Learning Bounded Tree-Width Bayesian Networks via Sampling

Learning Bayesian networks with bounded tree-width has attracted much attention recently, because low tree-width allows exact inference to be performed efficiently. Some existing methods [12, 14] tackle the problem by using k-trees to learn the optimal Bayesian network with tree-width up to k. In this paper, we propose a sampling method to efficiently find representative k-trees by introducing an Informative score function to characterize the quality of a k-tree. The proposed algorithm can efficiently learn a Bayesian network with tree-width at most k. Experiment results indicate that our approach is comparable with exact methods, but is much more computationally efficient.

Pharmacy students' use and views on over-the-counter (OTC) medicines; a questionnaire study

Introduction
The role of the pharmacist centers on ensuring the safe and effective use of medicines, including over-the-counter (OTC) medicines. It is important to ascertain pharmacy students’ use and opinions on OTC medicines, given that they are the pharmacists of the future and that this market continues to expand. This study aimed to investigate Queen’s University Belfast (QUB) final year pharmacy students’ use and views on OTC medicines. Scarce work has been conducted in this area to date.

Methods
Following ethical approval and a pilot study, all students (n=155) were invited to participate in a self-completed questionnaire (n=20 questions), distributed at a mandatory class. Descriptive statistics and non-parametric tests (Chi-squared and Mann Whitney U-test) were used for data analyses.

Results
The response rate was 99.4% (154/155). The majority (153/155) reported using OTC medicines; the key consideration during personal product selection was effectiveness. Most [96.1% (147/153)] were in agreement that safety was the over-riding concern during OTC consultations. While 96.1% (149/155) considered that using an evidence-based approach improved the quality of patient care, 68.0% (104/153) would be prepared to sell a product that lacks evidence of effectiveness, provided it would not cause harm.

Conclusions
The importance of evidence of effectiveness was acknowledged, yet many students in this study were prepared to recommend unproven products. Further strategies are required at QUB to ensure this routine consideration alongside safety in practice.

Occupy Differently: Space, Community and Urban Counter-Conduct

This article demonstrates how the concept of counter-conducts helps us understand Occupy by directing attention to the correlation between the way advanced liberalism works to control urban spaces and the way that control is countered through Occupy’s tactics. The first section outlines the term counter-conducts by looking to Foucault’s short and undeveloped theorisation. The second examines how advanced liberalism conducts conduct through the use of urban space, concentrating on London which comes to form a space of and for the mobility and circulation of goods, people and ideas. Occupy’s tactics directly confront and counter such movement while engaging in its own forms of counter-circulation and (im)mobility. The third section examines how advanced liberal techniques have increasingly come to use a particular, heavily instrumentalised understanding of community in order to divide and control urban populations. Occupy’s tactics embody versions of community which confront and oppose such instrumentalisation, ultimately both engaging with that control and partially reproducing it. Through these counter-conducts we can come to a view of Occupy as inevitably succeeding in its failure as a movement and failing in its success, while opening to an (im)possible
futurity of occupying urban space differently.

Re-Reading the Riots: Counter-Conduct in London 2011

The riots that took place in England in August 2011 have widely been described as destructive, senseless and without purpose. This article, taking inspiration from Michel Foucault’s later work on revolt as counter-conduct, argues for a new understanding of how to read political expression and thereby calls for the riots to be thought differently, as a form of counter-conduct. This demands a new appreciation for the possibilities of revolt where spontaneous, impulsive, mundane and non-spectacular events like riots can be construed as political rather than purely criminal. It also opens up possibilities for how we might understand the ethos of the ‘revolting subject’.

Learning Bayesian Networks with Bounded Tree-Width via Guided Search

Bounding the tree-width of a Bayesian network can reduce the chance of overfitting, and allows exact inference to be performed efficiently. Several existing algorithms tackle the problem of learning bounded tree-width Bayesian networks by learning from k-trees as super-structures, but they do not scale to large domains and/or large tree-width. We propose a guided search algorithm to find k-trees with maximum Informative scores, which is a measure of quality for the k-tree in yielding good Bayesian networks. The algorithm achieves close to optimal performance compared to exact solutions in small domains, and can discover better networks than existing approximate methods can in large domains. It also provides an optimal elimination order of variables that guarantees small complexity for later runs of exact inference. Comparisons with well-known approaches in terms of learning and inference accuracy illustrate its capabilities.

Counter-Mappings: Cartography and Difference

Introduction to the co-edited book 'Cartographies of Differences: Interdisciplinary Perspectives