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Sex-specific independent risk factors of urinary incontinence in acute stroke patients:a multicentre registry-based cohort study
Get PDFBackgroundThe presence of urinary incontinence (UI) in acute stroke patients indicates poor outcomes in men and women. However, there is a paucity and inconsistency of data on UI risk factors in this group and hence we conducted a sex-specific analysis to identify risk factors.MethodsData were collected prospectively (2014–2016) from the Sentinel Stroke National Audit Program for patients admitted to four UK hyperacute stroke units. Relevant risk factors for UI were determined by stepwise multivariable logistic regression, presented as odds ratios (OR) and 95% confidence intervals (CI).ResultsThe mean (±SD) age of UI onset in men (73.9 year ± 13.1; n = 1593) was significantly earlier than for women (79.8 year ± 12.9; n = 1591: p < 0.001). Older age between 70 and 79 year in men (OR = 1.61: CI = 1.24–2.10) and women (OR = 1.55: CI = 1.12–2.15), or ≥80 year in men (OR = 2.19: CI = 1.71–2.81), and women (OR = 2.07: CI = 1.57–2.74)–reference: <70 year–both predicted UI. In addition, intracranial hemorrhage (reference: acute ischemic stroke) in men (OR = 1.64: CI = 1.22–2.20) and women (OR = 1.75: CI = 1.30–2.34); and prestroke disability (mRS scores ≥ 4) in men (OR = 1.90: CI = 1.02–3.5) and women (OR = 1.62: CI = 1.05–2.49) (reference: mRS scores < 4); and stroke severity at admission: NIHSS scores = 5–15 in men (OR = 1.50: CI = 1.20–1.88) and women (OR = 1.72: CI = 1.37–2.16), and NIHSS scores = 16–42 in men (OR = 4.68: CI = 3.20–6.85) and women (OR = 3.89: CI = 2.82–5.37) (reference: NIHSS scores = 0–4) were also significant. Factors not selected were: a history of congestive heart failure, hypertension, atrial fibrillation, diabetes and previous stroke.ConclusionsWe have identified similar risk factors for UI after stroke in men and women including age >70 year, intracranial hemorrhage, prestroke disability and stroke severity
Implementing precision methods in personalizing psychological therapies:Barriers and possible ways forward
Get PDFA WiFi RSS-RTT Indoor Positioning Model Based on Dynamic Model Switching Algorithm
Get PDFThe advances in WiFi technology have encouraged the development of numerous indoor positioning systems. However, their performance varies significantly across different indoor environments, making it challenging in identifying the most suitable system for all scenarios. To address this challenge, we propose an algorithm that dynamically selects the most optimal WiFi positioning model for each location. Our algorithm employs a Machine Learning weighted model selection algorithm, trained on raw WiFi RSS, raw WiFi RTT data, statistical RSS & RTT measures, and Access Point line-of-sight information. We tested our algorithm in four complex indoor environments, and compared its performance to traditional WiFi indoor positioning models and state-of-the-art stacking models, demonstrating an improvement of up to 1.8 meters on average
Epistemic Violence and Colonial Legacies in the Representation of Refugee Women:Contesting Narratives of Vulnerability and Victimhood
Get PDFThe traditional drafting and subsequent implementation of international refugee law have been criticised for relying on a male-centric understanding of persecution. Whilst this framework has recently shifted to include a more gender-sensitive interpretation, I argue that this introduction of gender within refugee status determination has traditionally relied on narratives infused with gendered and racialised stereotypes. In particular, it relies on a ‘white saviour’ colonial narrative that perceives refugee women as vulnerable victims in need of saving. Drawing on a decolonial and critical epistemological analysis that includes both a race and gender dimension, I unpack the epistemic violence and hidden colonial legacies in the representation of refugee women in case-law. Ultimately, this article concludes with a call for reframing the legal narrative around refugee women by approaching them as political actors rather than oppressed and vulnerable subjects
Priorities for HIV and chronic pain research: results from a survey of individuals with lived experience
Get PDFThe Global Task Force on Chronic Pain in HIV published seven research priorities in the field of HIV-associated chronic pain in 2019: (1) causes; (2) management; (3) treatment individualization and integration with addiction treatment; (4) mental and social health factors; (5) prevalence; (6) treatment cost effectiveness; and (7) prevention. The current study used a web-based survey to determine whether the research topics were aligned with the priorities of adults with lived experiences of HIV and chronic pain. We also collected information about respondents’ own pain and treatment experiences. We received 311 survey responses from mostly US-based respondents. Most respondents reported longstanding, moderate to severe, multisite pain, commonly accompanied by symptoms of anxiety and/or depression. The median number of pain treatments tried was 10 (IQR = 8, 13), with medications and exercise being the most common modalities, and opioids being viewed as the most helpful. Over 80% of respondents considered all research topics either “extremely important” or “very important”. Research topic #2, which focused on optimizing management of pain in people with HIV, was accorded the greatest importance by respondents. These findings suggest good alignment between the priorities of researchers and US-based people with lived experience of HIV-associated chronic pain
