Search Results (10,825)

As a task in the digital preservation of calligraphy stone inscriptions, an invaluable cultural heritage, style classification faces prominent challenges: insufficient feature representation of single-channel rubbings, and difficulties in effectively capturing the complex strokes and spatial layouts inherent to calligraphic works. To tackle these issues, an efficient deep learning model integrated with the dual-path attention mechanism of Bottleneck Attention Module (BAM) is proposed in this paper, which is designed to achieve accurate and efficient classification of calligraphy styles. With the lightweight network EfficientNetB2 as its backbone, this model innovatively integrates the BAM. It realizes the channel-spatial collaborative attention in calligraphy analysis, with the weight of stroke structure features increased to over 85%. Through the synergistic effect of channel attention and spatial attention, the model’s ability to extract stroke structure and spatial layout features from calligraphy images is significantly enhanced. The experimental results on the stratified sampling dataset show that the model achieves an accuracy of 98.44% on the test set, a confusion matrix recall rate of 94.80%, an F1-score of 0.9675, a precision of 0.8690, and a macro-averaged Area Under the Curve (AUC) value of 0.9694. To further validate the effectiveness of the BAM module and the necessity of its dual-path design, we conducted a systematic ablation experiment analysis. The experiment used EfficientNet-B2 as the baseline model and sequentially compared the contributions of different attention mechanisms. The experimental results show that the method proposed in this paper balances efficiency and performance, and holds practical significance in fields such as ancient book authentication and calligraphy research. Full article

Cultural ecosystem services (CESs) play a critical role in urban residents’ well-being, yet conventional evaluations rely heavily on green-space area and overlook how facility quality and basic services influence the delivery of actual cultural benefits. To address this methodological gap, this study develops a three-tier evaluation framework—service potential, actual supply capacity, and actual service utility—to quantify multistage attenuation in CES provision across 95 parks in seven central districts of Shenyang, China. The framework integrates 114 quantitative and qualitative indicators from field surveys, national facility standards, and perception-based assessments, enabling a scientifically robust and replicable assessment of how cultural benefits are transformed from ecological structure to human experience. Results reveal that single-index, area-based assessments substantially overestimate CES supply: district-level supply–demand ratios drop from 66 to 195% to only 11–55% once quality and basic services are incorporated. Comprehensive and special parks retain the highest CES potential, whereas community and linear parks undergo significant losses due to aging facilities, insufficient maintenance, and inadequate infrastructure. Education and cultural services exhibit the most severe shortages, with deficits reaching 59–84%, underscoring structural limitations in learning-oriented spaces. By distinguishing structural (quantity), functional (quality), and experiential (basic service) constraints, the framework provides clear diagnostic guidance for targeted planning and management. Its multistage structure also reflects broader principles of sustainable urban development: improving CES requires not only expanding ecological elements but also enhancing service quality, strengthening infrastructure, and promoting equitable access to cultural benefits. The framework’s generalizability makes it applicable to high-density cities worldwide facing land scarcity and green-space inequality, supporting efforts aligned with SDG 11 to build inclusive, resilient, and culturally vibrant urban environments. Full article

γ-Aminobutyric acid (GABA) is a bioactive metabolite valued in functional foods, but its microbial production is strongly influenced by nutrient availability. Levilactobacillus brevis CRL 2013 is an efficient GABA producer; however, its biosynthesis depends on culture medium composition. In this study, integrated physiological, proteomic, and transcriptional analyses were applied to assess the influence of nitrogen source composition and concentration on GABA production. No extracellular GABA was detected in a chemically defined medium containing all amino acids and glutamate (CDMg), whereas supplementation with yeast extract or Casitone restored high-level production. The highest GABA accumulation (~250 mM) was obtained in CDMg supplemented with 1% yeast extract or 2% Casitone, and a clear peptide dose-dependent effect was observed. In contrast, other protein hydrolysates or free amino acids alone did not stimulate GABA synthesis. Proteomic analysis revealed overexpression of the key enzyme GadB and changes in nucleotide and fatty acid pathways. Transcriptional analysis confirmed that peptide supplementation was accompanied by increased transcription of the gadRCB–gltX operon, in agreement with GABA accumulation. Overall, these results demonstrated that peptide composition and availability are critical determinants of GABA biosynthesis in Lv. brevis CRL 2013and provide a basis for optimizing peptide-based media to enhance GABA formation in food fermentations. Full article

