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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Ouled-Cheikh, Jazel;

    Datasets used results obtained in the publication Ouled-Cheikh, J., March, D., Borras-Chavez, R., Drago, M., Goebel, M. E., Fariña, J. M., Gazo, M., Coll, M., Cardona L., 2024. Future climate-induced distribution shifts in a sexually dimorphic key predator of the Southern Ocean. Global Change Biology. The folder structure and the particularities of each dataset are explained in the README file.

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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Recolector de Cienci...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Authors: Thiery, Wim; Lange, Stefan; Rogelj, Joeri; Schleussner, Carl-Friedrich; +33 Authors

    This data set contains the essential files used as input for the analysis, intermediate files produced during the analysis, and the key output fields. The code of the analysis is available here: https://github.com/VUB-HYDR/2021_Thiery_etal_Science Input fields: - isimip.zip: Postprocessed ISIMIP2b simulation output. This data set is very similar to the data presented in Lange et al. (2020 Earth's Future) but includes selected additional impact models and scenarios (notably RCP8.5). This data set also includes the gridded population data. - GMT_50pc_manualoutput_4pathways.xlsx: Global mean temperature anomaly trajectories from the IPCC SR15 - wcde_data.xlsx: postprocessed cohort size data originally obtained from the Wittgenstein Centre Human Capital Data Explorer. - WPP2019_MORT_F16_1_LIFE_EXPECTANCY_BY_AGE_BOTH_SEXES.xlsx: Postprocessed life expectancy data originally obtained from the UNited Nations World Population Programme Intermediate files *only use if you're interested in reproducing the results*: - workspaces.zip: Postprocessed ISIMIP2b simulation output. These matlab workspaces contain data on land area annually exposed to extreme events which is stored in a format designed to speed up the analysis. - mw_isimip.mat: ISIMIP2 simulations metadata (e.g. model, gcm and rcp name per simulation) - mw_countries.mat: information on the countries used in the analysis (e.g. border polygon coordinates) - mw_exposure.mat: age-dependent exposure computed from the ISIMIP and population data - mw_exposure_pic.mat: pre-industrial control age-dependent exposure computed from the ISIMIP and population data - mw_exposure_pic_coldwaves.mat: pre-industrial control age-dependent exposure to coldwaves computed from the ISIMIP and population data Output of the analysis: - mw_output.mat: Matlab workspace containing all variables produced during the analysis presented in thepaper. Use this file if you wish to look up certain numbers or want to use the study results for further analysis.

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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: ZENODO
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: CSIC - Unidad de Tecnología Marina (UTM);

    Oceanographic data acquired during the TRANSIT_20220212 Cruise (29HE20220212) on board the Research Vessel Hespérides in 2022. Transit voyage without any scientific work.

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    Digital.CSIC
    Dataset . 2022
    Data sources: Digital.CSIC
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      Digital.CSIC
      Dataset . 2022
      Data sources: Digital.CSIC
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Campos-Carriedo, Felipe; Iribarren, Diego; Calvo-Rodríguez, Fernando; García-Díaz, Álvaro; +1 Authors

    As the European Union embarks on the energy transition, several challenges need to be faced to ensure that this shift is conducted from a holistic perspective that avoids burden-shifting across sustainability dimensions. One of the main concerns refers to the future availability of materials that clean technologies require. Critical rawmaterial assessment serves to guide the management of such mineral resources in a new paradigm of increasing demand. This work delves into the methodological fundamentals of several product-level criticality indicators in order to discuss their implications within the context of the ecodesign of two hydrogen-related products. Overall, criticality is advised to be assessed making use of several indicators. In the case study of a proton exchange membrane fuel cell stack, the combined interpretation of criticality indicators leads to identifying platinum as the main hotspot, while yttrium and lanthanum account for the most relevant criticality contributions in the casestudy of a solid oxide electrolysis cell stack. The authors would like to thank Gonzalo Puig-Samper and Eleonora Bargiacchi for the insights provided. This work has been carried out within the framework of the projects eGHOST and SH2E. These projects have received funding from the Fuel Cells and Hydrogen 2 Joint Undertaking (now Clean Hydrogen Partnership) under Grant Agreements No. 101007166 and 101007163, respectively. This Joint Undertaking receives support from the European Union’s Horizon 2020 Research and Innovation programme, Hydrogen Europe and Hydrogen Europe Research. The contents of this document are provided “AS IS”. It reflects only the authors’ view and the Joint Undertaking is not responsible for any use that may be made of the information it contains.

