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63 Research products, page 1 of 7

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  • Open Access English
    Authors: 
    Meijer, Jeroen; Lamoree, Marja; Hamers, Timo; Antingac, Jean-Philippe; Hutinet, Sébastien; Debrauwer, Laurent; Covaci, Adrian; Huber, Carolin; Krauss, Martin; Walker, Douglas I; +3 more
    Publisher: Zenodo
    Country: Belgium
    Project: EC | HBM4EU (733032), EC | HBM4EU (733032)

    This is the collection associated with list S71 CECSCREEN HBM4EU CECscreen: Screening List for Chemicals of Emerging Concern Plus Metadata and Predicted Phase 1 Metabolites on the NORMAN Suspect List Exchange. https://www.norman-network.com/nds/SLE/ CECScreen is part of the HBM4EU project (coord. UBA) > WP16 "emerging chemicals" (lead INRA, JP Antignac/L Debrauwer) > Task 16.1 (lead IRAS, J Vlanderen / R Vermeulen) > Main contributor (J Meijer) > Involved Partners (M Lamoree, T Hamers, S Hutinet, A, Covaci, C Huber, M Krauss, DI Walker, EL Schymanski). Further details in Meijer et al (2021) DOI: 10.1016/j.envint.2021.106511. Dataset DOI: 10.5281/zenodo.3956586. Update 23/7/2020 (v0.1.1): updated MetFrag files to remove elements causing errors (Os, Pd, Ag, Be). Update 8 Nov 2022 (v0.1.2) removed new lines in several synonyms as detected at BioHackEU22.

  • Open Access English
    Authors: 
    Lavagnoli, Sergio; Lopes, Gustavo; Simonassi, Loris; Torre, Antonino Federico Maria;
    Publisher: Zenodo
    Project: EC | SPLEEN (820883)

    This is an open-access database of experimental data of the flow in a high-speed low-pressure turbine cascade. The data have been collected at the von Karman Institute for Fluid Dynamics in the period 2018-2022 within the H2020 Clean Sky 2 project SPLEEN – Secondary and Leakage Flow Effects in High-Speed Low-Pressure Turbines, a project in collaboration with Safran Aircraft Engines. This version contains documents that describe the experimental setup, instrumentation, measurement uncertainties, geometries, and database structure. The database contains experimental data of the test campaign conducted on the linear cascade codenamed SPLEEN C1 in the VKI high-speed wind tunnel S1/C. The turbine cascade geometry is representative of designs of high-speed low-pressure turbines for next-generation geared turbofan engines. The measurement datasets describe the flow through the turbine cascade tested at on- and off-design conditions, with and without a wake generator located upstream of the cascade, and with and without endwall cavity injection/suction. The database includes measurements of pressure, temperature, flow angles, Mach numbers, pressure loss, unsteady blade and endwall pressure and quasi-shear-stress. Version v1 of the database includes measurement datasets performed on the turbine cascade WITH FLAT ENDWALL (no cavity) WITHOUT WAKE GENERATOR (Steady inlet flow). Future versions will also include experimental data of the test case turbine equipped with a wake generator (unsteady inflow with wakes) and endwall cavity flow purge / suction. The project has received Funding from the Clean Sky 2 Joint Undertaking under the European Union's Horizon 2020 research and innovation program under the grant agreement 820883.

  • Open Access English
    Authors: 
    Panagiotis Karras;
    Publisher: Zenodo
    Project: EC | INHuMAN (841092), EC | INHuMAN (841092)

    Although melanoma is notorious for its high degree of heterogeneity and plasticity1,2, the origin and magnitude of cell state diversity remains poorly understood. Equally, it is not known whether melanoma growth and metastatic dissemination are supported by overlapping or distinct melanoma subpopulations. By combining mouse genetics, unbiased lineage tracing and quantitative modelling, single-cell and spatial transcriptomics, we provide evidence of a hierarchical model of tumour growth that mirrors the cellular and molecular logic underlying embryonic neural crest cell fate specification and differentiation. Our findings indicate that tumorigenic competence is associated with a spatially localized perivascular niche environment, a phenotype acquired through a NOTCH3-dependent intercellular communication pathway established by endothelial cells. Consistent with a model in which only a fraction of melanoma cells is fated to fuel growth, temporal single-cell tracing of a population of melanoma cells harbouring a mesenchymal-like state revealed that these cells do not contribute to primary tumour growth but, instead, constitutes a pool of metastatic-initiating cells that can switch cell identity while disseminating to secondary organs. Our data provide a spatially and temporally resolved map of the diversity and trajectories of cancer cell states within the evolving melanoma ecosystem and suggest that the ability to support growth and metastasis are limited to distinct pools of melanoma cells. The observation that these phenotypic competencies can be dynamically acquired upon exposure to specific niche signals warrant the development of therapeutic strategies that interfere with the cancer cell reprogramming activity of such microenvironmental cues.

