136986 research outputs found
Sort by
Biopsychosocial prognostic indicators in Functional Neurological Disorder: A systematic review
No full textBACKGROUND: Functional Neurological Disorder (FND) may result in significant disability. Biopsychosocial and contextual factors contributing to health outcomes in FND remain unclear. PURPOSE: To ascertain the current evidence relating to biopsychosocial and contextual factors of prognostic relevance in adults with FND. METHODS: A systematic review was conducted. Studies of adults with FND were included. Methodological quality was assessed using the Joanna Briggs Institute checklist for cohort studies. A best-evidence synthesis approach was applied to consider the quantity and consistency of findings. Outcomes measured were mapped to the biopsychosocial domains of the International Classification of Functioning, Disability and Health framework. FINDINGS: The search yielded 6019 references. Thirty studies (3000 participants) examining 2309 people with FND met inclusion criteria. Ten were deemed high methodological quality and 17 medium quality. Biologically, age was unrelated to outcomes. Psychologically, a history of psychiatric treatment, somatisation and alexithymia were associated with negative outcomes. Socially, there was strong evidence that workforce participation was associated with better outcomes. Seizure frequency and illness duration were characteristics unrelated to outcomes. Factors associated with an individual were examined more often than broader systemic contextual factors. CONCLUSIONS: This review summarises existing knowledge around biopsychosocial prognostic indicators of recovery in adults with FND. Workforce participation is associated with better health outcomes in FND. A change in seizure frequency may not translate to participation in life roles. There was limited research investigating the impact of systemic contextual factors. A more consistent approach in this research area would further reveal the true state of phenomena
The landscape of violence against left-behind women in rural China: prevalence estimates and associated factors
No full textBACKGROUND AND OBJECTIVES: Violence against women (VAW) is a critical public health issue, yet the experiences among left-behind women in rural China-resulting from rapid urbanisation-are largely overlooked. This study aimed to uncover the prevalence of VAW within this specific population and identify associated factors. METHODS: A cross-sectional survey was conducted in Henan Province, China, in July 2023. A multistage stratified random sampling method was used to recruit rural left-behind women. Data on VAW were collected through validated questionnaires. To establish the full landscape of violence they might experience, VAW was assessed as intimate partner violence (IPV) and non-partner violence (NPV). As a new form of IPV, remote-IPV was also assessed. Prevalence estimates for various forms, types and specific items of violence were presented as frequencies with corresponding percentages. Random forest combined logistic regression was used to explore the associated factors of VAW. RESULTS: Among 1516 eligible rural left-behind women, the median age was 52.0 years (IQR: 43.0-57.0). Overall, 31.1% reported experiencing VAW in their lifetime, of which 28.2% reported IPV, 5.4% reported remote-IPV and 7% reported NPV. In their past life, physical abuse (19.9%) was the most commonly reported IPV type, social abuse (3.3%) was the most commonly reported remote-IPV type and emotional abuse (5.9%) was the most commonly reported NPV type. VAW was significantly associated with advanced age (OR: 1.04, 95% CI: 1.02 to 1.06, p<0.001), marital dissatisfaction (OR: 3.42, 95% CI: 2.00 to 6.05, p<0.001) and husband's high-risk lifestyle behaviours (ORs varying from 1.37 to 2.59), including playing card, fighting and quarrelling history. CONCLUSIONS: VAW is highly prevalent and remains a significant serious public health problem for rural left-behind women in China. Depicting the landscape of VAW forms and types is beneficial to deeply understand the magnitude of the violence and to monitor the progress in addressing VAW
Romantic Jealousy, Intimate Partner Violence, and Envy: An Ethnographic Study of Acid Attacks in Cambodia
No full textAcid attacks are generally considered to be a pernicious expression of gender-based violence (GBV) and a global health issue that until recently mainly affected countries in Africa, South and Southeast Asia, and Latin America. However, little is known about the cultural contexts for acid attacks and, in particular, the culture-gender intersect. In Cambodia, the first publicly reported case took place in 1999, and attacks have continued since then. This study aims to identify the cultural construction and meaning of acid attacks from the inside out to provide evidence to guide culturally acceptable interventions. Ethnographic fieldwork was conducted with survivors, their families, and perpetrators in towns and villages across Cambodia, representing 88 cases of acid attacks. Qualitative analysis was conducted to identify the cultural beliefs related to the perceived causes and significance of acid attacks. The "cultural attractors" driving acid attacks