Digital twins (DTs) powered by artificial intelligence (AI) are becoming important transformational tools in healthcare, enabling real-time simulation and personalized decision support at the patient level. The aim of this review is to critically examine the evolution, current applications, and future potential of AI-based DTs in healthcare, with a particular focus on their role in enabling real-time simulation and personalized patient-level decision support. Specifically, the review aims to provide a comprehensive overview of how AI-based DTs are being developed and implemented in various clinical domains, identifying existing scientific and technical gaps and highlighting methodological, regulatory, and ethical issues. Taking a “local to global” perspective, the review aims to explore how individual patient-level models can be scaled and integrated to inform population health strategies, global data networks, and collaborative research ecosystems. This will provide a structured foundation for future research, clinical applications, and policy development in this rapidly evolving field. Locally, DTs allow medical professionals to model individual patient physiology, predict disease progression, and optimize treatment strategies. Hospitals are implementing AI-based DT platforms to simulate workflows, efficiently allocate resources, and improve patient safety. Generative AI further enhances these applications by creating synthetic patient data for training, filling gaps in incomplete records, and enabling privacy-respecting research. On a broader scale, regional health systems can use connected DTs to model population health trends and predict responses to public health interventions. On a national scale, governments and policymakers can use these insights for strategic planning, resource allocation, and increasing resilience to health crises. Internationally and globally, AI-based DTs can integrate diverse datasets across borders to support research collaboration and improve early pandemic detection. Generative AI contributes to global efforts by harmonizing heterogeneous data, creating standardized virtual patient cohorts, and supporting cross-cultural medical education. Combining local precision with global insights highlights DTs’ role as a bridge between personalized and global health. Despite the efforts of medical and technical specialists, ethical, regulatory, and data governance challenges remain crucial to ensuring responsible and equitable implementation worldwide. In conclusion, AI-based DTs represent a transformative paradigm, combining individual patient care with systemic and global health management. These perspectives highlight the potential of AI-based DTs to bridge precision medicine and public health, provided ethical, regulatory, and governance challenges are addressed responsibly. Full article

Mesenchymal stromal cells (MSCs) are multipotent and play an important role in regenerative processes such as wound healing. Data on possible changes and functional restrictions of MSCs due to cisplatin chemotherapy, for example, in the treatment of head and neck cancer, diverge. The aim of this study was to evaluate the influence of cisplatin on MSCs with regard to their defining characteristics and their ability to differentiate and to migrate. MSCs from four human donors (a 59-year-old man, a 63-year-old woman, a 70-year-old man, and a 61-year-old man) were cultured in vitro with and without cisplatin for 24 h, and toxic and subcytotoxic concentrations were determined using an MTT. We then examined the surface phenotype markers (flow cytometry), migration (scratch assay), histological differentiation markers (adipo-, chondro-, osteogenic), and the expression of selected line-associated genes in real-time quantitative PCR (RT-qPCR) (LEP, SOX9, RUNX2). These characteristics were evaluated after treatment with different subcytotoxic, clinically relevant doses of cisplatin. Flow cytometry confirmed the presence of MSCs-characteristic surface markers, which remained stable under treatment with subcytotoxic doses of cisplatin. Cisplatin exposure reduced the mRNA abundance of leptin (a marker for adipogenic differentiation) but increased SOX9 mRNA abundance (chondrogenic differentiation). RUNX (osteogenic differentiation) did not change post cisplatin exposure. Histological analysis showed no difference with regard to osteogenic, chondrogenic, and adipogenic differentiation at doses up to 10 μM cisplatin. Cell migration was not restricted by cisplatin exposure under the conditions used here. The characteristics of MSCs were not different to controls post cisplatin exposure. mRNA analysis suggested induced changes by cisplatin, although this effect was not histologically detectable even at high doses. Based on the single-molecule markers used here, indications for an inhibitory effect of cisplatin on adipogenic differentiation and a rather enhancing effect on chondrogenic and osteogenic differentiation may be hypothesized. The process observed here could further aggravate the already serious problem of malnutrition in head and neck cancer patients, for example. Taken together though, our study confirms overall MSCs tolerance towards cisplatin. Full article

