Search Results (10,924)

When examining ground-penetrating radar (GPR)-based advanced detection ahead of the tunnel face for tunnel constructions, existing numerical forward simulations have not effectively accounted for the actual orientation of the strata and the conditions, limiting their theoretical guidance. In this study, we classify tunnel boring through strata attitudes into horizontal, vertical, positively inclined, reverse inclined, and other anomalous structures. We also consider tunnel faces with different planarity (perfectly smooth or irregular). Using the finite-difference time-domain method with a generalized perfectly matched layer, we simulated 21 forward models for GPR-based advanced detection ahead of the tunnel face. The comparative simulation results indicate that the superposition of reflections from different directions at irregular tunnel faces, lithological interfaces, complicated numerical forward models of typical target geological bodies, making it difficult to distinguish the reflection signals of target geological bodies, and the signal strength in numerical forward modeling profiles with antenna touch with tunnel face is significantly stronger than those without such touch. The flatness of the tunnel face and the close proximity between the antenna and tunnel face are the keys to obtain high-quality original data. These research findings will contribute to improving instruments, data processing, and geologic interpretation in future. Full article

Stilling basins are critical energy-dissipating structures in high-head hydraulic projects, yet conventional stilling basins often face challenges of insufficient energy dissipation and excessive bottom pressure under high water head and large unit discharge conditions. The integration of sudden expansion and drop sill into stilling basin design has emerged as a potential solution, but its hydraulic characteristics and the specific impact of sudden expansion remain inadequately quantified and understood. To address this research gap, this study experimentally investigates the hydraulic performance of stilling basins with sudden expansion and drop sill, conducting physical model tests on nine design schemes that contrast basins with and without sudden expansion. The tests measure time-averaged pressure, fluctuating pressure, and aeration concentration at key positions of the basin floor. The results demonstrate that the drop sill stilling basin with sudden expansion is technically feasible for application under conditions of high water head and large unit discharge. In the direction perpendicular to the flow, the distributions of time-averaged pressure, fluctuating pressure, and aeration concentration are non-uniform, generally exhibiting a decreasing trend in the order of the 1/4 centerline, chute extension line, 1/2 centerline, and near-sidewall line. Specifically, the time-averaged pressure, fluctuating pressure, and aeration concentration at the bottom of the sudden-expansion basin are, respectively, lower than those of the non-sudden-expansion basin. Notably, the primary protection zones of the sudden-expansion and drop sill stilling basin are situated between the chute extension line and the 1/4 centerline, as well as in the region ranging from the drop sill to 0.4l (with l denoting the stilling basin length). These findings verify that sudden expansion significantly modifies the hydraulic characteristics of stilling basins by reducing pressure and aeration concentration in key areas, and further provide quantitative design parameters and theoretical support for the optimization of sudden-expansion and drop sill stilling basins in high-head hydraulic engineering projects. Full article

Amid global climate change, China’s energy-intensive industries face substantial challenges in achieving low-carbon transformation. While existing studies largely focus on individual determinants of emission reduction, insufficient attention has been paid to the dynamic interactions among multiple dimensions. To complement this perspective, this study integrates co-evolution theory with the technology–organization–environment (TOE) framework, applying dynamic fuzzy-set qualitative comparative analysis (fsQCA) to panel data from 30 Chinese provinces between 2005 and 2022. The results indicate that low carbon intensity arises from the synergistic interaction of factors rather than isolated elements, whereas high intensity is driven by systemic mismatches rather than the mere absence of low-carbon conditions. This research identifies five enabling configurations, led by the digital-green dual drive, alongside three inhibiting pathways, most notably the regulation-volatility trap. Evolutionary trajectories exhibit significant regional variation: the eastern region leverages digital-market mechanisms through innovation strategies, whereas the central region shifted toward government-led upgrading following the 2016 supply-side structural reform. The western region relies on top-down administrative governance to compensate for limited digital capabilities. Meanwhile, the northeast region remains trapped in a composite lock-in due to the structural misalignment between legacy industrial scale and the integration of digital and green innovations. These findings provide a systems-oriented basis for differentiated policymaking in emerging economies. Full article