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    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: ZENODO
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: ZENODO
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      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Rodero, María Del Rosario; Lebrero, Raquel; Serrano, Esteban; Lara, Enrique; +3 Authors

    Excel document that contains the data of the article: ‘Technology validation of photosynthetic biogas upgrading in a semi-industrial scale algal-bacterial photobioreactor’. This dataset shows the values obtained during the experimental period and it complements the corresponding article.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
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    ZENODO
    Dataset . 2019
    License: CC BY NC ND
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2019
    License: CC BY NC ND
    Data sources: ZENODO
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2019
    License: CC BY NC ND
    Data sources: Datacite
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      ZENODO
      Dataset . 2019
      License: CC BY NC ND
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2019
      License: CC BY NC ND
      Data sources: ZENODO
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      ZENODO
      Dataset . 2019
      License: CC BY NC ND
      Data sources: Datacite
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    Authors: Gili Sardà, Josep María; CSIC - Unidad de Tecnología Marina (UTM);

    The ECOREST_AUV campaign will focus on monitoring restored populations in closed areas and adjacent fishing grounds to assess the evolution of restored populations and monitor the evolution of ecosystem services provided, as well as the provision of habitat, breeding areas or a possible spillover effect of closed areas in adjacent areas. Oceanographic data acquired during the ECOREST_AUV Cruise (29GD20230602) on board the Research Vessel García del Cid in 2023.

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    Digital.CSIC
    Dataset . 2023
    Data sources: Digital.CSIC
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      Digital.CSIC
      Dataset . 2023
      Data sources: Digital.CSIC
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    Authors: Plaza, Aitor; Iriarte, Xabier; Castellano-Aldave, Carlos; Carlosena, Alfonso; +3 Authors

    This dataset contains the measurements of the procedure to fully characterise a novel vibration energy harvester (presented in https://doi.org/10.1016/j.apenergy.2023.120715) operating in the ultra-low-frequency range. The details of the experimental setup and fully characterization procedure can be found in: https://doi.org/10.3390/s24123813 The experimental measurements include not only the input (acceleration)–output (energy) response but also the (internal) dynamic behaviour of the system, making use of a synchronised image processing and signal acquisition system. The result of the processed video (angular positions of the masses) and calculation of their two time derivatives by means of the Tikhonov regularization have also been included. Additionally, the calculation of the power generated in the windings has also been included. In "Videos" folder are the recorded videos at 240fps. In "Measurements" folder data form each experiment can be found in different files. First column is time, second and third columns are accelerometer measurements, and the rest of the columns are the different voltages measured at each coil. In "Post-processed data" are the estimated angular positions (2,3,4 columns), velocities (4,5,6 columns) and accelerations (7,8,9 columns) obtained form the post-processed videos. The last column is the estimated power harvested by the device. The name of the file name is in line with the experiment.

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    Mendeley Data
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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    Mendeley Data
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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      Mendeley Data
      Dataset . 2024
      License: CC BY
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      Mendeley Data
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
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    Authors: Martín, Héctor; CSIC - Unidad de Tecnología Marina (UTM);

    Search and location of the remains of the submarine in the area using side-scan sonar and visual identification with a mini submarine. ARM-REC Cruise (29SG20220502) carried out on the Research Vessel Sarmiento de Gamboa in 2022.