Facial expression recognition (FER) is a key task in affective computing and human–computer interaction, aiming to decode facial muscle movements into emotional categories. Although deep learning-based FER has achieved remarkable progress, robust recognition under uncontrolled conditions (e.g., illumination change, pose variation, occlusion, and cultural diversity) remains challenging. Traditional Convolutional Neural Networks (CNNs) are effective at local feature extraction but limited in modeling global dependencies, while Vision Transformers (ViT) provide global context modeling yet often neglect fine-grained texture and frequency cues that are critical for subtle expression discrimination. Moreover, existing approaches usually focus on single-domain representations and lack adaptive strategies to integrate heterogeneous cues across spatial, semantic, and spectral domains, leading to limited cross-domain generalization. To address these limitations, this study proposes a unified Multi-Domain Feature Enhancement and Fusion (MDFEFT) framework that combines a ViT-based global encoder with three complementary branches—channel, spatial, and frequency—for comprehensive feature learning. Taking into account the approximately bilateral symmetry of human faces and the asymmetric distortions introduced by pose, occlusion, and illumination, the proposed MDFEFT framework is designed to learn symmetry-aware and asymmetry-robust representations for facial expression recognition across diverse domains. An adaptive Cross-Domain Feature Enhancement and Fusion (CDFEF) module is further introduced to align and integrate heterogeneous features, achieving domain-consistent and illumination-robust expression understanding. The experimental results show that the proposed method consistently outperforms existing CNN-, Transformer-, and ensemble-based models. The proposed model achieves accuracies of 0.997, 0.796, and 0.776 on KDEF, FER2013, and RAF-DB, respectively. Compared with the strongest baselines, it further improves accuracy by 0.3%, 2.2%, and 1.9%, while also providing higher F1-scores and better robustness in cross-domain testing. These results confirm the effectiveness and strong generalization ability of the proposed framework for real-world facial expression recognition. Full article

Background/Objectives: Craft non-alcoholic and low-alcohol beer (NABLAB) is attracting increasing attention as potential functional beverages due to their content of bioactive compounds such as polyphenols, vitamins, and minerals, and their suitability for health-oriented lifestyles. This study investigated Italian consumers’ perceptions of craft NABLAB and explored possible generational differences in their acceptance. Methods: A descriptive cross-sectional online survey was conducted between March 2024 and March 2025 among adults living in Italy. The questionnaire, composed entirely of closed-ended questions, investigated familiarity with craft NABLAB, attitudes toward their potential health-related properties, and willingness to recommend them. Results: A total of 527 valid responses were analyzed descriptively and grouped by generation (Generation Z, Millennials, Generation X, and Baby Boomers). Results showed that 68.3% of participants would recommend craft NABLAB to others interested in their functional properties, while 55.0% reported higher motivation to purchase when informed about their potential health benefits. Familiarity with these products remained limited (34.7% had tried them, and only 22.2% considered them easy to find). Baby Boomers and Millennials were more receptive, possibly due to greater health awareness and openness to innovation, whereas Generation Z displayed curiosity despite lower consumption experience. Conclusions: Overall, Italian consumers show a growing interest in craft NABLAB, especially when linked to wellness and active lifestyle benefits. Enhancing product availability and communication focused on health and functionality could promote more moderate and conscious drinking habits, contributing to a gradual cultural shift toward reduced alcohol consumption. Full article

