Search Results (12,527)

The COVID-19 pandemic prompted governments to implement lockdowns and social distancing measures to curb transmission, which, in South Africa, disrupted economic activity, reduced household income, and challenged the sustainability of household food access. This study assessed food accessibility, availability, dietary diversity, food security status, and coping strategies among households in the Tygerberg region during lockdowns. A cross-sectional design was employed using a researcher-administered questionnaire to collect sociodemographic and household data. Food security was assessed using the Household Food Insecurity Access Scale and the Household Food Security Survey Module, dietary diversity using a 24 h recall, and coping strategies through a standardized tool. Among the 432 households surveyed, 62% reported reduced income during lockdowns, while approximately 80% experienced food insecurity in the preceding 30 days and 72% over the past year. Dietary diversity was low in 47.3% of households, consuming fewer than seven food groups, and medium in 46.4%, consuming eight to eleven food groups. Common coping strategies included purchasing cheaper, less preferred foods, skipping meals, and reliance on social relief measures such as food parcels and the Social Relief of Distress grant. Overall, while food availability remained relatively stable, economic access emerged as the principal constraint, undermining dietary quality and household resilience and highlighting the need for income-responsive and socially sustainable food security interventions to strengthen urban food system resilience during prolonged socio-economic shocks. Full article

Although heritage reconstruction can effectively restore physical form, the regeneration of living cultural experience remains theoretically underexplored in heritage tourism scholarship. This study introduces the concept of post-reconstruction experiential disjunction (PRED)—the structural misalignment among reconstructed material form, historically embedded cultural scripts, and the embodied practices of contemporary visitors—and develops the Material–Script–Practice (MSP) framework around it. Taking Yuyuan Garden (愚园) in Nanjing as an empirical case, a mixed-methods design combines online discourse analysis, field observation, and a questionnaire survey (N = 300). Findings reveal that Cultural Script most strongly predicts disjunction mitigation—a four-item scale capturing visitors’ holistic sense of experiential connectivity (α = 0.832), followed by Material Form; Embodied Practice contributes comparatively little. Photographers show significantly lower mitigation levels than other groups, owing to structural conflicts between professional visual practice and the cultural logic of classical garden space. The MSP framework reveals a weighted hierarchy among its three dimensions: a finding that extends and empirically specifies the theoretical insights of Lefebvre’s spatial triad and Edensor’s heritage performance theory, neither of which typically foregrounds differential explanatory weight among their constituent elements. When cultural scripts offer accessible meaning pathways for visitors of diverse backgrounds, heritage spaces can move beyond formal reconstruction toward experiential reconstitution, sustaining the conditions for long-term heritage preservation. Full article

Opera Out of Opera 2 (OOO2) is a Creative Europe cooperation project that experiments with digital, participatory strategies to reconnect opera with younger audiences and to reshape professional capacity for conservatory students. Rather than treating opera as a fixed repertoire to be transmitted, the project frames it as a site of co-creation, where youth and emerging professionals share agency in how the art form is presented, mediated and discussed. This article has two related aims. First, it examines how OOO2’s digital-first Audience Engagement Strategy (AES) may contribute to audience development among 18–25-year-olds, focusing on reach, participation patterns and perceived accessibility. Second, it investigates how participation in the project appears to affect conservatory students’ entrepreneurial self-efficacy and their understanding of their potential social role as musicians. Methodologically, the study combines a participatory action research (PAR) framework with an embedded single-case design. Quantitative data include pre- and post-intervention questionnaires with 132 higher music education students. An audience survey completed by 1256 spectators, complemented by social media and web analytics, is also embedded. Qualitative material derives from semi-structured interviews (n = 30), focus groups with project stakeholders and direct observation of workshops, rehearsals and performances. Results indicate a marked digital reach among younger audience and suggest that shorter formats, informal settings and second-screen mediation can lower perceived barriers to opera attendance for first-time or occasional spectators. Among students, mean scores for entrepreneurial self-efficacy increased from 3.2 (SD = 0.8) to 4.1 (SD = 0.7), corresponding to a large effect size (Cohen’s d = 1.20, p < 0.01), a pattern broadly consistent with research on self-efficacy and capacity creation in music and arts-based entrepreneurship education. The discussion connects these findings with a bibliometric mapping of audience development in opera, conducted on 147 Scopus-indexed documents, and argues that OOO2 occupies a still under-theorized intersection between youth-centred cultural participation and entrepreneurial capacity-building in higher music education. While the single-case design and the use of self-constructed survey items limit generalizability, the project may offer a useful reference point for institutions seeking to rethink opera’s approach as a digitally mediated, socially engaged and educationally meaningful practice. Full article

