Environmental justice and the expanding geography of wind power conflicts

Unidad de excelencia María de Maeztu MdM-2015-0552Wind power is expanding globally. Simultaneously, a growing number of conflicts against large-scale wind farms are emerging in multiple locations around the world. As these processes occur, new questions arise on how electricity from wind is being generated, how such energy is flowing within societies, and how these production-flows are being shaped by specific power structures. The present paper explores the expanding geography of wind energy conflicts by analyzing 20 case studies from across the Americas, Africa, Asia and Europe. Based on the Environmental Justice Atlas database, it reflects on how land pressures and patterns of uneven development emerge as two features of the current expansion of wind farms. Following a relational analysis, these patterns are examined to interpret the plural instances of opposition emerging throughout the rural spaces of the world. The article argues that previously unexplored forms of collective action are expanding the scope and content of the "wind energy debate". In addition to the claims of "landscape" and "wildlife protection" addressed by the existing literature, this study sheds light on the rural/peripheral contexts where opposition emerges through the defense of indigenous territories, local livelihoods and communal development projects. The study contends that these "emerging storylines" embrace an environmental justice perspective when challenging the socially unequal and geographically uneven patterns reproduced by the ecological modernization paradigm. From this lens, cases of local opposition are not interpreted as selfish forces blocking a low-carbon transition, but instead, are understood as political instances that enable a wider discussion about the ways such transition should take place

Contesting energy transitions : wind power and conflicts in the Isthmus of Tehuantepec

Unidad de excelencia María de Maeztu MdM-2015-0552This article studies the expansion of large-scale wind energy projects on the Isthmus of Tehuantepec (Mexico) and local socio-environmental conflicts that have emerged in response. It explores how the neoliberal agenda in Mexico is shaping a specific way of implementing wind energy projects, and how this is leading to local resistance and the production of alternatives. The article is based on a historical analysis reconstructing the main features of wind power development, and pathways of struggle. By following a political ecology perspective, wind energy is seen as embedded in a wider frame of power relations and the uneven patterns of the Mexican economy. The struggles of indigenous groups are thus analyzed as the expression of peripheral communities against the enclosure of communal lands, the private appropriation of benefits, and the lack of democratic procedures involved in these projects. The discussion emphasizes the role of communal identities and institutions in building successful networks, while introducing new concepts (energy sovereignty) and alternative schemes in wind power production (cooperatives). The overall approach of the article is that any move towards a different energy system should be politically encouraged by social and cultural means, rather than be largely economically motivated

Electronic structure of porphyrin-based metal– organic frameworks and their suitability for solar fuel production photocatalysis

Metal–organic frameworks (MOFs) can be exceptionally good catalytic materials thanks to the presence of active metal centres and a porous structure that is advantageous for molecular adsorption and confinement. We present here a first-principles investigation of the electronic structure of a family of MOFs based on porphyrins connected through phenyl-carboxyl ligands and AlOH species, in order to assess their suitability for the photocatalysis of fuel production reactions using sunlight. We consider structures with protonated porphyrins and those with the protons exchanged with late 3d metal cations (Fe2+, Co2+, Ni2+, Cu2+, Zn2+), a process that we find to be thermodynamically favorable from aqueous solution for all these metals. Our band structure calculations, based on an accurate screened hybrid functional, reveal that the bandgaps are in a favorable range (2.0 to 2.6 eV) for efficient adsorption of solar light. Furthermore, by approximating the vacuum level to the pore centre potential, we provide the alignment of the MOFs' band edges with the redox potentials for water splitting and carbon dioxide reduction, and show that the structures studied here have band edges positions suitable for these reactions at neutral pH.Royal Society for an International Exchange Scheme grantVia our membership of the UK's HPC Materials Chemistry Consortium, which is funded by EPSRC (EP/L000202), this work made use of the facilities of ARCHER, the UK's national high-performance computing services, which are funded by the Office of Science and Technology through EPSRC's High End Computing ProgrammeEuropean Research Council through an ERC Starting Grant (ERC2011-StG-279520-RASPA)MINECO (CTQ2013-48396-P)Andalucía Region (FQM-1851)University of Granad

Effect of confinement on the solubility of salt in water: A simulation study on zeolites

