Search Results (785)

The danwei community emerged as a basic socio-spatial unit in China’s urban landscape, primarily constructed in the mid-20th century. Today, amid population aging and the deterioration of service facilities supporting health environment, the mental and physical conditions of danwei residents are increasingly challenged. Through an investigation of the built environment history and physical activity patterns in Community Hua, a typical case of former danwei community in Chengdu, China, this paper indicates that danwei communities have accumulated health-promoting legacies rooted in their historical spatial planning and collective lifestyle. The tangible legacy includes an open space system centered around green facilities, while the intangible legacy encompasses a diverse range of well-organized sports and cultural events. Following the reform of unit society in China in the late 1990s, these health-promoting legacies continue to exist within the danwei communities. Consequently, this study suggests that future renewal of open spaces within danwei neighborhood should be based on community history, thus the spatial legacy benefiting residents’ health can be preserved and utilized. Full article

Osorno volcano (41.1° S, 72 W) is located in the Andean Southern Volcanic Zone. The volcano lies within a national park as part of the protected areas system. This setting provides an opportunity to compare soil microbial communities between sectors with (H) and without (NI) anthropogenic activities within a volcanic territory. To do so, we selected one of the most visited volcanoes in Chilean Patagonia to examine composition, diversity (taxonomic and phylogenetic), and co-presence and mutual exclusion interaction networks between members of volcanic soil bacterial communities. Soil DNA was extracted, and the 16S rRNA gene was analyzed by high-throughput DNA sequencing, followed by taxonomic identification. The most prevalent phylum across all sites (H and NI) was Pseudomonadota, followed by Acidobacteriota, Actinobacteriota, and Chloroflexota. Based on taxonomic and phylogenetic indices, we found that the diversity of bacteria was significantly less in the humanized area than in the non-intervened areas. Beta diversity analysis also revealed a clear separation between humanized and non-intervened soils. Additionally, a decrease in network connectivity was observed at NI sites. Our results provide clear evidence that anthropogenic factors, such as tourism, vehicle parking, and combustion processes, are key drivers shaping bacterial community structure in volcanic soils, with potential consequences for ecosystem health and the capacity to provide ecosystem services. Full article

The rapid proliferation of heterogeneous applications, from latency-critical video delivery to bandwidth-intensive file transfers, poses increasing challenges for modern communication networks. Traditional traffic engineering approaches often fall short in meeting diverse Quality of Experience (QoE) requirements under such conditions. To overcome these limitations, this study proposes a QoE-driven distribution framework for mixed traffic in Software-Defined Networking (SDN) environments. The framework integrates flow categorization, adaptive path selection, and feedback-based optimization to dynamically allocate resources in alignment with application-level QoE metrics. By prioritizing delay-sensitive flows while ensuring efficient handling of high-volume traffic, the approach achieves balanced performance across heterogeneous service demands. In our 15-RSU Mininet tests under service number = 1 and offered demand = 10 ms, JOGAF attains max end-to-end delays of 415.74 ms, close to the 399.64 ms achieved by DOGA, while reducing the number of active hosts from 5 to 3 compared with DOGA. By contrast, HNOGA exhibits delayed growth of up to 7716.16 ms with 2 working hosts, indicating poorer suitability for latency-sensitive flows. These results indicate that JOGAF achieves near-DOGA latency with substantially lower host activation, offering a practical energy-aware alternative for mixed traffic SDN deployments. Beyond generic communication scenarios, the framework also shows strong potential in Intelligent Transportation Systems (ITS), where SDN-enabled vehicular networks require adaptive, user-centric service quality management. This work highlights the necessity of coupling classical traffic engineering concepts with SDN programmability to address the multifaceted challenges of next-generation networking. Moreover, it establishes a foundation for scalable, adaptive data distribution strategies capable of enhancing user experience while maintaining robustness across dynamic traffic environments. Full article

