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.
12,871
datasets available to search
ShareScore release 0.9.0
Dataset results
12,871 results for “aging;”
Fig. 6 in Age, Growth and Reproduction of Coryphaena hippurus (Linnaeus, 1758) in Maltese Waters, Central Mediterranean
Fig. 6: Von Bertalanffy growth curve for males and females
Fig. 3 in Age determination of the Mongolian wild ass (Equus hemionus Pallas, 1775) by the dentition patterns and annual lines in the tooth cementum
Fig. 3. Occurrence of deciduous and permanent first premolars in the Mongolian wild ass skull.
Fig. 1 in Age determination of the Mongolian wild ass (Equus hemionus Pallas, 1775) by the dentition patterns and annual lines in the tooth cementum
Fig. 1. First lower incisor (A) and its longitudinal section (B) with annual lines (C).
Human genetic variants and age are the strongest predictors of humoral immune responses to common pathogens and vaccines
<p>Online Supplementary Dataset of the manuscript "Human genetic variants and age are the strongest predictors of humoral immune responses to common pathogens and vaccines"</p>
A combined experimental/numerical investigation on hygrothermal aging of fiber-reinforced composites
<p>The x-ray scan data and videos used in the following paper to where the references should be given:</p> <p>Rocha, I.B.C.M., van der Meer, F.P., Raijmaekers, S., Lahuerta, F., Nijssen, R.P.L., Mikkelsen, L.P., Sluys, L.J., A combined experimental/numerical investigation on hygrothermal aging of fiber-reinforced composites, European Journal of Mechanics / A Solids, doi: <a href="https://doi.org/10.1016/j.euromechsol.2018.10.003">https://doi.org/10.1016/j.euromechsol.2018.10.003</a>, 2018.</p> <p>More details on the scans can be found in the paper.</p> <p>The following relations is between the files and the figures from the paper</p> <p>Fig 7: YouTube:<a href="https://youtu.be/o4NLVGRgTW8">https://youtu.be/o4NLVGRgTW8</a> File:<a href="https://zenodo.org/api/files/f43d3d15-fc47-492f-b805-572e70aae812/LFoV-Ref-036_036-LFOV-2.5mm-x4_recon.mpg?versionId=d8c523f6-9cf7-4e38-8e8c-1e6fe0bd2876">LFoV-Ref-036_036-LFOV-2.5mm-x4_recon.mpg</a><br> Fig 8a: YouTube:<a href="https://youtu.be/hbxVToJD7Mc">https://youtu.be/hbxVToJD7Mc</a> File:<a href="https://zenodo.org/api/files/f43d3d15-fc47-492f-b805-572e70aae812/SFoV-Ref-Surf-165b-side-0.5-20x_recon.mpg?versionId=edb0f8c2-6eb8-42c1-a968-ed44f247f53a">SFoV-Ref-Surf-165b-side-0.5-20x_recon.mpg </a><br> Fig 8b: YouTube:<a href="https://youtu.be/keVhRX78m7o">https://youtu.be/keVhRX78m7o</a> File:<a href="https://zenodo.org/api/files/f43d3d15-fc47-492f-b805-572e70aae812/SFoV-Ref-Center-165b-center-0.5-20x_recon.mpg?versionId=ec6fb064-14f2-40f4-9aba-e3eb9416e427">SFoV-Ref-Center-165b-center-0.5-20x_recon.mpg </a><br> Fig 9: YouTube:<a href="https://youtu.be/N-ji_cDbEXc">https://youtu.be/N-ji_cDbEXc</a> File:<a href="https://zenodo.org/api/files/f43d3d15-fc47-492f-b805-572e70aae812/LFoV-65C-179a-2863-179a_recon.mpg?versionId=527e02a2-9a69-4ad5-bc51-a6096dd0ecc6">LFoV-65C-179a-2863-179a_recon.mpg </a><br> Fig 10a: YouTube:<a href="https://youtu.be/T-Yq3fkGxzA">https://youtu.be/T-Yq3fkGxzA</a> File:<a href="https://zenodo.org/api/files/f43d3d15-fc47-492f-b805-572e70aae812/SFoV-65C-Surf-179a-center-and-side_179a-side-0.5mm-x20_recon.mpg?versionId=9a15a8ad-c55b-44d0-bece-6ee8f093179c">SFoV-65C-Surf-179a-center-and-side_179a-side-0.5mm ...