cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25824/redu/j2nlay
title: Multimodal hydrological dataset for flash flood modeling in an urban watershed

description: This dataset contains data acquired from P-band weather radar, river water levels, and water temperatures collected every five minutes for an urban watershed located in Campinas city, in the Southeast region of Brazil. The dataset has 12265 samples and gathers data on the 145 events of highest water levels from November 2014 to June 2019. It contains 15 variables, namelly: data, time_match, precipitation interpreted from data of 10 radar grids (which correspond to the watershed area), average precipitation, water level and water temperature in the watershed outlet. A baseline study using this dataset can be found in the Master Thesis entitled "Data-driven model for flood prediction in an urban watershed in Campinas, Brazil, aiming at building an early warning system"
DOI: 10.34740/kaggle/dsv/4660202
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.57841/casdc.0000028
title: 1
DOI: 10.5281/zenodo.7323849
title: bedrock DEM in the vicinity of lac de Bossons

description: bedrock DEM in the vicinity of lac de Bossons calculated from radar 2021, radar 2022, bathymetry sept 2022 and surface DEM from sept 2022. Format: x, y (meters Lambert 2) and z ((meters NGF IGN 69).
DOI: 10.5281/zenodo.7323848
title: bedrock DEM in the vicinity of lac de Bossons

description: bedrock DEM in the vicinity of lac de Bossons calculated from radar 2021, radar 2022, bathymetry sept 2022 and surface DEM from sept 2022. Format: x, y (meters Lambert 2) and z ((meters NGF IGN 69).
DOI: 10.5281/zenodo.7064893
title: ATR Spectra of Human Milk Fat

description: ATR spectra of human milk fat. This dataset was employed in the paper "Solvent-Free Lipid Separation and Attenuated Total Reflectance Infrared Spectroscopy for Fast and Green Fatty Acid Profiling of Human Milk" published in MDPI Foods, DOI: https://doi.org/10.3390/foods11233906.
description: This work was funded by the European Union's Horizon 2020 Research and Innovation Programme through the Nutrishield project (https://nutrishield-project.eu/) [Grant Agreement No 818110] as well as the COMET Center CHASE (project No 868615), which is funded within the framework of COMET (Competence Centers for Excellent Technologies) by BMVIT, BMDW, and the Federal Provinces of Upper Austria and Vienna. The COMET program is run by the Austrian Research Promotion Agency (FFG). This research was funded by Instituto de Salud Carlos III and co-funded by the European Union (grant numbers CP16/00034 and CPII21/00003).
DOI: 10.5281/zenodo.7064892
title: ATR Spectra of Human Milk Fat

description: ATR spectra of human milk fat. This dataset was employed in the paper "Solvent-Free Lipid Separation and Attenuated Total Reflectance Infrared Spectroscopy for Fast and Green Fatty Acid Profiling of Human Milk" published in MDPI Foods, DOI: https://doi.org/10.3390/foods11233906.
description: This work was funded by the European Union's Horizon 2020 Research and Innovation Programme through the Nutrishield project (https://nutrishield-project.eu/) [Grant Agreement No 818110] as well as the COMET Center CHASE (project No 868615), which is funded within the framework of COMET (Competence Centers for Excellent Technologies) by BMVIT, BMDW, and the Federal Provinces of Upper Austria and Vienna. The COMET program is run by the Austrian Research Promotion Agency (FFG). This research was funded by Instituto de Salud Carlos III and co-funded by the European Union (grant numbers CP16/00034 and CPII21/00003).
DOI: 10.57841/casdc.0000029
title: 黄河三角洲
DOI: 10.57841/casdc.0000030
title: 黄河三角洲
DOI: 10.6084/m9.figshare.20496249
title: Mapping hydrogen storage capacities of UK offshore hydrocarbon fields and exploring potential synergies with offshore wind

