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9,277 results for “ETS”
PM_047009_F_Prunet_et_Bellpuig
<u>File Name</u>: PM_047009_F_Prunet_et_Bellpuig.jpg <br><u>Sublocation</u>: Église de la Trinité <br><u>Location</u>: Prunet-et-Bellpuig <br><u>Province</u>: Occitanie, Pyrénées-Orientales <br><u>Country</u>: France <br><u>Header</u>: Vue du site et l'église <br><u>Description</u>: Church (Église de la Trinité) The site Romanesque 12th century (?) <br><u>Keywords</u>: Cultural heritage, Europe, France, Historic site, Monuments, My photography, Occitanie, Prunet-et-Bellpuig, Pyrénées-Orientales, Romanesque, Romanesque Catalonia, Styles, Thematic <br><br><u>Author</u>: Photo: Paul M.R. Maeyaert <br><u>Copyright</u>: Paul M.R. Maeyaert <br>
PM_047020_F_Prunet_et_Bellpuig
<u>File Name</u>: PM_047020_F_Prunet_et_Bellpuig.jpg <br><u>Sublocation</u>: Église de la Trinité <br><u>Location</u>: Prunet-et-Bellpuig <br><u>Province</u>: Occitanie, Pyrénées-Orientales <br><u>Country</u>: France <br><u>Header</u>: Extérieur, la porte <br><u>Description</u>: Church (Église de la Trinité) The entrance door Ironwork Romanesque <br><u>Keywords</u>: Architecture, Cultural heritage, Cultural property, Door/gate/door lock/attributes, Europe, France, Ironwork, Monuments, My photography, Occitanie, Prunet-et-Bellpuig, Pyrénées-Orientales, Romanesque, Romanesque Catalonia, Styles, Techniques <br><br><u>Author</u>: Photo: Paul M.R. Maeyaert <br><u>Copyright</u>: Paul M.R. Maeyaert <br>
PM_047010_F_Prunet_et_Bellpuig
<u>File Name</u>: PM_047010_F_Prunet_et_Bellpuig.jpg <br><u>Sublocation</u>: Église de la Trinité <br><u>Location</u>: Prunet-et-Bellpuig <br><u>Province</u>: Occitanie, Pyrénées-Orientales <br><u>Country</u>: France <br><u>Header</u>: Extérieur <br><u>Description</u>: Church (Église de la Trinité) Exterior Northeast, the apse Romanesque 12th century (?) <br><u>Keywords</u>: Cultural heritage, Europe, France, Monuments, Occitanie, Prunet-et-Bellpuig, Pyrénées-Orientales, Romanesque, Romanesque Catalonia, Styles <br><br><u>Author</u>: Photo: Paul M.R. Maeyaert <br><u>Copyright</u>: Paul M.R. Maeyaert <br>
PM_047017_F_Prunet_et_Bellpuig
<u>File Name</u>: PM_047017_F_Prunet_et_Bellpuig.jpg <br><u>Sublocation</u>: Église de la Trinité <br><u>Location</u>: Prunet-et-Bellpuig <br><u>Province</u>: Occitanie, Pyrénées-Orientales <br><u>Country</u>: France <br><u>Header</u>: Extérieur, la porte <br><u>Description</u>: Church (Église de la Trinité) The entrance door Ironwork Romanesque <br><u>Keywords</u>: Architecture, Cultural heritage, Cultural property, Door/gate/door lock/attributes, Europe, France, Monuments, My photography, Occitanie, Prunet-et-Bellpuig, Pyrénées-Orientales, Romanesque, Romanesque Catalonia, Styles <br><br><u>Author</u>: Photo: Paul M.R. Maeyaert <br><u>Copyright</u>: Paul M.R. Maeyaert <br>
Data needed to reproduce the flood hazard modeling of Pollack et al., 2024
<p>This repository contains some of the data needed (Data_Flood_Modeling) to reproduce the flood hazard modeling of Pollack et al., 2024 "[Funding rules that promote equity in climate adaptation outcomes](https://osf.io/preprints/osf/6ewmu)." which are required to run the codes https://github.com/CoRE-Lab-UCF/Pollack_et_al_2024.git </p> <p>Specifically, this repository contains:</p> <ol> <li>dem_subgrid_1m_nbd.asc (DEM at 1m resolution in ascii format. Source DEM is CoNED, see Supporting material of Pollack et al., 2024)</li> <li>Gloucester_street_light_utm.tif (Basemap in UTM coordinates, UTM18N with EPSGcode=26918)</li> <li>sfincs.inp (Model file of SFINCS)</li> <li>Unique_Land_Classes_CN.xls (Table including the land cover classes and corresponding Manning coefficients used for surface roughness)</li> </ol>
Nikas_et_al_2021_STOTEN_DATASET
<p>This dataset contains the underlying data for the following publication: Nikas, A., Elia, A., Boitier, B., Koasidis, K., Doukas, H., Cassetti, G., ... & Chiodi, A. (2021). Where is the EU headed given its current climate policy? A stakeholder-driven model inter-comparison. <em>Science of The Total Environment</em>, 148549. <a href="https://doi.org/10.1016/j.scitotenv.2021.148549">https://doi.org/10.1016/j.scitotenv.2021.148549</a></p>
Sognnaes_et_al_2021_NCC_DATASET
<p>This dataset contains the underlying data for the following publication: <strong>I. Sognnaes, A. Gambhir, D.-J. Van de Ven, A. Nikas, A. Anger-Kraavi, H. Bui, L. Campagnolo, E. Delpiazzo, H. Doukas, S. Giarola, N. Grant, A. Hawkes, A. Koberle, A. Kolpakov, S. Mittal, J. Moreno, S. Perdana, J. Rogelj, M. Vielle, & G.P. Peters. (2021). A multi-model analysis of long-term emissions and warming implications of current mitigation efforts. Nature Climate Change.</strong></p>