Motivation: Salinity is an important concept to understand the environmental conditions and organisms that can be found in water as well and depends on the solubility of salts in water. The effect of temperature and pressure on the solubility of salts (as sodium chloride) in water and other solvents has been widely studied. However, there is scarce studies on the solubility of salts in confined systems, and how the confinement affects to the solvation of salts. Zeolites are a group of crystalline porous solids based on silica and they exhibit high surface area, high thermal stability, and high exchange capacity. Pure silica zeolites are hydrophobic, but the presence of cations can change this nature making them suitable for a variety of applications such as drying of refrigerants, removal of atmospheric pollutants, separation of air components, recovering radioactive ions from waste solutions, catalysis of hydrocarbon reactions, and many others. In this work, we study the influence of the confinement of water in two types of zeolite on the solubility of sodium chloride.Methods: To study the influence that confinement of water in zeolites has on the dissociation of NaCl clusters, we carry out molecular simulation using two techniques, Molecular Dynamics (MD) and Monte Carlo methods (MC). All simulations are performed using the RASPA simulation code and the force fields and models used for water and the ions are taken from the literature and previously validated. As initial step, we use MD to analyse the effect of temperature and system size on the dissociation of salt. Then, the effect of confinement is analysed using MC simulations. For this purpose we calculated the adsorption of water in two commercial zeolites (MFI and FAU) and after obtaining the adsorption capacity of water for these structures, we study the dissociation of salt in the adsorbed water. We focus on the effect exerted by the number of cations on the zeolites, the topology and the initial concentration of salt.Results: Our results show that the size of the simulating box has an impact on the dissociation of ions, obtaining that the larger the box, the better the dissociation. In the confined systems, we found that in the pure silica MFI zeolite (longitudinal channels connected to zig-zag channels) dissociation is enhanced and the same occurs in the pure FAU zeolite (cages connected throw windows). Nevertheless, for the FAU zeolite with aluminium atoms, the dissociation of ions is hampered when increasing the number of Al substitutions. On the contrary, the presence of aluminium in the MFI does not alter the dissociation of ions

Understanding Nanopore Window Distortions in the Reversible Molecular Valve Zeolite RHO

Molecular valves are becoming popular for potential biomedical applications. However, little is known concerning their performance in energy and environmental areas. Zeolite RHO shows unique pore deformations upon changes in hydration, cation siting, cation type, or temperature-pressure conditions. By varying the level of distortion of double eight-rings, it is possible to control the adsorption properties, which confer a molecular valve behavior to this material. We have employed interatomic potentials-based simulations to obtain a detailed atomistic view of the structural distortion mechanisms of zeolite RHO, in contrast with the averaged and space group restricted information provided by diffraction studies. We have modeled four aluminosilicate structures, containing Li$^+$, Na$^+$, K$^+$, Ca$^{2+}$, and Sr$^{2+}$ cations. The distortions of the three different zeolite rings are coupled, and the six- and eight-membered rings are largely flexible. A large dependence on the polarizing power of the extra-framework cations and with the loading of water has been found for the minimum aperture of the eight-membered rings that control the nanovalve effect. The calculated energy barriers for moving the cations across the eight-membered rings are very high, which explains the experimentally observed slow kinetics of the phase transition as well as the appearance of metastable phases

Improving Ammonia Production Using Zeolites

Motivation: Ammonia production is one of the most important industries in the world, being of capital importance in agriculture as source of nitrogen for growing plants. However, ammonia production depends on plentiful supplies of energy and large percentages of production are not achieved [1]. In order to overcome this issue, an alternative production method is highly necessary. In this work we explore the use of zeolites to improve the ammonia production method. Zeolites are molecular sieves commonly used in chemical industry as catalyst to its size pores, in agriculture as soil conditioner and to soften water by ion exchange.Methods: The ammonia formation reaction in zeolites has been explored in this work using Monte Carlo simulations in the Grand Canonical ensemble (GCMC). All simulations have been carried out using the simulation code RASPA [2]. Atomic interactions were modeled with Lennard-Jones parameters; while electrostatic interactions have been considered through coulombic potentials and the application of Ewald summations [3]. In this work we selected BEA, FAU, FER, ITQ-29,MFI and MOR zeolites because they are the most commercialized and available zeolites for industrial processes like this.Results: Our results show the yield improvement of the ammonia synthesis reaction using zeolites. At 873 K and 1000 bar, we improve the ammonia production since 35% (reaction in the bulk) to 50% (using zeolite); it represents 40% improvement in the yield of the reaction. Using BEA, at 550 K and 200 bar, we have obtained a yield above 95%. In some cases we have obtained results equivalent to a temperature change of 100 ºC. FAU produces a greater effect than FER; this is due to its topology of cages that it is more effective than channels.Conclusions: In this work we have explored the use of zeolites for the improvement of the ammonia formation reaction. We have studied 6 well-known zeolites. Results obtained in this work represent an increase of 44% respect to the reaction carried out nowadays. This technique could be one of the technologies used in the future to help this industry in all aspects; yield, environmental and economic. The next step would be to improve the use of these zeolites, an example of improvement could be the incorporation of cations to the system in order to obtain a better performance of the zeolite

