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12,871 results for “aging”
COVID-19 risk of death by age
<p><strong>This is a version of the plot without split into gender-adjusted risks. For the newer version with gender-adjusted curves, please visit </strong><em>https://zenodo.org/record/3787931</em><br> doi:10.5281/zenodo.3787931</p> <p>This figure plots the risk of death in COVID-19 adjusted by the age and derived from the case fatality data kindly collected by the team of data scientists and data engineers in the Kaggle project Data Science for COVID-19 in South Korea (DS4C) hosted at https://www.kaggle.com/kimjihoo/coronavirusdataset.</p> <p>The model for the plot was created with the release 2.1 of the Python & C library initially published on April 3, 2020 on GitHub at https://github.com/yuryatin/covid19_age_adjusted_mortality.</p> <p>Please, visit https://github.com/yuryatin/covid19_age_adjusted_mortality for more detailed description of the model and the source code.</p>
COVID-19 case fatality-derived risk of death adjusted by age and gender
<p>This figure plots the risk of death in COVID-19 adjusted by the age and gender, which was modeled with the case fatality data kindly collected by the team of data scientists and data engineers in the Kaggle project <em>Data Science for COVID-19 in South Korea (DS4C)</em>, which is hosted at https://www.kaggle.com/kimjihoo/coronavirusdataset.</p> <p>The model for the plot was built with the release 2.2 of the open-sourced Python & C library for macOS and Linux initially published under <strong>GPLv3</strong> license on April 3, 2020, on GitHub at https://github.com/yuryatin/covid19_age_adjusted_mortality.</p> <p>Please, visit <a href="https://github.com/yuryatin/covid19_age_adjusted_mortality"><strong>https://github.com/yuryatin/covid19_age_adjusted_mortality</strong></a> for more detailed description of the model and for the source code.</p>
Estonian Stone Age settlement sites: a dataset
<p>This dataset includes the list of Stone Age settlement sites in the territory of Estonia. The list was compiled from published sources, grey literature and existing database records for unpublished sites. The current revision (version 1) of the dataset includes sites from recent systematic surveys conducted until 2017 (with some exceptional sites found later). Only sites with known exact locations were included into the dataset.</p> <p>The sites are classified into four stages of the Stone Age: pre-pottery Mesolithic (9000–5200 cal. BC), Narva (5200–3900 cal. BC), Comb Ware (3900–1800 cal. BC) and Corded Ware (2800–2000 cal. BC). The classification is based on typo-chronology of find materials, also using existing radiocarbon and other dating methods, if possible. The number of sites is 410, with 244 pre-pottery Mesolithic sites, 39 sites with Narva pottery, 60 sites with Comb Ware and 67 sites with Corded Ware. As there is a row dedicated to every habitation period in a location the number of unique site locations is smaller.</p>
Building age map, Vienna, around 1920
<p><strong>This data respository</strong> includes the following datasets:</p> <ol> <li>Building stock map 1920 (BSM_1920.shp) and its attribute table (BSM_1920_attribute_table.csv)</li> <li>Areas out of scope 1920 (AOOS_1920.shp)</li> <li>Scope of analog building age map 1920 (SABAM_1920.shp)</li> </ol>
DETERMINING AGES OF APOGEE GIANTS WITH KNOWN DISTANCES - Full PDFs
<p>Supplementary data to Feuillet+ (2016, ApJ, arXiv:1511.04088):</p> <p>Using the APOGEE survey instrument and the NMSU 1m telescope, we observe a sample of bright, nearby, red giant stars with known distances measured by Hipparcos. By applying Bayesian analysis and hierarchical modeling, we determine individual stellar ages and the star formation histories of single alpha-abundance subsamples. The probability distribution functions (PDFs) and modeled star formation histories (SFHs) of all stars analyzed in this paper.</p> <p>Data included: APOGEE/2MASS ID, the age values for PDFs in log(age), the isochrone matching likelihood function as given in Equation 4 of paper, the age PDF of a Bayesian analysis using a flat SFH (Section 4.3), the hierarchically modeled SFH using an alpha-abundance dependent Gaussian+uniform model (Section 4.6), and the age PDF of an empirical Bayesian analysis using the hierarchically modeled SFH (Section 4.6). Individual ages of stars in the paper are taken as the mean of the age PDF, however, most PDFs are non-Gaussian, which introduces complicated errors into the selection of a single age.</p>