The evolution of TMJ-replacements has been driven by advancements in personalization, materials and digital planning technologies. However, there is little data on how surgeons perceive the prosthetic systems and their limitations in practice. The perspective from surgeons is critical to identifying the gap between current technology and clinical need. Using an international, structured survey based on a modified Delphi methodology, including expert validation, pilot testing and global distribution through professional networks, the status of the TMJ-replacement ecosystem was obtained. The questions covered aspects such as the workflow, the integration of components, the design features, the use of materials, the fixation strategy for each component, and usability of surgical guides. The responses were quantitatively analyzed using descriptive statistics. 250 surgeons were included; the majority of surgeons preferred to have all elements of the TMJ-replacement system provided by a single system or company (i.e., the prosthesis and plates), with 86.0% of surgeons indicating this preference and 71.2% of surgeons indicating that having access to STL files for use in surgical navigation is an important feature. Approximately 88.4% of surgeons indicated that flexibility in the design of the prosthesis is important, while 61.6% of respondents indicated that design issues contribute to failures of TMJ prostheses. Issues related to the fixation of the prosthetic components, particularly screw loosening, were also commonly reported by surgeons with respect to failure. Surgeons also indicated concerns with regard to the bulkiness (73.2%) and the fit accuracy (68.4%) of the surgical guides. In terms of material selection, 78.0% of respondents preferred to be able to choose the type of metal alloy for the TMJ replacement system. TMJ replacement is viewed by surgeons as a system-dependent procedure that requires the integration of design, materials, fixation and digital workflow. The currently available prosthetic solutions only partially meet the needs of surgeons. Full article

Social robots hold promise for enhancing later-life support, but user needs and preferences for multimodal interaction modalities remain underexplored. This study explores awareness, willingness, perceived barriers, and modality–function associations across multiple interaction modalities among middle-aged and older adults, and proposes a conceptual five-layer architecture for design guidance. A questionnaire survey with 199 Chinese respondents (aged 45–64: 89.4%, 65+: 10.6%) examined perceptions of voice, visual, gestural, affective, sEMG, and brain–computer interface interactions. Voice and visual modalities were the most preferred; gesture and affective interactions were moderately accepted; awareness of sEMG was high but may reflect confusion with other sensor technologies; and BCI awareness and willingness were low. Based on survey findings and the literature, a conceptual five-layer architecture is presented to inform future social-robot design. The sample predominantly comprised middle-aged participants, so findings reflect prospective later-life users rather than the broader older-adult population. This study offers user-centered insights into multimodal social-robot interaction and provides design implications for future development rather than evaluating emotional-health interventions. Full article

The rapid expansion of generative artificial intelligence (AI) is transforming higher education and creating new opportunities that are associated with the development of perceived professional competencies. At the same time, the accounting profession increasingly requires graduates who can evaluate sustainability disclosures and form informed judgments regarding sustainability-related information. However, limited research has examined how AI-supported learning relates to sustainability-oriented decision-making capabilities in accounting education. Drawing on Decision Support Systems (DSS) theory and constructivist learning theory, this study examines the associations between generative AI-supported learning and students’ perceived sustainability judgment capability. Specifically, the study investigates the mediating roles of perceived critical thinking and perceived sustainability knowledge, as well as the moderating role of AI literacy. A quantitative, cross-sectional research design was employed using self-reported survey data collected from 721 accounting students, and the proposed relationships were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings indicate that generative AI-supported learning is positively associated with students’ perceived critical thinking and perceived sustainability knowledge. In turn, both constructs show significant positive relationships with perceived sustainability judgment capability, with perceived sustainability knowledge demonstrating a stronger association. Additionally, AI literacy strengthens the relationships between generative AI-supported learning and the cognitive constructs. Importantly, the study captures students’ self-reported perceptions of their cognitive and judgment-related capabilities and does not assess objective cognitive performance or demonstrated judgment ability. The study contributes to the literature by positioning generative AI as an educational decision-support mechanism associated with perceived sustainability-oriented judgment capability through cognitive pathways, while highlighting the importance of aligning theoretical claims with perceptual measurement approaches. Full article