Water adsorption in hydrophilic zeolites: experiment and simulation

We have measured experimental adsorption isotherms of water in zeolite LTA4A, and studied the regeneration process by performing subsequent adsorption cycles after degassing at different temperatures. We observed incomplete desorption at low temperatures, and cation rearrangement at successive adsorption cycles. We also developed a new molecular simulation force field able to reproduce experimental adsorption isotherms in the range of temperatures between 273 K and 374 K. Small deviations observed at high pressures are attributed to the change in the water dipole moment at high loadings. The force field correctly describes the preferential adsorption sites of water at different pressures. We tested the influence of the zeolite structure, framework flexibility, and cation mobility when considering adsorption and diffusion of water. Finally, we performed checks on force field transferability between different hydrophilic zeolite types, concluding that classical, non-polarizable water force fields are not transferable.The European Research Council through an ERC Staring Grant (Sofia Calero), and the MICINN (CTQ2010-16077) project

Estrés, afrontamiento y calidad de vida relacionada a la salud en pacientes con cáncer de mama.

El cáncer de mama puede ser considerado un evento de vida potencialmente estresante pues demanda cambios que tienden a exceder la capacidad de las pacientes para afrontar dicha condición, lo que afecta negativamente su CVRS. Este estudio examina la contribución que tienen el estrés percibido, el estrés traumático, los estilos de afrontamiento, la migración y el tipo de tratamiento recibido sobre la variabilidad de los componentes físico y mental de la CVRS de 53 mujeres mastectomizadas, que han sido diagnosticadas por primera vez con cáncer de mama. Los instrumentos utilizados comprendieron la adaptación española del cuestionario de salud (SF-36) (Alonso, Prieto & Antó, 1995), el inventario de estimación de afrontamiento COPE (Carver, Scheier & Weintraub, 1989), la escala de estrés percibido EEP (Cohen, Kamarck & Mermelstein, 1983) y la adaptación peruana de la escala de estrés traumático (Gargurevich, 2006). Se encontraron niveles promedio y altos de la CVRS. El componente físico se vio más afectado que el componente mental, especialmente en las pacientes migrantes. En el componente físico, se obtuvo un modelo conformado por la migración, el tipo de tratamiento y el estrés traumático, quienes explicaron el 30% de su variabilidad. En tanto, en el componente mental se obtuvieron dos modelos; el primero conformado por el estrés traumático y el estrés percibido, quienes explicaron el 39% de su variabilidad; mientras que el segundo, conformado por el estrés traumático, estrés percibido y el estilo orientado a la emoción explicaron el 42% de su variabilidad. Palabras clave: Calidad de vida relacionada a la salud (CVRS), afrontamiento, estrés percibido,estrés traumático, cáncer de mama, migración y tipo de tratamiento.Breast cancer might be considered a life-threatening event as it demands changes that could exceed the patient’s abilities to cope with their illness, therefore, affect HRQoL in a negative way. This study analyzes the contribution that traumatic stress, perceived stress, coping, migration and type of treatment have on the variability of physical and metal components of the HRQoL of 53 mastectomized women with breast cancer. The instruments used include the Spanish adaptation of the SF-36 health survey (Alonso, Prieto & Antó, 1995), the COPE Inventory (Carver, Scheier & Weintraub, 1989), the Perceived Stress Scale PSS (Cohen, Kamarck & Mermelstein, 1983) and the Peruvian adaptation of the traumatic stress scale (Gargurevich, 2006). The analysis found medium and high levels of the HRQoL. Physical component was more affected than mental component, especially in migrant patients. The model of the physical component was comprised by migration, treatment type and traumatic stress, which explained 30% of its variability. On the other hand, two models were obtained from the mental component; the first was comprised by traumatic stress and perceived stress, which explained 39% of its variability, while the second model, comprised by traumatic stress, perceived stress an emotion-oriented stress, explained 42% of its variabilityTesi

Measuring Control to Dynamically Induce Flow in Tetris.

