Resultados de investigación

Nowadays, there is a severe problem with waste generation, especially with single-use packaging. Although the trend is to try to recycle or reuse this waste, a significant amount still ends up in landfills, which represents a serious environmental problem. This waste includes laminated materials, which are difficult to recycle because the polymeric material and aluminium layers cannot be separated easily. This work proposes the study of the valorisation of several laminated wastes as radon barriers for indoor spaces due to the similarity in composition between these waste and commercial radon barriers. This dataset contains the experimental data generated during the evaluation of laminated wastes composed of polymeric and aluminium materials as potential radon barriers for indoor spaces. It includes the raw radon concentration measurements recorded in the source and receiver chambers during 48-hour diffusion tests, the main specifications of the experimental set-up used to perform the measurements, and the thickness of the laminated waste samples used in the study. The experimental data were used to calculate the radon concentration reduction and the radon diffusion coefficient, following a modified version of the ISO/TS 11665–13:2017 standard, as reported in the associated publication., This work is financed by grant SUB-33/2021 funded by the Spanish Nuclear Safety Council for laminated wastes, and by grant PID2021-125345OA-I00 funded by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe” for metallised wastes. B.Ruvira was funded by a pre-doctoral grant from the CSN-UPV "Vicente Serradell" Chair. The authors would like to thank GDES for their collaboration during the research.

Se incluye una muestra de 60 rankings globales de universidades, categorizados en función de una taxonomía propuesta. Estos contenidos constituyen los datos utilizados en un capítuo de libro de futura publicación.

The sponsored content on social networks has raised new questions and research objectives, including discussions regarding the budget invested in these sites by political parties, as well as the new central role that technology corporations play in electoral contexts. This dataset comprises 10,485 Facebook Ad corpus obtained from the Facebook Ad Library through a web crawler developed in Pyhton. The dataset elements correspond to the Facebook Ads paid by the main national political parties during the two 2019 Spanish General Elections precampaign and campaign. The parties are the following: Partido Socialista Obrero Español (PSOE), Partido Popular (PP), Ciudadanos, Unidas Podemos (coalition of Podemos and Izquierda Unida) and Vox. The General Elections were held on April 28 and November 10., We would like to thank Exponentia CIO Juan Besari for providing the appropriate hardware to carry out the Facebook Ad extraction processes.

The dataset contains the input data that has been entered into the mathematical model to develop the case study. The data is provided by the company and the values have been structured according to the indices defined in the model. Input data details have been added to make the model replicable.

This dataset contains the experimental data generated during the development and evaluation of a methodology for applying a commercially available water-based vinyl paint as a radon mitigation barrier for indoor spaces. It includes the raw radon concentration measurements recorded in the source and receiver chambers during diffusion tests performed on samples coated with different numbers of paint coats and paint coat thicknesses. The dataset also includes experimental results obtained using a commercially available anti-radon paint as a reference material for comparison, together with the main specifications of the experimental set-up and the thickness measurements of the paint coats. These experimental data were used to determine the radon concentration reduction and the radon diffusion coefficient following a modified version of the ISO/TS 11665-13:2017 standard, as reported in the associated publication. The experimental data were generated using a two-chamber radon diffusion test following a modified version of ISO/TS 11665-13:2017. The experimental set-up consisted of two sealed AISI 316L stainless steel chambers separated by the test sample. A sealed pitchblende stone (1.469 kBq) was placed inside the source chamber, while the receiver chamber collected the radon that permeated through the sample. Radon concentration in both chambers was continuously monitored using two Durridge RAD7 detectors connected in closed-loop circuits. Temperature and relative humidity were monitored throughout the experiments. Each test lasted 48 hours, during which radon concentrations in the source and receiver chambers were recorded at 30-minute intervals. These raw experimental data were subsequently used to calculate the radon concentration reduction and the radon diffusion coefficient following the procedure described in ISO/TS 11665-13:2017. The dataset also includes the main specifications of the experimental set-up, such as chamber characteristics, radon source activity and test area. The thickness of each paint coat was determined from eight measurements taken at different locations on the coated sample, from which the mean thickness and the standard deviation were calculated. The radon concentration data recorded by the RAD7 detectors at 30-minute intervals were exported. For each experiment, the dataset includes the test date and the radon concentration values measured in the source and receiver chambers throughout the 48-hour test. No additional processing, filtering or normalization was applied to the concentration data before their inclusion in the dataset. The experimental set-up specifications were compiled from the laboratory protocol used during the diffusion tests. For the thickness data, the reported mean thickness and standard deviation were calculated from eight thickness measurements taken at different locations on each coated sample.