The aviation industry faces increasing pressure to reduce its environmental footprint, prompting airlines to adopt green marketing practices that align with sustainability goals. Grounded in the Elaboration Likelihood Model (ELM), this study investigates the influence of green marketing on consumers’ repurchase intentions, with electronic word-of-mouth (e-WOM) as a mediating factor. An online survey was conducted among 390 airline passengers in Turkey, and the data were analyzed using structural equation modeling. The results indicate that green marketing significantly enhances both e-WOM and repurchase intention. Additionally, information quality and credibility exert significant effects on e-WOM and make a modest direct contribution to repurchase intention. While e-WOM is positively associated with repurchase intention, its mediating role in the relationship between green marketing and repurchase intention is not statistically supported. These findings suggest that e-WOM functions as a reinforcing rather than a transmitting mechanism linking green marketing to repurchase intention. The model explains 68.9% of the variance in repurchase intention and 18.9% in e-WOM. The study contributes by integrating green marketing, e-WOM, and information characteristics within an ELM-based framework for the airline context, offering actionable insights for sustainability-oriented marketing strategies. Full article

Background/Objectives: Decoding affective states from Electroencephalography (EEG) signals is fundamental to non-invasive Brain–Computer Interfaces. Despite recent advances, accurate recognition is impeded by the inherently non-stationary nature of physiological signals and the entanglement of spatio-temporal dynamics within high-dimensional recordings. While Transformers excel at global modeling, they often neglect the continuous dynamical properties of neural signals and suffer from quadratic complexity. Methods:In this paper, we propose the Spatio-Temporal Hybrid Mamba-Attention (STHMA), a framework designed to explicitly disentangle and model EEG dynamics via linear-complexity State Space Models. First, to incorporate domain knowledge, we introduce a Dual-Domain Physics-Aware Embedding module. This module fuses learnable temporal convolutions with explicit frequency-domain spectral features, ensuring fidelity to neurophysiological principles. Second, we propose a novel Decoupled Spatial–Temporal Scanning strategy. By dynamically reconfiguring the serialization of the data tensor, our model strictly separates the learning of instantaneous functional connectivity from the tracking of emotional state evolution, thereby preventing the structural collapse common in 1D sequence models. Results:Extensive experiments on the FACED and SEED-V datasets demonstrate that the STHMA achieves state-of-the-art performance, significantly exceeding the random chance baselines (11.11% for 9-class FACED and 20.00% for 5-class SEED-V). Conclusions:The results validate that combining Physics-Aware Embeddings with decoupled state-space modeling offers a scalable and effective paradigm for EEG emotion recognition. Full article

Urgent demand for wound healing treatments has driven rapid advancement in electronic skin technology. As a promising wound healing approach, electronic skin offers advantages such as flexible conformability, autonomous sensing, and intelligent regulation. However, mainstream electronic healing patches face significant challenges in complex wound applications, including insufficient coordination, delayed response, limited healing efficiency, and inadequate feedback. Therefore, developing innovative wound healing technologies that integrate high efficiency, multi-module drive, and closed-loop feedback is imperative. The advanced development of electronic skin for wound healing is urgently needed to be systematically reviewed. Here, first, the structural innovations and design strategies for biomimetic thermotherapeutic electronic skins based on thermoelectric polymer composites and interactive temperature biomimetic regulation are summarized. Subsequently, several emerging bioelectrically active electronic skins are reviewed, including drug-delivery electronic skins, multifunctional hydrogel-integrated electronic skins, and photoelectric synergistic stimulation electronic skins, along with an analysis of their advanced designs and innovative advantages. Last but not least, potential challenges facing the future development of electronic skin are explored. Practical solutions are proposed for advancing low-cost, clinically applicable, and scalable electronic skin development, aiming to drive breakthrough progress in therapeutic wound healing. Full article

