Transmission of light through periodic arrays of square holes : from a metallic wire mesh to an array of tiny holes

A complete landscape is presented of the electromagnetic coupling between square holes forming a two-dimensional periodic array in a metallic film. By combining both experimental and theoretical results along with a first-principles Fano model, we study the crossover between the physics of metallic wire meshes (when holes occupy most of the unit cell) and the phenomenon of extraordinary optical transmission, which appears when the size of the holes is very small in comparison with the period of the array

Modelling of batteries for application in light electric urban vehicles

[EN] In this paper a dynamic model of a battery that lets simulate different types of batteries in light electric urban vehicles applications is proposed. The model is directly parameterizable from discharging experimental curves in test facilities. It properly fits to the particular behaviour observed in the charging/discharging curves in LiFePo 4 batteries. For the calibration of the proposed model experimental data from an experimental facility have been used and validation results are presented. The model is implemented in the object oriented modelling language Modelica reusing classes from the Modelica Standard Library. The calibration and the calibration has been performed with Dymola modelling tool.[ES] En este artículo se propone un modelo dinámico de batería que permite simular el comportamiento de distintos tipos de baterías para su aplicación en vehículos eléctricos urbanos ligeros. El modelo es fácilmente parametrizable a partir de las curvas de descarga experimentales del equipo real y se ajusta adecuadamente al comportamiento particular de la curva de carga/descarga de las baterías de Litio-Ferrofosfato (LiFePo4). Se han utilizado los datos obtenidos sobre una instalación experimental para la calibración del modelo propuesto y se presentan resultados de la validación del mismo. El modelo se ha implementado en el lenguaje de modelado orientado a objetos Modelica reutilizando clases de su librería estándar Modelica Standard Library. La calibración y validación se ha realizado con la herramienta de modelado Dymola.Al personal técnico del Grupo de Automática, Robótica y Mecatrónica de la Universidad de Almería (TEP-197) a cargo de la microrred experimental, por su inestimable ayuda en la obtención de los registros experimentales utilizados. El presente trabajo ha sido parcialmente financiado por el Proyecto DPI2017-85007-R del Plan Nacional R+D+i del Ministerio de Ciencia, Innovación y Universidades del Reino de España y por el Fondo Europeo de Desarrollo Regional (FEDER).Gómez, F.; Yebra, L.; Giménez, A.; Torres-Moreno, J. (2019). Modelado de baterías para aplicación en vehículos urbanos eléctricos ligeros. Revista Iberoamericana de Automática e Informática. 16(4):459-466. https://doi.org/10.4995/riai.2019.10609SWORD459466164A123 Systems, 2012. Nanophosphate High Power Lithium Ion Cell ANR26650M1-B.Ahmed, M., 2016. Modeling Lithium-ion Battery Chargers in PLECS R . Tech.rep.Ansean, D., Gonzalez, M., Viera, J. C., Alvarez, J. C., Blanco, C., García, V. M., 2013. Evaluation of LiFePO4batteries for Electric Vehicle applications. In: 2013 Int. Conf. New Concepts Smart Cities Foster. Public Priv. Alliances. IEEE, Gijon, Spain, p. 8. URL: https://ieeexplore.ieee.org/document/6708211 http://doi.org/10.1109/SmartMILE.2013.6708211Berecibar, M., Garmendia, M., Gandiaga, I., Crego, J., Villarreal, I., 2016. State of health estimation algorithm of LiFePO4battery packs based on differential voltage curves for battery management system application. Energy 103, 784-796. https://doi.org/10.1016/j.energy.2016.02.163Brondani, M. D. F., Sausen, A. T. Z. R., Sausen, P. S., Binelo, M. O., 2017. Battery Model Parameters Estimation Using Simulated Annealing. TEMA(Sao Carlos) 18 (1), 127. URL: https://tema.sbmac.org.br/tema/article/view/1003 https://doi.org/10.5540/tema.2017.018.01.0127Dempsey, M., Gäfvert, M., Harman, P., Kral, C., Otter, M., Treffinger, P., 2006. Coordinated automotive libraries for vehicle system modelling. In: 5thModel. Conf. 2006. The Modelica Association, Vienna, Austria, pp. 33-41.URL: https://www.modelica.org/events/modelica2006/Proceedings/sessions/Session1b2.pdfDizqah,A.M.,Busawon,K.,Fritzson,P.,2012.ACAUSALMODELINGAND SIMULATION OF THE STANDALONE SOLAR POWER SYSTEMS AS HYBRID DAEs. In: 53rd Int. Conf. Scand. Simul. Soc. pp. 1-7.Dymola - Dynamic Modeling Laboratory - User Manual, 2018. Dymola. URL: http://www.dymola.comElmqvist, H., Olsson, H., Mattsson, S. E., Brück, D., Schweiger, C., Joos, D., Otter, M., 2005. Optimization for design and parameter estimation. In: In4th International Modelica Conference.Fritzson, P., 2015. Principles of Object-Oriented Modeling and Simulation with Modelica 3.3: A Cyber-Physical Approach, 2nd Edition. Wiley. https://doi.org/10.1002/9781118989166Gómez, F.J., Yebra, L.J., Giménez, A., 2018. Modelling a Smart-Grid for a Solar Powered Electric Vehicle. In: Technische Universität Wien (Ed.), 9th Vienna Conf. Math. Model. Vol. 55. ARGESIM Publisher, Vienna, Vienna,Austria, pp. 5-6. URL: https://www.asim-gi.org/fileadmin/user_upload_argesim/ARGESIM_Publications_OA/MATHMOD_Publications_OA/MATHMOD_2018_AR55/articles/a55113.arep.55.pdf DOI: 10.11128/arep.55.a55113. https://doi.org/10.11128/arep.55.a55113Hausmann, A., Depcik, C., 2013. Expanding the Peukert equation for battery capacity modeling through inclusion of a temperature dependency. J. Power Sources 235, 148-158. URL: https://www.sciencedirect.com/science/article/pii/S0378775313002322. https://doi.org/10.1016/j.jpowsour.2013.01.174Kroeze, R. C., Krein, P. T., 2008. Electrical battery model for use in dynamic electric vehicle simulations. In: 2008 IEEE Power Electron. Spec. Conf. IEEE, Rhodes, Greece, pp. 1336-1342. URL: http://ieeexplore.ieee.org/document/4592119/. https://doi.org/10.1109/PESC.2008.4592119NREL, 2015. Technoeconomic Modeling of Battery Energy Storage in SAM. Tech. Rep.September.URL: http://www.nrel.gov/docs/fy15osti/64641.pdfOlsson, H., Mattsson, S. E., Hilding Elmqvist, 2006. Calibration of Static Models using Dymola. In: Proc. 5th Int. Model. Conf. The Modelica Association (http://www.modelica.org/) and Arsenal Research (http://www.arsenal.ac.at/), Vienna, Austria, pp. 615-620.URL: https://modelica.org/events/modelica2006/Proceedings/sessions/Session6a3.pdfPetzl, M., Danzer, M. A., 2013. Advancements in OCV measurement and analysis for lithium-ion batteries. IEEE Trans. Energy Convers. 28 (3), 675-681. https://doi.org/10.1109/TEC.2013.2259490Seaman, A., Dao, T.-S., McPhee, J., jun 2014. A survey of mathematics-based equivalent-circuit and electrochemical battery models for hybrid and electric vehicle simulation. J. Power Sources 256, 410-423. URL: https://www.sciencedirect.com/science/article/pii/S0378775314000810. https://doi.org/10.1016/j.jpowsour.2014.01.057Torres-Moreno, J. L., Gimenez-Fernandez, A., Perez-Garcia, M., Rodriguez, F., 2018. Energy management strategy for micro-grids with pv-battery systemsand electric vehicles. Energies 11 (3). URL: http://www.mdpi.com/1996-1073/11/3/522 DOI: 10.3390/en11030522. https://doi.org/10.3390/en11030522Tremblay, O., Dessaint, L., 2009. Experimental validation of a battery dynamic model for EV applications. World Electr. Veh. J. 3, 1-10. https://doi.org/10.3390/wevj3020289TÜV SÜD Certification and Testing (China) Co. Ltd., 2016. Test Report IEC-62619A BYD B-Box. Tech. rep., TÜV SÜD Certification and Testing (China) Co. Ltd., Shenzhen (China). URL: https://www1.fenecon.de/web/content/34638van Baten, J., 2017. ScanIt. URL: https://www.amsterchem.com/scanit.htmlWang, W., Chung, H. S. H., Zhang, J., 2014. Near-real-time parameter estimation of an electrical battery model with multiple time constants and SoCdependent capacitance. 2014 IEEE Energy Convers. Congr. Expo. ECCE 2014 29 (11), 3977-3984. URL: https://ieeexplore.ieee.org/document/6714474. https://doi.org/10.1109/ECCE.2014.6953942Zambrano Bigiarini, M., 2017. hydroGOF: Goodness-of-fit functions for comparison of simulated and observed hydrological time series. URL: http://hzambran.github.io/hydroGOF/Zhang, W.-J., mar 2011. Structure and performance of LiFePO4 cathode materials: A review. J. Power Sources 196 (6), 2962-2970. URL: https://www.sciencedirect.com/science/article/pii/S037877531002104X{#}bib0005. https://doi.org/10.1016/j.jpowsour.2010.11.11

Gelsilox: a novel strategy for the study of dynamics alteration in the thiol redox proteome

