Strategy Alternatives for Homeland Air and Cruise Missile Defense

Air and cruise missile defense of the U.S. homeland is characterized by a requirement to protect a large number of critical assets nonuniformly dispersed over a vast area with relatively few defensive systems. In this article, we explore strategy alternatives to make the best use of existing defense resources and suggest this approach as a means of reducing risk while mitigating the cost of developing and acquiring new systems. We frame the issue as an attacker‐defender problem with simultaneous moves. First, we outline and examine the relatively simple problem of defending comparatively few locations with two surveillance systems. Second, we present our analysis and findings for a more realistic scenario that includes a representative list of U.S. critical assets. Third, we investigate sensitivity to defensive strategic choices in the more realistic scenario. As part of this investigation, we describe two complementary computational methods that, under certain circumstances, allow one to reduce large computational problems to a more manageable size. Finally, we demonstrate that strategic choices can be an important supplement to material solutions and can, in some cases, be a more cost‐effective alternative.     

A mixture of experts latent position cluster model for social network data

Social network data represent the interactions between a group of social actors. Interactions between colleagues and friendship networks are typical examples of such data.The latent space model for social network data locates each actor in a network in a latent (social) space and models the probability of an interaction between two actors as a function of their locations. The latent position cluster model extends the latent space model to deal with network data in which clusters of actors exist — actor locations are drawn from a finite mixture model, each component of which represents a cluster of actors.A mixture of experts model builds on the structure of a mixture model by taking account of both observations and associated covariates when modeling a heterogeneous population. Herein, a mixture of experts extension of the latent position cluster model is developed. The mixture of experts framework allows covariates to enter the latent position cluster model in a number of ways, yielding different model interpretations.Estimates of the model parameters are derived in a Bayesian framework using a Markov Chain Monte Carlo algorithm. The algorithm is generally computationally expensive — surrogate proposal distributions which shadow the target distributions are derived, reducing the computational burden.The methodology is demonstrated through an illustrative example detailing relationships between a group of lawyers in the USA.     

The Benefits of Dispositional Mindfulness in Physical Health: A Longitudinal Study of Female College Students

Abstract

Objective: This article examines the relationship between dispositional mindfulness, health behaviors (eg, sleep, eating, and exercise), and physical health. Participants: Participants included 441 college women. Methods: Women completed self-report surveys at the beginning and end of a 10-week academic quarter. The study was conducted over 5 academic quarters from fall 2008 to fall 2010. Results: Findings indicated that higher levels of dispositional mindfulness were related to healthier eating practices, better quality of sleep, and better physical health. Dispositional mindfulness contributed to better physical health even after controlling for traditional health habits. Finally, bidirectional mediational relationships were found between healthy eating and dispositional mindfulness as well as between sleep quality and dispositional mindfulness when physical health was the outcome variable. Conclusions: Findings suggest that incorporating mindfulness training into programming on college campuses may be beneficial, as results indicate that dispositional mindfulness is related to positive physical health among college students.     

News Media Coverage of Islam and Muslims in Australia: An Opinion Survey among Australian Muslims

Existing research has explored the ways the mainstream news media covers Muslims and Islam, but few studies have examined Muslims’ reactions to this reporting. Studies that have investigated this issue have identified that the responses of Muslims to news media coverage tend to be largely negative because of the lack of Muslim news sources, the stereotypical representation of Muslims in news coverage, the portrayal of Muslims as the enemy within, and the conflation of Muslims with terrorism. This paper further explores the attitudes of Muslims to news media coverage of Islam and Muslims by drawing on data from 14 focus groups (N?=?104 participants) conducted with Australian Muslims. Similar to previous research, findings reveal that Australian Muslims are highly critical of news media coverage of Islam and Muslims and express concern about the divisiveness that such portrayal can have for Australian society. However, the study participants also had positive comments to make about the news media. Possible solutions to negative news media portrayals of Muslims are considered.     

Using Simulations to Enhance Interprofessional Competencies for Social Work and Nursing Students

There is an increased emphasis on interprofessional education in the healthcare field, including social work. This paper discusses the design and implementation of an innovative idea in teaching that brings social work and nursing students together for skill development to do interprofessional work. Computer generated mannequin simulations have been used extensively in teaching medical, nursing, pharmacy, and other healthcare professions, but are a relatively new pedagogical tool in social work. Using the four interprofessional competencies put forward by the interprofessional collaborative, the authors describe the objectives, the cases utilized, the process of simulations, the technique of debriefing, and the themes that emerged from these reflective observations.     

Son preference in rural China: patrilineal families and socioeconomic change

This article draws on a survey conducted in six provinces in summer 2008 to investigate the determinants of son preference in rural China. The analysis confirms the conventional wisdom that son preference is embedded within patrilineal family structures and practices. We extend our analysis by exploring specific aspects of variation within patrilineal family culture. We find that the patrilineal group (clan) composition of villages and family participation in practices such as building ancestral halls and updating genealogies significantly influence son preference. Yet even though son preference is embedded within patrilineal family culture, our analysis suggests that over time the attenuation of son preference is likely. This is because determinants associated with socioeconomic change—for instance, higher levels of education, direct exposure to official policy education materials, higher income (a proxy for rural industrialization), and agricultural mechanization—all attenuate son preference. Being younger and female are also associated with weaker son preference, and both characteristics are likely to interact with education and industrialization to further dilute son preference in the longer term. Nevertheless, our findings suggest that concerted efforts are needed to ameliorate institutional discrimination against rural people in welfare provisioning and in labor markets, and to promote multiple dimensions of gender equality, including in land rights, wage rates, and education.     

Variable Selection for Qualitative Interactions

In this article we discuss variable selection for decision making with focus on decisions regarding when to provide treatment and which treatment to provide. Current variable selection techniques were developed for use in a supervised learning setting where the goal is prediction of the response. These techniques often downplay the importance of interaction variables that have small predictive ability but that are critical when the ultimate goal is decision making rather than prediction. We propose two new techniques designed specifically to find variables that aid in decision making. Simulation results are given along with an application of the methods on data from a randomized controlled trial for the treatment of depression.