  • Open Access English
    Authors: 
    Rossetti, Alessandra; Van Waes, Luuk;
    Publisher: Zenodo
    Country: Belgium
    Project: EC | PLanTra (888918), EC | PLanTra (888918)

    This folder contains data on text simplification collected from an experimental study with second-language university students. We adopted a pre-test and post-test design, and randomly divided participants into experimental and control group. In the pre-test, participants were given an extract of a corporate report dealing with sustainability and were asked to revise it to make it easier to read for a lay customer. Subsequently, they took part in training. The experimental group received training on both plain language and sustainability, while the control group received training exclusively on the topic of sustainability. In the post-test session (2-3 days after the pre-test), all participants were assigned a second extract of a corporate report dealing with sustainability, and were asked again to make it easier to read for a lay customer by applying what they had learned from their respective training. This design allowed us to examine the impact of plain language training on text simplification (revision) tasks. The texts were in English while the participants were native speakers of other languages (mainly Dutch), so the text simplification took place in their second language. This project (PLanTra) has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 888918. Please see "readme" file for additional information.

  • Open Access English
    Authors: 
    Van der Stocken, Tom;
    Publisher: Dryad
    Project: EC | GLOMAC (896888), EC | GLOMAC (896888)

    This dataset contains data on future changes in sea-surface water properties along the global distribution of mangrove forests. This includes the coordinates of mangrove occurence and associated information on present (2000-2014) and future (2090-2100) sea-surface temperature (SST), sea-surface salinity (SSS), and sea-surface density (SSD, derived from SST and SSS, using the UNESCO EOS-80 equation of state polynomial for seawater - 'sw_dens.m' in MATLAB). SST and SSS fields from which the data were extracted, are from the Bio-ORACLE database. Additionally, for each of the mangrove occurence points (longitude, latitude), information is provided about the main mangrove biogeographical region and associated province as provided in the Marine Ecoregions of the World dataset (Spalding et al., 2007, BioScience), alowing for a spatial analysis of the data. More information and details about the data are provided in the README sheet of the Excel data file. For details about the data, we refer to the README sheet that is provided in the Excel data file, as well as the Methods section in the associated manuscript.

  • Open Access English
    Authors: 
    Nicolas, Judith; Albouy, Geneviève; King, Brad R.;
    Publisher: Zenodo
    Project: EC | CLASSy Aging (887955), EC | Stim-Plast-O (703490), EC | CLASSy Aging (887955), EC | Stim-Plast-O (703490)

    Data set of manuscript entiteld Sigma Oscillations Protect or Reinstate Motor Memory Depending on their Temporal Coordination with Slow Waves EEG files : Brainvision *.dat; *.edf : eeg files of the experimental nap *.vhdr: corresponding header files *.vmrk: corresponding marker files time starting from recording sample *._Pauselog.txt: markers with condition in the stimulation computer time Sleep Scores: Scores by the sleep technician (one file per participants). Surveys: General survey (first screening) and complete survey (for inclusion). Code correspondance is provided in ID_correspondance.txt BehavData: For each participant, a text file with all the cues and responses logged for each tasks. *_raw.txt are present when an issue arised during experiment and a task needed to be re-started.

  • Open Access English
    Authors: 
    Toso, Stefano; Imran, Muhammad; Mugnaioli, Enrico; Moliterni, Anna; Caliandro, Rocco; Schrenker, Nadine J.; Pianetti, Andrea; Zito, Juliette; Zaccaria, Francesco; Wu, Ye; +6 more
    Publisher: Zenodo
    Project: EC | REALNANO (815128), EC | REALNANO (815128)

    This dataset provides the raw data associated with the publication "Halide Perovskites as Disposable Epitaxial Templates for the Phase-Selective Synthesis of Lead Sulfochloride Nanocrystals".It contains: A readme file meant to help the user navigate the database The raw data associated with all the plots and charts found in the Main Text and in the Supplementary information. The raw data collected during the 3D electron diffraction experiments on Pb3S2Cl2 Nanocrystals. The CIF files of all the crystal structures refined in the work An atomistic model of the Pb4S3Cl2/CsPbCl3 interface, which can be visualized with the freeware software Vesta. The authors acknowledge financial support from the Research Foundation - Flanders (FWO) through a postdoctoral fellowship to N.J.S. (FWO Grant No. 1238622N). The access to the National Synchrotron Light Source, Brookhaven National Laboratory, was supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, under Contract No. DE-AC02-98CH10886 (NSLS-II Proposal Number 307441).