Dynamic Difficulty Adjustment (DDA) is a set of techniques that aim to automatically adapt the difficulty of a video game based on the player’s performance. This paper presents a methodology for DDA using ideas from the theory of flow and case-based reasoning (CBR). In essence we are looking to generate game sessions with a similar difficulty evolution to previous game sessions that have produced flow in players with a similar skill level. We propose a CBR approach to dynamically assess the player’s skill level and adapt the difficulty of the game based on the relative complexity of the last game states. We develop a DDA system for Tetris using this methodology and show, in a experiment with 40 participants, that the DDA version has a measurable impact on the perceived flow using validated questionnaires.pre-print456 K

Multi-scale Entropy Evaluates the Proarrhythmic Condition of Persistent Atrial Fibrillation Patients Predicting Early Failure of Electrical Cardioversion

[EN] Atrial fibrillation (AF) is nowadays the most common cardiac arrhythmia, being associated with an increase in cardiovascular mortality and morbidity. When AF lasts for more than seven days, it is classified as persistent AF and external interventions are required for its termination. A well-established alternative for that purpose is electrical cardioversion (ECV). While ECV is able to initially restore sinus rhythm (SR) in more than 90% of patients, rates of AF recurrence as high as 20-30% have been found after only a few weeks of follow-up. Hence, new methods for evaluating the proarrhythmic condition of a patient before the intervention can serve as efficient predictors about the high risk of early failure of ECV, thus facilitating optimal management of AF patients. Among the wide variety of predictors that have been proposed to date, those based on estimating organization of the fibrillatory (f-) waves from the surface electrocardiogram (ECG) have reported very promising results. However, the existing methods are based on traditional entropy measures, which only assess a single time scale and often are unable to fully characterize the dynamics generated by highly complex systems, such as the heart during AF. The present work then explores whether a multi-scale entropy (MSE) analysis of thef-waves may provide early prediction of AF recurrence after ECV. In addition to the common MSE, two improved versions have also been analyzed, composite MSE (CMSE) and refined MSE (RMSE). When analyzing 70 patients under ECV, of which 31 maintained SR and 39 relapsed to AF after a four week follow-up, the three methods provided similar performance. However, RMSE reported a slightly better discriminant ability of 86%, thus improving the other multi-scale-based outcomes by 3-9% and other previously proposed predictors of ECV by 15-30%. This outcome suggests that investigation of dynamics at large time scales yields novel insights about the underlying complex processes generatingf-waves, which could provide individual proarrhythmic condition estimation, thus improving preoperative predictions of ECV early failure.This research has been supported by grants DPI2007-83952-C3 from MINECO/AEI/FEDER EU, SBPLY/17/180501000411 from Junta de Comunidades de Castilla la Mancha and AICO/2019/036 from Generalitat Valenciana.Cirugeda Roldan, EM.; Calero, S.; Hidalgo, VM.; Enero, J.; Rieta, JJ.; Alcaraz, R. (2020). Multi-scale Entropy Evaluates the Proarrhythmic Condition of Persistent Atrial Fibrillation Patients Predicting Early Failure of Electrical Cardioversion. Entropy. 