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  • NEANIAS Atmospheric Research Community
  • 2019-2023
  • Research data
  • Dataset
  • European Commission
  • IT
  • ZENODO

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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: Rovere, Alessio; Rubio Sandoval, Karla Zurisadai; Ryan, Deirdre D.; Richiano, Sebastian; +5 Authors

    This repository contains the supplementary information and raw data annexed to the manuscript "Quaternary and Pliocene sea-level changes at Camarones, central Patagonia, Argentina", authored by Karla Rubio-Sandoval et al. and submitted for consideration in the journal Quaternary Science Reviews. The folder contains the following items. 1. Raw_data.xlsxThis is an excel file that includes all survey and analytical data in several sheets, briefly described hereafter. - GNSS data. Data surveyed with differential GNSS in the field.- Sea level index points. Datapoints used as sea-level index points, and associated calculations of paleo Relative Sea Level.- AAR Summary. Table summarising the main results of the AAR analyses.- AAR complete sheet. The complete set of analytical data done for the Amino Acid Racemization dating.- Radiocarbon data. The analytical results of radiocarbon dating.- Literature ages. A compilation of the Electron Spin Resonance and U-series ages published for the Camarones site.- Transects. Topographical transects extracted from the TanDEM-X Digital Elevation model and referred to the GEOIDEAR 16 geoid.- Distance plot. Data for plotting Relative Sea Level vs distance along the coast of the sea-level index points described in the manuscript. 2. Holocene (folder)This folder contains two excel files ("Area_Camarones_Accepted.xlsx" and "Area_Camarones_Rejected.xlsx") that include the Holocene data described in the paper compiled following the standard HOLSEA template. 3. Runup_modellingThis folder contains three folders, each with a Jupyter notebook (.ipynb) and datasets to perform the runup calculations described in the manuscript.

    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 . 2023
    License: CC BY
    Data sources: ZENODO
    ZENODO
    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/ ZENODOarrow_drop_down
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: ZENODO
      ZENODO
      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/
    Authors: Canepa, Elisabetta;

    We need affect-based stimuli specifically conceived to investigate architectural spaces. The RESONANCES project crafted ATLAS, a dATabase of visuaL Atmospheric Stimuli. It collects a series of spatial patterns born from a systematic selection of generators of atmosphere. Generators of atmosphere are architectural features designed to afford atmospheric effects (such as lights, colors, materials, and proportions). ATLAS is an open-access tool that supports researchers interested in studying emotional reactions to architectural features by providing reliable, standardized, and reproducible stimuli. In this dataset, ATLAS stimuli are presented as videos. This database was developed within the Resonances project — Architectural Atmospheres: The Emotional Impact of Ambiances Measured through Conscious, Bodily, and Neural Responses. This project received funding from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement no. 101025132. The content of this work reflects only the authors' view. The European Research Executive Agency 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 . 2023
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: ZENODO; Sygma
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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
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      ZENODO
      Dataset . 2023
      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 . 2023
      License: CC BY
      Data sources: ZENODO; Sygma
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    Authors: Canepa, Elisabetta;

    We need affect-based stimuli specifically conceived to investigate architectural spaces. The RESONANCES project crafted ATLAS, a dATabase of visuaL Atmospheric Stimuli. It collects a series of spatial patterns born from a systematic selection of generators of atmosphere. Generators of atmosphere are architectural features designed to afford atmospheric effects (such as lights, colors, materials, and proportions). ATLAS is an open-access tool that supports researchers interested in studying emotional reactions to architectural features by providing reliable, standardized, and reproducible stimuli. In this dataset, ATLAS stimuli are presented as 2D images. This database was developed within the Resonances project — Architectural Atmospheres: The Emotional Impact of Ambiances Measured through Conscious, Bodily, and Neural Responses. This project received funding from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement no. 101025132. The content of this work reflects only the authors' view. The European Research Executive Agency 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 . 2023
    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 . 2023
    License: CC BY
    Data sources: ZENODO; Sygma
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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 . 2023
      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 . 2023
      License: CC BY
      Data sources: ZENODO; Sygma
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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: Canepa, Elisabetta; Condia, Bob; Beighle, Kory; Djebbara, Zakaria; +1 Authors

