1,893 research outputs found

    Asymmetry in Leader Image Effects and the Implications for Leadership Positioning in the 2010 British General Election

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    Using national survey data on voters' perceptions of party leaders during the 2010 British general election campaign, we use logistic regression analysis to explore the association between specific image attributes and overall satisfaction for each leader. We find attribute-satisfaction relationships differ in some respects between the three main party leaders, demonstrating that leader image effects are not symmetrical across leaders. We find evidence that negative perceptions have more powerful effects on satisfaction than positive ones, implying that parties should seek to determine a leader's image attribute perceptions measured against the public's expectations of them on the same dimensions. The positions that campaigners ought then to choose are those that will have the most beneficial effect in encouraging voting behaviour for each particular leader or discouraging voting behaviour for an opponent

    Losing Weight: A KECK Spectroscopic Survey of the Massive Cluster of Galaxies RX J1347-1145

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    We present a sample of 47 spectroscopically confirmed members of RX J1347-1145, the most luminous X-ray cluster of galaxies discovered to date. With two exceptions, all the galaxies in this sample have red B-R colors and red spectral indices, with spectra similar to old local ellipticals. Using all 47 cluster members, we derive a mean redshift of 0.4509\pm 0.003, and a velocity dispersion of 910\pm130 km/sec, which corresponds to a virial mass of 4.4 x 10^{14} h^{-1} Solar masses with an harmonic radius of 380 h^{-1} kpc. The derived total dynamical mass is marginally consistent with that deduced from the cluster's X-ray emission based on the analysis of ROSAT/ASCA images (Schindler et al. 1997), but not consistent with the more recent X-ray analyses of Allen (2000), Ettori, Allen & Fabian (2001) and Allen, Schmidt & Fabian (2002). Furthermore, the dynamical mass is significantly smaller than that derived from weak lensing (Fischer & Tyson 1997) and from strong lensing (Sahu et al. 1998). We propose that these various discrepant mass estimates may be understood if RX J1347-1145 is the product of two clusters caught in the act of merging in a direction perpendicular to the line of sight, although there is no evidence from the galaxy redshift distribution supporting this hypothesis. Even with this hypothesis, a significant part of the extremely high X-ray luminosity must still arise from non-virialized, presumably shocked, gas. Finally, we report the serendipitous discovery of a lensed background galaxy at z=4.083 which will put strong constraints on the lensing mass determination once its counter-image is securely identified.Comment: Minor changes to conform to version accepted by Ap

    Adaptive smartphone-based sensor fusion for estimating competitive rowing kinematic metrics.

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    Competitive rowing highly values boat position and velocity data for real-time feedback during training, racing and post-training analysis. The ubiquity of smartphones with embedded position (GPS) and motion (accelerometer) sensors motivates their possible use in these tasks. In this paper, we investigate the use of two real-time digital filters to achieve highly accurate yet reasonably priced measurements of boat speed and distance traveled. Both filters combine acceleration and location data to estimate boat distance and speed; the first using a complementary frequency response-based filter technique, the second with a Kalman filter formalism that includes adaptive, real-time estimates of effective accelerometer bias. The estimates of distance and speed from both filters were validated and compared with accurate reference data from a differential GPS system with better than 1 cm precision and a 5 Hz update rate, in experiments using two subjects (an experienced club-level rower and an elite rower) in two different boats on a 300 m course. Compared with single channel (smartphone GPS only) measures of distance and speed, the complementary filter improved the accuracy and precision of boat speed, boat distance traveled, and distance per stroke by 44%, 42%, and 73%, respectively, while the Kalman filter improved the accuracy and precision of boat speed, boat distance traveled, and distance per stroke by 48%, 22%, and 82%, respectively. Both filters demonstrate promise as general purpose methods to substantially improve estimates of important rowing performance metrics

    On point estimation of the abnormality of a Mahalanobis index

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    Mahalanobis distance may be used as a measure of the disparity between an individualā€™s profile of scores and the average profile of a population of controls. The degree to which the individualā€™s profile is unusual can then be equated to the proportion of the population who would have a larger Mahalanobis distance than the individual. Several estimators of this proportion are examined. These include plug-in maximum likelihood estimators, medians, the posterior mean from a Bayesian probability matching prior, an estimator derived from a Taylor expansion, and two forms of polynomial approximation, one based on Bernstein polynomial and one on a quadrature method. Simulations show that some estimators, including the commonly-used plug-in maximum likelihood estimators, can have substantial bias for small or moderate sample sizes. The polynomial approximations yield estimators that have low bias, with the quadrature method marginally to be preferred over Bernstein polynomials. However, the polynomial estimators sometimes yield infeasible estimates that are outside the 0ā€“1 range. While none of the estimators are perfectly unbiased, the median estimators match their definition; in simulations their estimates of the proportion have a median error close to zero. The standard median estimator can give unrealistically small estimates (including 0) and an adjustment is proposed that ensures estimates are always credible. This latter estimator has much to recommend it when unbiasedness is not of paramount importance, while the quadrature method is recommended when bias is the dominant issue

    Developmental differences in myocyte contractile response after cardioplegic arrest