description: S1 Field data, suitability criteria and suitability matrix
DOI: 10.6084/m9.figshare.20496249.v2
title: Mapping hydrogen storage capacities of UK offshore hydrocarbon fields and exploring potential synergies with offshore wind

description: S1 Field data, suitability criteria and suitability matrix
DOI: 10.6084/m9.figshare.20496249.v1
title: Mapping hydrogen storage capacities of UK offshore hydrocarbon fields and investigating potential synergies with offshore wind

description: S1 Field data, suitability criteria and suitability matrix
DOI: 10.17028/rd.lboro.21617505
title: Measured indoor temperature in two unoccupied dwellings and weather data during the summer with the hottest UK temperature on record, 2022

description: This dataset is maintained by Max Eastwood (m.w.eastwood@lboro.ac.uk), Building Energy Research Group (BERG), School of Architecture, Building and Civil Engineering, Loughborough University. --- This dataset provides the measured indoor dry bulb temperatures and surrounding weather conducted in the Loughborough Matched Pair test houses during summer 2022. The dataset is made publicly available here. This dataset includes: 1. README.txt: A Read Me file with more details of the study and the dataset. 2. Dataset_descriptor.pdf: a guidance document containing information on the measurment work carried out. 3. West_AT_10minute.csv: 10-minute dry bulb temperature measured in the West house (AT = Air Temperature) 4. East_AT_10minute.csv: 10-minute dry bulb temperature measured in the East house 5. Weather_20second.csv: 20-second weather data compiled from the test house weather station. Other information on the houses' geometry and construction can be found here: https://doi.org/10.17028/rd.lboro.8094575 <br>
DOI: 10.17028/rd.lboro.21617505.v2
title: Measured indoor temperature in two unoccupied dwellings and weather data during the summer with the hottest UK temperature on record, 2022

description: This dataset is maintained by Max Eastwood (m.w.eastwood@lboro.ac.uk), Building Energy Research Group (BERG), School of Architecture, Building and Civil Engineering, Loughborough University. --- This dataset provides the measured indoor dry bulb temperatures and surrounding weather conducted in the Loughborough Matched Pair test houses during summer 2022. The dataset is made publicly available here. This dataset includes: 1. README.txt: A Read Me file with more details of the study and the dataset. 2. Dataset_descriptor.pdf: a guidance document containing information on the measurment work carried out. 3. West_AT_10minute.csv: 10-minute dry bulb temperature measured in the West house (AT = Air Temperature) 4. East_AT_10minute.csv: 10-minute dry bulb temperature measured in the East house 5. Weather_20second.csv: 20-second weather data compiled from the test house weather station. Other information on the houses' geometry and construction can be found here: https://doi.org/10.17028/rd.lboro.8094575 <br>
DOI: 10.17028/rd.lboro.21617505.v1
title: Measured indoor temperature in two unoccupied dwellings and weather data during the hottest UK summer on record, 2022

description: This dataset is maintained by Max Eastwood (m.w.eastwood@lboro.ac.uk), Building Energy Research Group (BERG), School of Architecture, Building and Civil Engineering, Loughborough University. --- This dataset provides the measured indoor dry bulb temperatures and surrounding weather conducted in the Loughborough Matched Pair test houses during summer 2022. The dataset is made publicly available here. This dataset includes: 1. README.txt: A Read Me file with more details of the study and the dataset. 2. Dataset_descriptor.pdf: a guidance document containing information on the measurment work carried out. 3. West_AT_10minute.csv: 10-minute dry bulb temperature measured in the West house (AT = Air Temperature) 4. East_AT_10minute.csv: 10-minute dry bulb temperature measured in the East house 5. Weather_20second.csv: 20-second weather data compiled from the test house weather station. Other information on the houses' geometry and construction can be found here: https://doi.org/10.17028/rd.lboro.8094575 <br>
DOI: 10.57841/casdc.0000031
title: 黄河三角洲
DOI: 10.5281/zenodo.7218037
title: Internal rotation and buoyancy travel time of 60 gamma Doradus stars from uninterrupted TESS light curves spanning 352 days