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    Digital.CSIC
    Dataset . 2022
    Data sources: Digital.CSIC
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      Digital.CSIC
      Dataset . 2022
      Data sources: Digital.CSIC
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    Authors: Buessler, Ken; CSIC - Unidad de Tecnología Marina (UTM);

    EXport Processes in the Ocean from Remote Sensing (EXPORTS) is a large-scale NASA-led field campaign that will provide critical information for quantifying the export and fate of upper ocean net primary production (NPP) using satellite observations and state of the art ocean technologies. The goal of EXPORTS is to understand how the organic carbon makes it to the twilight zone and deep ocean interior, and how lon it stays there, which is vital to understanding present and future ocean ecosystems and global climate. Oceanographic data acquired during the EXPORTS Cruise (29SG20210503) on board the Research Vessel Sarmiento de Gamboa in 2021.

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    Digital.CSIC
    Dataset . 2021
    Data sources: Digital.CSIC
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      Digital.CSIC
      Dataset . 2021
      Data sources: Digital.CSIC
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    Authors: Muñoz, Alfonso; CSIC - Unidad de Tecnología Marina (UTM);

    The MARIBNO project is located in the NW zone of Iberia, which constitutes an ideal environment to raise the following main objectives: 1. Study of the cortical structure at the western end of the Cantabrian Mountains and the transition zone between the western and northern margins of Iberia. 2. Study of the tectonic control exerted by the previous structures during the two main alpine stages. 3. Mapping and characterization of cortical domains using a multidisciplinary approach. Definition and application of geophysical and geological criteria applicable to the zonation of cortical domains in other parts of the world with similar contexts. Oceanographic data acquired during the MARIBNO Cruise (29SG20210914) on board the Research Vessel Sarmiento de Gamboa in 2021.

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    Digital.CSIC
    Dataset . 2021
    Data sources: Digital.CSIC
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      Digital.CSIC
      Dataset . 2021
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    Authors: Ouled-Cheikh, Jazel;

    Datasets used results obtained in the publication Ouled-Cheikh, J., March, D., Borras-Chavez, R., Drago, M., Goebel, M. E., Fariña, J. M., Gazo, M., Coll, M., Cardona L., 2024. Future climate-induced distribution shifts in a sexually dimorphic key predator of the Southern Ocean. Global Change Biology. The folder structure and the particularities of each dataset are explained in the README file.

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    Authors: Thiery, Wim; Lange, Stefan; Rogelj, Joeri; Schleussner, Carl-Friedrich; +33 Authors

    This data set contains the essential files used as input for the analysis, intermediate files produced during the analysis, and the key output fields. The code of the analysis is available here: https://github.com/VUB-HYDR/2021_Thiery_etal_Science Input fields: - isimip.zip: Postprocessed ISIMIP2b simulation output. This data set is very similar to the data presented in Lange et al. (2020 Earth's Future) but includes selected additional impact models and scenarios (notably RCP8.5). This data set also includes the gridded population data. - GMT_50pc_manualoutput_4pathways.xlsx: Global mean temperature anomaly trajectories from the IPCC SR15 - wcde_data.xlsx: postprocessed cohort size data originally obtained from the Wittgenstein Centre Human Capital Data Explorer. - WPP2019_MORT_F16_1_LIFE_EXPECTANCY_BY_AGE_BOTH_SEXES.xlsx: Postprocessed life expectancy data originally obtained from the UNited Nations World Population Programme Intermediate files *only use if you're interested in reproducing the results*: - workspaces.zip: Postprocessed ISIMIP2b simulation output. These matlab workspaces contain data on land area annually exposed to extreme events which is stored in a format designed to speed up the analysis. - mw_isimip.mat: ISIMIP2 simulations metadata (e.g. model, gcm and rcp name per simulation) - mw_countries.mat: information on the countries used in the analysis (e.g. border polygon coordinates) - mw_exposure.mat: age-dependent exposure computed from the ISIMIP and population data - mw_exposure_pic.mat: pre-industrial control age-dependent exposure computed from the ISIMIP and population data - mw_exposure_pic_coldwaves.mat: pre-industrial control age-dependent exposure to coldwaves computed from the ISIMIP and population data Output of the analysis: - mw_output.mat: Matlab workspace containing all variables produced during the analysis presented in thepaper. Use this file if you wish to look up certain numbers or want to use the study results for further analysis.

