Search Results (4,030)

Advancements in targeted therapies and immunotherapies have improved survival for individuals with metastatic non-small-cell lung cancer (mNSCLC), creating a growing population of Canadians living long-term with the disease. These individuals face ongoing physical, emotional, and practical challenges, yet existing supportive care services are often designed for patients receiving curative intent treatment and may not adequately address the challenges of those undergoing continuous treatment. To explore these experiences and inform the development of supports tailored to their needs, eight participants with mNSCLC completed one-on-one virtual interviews. They described limited support for managing side effects and psychosocial concerns despite general satisfaction with oncology care. Fatigue and cognitive challenges impacted daily functioning, and emotional challenges (e.g., fear of progression, stigma, and difficulty finding meaning) impacted quality of life. Financial burden, including unexpected costs and loss of income, further affected their well-being. Existing supports, such as exercise programs, were viewed positively but were often difficult to access, were offered only short-term, and required patients to find them independently. Recommendations included improved coordination and communication across the healthcare system, alongside tailored interventions such as navigation services, resource directories, health promotion supports, and expanded peer support. Overall, people living long term with mNSCLC face distinct challenges and unmet supportive care needs, highlighting the importance of integrating supportive services into routine oncology care. Full article

Wearable sensors have become valuable tools for assessing gait in both laboratory and free-living environments. However, detection of walking in free-living environments remains challenging, especially in clinical populations. Machine learning models may offer more robust gait identification, but most are trained on healthy participants, limiting their generalizability to other populations. To extend a previously validated machine learning model, an updated model was trained using an open dataset (PAMAP2), before progressively including training datasets with additional healthy participants and a clinical osteoarthritis population. The performance of the model in identifying walking was also evaluated using a frequency-based gait detection algorithm. The results showed that the model trained with all three datasets performed best in terms of activity classification, ultimately achieving a high accuracy of 96% on held-out test data. The model generally performed on par with the heuristic, frequency-based method for walking bout identification. However, for patients with slower gait speeds (<0.8 m/s), the machine learning model maintained high recall (>0.89), while the heuristic method performed poorly, with recall as low as 0.38. This study demonstrates the enhancement of existing model architectures by training with diverse datasets, highlighting the importance of dataset diversity when developing more robust models for clinical applications. Full article

In the contemporary urban context, safety in public space presents profound inequalities linked to gender, especially in the night period. This research explores how the subjective perception of security in the central district of Madrid affects women’s mobility patterns and use of public space. Through a mixed methodology, which combines spatial analysis with sensitive cartographies and collective mapping, it seeks to make visible the conditions of (in)security experienced in the city. The approach adopts a feminist and multi-scalar perspective, ranging from the object to the district scale. The analysis is structured around four layers: mobility, urban environment, green areas and night-time uses. Tools such as Geographic Information Systems were used for the treatment of objective data and qualitative techniques such as interviews and tours accompanied by a set of subjective perceptions. The results show the existence of multiple barriers that condition women’s access to and enjoyment of public space, revealing a discrepancy between what is planned and what is lived. The final considerations anticipate the possibility of replicating the methodology applied in urban planning, proposing future strategies to build safer, more inclusive and sensitive environments to the diversity of their inhabitants. Full article

The deterioration of the global climate and accelerated urbanization have led to intense pressure on surface space resources. As a strategic development field, deep underground space has become a crucial direction for alleviating human habitation pressure. However, current research on deep underground space mostly focuses on fields such as geology and medicine, while the design of habitable environments lacks interdisciplinary integration and systematic approaches. Taking deep underground space as the research object, this study first clarifies the interdisciplinary research context through bibliometric analysis. Then, combined with geological data (ground temperature, groundwater, and ground stress, etc.) from major cities in China, it defines the characteristics of the in situ environment and the characteristics of the development and utilization of deep underground space. By comparing the habitable design experiences of extreme environments, such as space stations, Moon habitats, and desert survival modules, the study extracts five categories of design elements: natural conditions, construction status, social economy, users, and existing resources. Ultimately, it establishes a demand-oriented, five-dimensional habitable design methodology covering in situ environment adaptation, living support, medical and health services, resilience and flexibility, and existing space renovation. This research clarifies the differentiated design strategies for hundred-meter-level and kilometer-level deep underground spaces, providing theoretical support for the scientific development of deep underground space and serving as a reference for habitable design in other extreme environments. Full article