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    AbstractAlthough developmental differences in left ventricular function after cardioplegic arrest and rewarming have been postulated, whether differences exist at the level of the myocyte remains unexplored. This project tested the hypothesis that there is a differential effect of hypothermic hyperkalemic cardioplegic arrest with subsequent rewarming on contractile function of immature compared with adult ventricular myocytes. Myocytes were isolated from the left ventricular free wall of five immature and five adult rabbits and incubated for 2 hours in hyperkalemic modified Ringer's solution at 4Ā° C (cardioplegia) or for 2 hours in cell culture medium at 37Ā° C (normothermia). Myocytes were resuspended (ā€œrewarmedā€) in 37Ā° C cell culture medium after the incubation protocol. Normothermic baseline contractile performance was lower in immature, compared with adult, myocytes. Specifically, myocyte shortening velocity was 62 Ā± 4 Ī¼m/sec in immature and 112 Ā± 6 Ī¼m/sec in adult myocytes (p < 0.01). After cardioplegia and rewarming, immature myocyte contractile function was unchanged, whereas adult myocyte contractile function was significantly diminished. For example, myocyte shortening velocity was 65 Ā± 4 Ī¼m/sec in immature and 58 Ā± 3 Ī¼m/sec in adult myocytes (p < 0.01 versus normothermic). Myocyte surface area, which reflects myocyte volume, was increased after cardioplegia and rewarming in adults (3582 Ā± 55 versus 3316 Ā± 46 Ī¼m2, p < 0.01), but remained unchanged in immature myocytes (2212 Ā± 27 versus 2285 Ā± 28 Ī¼m2, p = not significant). These unique findings demonstrate a preservation of myocyte contractile function and volume regulation in immature myocytes after cardioplegic arrest and rewarming. Thus this study directly demonstrates that developmental differences exist in myocyte responses to hypothermic hyperkalemic cardioplegic arrest with subsequent rewarming. (J THORAC CARDIOVASC SURG 1996;111:1257-66

    The Kinetic Sunyaev-Zel'dovich effect as a probe of the physics of cosmic reionization: the effect of self-regulated reionization

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    We calculate the angular power spectrum of the Cosmic Microwave Background (CMB) temperature fluctuations induced by the kinetic Sunyaev-Zel'dovich (kSZ) effect from the epoch of reionization (EOR). We use detailed N-body+radiative transfer simulations to follow inhomogeneous reionization of the intergalactic medium (IGM). For the first time we take into account the "self-regulation" of reionization: star formation in low-mass dwarf galaxies (10^8 M_\sun \lesssim M \lesssim 10^9 M_\sun) or minihalos (10^5 M_\sun \lesssim M \lesssim 10^8 M_\sun) is suppressed if these halos form in the regions that were already ionized or Lyman-Werner dissociated. Some previous work suggested that the amplitude of the kSZ power spectrum from the EOR can be described by a two-parameter family: the epoch of half ionization and the duration of reionization. However, we argue that this picture applies only to simple forms of the reionization history which are roughly symmetric about the half-ionization epoch. In self-regulated reionization, the universe begins to be ionized early, maintains a low level of ionization for an extended period, and then finishes reionization as soon as high-mass atomically-cooling halos dominate. While inclusion of self-regulation affects the amplitude of the kSZ power spectrum only modestly (\sim 10 %), it can change the duration of reionization by a factor of more than two. We conclude that the simple two-parameter family does not capture the effect of a physical, yet complex, reionization history caused by self-regulation. When added to the post-reionization kSZ contribution, our prediction for the total kSZ power spectrum is below the current upper bound from the South Pole Telescope. Therefore, the current upper bound on the kSZ effect from the EOR is consistent with our understanding of the physics of reionization

    Detection of Airborne Biological Particles in Indoor Air Using a Real-Time Advanced Morphological Parameter UV-LIF Spectrometer and Gradient Boosting Ensemble Decision Tree Classifiers

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    We present results from a study evaluating the utility of supervised machine learning to classify single particle ultraviolet laser-induced fluorescence (UV-LIF) signatures to investigate airborne primary biological aerosol particle (PBAP) concentrations in a busy, multifunctional building using a Multiparameter Bioaerosol Spectrometer. First we introduce and demonstrate a gradient boosting ensemble decision tree algorithmā€™s ability to accurately classify laboratory generated PBAP samples into broad taxonomic classes with a high level of accuracy. We then develop a framework to appraise the classification accuracy and performance using the Hellinger distance metric to compare product parameter probability density function similarity; this framework showed that key training classes were sufficiently different in terms of particle fluorescence and morphology to facilitate classification. We also demonstrate the utility of including advanced morphological parameters to minimise inter-class conflation and improve classification confidence, where relying on the fluorescent spectra alone would likely result in misattribution. Finally, we apply these methods to ambient data collected within a large multi-functional building where ambient bacterial- and fungal-like classes were identified to display trends corresponding to human activity; fungal-like classes displayed a consistent diurnal trend with a maximum at midday and hourly peaks correlating to movements within the building; bacteria-like aerosol displayed complex, episodic events during opening hours. All PBAP classes fell to low baseline concentrations when the building was unoccupied overnight and at weekendsPeer reviewe
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