Search Results (1,028)

Virtual reality heritage experiences can be understood as multisensory interaction systems, yet how auditory, haptic, and gestural cues combine at the system level to shape electronic word-of-mouth (eWOM) intention remains insufficiently understood. Addressing this problem from a configurational systems perspective, this study applies fuzzy-set qualitative comparative analysis (fsQCA) to five auditable interaction cues (acoustic clarity, rhythmic drive, vibrotactile actuation level, gesture complexity, and compound gesture frequency) across a set of widely used VR cultural heritage applications. The results identify two sufficient system-level pathways to high eWOM intention: a rhythm-driven, low-burden pathway and a coordination-driven pathway characterized by clearer audio, stronger rhythmic structure, and tighter haptic and gestural action closure. Low eWOM intention is most consistently associated with weak cue interpretability, limited temporal drive, or unbalanced stimulation patterns, suggesting that isolated enhancement of single channels does not reliably translate into downstream sharing intentions. These findings reposition VR heritage design as a problem of configuring coherent multisensory interaction systems rather than maximizing individual stimuli. The study contributes a bounded, case-comparative account of how auditable cue bundles shape eWOM intention and offers system design guidance for resource-sensitive multisensory coordination in VR heritage applications. 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

This article examines the ethical and aesthetic stakes of cultural borrowing in fashion through the case of Yves Saint Laurent’s sustained engagement with Moroccan visual and material traditions. Drawing on postcolonial theory, fashion studies, and aesthetic philosophy and supported by visual analysis and qualitative research, this study interrogates the tension between cultural appreciation and appropriation that structures Saint Laurent’s legacy. His designs amplified global visibility for Moroccan craftsmanship, yet this visibility was mediated through Western systems of authorship that privileged the couturier while obscuring the cultural, spiritual, and artisanal labor underpinning the motifs he reinterpreted. Saint Laurent’s own positionality, born within the colonial milieu of French Algeria, further complicates this dynamic, enabling both cultural intimacy and the exercise of hierarchical distance from the traditions he transformed for Parisian haute couture. This discussion also requires acknowledging that Moroccan cultural heritage, shaped by the intertwined influences of Amazigh, Arab, Islamic, and Jewish traditions, embodies religious meanings that extend beyond the purely aesthetic. By considering the religious, symbolic, and communal values embedded within Moroccan aesthetic forms, this article foregrounds the ethical dilemmas that arise when culturally and spiritually situated practices are reframed within Western fashion. This study ultimately contends that acts of borrowing can serve both as homage and erasure, suggesting that the relationship between appropriation and appreciation is better understood as a flexible spectrum rather than a rigid binary. Full article

Carbon fiber-reinforced polymer (CFRP) is extensively applied in aerospace and rail transportation industries, and the quality of CFRP joint holes is crucial for ensuring joint performance and service reliability. However, CFRP drilling involves complex interactions among drilling parameters, tool geometry, and multiple quality indicators, making it difficult to accurately predict drilling quality and identify optimal process parameters. In this study, drilling experiments using twist drills and dagger drills were conducted to analyze the relationships among drilling parameters, drilling physical indicators, and drilling quality indicators. Compared to the twist drill, the dagger drill maintained lower thrust force and cutting temperature, and reduced the delamination factor, burr factor, and drilling wall roughness by 20.6%, 95.5%, and 81.1% on average, respectively. To consider the effect of different drilling indicators on the quality of CFRP drilling holes, a comprehensive fuzzy evaluation prediction model FCE-NN for drilling quality was proposed. The average prediction accuracy reached 91.3% and the drilling indicators FCE were output. The NSGA-II algorithm was employed, and an entropy-weighted TOPSIS method integrated with fuzzy comprehensive evaluation (FCE) was used to rank the Pareto-optimal solutions, thereby achieving multi-objective optimization of the thrust factor, delamination factor, and machining efficiency. Full article

This study develops a comprehensive carbon footprint assessment model that integrates forward and reverse logistics to evaluate and compare greenhouse gas emissions from online and offline apparel sales channels in China, with a particular focus on high return rates. The model quantifies emissions from transportation, packaging, storage, and operations, incorporating return and exchange logistics. The system boundary is limited to enterprise-controllable sales-phase activities and excludes consumer travel. Three sales models are compared: factory-to-consumer (F2C), traditional business-to-consumer (B2C) e-commerce, and brick-and-mortar retail (BMR). Within this defined boundary, BMR exhibits the lowest carbon footprint (0.296 kg CO₂e/item), followed by F2C (0.408 kg CO₂e/item) and B2C (0.602 kg CO₂e/item). Packaging dominates online emissions (55–57%), whereas store operations are the main contributor to offline emissions (43%). Return rates are identified as a decisive factor, accounting for over 31% of e-commerce emissions and potentially increasing them by 171.3% under extreme scenarios. Sensitivity analysis reveals that trunk line distance (factory to warehouse) has a greater impact on emissions than last-mile return route optimization. Relocating the factory closer to consumers reduces B2C transport emissions by 72.3%, whereas replacing conventional packaging with recycled plastic reduces total B2C emissions by 46.0%. These findings provide channel-specific sustainability strategies: return reduction and packaging innovation for online channels, and energy efficiency improvements for physical stores. These results are conditional on the defined system boundary. If consumer travel by private car were included, the relative advantage of offline channels would diminish or could reverse. Full article