As organizational competition intensifies, employees have become increasingly responsive to evaluative cues from their work environment. Among these, underdog expectations—employees’ perceptions that others view them as unlikely to succeed—can trigger strong psychological reactions that shape interpersonal behavior. Drawing on self-determination theory, this study examines how underdog expectations influence employees’ interpersonal counterproductive work behavior (CWB-I). Using a three-wave time-lagged survey design with 221 employees, we found that underdog expectations positively predict CWB-I through two parallel psychological mechanisms: increased moral disengagement and reduced perceived insider status. In addition, organization-based self-esteem (OBSE) strengthens these indirect effects, such that the mediating relationships are stronger among employees with high OBSE. These findings extend research on underdog expectations by revealing both relational and cognitive pathways linking negative evaluative expectations to interpersonal deviance, while also highlighting the complex role of self-evaluative organizational identity in shaping employees’ behavioral responses to status-based threats. Full article

The cultural heritage of the Valencian Community constitutes a strategic asset of the highest order for sustainable development and territorial cohesion. This article analyses the enhancement of Sites of Cultural Interest (BICs) in the province of Alicante, examining the interplay between regulatory frameworks for protection, heritage management strategies and their capacity to generate local employment. An explanatory sequential mixed-methods design was adopted, comprising two complementary phases. In the first, quantitative phase, the geographical distribution of BICs and their relationship with employment indicators were established through statistical and cartographic analysis. In the second phase, which was qualitative in nature, the causal mechanisms identified in the first phase were explored in greater depth through structured surveys and semi-structured interviews with municipal officials. The results show that, beyond the causal factors related to the density of listed buildings and their location, the greatest benefit is derived from incorporating institutional, governance, and local management capacity variables into the analytical models as primary explanatory factors. These factors facilitate the transformation of heritage into an engine of economic and social prosperity, capable of preserving the identity of local communities and promoting a living and accessible heritage that generates well-being. Full article

Field-programmable gate arrays (FPGAs) are increasingly used to bring biometric recognition from cloud- or GPU-centric deployments to resource-constrained edge devices where latency, power, and privacy are critical. This paper surveys recent (2021–2025) FPGA and FPGA-SoC implementations across five widely deployed modalities: face, fingerprint, iris, speaker (voiceprint), and finger vein. For each modality, we summarize representative implementations and the performance figures commonly reported in the literature (e.g., accuracy or EER, latency/throughput, resource usage, and power), highlighting the algorithm–hardware co-design choices that enable real-time operation. Across modalities, successful designs repeatedly employ streaming/dataflow architectures, aggressive quantization and fixed-point arithmetic, reuse-aware buffering, and heterogeneous CPU–FPGA partitioning, often supported by high-level synthesis and vendor deep learning IP. Beyond throughput, we discuss how FPGAs facilitate privacy-preserving on-device processing and can integrate template protection and presentation attack detection within the same fabric. Finally, we identify open challenges related to scalability to larger models, memory-bandwidth constraints, and design productivity, and outline research directions enabled by emerging adaptive FPGA architectures and more automated toolflows. Overall, the surveyed evidence indicates that FPGAs are a compelling platform for deterministic, energy-efficient, and secure biometric inference at the sensor edge. Full article

Rural public spaces are crucial to the daily activities of older adults; however, limited research has examined the effects of their environmental characteristics on older adults’ spatiotemporal behavior and perception from a multisensory perspective. This study hypothesizes that composite sensory environments have significant nonlinear predictive effects on older adults’ behavior types and satisfaction. In this study, 10 sample spaces were selected in Qingdao, China. Multi-source data were collected through a two-week period of unobtrusive observation and subjective questionnaire surveys (N = 241). Multiple logistic regression was used to analyze the main effects of environmental characteristics, and an MLP model with a single hidden layer of 100 units was constructed to predict dwell time and satisfaction. The results show that, in the investigated rural context, older adults’ dominant behavior was social activity (81.12%), which mainly occurred in built spaces such as squares. Multiple logistic regression indicated that, among the various environmental factors, visual aesthetics had a statistically significant effect on behavior types (p = 0.013). The MLP model achieved prediction accuracies of 85.3% for dwell time and 93.1% for satisfaction. The key predictive variables were volume perception (100% importance), the Natural Sound Index (NSI) (92.1%), and visual aesthetics (89.3%). Subgroup heterogeneity analysis further showed that older-old adults and those with poorer health conditions were more sensitive to pavement quality and physical comfort, whereas older adults living alone or with limited household companionship were more strongly influenced by visual aesthetics and natural soundscape quality. The theoretical significance of this study lies in proposing quantitative measures of natural sound and odor indices and revealing that, in the specific northern rural built environment, the coordinated design of visual and auditory environments plays an important role in improving spatial quality. The findings provide empirical support for the age-friendly micro-renewal of rural public spaces in specific regions. However, due to the limitations of single-season data and a relatively small sample size, their generalizability needs to be further verified across regions. Full article

