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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: Negri, Valentina; Vázquez, Daniel; Sales-Pardo, Marta; Guimerà, Roger; +1 Authors

    Dataset of process simulations results of the natural gas sweetening and flue gas treatment (first and second sheet, respectively as indicated by the sheet name in the .xlsx file). The dataset refers to the publication Bayesian Symbolic Learning to Build Analytical Correlations from Rigorous Process Simulations: Application to CO2 Capture Technologies by V. Negri, Vàzquey D., Sales-Pardo, Marta, Guimerà, R. and Guillén-Gosàlbez, G. The training and testing dataset are used to generate the figures in the main manuscript and supplementary information.

    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
    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 . 2022
    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 . 2022
    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 . 2022
    License: CC BY
    Data sources: Datacite
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    influenceAverage
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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/ ZENODOarrow_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/
      ZENODO
      Dataset . 2022
      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 . 2022
      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 . 2022
      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/
    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.

    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
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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/
  • 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: 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.

    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
    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
    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
    0
    citations0
    popularityAverage
    influenceAverage
    impulseAverage
    BIP!Powered by BIP!
    visibility317
    visibilityviews317
    downloaddownloads197
    Powered by Usage counts
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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/ ZENODOarrow_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/
      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
  • image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao

    Digital Annex for the following thesis: Vila-Viçosa, C. (2023). Natural History, Biogeography and Evolution of the Iberian white oak syngameon (Quercus L. Sect. Quercus). Ph.D. Thesis, Faculdade de Ciências da Universidade do Porto, Portugal Abstract: The genus Quercus L. is one of the most diverse and important group of woody plants, particularly when considering that they are the trees that rule the Northern Hemisphere forests. Oaks have an intricate Biogeography that criss-crosses diverse climatic and edaphic gradients, encompassing a huge ambiguity in terms of species delimitation. Frequently, the taxonomic proposals brought by traditional Linnaean Botany are either insufficient or rather inflate the number of species and nomenclatural assignments, which are further diluted into inconsistent taxonomic ranks, varying from species to subspecies and varieties. The supremacy given to morphological characters that are inherently fragile and plastic, spread across the distribution areas of distinct lineages, may carry ambiguity on the identification and proper species delimitation. From the oaks that are distributed across the Western Palearctic region, the ones that are deciduous or brevi-deciduous present higher levels of ambiguity in terms of species number and their delimitation. This ambiguity is particularly strong in the circummediterranean region and in the transitional areas between the two major biogeographic Regions of the western Palearctic region, the Euro-Siberian and Mediterranean. This degree of uncertainty, which increases towards the Southern European Peninsulas, is amplified by the ease that the different species of oaks tend to hybridize among them. The present work provides a holistic framework that covers multiple areas, from the taxonomic and evolutive study of this genus, to biogeography and molecular characterization. Its major objective was to resolve the species delimitation of the Iberian deciduous and marcescent oaks and putative introgression among them, enhancing the available knowledge about species diversity, which can foster suitable species and forest conservation. A specific objective was to cross-reference the natural history revision and the different taxonomic treatments brought by distinct authors, with personal observations. These data were then incorporated into ecological modelling and molecular characterization, which in the end fed a newly updated taxonomic proposal. In Section A we obtained results from extensive field, herbaria, and literature review, updating the nomenclature of the Portuguese and western Mediterranean oaks. Section B was supported by Section A’s in-depth review and enabled finer species distribution models, nurturing both hindcast (since ca. 20 Kyr) and forecast (2070-2100) exercises of the range dynamics of Mediterranean oaks species. The study of past and future range shifts solved important pending biogeographic questions, especially related to past range-shifts. Such past-range shifts improved our knowledge on species responses to climate dynamics and allowed a better anticipation of future responses of range shifts driven by climate change. Section C encompassed the molecular characterization of Iberian white oak species and their hybrids, whose delimitation is often faltering when one intends to infer about species rank, or hypothesize about the participation of parent taxon in natural hybrid swarms. This work allowed us to solve the phylogenetic backbone of western Palearctic white oaks, suggesting a significant segregation of the Iberian pedunculate oaks and unveiling two subsections inside Section Quercus. These subsections are biogeographically well-segregated and present diverse levels of introgression among species. Results demonstrated the efficiency of RADSeq for rebuilding the reticulate phylogeny of the Eurasian white oaks, showcasing the significance of the Iberian Peninsula as a major hotspot for oak diversity. We implemented a circular approach to these methods, which retro-fed themselves in terms of insight generation, enabling a powerful strategy to solve the evolutionary history of this difficult groups of plants. We estimate that the reticulate historical biogeography of the western Palearctic white oaks deserves further scrutiny by adding vicariant oak populations from northern Africa, the Near East and southern European Peninsulas. Methods should again follow this similar additive and sequential process of adjoining deep Natural History examination, with extensive fieldwork in type populations and genome-wide molecular surveys, in order to solve this group of plants. With the present work, we were able to significantly improve on the depiction of the basic unit of Biodiversity (the Species), in the complex Quercus genus. We provided tools to enable further efforts for the conservation of the Mediterranean oak forests, which overwhelm one of the most important (and one of the most threatened) Biomes for plant conservation at the global scale.