description: Description:<br> Electronic versions of Table A.1 and A.2 from the Appendix of<br> Garcia et al. (2022b), as well as all analysed g-mode period-spacing<br> patterns from this work. Abstract:<br> Context. Gamma Doradus (hereafter gamma Dor) stars are gravity-mode<br> pulsators whose periods carry information about the internal structure of<br> the star. These periods are especially sensitive to the internal rotation<br> and chemical mixing, two processes that are currently not well constrained<br> in the theory of stellar evolution.<br> Aims. We aim to identify the pulsation modes and deduce the internal<br> rotation and buoyancy travel time for 106 gamma Dor stars observed<br> by the TESS mission in its southern continuous viewing zone (hereafter<br> S-CVZ). We rely on 140 previously detected period-spacing patterns, that is,<br> series of (near-)consecutive pulsation mode periods.<br> Methods. We used the asymptotic expression to compute gravity-mode<br> frequencies for ranges of the rotation rate and buoyancy travel time that<br> cover the physical range in γ Dor stars. Those frequencies were fitted to<br> the observed period-spacing patterns by minimizing a custom cost function.<br> The effects of rotation were evaluated using the traditional approximation<br> of rotation, using the stellar pulsation code GYRE.<br> Results. We obtained the pulsation mode identification, internal rotation<br> and buoyancy travel time for 60 TESS gamma Dor stars. For the remaining 46<br> targets, the detected patterns are either too short or contained too many<br> missing modes for unambiguous mode identification, and longer light curves<br> are required. For the successfully analysed stars, we found that<br> period-spacing patterns from 1-yr long TESS light curves can constrain the<br> internal rotation and buoyancy travel time to a precision of 0.03 d^{−1} and<br> 400s, respectively, which is about half as precise as literature results<br> based on 4-yr Kepler light curves of gamma Dor stars.
description: The research leading to these results has received funding from the the KU\,Leuven Research Council (grant C16/18/005: PARADISE) and from the BELgian federal Science Policy Office (BELSPO) through PRODEX grants for the Gaia and PLATO space missions. TVR gratefully acknowledges support from the Research Foundation Flanders (FWO) under grant agreement N$^\circ$12ZB620N.
DOI: 10.5281/zenodo.7218038
title: Internal rotation and buoyancy travel time of 60 gamma Doradus stars from uninterrupted TESS light curves spanning 352 days

description: Description:<br> Electronic versions of Table A.1 and A.2 from the Appendix of<br> Garcia et al. (2022b), as well as all analysed g-mode period-spacing<br> patterns from this work. Abstract:<br> Context. Gamma Doradus (hereafter gamma Dor) stars are gravity-mode<br> pulsators whose periods carry information about the internal structure of<br> the star. These periods are especially sensitive to the internal rotation<br> and chemical mixing, two processes that are currently not well constrained<br> in the theory of stellar evolution.<br> Aims. We aim to identify the pulsation modes and deduce the internal<br> rotation and buoyancy travel time for 106 gamma Dor stars observed<br> by the TESS mission in its southern continuous viewing zone (hereafter<br> S-CVZ). We rely on 140 previously detected period-spacing patterns, that is,<br> series of (near-)consecutive pulsation mode periods.<br> Methods. We used the asymptotic expression to compute gravity-mode<br> frequencies for ranges of the rotation rate and buoyancy travel time that<br> cover the physical range in γ Dor stars. Those frequencies were fitted to<br> the observed period-spacing patterns by minimizing a custom cost function.<br> The effects of rotation were evaluated using the traditional approximation<br> of rotation, using the stellar pulsation code GYRE.<br> Results. We obtained the pulsation mode identification, internal rotation<br> and buoyancy travel time for 60 TESS gamma Dor stars. For the remaining 46<br> targets, the detected patterns are either too short or contained too many<br> missing modes for unambiguous mode identification, and longer light curves<br> are required. For the successfully analysed stars, we found that<br> period-spacing patterns from 1-yr long TESS light curves can constrain the<br> internal rotation and buoyancy travel time to a precision of 0.03 d^{−1} and<br> 400s, respectively, which is about half as precise as literature results<br> based on 4-yr Kepler light curves of gamma Dor stars.
description: The research leading to these results has received funding from the the KU\,Leuven Research Council (grant C16/18/005: PARADISE) and from the BELgian federal Science Policy Office (BELSPO) through PRODEX grants for the Gaia and PLATO space missions. TVR gratefully acknowledges support from the Research Foundation Flanders (FWO) under grant agreement N$^\circ$12ZB620N.
DOI: 10.5281/zenodo.7398085
title: Internal rotation and buoyancy travel time of 60 gamma Doradus stars from uninterrupted TESS light curves spanning 352 days