Great Ape Cerebral Aging - Expansion Relationship
<p>This contains data associated with the manuscript "The Uniqueness of Human Vulnerability to Brain Aging in Great Ape Evolution" https://www.biorxiv.org/content/10.1101/2022.09.27.509685v1</p> <p> </p> <p>The chimp.zip and IXI.zip contain data for the chimpanzee and human samples respectively. This includes the input matrix (subject x gray matter voxels), OPNMF bootstrap outputs, and OPNMF parcellaitons (2-40).</p> <p> </p> <p>The outputs.zip contains outputs from the analyses conducted for the manuscript using the code from https://github.com/viko18/GreatApe_Aging.</p> <p> </p> <p>The expansion_map.zip contains the modulated jacobians and templates following cross-species registration for the chimpanzee, baboon, and macaque templates.</p> <p> </p> <p>y_JunaChimp_brain.nii.gz is the deformtion field map from chimpanzee template space to human and iy_*.nii.gz is the inverse, so human to chimpanzee.</p> <p> </p> <p>Davi130_MNI_3mm_cortex.nii.gz is the avi130 chimpanzee parcellation in human MNI sapce.</p>
Phlorest phylogeny derived from Kitchen et al. 2009 'Bayesian phylogenetic analysis of Semitic languages identifies an Early Bronze Age origin of Semitic in the Near East'
<p>Cite the source of the dataset as:</p> <blockquote> <p>Kitchen A, Ehret C, Assefa S & Mulligan CJ. 2009. Bayesian phylogenetic analysis of Semitic languages identifies an Early Bronze Age origin of Semitic in the Near East. Proceedings of the Royal Society B: Biological Sciences, 270(1668), 2703-2710.</p> </blockquote>
Number of bovine animals tested by age group, reporting country and target group, 2022
<p>The tables contain the number of bovine animals tested by age group, reporting country and target group, 2020.</p>
Supplementary files for: A dynamic 2000–540 Ma Earth history: From cratonic amalgamation to the age of supercontinent cycle
<p>Supplementary materials for the Earth-science Reviews paper 'A dynamic 2000–540 Ma Earth history: From cratonic amalgamation to the age of supercontinent cycle'. </p> <p>Supplementary Material 1 – Palaeomagnetic pole list for the ca. 2000–540 Ma interval.<br> Supplementary Material 2 – IGCP 440 pre-700 Ma geotectonic database (with minor corrections made) in shapefiles format<br> Supplementary Material 3 – Neoproterozoic sedimentary facies point data of Li et al. (2013) in shapefile format<br> Supplementary Material 4 – Generalised global large igneous province (LIP) database for 2010–0 Ma (after Ernst et al., 2021) in both shapefile and Excel formats<br> Supplementary Material 5 – Global passive margin database of (Bradley, 2008) in shapefile format<br> Supplementary Material 6 – Global orogen database of Condie et al. (2021) with minor modifications and in shapefile format<br> Supplementary Material 7 – Global 2000–540 Ma full-plate animation following the extended orthoversion principle, Scenario Ia (0-90W-0)<br> Supplementary Material 8 – Global 2000–540 Ma full-plate animation following the extended orthoversion principle, Scenario Ib (0-90E-0)<br> Supplementary Material 9 – 2000–540 Ma global animation highlighting the occurrence of LIP events in time and space, including possible plume centres.<br> Supplementary Material 10 – GPlates project files for the two alternative global 2000–540 Ma full-plate animations with associated geotectonic databases</p>
Data and code for 'Age truncation due to disease shrinks metapopulation viability for amphibians'