22(7):1-17. https://doi.org/10.3390/e22070748S117227Lippi, G., Sanchis-Gomar, F., & Cervellin, G. (2020). Global epidemiology of atrial fibrillation: An increasing epidemic and public health challenge. International Journal of Stroke, 16(2), 217-221. doi:10.1177/1747493019897870Lane, D. A., Skjøth, F., Lip, G. Y. H., Larsen, T. B., & Kotecha, D. (2017). Temporal Trends in Incidence, Prevalence, and Mortality of Atrial Fibrillation in Primary Care. Journal of the American Heart Association, 6(5). doi:10.1161/jaha.116.005155Duarte, R. C. F., Rios, D. R. A., Figueiredo, E. L., Caiaffa, J. R. S., Silveira, F. R., Lanna, R., … das Graças Carvalho, M. (2020). Thrombin Generation and other hemostatic parameters in patients with atrial fibrillation in use of warfarin or rivaroxaban. Journal of Thrombosis and Thrombolysis, 51(1), 47-57. doi:10.1007/s11239-020-02126-3Khoo, C. W., Krishnamoorthy, S., Lim, H. S., & Lip, G. Y. H. (2012). Atrial fibrillation, arrhythmia burden and thrombogenesis. International Journal of Cardiology, 157(3), 318-323. doi:10.1016/j.ijcard.2011.06.088Zoni-Berisso, M., Lercari, F., Carazza, T., & Domenicucci, S. (2014). Epidemiology of atrial fibrillation: European perspective. Clinical Epidemiology, 213. doi:10.2147/clep.s47385Dietzel, J., Haeusler, K. G., & Endres, M. (2017). Does atrial fibrillation cause cognitive decline and dementia? EP Europace, 20(3), 408-419. doi:10.1093/europace/eux031Aliot, E., Botto, G. L., Crijns, H. J., & Kirchhof, P. (2014). Quality of life in patients with atrial fibrillation: how to assess it and how to improve it. Europace, 16(6), 787-796. doi:10.1093/europace/eut369Miyazawa, K., & Lip, G. Y. (2018). Atrial fibrillation. Medicine, 46(10), 627-631. doi:10.1016/j.mpmed.2018.07.009Blum, S., Meyre, P., Aeschbacher, S., Berger, S., Auberson, C., Briel, M., … Conen, D. (2019). Incidence and predictors of atrial fibrillation progression: A systematic review and meta-analysis. Heart Rhythm, 16(4), 502-510. doi:10.1016/j.hrthm.2018.10.022Berger, W. R., Meulendijks, E. R., Limpens, J., van den Berg, N. W. E., Neefs, J., Driessen, A. H. G., … de Groot, J. R. (2019). Persistent atrial fibrillation: A systematic review and meta-analysis of invasive strategies. International Journal of Cardiology, 278, 137-143. doi:10.1016/j.ijcard.2018.11.127Nattel, S., Guasch, E., Savelieva, I., Cosio, F. G., Valverde, I., Halperin, J. L., … Camm, A. J. (2014). Early management of atrial fibrillation to prevent cardiovascular complications. European Heart Journal, 35(22), 1448-1456. doi:10.1093/eurheartj/ehu028Kirchhof, P., Benussi, S., Kotecha, D., Ahlsson, A., Atar, D., Casadei, B., … Zeppenfeld, K. (2016). 2016 ESC Guidelines for the management of atrial fibrillation developed in collaboration with EACTS. European Heart Journal, 37(38), 2893-2962. doi:10.1093/eurheartj/ehw210Scheuermeyer, F. X., Andolfatto, G., Christenson, J., Villa‐Roel, C., & Rowe, B. (2019). A Multicenter Randomized Trial to Evaluate a Chemical‐first or Electrical‐first Cardioversion Strategy for Patients With Uncomplicated Acute Atrial Fibrillation. Academic Emergency Medicine, 26(9), 969-981. doi:10.1111/acem.13669Fried, A. M., Strout, T. D., & Perron, A. D. (2021). Electrical cardioversion for atrial fibrillation in the emergency department: A large single-center experience. The American Journal of Emergency Medicine, 42, 115-120. doi:10.1016/j.ajem.2020.02.001Brandes, A., Crijns, H. J. G. M., Rienstra, M., Kirchhof, P., Grove, E. L., Pedersen, K. B., & Van Gelder, I. C. (2020). Cardioversion of atrial fibrillation and atrial flutter revisited: current evidence and practical guidance for a common procedure. EP Europace, 22(8), 1149-1161. doi:10.1093/europace/euaa057Alegret, J. M., Viñolas, X., Tajes, H., Valdovinos, P., Palomares, R., Arias, M. A., & Bazán, V. (2020). Utility of Amiodarone Pre-Treatment as a Facilitator of the Acute Success of Electrical Cardioversion in Persistent Atrial Fibrillation. Cardiovascular Drugs and Therapy, 34(1), 89-94. doi:10.1007/s10557-019-06934-5Piccini, J. P., & Fauchier, L. (2016). Rhythm control in atrial fibrillation. The Lancet, 388(10046), 829-840. doi:10.1016/s0140-6736(16)31277-6Jaakkola, S., Lip, G. Y. H., Biancari, F., Nuotio, I., Hartikainen, J. E. K., Ylitalo, A., & Airaksinen, K. E. J. (2017). Predicting Unsuccessful Electrical Cardioversion for Acute Atrial Fibrillation (from the AF-CVS