cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5258/soton/d2454
title: Dataset of Segmented thermoelectric generator modelling and optimization using artificial neural networks by iterative training

description: This paper "Segmented thermoelectric generator modelling and optimization using artificial neural networks by iterative training" Published in Energy and AI. https://doi.org/10.1016/j.egyai.2022.100225
DOI: 10.11583/dtu.12504500
title: Corrigenda for the textbook: Turbulence in Coastal and Civil Engineering, by B. Mutlu Sumer and David R. Fuhrman

description: This document contains a list of known typographical errors for the textbook: <br>Sumer, B.M. & Fuhrman, D.R. (2020) Turbulence in Coastal and Civil Engineering. World Scientific. https://doi.org/10.1142/10829<br><br><br>
DOI: 10.11583/dtu.12504500.v6
title: Corrigenda for the textbook: Turbulence in Coastal and Civil Engineering, by B. Mutlu Sumer and David R. Fuhrman

description: This document contains a list of known typographical errors for the textbook: <br>Sumer, B.M. & Fuhrman, D.R. (2020) Turbulence in Coastal and Civil Engineering. World Scientific. https://doi.org/10.1142/10829<br><br><br>
DOI: 10.11583/dtu.14267861
title: Global Wind Atlas v3 (orography and bathymetry)

description: This data combines the GEBCO bathymetric dataset with the SRTMv3 and Viewfinder 3 arc-second orography data. The data is interpolated to 250m, and all land locations are given positive values, while water surfaces are given negative values.<br><b>Orographic height over land</b><br>Void-filled SRTM data was used between 60°N and 60°S, with a few exceptions where the void filling process introduced artifacts that were not present in the Viewfinder Panoramas Digital Elevation Model. This was particularly apparent in the Pacific islands.<br><br>North of 60°N the Viewfinder Panoramas DEM was used, allowing us to include model results for large parts of Scandinavia, Russia, and Canada. For these areas, the main sources to the Viewfinder Panoramas DEM are height contours from Russian military maps and Canadian Digital Elevation Data. The Viewfinder Panoramas DEM had several void regions which were filled using a cubic interpolation in the y-dimension of the raster. This was chosen after investigating many of the void regions and finding that they tended to run east-west.<br>Both DEM datasets were provided as 1° by 1° tiles in the WGS 1984 coordinate system (EPSG: 4326). To support the UTM projection used in the modeling, the data was re-projected to a 150m grid spacing using cubic interpolation. The interpolation was done using the Geospatial Data Abstraction Library (GDAL) tool gdalwarp. The 150m resolution was selected as it corresponds to the effective resolution of the SRTM data.<br>The data was then re-projected again in the WAsP model to the 250m using the approach of the European Wind Atlas.<br><br><b>Bathymetry data (Oceans)</b><b><br></b>Negative elevation data for seabed bathymetry was obtained from GEBCO’s gridded bathymetric data set, the GEBCO_2020 grid, which is a global terrain model for ocean and land at 15 arc-second intervals. The GEBCO_2020 grid was prepared for use in the GWA by the World Bank Group.<br>Data set attribution: GEBCO Compilation Group (2020) GEBCO 2020 Grid (doi:10.5285/a29c5465-b138-234d-e053-6c86abc040b9).<br><b>Data combination</b><b><br></b>The datasets were combined by first masking each using the fine resolution of the GSHHG coastline dataset, to ensure that all land values were positive and all water values were negative, with no data have a value of 0.
DOI: 10.17028/rd.lboro.23667174
title: Supplementary information files for A proposed universal definition of a Digital Product Passport Ecosystem (DPPE): Worldviews, discrete capabilities, stakeholder requirements and concerns