    This dataset is an output of the ‘Designing Atmospheres: Theory and Science’ Symposium (ATS), an Interfaces event of the Academy of Neuroscience for Architecture (ANFA), sponsored by the EU’s Horizon 2020 MSCA Program — RESONANCES Project, the Perkins Eastman Studio, and the KSTATE APDesign. The symposium was hosted in the College of Architecture, Planning and Design (APDesign), Kansas State University, Manhattan (Kansas, USA), on March 28, 2023. Speakers: Kory Beighle (Kansas State University), Elisabetta Canepa (University of Genoa | Kansas State University), Bob Condia (Kansas State University), Zakaria Djebbara (Aalborg University | TU Berlin), and Harry Francis Mallgrave (Illinois Institute of Technology). Recent advances in science confirm many of the architects’ deep-rooted intuitions, improving knowledge about the perception of space and the meaning of architectural and urban design. The symposium ‘Designing Atmospheres: Theory and Science‘ presented to an audience of students, educators, architects, and scientists a conversation about the experience of design and building, specifically speaking to the significance of atmospheres, affordances, and emotions. This dataset is made of seven files: no. 1 dataset summary (.pdf) no. 1 symposium poster (.pdf) no. 5 videos containing speakers’ presentations (.mp4) Recorded videos of each lecture are also available on the RESONANCES project website (www.resonances-project.com/harvest) and its YouTube channel (@resonancesproject5777). 'Designing Atmospheres: Theory and Science' Symposium is an Interfaces event of the Academy of Neuroscience for Architecture (ANFA), sponsored by the European Union's Horizon 2020 MSCA Program — RESONANCES Project, the Perkins Eastman Studio, and the KSTATE APDesign. The RESONANCES project received funding from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement no. 101025132. The content of the produced and published material reflects only the authors' views. The Research Executive Agency and the European Commission are 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 . 2023
    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 . 2023
    License: CC BY
    Data sources: ZENODO; Sygma
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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 . 2023
      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 . 2023
      License: CC BY
      Data sources: ZENODO; Sygma
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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: Maffezzoli, Niccolò; Cook, Eliza; van der Bilt, Willem G. M.; Støren, Eivind N.; +20 Authors

    This dataset refers to the ICELEARNING project - Detection of ice core particles via deep neural networks, by Maffezzoli N. et al., The Cryosphere, 10.5194/tc-17-539-2023, 2023. The main folder contains all TRAINING data. The TEST data are contained in the folder /test. Please refer to the icelearning GitHub repository for instructions. {"references": ["Maffezzoli, Niccol\u00f2, et al. \"Detection of ice core particles via deep neural networks.\" The Cryosphere 17.2 (2023): 539-565."]} For questions, contact niccolo.maffezzoli@unive.it

    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 . 2023
    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 . 2023
    License: CC BY
    Data sources: ZENODO
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: ZENODO
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    Authors: Canepa, Elisabetta;

    This dataset is an output of the ‘Generators of Architectural Atmosphere’ Symposium, an Interfaces event of the Academy of Neuroscience for Architecture (ANFA), sponsored by the EU’s Horizon 2020 MSCA Program — RESONANCES Project, the Perkins Eastman Studio, and the 2020 Regnier Chair. The symposium was hosted in the College of Architecture, Planning and Design (APDesign), Kansas State University, Manhattan (Kansas, USA), on April 12, 2022. Speakers: Bob Condia (Kansas State University), Elisabetta Canepa (University of Genoa and Kansas State University), Kutay Güler (Kansas State University), and Tiziana Proietti (Oklahoma University). Recent advances in science confirm many of the architect’s expert intuitions opening new doors to the perception of space and the meaning of architectural and urban design. The symposium ‘Generators of Architectural Atmosphere’ presented to an audience of students, educators, architects, and scientists a conversation about human perception of design and building, specifically speaking to the significance of atmosphere, mood, architectural proportion, and virtual reality. This dataset is made of six files: no. 1 dataset summary (.pdf) no. 1 symposium poster (.pdf) no. 4 videos containing speakers’ presentations (.mp4). Recorded videos of each lecture are also available on the RESONANCES project website (www.resonances-project.com/harvest) and its YouTube channel (UCk32skDiT4Bz1AHnltT51Yg). 'Generators of Architectural Atmosphere' Symposium is an Interfaces event of the Academy of Neuroscience for Architecture (ANFA), sponsored by the European Union's Horizon 2020 MSCA Program — RESONANCES Project, the Perkins Eastman Studio, and the 2020 Regnier Chair. The RESONANCES project has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement no. 101025132. The content of the produced and published material reflects only the authors' views. The Research Executive Agency and the European Commission are 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 . 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; Sygma
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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; Sygma
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    Authors: Bohleber, Pascal; Roman, Marco; Šala, Martin; Delmonte, Barbara; +5 Authors

    Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) offers micron-resolution 2D chemical imaging, which has been adapted recently to ice core analysis. Measurements were performed in 2020 at the Ca’Foscari University of Venice, in order to investigate the localization of impurities in the ice samples. Here an image is presented from applying LA-ICP-MS elemental imaging to a glacial (MIS2, bag 1065) samples of the EPICA Dome C ice core from central Antarctica. Lateral resolution is 35 microns both along and perpendicular to the scan direction. Considered as analytes are 23Na, 25Mg and 88Sr. Background and drift correction as well as image construction were performed using the software HDIP (Teledyne Photon Machines, Bozeman, MT, USA). Impurity images are acquired as a pattern of lines, without overlap in the direction perpendicular to that of the scan, and without any further spatial interpolation. Each pixel in an ice core chemical image has a size of 35 μm x 35 μm. For each chemical element the datasets comprise a numerical matrix which contains rows and columns according to the physical size of the image: an image of 7 mm x 35 mm in size has 200 rows and 1000 columns. The numerical entries in this matrix refer to the recorded intensity (e.g. in counts). Values lower than the detection limit are set to zero. Due to the careful synchronization, the individual pixels of the different chemical channels can be considered to be almost perfectly spatially aligned. In contrast, the mosaic of visual images obtained from the laser camera is not a-priori aligned with the chemical images. The visual images are generally characterized by air bubbles (dark blobs), grain boundaries (dark lines) and occasional sub-grain boundaries (thin dark lines).

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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: ZENODO
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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    Authors: Salusso, Davide; Ahmad, Rafia; Ahoba-Sam, Christian; Ramirez, Adrian; +8 Authors

    Supplementary material: N2 adsorption, PXRD, IR, modelling, test results, XAS, SEM, PES, TEM

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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: ZENODO
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    Authors: Ticali, Pierfrancesco; Salusso, Davide; Ahmad, Rafia; Ahoba-Sam, Christian; +9 Authors

    Supplementary material: N2 adsorption, PXRD, IR, modelling, test results, XAS, SEM, PES, TEM

    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 . 2021
    License: CC BY
    Data sources: ZENODO
    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: ZENODO
      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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    Authors: Cabanes, Simon; Espa, Stefania; Galperin, Boris; Young, Roland M. B.; +1 Authors