Deep retrofits are one of the few pathways to decarbonize the existing building stock while simultaneously improving climate resilience. These retrofits improve insulation, airtightness, and mechanical equipment efficiency. NRCan’s Prefabricated Exterior Energy Retrofit (PEER) project developed prefabricated building envelope retrofit solutions to enable net-zero performance. The PEER process was demonstrated on two different pilot projects completed between 2017 and 2023. In 2024, in partnership with industry partners, NRCan developed new low-carbon retrofit panel designs and completed a pilot project to evaluate their performance and better understand resiliency and occupant comfort post-retrofit. The Low-Carbon Climate-Resilient (LCCR) Living Lab pilot retrofit was completed in 2024 in Ottawa, Canada, using low-carbon PEER panels. This paper outlines the design and construction for the pilot, including panel designs, the retrofitting process, and post-retrofit building and envelope commissioning. The retrofitting process included the design and installation of new prefabricated exterior retrofitted panels for the walls and the roof. These panels were insulated with cellulose, wood fibre, hemp, and chopped straw. During construction, blower door testing and infrared imaging were conducted to identify air leakage paths and thermal bridges in the enclosure. The retrofit envelope thermal resistance is RSI 7.0 walls, RSI 10.5 roof, and an RSI 3.5 floor with 0.80 W/m²·K U-factor high-gain windows. The measured normalized leakage area @10Pa was 0.074 cm²/m². The net carbon stored during retrofitting was over 1480 kg CO₂. Monitoring equipment was placed within the LCCR to enable the validation of hygrothermal models for heat, air, and moisture transport, and energy, comfort, and climate resilience models. Full article

Psittacine Beak and Feather Disease (PBFD) is a highly contagious viral condition caused by Circovirus parrot—commonly known as Beak and Feather Disease Virus (BFDV)—a small, single-stranded DNA virus of the family Circoviridae. The disease primarily affects parrots (order Psittaciformes) and is characterized by progressive feather dystrophy, beak deformities, immunosuppression, and high mortality rates, particularly in juvenile birds. Although PBFD was initially documented in Australian psittacines, the virus has now attained global distribution, facilitated predominantly by the international trade in live parrots, both legal and illegal. This review provides a comprehensive synthesis of current knowledge on the virology, clinical presentation, molecular epidemiology, and phylogeographic spread of BFDV. Particular attention is given to the role of parrot trade in shaping transmission dynamics and genetic diversification. The review further evaluates existing biosecurity policies, diagnostic challenges, and disease management strategies within both captive and wild avian contexts. Given PBFD’s dual status as a veterinary concern and a growing conservation threat, strengthening international surveillance, regulating wildlife trade, and integrating molecular diagnostics into routine screening are critical priorities. Effective containment of BFDV requires a multidisciplinary approach involving veterinarians, aviculturists, conservation biologists, and policymakers to safeguard the health and genetic viability of endangered psittacine species globally. Full article

