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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: Vuorinen, Tommi A.T.; Veikkolainen, Toni; Oinonen, Kati; Hällsten, Jennifer; +8 Authors

    In summer 2018 the energy company St1 carried out its first stimulation of deep geothermal wells in Otaniemi, Espoo, in the Helsinki metropolitan area, southern Finland. The Institute of Seismology of University of Helsinki (ISUH) monitored the induced seismicity during the stimulation, and also months before and after it. This dataset consists of seismic waveforms of 254 induced earthquakes that occurred between 5 June 2018 to 8 August 2018, with local magnitudes between 0.5 and 1.8. Waveform, location and timing data have been produced at ISUH using seismic stations of the Finnish National Seismic Network (doi: 10.14470/UR044600), the temporary HEL broadband network, the temporary borehole network of St1 (doi: 10.1785/0220190253), and a pool of lightweight mobile seismic instruments operated by ISUH (GIPP data cubes, doi: 10.5880/GIPP.201802.1). The deployment is described in Hillers et al., 2020, The 2018 Geothermal Reservoir Stimulation in Espoo/Helsinki, Southern Finland: Seismic Network Anatomy and Data Features, doi:10.1785/0220190253. Event data, event metadata, and station metadata are provided in distinct directories. For event data, each event is assigned a subdirectory. Data formats follow generally accepted seismological standards.

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    Fairdata IDA Research Data Storage Service
    Dataset . 2023
    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/ Fairdata IDA Researc...arrow_drop_down
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      Fairdata IDA Research Data Storage Service
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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    Absorption Koeffizient der farbigen detritalen Substanz bei 443nm (adg in m^-1 bei 4 km Auflösung): Der Absorptionskoeffizient adg stellt den Anteil des einfallenden Lichts dar, das sowohl von detritalen Partikeln als auch von farbiger gelöster organischer Substanz (CDOM) absorbiert wird. Gelöste organische Substanz ist ein wichtiger Bestandteil des ozeanischen Kohlenstoffkreislaufs. Es wird auch als Proxy verwendet, um die Auswirkungen von Terrigenous Inputs in Küstengewässern zu bewerten. Συντελεστής απορρόφησης της χρωματισμένης αποτριχωτικής ύλης στα 443nm (adg σε m^-1 σε ανάλυση 4 km): Ο συντελεστής απορρόφησης adg αντιπροσωπεύει το κλάσμα του προσπίπτοντος φωτός που απορροφάται τόσο από τα διακριτικά σωματίδια όσο και από τη χρωματισμένη διαλυμένη οργανική ύλη (CDOM). Η διαλυμένη οργανική ύλη είναι ένα σημαντικό συστατικό του ωκεάνιου κύκλου του άνθρακα. Χρησιμοποιείται επίσης ως υποκατάστατο για την εκτίμηση των επιπτώσεων των εδαφικών εισροών στα παράκτια ύδατα. Współczynnik absorpcji barwnej substancji detrytalnej przy 443 nm (adg w m^-1 przy rozdzielczości 4 km): Współczynnik absorpcji adg reprezentuje ułamek padającego światła pochłanianego zarówno przez cząstki detrytalne, jak i przez kolorowe rozpuszczone substancje organiczne (CDOM). Rozpuszczone materia organiczna jest ważnym składnikiem oceanicznego cyklu węgla. Jest on również wykorzystywany jako wskaźnik zastępczy do oceny wpływu czynników atmosferycznych w wodach przybrzeżnych. Coeficientul de absorbție al materiei detritale colorate la 443nm (adg în m^-1 la o rezoluție de 4 km): Coeficientul de absorbție adg reprezintă fracțiunea de lumină incidentă absorbită atât de particulele detritale, cât și de materia organică colorată dizolvată (CDOM). Materia organică dizolvată este o componentă importantă a ciclului carbonului oceanic. Acesta este, de asemenea, utilizat ca indicator pentru a evalua impactul factorilor de producție terrigeni în apele costiere. Assorbiment Koeffiċjent tal-materja detritali kkulurita f’443nm (adg f’m^-1 b’riżoluzzjoni ta’ 4 km): Il-koeffiċjent ta’ assorbiment adg jirrappreżenta l-frazzjoni ta’ dawl inċidentali assorbit kemm minn partiċelli detritali kif ukoll minn materja organika maħlula kkulurita (CDOM). Il-materja organika maħlula hija komponent importanti taċ-ċiklu tal-karbonju oċeaniku. Tintuża wkoll bħala indikatur biex jiġi vvalutat l-impatt tal-inputs terriġenużi fl-ilmijiet kostali. Coefficiente di assorbimento della materia detritale colorata a 443nm (adg in m^-1 a risoluzione di 4 km): Il coefficiente di assorbimento adg rappresenta la frazione di luce incidente assorbita sia dalle particelle detritali che dalla materia organica disciolta colorata (CDOM). La materia organica disciolta è una componente importante del ciclo del carbonio oceanico. Viene anche utilizzato come proxy per valutare l'impatto degli input terrigeni nelle acque costiere. Coeficiente de absorción de materia detrital de color a 443 nm (adg en m^-1 a 4 km de resolución): El coeficiente de absorción adg representa la fracción de luz incidente absorbida tanto por partículas detritales como por materia orgánica disuelta coloreada (CDOM). La materia orgánica disuelta es un componente importante del ciclo del carbono oceánico. También se utiliza como representante para evaluar el impacto de los insumos territoriales en las aguas costeras. Коефициент на абсорбция на цветна детритална материя при 443nm (adg в m^-1 при разделителна способност 4 km): Коефициентът на поглъщане adg представлява частта от падащата светлина, абсорбирана както от детритните частици, така и от оцветената разтворена органична материя (CDOM). Разтворената органична материя е важен компонент на океанския въглероден цикъл. Той се използва и като заместител за оценка на въздействието на теригенните суровини в крайбрежните води. Coefficient d’absorption de la matière détritique colorée à 443nm (adg en m^-1 à 4 km de résolution): Le coefficient d’absorption adg représente la fraction de lumière incidente absorbée à la fois par les particules détritales et par la matière organique dissoute colorée (CDOM). La matière organique dissoute est une composante importante du cycle du carbone océanique. Il sert également de proxy pour évaluer l’impact des apports terriens dans les eaux côtières. Absorptiecoëfficiënt van gekleurde detritale materie bij 443nm (adg in m^-1 bij 4 km resolutie): De absorptiecoëfficiënt adg vertegenwoordigt de fractie van invallend licht geabsorbeerd door zowel detritale deeltjes als gekleurd opgelost organisch materiaal (CDOM). Opgelost organisch materiaal is een belangrijk onderdeel van de oceanische koolstofcyclus. Het wordt ook gebruikt als volmacht om de impact van terrigeneuze inputs in kustwateren te beoordelen.