    The formation of large scale structures in three-dimensional (3D) turbulent flows. How small-scale dynamics organize in turbulent flows to grow large scale coherent circulation? is at the heart of fundamental studies in fluid dynamics. It appears to be equally important for our understanding of atmospheric dynamics, oceanography, meteorology and more generally geophysical fluid dynamics. Here, we deliver a data collection that (1) gathers measurements of 3D turbulent flows that emulate planetary atmospheres of the gas giants. Turbulent flows are explored using three different approaches, laboratory experiments, numerical simulations and direct planetary observations. All data set are computed in order to easily extract flow properties, i.e. high resolution maps of the different velocity components and flow vorticity (useful for further diagnostic). The data collected are fully discribed in Cabanes et al GRL (2020) "Revealing the intensity of turbulent energy transfer in planetary atmospheres" and can be used to compute (2) theoretical diagnostics with the numerical codes that allow to reveal the physical meaning of flow measurements. Numerical codes are available on https://github.com/scabanes We deliver (1) data collection and (2) numerical codes in the following files attached: (1) Data collection: A PDF file named JUMP-zonal-jets-data-collection-GRL.pdf that describes the following data files and nomenclature. A zip File of the velocity fields in the lab, interpolated on Polar and Cartesian grids JUMP-JetsInTheLab.zip A netcdf file of velocity fields of our Saturn reference simulation uvData-SRS-istep-312000-nstep-50-niz-12.nc Two netcdf files of velocity fields from Cassini observations of Jupiter uvData-JupObs-istep-0-nstep-4-niz-1.nc StatisticalData-JupObs.nc A zip file of potential vorticity profiles for Saturn and Jupiter observations IPV-QGPV-Jupiter-Saturn.zip (2) Numerical codes: Codes for statistical analysis in spherical geometry on Github. --> https://github.com/scabanes/POST Codes for statistical analysis in cylindrical geometry on Github. --> https://github.com/scabanes/JUMP Codes for statistical analysis in cartesian geometry on Github. --> https://github.com/scabanes/JUMP The purpose of this data collection is to reveal statistical properties of planetary flows. By computing the same analysis on different data sets the researcher allows direct confrontation of planetary observations with idealized laboratory and numerical models. Idealized models are specially designed to sweep on a large array of parameters in order to understand what parameters control planetary global circulation. The data collected and generated by the researcher deliver (1) velocity measurements of 3D turbulent flows using the different approaches (observations-laboratory-numerics) and (2) guidelines to compute the appropriate statistical analysis through the PTST. Here, the ground-breaking novelty is that the researcher deliver the possibility to compute statistical diagnostics adapted to the different geometries: the spherical geometry of planetary flows, i.e. 2D latitude-longitude maps, the cylindrical geometry of laboratory experiments, i.e. 2D flows in a rotating cylindrical tank, and the Cartesian geometry of idealized numerical simulations. Indeed, the math behind each statistical diagnostics must account for the different geometrical configurations in order to properly confront the different approaches. The PTST is also designed to be easily re-used by different communities such as experimentalists, numericists and atmosphericists that deal with 3D or 2D turbulent flows. Acknowledgments This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement N° 797012.

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    ZENODO
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2020
    License: CC BY
    Data sources: ZENODO; Sygma
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      ZENODO
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2020
      License: CC BY
      Data sources: ZENODO; Sygma
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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: Rovere, Alessio; Rubio Sandoval, Karla Zurisadai; Ryan, Deirdre D.; Richiano, Sebastian; +5 Authors

    This repository contains the supplementary information and raw data annexed to the manuscript "Quaternary and Pliocene sea-level changes at Camarones, central Patagonia, Argentina", authored by Karla Rubio-Sandoval et al. and submitted for consideration in the journal Quaternary Science Reviews. The folder contains the following items. 1. Raw_data.xlsxThis is an excel file that includes all survey and analytical data in several sheets, briefly described hereafter. - GNSS data. Data surveyed with differential GNSS in the field.- Sea level index points. Datapoints used as sea-level index points, and associated calculations of paleo Relative Sea Level.- AAR Summary. Table summarising the main results of the AAR analyses.- AAR complete sheet. The complete set of analytical data done for the Amino Acid Racemization dating.- Radiocarbon data. The analytical results of radiocarbon dating.- Literature ages. A compilation of the Electron Spin Resonance and U-series ages published for the Camarones site.- Transects. Topographical transects extracted from the TanDEM-X Digital Elevation model and referred to the GEOIDEAR 16 geoid.- Distance plot. Data for plotting Relative Sea Level vs distance along the coast of the sea-level index points described in the manuscript. 2. Holocene (folder)This folder contains two excel files ("Area_Camarones_Accepted.xlsx" and "Area_Camarones_Rejected.xlsx") that include the Holocene data described in the paper compiled following the standard HOLSEA template. 3. Runup_modellingThis folder contains three folders, each with a Jupyter notebook (.ipynb) and datasets to perform the runup calculations described in the manuscript.

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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: ZENODO
    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: ZENODO
      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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    Authors: Canepa, Elisabetta;

    We need affect-based stimuli specifically conceived to investigate architectural spaces. The RESONANCES project crafted ATLAS, a dATabase of visuaL Atmospheric Stimuli. It collects a series of spatial patterns born from a systematic selection of generators of atmosphere. Generators of atmosphere are architectural features designed to afford atmospheric effects (such as lights, colors, materials, and proportions). ATLAS is an open-access tool that supports researchers interested in studying emotional reactions to architectural features by providing reliable, standardized, and reproducible stimuli. In this dataset, ATLAS stimuli are presented as videos. This database was developed within the Resonances project — Architectural Atmospheres: The Emotional Impact of Ambiances Measured through Conscious, Bodily, and Neural Responses. This project received funding from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement no. 101025132. The content of this work reflects only the authors' view. The European Research Executive Agency is not responsible for any use that may be made of the information it contains.

