applied in semi-natural pastures maintained high plant dive
Short- And Long-Term Micro & Nano Particles Exposure to Estuarine Model Species at Variable Salinities
Micro (< 5mm) & Nano (1-1000 nm) plastic (MNP) particles are ubiquitous in the environment and have been shown to have a variety of effects on aquatic organisms. The effects of MNP exposure can vary depending on the type of MNP, the concentration of MNP, the duration of exposure, and the salinity of the water. This study used 5 plastic types including polyester (PE), polypropylene (PP), polylactic acid (PLA), polyethylene terephthalate (PETE) and tire particles (TP) in two forms, solid plastic particles and microfibers. To assess potential impacts on exposed organisms, early life stages of the estuarine indicator species Inland Silverside (Menidia beryllina) and mysid shrimp (Americamysis bahia) were exposed to three concentrations at micro- and nano-size fractions, and separately to leachate, across a 5-25 PSU salinity gradient. This exposure study was performed in longer term (21 days for Inland Silverside and 28 days for mysid shrimp) and shorter term (4 days for Inland Silverside and 7 days for mysid shrimp). Following MNP exposures of 7d (A. bahia) and 96 h (M. beryllina), behavioral assays were performed post-exposure from each treatment using a Danio Vision Observation Chamber (Noldus, Wageningen, the Netherlands) for the dark: light cycle as described previously (Siddiqui et al., 2022; Siddiqui et al., 2023; Mundy et al., 2021; Segarra et al., 2021). These behavior studies provide important information for risk assessments and policy making that can establish knowledge for MNPs risk.
Compiled long-term community composition datasets of primary producers and consumers in both freshwater and terrestrial communities
This data package consists of two files to study long-term changes in communities across a range of systems (freshwater and terrestrial) and organism types (from short-lived (sub annual) to long-lived species) that are both primary producers and consumers. We compiled many datasets from publicly available archives (41 datasets are from 14 LTER sites). All datasets must have had a measure of species level abundance to calculate more derived community ecological metrics beyond species richness. These data can be used to study community dynamics over space and time.
FISHPASS ASSESSMENT PLAN LONG-TERM MONITORING OF HYDROLOGIC AND WATER QUALITY DATA
The Great Lakes Fishery Commissions’ (GLFC) FishPass project seeks to reconnect the waterscape for only desired species (i.e., selective passage) by integrating a multitude of existing and novel passage techniques and technologies. The probability of a fish passing through a sorting system is dependent on environmental conditions and a fish’s motivation ─ its internal state in relation to environmental stimuli. While fish decision making abilities introduce complexity to the sorting operations, they also provide an opportunity to exploit behavioral tendencies and abilities to achieve selective sorting. The FishPass Assessment Plan details a monitoring program aimed at quantifying fish movement and sorting capabilities associated with both individual mechanisms and integrated sorting systems. The results of the monitoring program will be used to inform future adjustments to the selection of techniques and technologies and their configuration to optimize passage of desirable species while blocking and/or removing undesirable species. A key component to the Assessment Plan is the long-term monitoring of abiotic variables in and around FishPass. This data set contains the hydrologic (e.g., river discharge, water level) and water quality data (e.g., temperature, specific conductivity, conductivity, and turbidity) collected at mostly static stations throughout the Boardman/Ottaway River. The dataset is updated annually. These data are collected until the initiation and/or substantial completion of the FishPass structure. Collection of this type of data are expected to continue after FishPass construction completion but modifications to the extent and location of monitoring stations are anticipated. As a result, a new dataset will be updated in the future containing all long term hydrologic and water quality monitoring post construction. R. Swanson, GLFC Assessment Biologist, is primarily responsible for maintaining the monitoring equipment, data retrieval, quality assuran
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.