To systematically quantify the ecosystem service values in aquaculture ponds and reveal their temporal dynamics, this study provides a scientific basis for promoting sustainable green aquaculture and enhancing ecological and economic benefits. Using a 0.4 hm² grass carp pond in Songjiang District, Shanghai as the study site, we developed an evaluation framework of “base equivalent—dynamic equivalent—value quantification” and incorporated temperature spatiotemporal adjustment factors and social development coefficients to refine traditional models. The results indicate significant seasonal fluctuations in ecosystem service values for grass carp ponds. The highest value occurs in July at 21,868.21 CNY, and the lowest occurs in February at 4110.22 CNY, with a peak-to-trough ratio of 5.3. Among the five service functions, hydrological regulation accounts for the largest share (approximately 55%), followed by gas regulation (20%) and climate regulation (10%), while environmental purification and aesthetic landscapes, though contributing smaller proportions, remain indispensable. Temperature adjustment factors significantly enhance aquatic plant photosynthesis and microbial metabolism during high-temperature periods (>25 °C), whereas low temperatures suppress these ecological processes. The integration of social development coefficients effectively corrects underestimations of willingness to pay for cultural services. Compared to traditional seasonal-scale assessments, the monthly-scale approach substantially improves the explanatory power for pond ecological processes, offering quantitative support for differentiated ecological compensation mechanisms and optimized aquaculture management practices. Full article

Background/Objective: Hypertension is a major global health concern and a leading cause of cardiovascular morbidity and mortality. Lifestyle behaviors, such as diet, physical activity, stress management, and self-confidence, markedly influence hypertension control. Exploring these behaviors can inform culturally relevant interventions for improving the prevention and management of hypertension and health outcomes of affected individuals. This study aimed to determine the effects of lifestyle behaviors, including dietary habits, physical activity, stress management, and self-confidence, on optimizing hypertension control among individuals in Saudi Arabia. Methods: A cross-sectional, descriptive–correlational design was used. Data were collected from 136 patients with hypertension attending primary healthcare centers in Saudi Arabia using validated scales for dietary habits, physical activity, perceived stress, and self-confidence, alongside blood pressure measurements. Data were analyzed using Statistical Package for the Social Sciences version 26. Results: The study revealed that most participants reported reasonably healthy dietary practices, low physical activity, and moderate stress and self-confidence. Significant sex differences (p < 0.05) were observed, with men and women reporting higher physical activity and stress, respectively. Education and age influenced dietary habits and self-confidence. Regression analysis identified age, education, and urban residence as predictors (p < 0.05) of blood pressure status, while stress, diet, and physical activity affected self-confidence and perceived stress levels. Conclusions: Hypertension management is influenced by interconnected lifestyle and psychosocial factors, and improving dietary habits, physical activity, stress management, and self-confidence is essential. Tailored interventions addressing demographic differences can enhance self-care behaviors and facilitate better hypertension control among Saudi individuals. Full article

According to the Australasian Society for Developmental Paediatrics, experiential learning and outdoor play contain elements of risk, bravery, uncertainty, exploration, personal challenge, and adventure. These attributes are fundamental to a child’s growth, development, and wellbeing, and yet, in contemporary society, outdoor experiences have significantly declined. This scoping review explores the benefits and affordances of nature-based risky play and adventure education across early childhood and adolescence, asking what developmental opportunities emerge when children and adolescents engage in meaningful outdoor challenges. Adopting a benefit–risk approach where safety is “as safe as necessary” rather than “as safe as possible,” the review identifies common elements across developmental stages. A scoping review following PRISMA-ScR guidelines synthesised empirical studies (2015–2025). Our review included 40 empirical studies from a total of 5218 references, using diverse methodologies conducted predominantly in Western nations. All 40 studies reported positive associations across multiple developmental domains. Eight key themes developed: resilience and confidence, wellbeing, physical skills, autonomy and agency, nature connectedness, quality play provision, and educator influence. Authentic child agency and autonomy functioned as critical mechanisms through which benefits are realised across early childhood and school-aged populations. Key benefits included enhanced mental health, social competence, and anxiety prevention. Implementation barriers persist, including parental anxiety, institutional liability concerns, and cultural risk aversion. Evidence overwhelmingly supports nature-based risky play and outdoor adventure education as beneficial for child and adolescent development. Translation into practice remains limited by stakeholder attitudes and systemic barriers. Future research should prioritise longitudinal studies, cross-cultural investigation, and equity-focused approaches addressing disparities in access to positive risk-taking. Full article