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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: ZENODO; Sygma
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: ZENODO; Sygma
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    Authors: Canepa, Elisabetta;

    We need affect-based stimuli specifically conceived to investigate architectural spaces. The RESONANCES project crafted ATLAS, a dATabase of visuaL Atmospheric Stimuli. It collects a series of spatial patterns born from a systematic selection of generators of atmosphere. Generators of atmosphere are architectural features designed to afford atmospheric effects (such as lights, colors, materials, and proportions). ATLAS is an open-access tool that supports researchers interested in studying emotional reactions to architectural features by providing reliable, standardized, and reproducible stimuli. In this dataset, ATLAS stimuli are presented as 2D images. This database was developed within the Resonances project — Architectural Atmospheres: The Emotional Impact of Ambiances Measured through Conscious, Bodily, and Neural Responses. This project received funding from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement no. 101025132. The content of this work reflects only the authors' view. The European Research Executive Agency is not responsible for any use that may be made of the information it contains.

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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: ZENODO; Sygma
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      ZENODO
      Dataset . 2023
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: ZENODO; Sygma
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    Authors: Canepa, Elisabetta; Condia, Bob; Beighle, Kory; Djebbara, Zakaria; +1 Authors

    This dataset is an output of the ‘Designing Atmospheres: Theory and Science’ Symposium (ATS), an Interfaces event of the Academy of Neuroscience for Architecture (ANFA), sponsored by the EU’s Horizon 2020 MSCA Program — RESONANCES Project, the Perkins Eastman Studio, and the KSTATE APDesign. The symposium was hosted in the College of Architecture, Planning and Design (APDesign), Kansas State University, Manhattan (Kansas, USA), on March 28, 2023. Speakers: Kory Beighle (Kansas State University), Elisabetta Canepa (University of Genoa | Kansas State University), Bob Condia (Kansas State University), Zakaria Djebbara (Aalborg University | TU Berlin), and Harry Francis Mallgrave (Illinois Institute of Technology). Recent advances in science confirm many of the architects’ deep-rooted intuitions, improving knowledge about the perception of space and the meaning of architectural and urban design. The symposium ‘Designing Atmospheres: Theory and Science‘ presented to an audience of students, educators, architects, and scientists a conversation about the experience of design and building, specifically speaking to the significance of atmospheres, affordances, and emotions. This dataset is made of seven files: no. 1 dataset summary (.pdf) no. 1 symposium poster (.pdf) no. 5 videos containing speakers’ presentations (.mp4) Recorded videos of each lecture are also available on the RESONANCES project website (www.resonances-project.com/harvest) and its YouTube channel (@resonancesproject5777). 'Designing Atmospheres: Theory and Science' Symposium is an Interfaces event of the Academy of Neuroscience for Architecture (ANFA), sponsored by the European Union's Horizon 2020 MSCA Program — RESONANCES Project, the Perkins Eastman Studio, and the KSTATE APDesign. The RESONANCES project received funding from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement no. 101025132. The content of the produced and published material reflects only the authors' views. The Research Executive Agency and the European Commission are not responsible for any use that may be made of the information it contains.

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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: ZENODO; Sygma
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      ZENODO
      Dataset . 2023
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      Data sources: Datacite
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      ZENODO
      Dataset . 2023
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      Data sources: ZENODO; Sygma
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    Authors: Maffezzoli, Niccolò; Cook, Eliza; van der Bilt, Willem G. M.; Støren, Eivind N.; +20 Authors