Comunicaciones a congreso

Two-step ATP-driven opening of cohesin head

The cohesin ring is a protein complex composed of four core subunits: Smc1A, Smc3, Rad21 and Stag1/2. It is involved in chromosome segregation, DNA repair, chromatin organization and transcription regulation. Opening of the ring occurs at the "head" structure, formed of the ATPase domains of Smc1A and Smc3 and Rad21. We investigate the mechanisms of the cohesin ring opening using techniques of free molecular dynamics (MD), steered MD and quantum mechanics/molecular mechanics MD (QM/MM MD). The study allows the thorough analysis of the opening events at the atomic scale: I) ATP hydrolysis at the Smc1A site, evaluating the role of the carboxy-terminal domain of Rad21 in the process; ii) the activation of the Smc3 site potentially mediated by the movement of specific amino acids; and iii) opening of the head domains after the two ATP hydrolysis events. Our study suggests that the cohesin ring opening is triggered by a sequential activation of the ATP sites in which ATP hydrolysis at the Smc1A site induces ATPase activity at the Smc3 site. Our analysis also provides an explanation for the effect of pathogenic variants related to cohesinopathies and cancer

Performance evaluation of a multiscale modelling system applied to particulate matter dispersion in a real traffic hot spot in Madrid (Spain)

Urban air pollution is one of the most important environmental problems nowadays. Understanding urban pollution is rather challenging due to different factors that produce a strongly heterogeneous pollutant distribution within streets. Observed concentrations depend on processes occurring at a wide range of spatial and temporal scales, complex wind flow and turbulence patterns induced by urban obstacles and irregular traffic emissions. The main objective of this paper is to model particulate matter dispersion at microscale while considering the effects of mesoscale processes. Computational Fluid Dynamic (CFD) PM10 simulations were performed taking into account high spatial resolution traffic emissions from a microscale traffic model and inlet vertical profiles of meteorological variables from Weather Research and Forecasting (WRF) model. This modelling system is evaluated by using meteorological and PM10 concentration data from intensive experimental campaigns carried out on 25th February and 6th July, 2015 in a real urban traffic hot-spot in Madrid. The effect of uncertainties in the inlet profiles from mesoscale input data on microscale results is assessed. Additionally, the importance of the sensible surface heat fluxes (SHF) provided by WRF and the selection of an appropriate turbulent Schmidt number in the dispersion equation are investigated. The main conclusion is that the modelling system accurately reproduces PM10 dispersion imposing appropriate inputs (meteorological variables and SHF) and a suitable turbulent Schmidt number. Better agreement is found for simulation with a low turbulent Schmidt number. This approach improves the standard microscale modelling alone because more realistic boundary conditions and mesoscale processes are considered

TEMPORAL AND SPATIAL VARIABILITY OF ATMOSPHERIC PARTICLE NUMBER SIZE DISTRIBUTIONS ACROSS SPAIN

This study synthesizes for the first time results from simultaneous aerosol measurements performed at seven diverse locations distributed all over the Spanish geography. The observations were carried out during two field campaigns in 2012–2013, one-month each and during different seasons. These field campaigns were performed in the framework of the Spanish Network of DMAs (REDMAAS) activities. Measurement sites were grouped as polluted sites (urban background) and clean sites (rural background and high-altitude sites). Seasonal differences were more important at polluted sites, mainly related to meteorology and aerosol sources. Higher total particle concentrations were found during the cold period, driven mainly by Aitken-mode particles (traffic-related aerosol particles).This work has been financed by the Ministry of Science and Innovation (CGL2011-15008-E, CGL2010-1777, CGL2011-27020, CGL2014-52877-R, CGL2010-11095-E, CGL2012-39623-C02-01, CGL2014-55230-R & PI15/0051

A long-term study of new particle formation in a coastal environment: Meteorology, gas phase and solar radiation implications

