Automatic Mode Switching in Atrial Fibrillation

Automatic mode switching (AMS) algorithms were designed to prevent tracking of atrial tachyarrhythmias (ATA) or other rapidly occurring signals sensed by atrial channels, thereby reducing the adverse hemodynamic and symptomatic consequences of a rapid ventricular response. The inclusion of an AMS function in most dual chamber pacemaker now provides optimal management of atrial arrhythmias and allows the benefit of atrioventricular synchrony to be extended to a population with existing atrial fibrillation. Appropriate AMS depends on several parameters: a) the programmed parameters; b) the characteristics of the arrhythmia; c) the characteristics of the AMS algorithm. Three qualifying aspects constitute an AMS algorithm: onset, AMS response, and resynchronization. Since AMS programs also provide data on the time of onset and duration of AMS episodes, AMS data may be interpreted as a surrogate marker of ATAs recurrence. Recently, stored electrograms corresponding to episodes of ATAs have been introduced, thus clarifying the accuracy of AMS in detecting ATAs Clinically this information may be used to assess the efficacy of an antiarrhythmic intervention or the risk of thromboembolic events, and it may serve as a valuable research tool for evaluating the natural history and burden of ATAs

Modelling departure time and mode choice

As a result of increasing road congestion and road pricing, modelling the temporal response of travellers to transport policy interventions has rapidly emerged as a major issue in many practical transport planning studies. A substantial body of research is therefore being carried out to understand the complexities involved in modelling time of day choice. These models are contributing substantially to our understanding of how travellers make time-of-day decisions (Hess et al, 2004; de Jong et al, 2003). These models, however, tend to be far too complex and far too data intensive to be of use for application in large-scale modelling forecasting systems, where socio-economic detail is limited and detailed scheduling information is rarely available. Moreover, model systems making use of the some of the latest analytical structures, such as Mixed Logit, are generally inapplicable in practical planning, since they rely on computer-intensive simulation in application just as well as in estimation. The aim of this paper, therefore, is to describe the development of time-period choice models which are suitable for application in large-scale modelling forecasting systems. Large-scale practical planning models often rely on systems of nested logit models, which can incorporate many of the most important interactions that are present in the complex models but which have low enough run-times to allow them to be used for practical planning. In these systems, temporal choice is represented as the choice between a finite set of discrete alternatives, represented by mutually exclusive time-periods that are obtained by aggregation of the actual observed continuous time values. The issues that face modellers are then: -how should the time periods be defined, and in particular how long should they be? -how should the choices of time periods be related to each other, e.g. is the elasticity for shorter shifts greater than for longer shifts? -how should time period choice be placed in the model system relative to other choices, such as that of the mode of travel? These questions cannot be answered on a purely theoretical basis but require the analysis of empirical data. However, there is not a great deal of data available on the relevant choices. The time period models described in the paper are developed from three related stated preference (SP) studies undertaken over the past decade in the United Kingdom and the Netherlands. Because of the complications involved with using advanced models in large-scale modelling forecasting systems, the model structures are limited to nested logit models. Two different tree structures are explored in the analysis, nesting mode above time period choice or time period choice above mode. The analysis examines how these structures differ by data set, purpose of travel and time period specification. Three time period specifications were tested, dividing the 24-hour day into: -twenty-four 1-hour periods; -five coarse time-periods; -sixteen 15-minute morning-peak periods, and two coarse pre-peak and post-peak periods. In each case, the time periods are used to define both the outbound and the return trip timings. The analysis shows that, with a few exceptions, the nested models outperform the basic Multinomial Logit structures, which operate under the assumption of equal substitution patterns across alternatives. With a single exception, the nested models in turn show higher substitution between alternative time periods than between alternative modes, showing that, for all the time period lengths studied, travellers are more sensitive to transport levels of service in their choice of departure time than in choice of mode. The advantages of the nesting structures are especially pronounced in the 1-hour and 15-minute models, while, in the coarse time-period models, the MNL model often remains the preferred structure; this is a clear effect of the broader time-periods, and the consequently lower substitution between time-periods.