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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2021
      License: CC BY
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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    Authors: CSIC - Unidad de Tecnología Marina (UTM);

    Oceanographic data acquired during the TRANSIT_20220212 Cruise (29HE20220212) on board the Research Vessel Hespérides in 2022. Transit voyage without any scientific work.

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    Digital.CSIC
    Dataset . 2022
    Data sources: Digital.CSIC
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      Digital.CSIC
      Dataset . 2022
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    Authors: Campos-Carriedo, Felipe; Iribarren, Diego; Calvo-Rodríguez, Fernando; García-Díaz, Álvaro; +1 Authors

    As the European Union embarks on the energy transition, several challenges need to be faced to ensure that this shift is conducted from a holistic perspective that avoids burden-shifting across sustainability dimensions. One of the main concerns refers to the future availability of materials that clean technologies require. Critical rawmaterial assessment serves to guide the management of such mineral resources in a new paradigm of increasing demand. This work delves into the methodological fundamentals of several product-level criticality indicators in order to discuss their implications within the context of the ecodesign of two hydrogen-related products. Overall, criticality is advised to be assessed making use of several indicators. In the case study of a proton exchange membrane fuel cell stack, the combined interpretation of criticality indicators leads to identifying platinum as the main hotspot, while yttrium and lanthanum account for the most relevant criticality contributions in the casestudy of a solid oxide electrolysis cell stack. The authors would like to thank Gonzalo Puig-Samper and Eleonora Bargiacchi for the insights provided. This work has been carried out within the framework of the projects eGHOST and SH2E. These projects have received funding from the Fuel Cells and Hydrogen 2 Joint Undertaking (now Clean Hydrogen Partnership) under Grant Agreements No. 101007166 and 101007163, respectively. This Joint Undertaking receives support from the European Union’s Horizon 2020 Research and Innovation programme, Hydrogen Europe and Hydrogen Europe Research. The contents of this document are provided “AS IS”. It reflects only the authors’ view and the Joint Undertaking is not responsible for any use that may be made of the information it contains.

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    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: ZENODO
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      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
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    Authors: Rodero, María Del Rosario; Lebrero, Raquel; Serrano, Esteban; Lara, Enrique; +3 Authors

    Excel document that contains the data of the article: ‘Technology validation of photosynthetic biogas upgrading in a semi-industrial scale algal-bacterial photobioreactor’. This dataset shows the values obtained during the experimental period and it complements the corresponding article.

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    ZENODO
    Dataset . 2019
    License: CC BY NC ND
    Data sources: Datacite
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    ZENODO
    Dataset . 2019
    License: CC BY NC ND
    Data sources: ZENODO
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    ZENODO
    Dataset . 2019
    License: CC BY NC ND
    Data sources: Datacite
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      ZENODO
      Dataset . 2019
      License: CC BY NC ND
      Data sources: Datacite
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      ZENODO
      Dataset . 2019
      License: CC BY NC ND
      Data sources: ZENODO
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      ZENODO
      Dataset . 2019
      License: CC BY NC ND
      Data sources: Datacite
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    Authors: Gili Sardà, Josep María; CSIC - Unidad de Tecnología Marina (UTM);

    The ECOREST_AUV campaign will focus on monitoring restored populations in closed areas and adjacent fishing grounds to assess the evolution of restored populations and monitor the evolution of ecosystem services provided, as well as the provision of habitat, breeding areas or a possible spillover effect of closed areas in adjacent areas. Oceanographic data acquired during the ECOREST_AUV Cruise (29GD20230602) on board the Research Vessel García del Cid in 2023.