  • Open Access English
    Authors: 
    Singh, Anurag; Valkenier, Hennie;
    Publisher: Zenodo
    Project: EC | ORGANITRA (802727), EC | ORGANITRA (802727)

    Dataset for the publication: Calix[6]arenes with halogen bond donor groups as selective and efficient anion transporters by A. Singh, A. Torres-Huerta, T. Vanderlinden, N. Renier, L. Martínez-Crespo, N. Tumanov, J. Wouters, K. Bartik, I. Jabin, H. Valkenier, Chem. Commun. 2022, doi:10.1039/D2CC008472E, containing: A file with the structures of compounds 1-5 (PDF) NMR spectra for the characterisation of compounds 1a, 1b, 1c, 2, and 3 (Mestrenova files) NMR spectra for the titration experiments with compounds 1-5 in different solvents (Mestrenova files) Concentrations of Host and Guests in the various titration experiments (Excel file) Transport data in the lucigenin assay (Excel file) Transport data in the HPTS assay (Excel file) {"references": ["Calix[6]arenes with halogen bond donor groups as selective\u00a0and efficient anion transporters by\u00a0A. Singh, A. Torres-Huerta, T. Vanderlinden, N. Renier, L. Mart\u00ednez-Crespo, N. Tumanov, J. Wouters, K. Bartik, I. Jabin, H. Valkenier,\u00a0Chem. Commun.\u00a02022, doi:10.1039/d2cc008472e"]}

  • Open Access English
    Authors: 
    Koppa, Akash; Rains, Dominik; Hulsman, Petra; Poyatos, Rafael; Miralles, Diego G.;
    Publisher: Zenodo
    Project: EC | DOWN2EARTH (869550), EC | DRY-2-DRY (715254), EC | DOWN2EARTH (869550), EC | DRY-2-DRY (715254)

    This repository contains the datasets used in the research article "A Deep Learning-Based Hybrid Model of Global Terrestrial Evaporation". The repository contains the following files: 1) Input - contains all the processed input used for training the deep learning models and the datasets used for creating the figures in the article. 2) Output - contains the final deep learning models and the outputs (evaporation and transpiration stress factor) outputs from the hybrid model developed in the study. Formats: All scripts are in the programming language Python. The datasets are in HDF5 and NetCDF file formats. The codes related to the research article and deep learning model are available in the following repository: https://github.com/akashkoppa/StressNet

  • Open Access English
    Authors: 
    Melo; Anache; Borges; Miralles; Martens; Fisher; Nóbrega; Moreno; Cabral; Rodrigues; +24 more
    Publisher: Zenodo
    Project: UKRI | "NORDESTE" (NE/N012488/1), UKRI | Brazilian Experimental da... (NE/R004897/1), EC | SEDAL (647423), EC | DRY-2-DRY (715254), UKRI | "Nordeste" (NE/N012526/1), UKRI | "NORDESTE" (NE/N012488/1), UKRI | Brazilian Experimental da... (NE/R004897/1), EC | SEDAL (647423), EC | DRY-2-DRY (715254), UKRI | "Nordeste" (NE/N012526/1)

