Understanding Law Enforcement Mental Health Communication and Police Officers’ Mental Health Support Preferences: A Grounded Theory Study

Throughout the United States, police officers experience cumulative stress and their mental health-related concerns often remain unaddressed. Recently, police departments have begun to offer more mental health support resources in an attempt to mitigate this issue. However, the underutilization of such support is a serious problem. The overall goal of this dissertation is to develop a grounded theory of mental health communication in law enforcement. Employing a constructivist grounded theory approach, data were collected in two sequential phases. Phase one involved 48 in-depth semi-structured interviews with active and retired police officers to examine how the messages police officers receive from society, police departments, and interpersonal relationships shape their perceptions of mental health. Guided by the findings in phase one, a one-time anonymous online survey was completed by 58 additional active police officers to further explore their preferences for mental health-related communication in receiving support and information about available resources in phase two. The theory explains and illustrates how two potential routes, involving multiple layers of influence, can shape police officers\u27 views of mental health and support seeking. Theoretically, this dissertation extends our current understanding of disclosure decisions and the role of communication in officers\u27 willingness to seek mental health support. The grounded theory presented in this dissertation also yields several practical implications for policymakers, department leadership, and families of vi police officers. Moreover, the grounded theory provides a foundation for building a more comprehensive explanation of mental health communication in first responder professions

Process of designing robust, dependable, safe and secure software for medical devices: Point of care testing device as a case study

This article has been made available through the Brunel Open Access Publishing Fund.Copyright © 2013 Sivanesan Tulasidas et al. This paper presents a holistic methodology for the design of medical device software, which encompasses of a new way of eliciting requirements, system design process, security design guideline, cloud architecture design, combinatorial testing process and agile project management. The paper uses point of care diagnostics as a case study where the software and hardware must be robust, reliable to provide accurate diagnosis of diseases. As software and software intensive systems are becoming increasingly complex, the impact of failures can lead to significant property damage, or damage to the environment. Within the medical diagnostic device software domain such failures can result in misdiagnosis leading to clinical complications and in some cases death. Software faults can arise due to the interaction among the software, the hardware, third party software and the operating environment. Unanticipated environmental changes and latent coding errors lead to operation faults despite of the fact that usually a significant effort has been expended in the design, verification and validation of the software system. It is becoming increasingly more apparent that one needs to adopt different approaches, which will guarantee that a complex software system meets all safety, security, and reliability requirements, in addition to complying with standards such as IEC 62304. There are many initiatives taken to develop safety and security critical systems, at different development phases and in different contexts, ranging from infrastructure design to device design. Different approaches are implemented to design error free software for safety critical systems. By adopting the strategies and processes presented in this paper one can overcome the challenges in developing error free software for medical devices (or safety critical systems).Brunel Open Access Publishing Fund

Mastering the Master Space

Supersymmetric gauge theories have an important but perhaps under-appreciated notion of a master space, which controls the full moduli space. For world-volume theories of D-branes probing a Calabi-Yau singularity X the situation is particularly illustrative. In the case of one physical brane, the master space F is the space of F-terms and a particular quotient thereof is X itself. We study various properties of F which encode such physical quantities as Higgsing, BPS spectra, hidden global symmetries, etc. Using the plethystic program we also discuss what happens at higher number N of branes. This letter is a summary and some extensions of the key points of a longer companion paper arXiv:0801.1585.Comment: 10 pages, 1 Figur