</a><br> Fig 10b: YouTube:<a href="https://youtu.be/4fZqXQY2VOs">https://youtu.be/4fZqXQY2VOs</a> File:<a href="https://zenodo.org/api/files/f43d3d15-fc47-492f-b805-572e70aae812/SFoV-65C-Center-179a-center-and-side_179a-center-0.5mm-x20_recon.mpg?versionId=33951d51-6763-4cf1-a88b-8e793813d4be">SFoV-65C-Center-179a-center-and-side_179a-center-0 ...</a><br> Fig 11a: YouTube:<a href="https://youtu.be/4L8BCa6tgFA">https://youtu.be/4L8BCa6tgFA</a> File:<a href="https://zenodo.org/api/files/f43d3d15-fc47-492f-b805-572e70aae812/SFoV-50C-Surf-2863-165a-side-0.5-20x_recon.mpg?versionId=147fb3ff-3b7a-4aed-971d-8085bcc821da">SFoV-50C-Surf-2863-165a-side-0.5-20x_recon.mpg </a><br> Fig 11b: YouTube:<a href="https://youtu.be/uBWqHxYG3GU">https://youtu.be/uBWqHxYG3GU</a> File:<a href="https://zenodo.org/api/files/f43d3d15-fc47-492f-b805-572e70aae812/SFoV-50C-Center-Spec-2863-165a-2863-165a-middle-0.5-20x_recon.mpg?versionId=f09a97f4-91a2-40a4-9109-4d2ef518933b">SFoV-50C-Center-Spec-2863-165a-2863-165a-middle-0. ...</a></p> <p> </p> <p> </p>
Data for 'Priors and Posteriors in Bayesian Timing of Divergence Analyses: the Age of Butterflies Revisited'
<p>Data and results for Chazot et al. (2018) 'Priors and Posteriors in Bayesian Timing of Divergence Analyses: the Age of Butterflies Revisited.'</p> <p>S1. List of taxa and Genbank accession codes.</p> <p>S2. Molecular matrix for the core analysis (S2a), the reduced dataset (S2b) and the dataset with a mitochondrial fragment (S2c).</p> <p>S3. RAxML topology (S3a) and time-calibrated tree (S3b) obtained from the core analysis. In S3a, numbers at the nodes indicate rapid-bootstrap support values. In S3b, node ages are the median of node age posterior distributions.</p> <p>S4. Tree obtained when using only deep-level fossil calibrations. Node ages are the median of node age posterior distributions.</p> <p>S5. Tree obtained when using only shallow-level fossil calibrations. Node ages are the median of node age posterior distributions.</p> <p>S6. Tree obtained from the reduced dataset. Node ages are the median of node age posterior distributions.</p> <p>S7. Tree obtained when using exponential fossil calibration priors. Node ages are the median of node age posterior distributions.</p> <p>S8. Tree obtained when adding a mitochondrial gene fragment. Node ages are the median of node age posterior distributions.</p> <p>S9. Tree obtained when using fossil information only modeled using lognormal priors. Node ages are the median of node age posterior distributions.</p> <p>S10. Tree obtained when using the host-plant ages obtained from Foster et al. (2017). In S10a node ages are the median of node age posterior distributions, while in S10b the node ages are the mode the mode of the kernel density estimate of the posterior distribution.</p> <p>S11. Tree obtained when using a Yule prior instead of Birth-Death tree prior. Node ages are the median of node age posterior distributions.</p>
Is tree age or tree size reducing height increment in Abies alba Mill. at its southernmost distribution limit?