This study investigates how externally designable attributes of eco-printed womenswear shape consumer acceptance. Existing research has paid more attention to sustainability attitudes in general than to how product-specific design cues influence acceptance in this context. Using an exploratory sequential mixed-methods design, the study combines qualitative interviews with a survey of 992 female consumers in mainland China. The results show that consumer acceptance develops through an attribute–value–attitude–intention pathway rather than from abstract environmental concern alone. Fabric Perception, Colour Preference, and Structure and Craft Awareness influence functional value, emotional value, and environmental value, which subsequently shape consumer attitude and purchase intention. Among these attributes, Structure and Craft Awareness exerts the strongest effect on environmental value and consumer attitude. The study further develops a data-calibrated analytic hierarchy process (DC-AHP) to translate behavioural evidence into design priorities. The findings extend sustainable fashion research by clarifying the product-based mechanism of consumer acceptance and provide evidence to support design-priority setting in eco-printed womenswear. Full article

This article offers an exploratory overview of the contemporary Ethiopian textile, fashion and apparel system. The contribution originated from a teaching experience in Addis Ababa within the framework of the AICS–UNIDO-funded project “Ethiopia: Support to Youth and Women through Products and Services Development and Public–Private Partnerships in the Fashion Value Chain” which prompted the authors to deepen their understanding of the local fashion ecosystem. Drawing on informal conversations, observations, and ethnographically oriented field notes, the authors developed the analysis through desk research and a review of the relevant literature. The picture that emerges reveals both the creativity and strong entrepreneurial drive of Ethiopian designers, alongside the structural barriers they commonly face, including limited access to materials, investment, and institutional support. Designers are shown to negotiate ongoing tensions between cultural heritage and global aesthetics, while also contending with local consumption patterns situated between second-hand clothing markets and international brands. These dynamics highlight both the challenges and the potential of the Ethiopian fashion scene, pointing to opportunities for mutual learning and for fostering fashion practices that are sustainable, globally relevant, and firmly grounded in local contexts. Full article

Background/Objectives: Surface Electromyography (sEMG) presents tremendous potential as a non-invasive interface for the detection of motor intent, yet the low signal-to-noise ratio, subject variability, and the need to capture patterns at both long and short timescales make the recognition of hand gestures challenging. Methods: In this paper, the HAMSNet model is presented, which is designed for the recognition of ten different hand gestures using the sEMG signal. Sliding window segmentation is employed to segment the signal into fixed-length time windows, and channel-wise z-score normalization is applied to reduce amplitude variations. To capture the signal at different timescales, the model utilizes the Hydra 1D convolutional neural network (1D CNN), which extracts both short-range and long-range features. Furthermore, the learned features are refined using the multi-head self-attention technique, which highlights the more discriminative time regions. Finally, the Squeeze-and-Excitation (SE) technique is employed to refine the obtained features by channel-wise recalibration. Results: The model is trained in end-to-end fashion, and the results are validated using the 80/20 split method, where the model achieves 0.9894 accuracy, Macro F1 of 0.9894, and an ROC-AUC score of 0.99977. Additionally, the model achieves an MSE score of 0.001969. Furthermore, the model also achieves high accuracy under the leave-one-subject-out cross-validation (LOSO-CV) protocol, providing encouraging evidence of subject-independent performance within the evaluated dataset. Conclusions: The obtained HAMSNet model’s results are compared with the existing results from the literature on the same dataset. The comparisons show that the HAMSNet outperforms the existing methods. An ablation study is conducted to validate the contribution of each component to the proposed model and an explainability analysis is conducted to indicate the interpretability of the model’s decisions. Full article