Score). The American Journal of Cardiology, 119(5), 749-752. doi:10.1016/j.amjcard.2016.11.026Fujimoto, Y., Yodogawa, K., Maru, Y., Oka, E., Hayashi, H., Yamamoto, T., … Shimizu, W. (2018). Advanced interatrial block is an electrocardiographic marker for recurrence of atrial fibrillation after electrical cardioversion. International Journal of Cardiology, 272, 113-117. doi:10.1016/j.ijcard.2018.07.135GRÖNBERG, T., HARTIKAINEN, J. E. K., NUOTIO, I., BIANCARI, F., VASANKARI, T., NIKKINEN, M., … AIRAKSINEN, K. E. J. (2014). Can We Predict the Failure of Electrical Cardioversion of Acute Atrial Fibrillation? The FinCV Study. Pacing and Clinical Electrophysiology, 38(3), 368-375. doi:10.1111/pace.12561Doruchowska, A., Wita, K., Bochenek, T., Szydło, K., Filipecki, A., Staroń, A., … Trusz-Gluza, M. (2014). Role of left atrial speckle tracking echocardiography in predicting persistent atrial fibrillation electrical cardioversion success and sinus rhythm maintenance at 6 months. Advances in Medical Sciences, 59(1), 120-125. doi:10.1016/j.advms.2013.10.003Luong, C. L., Thompson, D. J. S., Gin, K. G., Jue, J., Nair, P., Lee, P.-K., … Tsang, T. S. M. (2016). Usefulness of the Atrial Emptying Fraction to Predict Maintenance of Sinus Rhythm After Direct Current Cardioversion for Atrial Fibrillation. The American Journal of Cardiology, 118(9), 1345-1349. doi:10.1016/j.amjcard.2016.07.066Wałek, P., Sielski, J., Gorczyca, I., Roskal-Wałek, J., Starzyk, K., Jaskulska-Niedziela, E., … Wożakowska-Kapłon, B. (2020). Left atrial mechanical remodelling assessed as the velocity of left atrium appendage wall motion during atrial fibrillation is associated with maintenance of sinus rhythm after electrical cardioversion in patients with persistent atrial fibrillation. PLOS ONE, 15(1), e0228239. doi:10.1371/journal.pone.0228239Zhao, T. X., Martin, C. A., Cooper, J. P., & Gajendragadkar, P. R. (2017). Coarse fibrillatory waves in atrial fibrillation predict success of electrical cardioversion. Annals of Noninvasive Electrocardiology, 23(4), e12528. doi:10.1111/anec.12528Lombardi, F., Colombo, A., Basilico, B., Ravaglia, R., Garbin, M., Vergani, D., … Fiorentini, C. (2001). Heart rate variability and early recurrence of atrial fibrillation after electrical cardioversion. Journal of the American College of Cardiology, 37(1), 157-162. doi:10.1016/s0735-1097(00)01039-1Vikman, S., Mäkikallio, T. H., Yli‐Mäyry, S., Nurmi, M., Juhani Airaksinen, K., & Huikuri, H. V. (2003). Heart rate variability and recurrence of atrial fibrillation after electrical cardioversion. Annals of Medicine, 35(1), 36-42. doi:10.1080/07853890310004110VAN DEN BERG, M. P., VAN NOORD, T., BROUWER, J., HAAKSMA, J., VAN VELDHUISEN, D. J., CRIJNS, H. J. G. M., & VAN GELDER, I. C. (2004). Clustering of RR Intervals Predicts Effective Electrical Cardioversion for Atrial Fibrillation. Journal of Cardiovascular Electrophysiology, 15(9), 1027-1033. doi:10.1046/j.1540-8167.2004.03686.xZOHAR, P., KOVACIC, M., BREZOCNIK, M., & PODBREGAR, M. (2005). Prediction of maintenance of sinus rhythm after electrical cardioversion of atrial fibrillation by non-deterministic modelling. Europace, 7(5), 500-507. doi:10.1016/j.eupc.2005.04.007Seeck, A., Rademacher, W., Fischer, C., Haueisen, J., Surber, R., & Voss, A. (2013). Prediction of atrial fibrillation recurrence after cardioversion—Interaction analysis of cardiac autonomic regulation. Medical Engineering & Physics, 35(3), 376-382. doi:10.1016/j.medengphy.2012.06.002Eren, H., Kaya, Ü., Öcal, L., Şenbaş, A., & Kalçık, M. (2019). The presence of fragmented QRS may predict the recurrence of nonvalvular atrial fibrillation after successful electrical cardioversion. Annals of Noninvasive Electrocardiology, 25(1). doi:10.1111/anec.12700Langberg, J. J., Burnette, J. C., & McTeague, K. K. (1998). Spectral analysis of the electrocardiogram predicts recurrence of atrial fibrillation after cardioversion. Journal of Electrocardiology, 31, 