This paper presents the first exploration of young carers in early childhood (YCEC), in the context of whole family support, through the application of the Power Threat Meaning Framework (PTMF). Existing contributions to young carer research have shaped social policy, legislation, and practice concerned with whole family approaches to the identification, assessment, and support for young carers globally. To date, the literature has predominantly focused on young carers in middle childhood to young adulthood, contributing to socially constructed Eurocentric ideologies of who young carers are likely to be. As such, YCEC remain disempowered in broader young carer and family science discourse. This qualitative exploration centers upon the experiences of three families. Primary data collated retrospective accounts of two adult siblings supported by documentary data obtained by participants through a subject access request (SAR). Secondary data derived from two case studies, drawn from the lead author’s master’s dissertation, offering experiences of families each with a young carer aged four years old. Participants lived in England, United Kingdom (UK). Deductive analysis utilized dual methodological approaches, offering nuanced insight. Thematic codes were synthesized into predetermined themes. ‘Power,’ ‘threat,’ ‘meaning,’ ‘threat responses,’ and ‘strengths’ to explore the application of the PTMF beyond individual experience. Findings show systemic and structural powers held within the lives of YCEC. This disempowers the ethos of whole family support, which should serve to endorse integrated working and foster the autonomous functioning of family life. Findings consider threats, worsening vulnerabilities, and exposure to harm. Meaning is deduced from findings offering recommendations for future research, practice, and policy decisions. In conclusion, opportunities for the prevention of inappropriate caring roles, early identification, and intervention have been missed. This study adds to the growing exploration of the PTMF. It harnesses its potential application as a holistic assessment tool and qualitative data analysis framework, helping to bridge structural and developmental viewpoints which typically frame the current understanding of family functioning and related social policy. Full article

As the core space for students’ daily living and learning, the quality of the indoor wind environment and air quality in dormitory buildings is particularly critical. However, existing studies often neglect natural ventilation optimization under local climatic conditions and the multidimensional evaluation of health benefits, leaving notable gaps in dormitory design. Under the Healthy China Initiative, the indoor wind environment in university dormitories directly impacts students’ health and learning efficiency. This study selects dormitory buildings in Xuzhou as the research object and employs ANSYS FLUENT 2020 software for computational fluid dynamics (CFD) simulations, combined with orthogonal experimental design methods, to systematically investigate and optimize the indoor wind environment with a focus on healthy ventilation standards. The evaluation focused on three key metrics—comfortable wind speed ratio, air age, and CO₂ concentration—considering the effects of building orientation, corridor width, and window geometry, and identifying the optimal parameter combination. After optimization based on the orthogonal experimental design, the proportion of comfortable wind speed zones increased to 44.6%, the mean air age decreased to 258 s, and CO₂ concentration stabilized at 613 ppm. These results demonstrate that the proposed optimization framework can effectively enhance indoor air renewal and pollutant removal, thereby improving both air quality and the health-related performance of dormitory spaces. The novelty of this study lies in integrating regional climate conditions with a coordinated CFD–orthogonal design approach. This enables precise optimization of dormitory ventilation performance and provides locally tailored, actionable evidence for advancing healthy campus design. Full article

Despite the widespread adoption of network monitoring tools, Managed Service Providers (MSPs), specifically small- and medium-sized enterprises (SMEs), continue to face persistent challenges in achieving predictive, multi-tenant-aware visibility across distributed client networks. Existing monitoring systems lack integrated predictive analytics and edge intelligence. To address this, we propose an AI- and IoT-driven monitoring and visualisation framework that integrates edge IoT nodes (Raspberry Pi Prometheus modules) with machine learning models to enable predictive anomaly detection, proactive alerting, and reduced downtime. This system leverages Prometheus, Grafana, and Mimir for data collection, visualisation, and long-term storage, while incorporating Simple Linear Regression (SLR), K-Means clustering, and Long Short-Term Memory (LSTM) models for anomaly prediction and fault classification. These AI modules are containerised and deployed at the edge or centrally, depending on tenant topology, with predicted risk metrics seamlessly integrated back into Prometheus. A one-month deployment across five MSP clients (500 nodes) demonstrated significant operational benefits, including a 95% reduction in downtime and a 90% reduction in incident resolution time relative to historical baselines. The system ensures secure tenant isolation via VPN tunnels and token-based authentication, while providing GDPR-compliant data handling. Unlike prior monitoring platforms, this work introduces a fully edge-embedded AI inference pipeline, validated through live deployment and operational feedback. Full article