The growing cultural diversity of higher education calls for systematic and curriculum-embedded approaches to the development of students’ intercultural competence. This article explores strategies for fostering intercultural sensitivity and effective cross-cultural communication, drawing on Bennett’s Developmental Model of Intercultural Sensitivity (DMIS) and Deardorff’s intercultural competence framework. The study situates these frameworks within an Internationalization at Home perspective, emphasizing the role of intentional pedagogy, assessment, and attention to the hidden curriculum in supporting intercultural learning. Adopting a design-based pedagogical research approach, the study examines how intercultural competence frameworks can be operationalized through developmentally sequenced classroom interventions in higher education. The pedagogical framework and activities, including cultural artifact presentations, critical incidents, simulations, role-plays, and structured reflective practices, were developed and implemented in culturally diverse bachelor’s and master’s level courses in Spanish higher education institutions within the Erasmus+ MULTICLASS project. Classroom-based evidence collected in Spanish higher education contexts, including reflective discussions, written reflections, and observed communicative behaviors, indicates that approximately 70% of students (n = 44; N = 63) demonstrated observable progression in intercultural sensitivity, most commonly from Minimization toward Acceptance. The contribution of this article lies in linking established intercultural competence models with practical guidance for curriculum design and pedagogical sequencing within Internationalization at Home contexts. Full article

Schools situated in indigenous territories have historically replicated Western Eurocentric spatial models, often excluding local cultural knowledge and practices. This exclusion has impacted students’ emotional well-being, learning quality, and the contextual relevance of pedagogical approaches. This study aims to explores the socio-ecological context of school spaces in Mapuche territories in La Araucanía, Chile, and examines how teachers perceive these spaces and their influence on emotional regulation and learning. Using a qualitative multi-case study design, data were collected from three schools in Cholchol, Nueva Imperial, and Toltén through land cover/use mapping within a 3 km radius and semi-structured interviews with 15 teachers. Analysis was conducted using constructivist grounded theory. The findings reveal that schools are embedded in landscapes comprising agricultural zones, water bodies, monoculture plantations, and nearby Mapuche communities. Teachers conceptualize school spaces beyond physical infrastructure, recognizing socio-ecological and cultural dimensions. However, school design remains predominantly Western and monocultural, with limited integration of Mapuche spiritual and territorial elements. The main contribution of this research is to provide empirical evidence that strengthening the connection between school spaces and their biocultural context can enhance students’ sense of belonging, emotional regulation, and learning. This study advances the topic by highlighting the critical role of teachers’ perceptions and the socio-ecological context in the design of intercultural and sustainable schools, offering a concrete framework for overcoming regulatory and architectural limitations that continue to impede the implementation of inclusive public policies in indigenous educational settings. Full article

