cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.11583/dtu.21602280
title: Replicate data for: Improving seabed substrate mapping with high-resolution bottom trawl data

description: <strong>Data repository description</strong> This data repository is linked to the manuscript “Improving seabed substrate mapping with high-resolution bottom trawl data”, submitted to Estuarine, Coastal and Shelf Sciences, written by Karin J. van der Reijden, Verner B. Ernstsen, Jeppe Olsen, Grete E. Dinesen, Jørgen O. Leth, and Ole R. Eigaard. This repository contains a subfolder (“Fisheries_data”), this description, a geographic shapefile of the study areas, and an RDS.file named “final_dataset”. <br> <strong>Fisheries data</strong> This folder contains geoTIFF raster files for the five different fishing métiers presented/used in the manuscript. Each raster file represents the average annual Swept Area Ratio (SAR) estimates of that fishing métier over the period 2016-2020 for an area covering both study areas in a spatial resolution of 100 x 100 m. The raster files have a spatial projection of EPSG: 25832 (ETRS 89 / UTM 32). <br> <strong>StudyAreas.shp</strong> This geographic shapefile delineates the two study areas (StudyAreas.shp), with a spatial projection of EPSG: 25832 (ETRS 89 / UTM 32). <br> <strong>Final_dataset</strong> This rds.file contains the dataset used in the analysis of the manuscript, and is obtained as described in the manuscript. It is saved as a ‘simple feature collection’ and should be processed using the package “SF” in R. Each row represents a grid cell centroid of the fisheries rasters that is located within a substrate polygon. For each centroid, this dataset provides a unique ID (“grID”), the SAR-estimate for the five métiers (“OT_smallpelagics”, “OT_norwaylobster”, “OT_sandeel”, “OT_plaice”, “SDN_plaice”), and the water depth (“WaterDepth”). It further states the observed substrate type (“Substrate”), in which study area it is located (“StudyArea”), and whether the data was used for model training or validation (“Selection”). The final column (“geometry”) provides the spatial information of the centroid, in EPSG: 25832 (ETRS 89 / UTM 32).
DOI: 10.11583/dtu.21602280.v1
title: Replicate data for: Improving seabed substrate mapping with high-resolution bottom trawl data

description: <strong>Data repository description</strong> This data repository is linked to the manuscript “Improving seabed substrate mapping with high-resolution bottom trawl data”, submitted to Estuarine, Coastal and Shelf Sciences, written by Karin J. van der Reijden, Verner B. Ernstsen, Jeppe Olsen, Grete E. Dinesen, Jørgen O. Leth, and Ole R. Eigaard. This repository contains a subfolder (“Fisheries_data”), this description, a geographic shapefile of the study areas, and an RDS.file named “final_dataset”. <br> <strong>Fisheries data</strong> This folder contains geoTIFF raster files for the five different fishing métiers presented/used in the manuscript. Each raster file represents the average annual Swept Area Ratio (SAR) estimates of that fishing métier over the period 2016-2020 for an area covering both study areas in a spatial resolution of 100 x 100 m. The raster files have a spatial projection of EPSG: 25832 (ETRS 89 / UTM 32). <br> <strong>StudyAreas.shp</strong> This geographic shapefile delineates the two study areas (StudyAreas.shp), with a spatial projection of EPSG: 25832 (ETRS 89 / UTM 32). <br> <strong>Final_dataset</strong> This rds.file contains the dataset used in the analysis of the manuscript, and is obtained as described in the manuscript. It is saved as a ‘simple feature collection’ and should be processed using the package “SF” in R. Each row represents a grid cell centroid of the fisheries rasters that is located within a substrate polygon. For each centroid, this dataset provides a unique ID (“grID”), the SAR-estimate for the five métiers (“OT_smallpelagics”, “OT_norwaylobster”, “OT_sandeel”, “OT_plaice”, “SDN_plaice”), and the water depth (“WaterDepth”). It further states the observed substrate type (“Substrate”), in which study area it is located (“StudyArea”), and whether the data was used for model training or validation (“Selection”). The final column (“geometry”) provides the spatial information of the centroid, in EPSG: 25832 (ETRS 89 / UTM 32).
DOI: 10.11583/dtu.14695437
title: Spectral Albedo Data for Bifacial Photovoltaic Applications

