BUSCADOR RECOLECTA

The present dataset is the database and image database used to train and test the Convolutional Neural Network models of the scientific paper: Deep Learning algorithm, based on convolutional neural networks, for electrical equivalent electrical circuit recommendation for Electrochemical Impedance Spectroscopy

[EN] Considering the concerns for emissions reduction in the maritime sector, the present paper evaluates, through modeling and simulation, oxy-fuel combustion in a two-stroke ship engine (2SE) and the best production system configuration to obtain the required oxygen (O2). An initial model of a ship engine is calibrated with the engine manufacturer's data and then adapted to work with O2 as the oxidant to eliminate nitrogen oxide (NOx) emissions and with exhaust gas recirculation (EGR) to control the in-cylinder combustion temperature. Mixed Ionic-Electronic Conducting (MIEC) membranes produce the necessary O2 from the ambient air, which is heated up and pressurized by a heat exchanger and turbocharging coupled system to provide the air conditions required for the proper operation of the MIEC. Several layouts of this system are evaluated for the full load engine operating point to find the optimum O2 production system configuration. Results reveal that the engine operating under oxy-fuel combustion conditions avoids NOx emissions at the expense of higher brake-specific fuel consumption (BSFC) to obtain the original brake torque, and also expels a stream composed exclusively of CO2 and H2O, which facilitates the separation of CO2 from exhaust gases., This research has been partially supported by Grant CIPROM/2021/061 funded by Generalitat Valenciana. Also partially supported by Grant PID2021-123351OB-I00 funded by MCIN/AEI/10.13039/501100011033 and, as appropriate, by ERDF A way of making Europe . And also partially funded by Programa de Ayudas de Investigación y Desarrollo PAID-01-22, from Universitat Politècnica de València (UPV) which granted the Rossana s pre-doctoral contract.

[EN] Heterogeneous photocatalysts have attracted significant interest over the last few years. In this sense, improved photocatalytic properties for SiO2@TiO2 materials have been correlated with higher semiconductor's specific surface area and adsorption capability. However, the reported TiO2 shell optimizations did not consider the percentage of the photo-excited electron-hole (e¿-h+) pairs occurring in the inaccessible surface of the TiO2 shell. The present study aimed to find the best TiO2 shell thickness for the optimal harvest of light. For this purpose, the sol¿gel method was modified by applying a precise humid airflow to get a uniform deposition of titania on the surface of the SiO2 particles. As a result, photocatalysts with a robust and homogeneous TiO2 shell of different thicknesses (from 14 to 42 nm) with well-defined particle size for TiO2 crystals (ca. 12 nm) were obtained. The SiO2@TiO2 materials were extensively characterized. Finally, their photocatalytic activity was evaluated against methylene blue under irradiation by UVA light. Analysis of the results revealed that the most efficient photocatalyst has a TiO2 shell thickness of ca. 30 nm. Emission and photocurrent studies also agreed with the photocatalytic results suggesting a reduced e¿-h+ recombination rate. Thereby, for the first time, the relevance of shell thickness in supported photocatalysts has been demonstrated., The authors would like to acknowledge the Spanish Ministry of Science, Innovation, and Universities (PID2019-110441RB-C33 financed by MCIN/AEI/10.13039/501100011033 and TED2021-131952B-I00 financed by MCIN/AEI/10.13039/501100011033 and by European Union NextGenerationEU/PRTR). O. Cabezuelo and A. Diego-Lopez are indebted to the Universitat Politecnica de Valencia for the corresponding Predoctoral FPI fellowship (FPI-UPV/Subprograma 1). The authors would like to acknowledge the Servei de Microscopia Electronica from the Universitat Politecnica de Valencia (UPV) for the support on the composite characterization and sample preparation.Funding for the open access charge provided by CRUE-Universitat Politecnica de Valencia is acknowledged.r Funding for the open access charge provided by CRUE-Universitat Politècnica de València is acknowledged.

