HALOGAS: HI Observations and Modeling of the Nearby Edge-on Spiral Galaxy NGC 4565

We present 21-cm observations and models of the neutral hydrogen in NGC 4565, a nearby, edge-on spiral galaxy, as part of the Westerbork Hydrogen Accretion in LOcal GAlaxieS (HALOGAS) survey. These models provide insight concerning both the morphology and kinematics of HI above, as well as within, the disk. NGC 4565 exhibits a distinctly warped and asymmetric disk with a flaring layer. Our modeling provides no evidence for a massive, extended HI halo. We see evidence for a bar and associated radial motions. Additionally, there are indications of radial motions within the disk, possibly associated with a ring of higher density. We see a substantial decrease in rotational velocity with height above the plane of the disk (a lag) of -40 +5/-20 km/s/kpc and -30 +5/-30 km s/kpc in the approaching and receding halves, respectively. This lag is only seen within the inner ~4.75' (14.9 kpc) on the approaching half and ~4.25' (13.4 kpc) on the receding, making this a radially shallowing lag, which is now seen in the HI layers of several galaxies. When comparing results for NGC 4565 and those for other galaxies, there are tentative indications of high star formation rate per unit area being associated with the presence of a halo. Finally, HI is found in two companion galaxies, one of which is clearly interacting with NGC 4565.Comment: 17 pages, 16 figures, accepted for publication in the Astrophysical Journal, modified affiliatio

Multivariate Location: Robust Estimators And Inference

The sample mean can have poor efficiency relative to various alternative estimators under arbitrarily small departures from normality. In the multivariate case, (affine equivariant) estimators have been proposed for dealing with this problem, but a comparison of various estimators by Massé and Plante (2003) indicated that the small-sample efficiency of some recently derived methods is rather poor. This article reports that a skipped mean, where outliers are removed via a projection-type outlier detection method, is found to be more satisfactory. The more obvious method for computing a confidence region based on the skipped estimator (using a slight modification of the method in Liu & Singh, 1997) is found to be unsatisfactory except in the bivariate case, at least when the sample size is small. A much more effective method is to use the Bonferroni inequality in conjunction with a standard percentile bootstrap technique applied to the marginal distributions

Within Groups Multiple Comparisons Based On Robust Measures Of Location

Consider the problem of performing all pair-wise comparisons among J dependent groups based on measures of location associated with the marginal distributions. It is well known that the standard error of the sample mean can be large relative to other estimators when outliers are common. Two general strategies for addressing this problem are to trim a fixed proportion of observations or empirically check for outliers and remove (or down-weight) any that are found. However, simply applying conventional methods for means to the data that remain results in using the wrong standard error. Methods that address this problem have been proposed, but among the situations considered in published studies, no method has been found that gives good control over the probability of a Type I error when sample sizes are small (less than or equal to thirty); the actual probability of a Type I error can drop well below the nominal level. The paper suggests using a slight generalization of a percentile bootstrap method to address this problem

Pairwise multiple comparison tests when data are nonnormal

Numerous authors suggest that the data gathered by investigators are not normal in shape. Accordingly, methods for assessing pairwise multiple comparisons of means with traditional statistics will frequently result in biased rates of Type I error and depressed power to detect effects. One solution is to obtain a critical value to assess statistical significance through bootstrap methods. The SAS system can be used to conduct step-down bootstrapped tests. The authors investigated this approach when data were neither normal in form nor equal in variability in balanced and unbalanced designs. They found that the step-down bootstrap method resulted in substantially inflated rates of error when variances and group sizes were negatively paired. Based on their results, and those reported elsewhere, the authors recommend that researchers should use trimmed means and Winsorized variances with a heteroscedastic test statistic. When group sizes are equal, the bootstrap procedure effectively controlled Type I error rates.Social Sciences and Humanities Research Counci