Exploring the impact of digital humans on customer experience
Get PDFThis ongoing work focuses on the virtual technology of digital humans, specifically on the potential impacts on customer experience. It starts by introducing the development of a believability framework for digital humans, emphasizing the interactions between behaviour, personality, appearance, and environment to enhance their realism. The framework aims to alleviate the "uncanny valley" effect and improve consumer interaction by making digital humans more lifelike and emotionally intelligent. The study employs a design science research approach, creating digital humans as student ambassadors in a university scenario, and has undergone three iterations, including interviews with university faculty and staff, co-creative workshops with students, and field experiments. The goal is to conduct empirical tests to refine the framework, thus enhancing customer experience in a virtual world environment.<br/
Revisiting Sex, Class and Realism:British Cinema 1956-1963
Get PDFThis article looks back at the context in which Sex, Class and Realism: British Cinema 1956–1963 was written, the issues it addressed and some of the influences on it. It then considers some of the criticisms it has received and assesses its contribution to the study of British cinema of this period
A-B Transition in Superfluid <sup>3</sup>He and Cosmological Phase Transitions
Get PDFFirst-order phase transitions in the very early universe are a prediction of many extensions of the Standard Model of particle physics and could provide the departure from equilibrium needed for a dynamical explanation of the baryon asymmetry of the Universe. They could also produce gravitational waves of a frequency observable by future space-based detectors such as the Laser Interferometer Space Antenna. All calculations of the gravitational wave power spectrum rely on a relativistic version of the classical nucleation theory of Cahn-Hilliard and Langer, due to Coleman and Linde. The high purity and precise control of pressure and temperature achievable in the laboratory made the first-order A to B transition of superfluid 3He ideal for test of classical nucleation theory. As Leggett and others have noted, the theory fails dramatically. The lifetime of the metastable A phase is measurable, typically of order minutes to hours, far faster than classical nucleation theory predicts. If the nucleation of B phase from the supercooled A phase is due to a new, rapid intrinsic mechanism that would have implications for first-order cosmological phase transitions as well as predictions for gravitational wave production in the early universe. Here we discuss studies of the A-B phase transition dynamics in 3He, both experimental and theoretical, and show how the computational technology for cosmological phase transition can be used to simulate the dynamics of the A-B transition, support the experimental investigations of the A-B transition in the QUEST-DMC collaboration with the goal of identifying and quantifying the mechanism(s) responsible for nucleation of stable phases in ultra-pure metastable quantum phases
Application of artificial intelligence in cognitive load analysis using functional near-infrared spectroscopy:A systematic review
Get PDFCognitive load theory suggests that overloading of working memory may negatively affect the performance of human in cognitively demanding tasks. Evaluation of cognitive load is a difficult task; it is often assessed through feedback and evaluation from experts. Cognitive load classification based on Functional Near-InfraRed Spectroscopy (fNIRS) is now one of the key research areas in recent years, due to its resistance of artefacts, cost-effectiveness, and portability. To make fNIRS more practical in various applications, it is necessary to develop robust algorithms that can automatically classify fNIRS signals and less reliant on trained signals. Many of the analytical tools used in cognitive sciences have used Deep Learning (DL) modalities to uncover relevant information for mental workload classification. This review investigates the research questions on the design and overall effectiveness of DL as well as its key characteristics. We have identified 45 studies published between 2011 and 2023, that specifically proposed Machine Learning (ML) models for classifying cognitive load using data obtained from fNIRS devices. Those studies were analyzed based on type of feature selection methods, input, and DL model architectures. Most of the existing cognitive load studies are based on ML algorithms, which follow signal filtration and hand-crafted features. It is observed that hybrid DL architectures that integrate convolution and LSTM operators performed significantly better in comparison with other models. However, DL models especially hybrid models have not been extensively investigated for the classification of cognitive load captured by fNIRS devices. The current trends and challenges are highlighted to provide directions for the development of DL models pertaining to fNIRS research
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