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Showing papers by "Makarand Deo published in 2011"


Journal ArticleDOI
TL;DR: The predicted waves obtained using the proposed time series models when compared with the numerically generated waves showed good resemblance in terms of the selected error criteria and are a cost effective and convenient option when a site-specific information is desired.

38 citations


Journal ArticleDOI
TL;DR: In this article, the authors investigated the role of desmosomal protein plakophilin-2 (PKP2) expression in arrhythmia susceptibility and reentry dynamics.

24 citations


Journal ArticleDOI
TL;DR: In this article, the authors reported results from a fresh investigation carried out to determine wave spectral shapes with neural network (NN)s, support vector regression (SVR) and model tree (MT)s based on measurements made by wave buoys at two locations in Arabian Sea and Bay of Bengal off the Indian coast.
Abstract: Considerable works have been reported over last few decades on determination of wave spectral shapes. The resulting spectral models still involve large uncertainties, especially in handling spectra with two or more peaks. Hence studies indicating new options or re-examining some earlier ones in this regard should be welcome. This paper reports results from a fresh investigation carried out to determine wave spectral shapes with neural network (NN)s, support vector regression (SVR) and model tree (MT)s based on measurements made by wave buoys at two locations in Arabian Sea and Bay of Bengal off the Indian coast. It was found that in general all the three modern data driven approaches worked satisfactorily and they were more useful than the commonly adopted semi-empirical spectra. In order to obtain consistent and stable results the model calibration however needs to be made in a careful manner. Separate training over low and high sea states as well as for cases of double and multi-peaked spectra paid rich...

5 citations


Book ChapterDOI
26 Sep 2011
TL;DR: Computer modelling offers an attractive platform for studying the role of the Purkinje System in defibrillation, since the electrical activity everywhere in the system is known and can be visualized.
Abstract: Only relatively recently have we begun to understand how defibrillation shocks work on the mechanistic level (Cheng et al., 1999; Trayanova & Skouibine, 1998). Virtual electrode polarization has offered a plausible mechanism for explaining far field effects of defibrillation shocks. However, this body of work has not considered the role of the specialized cardiac conduction system, the Purkinje System (PS), in the defibrillation process. Despite its crucial role in activation, relatively little is known about the role of the PS in defibrillation. This is due to several factors which make recording from it challenging: The PS is a fine structure lying on the endocardium which makes it difficult to see and impale with microelectrodes. While Langendorf preparations allow easy access to the epicardium for optical recordings, the PS lies on the endocardium and is, therefore, much harder to access while maintaining the integrity of the ventricles. Depending on species, the PS penetrates various depths into the myocardium, masking midmyocardial activation. Plunge electrodes are one option for recording from the midmyocardium, but amplifier saturation immediately following large shocks would lose important information. Since the PS fibres are fine, the signals produced by them are very small and get easily swamped by signals from the myocardium. This is true for both electrical and optical recordings. Computer modelling, therefore, offers an attractive platform for studying the role of the PS in defibrillation, since the electrical activity everywhere in the system is known and can be visualized.

3 citations