description: This is the raw data used in the publication "The Effect of Spectral Albedo in Bifacial Photovoltaic Performance".<br>Nicholas Riedel-Lyngskær et al., 2022. The effect of spectral albedo in bifacial photovoltaic performance, Solar Energy, Volume 231,pp. 921-935.https://doi.org/10.1016/j.solener.2021.12.023<br><br>
DOI: 10.5281/zenodo.8131127
title: neoturris_breviconis_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.8131126
title: neoturris_breviconis_zanfona_1.fasta.gz

description: .
DOI: 10.11583/dtu.12554489
title: Arctic Vertical Land Motion (5x5 km)

description: NetCdf-file with Vertical Land Motion in the Arctic (above 50 deg N) in stereographic grid. Provided is data for ICE6G-D and Caron 2018 GIA-models, elastic Vertical Land Motion from present-day ice loss (1997-2015). Corrections for Geocenter Motion and Rotational Feedback are also provided.
DOI: 10.5281/zenodo.8131136
title: tiaropsis_multicirrata_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.8131135
title: tiaropsis_multicirrata_zanfona_1.fasta.gz

description: .
DOI: 10.11583/dtu.8204633.v2
title: ALEX17 flux-profile measurements: 3D sonic's wind profiles over complex terrain

description: The present dataset is part of the Alaiz Experiment-2017 (ALEX17) which consists of four 80m flux-profile masts instrumented with 19 3D sonic anemometers (3 masts with 5 levels, one mast with 4 levels). The masts are complemented with temperature and humidity 10min measurements (see references). The dataset has 11 months of wind measurements from August/2018 to July/2019. The experiment report shows the coordinates of all sensors, as well as instrument tilt and boom orientation. Both raw data at 20Hz, as well as 10min averages of quality-controlled and tilt corrected data are available.
DOI: 10.11583/dtu.8204633.v1
title: ALEX17 flux-profile measurements: 3D sonic's wind profiles over complex terrain

description: The present dataset is part of the Alaiz Experiment-2017 (ALEX17) which consists of four 80m flux-profile masts instrumented with 19 3D sonic anemometers (3 masts with 5 levels, one mast with 4 levels). The masts are complemented with temperature and humidity 10min measurements (see references). The dataset has 11 months of wind measurements from August/2018 to July/2019. The experiment report shows the coordinates of all sensors, as well as instrument tilt and boom orientation. Both raw data at 20Hz, as well as 10min averages of quality-controlled and tilt corrected data are available.
DOI: 10.5281/zenodo.8083495
title: Nanomaterial genotoxicity evaluation using the high-throughput p53-binding protein 1 (53BP1) assay - data from the article published in PlosOne

description: Data that have been used in the manuscript "Nanomaterial genotoxicity evaluation using the high-throughput p53-binding protein 1 (53BP1) assay" by M. Fontaine et al., published in PlosOne in 2023.
DOI: 10.5281/zenodo.8083494
title: Nanomaterial genotoxicity evaluation using the high-throughput p53-binding protein 1 (53BP1) assay - data from the article published in PlosOne

description: Data that have been used in the manuscript "Nanomaterial genotoxicity evaluation using the high-throughput p53-binding protein 1 (53BP1) assay" by M. Fontaine et al., published in PlosOne in 2023.
DOI: 10.1285/i9788883051975
title: «FU CHIAMATO ANALFABETO, COME QUASI NON HAVESSE IMPARATO NÈ PUR L'ALFABETO». Storia della parola analfabeta (o analfabeto) e dei suoi derivati
DOI: 10.1285/i9788883051975p0
title: Copertina
DOI: 10.11583/dtu.9988805
title: Data for "Distributed Quantum Sensing in a Continuous Variable Entangled Network"

