Women Living with a Traumatic Brain Injury in Prison; Self- and Public Stigma

Traumatic brain injury has been referred to as a silent epidemic in correctional services and little is known about how women with traumatic brain injury experience stigma and the possible intersects of this with other aspects of their lives. This study explored the experience of women in prison living with a traumatic brain injury and the impact of internalized/self-stigma and stigma in the prison context (public stigma). Thirteen women in prison took part in semi-structured interviews. Three themes were generated through reflexive thematic analysis. The first two – psychological distress of living with a traumatic braininjury in prison and living in the system with invisible disability – set out contexts of self- and public stigma of traumatic brain injury, intersecting with the stigma of being a woman in prison and with trauma histories relating to injury cause.These are underpinned by the third theme, wanting to be understood. Self-stigma of women in prison with a traumatic brain injury is a barrier to support seeking and intersects with difficulties in talking about the traumatic circumstancesthat led to the injuries. Systemic responses to traumatic brain injury and trauma for women in prison are required to support risk reduction and mental health recovery

An activities expansion of the transition polynomial of a multimatroid

The weighted transition polynomial of a multimatroid is a generalization of the Tutte polynomial. By defining the activity of a skew class with respect to a basis in a multimatroid, we obtain an activities expansion for the weighted transition polynomial. We also decompose the set of all transversals of a multimatroid as a union of subsets of transversals. Each term in the decomposition has the structure of a boolean lattice, and each transversal belongs to a number of terms depending only on the sizes of some of its skew classes. Further expressions for the transition polynomial of a multimatroid are obtained via an equivalence relation on its bases and by extending Kochol's theory of compatible sets.We apply our multimatroid results to obtain a result of Morse about the transition polynomial of a delta-matroid and get a partition of the boolean lattice of subsets of elements of a delta-matroid determined by the feasible sets. Finally, we describe how multimatroids arise from graphs embedded in surfaces and apply our results to obtain an activities expansion for the topological transition polynomial. Our work extends results for the Tutte polynomial of a matroid

Terra Metaphora:How Game Mechanics Communicate Narrative Information to Players

This thesis seeks to explore some of the ways game mediate representative and narrative information to players via their game mechanics, suggesting that game mechanics embody games’ unique form of narrative discourse. Previous attempts to reconcile and model the storytelling function of narrative games have taken disparate approaches that are not compatible with “classical” narratological models traditionally developed for the analysis of other narrative media, such as film and written prose. This research identifies some of the problems with “exceptional” treatment of games as narrative objects and proposes a model of narrativity for games more in line with other narrative texts. This “classical” model is then used as the basis for several “post-classical” narratological analyses to identify specific game mechanics and describe how games uniquely work to construct audience understanding of key narrative elements such as character, time, space, and plot. This is done through close textual analyses of several games, particularly role-playing games. These are identified here to be excellent sites of both narrative and ludic (game-like) content, and which employ both in concert in intricate ways to narrative effect. In addition to a written thesis, this research takes the form of PhD-by-practice, incorporating a custom-built video game designed to demonstrate, elaborate on, and inform the written material. The game, Terra Metaphora, is built to manipulate its own textual fabric to draw attention to the clandestine ways video game rules, systems, and procedures help craft story

“With Time and Space, I Can Be Me”: Black and Minority Ethnic Perspectives of the Role of Ethnicity and Social Identity in an Inpatient High Secure Setting

There is an increased number of inpatients in High Secure Forensic Hospitals from Black, Asian and Minority Ethnic (BAME) backgrounds and an under representation of research in this area. This project aimed to explore the lived experiences of these patients in a UK High Secure Hospital (HSPS) specifically in relation to their social and ethnic identity, if and how this is considered by staff in their treatment plans and understanding of perceived threat in the system. 7 semi structured interviews were conducted. A Reflexive Thematic Analysis was conducted and revealed four themes of i) intergenerational trauma ii) racial assumptions and misperceptions iii) identity as a form of sanctuary, and iii) perceived impact of ethnicity on care. Participants spoke of the negative impacts of colonisation, and historical and present racist public attitudes on their mental health. Racial assumptions and misperceptions were found to perpetuate ongoing stress and mistrust in mental health systems and staff at the HSPS which impacted on their identity and recovery. When aspects of social and ethnic identity were considered, this facilitated trust and pathed the way for recovery. Additionally, service users made calls for further representation of BAME professionals in the HSPS and a want for advocacy in early stages of admission. Findings indicate that BAME service users need enhanced support from staff through cultural competence, recognition of social and ethnic identity in assessments and treatment plans, and peer support from service users with lived experiences. Future calls for research could consider the efficacy of considering social and ethnic identities at assessment, the impact of racial trauma and the impact on treatment outcomes through Experts by Experience (EbE) advocates. Strengths and limitations are discussed. <br/

Going Beyond the Ordinary — User Perceptions of the Impact of Multisensory Elements on Presence in Virtual Reality at the Royal Opera House

This exploratory study investigates the relative impacts of incorporating additional sensory- and embodiment-enhancing elements into virtual reality (VR) experiences beyond standard headset features, including vibrating floors, blowing wind, accurately rendered hands, free-roam walking and seeing avatars of real people; the outcome is sometimes called a hyper-reality experience. After taking part in the ‘Current Rising’ immersive experience at the Royal Opera House, 726 participants completed a survey examining the different perceived impacts the various additional elements were thought to have on presence. Blowing wind and free-roam walking were thought to be most impactful on presence, followed by floor vibration (contrary to expectations), along with seeing avatars. Conversely, virtual hands were thought to exhibit the least influence, despite being rendered with greater detail and precision than those commonly found in standard VR applications. Past VR experience only minimally affected these reported impacts, suggesting that hyper-reality experiences introduce novel elements even to experienced users. By looking at the perceived impact on presence over a rich, holistic range of factors (multisensory elements, virtual bodies, prior experience and enjoyment) in a real-world cultural experience, these findings offer practical guidance for immersive experience designers and researchers to optimise presence. Future research should explore more nuanced assessments of presence and consider non-correlational experimental designs that mitigate various highlighted potential biases and confounding factors

A Comparative Analysis of Machine Learning Based Power Flow Study with Custom Made Open Source Python Codes

Power flow analysis is a cornerstone of power system planning and operation, involving the solution of nonlinear equations to determine the steady-state operating conditions of the power grid. Traditionally, these equations are solved using iterative methods, which, despite their accuracy, are computationally intensive, may not converge to the solution and involve high time and space complexity. The challenges above can be overcome using Machine Learning (ML). Consequently, in this paper, a comprehensive comparative analysis of different ML algorithms developed for solving the power flow equations are presented. Experimental simulations for IEEE 3-bus and IEEE 118-bus networks have been conducted using custom-developed, open-source Python codes and technical insights are highlighted