The manufacturing sector drives industrialisation and contributes substantially to economic growth and employment creation. Despite this, it faces the challenges of diminishing size and lack of competitiveness, mainly due to operational uncertainty. The study developed an approach to managing operational uncertainty using Industry 4.0 and 5.0 technologies. It employed a multimethod quantitative design based on the post-positivist paradigm, with data collected from 22 experts and 262 responses from a manufacturing firms’ survey. The study employed an integrated fuzzy decision-making trial and evaluation laboratory (DEMATEL) with partial least squares structural equation modelling (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA). The fuzzy DEMATEL results reveal that growing geopolitical tension, cost-of-living-driven consumer behavioural change, pandemic turbulence, lack of energy stability and security, and the entrenched power of large firms are causal dimensions of operational uncertainty. Industry 4.0 and 5.0 technologies, with capabilities for scenario planning and supply chain integration, flexible production and mass customisation, real-time system and process monitoring and response, root cause analysis, and sustainable solutions, can manage operational uncertainty. These technologies include artificial intelligence (AI), the Internet of Things (IoT), big data analytics, and, to a lesser extent, advanced robotics, blockchain, and augmented and virtual reality (AR/VR). This study advanced configuration theory and a new integrated methodology (fuzzy-DEMATEL-PLS-SEM-fsQCA) to develop solutions for sustained performance during operational uncertainty in manufacturing. This research offers valuable information to advance the subject, make meaningful changes in day-to-day manufacturing operations, and promote practical real-world problem solving. Full article

Accurate plant recognition in desert grasslands is essential for ecological monitoring, yet existing models face critical limitations: poor generalization in complex natural environments and excessive computational demands for mobile deployment. This study proposes YOLOv11-PKD, a lightweight model integrating structured pruning and knowledge distillation for efficient desert grassland plant identification. First, we develop YOLOv11-STC, a high-capacity teacher model incorporating the SPPCSPC module for multi-scale feature extraction, Triplet Attention for spatial refinement, and a GSConv-based Slim Neck for optimized feature fusion. This architecture achieves 88.3% mAP50 on the DGPlant48 dataset, outperforming the baseline YOLOv11n by 6.8%. To enable edge deployment, we apply channel pruning guided by BatchNorm scaling factors, compressing the model by 19.75% in PParameters and 20% in GFLOPS (YOLOv11-Pruned: 79.5% mAP50, 4.7 MB). Subsequently, L2-based knowledge distillation recovers performance, yielding YOLOv11-PKD with 87.9% mAP50—approaching teacher-level accuracy—while maintaining 5.0 MB size, 2.150 M parameters, and 5.5 GFLOPS. The model is successfully deployed via a mobile application, achieving ~1 s response times for field-based plant identification. This work demonstrates a practical balance between accuracy and efficiency for resource-constrained ecological monitoring. Full article

Background/Objectives: Coping with death is an essential yet challenging aspect of nursing. In Ecuador, limited training and cultural factors may influence how nurses face the process of death and dying. This study aimed to explore nurses’ perspectives and highlight the degree of congruence between the numerical and discursive data provided by participants. Methods: A sequential explanatory mixed-methods design (QUAN → qual) using questionnaires and qualitative interviews was employed. The quantitative phase included 497 nurses who completed the Bugen Coping with Death Scale and the qualitative phase involved semi-structured interviews with 18 nurses. Quantitative data were analysed descriptively, while qualitative data underwent thematic analysis. Integration occurred at the methodological level—through the building of the qualitative data collection instrument—and at the levels of analysis and interpretation. Results: Nurses demonstrated moderate coping levels on the Bugen Coping with Death Scale. Although many reported being comfortable discussing death, qualitative data revealed substantial emotional distress and limited preparedness—particularly when facing their own mortality or the death of loved ones. Nurses expressed fear of suffering, sadness, and helplessness, especially when caring for dying children or young mothers. Communication with patients and families at the end of life emerged as a major challenge. Spirituality was identified as a key coping resource. Conclusions: Coping with death remains a complex and emotionally demanding process for nurses in Ecuador. Continuous education, emotional support, and training in spiritual and psychological dimensions of care are essential to strengthen nurses’ resilience and enhance the quality of care. Full article