description: Description:<br> Electronic versions of Table A.1 and A.2 from the Appendix of<br> Garcia et al. (2022b), as well as all analysed g-mode period-spacing<br> patterns from this work. Abstract:<br> Context. Gamma Doradus (hereafter gamma Dor) stars are gravity-mode<br> pulsators whose periods carry information about the internal structure of<br> the star. These periods are especially sensitive to the internal rotation<br> and chemical mixing, two processes that are currently not well constrained<br> in the theory of stellar evolution.<br> Aims. We aim to identify the pulsation modes and deduce the internal<br> rotation and buoyancy travel time for 106 gamma Dor stars observed<br> by the TESS mission in its southern continuous viewing zone (hereafter<br> S-CVZ). We rely on 140 previously detected period-spacing patterns, that is,<br> series of (near-)consecutive pulsation mode periods.<br> Methods. We used the asymptotic expression to compute gravity-mode<br> frequencies for ranges of the rotation rate and buoyancy travel time that<br> cover the physical range in γ Dor stars. Those frequencies were fitted to<br> the observed period-spacing patterns by minimizing a custom cost function.<br> The effects of rotation were evaluated using the traditional approximation<br> of rotation, using the stellar pulsation code GYRE.<br> Results. We obtained the pulsation mode identification, internal rotation<br> and buoyancy travel time for 60 TESS gamma Dor stars. For the remaining 46<br> targets, the detected patterns are either too short or contained too many<br> missing modes for unambiguous mode identification, and longer light curves<br> are required. For the successfully analysed stars, we found that<br> period-spacing patterns from 1-yr long TESS light curves can constrain the<br> internal rotation and buoyancy travel time to a precision of 0.03 d^{−1} and<br> 400s, respectively, which is about half as precise as literature results<br> based on 4-yr Kepler light curves of gamma Dor stars.
description: The research leading to these results has received funding from the the KU\,Leuven Research Council (grant C16/18/005: PARADISE) and from the BELgian federal Science Policy Office (BELSPO) through PRODEX grants for the Gaia and PLATO space missions. TVR gratefully acknowledges support from the Research Foundation Flanders (FWO) under grant agreement N$^\circ$12ZB620N.
DOI: 10.5281/zenodo.7400259
title: Vedlegg: Spretter mellom perioder

description: Vedlegget omfatter et materialeutvalg av spretter (draktspenner) fra middelalder og nyere tid, med kriterier for utvalg, kilder til datering samt katalog over oversikten.
description: Draktspenner, spretter, middelalder, nyere tid
DOI: 10.5281/zenodo.7400258
title: Vedlegg: Spretter mellom perioder

description: Vedlegget omfatter et materialeutvalg av spretter (draktspenner) fra middelalder og nyere tid, med kriterier for utvalg, kilder til datering samt katalog over oversikten.
description: Draktspenner, spretter, middelalder, nyere tid
DOI: 10.5281/zenodo.7243603
title: zebrafish scRNA data set objects

