BUSCADOR RECOLECTA

Datasets are available in CSV format, being the field delimiter « , » (comma). For further clarification, please look at the README files of every data subset., Part B of this dataset is available at http://hdl.handle.net/2445/139554 under embargoed access, This dataset refers to PERCEIVE tasks 2.2, 2.3, 2.4 and 2.5. These tasks analyze the data sets developed by PERCEIVE task 2.1 in order to identify, quantify and synthetize the most important variables to asses identification with EU by citizens. The results feed an update of the data set developed in task 2.1. Finally, these data is be used to model convergence of EU citizens' identification in the case study regions. Data consists of the quantitative statistical information used to produce all the results of WP2 and the indicators regarding the variables of interest obtained by means of different statistical techniques. Moreover, data on absorption of EU funds, provided by the EC and other research centres and collected in task 2.5, is be gathered in this data set, together with the results of convergence analysis. This data set is be used to evaluate the EU citizens’ perception of the EU project in relation to regional performance of the cohesion policy and institutional quality. WP2 uses primary data from the survey developed in WP1 (“PERCEIVE: WP1: Framework for comparative analysis of the perception of Cohesion Policy and identification with the European Union at citizen level in different European countries: Task1.3: Survey at citizen level” data set) and also comparative case studies on EU countries and regions, coming also from WP1 (”PERCEIVE: WP1: Framework for comparative analysis of the perception of Cohesion Policy and identification with the European Union at citizen level in different European countries: Task1.1: The framework for the comparative analysis” and ”PERCEIVE: WP1: Framework for comparative analysis of the perception of Cohesion Policy and identification with the European Union at citizen level in different European countries: Task1.2: Focus group with Cohesion Policy practitioners” data sets). The data set incorporates data from existing sources including Eurostat and information resulting from the Survey conducted at WP1 of the PERCEIVE’s project. As regards secondary data, no additional treatment is needed. Info about the sources of such data, including references to technical details, is provided in the dataset's codebook.

Datasets are available in CSV format, being the field delimiter « , » (comma). For further clarification, please look at the README files of every data subset., Part A of this dataset is publicly available at http://hdl.handle.net/2445/137318, This dataset refers to PERCEIVE tasks 2.4 and 2.5. These tasks analyze the data sets developed by PERCEIVE task 2.1 in order to identify, quantify and synthetize the most important variables to asses identification with EU by citizens. The results feed an update of the data set developed in task 2.1. Finally, these data is be used to model convergence of EU citizens' identification in the case study regions. Data consists of the quantitative statistical information used to produce all the results of WP2 and the indicators regarding the variables of interest obtained by means of different statistical techniques. Moreover, data on absorption of EU funds, provided by the EC and other research centres and collected in task 2.5, is be gathered in this data set, together with the results of convergence analysis. This data set is be used to evaluate the EU citizens’ perception of the EU project in relation to regional performance of the cohesion policy and institutional quality. WP2 uses primary data from the survey developed in WP1 (“PERCEIVE: WP1: Framework for comparative analysis of the perception of Cohesion Policy and identification with the European Union at citizen level in different European countries: Task1.3: Survey at citizen level” data set) and also comparative case studies on EU countries and regions, coming also from WP1 (”PERCEIVE: WP1: Framework for comparative analysis of the perception of Cohesion Policy and identification with the European Union at citizen level in different European countries: Task1.1: The framework for the comparative analysis” and ”PERCEIVE: WP1: Framework for comparative analysis of the perception of Cohesion Policy and identification with the European Union at citizen level in different European countries: Task1.2: Focus group with Cohesion Policy practitioners” data sets). The data set incorporates data from existing sources including Eurostat and information resulting from the Survey conducted at WP1 of the PERCEIVE’s project. As regards secondary data, no additional treatment is needed. Info about the sources of such data, including references to technical details, is provided in the dataset's codebook.