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    Authors: orcid bw Oziel, Laurent;
    Oziel, Laurent
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Oziel, Laurent in OpenAIRE

    This repository contains the post-processed model outputs underlying the main figures in the paper "Climate change and terrigenous inputs decrease the efficiency of the future Arctic Ocean’s biological carbon pump" by Oziel et al. in Nature Climate Change. The repository also contains the jupyter notebooks (python) scripts used to produce the figures, the custom model code as well as the mesh informations to reproduce the model run.

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    Authors: orcid bw Paprotny, Dominik;
    Paprotny, Dominik
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Paprotny, Dominik in OpenAIRE

    The HANZE dataset covers riverine, pluvial, coastal and compound floods that have occurred in 42 European countries. It contains: 2521 historical floods with impact data (1870-2020); 237 further historical floods with significant impacts, but without precise impact data (1950-2020) Nearly 15,000 modelled floods with a potential to cause significant impacts, classified by actual historical occurrence or non-occurrence impacts (1950-2020). Historical floods and the classification of modelled floods was completed by extensive data-collection from more than 900 sources ranging from news reports through government databases to scientific papers. Impact data collected or modelled include area inundated, fatalities, persons affected or economic loss. Economic losses were inflation- and exchange-rate adjusted to 2020 value of the euro. The historical catalogue (lsit A) also includes losses in the original currencies and price levels. The spatial footprint of affected areas is consistently recorded using more than 1400 subnational units corresponding, with minor exceptions, to the European Union’s Nomenclature of Territorial Units for Statistics (NUTS), level 3. Apart from the possibility to download the data, the database can be viewed, filtered and visualized online: https://naturalhazards.eu. The dataset contains the following files (CSV comma-delimited, UTF8, and ESRI shapefiles in zipped folders): HANZE_historical_floods_catalogue_listA.csv - historical floods with impact data (1870-2020) HANZE_historical_floods_catalogue_listB.csv - historical floods without impact data (1950-2020) HANZE_potential_flood_catalogue_all.csv - modelled potential floods (1950-2020) HANZE_list_of_references.csv - List of all references used in the catalogues HANZE_model_completness_analysis.csv - Comparison between modelled and reported footprints of historical floods Regions_v2010_simplified.zip - Map of subnational regions (v2010) Regions_v2021_simplified.zip - Map of subnational regions (regions v2021) v1.1: errors in two records in "HANZE_historical_floods_catalogue_listB.csv" (wrong country code in event ID 8227 and wrong start date in event ID 8237) were corrected. This work was supported by the German Research Foundation (DFG) through project "Decomposition of flood losses by environmental and economic drivers" (FloodDrivers), project no. 449175973 