description: Raw and processed oscilloscope data for the experiment on distributed quantum sensing in a continuous variable entangled network, published in Nature Physics (2019), https://doi.org/10.1038/s41567-019-0743-x<br>The dataset contains the following three files in HDF5 format:<br>(1): <b>distsens_raw.hdf5</b> --- The raw oscilloscope traces of the homodyne output. (The file is as large as 7.66GB!)<br><br>(2): <b>distsens_phasecalibration.hdf5 </b>--- The oscilloscope traces for phase calibration.<br>(3): <b>distsens_spectra.hdf5</b> --- averaged power spectral density results processed from the raw oscilloscope traces. This file is only 15.9 MB, and is provided in case (1) is too slow to download or process.<br>A Jupyter Notebook "<b>distributed_sensing.ipynb</b>" can be found at <b>https://github.com/qpit/distributed-quantum-sensing</b>. This notebook documents and run the data analysis of the files provided here.<br>
DOI: 10.11583/dtu.9988805.v1
title: Data for "Distributed Quantum Sensing in a Continuous Variable Entangled Network"

description: Raw and processed oscilloscope data for the experiment on distributed quantum sensing in a continuous variable entangled network, published in Nature Physics (2019), https://doi.org/10.1038/s41567-019-0743-x<br>The dataset contains the following three files in HDF5 format:<br>(1): <b>distsens_raw.hdf5</b> --- The raw oscilloscope traces of the homodyne output. (The file is as large as 7.66GB!)<br><br>(2): <b>distsens_phasecalibration.hdf5 </b>--- The oscilloscope traces for phase calibration.<br>(3): <b>distsens_spectra.hdf5</b> --- averaged power spectral density results processed from the raw oscilloscope traces. This file is only 15.9 MB, and is provided in case (1) is too slow to download or process.<br>A Jupyter Notebook "<b>distributed_sensing.ipynb</b>" can be found at <b>https://github.com/qpit/distributed-quantum-sensing</b>. This notebook documents and run the data analysis of the files provided here.<br>
DOI: 10.1285/i9788883051975pi
title: Frontespizio e pagine iniziali
DOI: 10.5258/soton/d2383
title: Dataset supporting the article - Adaptive codebook-based channel estimation in OFDM-aided hybrid beamforming mmwave systems

description: This dataset supports the publication "Adaptive Codebook-Based Channel Estimation in OFDM-Aided Hybrid Beamforming mmWave Systems" by Y Zhang, M El-Hajjar, L-L Yang in IEEE Open Journal of the Communications Society This dataset contains: Figure 5, 6, and 7 of the aforementioned paper. Each folder is named according to its content, where the curves of each figure are stored in mat files. To regenerate the results, please use the Matlab. The figures are as follows: - Figure-5: Contains the dataset of Figure. 5. MSE performance of channel estimation with different K and N values. - Figure-6: Contains the dataset of Figure 6. Comparison of MSE performance of the codebook-based and SBL-based channel estimation, when Nt = 8 and Nr = 8 - Figure-7: Contains the dataset of Figure7.chievable rates of the OFDM systems with respectively the proposed channel estimation and the conventional codebook-based channel estimation. Date of data collection: 09, 2021 ~ 09,2022
DOI: 10.1285/i9788883051975p1
title: «FU CHIAMATO ANALFABETO, COME QUASI NON HAVESSE IMPARATO NÈ PUR L'ALFABETO». Storia della parola analfabeta (o analfabeto) e dei suoi derivati