[EN] A "high-fat, high-energy diet" is commonly recommended for children with cystic fibrosis (CF), leading to negative consequences on dietary patterns that could contribute to altered colonic microbiota. The aim of this study was to assess dietary intake and to identify possible associations with the composition of faecal microbiota in a cohort of children with CF. A cross-sectional observational study was conducted, including a 3-day food record simultaneously with the collection of faecal samples. The results showed a high fat intake (43.9% of total energy intake) and a mean dietary fibre intake of 10.6 g/day. The faecal microbiota was characterised at the phylum level as 54.5% Firmicutes and revealed an altered proportion between Proteobacteria (32%) and Bacteroidota (2.2%). Significant associations were found, including a negative association between protein, meat, and fish intake and Bifidobacterium, a positive association between lipids and Escherichia/Shigella and Streptococcus, a negative association between carbohydrates and Veillonella and Klebsiella, and a positive association between total dietary fibre and Bacteroides and Roseburia. The results reveal that a "high-fat, high-energy" diet does not satisfy dietary fibre intake from healthy food sources in children with CF. Further interventional studies are encouraged to explore the potential of shifting to a high-fibre or standard healthy diet to improve colonic microbiota., The authors would like to thank the Universitat Politècnica de València for the pre-doctoral
contract from Vicerrectorado de Investigación given to Jazmín Viteri Echeverría (PAID-01-22). This
project was funded with the First Project Grant (PAID-06-22) and Postdoctoral Research Fostering Grant (PAIDPD-22) from Vicerrectorado de Investigación (Universitat Politècnica de València)
awarded to Andrea Asensio-Grau.

[EN] A new optimized photocatalyst for wastewater remediation at neutral pH has been developed and fully characterized. The catalyst features microparticles of SiO2 as a supporting substrate and a uniform shell of WO3 nanoparticles externally decorated with Fe3O4 nanocrystals. The photocatalytic activity of SiO2@WO3@Fe3O4 was evaluated and compared to its SiO2@WO3 counterpart on the photodegradation of methylene blue (MB) under visible light, with and without H2O2. Best results were obtained for SiO2@WO3@Fe3O4 in the presence of H2O2, whose potential for wastewater remediation was further evaluated on the photodegradation and mineralization of a contaminant of emerging concern such as diclofenac (DCF). Furthermore, a photocatalytic mechanism was proposed based on the performed electron paramagnetic resonance (EPR) experiments, which provided evidence for the intermediates generated in all the involved photocatalytic processes. Hence it was proven that .OH is the species responsible for the photocatalyzed oxidation of MB and DCF. The generation of .OH is boosted by a synergistic effect between Fe3O4 and WO3 in the presence of light and H2O2., The authors would like to acknowledge the Spanish Ministry of Science, Innovation, and Universities (PID2019-110441RB-C33 financed by MCIN/AEI/10.13039/501100011033 and TED2021-131952B-I00 financed by MCIN/AEI/10.13039/501100011033 and by European Union NextGenerationEU/PRTR) . A. Diego-Lopez and O. Cabezuelo are indebted to the Universitat Politecnica de Valencia for the Predoctoral FPI fellowship (FPI-UPV/Subprograma 1) . The authors would like to acknowledge the Servei de Microscopia Electronica from the Universitat Politecnica de Valencia (UPV) for the support on the composite characterization and sample preparation.

[EN] Third-generation (3G) rice pellets were obtained using rice flour (RF) and rice grits (RG), raw materials of similar compositions but different particle sizes. The samples were mixed with water to 25% moisture and extruded using a laboratory single-screw extruder (Kompakt KE 19/25 extruder) and three compression ratios (1:1, 2:1, and 3:1). The pellets were expanded using a microwave oven subjected to 1000 W/g power. After evaluating the expansion kinetics and the sectional expansion index (SEI), it was observed that the 3:1 compression ratio allowed for greater expansion, while the particle difference showed no significant difference (p > 0.05) in the SEI., This research was funded by the FPI Ph.D. contract granted by Universitat Politècnica de València Subprograma 1 (PAID-01-22).

[EN] The present research explores an innovative approach to objectively assessing urban streets attributes using 3D point clouds and Geographic Information Systems (GIS). Urban streets are vital
components of cities, playing a significant role in the lives of their residents. Usually, the evaluation of some of their physical attributes has been subjective, but this study leverages 3D point clouds and digital terrain models (DTM) to provide a more objective perspective. This article undertakes a microurban analysis of basic physical characteristics (slope, width, and human scale) of a representative street in the historic centre of Valencia (Spain), utilizing 3D laser-scanned point clouds and GIS tools. Applying the proposed methodology, thematic maps were generated, facilitating the objective identification of areas with physical attributes more conducive to suitable pedestrian dynamics.
This approach provides a comprehensive understanding of urban street attributes, emphasizing the importance of addressing their assessment through advanced digital technologies. Moreover, this versatile methodology has diverse applications, contributing to social sustainability by enhancing the quality of urban streets and open spaces., This research was funded by the project "Analysis and Development of HBIM Integration into GIS for Creating a Cultural Heritage Tourism Planning Protocol" (ref. PID2020-119088RB-I00), funded by the Ministry of Science and Innovation, Government of Spain, and the "Programa de Ayudas de Investigacion y Desarrollo (PAID-01-22)" by the Universitat Politecnica de Valencia. The APC will be funded by Universitat Politecnica de Valencia.