New particle formation (NPF) was investigated at a coastal background site in Southwest Spain over a four-year period using a Scanning Particle Mobility Sizer (SMPS). The goals of the study were to characterise the NPF and to investigate their relationship to meteorology, gas phase (O3, SO2, CO and NO2) and solar radiation (UVA, UVB and global). A methodology for identifying and classifying the NPF was implemented using the wind direction and modal concentrations as inputs. NPF events showed a frequency of 24% of the total days analyzed. The mean duration was 9.2±4.2 hours. Contrary to previous studies conducted in other locations, the NPF frequency reached its maximum during cold seasons for approximately 30% of the days. The lowest frequency took place in July with 10%, and the seasonal wind pattern was found to be the most important parameter influencing the NPF frequency. The mean formation rate was 2.2±1.7 cm-3 s-1, with a maximum in the spring and early autumn and a minimum during the summer and winter. The mean growth rate was 3.8±2.4 nm h-1 with higher values occurring from spring to autumn. The mean and seasonal formation and growth rates are in agreement with previous observations from continental sites in the Northern Hemisphere. NPF classification of different classes was conducted to explore the effect of synoptic and regional-scale patterns on NPF and growth. The results show that under a breeze regime, the temperature indirectly affects NPF events. Higher temperatures increase the strength of the breeze recirculation, favouring gas accumulation and subsequent NPF appearance. Additionally, the role of high relative humidity in inhibiting the NPF was evinced during synoptic scenarios. The remaining meteorological variables (RH), trace gases (CO and NO), solar radiation, PM10 and condensation sink, showed a moderate or high connection with both formation and growth rates.This work was partially supported by the Andalusian Regional Government through projects P10-RNM-6299 and P12-RNM-2409, the Spanish Ministry of Science and Technology (MINECO) through projects CGL2010-18782, CGL2011-24891/CLI, CGL2013-45410-R and the Complementary Action CGL2011-15008-E.European Union through the ACTRIS project (EU INFRA-2010-1.1.16-262254)

The role of retinal fluid location in atrophy and fibrosis evolution of patients with neovascular age-related macular degeneration long-term treated in real world

Purpose: To assess the effect of clinical factors on the development and progression of atrophy and fibrosis in patients with neovascular age-related macular degeneration (nAMD) receiving long-term treatment in the real world. Methods: An ambispective 36-month multicentre study, involving 359 nAMD patients from 17 Spanish hospitals treated according to the Spanish Vitreoretinal Society guidelines, was designed. The influence of demographic and clinical factors, including the presence and location of retinal fluid, on best-corrected visual acuity (BCVA) and progression to atrophy and/or fibrosis were analysed. Results: After 36 months of follow-up and an average of 13.8 anti-VEGF intravitreal injections, the average BCVA gain was +1.5 letters, and atrophy and/or fibrosis were present in 54.8% of nAMD patients (OR = 8.54, 95% CI = 5.85-12.47, compared to baseline). Atrophy was associated with basal intraretinal fluid (IRF) (OR = 1.87, 95% CI = 1.09-3.20), whereas basal subretinal fluid (SRF) was associated with a lower rate of atrophy (OR = 0.40, 95% CI = 0.23-0.71) and its progression (OR = 0.44, 95% CI = 0.26-0.75), leading to a slow progression rate (OR = 0.34, 95% CI = 0.14-0.83). Fibrosis development and progression were related to IRF at any visit (p < 0.001). In contrast, 36-month SRF was related to a lower rate of fibrosis (OR = 0.49, 95% CI = 0.29-0.81) and its progression (OR = 0.50, 95% CI = 0.31-0.81). Conclusion: Atrophy and/or fibrosis were present in 1 of 2 nAMD patients treated for 3 years. Both, especially fibrosis, lead to vision loss. Subretinal fluid (SRF) was associated with good visual outcomes and lower rates of atrophy and fibrosis, whereas IRF yields worse visual results and a higher risk of atrophy and especially fibrosis in routine clinical practice

Oral Anticoagulation and Risk of Symptomatic Hemorrhagic Transformation in Stroke Patients Treated With Mechanical Thrombectomy: Data From the Nordictus Registry

Introduction: We aimed to evaluate if prior oral anticoagulation (OAC) and its type determines a greater risk of symptomatic hemorrhagic transformation in patients with acute ischemic stroke (AIS) subjected to mechanical thrombectomy. Materials and Methods: Consecutive patients with AIS included in the prospective reperfusion registry NORDICTUS, a network of tertiary stroke centers in Northern Spain, from January 2017 to December 2019 were included. Prior use of oral anticoagulants, baseline variables, and international normalized ratio (INR) on admission were recorded. Symptomatic intracranial hemorrhage (sICH) was the primary outcome measure. Secondary outcome was the relation between INR and sICH, and we evaluated mortality and functional outcome at 3 months by modified Rankin scale. We compared patients with and without previous OAC and also considered the type of oral anticoagulants. Results: About 1.455 AIS patients were included, of whom 274 (19%) were on OAC, 193 (70%) on vitamin K antagonists (VKA), and 81 (30%) on direct oral anticoagulants (DOACs). Anticoagulated patients were older and had more comorbidities. Eighty-one (5.6%) developed sICH, which was more frequent in the VKA group, but not in DOAC group. OAC with VKA emerged as a predictor of sICH in a multivariate regression model (OR, 1.89 [95% CI, 1.01–3.51], p = 0.04) and was not related to INR level on admission. Prior VKA use was not associated with worse outcome in the multivariate regression model nor with mortality at 3 months. Conclusions: OAC with VKA, but not with DOACs, was an independent predictor of sICH after mechanical thrombectomy. This excess risk was associated neither with INR value by the time thrombectomy was performed, nor with a worse functional outcome or mortality at 3 months