description: This work traces the history of the word analfabeto. The latter represents the original form of the term, which appeared at the beginning of the 17th century, and which was first joined and then replaced by the anethymological form, analfabeta. This study outlines the history of a lexicographical ghost, whose origins are associated with Bonavilla (1807) before being handed down, through a series of quotations, to contemporary vocabularies. The history of the earliest attestations is reconstructed, including the confusion between Justinian and Justin characterising the earliest contexts as well as the communicative use of the word among scholars. In addition, the process of progressive substitution of analfabeto with analfabeta is observed by commenting on the point of view of nineteenth- and early twentieth-century dictionaries. Finally, this work reports on the events surrounding crucial issues such as the right to vote and legislative reforms, before reporting on the success story that is represented by the affirmation of the derivative analfabetismo.
DOI: 10.1285/i9788883051975p3
title: Indice
DOI: 10.1285/i9788883051975p5
title: Premessa. Tra gli specchi
DOI: 10.1285/i9788883051975p7
title: Un Geometra analfabeta
DOI: 10.1285/i9788883051975p21
title: L'imperatore analfabeto
DOI: 10.1285/i9788883051975p33
title: Citazioni e insulti
DOI: 10.1285/i9788883051975p47
title: La parola ai dizionari
DOI: 10.1285/i9788883051975p57
title: Riforme legislative, diritto di voto e un altro imperatore analfabeta
DOI: 10.25345/c5pz51x18
title: MassIVE MSV000092389 - GNPS - Tsunoda Diphenhydramine Study - reupload for summer school
title: study of diphenhydramine in blood and skin - untargeted mass spectrometry analysis [doi:10.25345/C5SJ2X] - reupload for summer school
DOI: 10.1285/i9788883051975p71
title: Analfabetismo in Italia e in italiano
DOI: 10.1285/i9788883051975p81
title: Italiano o latino?
DOI: 10.1285/i9788883051975p91
title: Derivazione, influenze e locuzioni
DOI: 10.1285/i9788883051975p109
title: Appendice. Glossario e indice lessicografico delle forme citate
DOI: 10.1285/i9788883051975p119
title: Riferimenti bibliografici
DOI: 10.1285/i9788883051975p137
title: Colophon
DOI: 10.5281/zenodo.8131156
title: aegina_citrea_decontaminated_gx.fasta.gz

description: .
DOI: 10.5281/zenodo.8131155
title: aegina_citrea_decontaminated_gx.fasta.gz

description: .
DOI: 10.11583/dtu.14401994
title: Large stabilizing wall - mesh & load configuration

description: This data set contains the mesh and load configuration for a finite element model of large stabilizing reinforced concrete wall presented as an example in the publication with DOI: https://doi.org/10.1002/suco.202100302 The data set consists of the following files:<br><br>Nodal_coordinates.csv: List of coordinates (“x”, “y” and “z”) for the finite element vertices/nodes (“Node”).<br>Topology.csv: List of node numbers (“Node 1”, “Node 2” and “Node 3” for the finite elements (“Element”).<br>Line_Load.csv: List of line loads (“Line load”) defined in terms of the node numbers of the segment end-points (“Node 1” and “Node 2”), the end-point intensities (“Load 1” and “Load 2”), and the components of the load direction vector (“Direction – x”, “Direction – y” and “Direction – z”).<br><br>Domain_load.csv: List of domain loads (“Domain load”) defined in terms of the finite element (“Element”), the load intensity (“Load”), and the components of the load direction vector (“Direction – x”, “Direction – y” and “Direction – z”).<br><br>
DOI: 10.11583/dtu.14401994.v1
title: Large stabilizing wall - mesh & load configuration