description: Combined and converted scRNA data from http://tome.gs.washington.edu/ (Qiu et al. 2022), see a detailed description of the study here: https://www.nature.com/articles/s41588-022-01018-x Data were downloaded from http://tome.gs.washington.edu/ as R rds files, combined into a single Seurat object and converted into loom and AnnData (h5ad) files to be able to analyse with e.g. python scanpy package. If you use this data, please cite Farrel et al. 2018, Wagner et al. 2018 and Qiu et al. 2022.
description: {"references": ["Qiu, C., Cao, J., Martin, B.K., Li, T., Welsh, I.C., Srivatsan, S., Huang, X., Calderon, D., Noble, W.S., Disteche, C.M. and Murray, S.A., 2022. Systematic reconstruction of cellular trajectories across mouse embryogenesis. Nature genetics, 54(3), pp.328-341.", "Satija, R., Farrell, J.A., Gennert, D., Schier, A.F. and Regev, A., 2015. Spatial reconstruction of single-cell gene expression data. Nature biotechnology, 33(5), pp.495-502.", "Wolf, F.A., Angerer, P. and Theis, F.J., 2018. SCANPY: large-scale single-cell gene expression data analysis. Genome biology, 19(1), pp.1-5.", "Farrell, J.A., Wang, Y., Riesenfeld, S.J., Shekhar, K., Regev, A. and Schier, A.F., 2018. Single-cell reconstruction of developmental trajectories during zebrafish embryogenesis. Science, 360(6392), p.eaar3131.", "Wagner, D.E., Weinreb, C., Collins, Z.M., Briggs, J.A., Megason, S.G. and Klein, A.M., 2018. Single-cell mapping of gene expression landscapes and lineage in the zebrafish embryo. Science, 360(6392), pp.981-987."]}
DOI: 10.5281/zenodo.7243602
title: zebrafish scRNA data set objects

description: Combined and converted scRNA data from http://tome.gs.washington.edu/ (Qiu et al. 2022), see a detailed description of the study here: https://www.nature.com/articles/s41588-022-01018-x Data were downloaded from http://tome.gs.washington.edu/ as R rds files, combined into a single Seurat object and converted into loom and AnnData (h5ad) files to be able to analyse with e.g. python scanpy package. If you use this data, please cite Farrel et al. 2018, Wagner et al. 2018 and Qiu et al. 2022.
description: {"references": ["Qiu, C., Cao, J., Martin, B.K., Li, T., Welsh, I.C., Srivatsan, S., Huang, X., Calderon, D., Noble, W.S., Disteche, C.M. and Murray, S.A., 2022. Systematic reconstruction of cellular trajectories across mouse embryogenesis. Nature genetics, 54(3), pp.328-341.", "Satija, R., Farrell, J.A., Gennert, D., Schier, A.F. and Regev, A., 2015. Spatial reconstruction of single-cell gene expression data. Nature biotechnology, 33(5), pp.495-502.", "Wolf, F.A., Angerer, P. and Theis, F.J., 2018. SCANPY: large-scale single-cell gene expression data analysis. Genome biology, 19(1), pp.1-5.", "Farrell, J.A., Wang, Y., Riesenfeld, S.J., Shekhar, K., Regev, A. and Schier, A.F., 2018. Single-cell reconstruction of developmental trajectories during zebrafish embryogenesis. Science, 360(6392), p.eaar3131.", "Wagner, D.E., Weinreb, C., Collins, Z.M., Briggs, J.A., Megason, S.G. and Klein, A.M., 2018. Single-cell mapping of gene expression landscapes and lineage in the zebrafish embryo. Science, 360(6392), pp.981-987."]}
DOI: 10.5281/zenodo.7244441
title: frog scRNA data set objects