This study explores the impact of public elderly care services on social participation among rural older adults and examines the underlying mechanisms, providing empirical evidence for improving the rural elderly care system and promoting sustainable development in rural aging societies in China. Using four waves of panel data from the China Longitudinal Aging Social Survey (CLASS) (2014–2020), this research focuses on home- and community-based elderly care services. Employing a two-way fixed-effects model and an instrumental variable approach, the study finds that the accessibility of public elderly care services significantly promotes social participation among rural older adults. This result remains robust after conducting various checks, such as replacing outcome variables, altering measurement methods, and adjusting sample sizes. Heterogeneity analysis reveals that the positive effects are more pronounced among older adults with higher education, those co-residing with adult children, and those in more economically developed regions. The accessibility of public elderly care services primarily facilitates social participation by alleviating labor supply constraints, improving mental health, and strengthening the willingness to engage. The findings suggest that improving the accessibility of public elderly care services can significantly enhance social participation and recommend expanding service coverage as a core strategy to promote active aging in rural areas, with a focus on fostering localized models like rural mutual aid and neighborhood care. Additionally, addressing information asymmetry by establishing “village-level public elderly care information service stations” and creating time banks for mutual aid care at the township level could help foster a virtuous cycle of intergenerational support. Full article

In order to reach and maintain hepatitis C virus (HCV) elimination goals, it is imperative to reach marginalized people who do not engage with traditional testing and treatment. Peer-led interventions are effective in engaging such individuals. Studies have demonstrated community pharmacy as a low-threshold setting for HCV testing, but pharmacy teams’ competing demands are a barrier to maximizing potential. This pilot project aimed to assess whether a pharmacy-based peer-led model of HCV testing was implementable, deliverable, able to engage marginalized people, and overcome pharmacy staff constraints. We implemented a peer-led HCV testing service in one community pharmacy in the Midlands, England, providing four focused phases of testing, totalling 198 h, over two years. In total, 591 tests for antibodies or RNA were undertaken, identifying 24 active infections. Subsequent phases retested 20%, 16%, and 11% of those tested in combined preceding phases. In response to feedback, phases 3 and 4 included health screening (blood pressure, cholesterol, diabetes, and nurse-performed Fibroscans^®). We demonstrate engagement and the ability to identify and refer those with abnormal results to appropriate healthcare. This pilot shows that peer-led testing in the pharmacy setting can be implemented and warrants further scale up and evaluation. Full article

Background: Displaced individuals endure challenges, including conflict, forced migration, family separation, human rights violations, limited access to essential services, and increased exposure to violence and abuse. These hardships significantly impact their mental health, often leading to heightened trauma-related symptoms. Methods: We used a cross-sectional correlational design in refugee camps, homes, and centers across Jordan and Spain. 200 refugees with confirmed status in the past ten years were recruited. Demographic data were collected via a demographic form, the PTSD-8 Inventory assessed traumatic symptoms, and data analysis included descriptive statistics, independent t-tests, one-way ANOVA, and Chi-square tests. Results: Most participants had a secondary education, were unemployed, and had low incomes. PTSD symptoms were prevalent, with rates of recurrent thoughts (63.5%), re-experiencing events (57.5%), nightmares (50.5%), sudden reactions (56.5%), activity avoidance (53.5%), avoidance of specific thoughts or feelings (56.5%), jumpiness (53.5%), hypervigilance (53.5%), feeling on guard (41.5%), and general avoidance (43.5%) rated from rarely to most of the time. All symptoms were significantly more frequent among refugees in Jordan than in Spain. Conclusions and Recommendations: Intrusive thoughts were more frequent among females, urban residents, and unemployed individuals. Avoidance behaviors were higher in married and unemployed individuals. Hypervigilance was more prevalent among females, married individuals, and those with lower incomes. Regionally, females and married individuals in Jordan exhibited more intrusive thoughts and avoidance. In Spain, intrusive thoughts and hypervigilance were more common among females and the unemployed. The findings highlight the urgent need for targeted mental health interventions, particularly in refugee camps like those in Jordan, where PTSD symptom rates were significantly higher. Programs should prioritize trauma-focused therapies, such as Cognitive Behavioral Therapy, while adopting gender-sensitive approaches to address the heightened vulnerability of women and unemployed individuals. Given the strong link between unemployment and symptom severity, livelihood support and vocational training should be integrated into psychosocial care. Policymakers in host countries like Jordan could benefit from adopting integration strategies similar to Spain’s, which may contribute to lower PTSD prevalence. Additionally, community-based awareness initiatives could improve early symptom recognition and access to care. Future research should explore longitudinal outcomes to assess the long-term impact of displacement and resettlement conditions on mental health. Full article