description: Supplementary files for article A proposed universal definition of a Digital Product Passport Ecosystem (DPPE): Worldviews, discrete capabilities, stakeholder requirements and concerns This paper contributes new knowledge and understanding about the role that Product Passports might play in advancing sustainable business practices towards a Circular Economy. The significance of this research is the proposed universal definition of a Digital Product Passport Ecosystem (DPPE) for international policy, industrial and technical communities. The novelty of this research lies in the systems thinking approach, coupled with systems engineering, to define and model a DPPE as a System of Systems to derive a definition. Stakeholder perspectives and requirements concerning Product Passports were synthesised using data and analysis from the European Commission's (EC) open consultation on the Sustainable Products Initiative (SPI). Nine high-level capabilities of a DPPE have been identified, and each is explored by mapping a list of information requirements discussed within the consultation. It is shown that different Product Passport applications benefit (or detriment) different stakeholder groups. Findings suggest that DPPE solutions must be systemic, providing interoperability across multiple product life cycles, organisations, supply chains, and value chains in order to operate across international borders: thus realising benefits for world (circular) economies and the planet. Furthermore, it is proposed that if stakeholders utilise a universal definition of a DPPE in conjunction with a set of agreed ethical principles to underpin legislation, there would be fewer contradictions and ambiguity between stakeholders regarding the purpose of a Product Passport and the reasons for sharing data. Finally, the authors conclude that more research is needed on incentives for producers to share data and integrate their existing production systems with the broader ecosystem architectures to allow for maximum interoperability with minimal duplication. In addition, future research should determine specific DPP information requirements on a product-by-product basis, along with opportunities that a DPPE will enable towards industrial symbiosis.
DOI: 10.17028/rd.lboro.23667174.v1
title: Supplementary information files for A proposed universal definition of a Digital Product Passport Ecosystem (DPPE): Worldviews, discrete capabilities, stakeholder requirements and concerns

description: Supplementary files for article A proposed universal definition of a Digital Product Passport Ecosystem (DPPE): Worldviews, discrete capabilities, stakeholder requirements and concerns This paper contributes new knowledge and understanding about the role that Product Passports might play in advancing sustainable business practices towards a Circular Economy. The significance of this research is the proposed universal definition of a Digital Product Passport Ecosystem (DPPE) for international policy, industrial and technical communities. The novelty of this research lies in the systems thinking approach, coupled with systems engineering, to define and model a DPPE as a System of Systems to derive a definition. Stakeholder perspectives and requirements concerning Product Passports were synthesised using data and analysis from the European Commission's (EC) open consultation on the Sustainable Products Initiative (SPI). Nine high-level capabilities of a DPPE have been identified, and each is explored by mapping a list of information requirements discussed within the consultation. It is shown that different Product Passport applications benefit (or detriment) different stakeholder groups. Findings suggest that DPPE solutions must be systemic, providing interoperability across multiple product life cycles, organisations, supply chains, and value chains in order to operate across international borders: thus realising benefits for world (circular) economies and the planet. Furthermore, it is proposed that if stakeholders utilise a universal definition of a DPPE in conjunction with a set of agreed ethical principles to underpin legislation, there would be fewer contradictions and ambiguity between stakeholders regarding the purpose of a Product Passport and the reasons for sharing data. Finally, the authors conclude that more research is needed on incentives for producers to share data and integrate their existing production systems with the broader ecosystem architectures to allow for maximum interoperability with minimal duplication. In addition, future research should determine specific DPP information requirements on a product-by-product basis, along with opportunities that a DPPE will enable towards industrial symbiosis.
DOI: 10.6084/m9.figshare.23667159
title: Dataset: 'Sea turtle egg yolk and albumen as biomonitoring matrices for maternal burdens of organic pollutants'

description: This archive contains the dataset used for the publication: <br> Munoz C.C. and Vermeiren P. (2023) Sea turtle egg yolk and albumen as biomonitoring matrices for maternal burdens of organic pollutants, Marine Pollution Bulletin https://doi.org/10.1016/j.marpolbul.2023.115280 ---------------------------------------------------------------- column names: ID -&gt; unique egg identifier Compound_class, Compound -&gt; names of all compounds analysed, with their detected levels (LOD-value when below the detection limit, NA when PBDEs were not analysed in plasma), as described in the publication. Yolk_cen, Albumen_cen, Plasma_cen -&gt; indicated if the values was &lt; LOD (TRUE) ----------------------------------------------------------------
DOI: 10.6084/m9.figshare.23667159.v1
title: Dataset: 'Sea turtle egg yolk and albumen as biomonitoring matrices for maternal burdens of organic pollutants'

