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The shaping of contemporary morality in intimacy decision-making in Britain
No full textIn this paper I aim to draw attention to the continued emphasis on ‘moral tales in stories of family construction. In research projects on both conventional family practices such as marriage and non-conventional ones such as living apart together (LAT) and mixed-sex civil partnerships, morality continues to emerge as a core guiding principle for how relationships are organised and maintained. Yet beyond the importance of children in these moral tales, little consideration is given to the other dimensions and shapes that this ‘morality’ may take. Here I bring together three qualitative research projects to illustrate the strong drive of moral obligations in the face of family fluidity, relationship plurality, and individualised therapeutic discourse. With this data I argue that obligations continue to organise relationship decision-making, and we can imagine these obligations as formed of three interrelated dimensions: (1) social ‘oughts’, formed of culture, norms, and values (e.g., we ought to get married because that is the normal thing to do in our society), (2) relational ‘oughts’, including children, family, friends, life/family course, death, health (e.g., we ought to live apart to protect the children), and (3) individual ‘oughts’, which involve strongly held personal beliefs, and an ethic of self-care (e.g., we ought to get a civil partnership because it aligns with my feminist values). Understanding the shape of contemporary intimate morality is an important step in developing future theory, policy, and practice in the field
Patterns and correlates of physical activity among Nigerian community-dwelling older adults
No full textBackground and aim: Physical inactivity is a common risk factor for morbidity and mortality, particularly among older adults, and its context-specific values and determinants are necessary for informed health policy and programmatic interventions. This study assessed levels and correlates of Physical Activity (PA) among Nigerian community-dwelling older adults. Methods: Adults who were ≥ 65 years old (n = 246) participated in the cross-sectional study. PA was assessed using the International Physical Activity Questionnaire for the Elderly (IPAQ-E) and the Physical Activity Scale for the Elderly (PASE). Correlates of PA were evaluated in terms of functional status, depression, quality of life (QoL), age, and gender. Results: The mean age of the participants was 72.4 ± 7.14 years. Based on IPAQ-E, rates for low, moderate, and high levels of PA were 21.1%, 51.6%, and 27.2% respectively, with higher MET outputs for walking (1177.8 ± 1195.9) and moderate PA (1128.5 ± 1738.9). Based on PASE, PA levels were 82.1% and 17.9% for low and moderate PA, with the highest scores for light housework (19.4 ± 10.4), caregiving (15.7 ± 17.4), and heavy housework (12.1 ± 12.5) activities. The majority (68.7%) of the respondents had higher QoL and mild depression (54.1%). There was a significant association between IPAQ-E and age (χ2 = 16.799; p = 0.020), QoL (χ2 = 9.817; p = 0.010), and instrumental activity of daily living (χ2 = 17.125; p = 0.002). Conclusions: Nigerian community-dwelling older adults engaged in low-to-moderate PA. Socio-demographics and QoL, rather than depression, are significantly associated with PA. Tailored physical activity interventions are necessary to improve depression in this population, as addressing QoL and socio-demographic factors seems to be significantly linked only with PA engagement, more than depressive symptoms
Re: comment on: Miedany et al. response letter: Beyond the symptoms: personalizing giant cell arteritis care through multidimensional patient reported outcome measure. Volume 75, December 2025, 152844
No full textThis correspondence critically discusses the validity of a multidimensional tool published in Seminars in Arthritis and Rheumatism. The authors argue that it fundamentally fails to meet the FDA definition of a Patient-Reported Outcome Measure (PROM), highlighting serious methodological flaws such as the inappropriate mixing of clinical parameters with patient views and a lack of transparency regarding patient involvement. It concludes by urging an independent review to ensure clinical tools adhere to rigorous psychometric standards before adoption
Deep learning for collective anomaly detection
No full textAnomaly detection has been a cornerstone of research across diverse disciplines, remaining a critical and evolving field of study for several decades. While several approaches, including deep learning (DL), have been explored to design general solutions for anomaly detection, there is a lack of structured survey articles on the collective (or group) anomaly detection problem (CAD). This article fills this gap and presents the first comprehensive review dedicated exclusively to DL-based methods for CAD. A two-level taxonomy is proposed to categorize CAD methods based on their underlying algorithms into generative, discriminative, or hybrid, and the methods are further classified according to their DL architecture. The literature review we conducted on CAD reveals that the existing approaches utilizing deep learning address a wide range of applications, including cybersecurity, IoT, and key performance indicators (KPIs). Different application domains of CAD and benchmark datasets are discussed. Moreover, the commonly used datasets for CAD are described and discussed from different application scenarios. Finally, the limitations and drawbacks of the different trends used to solve the problem of CAD are outlined, and the challenges and future research directions are discussed