Concerns about the health of the planet have grown dramatically, and the dyeing sector of the textile industry is one of the most polluting of all industries. Nanoclays can clean dyeing wastewater using their adsorption capacities. In this study, as a new finding, it was possible to analyze and quantify the amount of metal ions substituted by anionic dyes when adsorbed, and to determine the optimal amount of nanoclay to be used to adsorb all the dye. The tests demonstrated the specific amount of nanoclay that must be used and how to optimize the subsequent processes of separation and processing of the nanoclay. Hydrotalcite was used as the adsorbent material. Direct dyes were used in this research. X-ray diffraction (XRD) patterns allowed the shape recovery of the hydrotalcite to be checked and confirmed the adsorption of the dyes. An FTIR analysis was used to check the presence of characteristic groups of the dyes in the resulting hybrids. The thermo-gravimetric (TGA) tests corroborated the dye adsorption and the thermal fastness improvement. Total solar reflectance (TSR) showed increased radiation protection for UV-VIS-NIR. Through the work carried out, it has been possible to establish the maximum adsorption point of hydrotalcite.

Computational 3D models of human atria and torso with encoded anatomical and functional heterogeneity. The finite element model of the atria is a multi-layer mesh with a homogeneous wall thickness between 600 and 900 μm (754.893 nodes and 515.010 elements), built with linear hexahedral elements and with regular spatial resolution of 300 µm. The model consists of: 21 regions with 53 sub-divisions representing the detailed description of fibre orientation; electrophysiological heterogeneity represented by 8 cellular models with differences in the action potential properties; and conduction velocities and anisotropy ratios tuned to each atrial region. The torso was modelled using a dataset obtained from the online open repository at the Centre for Integrative Biomedical Computing (CBIC) from University of Utah. The torso model has 190.804 nodes and 1.149.531 tetrahedral elements with a spatial resolution of 0.6 mm. It has 6 different regions: lungs, bones, liver, ventricle, blood pools, and flesh.

The data were use to study the degradation of Methylparaben using WO3 Nanostructures. WO3 nanostructures were synthesized with different complexing agents (0.05 M H2O2 and 0.1 M citric acid) and annealing conditions (400 _C, 500 _C and 600 _C) to obtain optimal WO3 nanostructures to use them as a photoanode in the photoelectrochemical (PEC) degradation of an endocrine disruptor chemical. X-ray photoelectron spectroscopy was performed to provide information of the electronic states of the nanostructures. The crystallinity of the samples was observed by a confocal Raman laser microscope and X-ray diffraction. Furthermore, photoelectrochemical measurements (photostability, photoelectrochemical impedance spectroscopy, Mott–Schottky and water-splitting test) were also performed using a solar simulator with AM 1.5 conditions at 100 mW_cm-2. Once the optimal nanostructure was obtained, the PEC degradation of methylparaben was carried out. It was followed by ultra-high-performance liquid chromatography and mass spectrometry, which allowed to obtain the concentration of the contaminant during degradation and the identification of degradation intermediates.

This dataset contains the raw data of the measurements presented in the paper: "A Computational Efficient Nyquist Shaping Approach for Short-Reach Optical Communications" (https://doi.org/10.1109/JLT.2019.2961506). - Medidas_BER_EVM.xls: contains BER and EVM measurements made for different types of modulations for both the HC-SCM modulator and the OVS-SCM, varying the following parameters: oversampling factor, transmitter filter span, rolloff factor, receiver filter span, receiver equalizer order, pre-emphasis filter (in transmission) - Medidas_Potencia.xls: contains BER and EVM values varying the received power for HC-SCM and OVS-SCM modulations; for all QAM modulations under study.

[EN] The H2020 project “Green Cities for Climate and Water Resilience, Sustainable Economic Growth, Healthy Citizens and Environments" (GROW GREEN, Grant Agreement: 730283), developed green infrastructure pilots in: Manchester, Valencia and Wroclaw. The monitoring framework supported the pilot analysis and its impact assessment through the development of core Key Performance Indicators (KPIs) through all pilots. The historical evolution of these core KPIs are available on the Grow-Green Open Data platform sharing the software architecture for the smart city platform of Valencia City. It is an implementation of Telefónica’s Thinking Cities platform, which is based on the FIWARE standards and interfaces. All monitoring data are included on this dataset grouped on the core KPIs structure., This research was co-funded by the European Commission through the H2020 project “Green Cities for Climate and Water Resilience, Sustainable Economic Growth, Healthy Citizens and Environments (GROW GREEN)” Grant Agreement: 730283.