Low-frequency oscillations analysis in ac railway networks using eigenmode identification

IEEE Energy Conversion Congress and Exposition, ECCE (13th. 2021. Virtual

Comparative Study of Atmospheric Water-Soluble Organic Aerosols Composition in Contrasting Suburban Environments in the Iberian Peninsula Coast

This is an accepted version of the published document.[Abstract] This study investigates the structural composition and major sources of water-soluble organic matter (WSOM) from PM2.5 collected, in parallel, during summer and winter, in two contrasting suburban sites at Iberian Peninsula Coast: Aveiro (Portugal) and Coruña (Spain). PM10 samples were also collected at Coruña for comparison. Ambient concentrations of PM2.5, total nitrogen (TN), and WSOM were higher in Aveiro than in Coruña, with the highest levels found in winter at both locations. In Coruña, concentrations of PM10, TN, and WSOM were higher than those from PM2.5. Regardless of the season, stable isotopic δ13C and δ15N in PM2.5 suggested important contributions of anthropogenic fresh organic aerosols (OAs) at Aveiro. In Coruña, δ13C and δ15N of PM2.5 and PM10 suggests decreased anthropogenic input during summer. Although excitation-emission fluorescence profiles were similar for all WSOM samples, multi-dimensional nuclear magnetic resonance (NMR) spectroscopy confirmed differences in their structural composition, reflecting differences in aging processes and/or local sources between the two locations. In PM2.5 WSOM in Aveiro, the relative distribution of non-exchangeable proton functional groups was in the order: HC (40–43%) > HCC (31–39%) > HCO (12–15%) > Ar-H (5.0–13%). However, in PM2.5 and PM10 WSOM in Coruña, the relative contribution of HCO groups (24–30% and 23–29%, respectively) equals and/or surpasses that of HCC (25–26% and 25–29%, respectively), being also higher than those of Aveiro. In both locations, the highest aromatic contents were observed during winter due to biomass burning emissions. The structural composition of PM2.5 and PM10 WSOM in Coruña is dominated by oxygenated aliphatic compounds, reflecting the contribution of secondary OAs from biogenic, soil dust, and minor influence of anthropogenic emissions. In contrast, the composition of PM2.5 WSOM in Aveiro appears to be significantly impacted by fresh and secondary anthropogenic OAs. Marine and biomass burning OAs are important contributors, common to both sites.Thanks are due for the financial support to: CESAM (UID/AMB/50017 - POCI-01-0145-FEDER-007638); Organic Chemistry Research Unit (QOPNA, UID/QUI/00062/2013); FCT/MEC through national funds, Portuguese NMR network, and “Programa Operacional Potencial Humano - POPH”; FEDER within the PT2020 Partnership Agreement; and Compete 2020. FCT/MEC is also acknowledged for an Investigator FCT Contract (IF/00798/2015). This work was also supported by Xunta de Galicia (Programa de Consolidación y Estructuración de Unidades de Investigación Competitivas Refs. GRC2013-047 and ED431C 2017/28). João T.V. Matos and P. Esperón are greatly acknowledged for their collaborationPortugal. Fundação para a Ciência e a Tecnologia; UID/AMB/50017Portugal. Fundação para a Ciência e a Tecnologia; UID/QUI/00062/2013Portugal. Fundação para a Ciência e a Tecnologia; IF/00798/2015Xunta de Galicia; GRC2013-047Xunta de Galicia; ED431C 2017/2

Novel Modeling of Combinatorial miRNA Targeting Identifies SNP with Potential Role in Bone Density