are based on Khmer Buddhist beliefs such as karmic links between perpetrator and their target, inherited endowment, character, the Buddhist "triple poison," zodiacal birth status, astrological incompatibility of a couple, and moral blindness. One group of attacks can be seen as gender-based, either triggered by romantic jealousy or in the context of intimate partner violence. A second group, triggered by envy, is not gender-based and arises as a result of community conflict and inequity. The analysis of conceptual metaphors can enrich our understanding of the complex emotions of romantic jealousy and envy. The cultural lens enriches an intersectoral understanding of violence, including GBV, wherein local Buddhist "cultural attractors" explain the cruelty of perpetrators and the suffering of survivors. Further research can inform the cultural responsiveness of multidisciplinary interventions involving trauma-informed Buddhist therapy
Computational Design of Materials for Sintering: Challenges and Prospects
No full textThis study discusses strategies and challenges for computational design of sintered materials. In this context, the importance of fast acting reduced order models to efficiently explore the multi-dimensional design space of materials is highlighted. The study also presents an example of a reduced order model for designing pre-alloyed powders that can be densified by using super-solidus liquid phase sintering. The design exercise is based on an integrated computational materials engineering (ICME) framework involving genetic algorithm to optimize the chemical composition of high-speed steels (HSS) to simultaneously improve the sintering response and the resultant properties. Thermodynamic simulations, based on the CALPHAD method, are used to establish microstructural constraints through phase stability at equilibrium. Results of the design exercise in comparison with conventional alloys are presented. We show that new HSS alloys with improved sintering performance can be designed while simultaneously enhancing their performance properties
Enhancing cognitive accessibility in assessments for children with neurodisability: development and implementation of an adaptation tracking questionnaire
No full textPURPOSE: The range of impairments in children with neurodisability (ND) complicates data collection, yet individualising materials and procedures could enable more children to self-report. This study introduces the Cognitive Accessibility Tracking Questionnaire (CATQ), designed to monitor changes enhancing accessibility ("adaptations") in interview-administered patient-reported outcome measures (PROMs). The CATQ is used in a longitudinal study of mental health and participation in children with ND investigating adaptation use and its utility in assessing the risk of bias introduced by these adaptations. MATERIALS AND METHODS: The 13-item CATQ was developed with experts in ND and augmentative and alternative communication. Predictors of PROM adaptations were analysed using linear regression; the overall change was tested with a t-test and item-specific agreement with Cohen's weighted kappa and proportion of agreement. RESULTS: Six interviewers conducted 69 interviews, interviewing 43 children once or twice. Common adaptations included explaining/replacing concepts (56.5% of interviews), exemplifying (60.9%), or repeating questions/instructions (50.7%). Child age, seizure history, verbal communication abilities, adaptive behaviour, and interviewer identity predicted adaptation use. Adaptation use did not differ between the two data collection points, 13 months apart. CONCLUSION: The CATQ enhances methodological rigor by tracking adaptations and facilitating risk-of-bias-assessment by analysing adaptation changes and factors affecting their use
Treatment-Refractory Tracheobronchitis in Crohn's Disease: A Rare Pulmonary Manifestation of Inflammatory Bowel Disease
No full textLarge airway inflammation is a rare and under-recognised pulmonary manifestation of Crohn's disease. It is associated with significant morbidity and occurs independent of intestinal disease activity. Inflammation of the trachea and bronchi in inflammatory bowel diseases is typically responsive to corticosteroids or anti-tumour necrosis factor agents. In this report, we present a case of tracheobronchitis in Crohn's disease presenting with a chronic productive cough while on adalimumab. The diagnosis was made by bronchoscopy, which revealed inflammation of the trachea and main bronchi, with biopsies demonstrating squamous cell metaplasia consistent with pulmonary inflammatory bowel disease. The patient was unable to be weaned off steroids and, in the presence of an elevated fractional expired nitric oxide, dupilumab was trialled, which resulted in minimal improvement in his symptoms
Chronic Disease Management to Enhance Medication Adherence Trajectories in Long-Term Survivors of Stroke: A Population-Based Cohort Study