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    Digital.CSIC
    Dataset . 2023
    Data sources: Digital.CSIC
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      Digital.CSIC
      Dataset . 2023
      Data sources: Digital.CSIC
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    Authors: Plaza, Aitor; Iriarte, Xabier; Castellano-Aldave, Carlos; Carlosena, Alfonso; +3 Authors

    This dataset contains the measurements of the procedure to fully characterise a novel vibration energy harvester (presented in https://doi.org/10.1016/j.apenergy.2023.120715) operating in the ultra-low-frequency range. The details of the experimental setup and fully characterization procedure can be found in: https://doi.org/10.3390/s24123813 The experimental measurements include not only the input (acceleration)–output (energy) response but also the (internal) dynamic behaviour of the system, making use of a synchronised image processing and signal acquisition system. The result of the processed video (angular positions of the masses) and calculation of their two time derivatives by means of the Tikhonov regularization have also been included. Additionally, the calculation of the power generated in the windings has also been included. In "Videos" folder are the recorded videos at 240fps. In "Measurements" folder data form each experiment can be found in different files. First column is time, second and third columns are accelerometer measurements, and the rest of the columns are the different voltages measured at each coil. In "Post-processed data" are the estimated angular positions (2,3,4 columns), velocities (4,5,6 columns) and accelerations (7,8,9 columns) obtained form the post-processed videos. The last column is the estimated power harvested by the device. The name of the file name is in line with the experiment.

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    Mendeley Data
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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    Mendeley Data
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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      Mendeley Data
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
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      Mendeley Data
      Dataset . 2024
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    Authors: Martín, Héctor; CSIC - Unidad de Tecnología Marina (UTM);

    Search and location of the remains of the submarine in the area using side-scan sonar and visual identification with a mini submarine. ARM-REC Cruise (29SG20220502) carried out on the Research Vessel Sarmiento de Gamboa in 2022.

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    Digital.CSIC
    Dataset . 2022
    Data sources: Digital.CSIC
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      Digital.CSIC
      Dataset . 2022
      Data sources: Digital.CSIC
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    Authors: Buessler, Ken; CSIC - Unidad de Tecnología Marina (UTM);

    EXport Processes in the Ocean from Remote Sensing (EXPORTS) is a large-scale NASA-led field campaign that will provide critical information for quantifying the export and fate of upper ocean net primary production (NPP) using satellite observations and state of the art ocean technologies. The goal of EXPORTS is to understand how the organic carbon makes it to the twilight zone and deep ocean interior, and how lon it stays there, which is vital to understanding present and future ocean ecosystems and global climate. Oceanographic data acquired during the EXPORTS Cruise (29SG20210503) on board the Research Vessel Sarmiento de Gamboa in 2021.

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    Digital.CSIC
    Dataset . 2021
    Data sources: Digital.CSIC
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      Digital.CSIC
      Dataset . 2021
      Data sources: Digital.CSIC
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    Authors: Muñoz, Alfonso; CSIC - Unidad de Tecnología Marina (UTM);

    The MARIBNO project is located in the NW zone of Iberia, which constitutes an ideal environment to raise the following main objectives: 1. Study of the cortical structure at the western end of the Cantabrian Mountains and the transition zone between the western and northern margins of Iberia. 2. Study of the tectonic control exerted by the previous structures during the two main alpine stages. 3. Mapping and characterization of cortical domains using a multidisciplinary approach. Definition and application of geophysical and geological criteria applicable to the zonation of cortical domains in other parts of the world with similar contexts. Oceanographic data acquired during the MARIBNO Cruise (29SG20210914) on board the Research Vessel Sarmiento de Gamboa in 2021.

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    Digital.CSIC
    Dataset . 2021
    Data sources: Digital.CSIC
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Digital.CSIC
      Dataset . 2021
      Data sources: Digital.CSIC
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