Aim: With the intensification of population aging, the public health challenges posed by multimorbidity have become increasingly severe. This study employs bibliometric analysis to elucidate research hotspots and trends in the field of multimorbidity against the backdrop of global aging. The immediate aim is to systematically map the intellectual landscape and evolving patterns in multimorbidity research. The ultimate long-term aim is to provide a scientific basis for optimizing chronic disease prevention systems and guiding future research directions. Methods: The study adopted the descriptive research method and employed a bibliometric approach, analyzing 8129 publications related to multimorbidity from the Web of Science Core Collection. Using CiteSpace, we constructed and visualized several knowledge structures, including collaboration networks, keyword co-occurrence networks, burst detection maps, and co-citation networks within the multimorbidity research domain. Results: The analysis included 8129 articles from 2004 to 2024, published across 1042 journals, with contributions from 740 countries/regions, 33,931 institutions, and 40,788 authors. The five most frequently occurring keywords were prevalence, health, older adult, mortality, and risk. The top five contributing countries globally were the United States, the United Kingdom, Germany, China, and Spain. Five pivotal research trajectories delineate the intellectual architecture of this field: ① Evolution of Disease Cluster Management: Initial investigations (2013–2014) prioritized disease cluster coordination within general practice settings, particularly cardiovascular comorbidity management through primary care protocols and self-management strategies. ② Paradigm Shifts in Health Impact Assessment: Multimorbidity outcome research demonstrated sequential transitions—from physical disability evaluation (2013) to mental health consequences like depression (2016), culminating in current emphasis on holistic health indicators including frailty syndromes (2015–2019). ③ Expansion of Risk Factor Exploration: Analytical frameworks evolved from singular physical activity metrics (2014) toward comprehensive lifestyle-related determinants encompassing behavioral and environmental dimensions (2021). ④ Emergence of Polypharmacy Scholarship: Medication optimization studies emerged as a distinct research stream since 2016, addressing therapeutic complexities in multimorbidity management. ⑤ Frontier Investigations: Cutting-edge directions (2019–2021) feature cardiometabolic multimorbidity patterns and their dementia correlations, signaling novel interdisciplinary interfaces. Conclusions: The prevalence of multimorbidity is on the rise globally, particularly in older populations. Therefore, it is essential to prioritize the prevention of cardiometabolic conditions in older adults and to provide them with appropriate and effective health services, including disease risk monitoring and community-based chronic disease care. Full article

The integration of immigrant and refugee youth in Norway entails navigating linguistic, cultural, and social challenges that can hinder educational attainment, wellbeing, and future opportunities. Community-based mentoring has emerged as a promising strategy to support immigrant youth in their adaptation processes. This study explores how immigrant youth participants in the Vinn Vinn project experienced and perceived the role of mentoring in their social integration and overall wellbeing in three municipalities. The project, initiated by the Human Rights Academy in collaboration with Save the Children Norway, paired young immigrants (aged 16–23) with volunteer mentors who shared similar cultural and linguistic backgrounds. Drawing on twenty two semi-structured interviews and complemented by targeted observations of programme activities, the findings demonstrate that mentoring facilitated social belonging, improved language and cultural competence, reduced loneliness, and provided both emotional and practical support. Anchored in Bronfenbrenner’s ecological systems theory, the study highlights how mentoring created opportunities for positive interactions across micro- and meso-level systems, bridging individual needs with wider community and institutional structures. The article contributes to the scholarship on immigrant youth integration by showing how culturally responsive, community-based mentoring can complement formal welfare services and enhance wellbeing among young immigrants in Norway. Full article

Rapid population aging calls for a shift from static facility configuration toward understanding how spatial structures coordinate with everyday behavior. This study develops a structure–behavior coordination framework to examine how the spatial embedding of community service centers and surrounding facilities aligns with older adults’ mobility and activity chains. Using Guangzhou as a case, three representative facility aggregation forms—clustered, linear, and patchy—were identified through POI-based spatial analysis. Behavioral mapping supported by Public Participation GIS (PPGIS) and social network analysis captured facility co-use and path continuity, while rank-based measures (Rank-QAP and Rank-Biased Overlap) evaluated correspondence between structural and behavioral centralities. Findings show form-sensitive rather than typological coordination: the clustered case (FY) exhibits compact, mixed-use integration; the linear case (DJ) requires ground-level access along main pedestrian corridors; and the patchy case (LG) relies on a few highly accessible dual-core nodes where improved connectivity strengthens cohesion. Everyday facilities such as markets, parks, and plazas act as behavioral anchors linking routine routes. The framework offers a transferable tool and comparable metrics for diagnosing alignment between built structure and everyday behavior, guiding adaptive, evidence-based planning for age-friendly community systems. Full article