Japanese Encephalitis (JE) is a mosquito-borne viral infection that causes acute brain inflammation. First identified in Japan in 1871, the disease gained renewed global attention in 2025 after emerging in a non-endemic region, raising significant healthcare concerns. Vaccination remains the most effective strategy for preventing outbreaks. However, low- and middle-income countries (LMICs) face considerable challenges in implementing vaccination programs due to geographical, economic, and regulatory barriers. Most existing studies on JE vaccines (JEVs) have been conducted in higher-income countries, leaving critical gaps in data on efficacy and safety in LMIC settings. Furthermore, uncertainties surrounding cost-effectiveness make funding decisions more complex. This narrative review evaluates the current evidence on JE vaccination in LMICs, based on a literature search in PubMed and ScienceDirect covering 2005–2025. The review examines vaccine efficacy, safety, cost-effectiveness, and policy implementation. Findings show that JEVs demonstrate high efficacy and strong safety profiles, with mild adverse effects, most commonly fever. The live attenuated SA 14-14-2 vaccine (LAJEV) is particularly cost-effective, offering substantial economic benefits by reducing healthcare expenditures in endemic regions. To ensure sustainability, vaccination programs in LMICs require tailored policies and targeted financial support. Policy frameworks must be adapted to local contexts, enabling focused, effective, and equitable implementation. Full article

Background/Objectives: Multiple chronic conditions (MCCs) pose global health and social challenges, with caregiving often relying on family members, especially in low- and middle-income countries (LMICs). However, limited evidence exists regarding the factors influencing caregiver contribution (CC) to patient self-care among older adults with MCCs in these settings. Aim: The aim of this study was to examine the associations between caregivers’ and patients’ socio-demographic characteristics and patients’ clinical variables and the CC to patient self-care behaviors in adults with MCCs in an LMIC context. Methods: This multicenter, cross-sectional study included patient–caregiver dyads recruited from outpatient and community settings across Albania, between August 2020 and April 2021. CC was assessed using the Caregiver Contribution to Self-Care of Chronic Illness Inventory scale (CC-SCCII). Three multivariable linear regression models were used to explore associations with the three dimensions of CC to self-care maintenance, monitoring, and management. Results: Caregivers were mostly female, children, or spouses with a high level of education and employed. Patients were primarily female and had low education. Hypertension and diabetes were the most prevalent. Older and employed caregivers contributed less to CC to self-care maintenance, while higher education and caregiving experience increased it. Living with the patient and being a spouse reduced CC to self-care monitoring, whereas more caregiving hours and experience improved it. CC to self-care management was negatively influenced by cohabitation, presence of a second caregiver, and being a spouse, but improved with more caregiving hours. Conclusions: Socio-demographic and caregiving factors differently influence CC to self-care dimensions in older adults with MCCs in an LMIC. Tailored caregiver support programs are essential to enhance caregiver involvement and improve MCC patient outcomes in LMICs. Full article

Background/Objectives: Achondroplasia is the most common skeletal dysplasia, affecting 1 in 25,000 births. Limited research exists on the assessment of functional independence using standardized tools in children and adolescents with achondroplasia. The WeeFIM scale provides a comprehensive evaluation of daily living skills across multiple functional domains. This study aimed to assess the functional independence levels in children and adolescents with achondroplasia using WeeFIM and analyze functional capabilities. Methods: This multicenter cross-sectional study included 46 participants aged 6–18 years with confirmed achondroplasia. Data were collected through standardized WeeFIM assessments from medical centers and online surveys (2021–2024). WeeFIM evaluates 18 functional items across 3 domains: self-care (8 items), mobility (5 items), and cognition (5 items), scored 1–7 (complete dependence to independence). Results: Participants included 26 males (56.5%) and 20 females (43.5%). Most (78.3%) were diagnosed during infancy. The mean functional scores were highest for cognition (34.0/35, 97.1%), followed by self-care (51.2/56, 91.4%) and mobility (31.5/35, 90.0%). Most participants achieved near-complete independence in cognitive functions. Mobility tasks, particularly stair climbing and bathtub transfers, showed the greatest challenges. Functional independence increased with age, with significant improvements during early childhood to adolescence transition. Conclusions: Children and adolescents with achondroplasia demonstrate high functional independence across daily activities, with cognitive abilities largely unaffected. Although specific mobility challenges exist, most participants achieve independence with appropriate accommodations. These findings provide valuable baseline data for clinical care planning and support optimistic functional outcomes for pediatric patients with achondroplasia. Full article