In recent years, the development of generative artificial intelligence, particularly diffusion models such as Stable Diffusion (SD), has provided new opportunities for the digital representation and creative dissemination of cultural heritage. This study takes Shanghai revolutionary cultural heritage as a case study and develops an application-oriented integrated workflow for generating revolutionary cultural images. By introducing Low-Rank Adaptation (LoRA) into the SD framework and combining structural control with local refinement strategies, this study enhances the style expression and structural quality of the generated images. Furthermore, an interactive creation platform is constructed to support the generation and creation of revolutionary cultural images. The evaluation results, including subjective assessment and SSIM/LPIPS metrics, indicate that the proposed workflow achieves higher style consistency and structural reliability while improving the structural integrity and detail reliability of facial regions. The proposed workflow and platform are intended to support revolutionary cultural venues in practical digital production and dissemination of heritage content while also promoting public engagement with revolutionary culture, especially among younger audiences. This study highlights the application potential of generative Artificial Intelligence (AI) in enhancing the accessibility, digitalization, and sustainable dissemination of revolutionary cultural heritage. It also provides a practical reference for interdisciplinary research in the field of cultural heritage and AI-assisted digital communication. Full article

In this work we propose a new strategy for the optimization of the flap position of a high-lift configuration in the framework of a hybrid electric regional aircraft. The approach is based on the multidisciplinary design optimization software GEMSEO and the high-performance CFD solver CODA. The CFD solver CODA solves the RANS equations on a body-fitted mesh along with immersed boundary methods, while the package GEMSEO employs the COBYQA optimization algorithm. The main airfoil is meshed in a body-fitted fashion, and a refined region is created just where the flap can be located. The employment of immersed boundary methods allows us to arbitrarily change the deflection angle and leading edge position of the flap inside this refined region without the need of remeshing the whole computational domain. The main advantage of this methodology with respect to a full body-fitted mesh scheme is the computational efficiency when hundreds or thousands of CFD-RANS simulations are required by the optimizer. We demonstrate the effectiveness of this optimization methodology in the computation of the optimal configuration of the flap during takeoff and landing phases of a high-lift airfoil. Full article

To improve coating adhesion and tribological stability on aircraft-grade aluminum, this work utilizes periodic fiber-laser microtexts as a surface-engineering pre-treatment before applying an epoxy primer. AA2024-T3 panels were imprinted with rhombus, hexagon, and circular lattices (scale factors 100–250 µm; scan speeds 250–750 mm s⁻¹), then primed with an aerospace epoxy primer and evaluated within reciprocating sliding wear tests. Areal profilometry and sessile-drop goniometry measured topography and wettability, whereas friction–distance traces and scratch-track metrology resolved interfacial integrity. The textures expanded surface area and modified energy states in a geometry- and scale-dependent fashion, producing stable friction plateaus and smaller, less-lateral scratch scars compared to the untextured reference. Circular dimples reliably provided the best damage-tolerant behavior, a function of improved mechanical interlocking and debris/film management (reservoir and micro-trap effects), whereas polygonal lattices evidenced greater sensitivity to both scale and speed. Factorial analyses disclosed prevalent interaction effects amongst geometry, scale, and scan speed, reinforcing the notion that performance arises from co-optimized texture architecture rather than a single parameter. In systemic terms, laser-defined microtexts complemented with aerospace-standard primers represent a controllable pathway to vary friction, dampen wear, and improve coating–substrate adhesion. These results provide practical selection guides; and a broad selection prefers larger, well-spaced circular dimples for best-in-class performance and a transferable framework for designing texture-coating systems across aerospace and allied manufacturing contexts. Full article

The Book of Margery Kempe is an extraordinary work of female visionary writing, in which Margery Kempe narrates her intimate and direct communications with Jesus Christ. The aim of this paper is to investigate how Kempe fashions herself into an authoritative religious figure and the impact of her self-fashioning. The study reveals that Kempe builds up her image as a chosen woman through a designed narrative discourse, which features disorder, imbalance, and homogeneity. To be specific, Kempe intentionally foregrounds her spiritual life endorsed by Christ and downplays her secular life in order to establish her authority. Moreover, Kempe’s work replicates the essential ingredients of hagiography, namely trials, divine intervention, and redemption, which naturally elevates Kempe to sainthood and therefore justifies her position of spiritual authority. Following on from this, Kempe, like other holy women, is well-qualified to instruct her fellow Christians to emulate her form of life, that is, to live a devout life. The establishment of Kempe’s spiritual authority is the epitome of women’s pursuit of spiritual leadership in the later Middle Ages, when they struggled with social conventions and ecclesiastical regulations. Full article

