The Egyptian Cardiothoracic Surgeon (ECTS - E-Journal)
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    Do outside directors influence the financial performance of risk-taking firms? Evidence from the United Kingdom (UK) insurance industry

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    We examine the relation between outside board directors and six measures of financial performance using panel data for 1999-2012 drawn from the UK's property-casualty insurance industry. We find that the proportion of outsiders on the board is unrelated to performance; rather it is outsiders' financial expertise that has the most significant financial performance impact. In addition, superior performance can also be related to the financial expertise of inside directors, thereby reinforcing the importance of board-level financial expertise in the insurance industry. Our results have potential commercial and/or policy implications

    Supporting Democracy in Education (reprint) (in press)

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    Output-based disturbance rejection control for nonlinear uncertain systems with unknown frequency disturbances using an observer backstepping approach

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    This paper is concerned with the output feedback control design for a class of nonlinear uncertain systems subject to multiple sources of disturbances including model uncertainties, unknown constant disturbances, harmonic disturbances with unknown frequency and amplitude. The total disturbances and uncertainties are delicately represented by a compact exogenous model first. By incorporating the adaptive internal model principle, a set of dynamic estimators are developed for both state and disturbance observations. By means of observer backstepping technique, a composite output feedback controller is constructed based on the disturbance and state estimations. The stability of the closed-loop system is rigorously established based on Lyapunov stability criterion. A missile roll stabilization example is finally investigated to validate the effectiveness of the proposed control approach

    Ozonesonde profiles from the West Pacific Warm Pool: measurements and validation

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    We present a series of ozonesonde profiles measured from Manus Island, Papua New Guinea, during February 2014, with new insights on the calibration of ozonesondes for measurements in the tropical troposphere. The experiment formed a part of a wider airborne campaign involving three aircraft based in Guam, to characterise the atmospheric composition above the tropical West Pacific in unprecedented detail. Thirty-nine ozonesondes were launched between 2 and 25 February of which 34 gave good ozone profiles. Particular attention was paid to evaluating the background current of the ozonesondes, as this can amount to half the measured signal in the tropical tropopause layer (TTL). An unexpected contamination event affected the measurements and required a departure from standard operating procedures for the ozonesondes. The most significant departure was not exposing the sondes to ozone during preparation, which meant that the background current remained stable before launch. Comparison with aircraft measurements allows validation of the measured ozone profiles and confirms that for well-characterized sondes (background current ∼  50 nA) a constant background current could be assumed throughout the profile, equal to the minimum value measured during preparation just before launch. From this set of 34 ozonesondes, the minimum reproducible ozone concentration measured in the TTL was 12–13 ppbv; no examples of ozone concentrations  <  5 ppbv, as reported by other recent papers, were measured. The lowest ozone concentrations coincided with outflow from extensive deep convection to the east of Manus, consistent with uplift of ozone-poor air from the boundary layer. However, these minima were lower than the ozone concentration measured through most of the boundary layer, and were matched only by measurements at the surface in Manus

    The Devolution Project in Greater Manchester: Introduction to the Special Issue

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    Introduction Embracing the future is second nature in the North West and Greater Manchester in particular is no stranger to innovation and change—as long ago as the 1600s residents were adopting vegetarianism and their own way of doing things. During the industrial revolution Greater Manchester seized the initiative to become the world’s first modern industrial metropolis. It is home to the nation’s first public library, the birthplace of modern chemistry and the professional football league. It is where Dalton developed atomic theory and Rutherford split the atom. Inevitably it is also where the rainproof mackintosh was invented. (Sirotkin 2015) This quote comes from a blog written by Sirotkin (2015), exploring the implications of devolution for Greater Manchester (GM) for public health, but it also serves to illustrate a wider point: devolution is not just being advocated as a pragmatic solution to current problems, but heralded as fulfilment of Manchester’s destiny as a major city, ‘embracing the future’ and, it is implied, returning to the great days of Victorian England. Apart from the obvious issues with this comparison—not least the fact that Manchester’s Victorian greatness was built upon the backs of the poor (see Snow article, this special issue)—it raises interesting questions about the devolution project and its presentation both internally and to the wider world. Whether or not this project succeeds, and in what terms, are, of course, empirical questions which will need academic attention over the coming years. In this special issue, we set the scene for future work, bringing together academics and practitioners from a variety of fields to raise questions and highlight potential areas of interest. This introduction is intended to set the scene and to provide some context for the current ‘Devo Manc’ agenda

    Paragone: Notes on Hegemony and Realism in the 1950s

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    Snowball sampling for estimating exponential random graph models for large networks

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    The exponential random graph model (ERGM) is a well-established statistical approach to modelling social network data. However, Monte Carlo estimation of ERGM parameters is a computationally intensive procedure that imposes severe limits on the size of full networks that can be fitted. We demonstrate the use of snowball sampling and conditional estimation to estimate ERGM parameters for large networks, with the specific goal of studying the validity of inference about the presence of such effects as network closure and attribute homophily. We estimate parameters for snowball samples from the network in parallel, and combine the estimates with a meta-analysis procedure. We assess the accuracy of this method by applying it to simulated networks with known parameters, and also demonstrate its application to networks that are too large (over 40 000 nodes) to estimate social circuit and other more advanced ERGM specifications directly. We conclude that this approach offers reliable inference for closure and homophily

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