Model simulation data used in "Exploring the uncertainties in the aviation soot-cirrus effect" (Righi et al., Atmos. Chem. Phys., 2021)
<p>This dataset contains the output of the EMAC global model simulations analysed and discussed in Righi et al. (<i>Atmos. Chem. Phys.</i>, 2021). For details see the README.md file and Table 1 in the paper.</p>
Lalas_et_al_2021_Energies_DATASET
<p>This dataset contains the underlying data for the following publication: Lalas, D., Gakis, N., Mirasgedis, S., Georgopoulou, E., Sarafidis, Y., & Doukas, H. (2021). Energy and GHG Emissions Aspects of the COVID Impact in Greece. Energies, 14(7), 1955. <a href="https://doi.org/10.3390/en14071955">https://doi.org/10.3390/en14071955</a>.</p>
Giarola_et_al_2021_STOTEN_DATASET
<p>This dataset contains the underlying data for the following publication: Giarola, S., Mittal, S., Vielle, M., Perdana, S., Campagnolo, L., Delpiazzo, E., ... & van de Ven, D. J. (2021). Challenges in the harmonisation of global integrated assessment models: A comprehensive methodology to reduce model response heterogeneity. Science of the Total Environment, 783, 146861. <a href="https://doi.org/10.1016/j.scitotenv.2021.146861">https://doi.org/10.1016/j.scitotenv.2021.146861</a>.</p>
Doukas_et_al_2021_TRPD_DATASET
<p>This dataset contains the underlying data for the following publication: Doukas, H., Spiliotis, E., Jafari, M. A., Giarola, S. & Nikas, A. (2021). Low-cost emissions cuts in container shipping: Thinking inside the box. Transportation Research Part D: Transport and Environment, 94, 102815, <a href="https://doi.org/10.1016/j.trd.2021.102815">https://doi.org/10.1016/j.trd.2021.102815</a>.</p>
Datasets from Prokkola et al. 2021 bioRxiv, doi: https://doi.org/10.1101/2021.08.23.457324).
<p>Standard and maximum metabolic rate and aerobic scope datasets for Atlantic salmon juveniles.</p> <p><strong>In raw data files</strong> ("xxx_bgCorrected_alldata_xx"), oxygen saturations (O2.correct) are shown in mg O2/L after correcting for background respiration. </p> <p><strong>The analysed datasets </strong>("Analysed_xxx_data.txt"), contain values for each fish, combined with information of fixed and random effects for the models. These are the files for statistical analysis.</p> <p>See linked Github repository and the manuscript for details.</p>
Li_et_al_2021_MASGC_Dataset
<p>This dataset contains the underlying data for the following publication: Li, R., Perdana, S., Vielle, M. (2021), Potential integration of Chinese and European emissions trading market: welfare distribution analysis, Mitigation and Adaptation Strategies for Global Change, 26:22 <a href="https://doi.org/10.1007/s11027-021-09960-7">https://doi.org/10.1007/s11027-021-09960-7</a>.</p>
Volunteer kinematics from emergency lateral maneuvers, taken from van Rooij et al, 2013
<p>This data was extracted by the author as part of the OSCCAR project from the publication: </p> <p>Van Rooij, L., Elrofai, H., Philippens, M. M. G. M., & Daanen, H. A. M. (2013). Volunteer kinematics and reaction in lateral emergency maneuver tests. Stapp car crash journal, 57, 313 </p> <p>It is being made available to aid in the validation of Human Body Models.</p> <p>If you use this data, please cote the original paper.</p> <p>A model is available on request from the author of this upload, at Siemens Industry Software Netherlands BV. Modelling information regarding the experimental setup is also available in the public OSCCAR deliverable D3.2.</p>
S27 | KWRSJERPS2 | Extended Suspect List from Sjerps et al (KWRSJERPS)
<p>This is the collection associated with list S27 KWRSJERPS2 on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a></p> <p>S27 | KWRSJERPS2 | <strong>Extended Suspect List from Sjerps<em> et al</em> (KWRSJERPS)</strong></p> <p>Table S4 from Sjerps <em>et al</em>. 2016 Water Research 93: 254-264. </p> <p>DOI: <a href="http://www.sciencedirect.com/science/article/pii/S0043135416300938">10.1016/j.watres.2016.02.034</a>.</p> <p>14 Nov update: added CSV extract of docx. 29/4/2022 update: added missing InChIKey file.</p>
2000-2018 SUHII and Rural LST Monthly Means used in Sismanidis et al. 2022