Deep neural networks (DNNs) are traditionally analyzed as black-box function approximators, yet their internal structure exhibits phase transitions characteristic of complex physical systems. In this study, we investigate topological–functional decoupling—the phenomenon whereby a network retains full graph connectivity while losing computational function—in trained neural networks through the lens of percolation theory. By subjecting three distinct architectures (Shallow, Deep, and Wide MLPs) to a unified edge-pruning analysis on Fashion-MNIST, we uncover a fundamental divergence between structural integrity and computational capacity in this experimental setting. We report three key phenomena observed in these experiments: (1) the zombie network state under stochastic pruning, where the system retains global connectivity ($P_{\infty }\approx 1.0$) yet suffers a catastrophic functional collapse (accuracy falls below 50% of baseline at prunning ratio $p_f\approx 0.35$–$0.68$ depending on depth), proves that graph reachability does not imply computational capability; (2) depth fragility, where increased network depth triggers multiplicative signal decay (the avalanche effect), rendering deep architectures exponentially more vulnerable to random edge removal than shallow ones ($p_f^{\mathrm{deep}}\approx 0.35$ vs. $p_f^{\mathrm{shallow}}\approx 0.68$); and (3) scale-free universality, observed under magnitude-based pruning, where a robust functional skeleton maintains accuracy near the baseline (∼89%) up to extreme sparsity ($p_f\approx 0.85$–$0.95$) across all three architectures. Robustness stems not from holographic redundancy in the overall connection count but from the emergent heavy-tailed rich-club organization of weight magnitudes—a sparse set of high-magnitude synapses that form the functional backbone of the network, decoupled from the redundant topological mass. These findings offer new physical constraints for the design of resilient neuromorphic hardware. Full article

This article advances a critical rethinking of digital transformation in craft-based and socially embedded production systems by examining ateliers of social integration as community-led solidarity spaces where sewing and embroidery practices intersect with relational, care-oriented, and collective dimensions. Existing debates on digitalisation remain largely centred on automation, scale, and efficiency, overlooking how technology operates within care-based and territorially embedded economies. To address this gap, the article develops an alternative analytical framework grounded in relational economies and the ethics of care. While the phenomenon is transnational, the empirical analysis focuses on the Italian context and draws on data from CreAbility, an ongoing action-research project aimed at building a digital community of micro and small fashion enterprises, associations, and designers characterized by social and cultural impact. Against dominant, scale-oriented models of innovation, the article conceptualises ateliers of social integration as relational ecosystems in which value is co-produced through social ties, inclusion practices, and localized knowledge. From this perspective, digital technologies serve as situated mediators that extend and amplify proximity-based relations. This reframing challenges linear and growth-centred accounts of digital innovation, instead proposing a non-linear, care-centred, and place-based model of digital transformation. Methodologically, the study adopts a mixed-methods design combining quantitative and qualitative techniques. Data were collected between June and July 2025 through an online questionnaire distributed to a broader population of Italian ateliers of social integration and were complemented by participatory focus groups involving organisational representatives. The findings show that these ateliers operate as infrastructures of proximity in which production, care, and community are co-constitutive, and where digital practices support forms of extended embeddedness rather than substitution. In doing so, the article contributes to debates on digitalisation, social innovation, and the care economy by showing how alternative, relational, and non-scalable models of production can reshape the meaning and the trajectories of innovation. Full article

Personalized federated learning (PFL) faces significant challenges in resource-constrained edge environments, where strict communication budgets and severe system heterogeneity must be jointly addressed. Although one-shot federated learning reduces communication overhead, existing methods typically impose unified model architectures or rely on coarse manual selection strategies, limiting their adaptability to highly heterogeneous data distributions and restricting personalized representation capability. To overcome these limitations, we propose Personalized Federated Zero-shot Knowledge Distillation (pFedZKD), a data-free one-shot federated learning framework designed for structurally heterogeneous scenarios. The framework follows a decouple-and-reconstruct collaborative paradigm. On the client side (decoupling stage), we introduce Particle Swarm Optimization-based Federated Neural Architecture Search (PSO-FedNAS), a gradient-free neural architecture search method that enables each client to autonomously discover a customized convolutional architecture aligned with its local data distribution, eliminating the need for architectural consistency across clients. On the server side (reconstruction stage), to address parameter-space incompatibility caused by structural heterogeneity, we develop an architecture-agnostic multi-teacher zero-shot knowledge distillation mechanism (Multi-ZSKD). This method synthesizes pseudo-samples in latent space to extract semantic consensus from heterogeneous client models and transfers the aggregated knowledge to a unified global student model without accessing real data. The entire collaborative process is completed within a single communication round, substantially reducing communication cost while enhancing privacy preservation. Extensive experiments on MNIST, FashionMNIST, SVHN, and CIFAR-10 under heterogeneous data settings demonstrate that pFedZKD consistently achieves superior personalization accuracy, global generalization performance, and communication efficiency compared with state-of-the-art PFL methods. Full article