The different datasets are divided in folders as follows: 1. In situ experiments. The article is based on 7 different in situ experiments: a. 400C_5mLmin_fr10; b. 400C_10mLmin_fr23; c. 400C_20mLmin_fr6; d. 400C_30mLmin_fr12; e. 300C_10mLmin_fr4; f. 350C_10mLmin_fr18; g. 500C_10mLmin_fr9. (Due to space limitations, only the data corresponding to the experiment c were uploaded to this repository. The remaining data are accessible through private communication with Cecilia Granados-Miralles, c.granados.miralles@icv.csic.es). The folder “c_400C_20mLmin_fr6” contains in situ PXRD data (time resolution=5 s) collected during reduction at the temperature and gas flow indicated in the folder name (i.e. 400C_20mLmin stands for 400 °C and 20 mL/min). The temperature indicated in the file names is the set temperature but the sample temperature is the indicated in the folder name (i.e. Tset430 led to a sample temperature of 400 °C). Heating started on the frame indicated in the folder name (i.e. fr6 stands for frame 6). This folder contains 2D-diffraction images in *.tif format, which may be opened with the Python-based program for on-the-fly data processing and exploration of two-dimensional X-ray diffraction area detector data, available for free download at http://www.clemensprescher.com/programs/dioptas., 2. Ex situ experiments: a. PXRD_Cu 1D-diffraction patterns in *.dat format. 3 space-/tab-separated columns: 2theta angle (degree), Diffracted Intensity (arbitrary units), σ (arbitrary units); b. PXRD_Co Same as previous; c. NPD_DMC 1D-diffraction patterns in *.dat format. The first line indicates: narrowest 2theta angle measured, measurement step, widest 2theta angle. The following values are the diffracted intensities recorded for each 2theta step; d. NPD_HRPT; Same as previous e. VSMHysteresis loops: Magnetic moment as a function of a variable applied field in *.dat format. Several comma-separated columns of which the relevant are the 4th, 5th, and 6th columns, which contain: Magnetic Field (Oe), Moment (emu), M. Std. Err. (emu)., During the past decade, CoFe2O4 (hard)/Co–Fe alloy (soft) magnetic nanocomposites have been routinely prepared by partial reduction of CoFe2O4 nanoparticles. Monoxide (i.e., FeO or CoO) has often been detected as a byproduct of the reduction, although it remains unclear whether the formation of this phase occurs during the reduction itself or at a later stage. Here, a novel reaction cell was designed to monitor the reduction in situ using synchrotron powder X-ray diffraction (PXRD). Sequential Rietveld refinements of the in situ data yielded time-resolved information on the sample composition and confirmed that the monoxide is generated as an intermediate phase. The macroscopic magnetic properties of samples at different reduction stages were measured by means of vibrating sample magnetometry (VSM), revealing a magnetic softening with increasing soft phase content, which was too pronounced to be exclusively explained by the introduction of soft material in the system. The elemental compositions of the constituent phases were obtained from joint Rietveld refinements of ex situ high-resolution PXRD and neutron powder diffraction (NPD) data. It was found that the alloy has a tendency to emerge in a Co-rich form, inducing a Co deficiency on the remaining spinel phase, which can explain the early softening of the magnetic material., European Comission through FP7 program, NANOPYME project, grant agreement no. 310516. European Comission through H2020 program, AMPHIBIAN Project, grant agreement no. 720853. Danish National Research Foundation through Center for Materials Crystallography, DNRF-93. Danish Center for Synchrotron and Neutron Science through DanScatt. European Comission through FP7 program, NMI3-II project, grant agreement no. 283883., Peer reviewed

UE, programa H2020, Proyecto AMPHIBIAN n º 720853, Peer reviewed

UE, programa H2020, Proyecto AMPHIBIAN n º 720853., Peer reviewed

We provide the code for producing Functional Urban Areas by means of using OSM and Google maps data., Dades associades a l'article: Obaco A., Moisés; Royuela Mora, Vicente (2019): Identifying functional urban areas in Ecuador using a varying travel time approach,. Publicat a: Geographical Analysis, 2020, vol. 52, n. 1. (https://onlinelibrary.wiley.com/doi/10.1111/gean.12190). DOI: https://doi.org/10.1111/gean.12190., Podeu consultar l'article associat a: http://hdl.handle.net/2445/154578, Identifying integrated urban areas is an important issue for urban analysis and policy evaluation. In this paper, we provide a set of FUAs suitable for monitoring urbanization in Ecuador, a less developed country without commuting data. We do so substituting such socioeconomic flows by available information on road structure, which allow us to work with accessibility based on a varying travel time. In order to build Ecuadorean FUAs, we calibrate our methodology considering Colombian data. We perform several sensitivity analysis and robustness checks to Ecuador with alternative sources of socioeconomic flows. We conclude that the use of GIS data and the calibrated thresholds provide a set of FUAs close to the ones that would result of using commuting information.