    Funding for AmeriFlux data resources was provided by the U.S. Department of Energy's Office of Science. Davi de C. D. Melo was supported by the São Paulo State Research Foundation (FAPES) (grant 2016/23546-7) and by the Brazilian National Council for Scientific and Technological Development (CNPq) (project 409093/2018-1). Paulo Tarso S. Oliveira was supported by the Brazilian National Council for Scientific and Technological Development (CNPq) (grants 441289/2017-7 and 306830/2017-5) and the CAPES Print program. Rafael Rosolem would like to acknowledge the Brazilian Experimental datasets for MUlti-Scale interactions in the critical zone under Extreme Drought (BEMUSED) project [grant number NE/R004897/1] funded by the Natural Environment Research Council (NERC). Alvaro Moreno was financially supported by the NASA Earth Observing System MODIS project (grant NNX08AG87A) and the European Research Council (ERC) funding under the ERC Consolidator Grant 2014 SEDAL (Statistical Learning for Earth Observation Data Analysis, European Union) project under Grant Agreement 647423. Diego G. Miralles, Brecht Martens and Dominik Rains are supported by the European Research Council (ERC) DRY–2–DRY project (grant no. 715254) and the Belgian Science Policy Office (BELSPO) STEREO III ALBERI (grant no. SR/00/373) and ET–SENSE (grant. no SR/02/377) projects. Thiago R. Rodrigues was supported by the Brazilian National Council for Scientific and Technological Development (CNPq) with Bolsa de Produtividade em Pesquisa - PQ (Grant Number 308844/2018-1). Jorge Perez-Quezada and Mauricio Galleguillos were supported by the Chilean National Agency for Research and Development, grant FONDECYT 1211652. Rodolfo Nobrega and Anne Verhoef acknowledge support by the Newton/NERC/FAPESP Nordeste project: NE/N012488/1. Gabriela Posse acknowledges support by AERN 3632 and PNNAT 1128023 INTA Projects. Funding for site support: NPW tower: Brazilian National Institute for Science and Technology in Wetlands (INCT-INAU), Federal University of Mato Grosso (UFMT - PGFA and PGAT), University of Cuiabá (UNIC) and SESC-Pantanal; SDF tower: funded by the National Commission for Scientific and Technological Research (CONICYT, Chile) through grants FONDEQUIP AIC-37 and AFB170008 from the Associative Research Program. TF1 and TF2 towers: funded by the Deutsche Forschungsgemeinschaft (DFG) under Germany's Excellence Strategy – EXC 177 'CliSAP - Integrated Climate System Analysis and Prediction' – contributing to the Center for Earth System Research and Sustainability (CEN) of Universität Hamburg and by DFG project KU 1418/6-1. MCR and BAL towers: funded by the National Council for Scientific and Technological Research (CONICET, Argentina) grants PIP-11220100100044 and PIP-11220130100347CO, and by the National Agency for the Scientific and Technological Promotion (ANPCyT, Argentina) grant PICT 2010-0554. JBF contributed to this research at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. California Institute of Technology. Government sponsorship acknowledged. JBF was supported in part by NASA: ECOSTRESS and SUSMAP. Copyright 2021. All rights reserved. CAA, CST, and ESEC Towers: funded by National Observatory of Water and Carbon Dynamics in the Caatinga Biome (INCT-NOWCDCB), Federal University of Pernambuco (UFPE), FACEPE (Fundação de Amparo à Ciência e Tecnologia do Estado de Pernambuco) through the Project Caatinga-FLUX APQ 0062-1.07/15. Metadata of ‘Are remote sensing evapotranspiration models reliable across South American ecoregions?’ This document describes the file formatting and data used to run and evaluate the evapotranspiration models in this study. Because forcing data varies among models, each input file contains a different set of meteorological data placed within a folder named after the corresponding model. File format and time stamps Data files are CSV formatted with timestamps in the first column of the file. The following timestamps are used: GLEAM: Year (YYYY); Day of Year (DDD) PT-JPL: Year (YYYY); Month (MM); Day (DD) PM-MOD: Year (YYYY); Month (MM); Day (DD) PM-VI: Date (MM/DD/YYYY) Missing data Missing data are reported using ‘NaN’ as a replacement flag. Data for all days in a leap year are reported. Data format The column headers Name, Description and Units are adopted used in the data files to describe the following variables:: ETo, Penman-Monteith FAO-56 reference evapotranspiration (mm day-1); ETobs, Observed evapotranspiration (mm day-1); Rn, Surface Net Radiation (w m-2); Rg, Daylight shortwave Incoming Radiation (w m-2); Rgs_out, Shortwave Radiation - outgoing (w m-2); G, Soil heat flux (w m-2); P, Rainfall (mm day-1); T, Surface Air Temperature (ºC); Tmax, Maximum Temperature (ºC); Tmin, Minimum Temperature (ºC); Tday, Daytime Temperature (ºC); TminDay, Daytime Minimum Temperature (ºC); TminNight, Nighttime Minimum Temperature (ºC); Patm, Atmospheric Air Pressure (Pa); ea, Actual Vapor Pressure (kPa); es, Saturation Vapor Pressure (kPa); VPD, Vapor Pressure Deficit (kPa); eaDay, Daytime Actual Vapor Pressure (kPa); eaNight, Nighttime Actual Vapor Pressure (kPa); RH, Air Relative Humidity; RHDayTime, Daytime Air Relative Humidity; RHNightTime, Nighttime Air Relative Humidity; LAI, Leaf Area Index (m² m-²); SWC, Soil Water Content (mm m-1). Forcing data per model Each model requires a different set of forcing data, as follows: GLEAM: Rn, P, T, Rgs_out; PT-JPL: Tmax, Rn, RH (or ea); PM-MOD: Rg, Tday, TminDay, TminNight, RHDayTime, RHNighttime, eaDay, eaNight; PM-VI: ETo. Tower sites (IDs) and co-authors/PIs: SDF: J. P. Quezada and M. Galleguillos; TF1 and TF2: L. Kutzbach and D. Holl; GRO and SLU: G. Posse; BAL and MCC: M. Gassman and C. Perez; PDG, EUC and USR: O. Cabral; FM and SIN: J.S. Nogueira and T. Range; CAA: M. Moura; CST: A. C. D. Antonino; SJO: E. S. Souza and J. R. S. Lima; ESEC: B. Bezerra.

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