description: This archive contains the dataset used for the publication: <br> Munoz C.C. and Vermeiren P. (2023) Sea turtle egg yolk and albumen as biomonitoring matrices for maternal burdens of organic pollutants, Marine Pollution Bulletin https://doi.org/10.1016/j.marpolbul.2023.115280 ---------------------------------------------------------------- column names: ID -&gt; unique egg identifier Compound_class, Compound -&gt; names of all compounds analysed, with their detected levels (LOD-value when below the detection limit, NA when PBDEs were not analysed in plasma), as described in the publication. Yolk_cen, Albumen_cen, Plasma_cen -&gt; indicated if the values was &lt; LOD (TRUE) ----------------------------------------------------------------
DOI: 10.5281/zenodo.8138600
title: REACH_2ndCall_Shortlist_Anonymised

description: File with all participants of the 2nd round of the incubator, from the initially submitted applicants to the final winners.
DOI: 10.5281/zenodo.8138601
title: REACH_2ndCall_Shortlist_Anonymised

description: File with all participants of the 2nd round of the incubator, from the initially submitted applicants to the final winners.
DOI: 10.5281/zenodo.8138609
title: TP53 mutations are associated with improved survival in ovarian carcinoma patients receiving first-line chemotherapy plus bevacizumab: results from the MITO16A/MaNGO OV-2 study

description: <strong>PURPOSE</strong> Bevacizumab (BEV) is considered an effective treatment option for advanced ovarian carcinoma. However, to date, there are no biomarkers that define a BEV-responsive patient subpopulation. <strong>METHODS</strong> In the context of the MITO16A/MaNGO OV-2 trial, a phase IV study of chemotherapy combined with BEV in first-line treatment of advanced ovarian carcinoma, we evaluated <em>TP53</em> mutations by next generation sequencing (NGS) and p53 protein expression by immunohistochemistry (IHC) on 202 and 311 cases, respectively. We further correlated NGS and IHC data with clinicopathological characteristics and survival of patients. <strong>RESULTS</strong> <em>TP53</em> mutations of unknown function (named unclassified), mostly of the missense type, represented the majority of variants in our population (44.4%) and were associated with a significantly improved overall survival both in univariate (p=0.03, HR=0.43) and multivariate analysis (p=0.012, HR=0.39). Concordance between <em>TP53 </em>mutational analysis and protein expression was 91%. A trend toward improved OS was observed in patients with p53 IHC overexpression (HR=0.70, p=0.15) compared to p53 wild-type patients. <strong>CONCLUSION </strong>Our results indicate that the presence of unclassified <em>TP53</em> mutations has favorable prognostic significance in patients with ovarian carcinoma receiving upfront BEV plus chemotherapy. In particular, unclassified missense <em>TP53</em> mutations characterize a subpopulation of patients with a significant survival advantage, independently of clinicopathological characteristics. Our findings warrant future investigations to confirm the prognostic impact of <em>TP53 </em>mutations in BEV-treated ovarian carcinoma patients and deserve to be assessed for their potential predictive role in future randomized clinical studies.
DOI: 10.5281/zenodo.8138608
title: TP53 mutations are associated with improved survival in ovarian carcinoma patients receiving first-line chemotherapy plus bevacizumab: results from the MITO16A/MaNGO OV-2 study

description: <strong>PURPOSE</strong> Bevacizumab (BEV) is considered an effective treatment option for advanced ovarian carcinoma. However, to date, there are no biomarkers that define a BEV-responsive patient subpopulation. <strong>METHODS</strong> In the context of the MITO16A/MaNGO OV-2 trial, a phase IV study of chemotherapy combined with BEV in first-line treatment of advanced ovarian carcinoma, we evaluated <em>TP53</em> mutations by next generation sequencing (NGS) and p53 protein expression by immunohistochemistry (IHC) on 202 and 311 cases, respectively. We further correlated NGS and IHC data with clinicopathological characteristics and survival of patients. <strong>RESULTS</strong> <em>TP53</em> mutations of unknown function (named unclassified), mostly of the missense type, represented the majority of variants in our population (44.4%) and were associated with a significantly improved overall survival both in univariate (p=0.03, HR=0.43) and multivariate analysis (p=0.012, HR=0.39). Concordance between <em>TP53 </em>mutational analysis and protein expression was 91%. A trend toward improved OS was observed in patients with p53 IHC overexpression (HR=0.70, p=0.15) compared to p53 wild-type patients. <strong>CONCLUSION </strong>Our results indicate that the presence of unclassified <em>TP53</em> mutations has favorable prognostic significance in patients with ovarian carcinoma receiving upfront BEV plus chemotherapy. In particular, unclassified missense <em>TP53</em> mutations characterize a subpopulation of patients with a significant survival advantage, independently of clinicopathological characteristics. Our findings warrant future investigations to confirm the prognostic impact of <em>TP53 </em>mutations in BEV-treated ovarian carcinoma patients and deserve to be assessed for their potential predictive role in future randomized clinical studies.
DOI: 10.6084/m9.figshare.23650620
title: Raw Data