<p>Many factors limit height increment of trees when age and size increase in large-statured tree species. Height-diameter allometric relationships are commonly used measures of tree growth.</p> <p>The data were collected in a silver fir forest located in Southern Italy, at the southernmost distribution limit for this species. Through a stratified random sampling, 100 trees were selected. All the selected trees were then felled and the total tree height, height increments (internode distances), diameter at breast height, and diameter increments (ring widths) were measured.</p> <p>Conventional methods for estimating the current annual increment of stand volume are based on the uncertain assumption that height increment decreases with tree age. Conversely, size, rather than age, should be accounted for the observed senescence-related declines in relative growth rate and, consequently, implemented in silvicultural manuals. Results stem from a study on Abies alba Mill. at its southern limit of distribution.</p>
Age distribution Austria vs. Vienna
<p>The Figures produced from the Data Stewardship Project.</p>
Russian contact matrices by age
<p>We provide contact matrices by 5-year age groups for Tomsk, Russia relevant for the transmission of airborne infectious diseases. The dataset is provided in csv format. In the folder "total", we report the overall contact matrix; in folder “by_relation”, we report contact matrices by relation between the study participant and her/his contacts; in the folder "by_social_setting", we report the contact matrices by the social setting where the recorded contact took place.</p> <p>This dataset is associated with the publication: M. Ajelli, M. Litvinova. Estimating contact patterns relevant to the spread of infectious diseases in Russia. J Theor Biol 2017; 419:1-7.</p>
Data for the paper "Uncovering the birth of the Milky Way through accurate stellar ages with Gaia", accepted in Nature Astronomy
<p>Data files used in the paper that contain information that is not available in public catalogues, and that is necessary to produce the figures.</p> <p>The extended dataset consists of: i) (<strong>a</strong> and <strong>b</strong> panels of figure 1): two tables directly retrieved from the Gaia archive as described in Methods, supplemented by extinction information on a star-by-star basis; the code used to interpolate the 3-D extinction maps by Lallement et al. (2018) can be retrieved from \url{https://github.com/edober/dust_maps_3d}. ii) (<strong>c</strong> and <strong>d</strong> panels of Figure 1, Figure 2 and panel <strong>a </strong>of Figure 3): two tables with the derived solution CMDs. Two files with the necessary data to define the boxes used to select stars in the blue and red sequences of the halo CMD are also included. iii) (panel <strong>b</strong> of Figure 3): necessary tables with the age, metallicity and velocity data for the main progenitor and accreted satellite for realisation g15784 of the MaGICC program (Brook et al. 2012). The complete information on the final timestep of that simulation, together with scripts to read and plot the data are also included in the extended dataset.</p> <p>A explanatory README is contained within the tar file.</p>
Development of a Standard Test Method for Characterization of Asphalt Modifiers and Aging-Related Degradation Using an Extensional Rheometer
<p>Corresponding data set for Tran-SET Project No. 17BLSU01. Abstract of the final report is stated below for reference:</p> <p>"An extensional deformation test method using a Sentmanat Extensional Rheometer (SER) fixture inside a Dynamic Shear Rheometer (DSR) is developed in this study to investigate the degradation of the polymer due to aging and to investigate the effect of modifier type. A relationship between different percentages of modifier and ductility of the modified binder is also investigated. The sample geometrics used in this study are 1 mm 0.72 mm and 3 mm 0.72 mm. A total of one hundred and sixty-two samples were tested. Three modifiers Styrene-Butadiene-Styrene (SBS), Polyphosphoric Acid (PPA) and latex were used. One PG 76-22, one PG 64-22 and one polymer-modified asphalt emulsion (PAME) were used. First peak elongation