<p>This dataset provides the 2000-2018 SUHII and rural LST monhtly means used in Sismanidis et al. (2022). The source of the LST data is the the <a href="https://climate.esa.int/en/odp/#/project/land-surface-temperature">v1.0 Terra MODIS data product</a> created by the <a href="https://climate.esa.int/en/projects/land-surface-temperature/">ESA-CCI project on Land Surface Temperature (LST_cci)</a>.</p>
Supporting Data for: McKenna et al. (2018), Arctic sea-ice loss in different regions leads to contrasting Northern Hemisphere impacts
<p>This is a dataset of output from version 4 of the Reading Intermediate Global Circulation Model (IGCM4) that was used in the article: </p> <p>McKenna, C. M., Bracegirdle, T. J., Shuckburgh, E. F., Haynes, P. H., & Joshi, M. M. (2018). Arctic sea ice loss in different regions leads to contrasting Northern Hemisphere impacts. <em>Geophysical Research Letters</em>, 45, 945-954. <a href="https://doi.org/10.1002/2017GL076433">https://doi.org/10.1002/2017GL076433</a></p> <p> </p> <p>Files required to setup the IGCM4 simulations are given in the directory 'IGCM4_setup'.</p> <p>All other directories contain netcdf files of timeseries of various monthly mean fields for each IGCM4 simulation (see paper for details on these simulations). The available variables are:</p> <ul> <li>ua: zonal winds</li> <li>zg: geopotential height</li> <li>ts: surface temperature</li> <li>hfls, hfss, rlds, rlus: surface heatfluxes</li> <li>Flat, Fz, divF: Eliassen-Palm flux vectors and their divergence (only for months November-February)</li> </ul> <p>The ua and zg variables are given for different pressure levels indicated in the filenames (e.g., ua500 is ua at 500 hPa). ua is additionally given in terms of the zonal mean with latitude and pressure. zg is additionally given in terms of longitude and pressure, averaged over latitudes between 60N-80N. All files follow CF conventions in terms of metadata, variable names, etc. </p> <p>Note that the CTL, ATL, PAC, and ATLandPAC simulations were all run continuously in time (i.e., every year starts from the end of the previous year). The 0.5ATL and 0.5PAC simulations, however, were run for 300 years in three separate 100-year chunks (i.e., the initial conditions used to start each 100-year chunk were different). The three 100-year chunks have been appended together in the netcdf files. </p>
Southern African Power Pool GridPath Model Output Data - Chowdhury et al 2022 Joule
<p>This data repository holds GridPath model output data for the paper Chowdhury, A.K., Deshmukh, R., Wu, G., Uppal, A., Mileva, A., Curry, T., Armstrong, L., Galelli, S., and Kudakwashe, N. (2022) “Enabling a low-carbon electricity system for Southern Africa”, Joule. See Readme for more details. </p>
Science 2015 Farley et al Otx-a Library
<p>This dataset represents SEL-seq data generated by first constructing a dictionary of unique barcode tag-enhancer pairs by allowing 2 bp mismatches in the ~69 bp enhancers to buffer the sequencing mistakes. If more than one barcode tag was associated with a single enhancer the maximum reads between these tags were used. Barcoded tags that were attached to multiple enhancers were removed. The resulting dictionary contains 2,534,802 enhancers that are uniquely mapped to one or more barcode tags. 2 biological replicates were used in this experiment and the reads per million total reads (RPM) was used for each tag. In total 163,708 enhancers were detected by RNA-seq and 21,799 of them were defined as active enhancers by RPM ≥ 4 in either of the 2 replicates.</p> <p>Citation: Farley EK, Olson KM, Zhang W, Brandt AJ, Rokhsar DS, Levine MS. 2015. Suboptimization of developmental enhancers. <em>Science</em> <strong>350</strong>:325–328. doi:10.1126/science.aac6948</p> <p>Paper download link: https://www.science.org/doi/suppl/10.1126/science.aac6948/suppl_file/aac6948_tables_s1_and_s2.xlsx</p>
Datasets and R codes for Prokkola et al. 2022 adipose tissue samples
<p>Data and R codes for the analyses reported in Prokkola et al. (pre-print, 2022) <em>Adipose tissue mitochondrial respiration in Atlantic salmon: implications for sex-dependent life-history variation.</em></p> <p>Overview of files can be found in the README file.</p> <p>The file "Cell size data.zip" contains TIFF-images of adipose tissue cryosections, a README file, the result files for each image file and an R code for parsing the results files.</p> <p>To skip the data parsing steps and get the final data, download the AdiposeTissue_data_all.txt file (tab-separated).</p>
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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.