cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.11583/dtu.19688980.v1
title: Onshore wind generation time series for technology SP199 HH150 at resource grade C (PECD 2021 update)

description: This data (csv file) provides simulated hourly time series of onshore wind generation with specific power (SP) 199 W/m2 turbines at hub height (HH) of 150 m for the regions shown in the attached map. The analysed wind power plants are sited at the 50 % lowest mean wind speed locations in each region, i.e., in resource grade (RG) C. The map shows the resulting capacity factors (annual mean). The Excel file gives a rough indication if this wind technology is suitable for the different regions for this RG or not. The available land considers all onshore land area of a region, except lakes, cities, and very high elevation locations. The possible impact of any existing onshore wind installations in the region is not considered. 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 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 (1st link) describes the simulation methodology (combination of ERA5 and GWA data is used). It is requested that the paper is cited when the data are used. The linked related journal paper (2nd link) describes the concept of resource grades and how they can be applied in energy system analyses. 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.19689007
title: Onshore wind generation time series for technology SP277 HH200 at resource grade B (PECD 2021 update)

description: This data (csv file) provides simulated hourly time series of onshore wind generation with specific power (SP) 277 W/m2 turbines at hub height (HH) of 200 m for the regions shown in the attached map. The analysed wind power plants are sited at the 10...50 % highest mean wind speed locations in each region, i.e., in resource grade (RG) B. The map shows the resulting capacity factors (annual mean). The Excel file gives a rough indication if this wind technology is suitable for the different regions for this RG or not. The available land considers all onshore land area of a region, except lakes, cities, and very high elevation locations. The possible impact of any existing onshore wind installations in the region is not considered. 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 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 (1st link) describes the simulation methodology (combination of ERA5 and GWA data is used). It is requested that the paper is cited when the data are used. The linked related journal paper (2nd link) describes the concept of resource grades and how they can be applied in energy system analyses. 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.19689007.v1
title: Onshore wind generation time series for technology SP277 HH200 at resource grade B (PECD 2021 update)

description: This data (csv file) provides simulated hourly time series of onshore wind generation with specific power (SP) 277 W/m2 turbines at hub height (HH) of 200 m for the regions shown in the attached map. The analysed wind power plants are sited at the 10...50 % highest mean wind speed locations in each region, i.e., in resource grade (RG) B. The map shows the resulting capacity factors (annual mean). The Excel file gives a rough indication if this wind technology is suitable for the different regions for this RG or not. The available land considers all onshore land area of a region, except lakes, cities, and very high elevation locations. The possible impact of any existing onshore wind installations in the region is not considered. 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 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 (1st link) describes the simulation methodology (combination of ERA5 and GWA data is used). It is requested that the paper is cited when the data are used. The linked related journal paper (2nd link) describes the concept of resource grades and how they can be applied in energy system analyses. 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.16652059
title: Supporting data - Performance analysis of a high-efficiency multi-bed active magnetic regenerator device

description: Supporting data for publication 'Performance analysis of a high-efficiency multi-bed active magnetic regenerator device" submitted to the Applied Thermal Engineering (DOI 10.1016/j.applthermaleng.2021.117569)<br>The Excel sheet summarizes the experimental output parameters for the performance data presented in the publication. All data were measured continuously after reaching steady-state conditions, and the data were averaged over a time span of 600 s.
DOI: 10.11583/dtu.16652059.v1
title: Supporting data - Performance analysis of a high-efficiency multi-bed active magnetic regenerator device

description: Supporting data for publication 'Performance analysis of a high-efficiency multi-bed active magnetic regenerator device" submitted to the Applied Thermal Engineering (DOI 10.1016/j.applthermaleng.2021.117569)<br>The Excel sheet summarizes the experimental output parameters for the performance data presented in the publication. All data were measured continuously after reaching steady-state conditions, and the data were averaged over a time span of 600 s.
DOI: 10.11583/dtu.16887769
title: North Atlantic fish stock recruitment, spawning stock biomass, weight at age and numbers at age

description: AbstractThe correct prediction of the shape and strength of density-dependence in productivity is key to predicting future stock development and providing the best possible long-term fisheries management advice. We identify unbiased estimators of the relationship between somatic growth, recruitment and density, and applied these to 80 stocks in the Northeast Atlantic. The data used for the analysis is published here.MethodsThe data here have been used in an analysis of density dependent growth and recruitment currently submitted to Fish and Fisheries. The data set includes data on 25 species divided into 80 stocks. Usage NotesN1= number at age 1 and so forth, W1= weight at age 1 and so forth. -1 denotes missing value.
DOI: 10.11583/dtu.16887769.v1
title: North Atlantic fish stock recruitment, spawning stock biomass, weight at age and numbers at age