Rad-hard vertical JFET switch for the HV-MUX system of the ATLAS upgrade Inner Tracker

This work presents a new silicon vertical JFET (V-JFET) device, based on the trenched 3D-detector technology developed at IMB-CNM, to be used as switches for the High-Voltage powering scheme of the ATLAS upgrade Inner Tracker. The optimization of the device characteristics is performed by 2D and 3D TCAD simulations. Special attention has been paid to the on-resistance and the switch-off and breakdown voltages to meet the specific requirements of the system. In addition, a set of parameter values has been extracted from the simulated curves to implement a SPICE model of the proposed V-JFET transistor. As these devices are expected to operate under very high radiation conditions during the whole experiment life-time, a study of the radiation damage effects and the expected degradation on the device performance is also presented at the end of the paper.Comment: KEYWORDS: Radiation-hard electronics; Voltage distributions; Large detector systems for particle and astroparticle physics. 9 Pages, 7 Figure

The Change of Sales Modes in International Markets: Empirical Results for German and British High-Tech Firms

The choice of the appropriate sales mode belongs to the firm?s most important strategic decisions after entering into a foreign market. Thus, it is important that the selected foreign sales mode best suits a firm?s available resources and capabilities. However, these resources and capabilities change over time. Therefore, it might be necessary for a firm to adjust its foreign sales mode to these changing firm-specific conditions. Using a longitudinal data set of newly founded technology-based firms in Germany and the UK, this paper applies logistic regressions and analyses empirically the probabilities of changing between the two sales modes most frequently used by the sampled exporters: direct exports and exporting via an intermediary. The estimation results confirm the importance of the firm?s physical and intangible resources as well as the influence of transaction-specific assets on a sales mode change. However, the effects of the latter factors might be dominated by strategic considerations that are not covered by our data. For example, a young high-tech firm will resort to an intermediary regardless of its resources and transaction-specific assets if this is the only way of coming into contact with foreign customers. --High technology industries,internationalisation,sales modes

Pulsar State Switching from Markov Transitions and Stochastic Resonance

Markov processes are shown to be consistent with metastable states seen in pulsar phenomena, including intensity nulling, pulse-shape mode changes, subpulse drift rates, spindown rates, and X-ray emission, based on the typically broad and monotonic distributions of state lifetimes. Markovianity implies a nonlinear magnetospheric system in which state changes occur stochastically, corresponding to transitions between local minima in an effective potential. State durations (though not transition times) are thus largely decoupled from the characteristic time scales of various magnetospheric processes. Dyadic states are common but some objects show at least four states with some transitions forbidden. Another case is the long-term intermittent pulsar B1931+24 that has binary radio-emission and torque states with wide, but non-monotonic duration distributions. It also shows a quasi-period of $38\pm5$ days in a 13-yr time sequence, suggesting stochastic resonance in a Markov system with a forcing function that could be strictly periodic or quasi-periodic. Nonlinear phenomena are associated with time-dependent activity in the acceleration region near each magnetic polar cap. The polar-cap diode is altered by feedback from the outer magnetosphere and by return currents from an equatorial disk that may also cause the neutron star to episodically charge and discharge. Orbital perturbations in the disk provide a natural periodicity for the forcing function in the stochastic resonance interpretation of B1931+24. Disk dynamics may introduce additional time scales in observed phenomena. Future work can test the Markov interpretation, identify which pulsar types have a propensity for state changes, and clarify the role of selection effects.Comment: 25 pages, 6 figures, submitted to the Astrophysical Journa

Modeling Copper Price: A Regime-Switching Approach

This paper explores the virtues of Markov-Switching models to characterize the behavior of copper price. In particular, we study the performance of several univariate specifications of this type of models, both in and out of sample, comparing them also with constant parameter models such as ARMA and GARCH. The main finding is that allowing for a regime-switching variance in the error term is most relevant in explaining the behavior of this price.