Genetic algorithms for feature selection and weighting

Abstract Automated techniques to optimise the retrieval of relevant cases in a CBR system are desirable as a way to reduce the expensive knowledge acquisition phase. This paper concentrates on feature selection methods that assist in indexing the case-base, and feature weighting methods that improve the similarity-based selection of relevant cases. Two main types of method are presented: filter methods use no feedback from the learning algorithm that will be applied; wrapper methods incorporate feedback and hence take account of learning bias. Wrapper methods based on Genetic Algorithms have been found to deliver the best results with a tablet design application, but these generic methods are flexible about the criterion to be optimised, and should be applicable to a wide variety of problems. Introduction The majority of CBR systems rely on a good case-base organisation, an effective index and a (possibly knowledge intensive) similarity matching to select cases, that can then be used to solve a problem, see Many CBR tools provide standard means of constructing indexes. Isoft's ReCall is typical in using a C4.5 [Quinlan 1993] generated decision tree, constructed from the cases in the case-base, as the index. However, induction algorithms like C4.5 apply a greedy selection approach and so the features used by the index are not always the optimal ones. This is a particular problem when the cases contain many features irrelevant to the problem solving The cases identified by the index are next ranked according to their similarity to the new problem. The simplest similarity metric is Euclidean distance between normalised feature vectors. However, a "useful" (from the point of view of solving a problem) similarity should take account of the relative importances of various features. Certainly in a situation where many features are irrelevant to the problem to be solved, a simple similarity measure is insufficient. This problem can be partially solved by identifying and removing irrelevant features as before. However, a more flexible method assigns weights to the features to indicate their relative importance to the problem solving. Although the selection of the relevant features can usually be done quite accurately by an expert, feature weighting can only be done approximately by an expert, often by categorising the relevance as one from a small set of possible degrees of relevance. Therefore, applying an automated algorithm to find feature weights is attractive. Section 2 reviews feature selection and weighting methods. Our tablet formulation problem domain is introduced in Section 3

Consultant-2: pre- and post processing of machine learning applications.

The knowledge acquisition bottleneck in the development of large knowledge-based applications has not yet been resolved. One approach which has been advocated is the systematic use of Machine Learning (ML) techniques. However, ML technology poses difficulties to domain experts and knowledge engineers who are not familiar with it. This paper discusses Consultant-2, a system which makes a first step towards providing system support for a pre- and post-processing methodology where a cyclic process of experiments with an ML tool, its data, data description language and parameters attempts to optimize learning performance. Consultant-2 has been developed to support the use of Machine Learning Toolbox (MLT), an integrated architecture of 10 ML tools, and has evolved from a series of earlier systems. Consultant-0 and Consultant-1 had knowledge only about how to choose an ML algorithm based on the nature of the domain data. Consultant-2 is the most sophisticated. It, additionally, has knowledge about how ML experts and domain experts pre-process domain data before a run with the ML algorithm, and how they further manipulate the data and reset parameters after a run of the selected ML algorithm, to achieve a more acceptable result. How these several KBs were acquired and encoded is described. In fact, this knowledge has been acquired by interacting both with the ML algorithm developers and with domain experts who had been using the MLT toolbox on real-world tasks. A major aim of the MLT project was to enable a domain expert to use the toolbox directly; i.e. without necessarily having to involve either a ML specialist or a knowledge engineer. Consultant's principal goal was to provide specific advice to ease this process

Resilience and Leadership in Dangerous Contexts

Daniel B. Cnossen was born and raised in Topeka, growing up on a small farm. He spent his childhood reading, running, playing sports, and working on the farm. Cnossen enrolled in the United States Naval Academy in 1998. He had never before seen the ocean and did not know how to swim, but he asked his new friends at the academy to teach him; he would often skip lunch to spend time in the pool. Cnossen joined the Navy triathlon team to strengthen his swimming. By his senior year, he had been elected captain of the team, which he helped lead to a national championship. After graduation, he headed to San Diego to undergo training as a Navy SEAL. Cnossen served several tours overseas. On September 6, 2009, less than thirty-six hours on the ground in Kandahar, Afghanistan, he activated a landmine, losing both legs and suffering internal injuries. Lieutenant Cnossen is now back in the United States facing new challenges. He is doing so with the same dedication and enthusiasm that he used to surmount previous challenges. He is positive and appreciative of his friends and family, and he is happy to be alive. Described by some as stoic, Cnossen is seen by those who know him best as soft-spoken and humble. No one as full of curiosity, zest, and humor as he is could be described as stoic. As Cnossen began his rehabilitation, he noted that now he would be able to do even more pull-ups. While at the Walter Reed Army Medical Center, Cnossen and other troops were visited by President Barack Obama. As the president was leaving, he noticed a copy of War and Peace on Cnossen\u27s bedside table. The two men joked that merely lifting the book would be another form of physical therapy