Low-frequency hydrophones are used to detect underwater low-frequency acoustic signals and are widely applied in marine science, resource exploration, environmental monitoring, and military operations. Their primary advantage lies in the fact that low-frequency acoustic waves experience less attenuation in water, enabling long-distance detection. This characteristic makes them indispensable for long-range and wide-area sensing. In this study, a piston-structured hydrophone using a stack of lead zirconate titanate (PZT) piezoelectric ceramic sheets is designed. Finite element simulation analysis is used to derive the output voltage variation in the piezoelectric ceramic stack as a function of its thickness and end-face diameter. The piston-structured hydrophone is then designed accordingly. Results show that the piston structure, combined with the longitudinal stacking of PZT piezoelectric ceramic sheets, enhances the sensitivity of the piezoelectric hydrophone. The prepared hydrophone has a directivity of 360° in the operating frequency range of 1 Hz to 1 kHz, as well as a flat frequency response and high sensitivity of −161 dB. These research results indicate that the proposed sonar design provides valuable reference for the development of low-frequency sonar with higher sensitivity, which is of great significance to the development of marine science. Full article

Traditional textile crafts face significant challenges in preserving and transferring knowledge due to the aging of expert artisans and declining community engagement. The Phum Riang silk-weaving tradition in Suratthani Province is a critical example of indigenous knowledge systems that require systematic documentation and digital conservation strategies. This research aims to develop a comprehensive ontological framework to support the capture, organization, and preservation of traditional knowledge related to Phum Riang silk production processes, establishing practical methodologies applicable to broader cultural heritage craft digitization and knowledge management systems. The research methodology employs ontology engineering principles, using the Web Ontology Language to create structured knowledge representation systems. Data collection was conducted through ethnographic fieldwork, in-depth interviews with expert craftspeople, and systematic documentation covering production processes, materials, tools, and cultural practices. The developed ontology encompasses five primary knowledge domains: production processes, raw materials, traditional tools, geographical context, and cultural significance. The framework comprises 23 distinct classes organized in hierarchical structures, 15 object properties, and 12 data properties, complemented by business rules ensuring authenticity and quality control mechanisms. This framework has significant implications for cultural heritage digitization, indigenous intellectual property protection, systematic knowledge transfer across generations, cultural authenticity preservation, and traditional craft community economic sustainability. Full article

Introduction: In recent decades, demographic aging has led to an inversion of the population pyramid, with a marked increase in the proportion of older adults. This shift has been accompanied by a higher prevalence of chronic and life-limiting diseases, while there have also been significant technical and scientific advances. However, these developments have not been matched by a proportional expansion of healthcare human resources, including in palliative care (PC). Consequently, healthcare systems face increasing pressure, particularly in the provision of end-of-life care. Artificial intelligence (AI) has emerged as a promising tool to support and improve healthcare delivery. Objective: This study aims to review the literature on the impact of AI on palliative care, with particular emphasis on its clinical applications and ethical implications in end-of-life care. Methods: A narrative review was conducted using a structured search of PUBMED, CINAHL and Web of Science databases, covering publications from the last ten years (2015–2025). Search terms included combinations of “artificial intelligence”, “machine learning”, “palliative care”, “end-of-life care”, and “ethics”. Articles were included if they addressed clinical applications, implementation challenges or ethical aspects of AI in PC. Reference lists of selected articles were screened to identify additional relevant studies. The findings were analyzed and synthesized thematically into key domains of application and ethical concern. Results: The literature suggests that AI is currently a promising tool in PC, particularly in prognostication, symptom assessment, clinical decision support, and communication. These applications may represent a paradigm shift compared to conventional approaches. However, it is important not to forget that patients in PC need much more than algorithmic decision trees. Thus, current evidence is largely exploratory, with limited real-world validation. Empathetic emotional support, physical comfort and compassion are things that artificial intelligence cannot provide. AI does not replace humans in interpersonal relationships and dignity; it only complements them. Conclusions: AI-based technologies hold significant potential to address contemporary challenges in PC, including inequitable access, workforce strain, and the need for more efficient service delivery. Nevertheless, their implementation raises substantial ethical concerns related to autonomy, transparency, data governance, and the preservation of human dignity. AI should therefore be understood as a complementary tool that supports—but does not replace—the human dimension of PC. Full article