Intangible cultural heritage (ICH) is deeply embedded in everyday social life, yet its officially recognized spatial distribution reflects both the independent influences of cultural traditions, development trajectories, and governance practices, and the complex interactions among them. Focusing on 494 national-level ICH items across ten categories in Jiangsu(J), Zhejiang(Z), and Shanghai(H), this study adopts a social-geographical perspective to examine both the spatio-temporal evolution and the driving mechanisms of ICH recognition in one of China’s most developed regions. After rigorous verification of point-based ICH locations, we combine kernel density estimation and the average nearest neighbor index to trace changes across five batches of national designation, and then employ the univariate and interaction detectors of the Geodetector model to assess the effects of 28 natural, socioeconomic, and cultural-institutional variables. The results show, first, that ICH exhibits significant clustering along river corridors and historical cultural belts, with a persistent high-density core in the Shanghai–southern Jiangsu–northern Zhejiang zone and a clear shift over time from highly concentrated to more dispersed and territorially balanced recognition. Second, human-environment factors—especially factors such as urban and rural income and consumption; residents’ education and cultural expenditures; and public education and cultural facilities—have far greater explanatory power than natural conditions, while different ICH categories embed distinctively in urban and rural socio-economic contexts. Third, bivariate interactions reveal that natural and macroeconomic “background” variables are strongly amplified when combined with demographic and cultural factors, whereas interactions among strong human variables show bivariate enhancement with diminishing marginal returns. In summary, these findings enrich international debates on the geography of ICH by clarifying how recognition processes align with regional development and social equity agendas, and they provide a quantitative basis for category-sensitive, place-based strategies that coordinate income policies, public cultural services, and the joint safeguarding of tangible and intangible heritage in both urban renewal and rural revitalization planning. Full article

The rapid rise of the pre-loved luxury fashion market in China reflects a unique shift in consumer behaviour, shaped by growing concerns for sustainability, affordability, and personal expression. While global scholarship on circular fashion has expanded, studies remain predominantly focused on Western consumers, leaving Chinese market dynamics underexplored. This study addresses this gap by examining the motivations and channel engagement of Chinese consumers purchasing pre-loved luxury fashion, including pre-owned, vintage, and collectors’ items. A sequential mixed-methods design was employed, integrating quantitative data from a survey of 438 Chinese consumers with qualitative insights from 21 semi-structured interviews. Structural equation modelling revealed that economic, individual, and social motivations significantly influenced perceived value, which in turn enhanced engagement with resale channels. Functional motivations, though present, played a less prominent role. Furthermore, engagement with online and offline channels, including social media platforms, livestream commerce, and luxury consignment boutiques, was found to mediate the relationship between perceived value and purchase intention. The study contributes to theory by adapting established luxury value frameworks to the pre-loved context and by introducing channel engagement as a mediating construct in the consumption of second-hand luxury fashion. The main theoretical frameworks that underpin the study, such as the Brand Luxury Index and the Four Value Dimensions, are used to provide a clearer understanding of its conceptual foundation. In particular, some key quantitative indicators, such as β-values or R², would make the summary more specific and informative. Practically, the findings provide actionable insights for platform operators and luxury brands seeking to build consumer trust and enhance experiential value in China’s rapidly evolving resale market. By situating the research within a culturally specific and digitally advanced retail environment, the study broadens understanding of circular luxury fashion consumption in non-Western contexts. Full article

Mongolian patterns represent an important component of Mongolian cultural heritage, characterized by their dual structure of geometric symmetry and dynamic ornamental motifs. However, existing artificial intelligence-based generative methods struggle to preserve both low-frequency structural regularity and high-frequency decorative detail under limited data conditions. This study proposes a parameter-efficient digitization framework based on latent diffusion models (LDMs) fine-tuned with low-rank adaptation (LoRA) to achieve high-fidelity reconstruction of classic Mongolian patterns. A curated few-shot dataset and a low-rank constraint enable effective learning from only eight representative samples, while a dual-prompt mechanism and MSE-driven optimization improve geometric stability and semantic consistency. Integrated within a transparent ComfyUI workflow, the method supports controllable generation and reproducible experimentation. Experimental evaluations demonstrate that the proposed LoRA-LDM model achieves superior structural accuracy, reduced visual distortion, and enhanced motif preservation compared with baseline models. The results confirm the method’s applicability for digital preservation, reconstruction, and derivative design of structured cultural heritage motifs. Full article