    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao ZENODOarrow_drop_down
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    ZENODO
    Dataset . 2023
    Data sources: Datacite
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    ZENODO
    Dataset . 2023
    Data sources: Datacite
    ZENODO
    Dataset . 2023
    Data sources: ZENODO
    0
    citations0
    popularityAverage
    influenceAverage
    impulseAverage
    BIP!Powered by BIP!
    visibility53
    visibilityviews53
    downloaddownloads27
    Powered by Usage counts
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao ZENODOarrow_drop_down
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      ZENODO
      Dataset . 2023
      Data sources: Datacite
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      ZENODO
      Dataset . 2023
      Data sources: Datacite
      ZENODO
      Dataset . 2023
      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/
    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
    0
    citations0
    popularityAverage
    influenceAverage
    impulseAverage
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      Digital.CSIC
      Dataset . 2022
      Data sources: Digital.CSIC
  • 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.

    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 . 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
    0
    citations0
    popularityAverage
    influenceAverage
    impulseAverage
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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/
      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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    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
    0
    citations0
    popularityAverage
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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
      License: CC BY
      Data sources: Datacite
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    Authors: Cruz, Luis; Abreu, Rui;

    High energy consumption is a challenging issue that an ever increasing number of mobile applications face today.However, energy consumption is being tested in an ad hoc way, despite being an important non-functional requirement of an application.Such limitation becomes particularly disconcerting during software testing: on the one hand, developers do not really know how to measure energy; on the other hand, there is no knowledge as to what is the energy overhead imposed by the testing framework.In this paper, as we evaluate eight popular mobile UI automation frameworks, we have discovered that there are automation frameworks that increase energy consumption up to roughly 2200%.While limited in the interactions one can do, Espresso is the most energy efficient framework.However, depending on the needs of the tester, Appium, Monkeyrunner, or UIAutomator are good alternatives.In practice, results show that deciding which is the most suitable framework is vital. We provide a decision tree to help developers make an educated decision on which framework suits best their testing needs.

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    IEEE DataPort
    Dataset . 2018
    License: CC BY
    Data sources: Datacite
    0
    citations0
    popularityAverage
    influenceAverage
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      IEEE DataPort
      Dataset . 2018
      License: CC BY
      Data sources: Datacite
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    Authors: Negri, Valentina; Vázquez, Daniel; Sales-Pardo, Marta; Guimerà, Roger; +1 Authors

    Dataset of process simulations results of the natural gas sweetening and flue gas treatment (first and second sheet, respectively as indicated by the sheet name in the .xlsx file). The dataset refers to the publication Bayesian Symbolic Learning to Build Analytical Correlations from Rigorous Process Simulations: Application to CO2 Capture Technologies by V. Negri, Vàzquey D., Sales-Pardo, Marta, Guimerà, R. and Guillén-Gosàlbez, G. The training and testing dataset are used to generate the figures in the main manuscript and supplementary information.

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    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: ZENODO
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      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
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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
      Data sources: ZENODO
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
  • image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao

    Digital Annex for the following thesis: Vila-Viçosa, C. (2023). Natural History, Biogeography and Evolution of the Iberian white oak syngameon (Quercus L. Sect. Quercus). Ph.D. Thesis, Faculdade de Ciências da Universidade do Porto, Portugal Abstract: The genus Quercus L. is one of the most diverse and important group of woody plants, particularly when considering that they are the trees that rule the Northern Hemisphere forests. Oaks have an intricate Biogeography that criss-crosses diverse climatic and edaphic gradients, encompassing a huge ambiguity in terms of species delimitation. Frequently, the taxonomic proposals brought by traditional Linnaean Botany are either insufficient or rather inflate the number of species and nomenclatural assignments, which are further diluted into inconsistent taxonomic ranks, varying from species to subspecies and varieties. The supremacy given to morphological characters that are inherently fragile and plastic, spread across the distribution areas of distinct lineages, may carry ambiguity on the identification and proper species delimitation. From the oaks that are distributed across the Western Palearctic region, the ones that are deciduous or brevi-deciduous present higher levels of ambiguity in terms of species number and their delimitation. This ambiguity is particularly strong in the circummediterranean region and in the transitional areas between the two major biogeographic Regions of the western Palearctic region, the Euro-Siberian and Mediterranean. This degree of uncertainty, which increases towards the Southern European Peninsulas, is amplified by the ease that the different species of oaks tend to hybridize among them. The present work provides a holistic framework that covers multiple areas, from the taxonomic and evolutive study of this genus, to biogeography and molecular characterization. Its major objective was to resolve the species delimitation of the Iberian deciduous and marcescent oaks and putative introgression among them, enhancing the available knowledge about species diversity, which can foster suitable species and forest conservation. A specific objective was to cross-reference the natural history revision and the different taxonomic treatments brought by distinct authors, with personal observations. These data were then incorporated into ecological modelling and molecular characterization, which in the end fed a newly updated taxonomic proposal. In Section A we obtained results from extensive field, herbaria, and literature review, updating the nomenclature of the Portuguese and western Mediterranean oaks. Section B was supported by Section A’s in-depth review and enabled finer species distribution models, nurturing both hindcast (since ca. 20 Kyr) and forecast (2070-2100) exercises of the range dynamics of Mediterranean oaks species. The study of past and future range shifts solved important pending biogeographic questions, especially related to past range-shifts. Such past-range shifts improved our knowledge on species responses to climate dynamics and allowed a better anticipation of future responses of range shifts driven by climate change. Section C encompassed the molecular characterization of Iberian white oak species and their hybrids, whose delimitation is often faltering when one intends to infer about species rank, or hypothesize about the participation of parent taxon in natural hybrid swarms. This work allowed us to solve the phylogenetic backbone of western Palearctic white oaks, suggesting a significant segregation of the Iberian pedunculate oaks and unveiling two subsections inside Section Quercus. These subsections are biogeographically well-segregated and present diverse levels of introgression among species. Results demonstrated the efficiency of RADSeq for rebuilding the reticulate phylogeny of the Eurasian white oaks, showcasing the significance of the Iberian Peninsula as a major hotspot for oak diversity. We implemented a circular approach to these methods, which retro-fed themselves in terms of insight generation, enabling a powerful strategy to solve the evolutionary history of this difficult groups of plants. We estimate that the reticulate historical biogeography of the western Palearctic white oaks deserves further scrutiny by adding vicariant oak populations from northern Africa, the Near East and southern European Peninsulas. Methods should again follow this similar additive and sequential process of adjoining deep Natural History examination, with extensive fieldwork in type populations and genome-wide molecular surveys, in order to solve this group of plants. With the present work, we were able to significantly improve on the depiction of the basic unit of Biodiversity (the Species), in the complex Quercus genus. We provided tools to enable further efforts for the conservation of the Mediterranean oak forests, which overwhelm one of the most important (and one of the most threatened) Biomes for plant conservation at the global scale.

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    ZENODO
    Dataset . 2023
    Data sources: Datacite
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    ZENODO
    Dataset . 2023
    Data sources: Datacite
    ZENODO
    Dataset . 2023
    Data sources: ZENODO
    0
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      ZENODO
      Dataset . 2023
      Data sources: Datacite
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      ZENODO
      Dataset . 2023
      Data sources: Datacite
      ZENODO
      Dataset . 2023
      Data sources: ZENODO
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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
    0
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      Digital.CSIC
      Dataset . 2022
      Data sources: Digital.CSIC
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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
    0
    citations0
    popularityAverage
    influenceAverage
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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
      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/
    Authors: Cruz, Luis; Abreu, Rui;

    High energy consumption is a challenging issue that an ever increasing number of mobile applications face today.However, energy consumption is being tested in an ad hoc way, despite being an important non-functional requirement of an application.Such limitation becomes particularly disconcerting during software testing: on the one hand, developers do not really know how to measure energy; on the other hand, there is no knowledge as to what is the energy overhead imposed by the testing framework.In this paper, as we evaluate eight popular mobile UI automation frameworks, we have discovered that there are automation frameworks that increase energy consumption up to roughly 2200%.While limited in the interactions one can do, Espresso is the most energy efficient framework.However, depending on the needs of the tester, Appium, Monkeyrunner, or UIAutomator are good alternatives.In practice, results show that deciding which is the most suitable framework is vital. We provide a decision tree to help developers make an educated decision on which framework suits best their testing needs.

    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/ IEEE DataPortarrow_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/
    IEEE DataPort
    Dataset . 2018
    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/ IEEE DataPortarrow_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/
      IEEE DataPort
      Dataset . 2018
      License: CC BY
      Data sources: Datacite