<p>This repository provides all data and R code from the analysis for the following paper:</p> <p>Heard, G.W., Scroggie, M.P., Hollanders, M., and Scheele, B.C. (in press). Age truncation due to disease shrinks metapopulation viability for amphibians. <em>Journal of Applied Ecology</em>. </p> <p>The data are provided as a series of .csv files. A GRD file is provided for the landscape rasters. R code is provided separately for each of the following components:</p> <p>1. A script to complete regression modelling of age structure data for populations of the focal species pre- and post-Bd, plus estimation of adult survival rates from the age structure data using the 'catch curve' approach ('Age_structure_analysis.R').</p> <p>2. A script to generate the sample landscapes used for simulations of metapopulation dynamics for the pre- and post-Bd time periods ('Derive_landscape_rasters.R').</p> <p>3. A script with functions for simulating metapopulation dynamics with the aid of the STEPS R package ('STEPS_model.R').</p> <p>4. A script to run the metapopulation simulations across all the demographic and connectivity scenarios, where connectivity scenarios are defined by the sample landscapes ('Run_STEPS_simulations.R'). </p> <p>5. A script to fit logistic regression models to the outcomes of the metapopulation simulations (extinction versus persistence) ('Metapop_sims_analysis_GLM.R').</p> <p>6. A script to fit multivariate normal hypervolumes to the outcomes of the metapopulation simulations (extinction versus persistence) ('Metapop_sims_analysis_MVNH.R').</p> <p>7. A script to generate each of the figures in the manuscript, plus Table 2 which requires post-hoc data compilation ('Generate_figures.R'). </p> <p>In combination, the data files and scripts allow all analyses from the paper to be reproduced. </p>
The Femern-project: a large-scale excavation of a Stone Age landscape - supplementary data
<p>This dataset contains all radiocarbon dates from the Femern project.</p> <p>Please cite the dataset as: </p> <p>Måge, B.T., Groß, D., Kanstrup, M. 2023. The Femern-project: a large-scale excavation of a Stone Age landscape. In: Groß, D. and Rothstein, M.: Changing Identity in a Changing World. Archaeological Studies on Human Interaction in Northern Europe around 4000 cal BC. Leiden: Sidestone, supplementary material.</p> <p>19.02.2024: Dataset updated: Wrong species ID in original dataset for AAR-27426</p>
Age-depth model ensembles for SISAL v3 speleothem records
<p>Depth-age model ensembles created for the SISAL database v3 (version for publication), in supplement to <strong><a href="https://essd.copernicus.org/preprints/essd-2023-364/" target="_blank" rel="noopener">Kaushal et al., 2024</a></strong> and building on <a href="https://www.earth-syst-sci-data-discuss.net/essd-2020-39/">Comas-Bru, Rehfeld, Roesch et al., 2020</a>.</p> <p>This upload includes ensemble data for 5 methods (interpolation, linear regression, copRa, Bchron and Bacon) created following the protocol in previous versions but for newly included entities in the database.</p> <p>Each file contains a matrix with the first column giving the row number, the second the SISAL v3 sample ID, the third the depth in the speleothem (in mm), and the fourth to 2003rd column contains the 2000 age model ensemble members.</p>
Investigating the ageing process of polymer modified bitumen using a modified Thin-Film Oven Test in the aspect of recycling purpose within Weave-UNISONO 2021 project, NCN project No 2021/03/Y/ST8/00079
<div><strong>Summary:</strong></div> <div>One polymer-modified bitumen PMB 25/55-60 was tested in two stages: original and after the modified Thin-Film Oven Test (TFOT). The time ranges from 1h-5h, and temperatures from 120°C-200°C were used. The Fourier-Transform Infrared (FTIR) Spectroscopy and Dynamic Shear Rheometer (DSR) with parallel plates were conducted. Test temperatures range from 30–70°C for a 25 mm diameter plate and 0–30°C for an 8 mm plate with 10°C intervals and angular frequency range of 0.1, 1.0, and 10 Hz.