description: Combined and converted scRNA data from http://tome.gs.washington.edu/ (Qiu et al. 2022), see a detailed description of the study here: https://www.nature.com/articles/s41588-022-01018-x Data were downloaded from http://tome.gs.washington.edu/ as R rds files, combined into a single Seurat object and converted into loom and AnnData (h5ad) files to be able to analyse with e.g. python scanpy package. If you use this data, please cite Briggs et al. 2018 and Qiu et al. 2022.
description: {"references": ["Qiu, C., Cao, J., Martin, B.K., Li, T., Welsh, I.C., Srivatsan, S., Huang, X., Calderon, D., Noble, W.S., Disteche, C.M. and Murray, S.A., 2022. Systematic reconstruction of cellular trajectories across mouse embryogenesis. Nature genetics, 54(3), pp.328-341.", "Satija, R., Farrell, J.A., Gennert, D., Schier, A.F. and Regev, A., 2015. Spatial reconstruction of single-cell gene expression data. Nature biotechnology, 33(5), pp.495-502.", "Wolf, F.A., Angerer, P. and Theis, F.J., 2018. SCANPY: large-scale single-cell gene expression data analysis. Genome biology, 19(1), pp.1-5.", "Briggs, J.A., Weinreb, C., Wagner, D.E., Megason, S., Peshkin, L., Kirschner, M.W. and Klein, A.M., 2018. The dynamics of gene expression in vertebrate embryogenesis at single-cell resolution. Science, 360(6392), p.eaar5780."]}
DOI: 10.5281/zenodo.7244440
title: frog scRNA data set objects

description: Combined and converted scRNA data from http://tome.gs.washington.edu/ (Qiu et al. 2022), see a detailed description of the study here: https://www.nature.com/articles/s41588-022-01018-x Data were downloaded from http://tome.gs.washington.edu/ as R rds files, combined into a single Seurat object and converted into loom and AnnData (h5ad) files to be able to analyse with e.g. python scanpy package. If you use this data, please cite Briggs et al. 2018 and Qiu et al. 2022.
description: {"references": ["Qiu, C., Cao, J., Martin, B.K., Li, T., Welsh, I.C., Srivatsan, S., Huang, X., Calderon, D., Noble, W.S., Disteche, C.M. and Murray, S.A., 2022. Systematic reconstruction of cellular trajectories across mouse embryogenesis. Nature genetics, 54(3), pp.328-341.", "Satija, R., Farrell, J.A., Gennert, D., Schier, A.F. and Regev, A., 2015. Spatial reconstruction of single-cell gene expression data. Nature biotechnology, 33(5), pp.495-502.", "Wolf, F.A., Angerer, P. and Theis, F.J., 2018. SCANPY: large-scale single-cell gene expression data analysis. Genome biology, 19(1), pp.1-5.", "Briggs, J.A., Weinreb, C., Wagner, D.E., Megason, S., Peshkin, L., Kirschner, M.W. and Klein, A.M., 2018. The dynamics of gene expression in vertebrate embryogenesis at single-cell resolution. Science, 360(6392), p.eaar5780."]}
DOI: 10.14278/rodare.1546
title: (Data set) Optical study of RbV₃Sb₅: Multiple density-wave gaps and phonon anomalies

description: The folder contains the data set that the publication with the same name is based on. Origin file: Reflectivity Optical conductivity Band resolved DFT calculation (band structure + optical conductivity) Comparison of DFT and experiment (interband transitions) above and below CDW transition Further data sets are available upon request
DOI: 10.14278/rodare.1545
title: (Data set) Optical study of RbV₃Sb₅: Multiple density-wave gaps and phonon anomalies

description: The folder contains the data set that the publication with the same name is based on. Origin file: Reflectivity Optical conductivity Band resolved DFT calculation (band structure + optical conductivity) Comparison of DFT and experiment (interband transitions) above and below CDW transition Further data sets are available upon request
DOI: 10.5281/zenodo.7400341
title: pseudamia_nigra_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.7400340
title: pseudamia_nigra_spades_01.fasta.gz

description: .
DOI: 10.5517/ccdc.csd.cc2cjsnc
title: CCDC 2190883: Experimental Crystal Structure Determination

description: Related Article: Kaifan Zhang|2022|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.