description: AbstractThe correct prediction of the shape and strength of density-dependence in productivity is key to predicting future stock development and providing the best possible long-term fisheries management advice. We identify unbiased estimators of the relationship between somatic growth, recruitment and density, and applied these to 80 stocks in the Northeast Atlantic. The data used for the analysis is published here.MethodsThe data here have been used in an analysis of density dependent growth and recruitment currently submitted to Fish and Fisheries. The data set includes data on 25 species divided into 80 stocks. Usage NotesN1= number at age 1 and so forth, W1= weight at age 1 and so forth. -1 denotes missing value.
DOI: 10.5281/zenodo.4944295
title: Hypocentral Locations for El Hierro (2011) and Torreperogil (2012-2013) Seismic swarms

description: <strong>Hypocentral Locations for El Hierro and Torreperogil seismic swarms</strong><br> <br> Both xlsx files have 2 sheets: Master Cluster sheet: Hypocentral Parameters and associated hypocentral errors obtained by Master Cluster Method Hypoellipse sheet: Hypocentral Parameters and associated hypocentral errors obtained by Hypoellipse Method Each sheet have same header: Origin Time Timestamp (seconds) Latitude (deg) Longitude (deg) Depth (km) Error Origin Time (s) Latitude Error (km) Longitude Error (km) Depth Error (km) Errors with 0 value are missconvergences. <br> <br> New set
DOI: 10.5281/zenodo.4944294
title: Hypocentral Locations for El Hierro (2011) and Torreperogil (2012-2013) Seismic swarms

description: <strong>Hypocentral Locations for El Hierro and Torreperogil seismic swarms</strong><br> <br> Both xlsx files have 2 sheets: Master Cluster sheet: Hypocentral Parameters and associated hypocentral errors obtained by Master Cluster Method Hypoellipse sheet: Hypocentral Parameters and associated hypocentral errors obtained by Hypoellipse Method Each sheet have same header: Origin Time Timestamp (seconds) Latitude (deg) Longitude (deg) Depth (km) Error Origin Time (s) Latitude Error (km) Longitude Error (km) Depth Error (km) Errors with 0 value are missconvergences. <br> <br> New set
DOI: 10.18454/rulb.2023.43.24.1
title: Топ медиаплатформ в декабре 2019 г.

description: Russian Linguistic Bulletin, Выпуск 7 (43) 2023
DOI: 10.18454/rulb.2023.43.32.3
title: Терминологическая запись для термина brand ‘бренд’

description: Russian Linguistic Bulletin, Выпуск 7 (43) 2023
DOI: 10.18454/rulb.2023.43.24.2
title: Топ медиаплатформ в феврале 2020 г.

description: Russian Linguistic Bulletin, Выпуск 7 (43) 2023
DOI: 10.18454/rulb.2023.43.7.1
title: Современные англоязычные концепты внутренней исламской коммуникации (на основании данных корпусов BNC CoCA)

description: Russian Linguistic Bulletin, Выпуск 7 (43) 2023
DOI: 10.18454/rulb.2023.43.7.2
title: Примеры контекста образцов англоязычных текстов, содержащих концепт MUSLIM, в корпусах BNC и CoCA

description: Russian Linguistic Bulletin, Выпуск 7 (43) 2023
DOI: 10.18454/rulb.2023.43.9.3
title: Зависимость процента верных ответов от института обучения и количества изучаемых языков

description: Russian Linguistic Bulletin, Выпуск 7 (43) 2023
DOI: 10.11583/dtu.14705982
title: Questionnaire on perceived indoor climate and technical installations