</div> <div> </div> <div> </div> <div><strong>The dataset includes:</strong></div> <div>Basic characteristics of bituminous binder (R&B Temperatur, Penetration), CSV raw data:</div> <div> <ul> <li>01 - SP Pen.csv</li> </ul> </div> <div> </div> <div>Dynamic shear rheometer (Temperatures 0-70 °C, Angular Frequency 0.1Hz, 1.0Hz, 10 Hz, Complex Shear Modulus, Phase Angle):</div> <ul> <li>02.1 - DSR Rheology_Unaged.csv</li> <li>02.2 - DSR Rheology_2h_140C.csv</li> <li>02.3 - DSR Rheology_2h_200C.csv</li> <li>02.4 - DSR Rheology_5h_140C.csv</li> <li>02.5 - DSR Rheology_5h_200C.csv</li> </ul> <div> </div> <div>FTIR - Fourier-Transform Infrared Spectroscopy </div> <div> <ul> <li>OPUS Spectroscopy files.zip</li> </ul> </div> <div> </div> <div>--- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- ---</div> <div>to open the OPUS files, please go to the © Bruker webpage and download the free OPUS Viewer.</div> <div>https://www.bruker.com/en/products-and-solutions/infrared-and-raman/opus-spectroscopy-software/downloads.html</div> <div>--- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- ---</div> <div> </div>
Martian meteorite ejection ages compilation
<p>This dataset is a compilation of cosmic ray exposure (CRE) ages and terrestrial ages of martian meteorites (shergottites, nakhlites, chassignites, orthopyroxenite, and regolith breccia) in published literature as of July 2023. Igneous crystallization ages are listed where available; the dataset only lists meteorites with ejection age (CRE age with or without terrestrial age) data. The compilation is an update of an earlier version partially included in Udry et al. (2020). For meteorites with multiple reported CRE ages and terrestrial ages (the latter where available), a preferred age is given either based on an earlier compilation (in the 'Compilation Reference' field) or is calculated as the arithmetic average of multiple reported ages (in the 'Data Reference' field; for CRE ages only). In the latter case, the 'Compilation Reference' field is marked with 'this compilation'. Paired stones are combined under one entry.</p> <p>Note that this compilation is not an exhaustive listing of all CRE age, terrestrial age, or igneous crystallization age data reported for martian meteorites.</p> <p>This dataset contains two files: </p> <ol> <li>A spreadsheet (.xlsx) containing meteorite names, types, ejection age groups, CRE ages, terrestrial ages, ejection ages, data references, compilation references, list of nuclides measured, igneous crystallization ages, data references, and compilation references.</li> <li>A document (.docx) containing a list of references cited in this compilation.</li> </ol> <p><strong>References</strong></p> <p>C. D. K. Herd <em>et al.</em>, The source craters of martian meteorites: insights from a multi-method approach. <em>Lunar. Planet. Sci. Conf. </em><strong>LVI</strong>, abstract #2044 (2024).</p> <p>A. Udry <em>et al.</em>, What martian meteorites reveal about the interior and surface of Mars. <em>Journal of Geophysical Research: Planets</em> <strong>125</strong>, e2020JE006523 (2020).</p>
CLaMS mean age of air tracers for 15/01/2011 interpolated on simulated CAIRT retrieval grid
<p>The dataset contains simulation results from the Chemical Lagrangian Model of the Stratosphere (CLaMS) for January 15, 2011. These results are interpolated onto the simulated retrieval grid of the Changing-Atmosphere Infrared Tomography Explorer (CAIRT). The data includes six trace gases (SF₆, N₂O, CFC-11 (F11), CFC-12 (F12), HCFC-22 (F22), and CH₄) and the "exact" model mean age of air (BA). The file is provided in NetCDF format.</p>
Splicing accuracy varies across human introns, tissues, age and disease
<p>Alternative splicing impacts most multi-exonic human genes. Inaccuracies during this process may have an important role in ageing and disease. Here, we investigated splicing accuracy using RNA-sequencing data from >14K control samples and 40 human body sites, focusing on split reads partially mapping to known transcripts in annotation. We show that splicing inaccuracies occur at different rates across introns and tissues and are primarily affected by the abundance of core components of the spliceosome assembly and its regulators. Using publicly available data from RNA-knockdowns and CLIP-seq binding sites of numerous spliceosomal components and related regulators, we demonstrated the importance of RNA-binding proteins in splicing accuracy. We found that age is positively correlated with a global decline in splicing fidelity, mostly affecting genes implicated in neurodegenerative diseases. We found further support for the latter by observing a genome-wide increase in splicing inaccuracies in samples affected with Alzheimer's disease as compared to neurologically normal individuals. This in-depth characterisation of splicing has important implications for our understanding of the role of inaccuracies in ageing and human disease, particularly in neurodegenerative disorders.</p>