description: Effect of safranal or condesartan on 3-nitropropionicacid-induced biochemica. Behavioral and histological alterations in a rat model of huntington's isease
DOI: 10.6084/m9.figshare.23650620.v1
title: Raw Data

description: Effect of safranal or condesartan on 3-nitropropionicacid-induced biochemica. Behavioral and histological alterations in a rat model of huntington's isease
DOI: 10.5258/soton/d2460
title: Data associated with the PhD thesis entitled: "Investigating how benthic trawl gear design and location affect the resuspension of sediments and dissolved nutrients from the seafloor".

description: Data are for trawling experiments carried out in the Dornoch Firth area, Scotland for the years 2015, 2016 and 2017. Data were used in the thesis: "Investigating how benthic trawl gear design and location affect the resuspension of sediments and dissolved nutrients from the seafloor". Data in the 2015 file includes trawl component type (dimensions of the roller) and associated drag and pressure, and the resulting nutrient and Particle Size Distribution (PSD) data at different heights of the seafloor. Samples were collected at the Hollows and Dornoch Bay sites in the Dornoch Firth area on the 08/05/2015. Data in the 2016 file includes trawl component type (dimensions of the roller) and associated drag with consistent pressure (no added weights), and the resulting nutrient and Particle Size Distribution (PSD) data at different heights of the seafloor. Samples were collected at 6 sites: Banff, Hollows, Dornoch offshore, Lossie, Lossie prawn fishery and Dornoch offshore, between the 26/08/2016 to 04/10/2016. Data in the 2017 file includes a single trawl component type (400 Block, 600 long) and associated drag with added weights to simulate increasing pressure on the seafloor (tied up, 0kg, 60kg, 120kg). The resulting nutrient and Particle Size Distribution (PSD) data at different heights of the seafloor are reported. Samples were collected at 6 different sites: 2 at Banff-Buckie, 3 in the area of Lossie-Burghead and 1 at Dornoch. Trawls were conducted between the 01/08/2017 and 08/08/2017. This work was supported by a NERC CASE PhD studentship (NE/N007999/1).
DOI: 10.11583/dtu.14546616
title: Data for "Improved dynamic imaging of multiphase flow by constrained tomographic reconstruction” - simulation_attenuation_blur

description: Ground truth used for forward projection in the article 'Improved dynamic imaging of multiphase flow by constrained tomographic reconstruction'. The forward projections can be reconstructed and compared to with the file <i>simulation_attenuation_rotated.npy </i>https://doi.org/10.11583/DTU.14553741 to check the quality of the reconstruction. The code can be found at https://gitlab.gbar.dtu.dk/pwra/NumericalExperiments<br>This item is a part of the collection: Data for "Improved dynamic imaging of multiphase flow by constrained tomographic reconstruction”, https://doi.org/10.11583/DTU.c.5448594
DOI: 10.11583/dtu.13385936
title: Tennessee Eastman Reference Data for Fault-Detection and Decision Support Systems

description: Extended Tennessee Eastman Reference Data as presented in Reinartz et al. (2021). <br><br>The data contains simulations of 28 process faults for 6 different operating modes. Each fault is simulated 500 times with different seeds for the random number generator. <br>Additional simulations feature setpoint changes and mode transitions between the 6 operating modes. <br>All simulations have a duration of 100 hours with a sampling rate of 3 minutes. <br>Please refer to the Readme and publication for detailed information. <br>
DOI: 10.11583/dtu.19154117
title: Existing onshore wind generation time series (PECD 2021 update)

