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Down and Out in Birmingham and Leeds: Thinking the Lumpenproletariat in the Films of Penny Woolcock
Get PDF Portrayals of working-class people have long been part of British culture, be it in art, literature, music, theatre, photography, film or television. Perhaps the most notable shift in terms of how the working class are depicted in British film and television in recent years has been the increasing attention paid to what is variously known as the ‘impoverished underclass’, the ‘undeserving poor’, the ‘social residuum’ or the ‘lumpenproletariat’. Drawing on the current resurgence of working-class studies in the social sciences and humanities, this article rethinks these social categories in and through several films of Penny Woolcock that focus on ‘estates culture’ in the inner cities of Birmingham and Leeds. In so doing, this article suggests that, whilst filmed over twenty-odd years ago, Woolcock’s Macbeth and Tina Trilogy remain timely and apposite filmic representations in terms of thinking the idea of the lumpenproletariat in contemporary Britain. </jats:p
Feasibility of human ethomic biomarkers for the diagnosis and monitoring of hip osteoarthritis.
Get PDFRadiographic imaging is typically used to diagnose osteoarthritis (OA). However, patients would typically be sent for imaging after they present to a physician because of joint pain. By this time, the condition is likely irreversible. This study aims to determine if human ethomics (i.e. behavior) defined by whole-body kinematics during walking, can be used as a diagnostic biomarker of hip OA. Three-dimensional motion capture was performed on 106 participants with unilateral hip OA and 80 asymptomatic participants (N = 80) during walking. Sixteen sagittal plane joint angle variables were extracted and used as inputs into the prediction model. The categorical outcome was the radiographic severity of hip OA using the Kallgren-Lawrence (KL) scale (0 [no OA], 2, 3, 4[worse]). Functional data boosting was used for statistical modelling with bootstrap resampling. Our ethomics approach to hip OA diagnosis had positive likelihood ratio (LR+) values ranging from 4.79 (95 %CI 3.20, 7.42) to detect the presence of KL3, to 43.95 (95 % CI 14.9, 76.08) to detect the presence of any OA. The present approach had negative likelihood ratio (LR-) values ranging from 0.56 (95 %CI 0.33, 0.79) of 0.07 (95 %CI 0.04, 0.11) to detect the absence of KL4, to 0.07 (95 %CI 0.04, 0.11) to detect the absence of any OA. Human ethomics represents an ideal candidate for OA biomarkers that could overcome many of the logistical challenges of traditional imaging and biochemical biomarkers
Non-intrusive hardware-enhanced anomaly detection systems for embedded devices
No full textThe integrity of billions of embedded devices is threatened by adversarial attacks, environmental factors, architectural flaws and programming bugs. Conventional defences are largely class-specific: signature checking for adversarial attacks; error-checking memory for environmental faults; OS-level patches for architectural flaws; and static analysis for software defects. In contrast, anomaly detection provides threat-agnostic coverage, recognising deviations from a known safe behaviour or behavioural specification, independent of the root cause. This thesis explores hardware-enhanced anomaly detection in embedded devices, aiming to overcome challenges arising from the behavioural complexity of programs, the large amount of trace produced by processors and the non-linearity of trace data, facilitating non-intrusiveness (to avoid harmful delays), responsiveness (for timely detection), determinism (for consistency) and flexibility (for specialised use-cases), a set of traits identified in this work as desirable in a monitoring system but often missing in existing solutions. This work investigates non-security-related CPU registers for security purposes, measuring the suitability of hardware performance counters for anomaly detection and general-purpose registers for program execution partitioning. The first technical chapter evaluates machine learning algorithms (one-class SVM, local outlier factor, isolation forest, n-grams) on low-level CPU trace data, revealing the need for a trace reduction method, facilitating consistent data collection. Subsequent chapters introduce a HW/SW co-design (establishing the trace reduction requirement for non-intrusive monitoring) and a Fine-grained CPU-state-based Trace Qualification (FCSTQ) method, which partitions execution depending on selected bits of values constituting the current CPU-state, such as program counter, instruction and general purpose registers. The first study compares FCSTQ against periodic and every n-instruction sampling, showing it collects 8.3 and 9.6 times more consistent data, respectively. The second study evaluates automatic detection of regular, infrequent CPU-state events and contrasts it with control-flow-graph-based partitioning, which