force, (F1) is the binders’ stiffness and Second peak elongation force, (F2) is the polymer characteristics. F2 is more visible comparatively at the higher temperature. In most cases, F2 reduces after Rolling Thin Film Oven (RTFO) and Pressure Aging Vessel (PAV) aging. To normalize the stiffness effect of F1 on F2, in this study F2/F1 was used to analyze aging susceptibility of modifiers. All the testing temperatures used in this study exhibited a reduction in F2/F1 due to RTFO aging and further reduction due to PAV aging. Therefore, through this study, it is recommended that this parameter can be used to determine aging susceptibility of polymer in a polymer-modified asphalt binder. F2 is only obtained from the SBS and latex modified binders and emulsions. Addition of PPA did not show any F2, making SBS the most effective modifier among SBS, PPA and latex. F2 has a linear correlation with the percent of the polymer in the PMAE, SBS modified PG 64-22, SBS and PPA modified PG 64-22 and latex modified PG 64-22 with R2 values equal to 0.9934, 0.9323, 0.9893 and 0.9535 respectively, indicating extensional deformation test with SER very promising. Ductility analyses using final angular strain values indicate that modifiers increase ductility significantly while aging reduces ductility. Additional research is required for testing ultra-violet (UV) aged sample, and a DSR-based SER test specification will be developed subsequently."</p>
Dataset from 'Klever, L., Voudouris, D., Fiehler, K., & Billino, J. (2019). Age effects on sensorimotor predictions: What drives increased tactile suppression during reaching? Journal of Vision, 19(9):9, 1-17. doi:10.1167/19.9.9
<p>Dataset associated with the following publication:</p> <p>Klever, L., Voudouris, D., Fiehler, K., & Billino, J. (2019). Age effects on sensorimotor predictions: What drives increased tactile suppression during reaching? Journal of Vision.</p> <p>--------------------------------------------------------------</p> <p>We provide two files; one data file contains data on which analyses are based, the other one gives the column labels for the data file.</p> <p>-------------------------------------------------------------</p> <p>For further questions, please contact:<br> lena.klever[at]psychol.uni-giessen.de</p> <p> </p>
Age determination of galactic B-type stars in double-lined eclipsing binaries
<p>We present the results of age determination for galactic B-type main sequence stars which are components of double-lined eclipsing binaries. Only detached systems are considered. We analyze 38 binary systems that meet such criteria. The analysis is based on evolutionary computations and we consider that the age is determined if there is a common value from the radius−age diagrams and the agreement in the position of both components in the Hertzsprung-Russell diagram. In some cases, to meet these two conditions, it was necessary to adjust the value of the metallicity, Z or/and the parameter of overshooting from the convective core, αov. We determine the consistent age for 33 binaries out of 38. Besides, we made an extensive computations and for each system we give the range of αov and Z, for which the consistent solutions exist. The age of the studied B-type main sequence stars ranges, as counted from the Zero Age Main Sequence, from about 2.5 Myr to about 200 Myr.</p>
Dataset from: Transport and water age dynamics in soils: a comparative study of spatially-integrated and spatially-explicit models
<p>This dataset contains high-resolution vegetated lysimeter experimental dataset carried out in EPFL, Lausanne, Switzerland in March-August 2016. The lysimeter is 100 cm long with a diameter of 120 cm. During this experiment, a simultaneous spike injection of five different solutes (2,5-DFBA, 2-TFMBA, 3,4-DFBA, 2,6-DFBA, 3-TFMBA) took place on the 3rd of March 2016 at 14:00 in an hour. The solutes' mass recovery at the bottom of lysimeter was observed for these solutes.</p> <p>This dataset contains three files which are described in the following:</p> <ul> <li>"hydrologic_data.dat" contains the hourly fluxes (precipitation, irrigation, evapotranspiration measured from load cells, and the water draining at the bottom of lysimeter ) in mm/hr between the 19th of Feb-the 1st of Sep 2016.</li> <li>"tracer_data.dat" contains the tracer concentration observed at the bottom of lysimeter in mg/L. These samples are collected at variable frequencies with an approximate average of 1.5 samples per day.</li> <li>"additional_data.dat" informs you on dry mass and soil volume in the lysimeter, vegetation type, and volume of injection per solute.</li> </ul> <p> </p>