Addressing earthquake risk remains a significant global challenge, requiring rapid assessment of evacuation shelters for effective disaster response. Existing frameworks, such as FEMA’s Hazus, Copernicus EMS, and UNOSAT, offer valuable insights but are typically regional, static, and event-focused, lacking mechanisms for continuous shelter-level updates. This study introduces the Shelter Hazard Impact and Lifeline Outage Estimation (SHILOE) framework. SHILOE is a stepwise estimation approach integrating multisensor datasets for time-scaled assessments of shelter functionality and operability. These datasets include seismic intensity, liquefaction probability, tsunami inundation, IoT-derived power outage data, communication network disruptions, and social media. Application to the 2024 Noto Peninsula earthquake showed that ≥93.6% of designated and activated shelters were impacted by at least one hazard, with all experiencing at least one lifeline outage. The framework delivers estimates through three phases: immediate (within tens of minutes, e.g., simulation-based hazard models and lifeline data), intermediate (days, e.g., observation-based datasets), and refinement (ongoing, e.g., Social Networking Service and detailed field surveys). By progressively incorporating new data across these phases, SHILOE generates dynamic, facility-level insights that capture evolving hazard exposure and lifeline status. These outputs provide actionable information for emergency managers to prioritize resources, reinforce shelters, and sustain critical services, thereby advancing disaster resilience. Full article

Background: The functional capacity of older adults is a critical determinant of autonomy and quality of life, particularly in low-income populations from remote regions with limited access to health services. This study aimed to characterize the functional fitness (FF) of community-dwelling older adults in the interior of Amazonas, Brazil, stratified by sex and age group. Methods: A cross-sectional study was conducted with 807 older adults (471 females), aged ≥ 60 years, from four municipalities in northern Brazil. The FF was assessed using the Senior Fitness Test (SFT), including measures of strength (30-s Chair Stand Test—CST; 30-s Arm Curl Test—ACT), flexibility (Chair Sit and Reach Test-CSAR, Back Scratch Test-BST), balance/agility (8-Foot Up-and-Go Test—FUG), and aerobic endurance (6-min walk test—6MWT). Descriptive statistics, confidence intervals, and age- and sex-specific percentiles were calculated. Results: Results indicated a progressive decline in FF with advancing age. Males outperformed females in strength and endurance tests, whereas females exhibited better flexibility. Notable reductions in performance were observed after age 75, particularly in CST, ACT, FUG, and 6MWT. Overall, the functional profiles of this population were below international norms, especially among females and individuals aged ≥ 80. The prevalence of overweight was 39.3%, with socioeconomic vulnerability affecting over 90% of participants. Conclusions: Older adults in low-income, remote Amazonian Brazilian communities demonstrate marked functional decline with ageing, influenced by socioeconomic and environmental constraints. These findings highlight the urgency of implementing accessible, community-based interventions focused on physical activity, strength, mobility, and endurance to support healthy ageing in underserved regions. Full article

To address the flood risks driven by climate change and urbanization, this study proposes the DRIRA model (Driving Force, Resistance, Influence, Recoverability, Adaptability). Distinct from BRIC (Baseline Resilience Indicators for Communities) and PEOPLES (Population, Environmental/Ecosystem, Organized Governmental Services, Physical Infrastructure, Lifestyle, Economic Development, Social–Cultural Capital), the model emphasizes dynamic interactions across the entire disaster lifecycle, introduces the “Influence” dimension, and integrates SNA (Social Network Analysis) with a modified gravity model to reveal cascading effects and resilience linkages among cities. Based on an empirical study of 30 cities in the Central Plains Urban Agglomeration, and using a combination of entropy weighting, a modified spatial gravity model, and social network analysis, the study finds that: (1) Urban flood resilience increased by 35.5% from 2012 to 2021, but spatial polarization intensified, with Zhengzhou emerging as the dominant core and peripheral cities falling behind; (2) Economic development, infrastructure investment, and intersectoral governance coordination are the primary factors driving resilience differentiation; (3) Intercity resilience connectivity has strengthened, yet administrative fragmentation continues to undermine collaborative effectiveness. In response, three strategic pathways are proposed: coordinated development of sponge and resilient infrastructure, activation of flood insurance market mechanisms, and intelligent cross-regional dispatch of emergency resources. These strategies offer a scientifically grounded framework for balancing physical flood defenses with institutional resilience in high-risk urban regions. Full article