Patient experiences of radiation-induced menopause in cervical cancer: A scoping review
Get PDFIntroduction Radiation-induced menopause (RIM), a form of premature ovarian insufficiency, is a frequent yet under-recognised consequence of pelvic radiotherapy for cervical cancer. Beyond vasomotor and urogenital symptoms, RIM affects psychological wellbeing, sexual identity, and overall quality of life (QoL). For therapeutic radiographers, understanding survivorship impact is critical to delivering holistic, person-centred care that extends beyond treatment into long-term wellbeing. Methods A scoping review was conducted following PRISMA-ScR guidelines to map literature on experiences, QoL impacts, and supportive interventions for individuals assigned female at birth who developed RIM after external beam radiotherapy, brachytherapy, or chemoradiation for cervical cancer. Searches of PubMed, PsycINFO, Google Scholar, citation lists, and grey literature, were carried out between January–May, 2025, identifying English-language empirical and review studies. Two reviewers independently screened and extracted data, with methodological quality described using the QuADS tool. Results From 528 records, 21 studies (2006–2025) met inclusion criteria. Most focused on cervical cancer survivors from high-income countries, with limited evidence from diverse populations. RIM was consistently linked to high symptom burden and QoL impairment. Survivors reported abrupt, distressing menopausal changes compounded by limited clinician recognition. Hormone replacement therapy (HRT) and multidisciplinary care improved outcomes, yet uptake, communication, and equity gaps remain. Conclusion RIM is a major survivorship issue that remains inconsistently managed and insufficiently researched. Evidence underscores the need for early recognition, inclusive assessment, and proactive involvement of therapeutic radiographers within integrated survivorship pathways to support education and timely intervention. Implications for practice Embedding menopause education, validated PROMs, and sensitive communication within survivorship care can enhance QoL and promote equitable, multidisciplinary support for cervical cancer survivors
Peri-Dyeing: Laser dye fixation for efficient textile colouration and design
No full textConventional textile dyeing remains one of the most resource-intensive stages of garment production, characterised by high water and energy use and the generation of chemically contaminated effluent. This study explores an alternative approach to conventional dyeing through the development and evaluation of a laser dyeing process termed peri-dyeing, a digitally driven, non-contact colouration technique in which dye fixation was initiated by targeted laser irradiation directly at the fibre surface.Optimisation of laser parameters and dye application methods enabled controlled surface colouration of wool fabrics. Colour measurements, SEM imaging, and tensile strength analysis confirmed that high dye fixation efficiencies (82–96%) were achieved without compromising fibre integrity. Standardised testing demonstrated strong wash and rub colour fastness, indicating technical performance compatible with commercial textile applications. Design sampling validated the technique’s ability to produce fine linear detail, smooth tonal gradients, and multicolour imagery on both flat and textured substrates.The peri-dyeing process demonstrates the technical feasibility of a digitally controlled approach to textile colouration that avoids immersion dye baths and enables targeted dye application. The results indicate potential for reduced resource use and increased production flexibility. The paper highlights opportunities for integration into direct-to-garment and on-demand manufacturing contexts, supporting the development of more efficient and adaptable textile colouration workflows
Challenges and opportunities of synthetic data generation for machine learning-based intrusion detection systems in in-vehicle networks