A Study of Giant Pulses from PSR J1824-2452A

We have searched for microsecond bursts of emission from millisecond pulsars in the globular cluster M28 using the Parkes radio telescope. We detected a total of 27 giant pulses from the known emitter PSR J1824-2452A. At wavelengths around 20 cm the giant pulses are scatter-broadened to widths of around 2 microseconds and follow power-law statistics. The pulses occur in two narrow phase-windows which correlate in phase with X-ray emission and trail the peaks of the integrated radio pulse-components. Notably, the integrated radio emission at these phase windows has a steeper spectral index than other emission. The giant pulses exhibit a high degree of polarization, with many being 100% elliptically polarized. Their position angles appear random. Although the integrated emission of PSR J1824-2452A is relatively stable for the frequencies and bandwidths observed, the intensities of individual giant pulses vary considerably across our bands. Two pulses were detected at both 2700 and 3500 MHz. The narrower of the two pulses is 20 ns wide at 3500 MHz. At 2700 MHz this pulse has an inferred brightness temperature at maximum of 5 x 10^37 K. Our observations suggest the giant pulses of PSR J1824-2452A are generated in the same part of the magnetosphere as X-ray emission through a different emission process to that of ordinary pulses.Comment: Accepted by Ap

Social heuristics and social roles: Intuition favors altruism for women but not for men

Are humans intuitively altruistic, or does altruism require self-control? A theory of social heuristics, whereby intuitive responses favor typically successful behaviors, suggests that the answer may depend on who you are. In particular, evidence suggests that women are expected to behave altruistically, and are punished for failing to be altruistic, to a much greater extent than men. Thus, women (but not men) may internalize altruism as their intuitive response. Indeed, a meta-analysis of 13 new experiments and 9 experiments from other groups found that promoting intuition increased giving in a Dictator Game among women, but not among men (Study 1). Furthermore, this effect was shown to be moderated by explicit sex role identification (Study 2, N=1,831): the more women described themselves using traditionally masculine attributes (e.g., dominance, independence) relative to traditionally feminine attributes (e.g., warmth, tenderness), the more deliberation reduced their altruism. Our findings shed light on the connection between gender and altruism, and highlight the importance of social heuristics in human prosociality

Preliminary Testing for Normality: Is This a Good Practice?

Normality is a distributional requirement of classical test statistics. In order for the test statistic to provide valid results leading to sound and reliable conclusions this requirement must be satisfied. In the not too distant past, it was claimed that violations of normality would not likely jeopardize scientific findings (See Hsu & Feldt, 1969; Lunney, 1970). Recent revelations suggest otherwise (See e.g., Micceri, 1989; Keselman, Huberty, Lix et al., 1998; Erceg-Hurn, Wilcox, & Keselman, 2013; Wilcox and Keselman, 2003; Wilcox, 2012a, b). Unfortunately the data obtained in psychological investigations rarely, if ever, meet the requirement of normally distributed data (Micceri, 1989; Wilcox, 2012a, b). Consequently, it could be the case that the results from many of the investigations conducted in psychology provide invalid results. Accordingly, authors recommend that researchers attempt to assess the validity of assuming data are normal in form prior to conducting a test of significance (Erceg-Hurn, et al., 2013; Keselman, et al., 1998). Present evidence suggests that a popular fit-statistic, the Kolmogorov-Smirnov test does a poor job of evaluating whether data are normal. Our investigation based on this statistic and other fit-statistics provides a more favorable picture of preliminary testing for normality

Cluster approximations for infection dynamics on random networks

In this paper, we consider a simple stochastic epidemic model on large regular random graphs and the stochastic process that corresponds to this dynamics in the standard pair approximation. Using the fact that the nodes of a pair are unlikely to share neighbors, we derive the master equation for this process and obtain from the system size expansion the power spectrum of the fluctuations in the quasi-stationary state. We show that whenever the pair approximation deterministic equations give an accurate description of the behavior of the system in the thermodynamic limit, the power spectrum of the fluctuations measured in long simulations is well approximated by the analytical power spectrum. If this assumption breaks down, then the cluster approximation must be carried out beyond the level of pairs. We construct an uncorrelated triplet approximation that captures the behavior of the system in a region of parameter space where the pair approximation fails to give a good quantitative or even qualitative agreement. For these parameter values, the power spectrum of the fluctuations in finite systems can be computed analytically from the master equation of the corresponding stochastic process.Comment: the notation has been changed; Ref. [26] and a new paragraph in Section IV have been adde