description: This questionnaire was developed as part of an industrial PhD project between Saint-Gobain Nordic A/S and the Technical University of Denmark conducted by Lucile Sarran, under the supervision of Carsten Rode, Christian Hviid, Jakub Kolarik and Elisabeth Wærsted. Please cite as: Sarran, Lucile; Hviid, Christian Anker; Rode, Carsten (2019): Questionnaire on perceived indoor climate and technical installations. Technical University of Denmark. Dataset. https://doi.org/10.11583/DTU.14705982. This work is licensed under CC-BY version 4.0.<br>The questionnaire was sent in January 2019 to over 2,000 houses, both old and retrofitted, in a social housing complex. It aimed at understanding their satisfaction with the indoor environmental quality and the technical installations (heating and mechanical ventilation) in their homes. The questionnaire was sent in Danish. 344 households completed it (17.1%).<br>The following themes were developed in the questionnaire:- Background of the respondent- Satisfaction with thermal comfort- Respondents’ satisfaction with their possibility to control and interact with the heating system- Satisfaction with indoor air quality- Satisfaction with the quality of the ventilation supply air- Respondents’ satisfaction with their possibility to control and interact with the ventilation system- Window opening behaviour- Interest in diverse proposals regarding information and control on indoor climate.<br>This dataset consists of the questionnaire text, both the original Danish version and an English translation, in PDF format.<br>More information on the development of the questionnaire and the analysis of the results can be found in the following article: https://doi.org/10.1016/j.buildenv.2020.106946 <br>
DOI: 10.11583/dtu.16652074
title: Data for "Enhancement of Li-mediated ammonia synthesis by addition of oxygen"

description: Treated and raw data of Electrochemistry (CP, LSV, PEIS, FE vs O2)Mass spectrometryXRDXPSTheoretical calculations<br>The treated data can be opened with origin and excelThe raw data can be opened with EC-Lab (Echem Data), HighScorePlus (XRD), Avantage (XPS) or QUADERA (MS)The theoretical data can be opened with python.
DOI: 10.11583/dtu.16652074.v1
title: Data for "Enhancement of Li-mediated ammonia synthesis by addition of oxygen"

description: Treated and raw data of Electrochemistry (CP, LSV, PEIS, FE vs O2)Mass spectrometryXRDXPSTheoretical calculations<br>The treated data can be opened with origin and excelThe raw data can be opened with EC-Lab (Echem Data), HighScorePlus (XRD), Avantage (XPS) or QUADERA (MS)The theoretical data can be opened with python.
DOI: 10.5258/soton/d2381
title: Dataset in support of the publication 'A combined imaging, deformation and registration methodology for predicting respirator fitting'

description: Dataset in support of the journal article published in PLOS One https://doi.org/10.1371/journal.pone.0277570 The dataset includes the face geometry (.stl files) of 8 individuals, scanned with a MRI 3D imaging technique, with and without respirator in situ (loaded and unloaded, respectively). It also includes for each individual the result of a respirator to face registration characterised by different degree of respirator's deformation and the respirator's goodness of fit result. MicroCT scan of the respirator and its corresponding parameters are also included.
DOI: 10.11583/dtu.11798655
title: Circular Economy Business Model Configurator

description: ContentThe Circular Economy Business Model Configurator is a planning and decision-support tool suited for the early stage of when manufacturing companies decide to develop or change their business models for Circular Economy. The beta version of the tool is available in Excel and comprises four modules: · Module 1: identification of opportunities for designing new Circular Economy business models · Module 2: transforming opportunities into ideas, which means combining different business model patterns and adapting them to make sense for the company’s context · Module 3: configuration of complete circular economy business model concepts · Module 4: preliminary assessments of the economic and resource decoupling potential of business models <br>How to applyRecommended as support mainly for the facilitator of innovation processes or Circular Economy initiatives to access advanced recommendations and benchmark with best practices for discussing with the innovation team, to perform calculations for evaluating the resource decoupling or economic potential, and to structure and create an accounting of decisions taken during the process.Detailed instructions about how to use the tool are provided in the Workbook 2 (see Activity 2) available at http://circitnord.com/.<br><br>If you wish to obtain more information about this tool, please contact: mdpp@mek.dtu.dkdanpi@mek.dtu.dktmca@dtu.dk
DOI: 10.11583/dtu.11798655.v2
title: Circular Economy Business Model Configurator

description: ContentThe Circular Economy Business Model Configurator is a planning and decision-support tool suited for the early stage of when manufacturing companies decide to develop or change their business models for Circular Economy. The beta version of the tool is available in Excel and comprises four modules: · Module 1: identification of opportunities for designing new Circular Economy business models · Module 2: transforming opportunities into ideas, which means combining different business model patterns and adapting them to make sense for the company’s context · Module 3: configuration of complete circular economy business model concepts · Module 4: preliminary assessments of the economic and resource decoupling potential of business models <br>How to applyRecommended as support mainly for the facilitator of innovation processes or Circular Economy initiatives to access advanced recommendations and benchmark with best practices for discussing with the innovation team, to perform calculations for evaluating the resource decoupling or economic potential, and to structure and create an accounting of decisions taken during the process.Detailed instructions about how to use the tool are provided in the Workbook 2 (see Activity 2) available at http://circitnord.com/.<br><br>If you wish to obtain more information about this tool, please contact: mdpp@mek.dtu.dkdanpi@mek.dtu.dktmca@dtu.dk
DOI: 10.11583/dtu.11798655.v1
title: Circular Economy Business Model Configurator