description: This data set contains the mesh and load configuration for a finite element model of large stabilizing reinforced concrete wall presented as an example in the publication with DOI: https://doi.org/10.1002/suco.202100302 The data set consists of the following files:<br><br>Nodal_coordinates.csv: List of coordinates (“x”, “y” and “z”) for the finite element vertices/nodes (“Node”).<br>Topology.csv: List of node numbers (“Node 1”, “Node 2” and “Node 3” for the finite elements (“Element”).<br>Line_Load.csv: List of line loads (“Line load”) defined in terms of the node numbers of the segment end-points (“Node 1” and “Node 2”), the end-point intensities (“Load 1” and “Load 2”), and the components of the load direction vector (“Direction – x”, “Direction – y” and “Direction – z”).<br><br>Domain_load.csv: List of domain loads (“Domain load”) defined in terms of the finite element (“Element”), the load intensity (“Load”), and the components of the load direction vector (“Direction – x”, “Direction – y” and “Direction – z”).<br><br>
DOI: 10.15161/oar.it/76872
title: Geological 3D model of the Po Basin

description: The geological 3D model of the Po Basin includes the geometry of four stratigraphic horizons (top or unconformity) bounding lithological homogeneous successions of sedimentary units, in the Triassic - Pleistocene time interval, and 179 fault geometries. Each stratigraphic horizon is supplemented by its isobaths. Where possible, the thickness of the succession above or below, respectively for basal unconformity and top, is provided with the surface depth. The lithology, event process, and age of each sedimentary succession are also provided. Each fault, with its upper tip line, is supplemented with the kinematic, mean values for strike, dip azimuth, and dip derived from the 3D surface geometry, and the age of the oldest and youngest faulted or deformed stratigraphic horizon, if obtainable from the 3D geological model. This harmonized dataset and the related data model were obtained in the framework of the GO-PEG project, co-funded by the Connecting Europe Facility (CEF) of the European Commission. More specifically, this dataset is the output of the Go-Depth use case aiming to provide a methodology and a model to conceptualize, organize and deliver easy-to-use, high-quality, interoperable subsurface information for sustainable planning and use of natural resources. To this aim the data coming from European-funded projects GeoMol (Alpine Space Programme 2012-2015) and GeoERA HotLime (Horizon 2020, 2018-2021) has been used. In view of data interoperability, the data model has been developed as an extension of the INSPIRE Geology data model. The dataset is served through APIs conforming to the OGC API - Feature standard and it is also downloadable in GeoPackage format, anticipating the application of the principles established by the Open Data Directive (Directive (EU) 2019/1024) regarding the sharing of the High-Value Datasets. We acknowledge the listed researchers who contributed seismic and geological data interpretation to the GeoMol and HotLime Project.
description: The dataset has been elaborated in the framework of the GO-PEG (https://www.go-peg.eu/) project, co-funded by the Connecting Europe Facility (CEF) of the European Commission. The geological 3D model derives from the GeoMol project, funded by Alpine Space Programme 2012-2015 (https://www.geomol.eu/) and GeoERA HotLime project, funded by Horizon 2020 2018-2021 (https://geoera.eu/).
DOI: 10.15161/oar.it/76873
title: Geological 3D model of the Po Basin

