CaIIKinterstellar observations towards early-type disc and halo stars, abundances and distances of intermediate- and high-velocity clouds

We present Ca II K (lambda(air) = 3933.661 angstrom) interstellar observations towards 20 early-type stars, to place lower distance limits to intermediate- and high-velocity clouds (IHVCs) in their lines of sight. The spectra are also employed to estimate the Ca abundance in the low-velocity gas towards these objects, when combined with Leiden-Dwingeloo 21-cm HI survey data of spatial resolution 0 degrees.5. Nine of the stars, which lie towards IHVC complexes H, K and gp, were observed with the intermediate dispersion spectrograph on the Isaac Newton Telescope at a resolution R = lambda/Delta lambda of 9000 (similar to 33 km s(-1)) and signal-to-noise ratio (S/N) per pixel of 75-140. A further nine objects were observed with the Utrecht Echelle Spectrograph on the William Herschel Telescope at R = 40 000 (similar to 7.5 km s(-1)) and S/N per pixel of 10-25. Finally, two objects were observed in both Ca II K and Na I D lines using the 2D COUDE on the McDonald 2.7-m telescope at R = 35 000 (similar to 8.5 km s(-1)). The abundance of Ca II K {log(10)(A) = log(10)[N(Ca II K)]-log(10)[N(HI)]} plotted against HI column density for the objects in the current sample with heights above the Galactic plane (z) exceeding 1000 pc is found to obey the Wakker & Mathis (2000) relation. Also, the reduced column density of Ca II K as function of z is consistent with the larger sample taken from Smoker et al. (2003). Higher S/N observations than those previously taken towards HVC complex H stars HD 13256 and HILT 190 reinforce the assertion that this lies at a distance exceeding 4000 pc. No obvious absorption is detected in observations of ALS 10407 and HD 357657 towards IVC complex gp. The latter star has a spectroscopically estimated distance of similar to 2040 pc, although this was derived assuming the star lies on the main sequence and without any reddening correction being applied. Finally, no Ca II K absorption is detected towards two stars along the line of sight to complex K, namely PG 1610+529 and PG 1710+490. The latter is at a distance of similar to 700 pc, hence placing a lower distance limit to this complex, where previously only an upper distance limit of 6800 pc was available.

Bracketing: practical considerations in Husserlian phenomenological research

Nursing research leans heavily towards naturalism, with phenomenology commonly adopted. The three main schools of phenomenology used are Husserl's descriptive approach, Heidegger's interpretive hermeneutic approach and the Dutch Utrecht School of phenomenology which combines characteristics of both. Husserl's approach--the description of ordinary human experiences as perceived by each individual--involves four main steps: bracketing, intuiting, analysing and describing. Many phenomenological nurse researchers consciously decide to adopt a Heideggerian approach because of the perceived difficulties in achieving bracketing. This paper examines the concept of bracketing (epoché) and outlines some of the practical considerations when attempting to achieve it.

Min-BDeu and Max-BDeu Scores for Learning Bayesian Networks

This work presents two new score functions based on the Bayesian Dirichlet equivalent uniform (BDeu) score for learning Bayesian network structures. They consider the sensitivity of BDeu to varying parameters of the Dirichlet prior. The scores take on the most adversary and the most beneficial priors among those within a contamination set around the symmetric one. We build these scores in such way that they are decomposable and can be computed efficiently. Because of that, they can be integrated into any state-of-the-art structure learning method that explores the space of directed acyclic graphs and allows decomposable scores. Empirical results suggest that our scores outperform the standard BDeu score in terms of the likelihood of unseen data and in terms of edge discovery with respect to the true network, at least when the training sample size is small. We discuss the relation between these new scores and the accuracy of inferred models. Moreover, our new criteria can be used to identify the amount of data after which learning is saturated, that is, additional data are of little help to improve the resulting model.

Extended Tree Augmented Naive Classifier

This work proposes an extended version of the well-known tree-augmented naive Bayes (TAN) classifier where the structure learning step is performed without requiring features to be connected to the class. Based on a modification of Edmonds’ algorithm, our structure learning procedure explores a superset of the structures that are considered by TAN, yet achieves global optimality of the learning score function in a very efficient way (quadratic in the number of features, the same complexity as learning TANs). A range of experiments show that we obtain models with better accuracy than TAN and comparable to the accuracy of the state-of-the-art classifier averaged one-dependence estimator.