tends to yield irregular triggers. FCSTQ achieved an 8.6 times reduction in trace volume and an 11.2 times smaller worst-case observational gap. Both studies used the EEMBC Automotive 1.1 benchmark, chosen for its prior adoption in related work and modular composition. The final technical chapter amends the FCSTQ with programmable actions and dedicated memory, forming the Anomaly-detection-oriented Micro-scale Processing (AMP) system, allowing FCSTQ conditions to perform arithmetic operations and depend on their outcomes. This novel mechanism is capable of verifying adherence to a behavioural specification in hardware through independent background computation, as well as leveraging the trace reduction to enable non-intrusive anomaly detection in software, bridging a gap between performant but rigid hardware-based monitoring methods and relatively slow but flexible software-based monitoring methods
Moral distress within clinical psychology
Get PDFThis thesis explores the phenomenon of moral distress within the field of clinical psychology, a concept originally rooted in nursing but increasingly recognised across healthcare disciplines. Drawing on a scoping review and empirical research, the study investigates the correlates and predictors of moral distress within the UK clinical psychology workforce. The review identifies key contributors to moral distress, including ethical dilemmas, power imbalances, institutional limitations, and socio-political pressures that inhibit practitioners from acting in accordance with their moral or professional values. A quantitative approach was employed, comprising inferential analysis of survey data from a substantial dataset of 200 clinical psychologists and trainees. The results indicated significant positive correlations between moral distress, stress, and the intention to leave the profession. In contrast, moral distress was negatively correlated with job satisfaction. Notably, subscales measuring the frequency of moral distress were significant predictors of increased stress levels, reduced job satisfaction and intent to leave. With trainees reporting higher satisfaction and lower intent to leave than qualified psychologists. Age was negatively associated with levels of moral distress and job satisfaction, and positively associated with intent to leave, indicating that younger individuals reported higher distress, while older individuals reported lower satisfaction and greater turnover intentions. Women reported significantly higher average levels of distress on the level of distress subscale. Findings underscore the importance of addressing both individual and structural sources of moral distress and call for ethical, cultural, and systemic reforms. The thesis contributes to a growing discourse on the moral complexities faced by mental health professionals and highlights implications for training, policy, and clinical supervision
Relational Neuroscience: Insights from hyperscanning research
Get PDFHumans are highly social, typically without this ability requiring noticeable efforts. Yet, such social fluency poses challenges both for the human brain to compute and for scientists to study. Over the last few decades, neuroscientific research in human sociality has witnessed a shift in focus from single-brain analysis to complex dynamics occurring across several brains, posing questions about what these dynamics mean and how they relate to multifaceted behavioural models. We propose the term Relational Neuroscience to collate the interdisciplinary research field devoted to modelling the inter-brain dynamics subserving human connections, spanning from real-time joint experiences to long-term social bonds. Hyperscanning, i.e., simultaneously measuring brain activity from multiple individuals, has proven to be a highly promising technique to investigate inter-brain dynamics. Here, we discuss how hyperscanning can help investigate questions within the field of Relational Neuroscience, considering a variety of subfields, including cooperative interactions in dyads and groups, empathy, social attachment and bonding, and developmental neuroscience. While presenting Relational Neuroscience in the light of hyperscanning, our discussion also takes into account behaviour, physiology and endocrinology to properly interpret inter-brain dynamics in social contexts. We consider the strengths but also the limitations and caveats of hyperscanning to answer questions about interacting brains. The aim is to provide an integrative framework for future work to build better theories across a variety of contexts and research subfields to model human sociality
Dystopian Literature and Classical Social Theory: Aldous Huxley and Max Weber’s Elective Affinities
No full textDigital transformation of public services: a multi-level analysis of e-government, m-government, and smart government