This study examines how sustainability-oriented social marketing influences relationship quality and tourism relationship value, and how perceived brand coherence (Gestalt completeness) conditions this relationship. The growing emphasis on sustainable tourism and responsible consumption has increased the importance of socially oriented marketing communication in shaping long-term consumer–firm relationships. However, prior research has largely examined social marketing, relationship quality, and relationship value in isolation, with limited attention to how perceptual mechanisms strengthen these relational processes within contemporary, platform-mediated tourism environments. Addressing this gap, this study investigates how public-issue-promoted social marketing (PIPSM) influences relationship quality (RQ) and tourism relationship value (TRV) while incorporating Gestalt completeness (GC) as a moderating mechanism that captures perceptual coherence in brand communication. Using survey data collected from 400 consumers with prior tourism experience in Taiwan, the proposed model is tested through structural equation modeling, complemented by regression-based moderation analysis. The results indicate that PIPSM significantly enhances relationship quality, which in turn positively influences tourism relationship value. Furthermore, Gestalt completeness strengthens the relationship between RQ and TRV, suggesting that perceptually coherent communication amplifies relational outcomes. This study contributes to the literature by integrating social marketing, relationship marketing, and perceptual psychology into a unified framework. Rather than demonstrating direct sustainability outcomes, the findings highlight relational and perceptual pathways that may support sustainability-oriented behaviors. The study also offers practical implications by illustrating how socially oriented communication and coherent brand design across digital touchpoints can enhance customer engagement and long-term relational value. Full article

UAV aerial cinematography has become increasingly important in film production, surveying, and smart-city applications due to its efficiency and creative potential. However, existing UAV filming workflows still rely heavily on manual operation and professional piloting skills, resulting in complex mission design, limited planning autonomy, and inconsistent visual quality. To address these challenges, this paper proposes a unified aesthetics-aware trajectory planning framework for multi-region-of-interest (multi-ROI) UAV aerial cinematography that automatically generates safe, efficient, and visually coherent flight paths from user-specified ROIs. The proposed framework consists of three main components. First, for each ROI, candidate viewpoints are sampled using a spiral trajectory, and a learning-based aesthetic evaluation network is applied to select visually optimal viewpoints for local trajectory generation. Second, transition trajectories between ROIs are generated using a Goal-biased Bidirectional Rapidly exploring Random Tree Star (Goal-biased BiRRT*) planner and evaluated through a multi-objective cost function to determine the most suitable transition paths. Third, the global connection of multiple ROIs is formulated as a Set Traveling Salesman Problem (STSP) to obtain an efficient visiting sequence. By integrating learning-based aesthetic evaluation with hierarchical trajectory planning and coordinated multi-ROI route organization, the proposed framework jointly considers flight feasibility, planning efficiency, visual composition quality, and trajectory continuity within a unified planning pipeline. Experimental results demonstrate that the proposed method generates more visually appealing and coherent aerial trajectories than traditional manual or rule-based approaches, while significantly reducing operational complexity. The proposed system provides an effective solution for autonomous UAV aerial cinematography with improved global consistency, aesthetic performance, and practical planning capability in complex environments. Full article

Unsafe behaviors among construction workers constitute a major contributing factor to construction accidents, making it critically important to explore their underlying mechanisms and temporal dynamics from a cognitive perspective. This study employed an exploratory sequential mixed-methods approach. Initially, grounded theory was used to conduct three-level coding of in-depth interview data from 35 construction workers, resulting in the development of a cognitive theory model of unsafe behavior among construction workers comprising two main categories: ‘ perceptual recognition’ and ‘cognitive response’. Subsequently, a questionnaire was designed based on this model, and a 10-day longitudinal survey was conducted among 300 workers. Multi-group structural equation modelling was employed to analyze the temporal variation in the relationship between cognitive ability and unsafe behavior. The results indicate that: workers’ cognitive abilities can be decomposed into four dimensions—perceiving danger, identifying hazards, perceptual response, and decision-making response—and further summarized into two higher-order factors: perceptual recognition and cognitive response; (2) cognitive abilities are significantly negatively correlated with unsafe behavior; (3) this relationship exhibits significant temporal variations, with the inhibitory effect on Day 5 (path coefficient −0.95) being stronger than that on Day 1 (−0.88) and Day 10 (−0.50); furthermore, the ‘cognitive response → decision-making response’ path also shows significant differences between Day 5 and Day 10. The study reveals the pattern of fluctuations over time in the inhibitory effects of workers’ cognitive ability on unsafe behavior, providing a theoretical basis for construction companies to implement dynamic and targeted safety interventions. Full article