80-84. doi:10.1016/s0022-0736(98)90297-7Watson, J. N., Addison, P. S., Uchaipichat, N., Shah, A. S., & Grubb, N. R. (2007). Wavelet transform analysis predicts outcome of DC cardioversion for atrial fibrillation patients. Computers in Biology and Medicine, 37(4), 517-523. doi:10.1016/j.compbiomed.2006.08.003Cervigón, R., Sánchez, C., Castells, F., Blas, J. M., & Millet, J. (2007). Wavelet analysis of electrocardiograms to characterize recurrent atrial fibrillation. Journal of the Franklin Institute, 344(3-4), 196-211. doi:10.1016/j.jfranklin.2006.10.005Alcaraz, R., & Rieta, J. J. (2008). A non-invasive method to predict electrical cardioversion outcome of persistent atrial fibrillation. Medical & Biological Engineering & Computing, 46(7), 625-635. doi:10.1007/s11517-008-0348-5Alcaraz, R., & Rieta, J. J. (2009). Time and frequency recurrence analysis of persistent atrial fibrillation after electrical cardioversion. Physiological Measurement, 30(5), 479-489. doi:10.1088/0967-3334/30/5/005Lankveld, T., de Vos, C. B., Limantoro, I., Zeemering, S., Dudink, E., Crijns, H. J., & Schotten, U. (2016). Systematic analysis of ECG predictors of sinus rhythm maintenance after electrical cardioversion for persistent atrial fibrillation. Heart Rhythm, 13(5), 1020-1027. doi:10.1016/j.hrthm.2016.01.004ALCARAZ, R., HORNERO, F., & RIETA, J. J. (2011). Noninvasive Time and Frequency Predictors of Long-Standing Atrial Fibrillation Early Recurrence after Electrical Cardioversion. Pacing and Clinical Electrophysiology, 34(10), 1241-1250. doi:10.1111/j.1540-8159.2011.03125.xCosta, M., Goldberger, A. L., & Peng, C.-K. (2002). Multiscale Entropy Analysis of Complex Physiologic Time Series. Physical Review Letters, 89(6). doi:10.1103/physrevlett.89.068102Humeau-Heurtier, A. (2015). The Multiscale Entropy Algorithm and Its Variants: A Review. Entropy, 17(5), 3110-3123. doi:10.3390/e17053110Wu, S.-D., Wu, C.-W., Lin, S.-G., Wang, C.-C., & Lee, K.-Y. (2013). Time Series Analysis Using Composite Multiscale Entropy. Entropy, 15(3), 1069-1084. doi:10.3390/e15031069Valencia, J. F., Porta, A., Vallverdu, M., Claria, F., Baranowski, R., Orlowska-Baranowska, E., & Caminal, P. (2009). Refined Multiscale Entropy: Application to 24-h Holter Recordings of Heart Period Variability in Healthy and Aortic Stenosis Subjects. IEEE Transactions on Biomedical Engineering, 56(9), 2202-2213. doi:10.1109/tbme.2009.2021986Alcaraz, R., & Rieta, J. J. (2008). Adaptive singular value cancelation of ventricular activity in single-lead atrial fibrillation electrocardiograms. Physiological Measurement, 29(12), 1351-1369. doi:10.1088/0967-3334/29/12/001Vest, A. N., Da Poian, G., Li, Q., Liu, C., Nemati, S., Shah, A. J., & Clifford, G. D. (2018). An open source benchmarked toolbox for cardiovascular waveform and interval analysis. Physiological Measurement, 39(10), 105004. doi:10.1088/1361-6579/aae021Nabil, D., & Bereksi Reguig, F. (2015). Ectopic beats detection and correction methods: A review. Biomedical Signal Processing and Control, 18, 228-244. doi:10.1016/j.bspc.2015.01.008Martínez, A., Alcaraz, R., & Rieta, J. J. (2013). Ventricular activity morphological characterization: Ectopic beats removal in long term atrial fibrillation recordings. Computer Methods and Programs in Biomedicine, 109(3), 283-292. doi:10.1016/j.cmpb.2012.10.011Alcaraz Martínez, R. (2013). Journal of Medical and Biological Engineering, 33(5), 455. doi:10.5405/jmbe.1069Corino, V. D. A., Sassi, R., Mainardi, L. T., & Cerutti, S. (2006). Signal processing methods for information enhancement in atrial fibrillation: Spectral analysis and non-linear parameters. Biomedical Signal Processing and Control, 1(4), 271-281. doi:10.1016/j.bspc.2006.12.003Alcaraz, R., & Rieta, J. J. (2009). Sample entropy of the main atrial wave predicts spontaneous termination of paroxysmal atrial fibrillation. Medical Engineering & Physics, 31(8), 917-922. doi:10.1016/j.medengphy.2009.05.002Richman, J. S., & Moorman, J. R. (2000). Physiological time-series analysis using approximate entropy and sample entropy. American Journal of Physiology-Heart and Circulatory Physiology, 278(6), H2039-H2049. doi:10.1152/ajpheart.2000.278.6.h2039Alcaraz, R., Abásolo, D., Hornero, R., & Rieta, J. J. (2010). Optimal parameters study for sample entropy-based atrial fibrillation organization analysis. Computer Methods and Programs in Biomedicine, 99(1), 124-132. doi:10.1016/j.cmpb.2010.02.009Costa, M., Peng, C.