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    ZENODO
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      Dataset . 2024
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    Authors: orcid bw Sahare, Sanjay;
    Sahare, Sanjay
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Sahare, Sanjay in OpenAIRE
    ZIolek, Marcin;

    For more detailed information, one can visit 10.1039/D4TC00466C Sanjay Sahare thanks project No. 2021/43/P/ST3/02599 co-funded by the National Science Centre and the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska–Curie grant agreement no. 945339.

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    ZENODO
    Dataset . 2024
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    ZENODO
    Dataset . 2024
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      ZENODO
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      ZENODO
      Dataset . 2024
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    Authors: Baran Yoğurtçuoğlu (10019369); Tuba Bucak (10019372); Fitnat Güler Ekmekçi (10019375); Cüneyt Kaya (9280550); +1 Authors

    Rainbow trout (Oncorhynchus mykiss) has become by far the most frequently farmed freshwater fish species in Turkey, whereas very little is known about its establishment and invasiveness potential. We explored this potential through a combination of Maxent habitat suitability model and the Aquatic Species Invasiveness Screening Kit (AS-ISK) on the river basin scale by generating an overall risk score (ORS). The outcome of this approach was also incorporated with the spatial analysis of native salmonid species by generating a relative vulnerability score (RVS) to prioritize susceptibility of native species (or populations) and to propose risk hotspots by identifying their potential geographic overlap and interaction with O. mykiss. Results suggest that the northern basins (Eastern Black Sea, Western Black Sea and Marmara basins) are the most suitable basins for O. mykiss. According to the Basic Risk Assessment (BRA) threshold scores, O. mykiss is classified as “high risk” for 3 (12.0%) of the 25 river basins screened (Western Black Sea, Eastern Black Sea and Maritza-Ergene), and as “medium risk” for the remaining basins. The climate change assessment (CCA) scores negatively contributed the overall invasiveness potential of O. mykiss in 22 (88.0%) of the river basins and resulted in zero contribution for the remaining three, namely Aras-Kura, Çoruh river and Eastern Black Sea. The ORS score of river basins was lowest for Orontes and highest for Western Black Sea, whereas it was lowest for Konya-closed basin and highest for Eastern Black Sea, when CCA was associated. The micro-basins occupied by Salmo rizeensis had the highest mean habitat suitability with O. mykiss. Among the all species, S. abanticus had the highest RVS, followed by S. munzuricus and S. euphrataeus. The overall outcome of the present study also suggests that the establishment and invasiveness potential of O. mykiss may decrease under future (climate warmer) in Turkey, except for the northeast region. This study can provide environmental managers ...

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    Smithsonian figshare
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      Smithsonian figshare
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    Log and boot files of game 211

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    ZENODO
    Dataset . 2021
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    ZENODO
    Dataset . 2021
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    ZENODO
    Dataset . 2021
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      ZENODO
      Dataset . 2021
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      ZENODO
      Dataset . 2021
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      ZENODO
      Dataset . 2021
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    Authors: Adelle I. Molina (11462563); Robert M. Cerrato (9292635); Janet A. Nye (9292638);

    Parameter estimates from the best AFT model using all available data, including crabs from Bauer and Miller [ 52 ].