description: The geological 3D model of the Po Basin includes the geometry of four stratigraphic horizons (top or unconformity) bounding lithological homogeneous successions of sedimentary units, in the Triassic - Pleistocene time interval, and 179 fault geometries. Each stratigraphic horizon is supplemented by its isobaths. Where possible, the thickness of the succession above or below, respectively for basal unconformity and top, is provided with the surface depth. The lithology, event process, and age of each sedimentary succession are also provided. Each fault, with its upper tip line, is supplemented with the kinematic, mean values for strike, dip azimuth, and dip derived from the 3D surface geometry, and the age of the oldest and youngest faulted or deformed stratigraphic horizon, if obtainable from the 3D geological model. This harmonized dataset and the related data model were obtained in the framework of the GO-PEG project, co-funded by the Connecting Europe Facility (CEF) of the European Commission. More specifically, this dataset is the output of the Go-Depth use case aiming to provide a methodology and a model to conceptualize, organize and deliver easy-to-use, high-quality, interoperable subsurface information for sustainable planning and use of natural resources. To this aim the data coming from European-funded projects GeoMol (Alpine Space Programme 2012-2015) and GeoERA HotLime (Horizon 2020, 2018-2021) has been used. In view of data interoperability, the data model has been developed as an extension of the INSPIRE Geology data model. The dataset is served through APIs conforming to the OGC API - Feature standard and it is also downloadable in GeoPackage format, anticipating the application of the principles established by the Open Data Directive (Directive (EU) 2019/1024) regarding the sharing of the High-Value Datasets. We acknowledge the listed researchers who contributed seismic and geological data interpretation to the GeoMol and HotLime Project.
description: The dataset has been elaborated in the framework of the GO-PEG (https://www.go-peg.eu/) project, co-funded by the Connecting Europe Facility (CEF) of the European Commission. The geological 3D model derives from the GeoMol project, funded by Alpine Space Programme 2012-2015 (https://www.geomol.eu/) and GeoERA HotLime project, funded by Horizon 2020 2018-2021 (https://geoera.eu/).
DOI: 10.18742/23575080
title: Lotus contributors (issues 1-19)

description: List of all the contributors of issues 1 to 19 (1968-1974) of the journal <em>Lotus: Afro-Asian Writings</em>, published by the Afro-Asian Writers' Association. Names of contributors are accompanied by the year and issue in which they appear, the country of origin (as listed in the journal table of contents), and the type of contribution published. A second sheet in the document contains stats by countries of origin, showing the number of entries and authors from each country represented in these issues of the journal.
DOI: 10.18742/23575080.v1
title: Lotus contributors (issues 1-19)

description: List of all the contributors of issues 1 to 19 (1968-1974) of the journal <em>Lotus: Afro-Asian Writings</em>, published by the Afro-Asian Writers' Association. Names of contributors are accompanied by the year and issue in which they appear, the country of origin (as listed in the journal table of contents), and the type of contribution published. A second sheet in the document contains stats by countries of origin, showing the number of entries and authors from each country represented in these issues of the journal.
DOI: 10.11583/dtu.15156507
title: Sandeel survey 2017

description: The purpose of the sand eel dredge survey is to collect sand eels buried in the seabed and compare catches (number and age composition) with the previous year's collections to assess the year class strength of sand eel in area 1r, 2r and 3r of the different areas adopted by ICES in 2016. Data from the dredge survey is the basis for calculating an index, which is used in the stock assessment for sand eel in the North Sea.
DOI: 10.11583/dtu.15156507.v1
title: Sandeel survey 2017

description: The purpose of the sand eel dredge survey is to collect sand eels buried in the seabed and compare catches (number and age composition) with the previous year's collections to assess the year class strength of sand eel in area 1r, 2r and 3r of the different areas adopted by ICES in 2016. Data from the dredge survey is the basis for calculating an index, which is used in the stock assessment for sand eel in the North Sea.
DOI: 10.11583/dtu.12281033
title: The AMACONOE Database (full-scale nitrous oxide emission data)

description: This database consists of full-scale N<sub>2</sub>O emission data and related operational data reported in some publications.<br><b>Data 1</b> links to the publication ''Assessment of Full-Scale N<sub>2</sub>O Emission Characteristics and Testing of Control Concepts in an Activated Sludge Wastewater Treatment Plant with Alternating Aerobic and Anoxic Phases<i>, Environ. Sci. Technol., </i>2019, 53(21), 12485-12494''.<br><b>Data 2</b> links to the publication ''Seasonal and diurnal variability of N<sub>2</sub>O emissions from a full-scale municipal wastewater treatment plant,<i> Science of The Total Environment, </i>2015, 536, 1-11''.<br><b>Data 3</b> links to the publication ''N<sub>2</sub>O Emissions from Activated Sludge Processes, 2008−2009: Results of a National Monitoring Survey in the United States,<i> Environ. Sci. Technol., </i>2010, 44(12), 4505-4511''.