BUSCADOR RECOLECTA

[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.

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] Buildings have become a key source of greenhouse gas (GHG) emissions due to the consumption of primary energy, especially when used to achieve thermal comfort conditions. In addition, buildings play a key role for adapting societies to climate change by achieving more energy efficiency. Therefore, buildings have become a key sector to tackle climate change at the local level. However, public decision-makers do not have tools with enough spatial resolution to prioritise and focus the available resources and efforts in an efficient manner. The objective of the research is to develop an innovative methodology based on a geographic information system (GIS) for mapping primary energy consumption and GHG emissions in buildings in cities according to energy efficiency certificates

Mesenchymal stem cells (MSCs) osteogenic commitment before injection enhances bone regen-eration therapy results. Piezoelectric stimulation may be an effective cue to promote MSC pre-differentiation, and poly(vinylidene) fluoride (PVDF) cell culture supports, when combined with CoFe2O4 (CFO), offer a wireless in vitro stimulation strategy. Under an external magnetic field, CFO shift and magnetostriction deform the polymer matrix varying the polymer surface charge due to the piezoelectric effect. To test the effect of piezoelectric stimulation on MSCs, our approach is based on a gelatin hydrogel with embedded MSCs and PVDF-CFO electroactive mi-crospheres. Microspheres were produced by electrospray technique, favouring CFO incorpora-tion, crystallisation in -phase (85 %) and a crystallinity degree of around 55 %. The absence of cytotoxicity of the 3D construct was confirmed 24 hours after cell encapsulation. Cells were via-ble, evenly distributed in the hydrogel matrix and surrounded by microspheres, allowing local stimulation. Hydrogels were stimulated using a magnetic bioreactor, and no significant changes were observed in MSCs proliferation in short or long term. Nevertheless, piezoelectric stimula-tion upregulated RUNX2 expression after 7 days, indicating the activation of the osteogenic dif-ferentiation pathway. These results open the door for optimising a stimulation protocol allow-ing the application of the magnetically activated 3D electroactive cell culture support for MSCs pre-differentiation before transplantation.

This dataset includes the raw data used to carry out a study related to the analysis of the DORA Declaration on Twitter. The dataset includes the tweets collected from the Twitter Academic API (comprising three collections: tweets published by DORA, tweets mentioning DORA, and tweets including a DORA-related hashtag), supplementary material (including extra tables and figures), and the script used to collect data from Twitch API.

[EN] The integration of autonomous vehicles (AVs) into road transport requires robust ex-perimental tools to analyze human–machine interaction, particularly under conditions of system disengagement. This study presents the development and validation of the EVACH autonomous driving simulator, designed to reproduce SAE Level 2 and Level 3 driving modes in rural road scenarios. The simulator was customized through hardware and software developments, including a dedicated data acquisition system to ensure accurate detection of braking, steering, and other critical control inputs. Calibration tests demonstrated high reliability, with minor errors in brake and steering control meas-urements, consistent with values observed in production vehicles. To validate the virtual driving rural environment, comparative experiments were conducted between natu-ralistic road tests and simulator-based autonomous driving. Results showed that average speeds in simulation closely matched those recorded on real roads, with differences of less than 1 km/h and significantly lower variability. These findings confirm that the EVACH simulator provides a stable and faithful reproduction of autonomous driving conditions. The platform represents a validated and versatile tool for evaluating driver workload, takeover performance, and human–machine interaction, offering valuable support for current and future research on the safe deployment of automated vehicles.

This dataset includes supplementary material (code, raw data) created and collected to support a study on the visibility of Spanish Institutional Repositories on Google Search results.

This dataset contains the raw data of the measurements presented in the paper "Hardware Architecture of a QAM Receiver for Short-Range Optical Communications" (https://doi.org/10.1109/JLT.2022.3217357). Data presents the BER and EVM measurements made by changing the optical power transmitted for the proposed modulator.

Ezetimibe inhibits cholesterol uptake by modulation of intestinal sterol absorption. Currently, although some studies have shown alterations in ezetimibe levels caused by alterations in the ABCG5, ABCG8, NPC1L1 or UGT1A1 genes, there are no pharmacogenetic guidelines to confirm these biomarkers. The aim of this work was to evaluate the effect of 49 variants in 22 pharmacogenes related to metabolism and transport. A total of 96 healthy volunteers from four bioequivalence clinical trials of ezetimibe as monotherapy or in combination with simvastatin were studied. Blood samples were extracted for unconjugated ezetimibe plasma quantification and genotyping. No association of metabolizing enzyme variants with ezetimibe pharmacokinetic parameters was found. The results show some trends in the univariate analysis for ABCB1 rs2032582 or ABCC2 rs2273697 and Cmax (p univariate (puv) = 0.056 and 0.087, respectively), which finally reach significance in the multivariate analysis (p multivariate (pmv) = 0.049 and 0.048, respectively). Nevertheless, these results need to be validated in future studies.

This study compares four approaches previously proposed for diagnosing celiac disease in individuals on a gluten-free diet: IL-2 serum levels, gut-homing CD8+ T cells in blood, %TCRgamma delta+ intraepithelial lymphocytes, and UBE2L3 gene expression in blood.