No full textMachine learning-based intrusion detection systems (ML-IDS) for in-vehicle networks require diverse, high-quality datasets that are scarce because of privacy and data collection challenges. Collecting data in the real world often faces challenges, such as a lack of detailed attack scenarios and significant resource requirements. This survey examines synthetic data generation (SDG) as a solution and systematically reviews SDG methods, ML-IDS models, and their intersection in automotive security, which has not been addressed in prior surveys. We introduce a quantitative evaluation framework and apply it to synthetic and real datasets, such as SynCAN (Synthetic Controller Area Network), CAN-MIRGU (CAN Multi-Information Record Generating Unit) and Real ORNL (Oak Ridge National Laboratory) Automotive Dynamometer (ROAD) dataset. The results reveal critical limitations, since current synthetic approaches show reduced identifier coverage and unrealistic temporal patterns. Additionally, spatial network topology analysis reveals that synthetic datasets lack the hierarchical hub-and-spoke communication structures and functional subsystem coupling characteristic of real vehicular networks. Through a comprehensive analysis of more than 50 papers published in the time period from 2018 to 2025, we identified five research gaps, including temporal fidelity preservation, real-time constraints, cross-vehicle generalisation, attack diversity limitations, and quality validation requirements. Although SDG promises to address data scarcity and enable complex attack scenario simulations, current methods inadequately model authentic vehicular communications. We provide guidelines for developing temporally aware generation models and validation frameworks for practical deployment
Divergent impacts of climate change and human activities on vegetation dynamics across land use types in Hunan Province, China
Get PDFTerrestrial ecosystems in Hunan Province have undergone marked yet spatially heterogeneous vegetation changes under concurrent climate change and intensifying human activities. The aim of this study is to resolve how vegetation responses vary among land-use types by quantifying kernel Normalized Difference Vegetation Index (kNDVI) dynamics during 2000–2023 using precipitation, temperature, and solar radiation, coupled with trend analysis and a partial-derivative-based attribution. Mean kNDVI increased overall at 0.0016 yr−1; vegetation improved over 76.30% of the area, whereas 5.72% of the area experienced degradation. Built-up land exhibited the largest degraded fraction (35.04%). Human activities and temperature emerged as the dominant drivers of kNDVI change, contributing 62.25% and 27.92%, respectively, while precipitation (3.08%) and solar radiation (6.77%) played comparatively minor roles. Spatially, human activities primarily controlled vegetation dynamics in plains and urban clusters (~78% of the area), whereas temperature constrained vegetation in high-elevation mountain ranges. Analysis along the human footprint (HFP) gradient reveals that driver composition remains steady in resilient ecosystems (farmland and forest), despite increasing anthropogenic pressure, whereas fragile ecosystems (grassland and bareland) exhibited pronounced volatility and heightened sensitivity to environmental constraints. These findings provide a quantitative basis for developing sustainable ecological security strategies, incorporating region-specific measures such as adaptive afforestation, sustainable agricultural management, and strict ecological protection, to enhance ecosystem resilience by prioritizing the climate resilience of mountain forests and the stability of fragile grassland systems
What is happening in product obsolescence management? Three decades of review from 1993 to 2023
Get PDFAll products are likely to be influenced by obsolescence. The consequences can be serious since an obsolete part or component could raise issues in terms of cost, production, safety, and maintenance. To minimize the impact, strategies must be implemented throughout the product's intended life. This research reviews 188 papers on product obsolescence management published in the past three decades to understand the proposed strategies. Two research questions are addressed: (1) What is the academic landscape of product obsolescence management? (2) What are the main research topics and how are these topics covered by the literature? This work first conducts a bibliometric analysis and then analyzes the existing works under seven topics, i.e., general management, upgrade and replacement, mitigation, monitoring, forecasting, design refresh and strategy, and obsolescence impacts. The key approaches and performed actions are highlighted for each topic. The findings show that a range of products has been covered, whereas electronic hardware still constitutes a large proportion. Meanwhile, attention to software obsolescence has grown. Cost model-based strategies are a key means of obsolescence management, particularly for replacement, mitigation, and monitoring. The findings also reveal the need to consider multiple key aspects when implementing these strategies. Despite considerable research on different strategies, challenges remain in developing a long-term vision and techniques for obsolescence management, predicting obsolescence, integrating strategies, and addressing the diverse impacts across industries. Limited research has explored how to identify the most appropriate approach or performed action, and further studies are needed to develop new methods and techniques to manage obsolescence and also to provide systematic guidance for implementing obsolescence management strategies