description: This data (csv file) provides simulated hourly time series of existing onshore wind generation for the regions shown in the attached maps. Only regions with more than 5 wind power plants are simulated (otherwise the data are NaN). The maps show, respectively: capacity factors (annual mean), hub heights (weighted mean), specific powers (weighted mean), commissioning years of the fleets (weighted mean) and installed capacities (sum - note that some regions have higher than 6 GW of installations; due to readabiilty of the figure, above 6 GW are drawn with the same colour). The time stamps are in GMT; the variable (column) names relate to the region names shown in the maps. The data include also country-level aggregations, e.g., UK00 is the aggregated onshore wind generation of all the UK regions (weighted by regional installed capacities). The data are part of the variable renewable energy generation time series created for ENTSO-E in the 2021 update of the Pan-European Climate Database (PECD) dataset. ENTSO-E has used the data in ERAA 2021 and Winter Outlook 2021-2022 assessments, and they are used in TYNDP 2022. The simulations are carried out by DTU Wind Energy, with the future technology selection and data validation discussed and agreed with ENTSO-E and its members. The linked journal paper describes the simulation methodology (combination of ERA5 and GWA data is used) and provides country-level validation results. Please note that compared to the paper, the provided data include some adjustments based on the feedback from ENTSO-E and its members. It is requested that the paper is cited when the data are used. This item is part of a larger collection of wind and solar data: https://doi.org/10.11583/DTU.c.5939581
DOI: 10.11583/dtu.19154117.v1
title: Existing onshore wind generation time series (PECD 2021 update)

description: This data (csv file) provides simulated hourly time series of existing onshore wind generation for the regions shown in the attached maps. Only regions with more than 5 wind power plants are simulated (otherwise the data are NaN). The maps show, respectively: capacity factors (annual mean), hub heights (weighted mean), specific powers (weighted mean), commissioning years of the fleets (weighted mean) and installed capacities (sum - note that some regions have higher than 6 GW of installations; due to readabiilty of the figure, above 6 GW are drawn with the same colour). The time stamps are in GMT; the variable (column) names relate to the region names shown in the maps. The data include also country-level aggregations, e.g., UK00 is the aggregated onshore wind generation of all the UK regions (weighted by regional installed capacities). The data are part of the variable renewable energy generation time series created for ENTSO-E in the 2021 update of the Pan-European Climate Database (PECD) dataset. ENTSO-E has used the data in ERAA 2021 and Winter Outlook 2021-2022 assessments, and they are used in TYNDP 2022. The simulations are carried out by DTU Wind Energy, with the future technology selection and data validation discussed and agreed with ENTSO-E and its members. The linked journal paper describes the simulation methodology (combination of ERA5 and GWA data is used) and provides country-level validation results. Please note that compared to the paper, the provided data include some adjustments based on the feedback from ENTSO-E and its members. It is requested that the paper is cited when the data are used. This item is part of a larger collection of wind and solar data: https://doi.org/10.11583/DTU.c.5939581
DOI: 10.11583/dtu.19690606
title: Offshore wind generation time series for technology SP316 HH155 (PECD 2021 update)

description: This data (csv file) provides simulated hourly time series of offshore wind generation with specific power (SP) 316 W/m2 turbines at hub height (HH) of 155 m for the regions shown in the attached map. The analysed offshore wind power plants are sited at the best sites with max 100 km distance to shore, except for the far-offshore North Sea regions (the regions which do not have any connection to shore) where all locations are allowed. The map shows the resulting capacity factors (annual mean). The Excel file gives the average distance to shore for each individual region. Wake losses are modeled, with additional 5 % of other losses and unavailability considered. The time stamps are in GMT; the variable (column) names relate to the region names shown in the maps. The data include also country-level aggregations, e.g., UK00_OFF is the aggregated offshore wind generation of all the UK regions (weighted by regional installed capacities). The data are part of the variable renewable energy generation time series created for ENTSO-E in the 2021 update of the Pan-European Climate Database (PECD) dataset. ENTSO-E has used the data in ERAA 2021 and Winter Outlook 2021-2022 assessments, and they are used in TYNDP 2022. The simulations are carried out by DTU Wind Energy, with the future technology selection and data validation discussed and agreed with ENTSO-E and its members. The linked journal paper (1st link) describes the ERA5-based simulation methodology. It is requested that the paper is cited when the data are used. The linked related journal paper (2nd link) describes the modeling of wake losses for the offshore wind power plants and the storm shutdown behaviour (the smoothest storm shutdown technology is assumed). This item is part of a larger collection of wind and solar data: https://doi.org/10.11583/DTU.c.5939581