Resilience and Leadership in Dangerous Contexts

Daniel B. Cnossen was born and raised in Topeka, growing up on a small farm. He spent his childhood reading, running, playing sports, and working on the farm. Cnossen enrolled in the United States Naval Academy in 1998. He had never before seen the ocean and did not know how to swim, but he asked his new friends at the academy to teach him; he would often skip lunch to spend time in the pool. Cnossen joined the Navy triathlon team to strengthen his swimming. By his senior year, he had been elected captain of the team, which he helped lead to a national championship. After graduation, he headed to San Diego to undergo training as a Navy SEAL. Cnossen served several tours overseas. On September 6, 2009, less than thirty-six hours on the ground in Kandahar, Afghanistan, he activated a landmine, losing both legs and suffering internal injuries. Lieutenant Cnossen is now back in the United States facing new challenges. He is doing so with the same dedication and enthusiasm that he used to surmount previous challenges. He is positive and appreciative of his friends and family, and he is happy to be alive. Described by some as stoic, Cnossen is seen by those who know him best as soft-spoken and humble. No one as full of curiosity, zest, and humor as he is could be described as stoic. As Cnossen began his rehabilitation, he noted that now he would be able to do even more pull-ups. While at the Walter Reed Army Medical Center, Cnossen and other troops were visited by President Barack Obama. As the president was leaving, he noticed a copy of War and Peace on Cnossen\u27s bedside table. The two men joked that merely lifting the book would be another form of physical therapy

Romantic Partner Interference and Psychological Reactance in the Context of Caregiving for an Aging Family Member

Negotiating romantic relational dynamics is inherent to family caregiving situations, which continue to be on the rise in the United States. However, despite evidence that family caregiving duties are linked to a variety of negative relational outcomes, limited research examines communication processes that contribute to or alleviate the burden of caregiver duties on romantic relationships. Guided by psychological reactance theory (PRT), this study examined the link between romantic partner interference with family caregiving duties and the reactance process, as well as directness of communication about irritation as a type of freedom restoration behavior associated with reactance. Adults caring for aging family members recruited from MTurk (N = 187) completed an online survey as part of a larger study of romantic partner communication surrounding family caregiving. Results using PROCESS serial mediation indicated that greater partner interference was related to heightened perceptions of freedom threat, which was positively associated with the experience of reactance, which in turn was associated with communication about irritation. However, the association between reactance and directness of communication about irritation was negative, the opposite direction of what was hypothesized. Implications for PRT and interventions with caregivers and their romantic partners are discussed

On Dimer Models and Closed String Theories

We study some aspects of the recently discovered connection between dimer models and D-brane gauge theories. We argue that dimer models are also naturally related to closed string theories on non compact orbifolds of \BC^2 and \BC^3, via their twisted sector R charges, and show that perfect matchings in dimer models correspond to twisted sector states in the closed string theory. We also use this formalism to study the combinatorics of some unstable orbifolds of \BC^2.Comment: 1 + 25 pages, LaTeX, 11 epsf figure

Debugging knowledge-based applications with a generic toolkit.

Knowledge refinement tools assist in the debugging and maintenance of knowledge based systems (KBSs) by attempting to identify and correct faults in the knowledge that account for incorrect problem-solving. Most refinement systems target a single shell and are able to refine only KBSs implemented in this shell. Our KRUSTWorks toolkit is unusual in that it provides refinement facilities that can be applied to a number of different shells, and is designed to be extensible to new shells. The paper outlines the components of the KRUSTWorks toolkit and how it is applied to faulty KBSs. It describes its application to two real aerospace KBSs implemented in CLIPS and POWER-MODEL to demonstrate its flexibility of application