No full textPURPOSE: Although chronic disease management (CDM) has been reported to improve medication adherence after stroke or transient ischaemic attack (TIA), the impact on specific patterns of medication adherence is unclear. We aimed to evaluate the population effect of receiving a CDM claim on trajectories of medication adherence in long-term survivors of stroke/TIA. METHODS: A cohort study was undertaken using observational data from PRECISE (42 Australian Stroke Clinical Registry hospitals [Victoria and Queensland; 2012-2015] linked with medication dispensing and primary care claims). Community-dwelling adults with ≥ 1 primary care visit were included. The exposure was a CDM claim (versus no claim) in primary care within 7-18 months post-stroke/TIA. Medication adherence (antihypertensive, antithrombotic, lipid-lowering) was assessed between 19 and 30 months post-stroke/TIA, using group-based trajectory models. Average treatment effects were estimated using multi-level logistic regression with inverse probability treatment weights. RESULTS: Among 11 580 survivors of stroke/TIA (median age 70 years, 42% female; 45% with CDM claim), four distinct adherence patterns were identified: near-perfect adherence, high adherence, declining adherence, and non-use. After adjustment, having a CDM claim (vs no claim) promoted near-perfect adherence (odds ratio [OR]: 1.16 [95% CI 1.08-1.25]) for antithrombotic medications. Whereas, having a CDM claim (vs no CDM claim) promoted high adherence for antihypertensive (OR: 1.33 [95% CI 1.24-1.44]) or lipid-lowering (OR: 1.26 [95% CI 1.16-1.37]) medications. The odds of non-use were also reduced by 17%-23% in those with (vs without) a CDM claim. CONCLUSIONS: CDM claims were associated with favourable trajectories of medication adherence in long-term survivors of stroke/TIA
Urban heat in global cities and the role of nature-based solutions in mitigating future climate risks
No full textAbstract
Approximately eight billion people are living on Earth today with more than half (55%, ∼4.2 billion) living in cities—a proportion predicted to increase to 70% (∼6.6. billion) by 2050. As the human population grows, urban residents will face increasingly extreme temperatures under future climate change, which will affect human well-being, health, and mortality. However, nature-based solutions offer promising strategies to mitigate these impacts. Here, we analyst future projections of the maximum temperature of the warmest month, as a proxy for extreme heat exposure across 5646 cities in 218 countries. We show that by mid-century, this climate metric is projected to increase by an average of +1.7 °C (± 0.5 °C), with the largest increases (∼4 °C) projected to occur in mid-to-high latitude cities of Europe, North America, and Australia. We highlight the urgent need to adopt nature-based solutions to mitigate projected increases in urban heat and contribute to net-zero CO2 emissions goals
Emergent BAX-mutated clonal hematopoiesis after venetoclax-based therapy for breast cancer
No full textAxle-Based Vehicle Classification Utilising FMCW Side-Fire Tracking Radar
No full text© 2025 Victor Roger Jerzy DevilleAccurate axle-based vehicle classification underpins road safety, congestion management, roadway design, and efforts to decarbonise freight. Most existing axle counters rely on invasive sensors, such as piezoelectric strips, inductive loops, or weigh-in-motion platforms, that disrupt the road surface and incur high installation and maintenance costs. To address these limitations, this thesis presents, to the best of our knowledge, the first pole-mounted, side-firing FMCW radar system for fully non-invasive axle classification aligned with the 12-bin \textit{Austroads} standard.
A central contribution of this work is the use of time–frequency analysis at a fixed range bin to isolate the micro-Doppler signature of passing vehicles. Based on this analysis, we developed two radar-based approaches for vehicle axle classification: a model-based method and a data-driven method.
In the model-based approach, the bulk Doppler signal is first modelled to estimate vehicle length across a wide range of speeds. The residual micro-Doppler signature, induced by the rotational motion of the wheels, is then analysed to infer axle count and spacing. These features are then combined to assign the vehicle to an Austroads axle class.
To investigate whether learning-based methods can extract similar information directly from the spectrogram, a parallel data-driven pipeline is developed. A truncated ResNet-18 model is fine-tuned on synthetic spectrograms and evaluated on real-world data. This approach also relies on the micro-Doppler patterns embedded in the spectrogram to learn discriminative features for classification. Both methods are verified on a labelled dataset collected from highway traffic to demonstrate their effectiveness in real-world conditions, with simulations used to explore the effects of controlled parameters such as radar-vehicle relative position, speed, range, and signal-to-noise ratio.
Results indicate that non-invasive, weather-resilient radar systems can deliver axle-based classification accuracies approaching road authority standards. This suggests that, with further refinement, the technology could serve as a practical alternative to traditional invasive sensors, supporting scalable deployment for traffic monitoring, infrastructure maintenance, emissions reduction, and improved road safety without compromising roadway integrity