description: ContentThe Circular Economy Business Model Configurator is a planning and decision-support tool suited for the early stage of when manufacturing companies decide to develop or change their business models for Circular Economy. The beta version of the tool is available in Excel and comprises four modules: · Module 1: identification of opportunities for designing new Circular Economy business models · Module 2: transforming opportunities into ideas, which means combining different business model patterns and adapting them to make sense for the company’s context · Module 3: configuration of complete circular economy business model concepts · Module 4: preliminary assessments of the economic and resource decoupling potential of business models <br>How to applyRecommended as support mainly for the facilitator of innovation processes or Circular Economy initiatives to access advanced recommendations and benchmark with best practices for discussing with the innovation team, to perform calculations for evaluating the resource decoupling or economic potential, and to structure and create an accounting of decisions taken during the process.Detailed instructions about how to use the tool are provided in the Workbook 2 (see Activity 2) available at http://circitnord.com/.<br><br>If you wish to obtain access to this tool, please contact: mdpp@mek.dtu.dkdanpi@mek.dtu.dktmca@dtu.dk
DOI: 10.11583/dtu.14138057
title: PMF Files (TIP4P/2005)

description: Contains files with data of PMF landscape at different temperatures and pressures. The file names indicate the temperature and pressure of the system.<br>This folder contains data of TIP4P/2005 water model. The x column indicates the O--H distance (A), the y column contains the O-H-O angles (degrees) and the z column has the PMF values in kT<br>This item is a part of the collection “Data for scientific article- Potential of mean force based identification of strong and weak hydrogen bonds in liquid water”, https://doi.org/10.11583/dtu.c.5324957<br>
DOI: 10.11583/dtu.14138057.v1
title: PMF Files (TIP4P/2005)

description: Contains files with data of PMF landscape at different temperatures and pressures. The file names indicate the temperature and pressure of the system.<br>This folder contains data of TIP4P/2005 water model. The x column indicates the O--H distance (A), the y column contains the O-H-O angles (degrees) and the z column has the PMF values in kT<br>This item is a part of the collection “Data for scientific article- Potential of mean force based identification of strong and weak hydrogen bonds in liquid water”, https://doi.org/10.11583/dtu.c.5324957<br>
DOI: 10.11583/dtu.21548196
title: Data set for "Two-Dimensional Elliptically Shaped Electromagnetic Vibration Energy Harvester"

description: This data set is for the article "Two-Dimensional Elliptically Shaped Electromagnetic Vibration Energy Harvester". <br> The data contains the measured voltage as function of time for the different harvester configurations presented in the article. <br> The data is structured as follows: <br> The 1D vibrations and the 2D vibration directories contain the voltage as function of time for different frequencies for the respective configuration. <br> In the 1D vibration folder, the subdirectories are named after the angle that the harvester was placed at with respect to the direction of vibration. <br> In the 2D vibration folder the subdirectories are named after the frequency of vibration along the semi minor axis. <br> In each subdirectory the files are named according to the frequency at the semi major axis that the experiment was run at, eg. the file B825.txt contains the voltage measured as function of time for driven with a frequency of 8.25 Hz along the semi major axis. <br>
DOI: 10.11583/dtu.21548196.v1
title: Data set for "Two-Dimensional Elliptically Shaped Electromagnetic Vibration Energy Harvester"

description: This data set is for the article "Two-Dimensional Elliptically Shaped Electromagnetic Vibration Energy Harvester". <br> The data contains the measured voltage as function of time for the different harvester configurations presented in the article. <br> The data is structured as follows: <br> The 1D vibrations and the 2D vibration directories contain the voltage as function of time for different frequencies for the respective configuration. <br> In the 1D vibration folder, the subdirectories are named after the angle that the harvester was placed at with respect to the direction of vibration. <br> In the 2D vibration folder the subdirectories are named after the frequency of vibration along the semi minor axis. <br> In each subdirectory the files are named according to the frequency at the semi major axis that the experiment was run at, eg. the file B825.txt contains the voltage measured as function of time for driven with a frequency of 8.25 Hz along the semi major axis. <br>
DOI: 10.6084/m9.figshare.23653254
title: 412ERVi_Seq.fas

description: The DNA sequences of all the 412 novel ERVi identified in "Genome mining shows that retroviruses are pervasively invading vertebrate genomes"