    This dataset refers to the ICELEARNING project - Detection of ice core particles via deep neural networks, by Maffezzoli N. et al., The Cryosphere, 10.5194/tc-17-539-2023, 2023. The main folder contains all TRAINING data. The TEST data are contained in the folder /test. Please refer to the icelearning GitHub repository for instructions. {"references": ["Maffezzoli, Niccol\u00f2, et al. \"Detection of ice core particles via deep neural networks.\" The Cryosphere 17.2 (2023): 539-565."]} For questions, contact niccolo.maffezzoli@unive.it

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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2023
    License: CC BY
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: ZENODO
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    Authors: Canepa, Elisabetta;

    This dataset is an output of the ‘Generators of Architectural Atmosphere’ Symposium, an Interfaces event of the Academy of Neuroscience for Architecture (ANFA), sponsored by the EU’s Horizon 2020 MSCA Program — RESONANCES Project, the Perkins Eastman Studio, and the 2020 Regnier Chair. The symposium was hosted in the College of Architecture, Planning and Design (APDesign), Kansas State University, Manhattan (Kansas, USA), on April 12, 2022. Speakers: Bob Condia (Kansas State University), Elisabetta Canepa (University of Genoa and Kansas State University), Kutay Güler (Kansas State University), and Tiziana Proietti (Oklahoma University). Recent advances in science confirm many of the architect’s expert intuitions opening new doors to the perception of space and the meaning of architectural and urban design. The symposium ‘Generators of Architectural Atmosphere’ presented to an audience of students, educators, architects, and scientists a conversation about human perception of design and building, specifically speaking to the significance of atmosphere, mood, architectural proportion, and virtual reality. This dataset is made of six files: no. 1 dataset summary (.pdf) no. 1 symposium poster (.pdf) no. 4 videos containing speakers’ presentations (.mp4). Recorded videos of each lecture are also available on the RESONANCES project website (www.resonances-project.com/harvest) and its YouTube channel (UCk32skDiT4Bz1AHnltT51Yg). 'Generators of Architectural Atmosphere' Symposium is an Interfaces event of the Academy of Neuroscience for Architecture (ANFA), sponsored by the European Union's Horizon 2020 MSCA Program — RESONANCES Project, the Perkins Eastman Studio, and the 2020 Regnier Chair. The RESONANCES project has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement no. 101025132. The content of the produced and published material reflects only the authors' views. The Research Executive Agency and the European Commission are not responsible for any use that may be made of the information it contains.

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    ZENODO
    Dataset . 2022
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    Data sources: Datacite
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    ZENODO
    Dataset . 2022
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      ZENODO
      Dataset . 2022
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      ZENODO
      Dataset . 2022
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    Authors: Bohleber, Pascal; Roman, Marco; Šala, Martin; Delmonte, Barbara; +5 Authors

    Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) offers micron-resolution 2D chemical imaging, which has been adapted recently to ice core analysis. Measurements were performed in 2020 at the Ca’Foscari University of Venice, in order to investigate the localization of impurities in the ice samples. Here an image is presented from applying LA-ICP-MS elemental imaging to a glacial (MIS2, bag 1065) samples of the EPICA Dome C ice core from central Antarctica. Lateral resolution is 35 microns both along and perpendicular to the scan direction. Considered as analytes are 23Na, 25Mg and 88Sr. Background and drift correction as well as image construction were performed using the software HDIP (Teledyne Photon Machines, Bozeman, MT, USA). Impurity images are acquired as a pattern of lines, without overlap in the direction perpendicular to that of the scan, and without any further spatial interpolation. Each pixel in an ice core chemical image has a size of 35 μm x 35 μm. For each chemical element the datasets comprise a numerical matrix which contains rows and columns according to the physical size of the image: an image of 7 mm x 35 mm in size has 200 rows and 1000 columns. The numerical entries in this matrix refer to the recorded intensity (e.g. in counts). Values lower than the detection limit are set to zero. Due to the careful synchronization, the individual pixels of the different chemical channels can be considered to be almost perfectly spatially aligned. In contrast, the mosaic of visual images obtained from the laser camera is not a-priori aligned with the chemical images. The visual images are generally characterized by air bubbles (dark blobs), grain boundaries (dark lines) and occasional sub-grain boundaries (thin dark lines).