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    Smithsonian figshare
    Dataset . 2021
    License: CC BY
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      Smithsonian figshare
      Dataset . 2021
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    Authors: orcid bw de Vries, Joost;
    de Vries, Joost
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    de Vries, Joost in OpenAIRE
    orcid bw Poulton, Alex J.;
    Poulton, Alex J.
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Poulton, Alex J. in OpenAIRE
    orcid bw Young, Jeremy R.;
    Young, Jeremy R.
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Young, Jeremy R. in OpenAIRE
    orcid bw Monteiro, Fanny M.;
    Monteiro, Fanny M.
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Monteiro, Fanny M. in OpenAIRE
    +5 Authors

    CASCADE is a global dataset for 139 extant coccolithophore taxonomic units. CASCADE includes a trait database (size and cellular organic and inorganic carbon contents) and taxonomic-specific global spatiotemporal distributions (Lat/Lon/Depth/Month/Year) of coccolithophore abundance and organic and inorganic carbon stocks. CASCADE covers all ocean basins over the upper 275 meters, spans the years 1964-2019 and includes 33,119 taxonomic-specific abundance observations. Within CASCADE, we characterise the underlying uncertainties due to measurement errors by propagating error estimates between the different studies. Full details of the data set are provided in the associated Scientific Data manuscript. The repository contains five main folders: 1) "Classification", which contains YAML files with synonyms, family-level classifications, and life cycle phase associations and definitions; 2) "Concatenated literature", which contains the merged datasets of size, PIC and POC and which were corrected for taxonomic unit synonyms; 3) "Resampled cellular datasets", which contains the resampled datasets of size, PIC and POC in long format as well as a summary table; 4) "Gridded data sets", which contains gridded datasets of abundance, PIC and POC; 5) "Species lists", which contains spreadsheets of the "common" (>20 obs) and "rare" (<20 obs) species and their number of observations. The CASCADE data set can be easily reproduced using the scripts and data provided in the associated github repository: https://github.com/nanophyto/CASCADE/ (zenodo.12797197) Correspondence to: Joost de Vries, joost.devries@bristol.ac.uk v.0.1.2 has some fixes: 1. The wrongly specified S. neapolitana was removed from synonyms.yml (this species is now S. nana)2. Longitudes were corrected for Guerreiro et al., 20233. A double entry for Dimizia et al., 2015 was fixed4. Units in Sal et al., 2013 were correct to cells/L (previously cells/ml)5. Data from Sal et al., 2013 was re-done, as some species were missing6. Duplicate entries from Baumann et al., 2000 were dropped

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    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2024
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    ZENODO
    Dataset . 2024
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    ZENODO
    Dataset . 2024
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    ZENODO
    Dataset . 2024
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      Dataset . 2024
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      ZENODO
      Dataset . 2024
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      ZENODO
      Dataset . 2024
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      Dataset . 2024
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    Authors: Isabel J. Bejarano-Alva (10435808); Gisele A. M. Hirata (10435811); Klicia A. Sampaio (10435814); Eduardo A. C. Batista (10435817); +1 Authors

    Biodiesel, known as a mixture of fatty acid ethyl/methyl esters, is seen as an alternative, ecofriendly, biodegradable and renewable non-fossil fuel. The use of heterogeneous catalysts for biodiesel synthesis can solve several problems associated with the homogeneous alkaline catalyzed-transesterification. Therefore, this work reports the evaluation of the commercial resin Amberlyst A26OH, a strong anion exchange resin, as a heterogeneous catalyst for the batch transesterification of refined palm olein with ethanol. It was studied the effects of the main operational parameters, considering the molar ratio of the reaction mixture (MRRM), namely the molar ratio of ethanol to olein taking into account only the ethanol added to the reaction system, and the total molar ratio (TMR), in this case considering also the amount of ethanol carried by the resin after its pretreatment. It was determined an optimal range of operational conditions by response surface methodology, guaranteeing conversion to ethyl esters higher than 96% with a catalyst amount corresponding to a range from 10.4 to 11.4% of the oil quantity, a temperature within the range of 55 to 60 ºC and a MRRM within the range from 3.5:1 to 6.0:1.

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    figshare
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    figshare
    Dataset . 2021
    License: CC BY
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    Smithsonian figshare
    Dataset . 2020
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      Dataset . 2021
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      Dataset . 2021
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      Dataset . 2020
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