Code and data to reproduce the results of the paper: "Land Use Patterns and Climate Change---A Modeled Scenario of the Late Bronze Age in Southern Greece"
<p>Code and data to reproduce the results of Knitter et al. (2019): Land Use Patterns and Climate Change---A Modeled Scenario of the Late Bronze Age in Southern Greece. ERL.</p>
The Ubiquitin Ligase WWP1 Contributes to Shifts in Matrix Proteolytic Profiles and a Myocardial Ageing Phenotype with Diastolic Heart Failure
<p><strong><em>Aims</em></strong>. Ubiquitylation is a key event that regulates protein turnover, and induction of the ubiquitin ligase E3 WWP1 has been associated with age. Left ventricular hypertrophy (LVH) commonly occurs as a function of age and can cause heart failure with a preserved ejection fraction (EF; HFpEF). We hypothesized that overexpression (O/E) of WWP1 in the heart would cause LVH as well as functional and structural changes consistent with the ageing HFpEF phenotype.</p> <p><strong><em>Methods and Results.</em></strong> Global WWP1 O/E was achieved in mice (n=11) and echocardiography (40 MHz) performed to measure LV mass, EF, Doppler velocities (early-E, late/atrial-A), myocardial relaxation (E’), and isovolumetric relaxation time (IVRT) at 4, 6, and 8 weeks. Age matched wild type animals (n=15) were included as referent controls. LV EF was identical (60+1% vs 60+1%, p>0.90) with no difference in LV mass (67+3 vs 75+5, p>0.25) at 4 weeks. LVH and diastolic dysfunction occurred with WWP1 O/E wherein LV mass increased by over two-fold, E/A fell (impaired passive filling), and E/E’ was lower and IVRT prolonged (impaired LV relaxation). Collagen percent area increased by over two-fold with WWP1 O/E and increased expression of determinants of fibrosis and growth (qPCR) were also concomitantly increased.</p> <p><strong><em>Conclusion.</em></strong> Inducing WWP1 expression caused LVH with significant diastolic dysfunction, consistent with the HFpEF phenotype. Thus, targeting the WWP1 pathway may be a novel therapeutic target for this intractable form of HF associated with ageing</p>
Sea whip coral Leptogorgia virgulata in the Mid-Atlantic Bight: Colony complexity, age, and growth
<p>Datasets for the analyses described in the submitted publication: Sea whip coral <em>Leptogorgia virgulata </em>in the Mid-Atlantic Bight: Colony complexity, age, and growth. </p>
Rotary querns made of basaltic lava during the Roman Iron Age in the north-west European Barbaricum
<p>Catalogue of basaltic lava fragments. Compiled in 2016 for a Master thesis at the Christian-Albrechts University Kiel by Jonas Enzmann.</p> <p>The literature quotes and the article are published under:</p> <p>Enzmann, J. 2019: Die Handdrehmühlen aus Eifeler Basaltlava im nordwesteuropäischen Barbaricum während der Römischen Kaiserzeit – eine Diskussion zu überregionalen Verbreitungsrouten und -mechanismen auf Grundlage von Transportzonen. Siedlungs- und Küstenforschung im südlichen Nordseegebiet 42. 57-194.</p> <p>Enzmann, J. 2019: Rotary querns made from Eifel basaltic lava in the north-west European Barbaricum during the Roman Iron Age – A discussion about supra-regional exchange routes and mechanisms based on transport zones. Settlement and Coastal Research in the Southern North Sea Region 42. 57-194.</p>
Number of bovine animals tested by age group, reporting country and target group, 2018
<p>The tables contain the number of bovine animals tested by age group, reporting country and target group, 2018</p>
Fig. 4 in The Study Of Age-Related Variability Of Pigmentation Patterns Of The Shells Of Dreissena Polymorpha (Bivalvia, Dreissenidae) From Different Parts Of It'S Range
Fig. 4. Frequences of main pattern types at different age zones on zebra mussel shells.
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.