COVID-19 vaccination data in Israel by age over time until August 2021
<p>COVID-19 vaccination data in Israel processed to show vaccination by age over time. These datasets are derived from publicly available Ministry of Health data, but processed for analytics about uptake in different age groups over time. They cover the mass vaccination campaign for COVID-19 until August 2021. The campaign consisted of the administration of multiple doses of the Pfizer vaccine.</p>
Data and code for 'Age structure of amphibian populations with endemic chytridiomycosis, across climatic regions with markedly different infection risk'
<p>This repository provides all data and R code from the analysis presented in the following paper:</p> <p>Turner, A., Heard, G., Hall, A., Wassens, S. (in review). Age structure of amphibian populations with endemic chytridiomycosis, across climatic regions with markedly different infection risk.</p> <p>The data are provided as a series of .csv files, R script and two zip folders of R packages (Surv_mod and VB_mod)</p> <p>1. <strong>Skeleto_dat_ready_Jan2021.csv</strong> Data from frog surveys conducted by Anna Turner</p> <p>2. <strong>Geoffs_data.csv</strong> Data from frog surveys conducted by Geoff Heard</p> <p>3. <strong>Environmental_variables_skeleto.csv</strong> Environmental data collected during surveys </p> <p>4. <strong>sk.dat_July21.csv</strong> Collated data from Anna and Geoff - created by 'Data_collation_for_analysis_2.R' ready for analysis</p> <p>5. <strong>Variables_that_are_highly_correlated_with_each_other_season_wide.csv</strong> Testing for correlation</p> <p>6. <strong>Model_structure_skeleto_2.csv </strong>creates model structure for analysis</p> <p>7. <strong>Model_selection_statistics_June_21.csv </strong>Output from model</p> <p>R code is provided seperately for each of the following components:</p> <p>1. <strong>Data_collation_for_analysis_2.R</strong> Collating data from Anna and Geoffs datasets</p> <p>2. <strong>Skeleto_analysis_5.R - </strong>First uses regression modelling to explore factors correlated with variation in age</p> <p> - Following Scheele et al. (2016) regression models with a poisson distribution</p> <p> - Use bayesian non-linear regression to fit the Von Bertalanffy growth model to size-at-age data</p> <p> - Plots male and female growth curves</p> <p> - Uses catch curve approach to estimate survival from best fitting regression model following Scroggie (2012) but with bayesian implementation</p>
ArmmA (ARmorial Monumental du Moyen-Age)
<p>Voir le site web <a href="https://armma.saprat.fr">Armma</a>.</p> <p> </p> <p>Ce travail a bénéficié d'une aide de l'Etat gérée par l'Agence Nationale de la Recherche au titre du Programme d'Investissements d'Avenir portant la référence ANR-21-ESRE-0005 (ÉquipEx Biblissima+)</p>
Dataset for the identification of hypertension in school-aged children from Gqeberha, South Africa
<p>Dataset used to evaluate and compare different international references to identify hypertension among South African school-aged children from disadvantaged communities.</p> <p>It encompasses anonymized, unique, identification numbers, anthropometric and blood pressure measures, as well as blood pressure percentiles and the assigned categories derived from four different reference populations (American, German, global and the study population).</p>
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Allen Brain Atlas
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International Brain Laboratory public data
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OpenNeuro
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