Get PDFThis thesis examines the impact of digital transformation on public service by analyzing multi levels; e-government, m-government and smart government across three papers. The first paper examines the role of external rewards in e-government services adoption in Jordan, extending the Unified Theory of Acceptance and Use of Technology (UTAUT) to include external rewards as an extrinsic motivator, using national survey data, the results revealed that external rewards significantly increase citizens’ likelihood of e-government adoption when moderated by demographics and digital skills. The second paper explores how the citizen sentiment toward the national m-government application in Jordan is affected by media announcements, mandatory adoption, and different stages of the app development, by analyzing over 10,000 user reviews through sentiment analysis, topic modeling, regression, and fsQCA, it shows that app improvements and positive media framing enhance the public sentiment, while mandatory adoption raises resistance. The third paper investigates why countries lag behind AI implementation despite their AI readiness, proposing an extended TOE-G framework that incorporates governance alongside technology, organization, and environment, using data from 77 countries, the results revealed that while technological and environmental factors drive AI implementation, excessive governance may negatively affect the progress. Collectively, these papers contribute to the literature on e-government, m-government, and smart government by offering multi-level insights for policymakers to improve the adoption of public services
Neuroadaptive Admittance Control for Human-Robot Interaction With Human Motion Intention Estimation and Output Error Constraint
Get PDFHuman-robot interaction (HRI) is a crucial component in the field of robotics, and enabling faster response, higher accuracy, as well as smaller human effort, is essential to improve the efficiency, robustness, and applicability of HRI-driven tasks. In this article, we develop a novel neuroadaptive admittance control with human motion intention (HMI) estimation and output error constraint for natural and stable interaction. First, the interaction force information of the robot is utilized to predict the HMI and the stiffness in the admittance model is dynamically updated based on surface electromyography (sEMG) signals of the human upper limb to achieve human-like compliance. Then, based on the designed error transformation mechanism, an innovative prescribed performance control (PPC) is proposed that allows the trajectory error to converge to the given constraint range within a predefined time for any bounded initial conditions, thus enabling the robot to maintain a comprehensive performance of moving in the desired direction as guided by the human. Also, an adaptive neural network (NN) is employed to compensate for the uncertainty of robotics systems to improve the tracking accuracy further. According to the Lyapunov stability analysis criterion, our approach ensures that all states of the closed-loop system remain globally uniformly ultimately bounded. Finally, a series of real-world robot experiments demonstrate the effectiveness of the proposed framework
This conversation is about race: exploring Educational Psychologists’ experiences of promoting racial equity
Get PDFRacism remains a deeply embedded systemic feature of the UK education system, shaping the everyday experiences of Black and Global Majority Heritage children and young people. Although legislation, policies, and professional guidance influenced by sociopolitical movements have sought to challenge institutional racism, racial inequities continue to manifest in the practices and outcomes of school communities. These enduring disparities highlight the need for critical reflection and systemic transformation, underpinned by Critical Race Theory and a Critical Realist paradigm, to better understand and disrupt the structures that sustain them. This qualitative study addresses a gap in the literature concerning the applied practice of educational psychology. It explores two interrelated concerns: how anti-racist practice (ARP) is enacted and sustained within Local Authority (LA) Educational Psychology Services, and the conceptual ambiguities surrounding the promotion of racial equity (PRE) in education. Eight LA Educational Psychologists participated in in-depth, semi-structured interviews, analysed through an iterative process of Reflexive Thematic Analysis. Four overarching themes were constructed to represent how participants navigated their roles, agency, and ethical commitments to PRE within interconnected personal, relational, and institutional contexts. Participants’ accounts illustrated that engagement with PRE was shaped through ongoing reflexivity, ethical tension, and the influence of leadership and team cultures, alongside the embedded dynamics of whiteness within professional norms. The analysis attends to the affective, relational, and situated nature of this work, affirming that ARP is contextually produced within wider systems of power, culture, and structural constraint