The Community and Civil Research Group of Eötvös Loránd University (Budapest) investigated sustainable community activities in Hungary and abroad to identify local responses to global challenges. Using qualitative research methods, focus groups and interviews, this research defined the concepts of community service, community practice and working methods by analysing nearly 80 practical examples and 65 interviews in Hungary. The practical examples were used to create a “sustainable community model” and a methodological guide for community developers on how to implement community services. The steps of the process presented in the model are based on building community involvement and participation, mobilising local resources and capacities, creating community-based services, building sustainability and self-sufficiency and consolidating innovative training and community working practices. The research resulted in the creation of an online Community Repository, which provides community responses to the 17 UN Global Sustainability Challenges and Goals —economic growth, social inclusion and environmental protection—by organising the collected community services, small community practices and working methods around seven community development perspectives: governance, place, sustainable livelihoods, culture (and the arts), identity (belonging and connection), human rights and resilience and engagement and knowledge. This study provides a methodological foundation for developing resilient community-based services that contribute to sustainability, inclusivity and innovation. Full article

Artificial Intelligence (AI) holds significant potential to enhance sustainable non-chemical agricultural methods (NCAM) by optimising resource management, automating precision farming practices, and strengthening climate resilience. However, its widespread adoption among farmers’ remains limited due to socio-economic, infrastructural, and justice-related challenges. This study investigates AI adoption among NCAM farmers using an Integrated Mechanism for Sustainable Practices (IMSP) conceptual framework which combines the Technology Acceptance Model (TAM) with a justice-centred approach. A mixed-methods design was employed, incorporating Fuzzy-Set Qualitative Comparative Analysis (fsQCA) of AI adoption pathways based on survey data, alongside critical discourse analysis of thematic farmers narrative through a justice-centred lens. The study was conducted in Tamil Nadu between 30 September and 25 October 2024. Using purposive sampling, 57 NCAM farmers were organised into three focus groups: marginal farmers, active NCAM practitioners, and farmers from 18 districts interested in agricultural technologies and AI. This enabled an in-depth exploration of practices, adoption, and perceptions. The findings indicates that while factors such as labour shortages, mobile technology use, and cost efficiencies are necessary for AI adoption, they are insufficient without supportive extension services and inclusive communication strategies. The study refines the TAM framework by embedding economic, cultural, and political justice considerations, thereby offering a more holistic understanding of technology acceptance in sustainable agriculture. By bridging discourse analysis and fsQCA, this research underscores the need for justice-centred AI solutions tailored to diverse farming contexts. The study contributes to advancing sustainable agriculture, digital inclusion, and resilience, thereby supporting the United Nations’ Sustainable Development Goals (SDGs). Full article

In higher education, institutional quality is traditionally assessed through metrics such as academic programs, research output, educational resources, and community services. However, it is important that their activities align with student expectations, particularly in relation to interactive learning environments, learning management system interaction, curricular and co-curricular activities, accessibility, support services and other learning resources that ensure academic success and, jointly, career readiness. The growing popularity of student engagement metrics as one of the key measures to evaluate institutional efficacy is now a feature across higher education. By monitoring student engagement, institutions assess the impact of existing resources and make necessary improvements or interventions to ensure student success. This study presents a comprehensive analysis of student feedback from the StudentSurvey.ie dataset (2016–2022), which consists of approximately 275,000 student responses, focusing on student self-perception of engagement in the learning process. By using classical topic modelling techniques such as Latent Dirichlet Allocation (LDA) and Bi-term Topic Modelling (BTM), along with the advanced transformer-based BERTopic model, we identify key themes in student responses that can impact institutional strength performance metrics. BTM proved more effective than LDA for short text analysis, whereas BERTopic offered greater semantic coherence and uncovered hidden themes using deep learning embeddings. Moreover, a custom Named Entity Recognition (NER) model successfully extracted entities such as university personnel, digital tools, and educational resources, with improved performance as the training data size increased. To enable students to offer actionable feedback, suggesting areas of improvement, an n-gram and bigram network analysis was used to focus on common modifiers such as “more” and “better” and trends across student groups. This study introduces a fully automated, scalable pipeline that integrates topic modelling, NER, and n-gram analysis to interpret student feedback, offering reportable insights and supporting structured enhancements to the student learning experience. Full article