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    ZENODO
    Dataset . 2021
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    Dataset . 2021
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      ZENODO
      Dataset . 2021
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      ZENODO
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    Authors: Salusso, Davide; Ahmad, Rafia; Ahoba-Sam, Christian; Ramirez, Adrian; +8 Authors

    Supplementary material: N2 adsorption, PXRD, IR, modelling, test results, XAS, SEM, PES, TEM

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    ZENODO
    Dataset . 2021
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: ZENODO
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    Authors: Ticali, Pierfrancesco; Salusso, Davide; Ahmad, Rafia; Ahoba-Sam, Christian; +9 Authors

    Supplementary material: N2 adsorption, PXRD, IR, modelling, test results, XAS, SEM, PES, TEM

    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 . 2021
    License: CC BY
    Data sources: ZENODO
    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: ZENODO
      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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    Authors: Cabanes, Simon; Espa, Stefania; Galperin, Boris; Young, Roland M. B.; +1 Authors

    The formation of large scale structures in three-dimensional (3D) turbulent flows. How small-scale dynamics organize in turbulent flows to grow large scale coherent circulation? is at the heart of fundamental studies in fluid dynamics. It appears to be equally important for our understanding of atmospheric dynamics, oceanography, meteorology and more generally geophysical fluid dynamics. Here, we deliver a data collection that (1) gathers measurements of 3D turbulent flows that emulate planetary atmospheres of the gas giants. Turbulent flows are explored using three different approaches, laboratory experiments, numerical simulations and direct planetary observations. All data set are computed in order to easily extract flow properties, i.e. high resolution maps of the different velocity components and flow vorticity (useful for further diagnostic). The data collected are fully discribed in Cabanes et al GRL (2020) "Revealing the intensity of turbulent energy transfer in planetary atmospheres" and can be used to compute (2) theoretical diagnostics with the numerical codes that allow to reveal the physical meaning of flow measurements. Numerical codes are available on https://github.com/scabanes We deliver (1) data collection and (2) numerical codes in the following files attached: (1) Data collection: A PDF file named JUMP-zonal-jets-data-collection-GRL.pdf that describes the following data files and nomenclature. A zip File of the velocity fields in the lab, interpolated on Polar and Cartesian grids JUMP-JetsInTheLab.zip A netcdf file of velocity fields of our Saturn reference simulation uvData-SRS-istep-312000-nstep-50-niz-12.nc Two netcdf files of velocity fields from Cassini observations of Jupiter uvData-JupObs-istep-0-nstep-4-niz-1.nc StatisticalData-JupObs.nc A zip file of potential vorticity profiles for Saturn and Jupiter observations IPV-QGPV-Jupiter-Saturn.zip (2) Numerical codes: Codes for statistical analysis in spherical geometry on Github. --> https://github.com/scabanes/POST Codes for statistical analysis in cylindrical geometry on Github. --> https://github.com/scabanes/JUMP Codes for statistical analysis in cartesian geometry on Github. --> https://github.com/scabanes/JUMP The purpose of this data collection is to reveal statistical properties of planetary flows. By computing the same analysis on different data sets the researcher allows direct confrontation of planetary observations with idealized laboratory and numerical models. Idealized models are specially designed to sweep on a large array of parameters in order to understand what parameters control planetary global circulation. The data collected and generated by the researcher deliver (1) velocity measurements of 3D turbulent flows using the different approaches (observations-laboratory-numerics) and (2) guidelines to compute the appropriate statistical analysis through the PTST. Here, the ground-breaking novelty is that the researcher deliver the possibility to compute statistical diagnostics adapted to the different geometries: the spherical geometry of planetary flows, i.e. 2D latitude-longitude maps, the cylindrical geometry of laboratory experiments, i.e. 2D flows in a rotating cylindrical tank, and the Cartesian geometry of idealized numerical simulations. Indeed, the math behind each statistical diagnostics must account for the different geometrical configurations in order to properly confront the different approaches. The PTST is also designed to be easily re-used by different communities such as experimentalists, numericists and atmosphericists that deal with 3D or 2D turbulent flows. Acknowledgments This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement N° 797012.

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    ZENODO
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2020
    License: CC BY
    Data sources: ZENODO; Sygma
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      ZENODO
      Dataset . 2020
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      Data sources: Datacite
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      ZENODO
      Dataset . 2020
      License: CC BY
      Data sources: ZENODO; Sygma
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