While the ‘smart city’ concept is central to urban innovation, promising enhanced efficiency and livability, this paper interrogates a critical paradox: can cities be ‘smart’ yet ‘unlivable’? Existing indices, such as the IMD Smart City Index and the IESE Cities in Motion Index, while standard references, tend to prioritize technological and economic metrics, potentially failing to fully capture urban quality of life and sustainability. This study presents a preliminary attempt, based on an analysis of scientific literature, to critically examine current smart city indicators and propose a set of alternative indicators more representative of quality of life (QoL) and livability. The objective is not to overturn the rankings of cities like Zurich (high-ranking) and Athens (low-ranking), but to explore how a livability-focused approach, using more representative QoL indicators, might narrow the perceived gap between them, thereby highlighting diverse dimensions of urban performance. This research critically evaluates current smart city rankings. It aims to determine if livability-based indicators, supported by scientific literature, can provide a more balanced view of urban performance. This paper details how these alternative indicators were chosen, justifying their relevance to QoL with scientific support, and maps them to established smart city verticals (Smart Mobility, Smart Environment, Smart Governance, Smart Living, Smart People, Smart Economy). Finally, it outlines future research directions to further develop and validate this human-centric approach. Full article

This article illuminates the cosmology of Raa Haqi (often called Dersim Alevism or Kurdish Alevism), a rarely examined strand within Alevi Studies. Existing scholarship’s emphasis on identity politics and sparse ethnography has left Raa Haqi’s mythological and cosmological dimensions underexplored. This paper approaches Raa Haqi through a dual authority framework: (1) Ocak lineages and Ocak–talip relations—sustained by kinship institutions like kirvelik, musahiplik, and communal rites such as the cem—and (2) jiares, non-human agents from the Batın realm that manifest in Zahir as sacred places, objects, and animals. Methodologically, I conduct a close, motif-based reading of folktales compiled by Caner Canerik (2019, Dersim Masalları I), treating them as ethnographic windows into living theology. The analysis shows that tales encode core principles—rızalık (mutual consent), ikrar (vow), sır (the secret knowledge), fasting and calendrical rites, ritual kinship, and moral economies involving humans, animals, and Batın beings. Dreams, metamorphosis, and jiare-centered orientations structure time–space, ethics, and authority beyond the Ocak, including in individual re-sacralizations of objects and sites. I conclude that these narratives do not merely reflect belief; they actively transmit, test, and renew Raa Haqi’s cosmological order, offering Alevi Studies a theory-grounded, source-proximate account of Kurdish Alevi mythic thought. Full article

Background: Chronic pain affects nearly one in five adults worldwide and is increasingly recognized not only as a disease but as a potential risk factor for neurocognitive decline and dementia. While some evidence supports this association, existing systematic reviews are static and rapidly outdated, and none have leveraged advanced methods for continuous updating and robust uncertainty modeling. Objective: This protocol describes a living systematic review with dose–response Bayesian meta-analysis, enhanced by artificial intelligence (AI) tools, to synthesize and maintain up-to-date evidence on the prospective association between any type of chronic pain and subsequent cognitive decline. Methods: We will systematically search PubMed, Embase, Web of Science, and preprint servers for prospective cohort studies evaluating chronic pain as an exposure and cognitive decline as an outcome. Screening will be semi-automated using natural language processing models (ASReview), with human oversight for quality control. Bayesian hierarchical meta-analysis will estimate pooled effect sizes and accommodate between-study heterogeneity. Meta-regression will explore study-level moderators such as pain type, severity, and cognitive domain assessed. If data permit, a dose–response meta-analysis will be conducted. Living updates will occur biannually using AI-enhanced workflows, with results transparently disseminated through preprints and peer-reviewed updates. Results: This is a protocol; results will be disseminated in future reports. Conclusions: This living Bayesian systematic review aims to provide continuously updated, methodologically rigorous evidence on the link between chronic pain and cognitive decline. The approach integrates innovative AI tools and advanced meta-analytic methods, offering a template for future living evidence syntheses in neurology and pain research. Full article