As a key technology for achieving building heating electrification and decarbonization, the air-source heat pump (ASHP) has long been constrained by outdoor heat exchanger frosting in cold and humid regions. Frosting leads to increased thermal resistance, a sharp rise in air-side pressure drop, and the attenuation of heating capacity, while traditional active defrosting methods, such as reverse-cycle defrosting, suffer from high energy consumption and heating interruption. This review aims to systematically present the recent research progress of superhydrophobic surfaces (SHSs) as a highly efficient passive anti-frosting strategy. First, the complex phase-change dynamics of frosting and key influencing factors such as environment and surface characteristics are deeply analyzed. Second, it elucidates how superhydrophobic surfaces achieve delayed frosting and sloughing off defrosting by delaying nucleation, promoting droplet self-removal, and reducing ice adhesion. Furthermore, fabrication processes suitable for complex fin structures are systematically reviewed from the perspectives of subtractive manufacturing, in situ growth, and additive coatings, and their industrialization prospects are compared. Finally, the practical effects of this technology in improving heat transfer coefficients, reducing fan energy consumption, and improving defrosting efficiency are evaluated. Although superhydrophobic technology has significant energy-saving potential, it still faces challenges such as poor long-term durability, wettability failure under extreme conditions, and residual micro-droplets. Future research should focus on the development of highly durable materials, the matching design of micro–nano structures with macro flow channels, and active–passive synergistic anti-frosting strategies. Full article

Background: Retinitis pigmentosa (RP) is a progressive inherited retinal dystrophy that affects daily functioning, psychological well-being, and social participation. Although quantitative research describes disease burden, less is known about how individuals experience progressive vision loss in everyday life and within healthcare and social contexts. Methods: This qualitative study used semi-structured face-to-face interviews with adults diagnosed with RP. Purposive sampling was applied to ensure variation in demographic and clinical characteristics. Interviews were conducted in a tertiary ophthalmology clinic in Erzincan, Türkiye, between June and October 2025. Audio recordings were transcribed verbatim and analyzed using Braun and Clarke’s reflexive thematic analysis. Reporting followed the Consolidated Criteria for Reporting Qualitative Research (COREQ) checklist. Results: Sixteen participants (P1–P16) were included. Five themes were identified: (1) making sense of the illness and the diagnostic journey; (2) functional loss and the negotiation of independence; (3) psychological adaptation and identity reconstruction; (4) social relationships and social encounters; and (5) interaction with systems and the environment—accessibility and healthcare. Participants described early symptom normalization, delayed diagnostic pathways, and uncertainty persisting after diagnosis. Independence was shaped by safety concerns, environmental barriers, and reliance on support. Psychological adjustment fluctuated between fear of progression and efforts to sustain resilience. Social participation was influenced by support networks, concerns about being a burden, and stigma linked to invisible disability. Conclusions: Living with RP extends beyond visual impairment; building on prior qualitative work, our findings contextualize these experiences in Türkiye, highlighting how accessibility gaps, bureaucratic encounters in public institutions, and cost barriers within healthcare and public services can shape uncertainty, independence, and social participation. Full article

This systematic review examines how gender shapes exposure to and experiences of psychosocial risks in the workplace. Drawing on 89 empirical studies published between 2010 and 2024, the review synthesizes evidence from occupational health psychology, gender studies, and organizational research. Searches were conducted in PubMed, Web of Science, Scopus, CINAHL, and PsycINFO, and included empirical studies published in English and Spanish. Following PRISMA guidelines, a qualitative thematic synthesis was conducted to integrate findings across diverse sectors, populations, and methodological approaches. The evidence reveals persistent gendered patterns in psychosocial risk exposure and outcomes: women are more frequently exposed to emotionally demanding and relational forms of work and report poorer mental health outcomes; men experience performance-driven strain linked to workload, competition, and reward insecurity more often; and transgender and non-binary workers face additional psychosocial burdens associated with stigma, discrimination, and minority stress. Across the literature, structural and cultural determinants—such as occupational segregation, unequal recognition, and gendered organizational norms—emerge as central mechanisms underlying these disparities. Theoretical frameworks including effort–reward imbalance, demand–control, work–family conflict, organizational climate, and minority stress collectively contribute to explaining how gendered psychosocial risks are produced and sustained. Overall, the review underscores the need to move beyond individualistic and binary models of psychosocial risk toward gender-responsive approaches that account for structural, relational, and identity-based dimensions of work, thereby informing research and organizational strategies aimed at promoting equitable and sustainable well-being at work. Full article