Purpose: Access to assistive technology (AT) is a fundamental human right and a critical component of Universal Health Coverage (UHC). In the Middle East and North Africa (MENA) region, the scarcity of trained professionals remains a significant barrier to AT service provision. This study evaluates the effectiveness and perceived usefulness of the Assistive Technology Training Program (ATTP), a specialized continuing education initiative designed to build workforce capacity among rehabilitation and healthcare professionals. Methods: A convergent mixed methods design was used to analyze quantitative pre/post-test scores and qualitative focus group open-ended responses. Quantitative data were gathered from 386 participants across 11 MENA countries using a pre- and post-test assessment of AT knowledge. Qualitative utility and participant satisfaction were assessed through a 5-point Likert scale survey evaluating content relevance, trainer expertise, and facilities. Association tests (ANOVA and t-tests) were conducted to identify factors influencing knowledge gain. Results: Participants demonstrated a statistically significant improvement in AT knowledge, with the overall mean score increasing from 3.67 ± 1.13 to 7.50 ± 1.25 (p < 0.001). High levels of satisfaction were reported, with 92% of participants rating the training as “Very Good” or “Excellent” regarding its relevance to clinical needs. Association tests revealed that professional background (p < 0.001), employment status (p = 0.0017), level of education (p = 0.011), and prior training experience (p = 0.026) were significant factors in the magnitude of improvement, although all subgroups achieved significant learning gains. Qualitative thematic analysis per the focus group discussions using the WHO-GATE 5 P framework identified three major themes: (1) Structural Challenges: Issues with Products and Provision point toward a need for better infrastructure and localized supply chains. (2) Human Capital: Personnel barriers emphasize that training shouldn’t just be for professionals, but should extend to caregivers as well. (3) Systemic and Social Change: Policy and People focus on the “soft” side of AT moving toward user-involved guidelines and fighting social stigma to ensure rights are upheld. Conclusions: The ATTP is an impactful educational intervention that significantly enhances the foundational competencies of healthcare professionals in the MENA region. By addressing knowledge gaps and fostering practical skills, the program serves as a preliminary model that demonstrates potential for building regional capacity and supporting the United Nations’ Sustainable Development Goal (SDG) #3 related to health and wellbeing and SDG #4 related to quality education and lifelong learning opportunities for all. Further research is required to evaluate its long-term scalability and clinical impact. Full article

Traditional urban landscape evaluations have primarily relied on either objective spatial metrics, such as the Green View Index (GVI), or subjective human surveys, often failing to capture the complex mechanisms of human environmental perception. This study proposes a novel Explainable Artificial Intelligence (XAI) framework that integrates objective physical configuration with subjective cognitive assessment to predict human landscape preference. Utilizing 159 urban landscape images, we extracted physical features via semantic segmentation (SegFormer) and psychological perceptions via a zero-shot vision-language model (CLIP). Our hybrid Random Forest model successfully bridged these dimensions, achieving moderate yet promising predictive performance (Rsquare = 0.442). SHAP (Shapley Additive exPlanations) analysis revealed that psychological perceptions—specifically Safety (0.104), Fascination (0.096), and Tranquility (0.080)—outperformed traditional objective metrics like GVI (0.067) in determining overall preference, while sub-model interpretation linked these psychological responses to specific physical elements such as buildings, sky openness, low vegetation, and water bodies. The findings suggest that urban green space design should move beyond maximizing greenery quantity and instead prioritize spatial compositions that induce psychological security, visual interest, and restoration. The proposed framework offers a scalable and interpretable tool for human-centered landscape assessment, while acknowledging limitations related to sample size, cultural generalizability, pretrained model bias, and reliance on static two-dimensional imagery. Full article