MicroRNAs (miRNAs) are post-transcriptional regulators that bind to their target mRNAs through base complementarity. Predicting miRNA targets is a challenging task and various studies showed that existing algorithms suffer from high number of false predictions and low to moderate overlap in their predictions. Until recently, very few algorithms considered the dynamic nature of the interactions, including the effect of less specific interactions, the miRNA expression level, and the effect of combinatorial miRNA binding. Addressing these issues can result in a more accurate miRNA:mRNA modeling with many applications, including efficient miRNA-related SNP evaluation. We present a novel thermodynamic model based on the Fermi-Dirac equation that incorporates miRNA expression in the prediction of target occupancy and we show that it improves the performance of two popular single miRNA target finders. Modeling combinatorial miRNA targeting is a natural extension of this model. Two other algorithms show improved prediction efficiency when combinatorial binding models were considered. ComiR (Combinatorial miRNA targeting), a novel algorithm we developed, incorporates the improved predictions of the four target finders into a single probabilistic score using ensemble learning. Combining target scores of multiple miRNAs using ComiR improves predictions over the naïve method for target combination. ComiR scoring scheme can be used for identification of SNPs affecting miRNA binding. As proof of principle, ComiR identified rs17737058 as disruptive to the miR-488-5p:NCOA1 interaction, which we confirmed in vitro. We also found rs17737058 to be significantly associated with decreased bone mineral density (BMD) in two independent cohorts indicating that the miR-488-5p/NCOA1 regulatory axis is likely critical in maintaining BMD in women. With increasing availability of comprehensive high-throughput datasets from patients ComiR is expected to become an essential tool for miRNA-related studies. © 2012 Coronnello et al

Remagnetization strategies for induction machines operating with reduced flux levels

International Conference on Electrical Machines (ICEM) (2022. Valencia, Spain)This work was supported in part by Regional Government of Asturias (Spain) under project AYUD/2021/50988

Control strategies for induction motors in railway traction applications

Funding: This research was funded by the European Commission H2020 under grant UE-18-POWER2POWER-826417; The Spanish Ministry of Science, Innovation and Universities under grant MCIU-19-PCI2019-103490; and by the Government of Asturias under grant IDI/2018/000188 and FEDER funds

Design of a scaled roller-rig test bench for anti-slip control development for railway traction

This work was supported by the Government of the Principality of Asturias under Project AYUD/2021/50988

Power-hardware-in-the-loop emulation of the low-frequency oscillation phenomenon in AC railway networks

European Commission [UE-18-POWER2POWER-826417]; Spanish Ministry of Science, Innovation and Universities [MCIU-19-PCI2019-103490]; Government of Asturias [AYUD/2021/50988

Interlaboratory Comparison Reveals State of the Art in Microplastic Detection and Quantification Methods

\ua9 2025 The Authors. Published by American Chemical Society. In this study, we investigate the current accuracy of widely used microplastic (MP) detection methods through an interlaboratory comparison (ILC) involving ISO-approved techniques. The ILC was organized under the prestandardization platform of VAMAS (Versailles Project on Advanced Materials and Standards) and gathered a large number (84) of analytical laboratories across the globe. The aim of this ILC was (i) to test and to compare two thermo-analytical and three spectroscopical methods with respect to their suitability to identify and quantify microplastics in a water-soluble matrix and (ii) to test the suitability of the microplastic test materials to be used in ILCs. Two reference materials (RMs), polyethylene terephthalate (PET) and polyethylene (PE) as powders with rough size ranges between 10 and 200 μm, were used to press tablets for the ILC. The following parameters had to be assessed: polymer identity, mass fraction, particle number concentration, and particle size distribution. The reproducibility, SR, in thermo-analytical experiments ranged from 62%-117% (for PE) and 45.9%-62% (for PET). In spectroscopical experiments, the SR varied between 121% and 129% (for PE) and 64% and 70% (for PET). Tablet dissolution turned out to be a very challenging step and should be optimized. Based on the knowledge gained, development of guidance for improved tablet filtration is in progress. Further, in this study, we discuss the main sources of uncertainties that need to be considered and minimized for preparation of standardized protocols for future measurements with higher accuracy

Quantification of miRNA-mRNA Interactions

miRNAs are small RNA molecules (′ 22nt) that interact with their corresponding target mRNAs inhibiting the translation of the mRNA into proteins and cleaving the target mRNA. This second effect diminishes the overall expression of the target mRNA. Several miRNA-mRNA relationship databases have been deployed, most of them based on sequence complementarities. However, the number of false positives in these databases is large and they do not overlap completely. Recently, it has been proposed to combine expression measurement from both miRNA and mRNA and sequence based predictions to achieve more accurate relationships. In our work, we use LASSO regression with non-positive constraints to integrate both sources of information. LASSO enforces the sparseness of the solution and the non-positive constraints restrict the search of miRNA targets to those with down-regulation effects on the mRNA expression. We named this method TaLasso (miRNA-Target LASSO)