-K., L. Goldberger, A., & Hausdorff, J. M. (2003). Multiscale entropy analysis of human gait dynamics. Physica A: Statistical Mechanics and its Applications, 330(1-2), 53-60. doi:10.1016/j.physa.2003.08.022Pincus, S. M., & Goldberger, A. L. (1994). Physiological time-series analysis: what does regularity quantify? American Journal of Physiology-Heart and Circulatory Physiology, 266(4), H1643-H1656. doi:10.1152/ajpheart.1994.266.4.h1643Maturana-Candelas, A., Gómez, C., Poza, J., Pinto, N., & Hornero, R. (2019). EEG Characterization of the Alzheimer’s Disease Continuum by Means of Multiscale Entropies. Entropy, 21(6), 544. doi:10.3390/e21060544Crespo, A., Álvarez, D., Gutiérrez-Tobal, G. C., Vaquerizo-Villar, F., Barroso-García, V., Alonso-Álvarez, M. L., … Campo, F. del. (2017). Multiscale Entropy Analysis of Unattended Oximetric Recordings to Assist in the Screening of Paediatric Sleep Apnoea at Home. Entropy, 19(6), 284. doi:10.3390/e19060284Massey, F. J. (1951). The Kolmogorov-Smirnov Test for Goodness of Fit. Journal of the American Statistical Association, 46(253), 68-78. doi:10.1080/01621459.1951.10500769Williams, L. L., & Quave, K. (2019). Comparing Two Groups: t-Tests. Quantitative Anthropology, 89-104. doi:10.1016/b978-0-12-812775-9.00007-4Zweig, M. H., & Campbell, G. (1993). Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine. Clinical Chemistry, 39(4), 561-577. doi:10.1093/clinchem/39.4.561Qu, Z. (2011). Chaos in the genesis and maintenance of cardiac arrhythmias. Progress in Biophysics and Molecular Biology, 105(3), 247-257. doi:10.1016/j.pbiomolbio.2010.11.001Qu, Z., Hu, G., Garfinkel, A., & Weiss, J. N. (2014). Nonlinear and stochastic dynamics in the heart. Physics Reports, 543(2), 61-162. doi:10.1016/j.physrep.2014.05.002Qu, Z., Garfinkel, A., Chen, P.-S., & Weiss, J. N. (2000). Mechanisms of Discordant Alternans and Induction of Reentry in Simulated Cardiac Tissue. Circulation, 102(14), 1664-1670. doi:10.1161/01.cir.102.14.1664Dharmaprani, D., Dykes, L., McGavigan, A. D., Kuklik, P., Pope, K., & Ganesan, A. N. (2018). Information Theory and Atrial Fibrillation (AF): A Review. Frontiers in Physiology, 9. doi:10.3389/fphys.2018.00957Schotten, U., Dobrev, D., Platonov, P. G., Kottkamp, H., & Hindricks, G. (2016). Current controversies in determining the main mechanisms of atrial fibrillation. Journal of Internal Medicine, 279(5), 428-438. doi:10.1111/joim.12492Yin, R., Fu, Y., Yang, Z., Li, B., Pen, J., & Zheng, Z. (2017). Fibrillatory wave amplitude on transesophageal ECG as a marker of left atrial low-voltage areas in patients with persistent atrial fibrillation. Annals of Noninvasive Electrocardiology, 22(4), e12421. doi:10.1111/anec.12421Pourafkari, L., Baghbani-Oskouei, A., Aslanabadi, N., Tajlil, A., Ghaffari, S., Sadigh, A. M., … Nader, N. D. (2018). Fine versus coarse atrial fibrillation in rheumatic mitral stenosis: The impact of aging and the clinical significance. Annals of Noninvasive Electrocardiology, 23(4), e12540. doi:10.1111/anec.12540Nault, I., Lellouche, N., Matsuo, S., Knecht, S., Wright, M., Lim, K.-T., … Haïssaguerre, M. (2009). Clinical value of fibrillatory wave amplitude on surface ECG in patients with persistent atrial fibrillation. Journal of Interventional Cardiac Electrophysiology, 26(1), 11-19. doi:10.1007/s10840-009-9398-3Alcaraz, R., Sandberg, F., Sörnmo, L., & Rieta, J. J. (2011). Classification of Paroxysmal and Persistent Atrial Fibrillation in Ambulatory ECG Recordings. IEEE Transactions on Biomedical Engineering, 58(5), 1441-1449. doi:10.1109/tbme.2011.211265