Search Results (8,549)

This study examines the digital maturity of small- and medium-sized enterprises (SMEs) in the context of Industry 4.0. Despite growing awareness of the importance of digital transformation, many SMEs encounter structural and strategic challenges that impede their progress. Among their obstacles is the inadequacy of digital maturity models used to diagnose digital maturity levels in SMEs due to their typological, sectoral, geographical, and other specific characteristics. Using a constructivist and qualitative approach, we have developed a simplified, inclusive, and holistic assessment framework comprising six key dimensions (technology, culture, organization, people and human resources, strategic planning), associated with six progressive maturity levels. Our findings reveal that most SMEs studied in 2023 exhibit a beginner level of digital maturity. These enterprises are characterized by small-scale digital initiatives, often lacking a clear strategy, with limited or partial digitization of processes and heterogeneous technology adoption. The resulting self-assessment tool provides SMEs with practical guidance to launch, evaluate, and accelerate their digital transformation. This study contributes theoretically by proposing a practical digital maturity model and offering a tool to support SMEs and public policy. It highlights the need for tailored support, strategic alignment, and continuous training to unlock the full potential of Industry 4.0 in less urbanized and resource-constrained areas. Full article

Building fires are considered major disasters because of their significant effects on people, property, and the environment. This understanding has led to increased attention on developing preventive measures, particularly through the creation of effective methods for assessing fire risk. However, the effectiveness of these methods relies heavily on detailed physical and functional information of the building and data-driven decision-making. Building Information Modeling (BIM) has proven effective in representing structures, even in three dimensions. When integrated with Geographic Information Systems (GIS), it enhances spatial intelligence, leading to improved decision-making through robust multi-criteria approaches. Hence, this study develops a framework to assess fire risk in an indoor environment that deploys a BIM-based GIS and Multi-Criteria Decision-Making; this is specifically known as Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The developed framework consists of four steps: identifying fire risk parameters, calculating weights, conducting spatial fire risk assessments, and visualizing the results, where the developed concepts are tested and validated. According to the significant findings, the developed framework estimates that 18% of building rooms are at moderate risk, while the compared model identifies only 1%. This considerable difference could potentially arise from the detailed data structure of BIM and the spatial insights gained from GIS. By implementing the designed framework, key fire risk factors can be identified in three dimensions, accompanied by a comprehensive quantitative evaluation platform for fire risks within indoor environments. Full article

This study presents a quantitative methodological approach for evaluating universal accessibility in cultural heritage sites, grounded in the DALCO criteria—Deambulation/Mobility, Apprehension, Location, and Communication. The methodology is designed to be broadly applicable across diverse geographic and cultural contexts, thus offering a generalizable framework for assessing accessibility. At the same time, the study applies this approach to the specific case of the Ávila region (Spain), a territory with a high concentration of Assets of Cultural Interest (ACIs), including sites recognized as UNESCO World Heritage. In this way, the research simultaneously pursues a methodological aim, by testing and refining the DALCO-based framework, and a diagnostic aim, by providing a comprehensive evaluation of accessibility conditions in Ávila. Using a structured questionnaire, each ACI was assessed to determine its accessibility level across four key dimensions. The results reveal significant physical, communicative, and cognitive barriers across the region, with notable disparities among territorial zones. The proposed methodology offers a replicable and scalable tool for researchers, cultural institutions, and public authorities committed to fostering inclusive heritage environments, and provides a technical foundation for implementing universal design principles aligned with the SDG 11. Full article

In dynamic and open cloud service processes, particularly in distributed networked manufacturing environments, the complex and volatile manufacturing landscape introduces numerous uncertainties and disturbances. This paper addresses the common issue of cloud resource connection interruptions by proposing a path substitution strategy based on alternative service routes. By integrating agent-based simulation and complex network methodologies, a simulation model for evaluating the robustness of cloud manufacturing service systems is developed, enabling dynamic simulation and quantitative decision-making for the proposed robustness enhancement strategies. First, a hybrid modeling approach for cloud manufacturing service systems is proposed to meet the needs of robustness analysis. The specific construction of the hybrid simulation model is achieved using the AnyLogic 8.7.4 simulation software and Java-based secondary development techniques. Second, a complex network model focusing on cloud manufacturing resource entities is further constructed based on the simulation model. By combining the two models, two-dimensional robustness evaluation indicators—comprising performance robustness and structural robustness—are established. Then, four types of edge attack strategies are designed based on the initial topology and recomputed topology. To ensure system operability after edge failures, a path substitution strategy is proposed by introducing redundant routes. Finally, a case study of a cloud manufacturing project is conducted. The results show the following: (1) The proposed robustness evaluation model fully captures complex disturbance scenarios in cloud manufacturing, and the designed simulation experiments support the evaluation and comparative analysis of robustness improvement strategies from both performance and structural robustness dimensions. (2) The path substitution strategy significantly enhances the robustness of cloud manufacturing services, though its effects on performance and structural robustness vary across different disturbance scenarios. Full article

Natural playgrounds have garnered growing attention as supportive environments for children’s mental health. This study develops an analytical framework grounded in affordance theory and incorporates the Pleasure–Arousal–Dominance (PAD) model to examine the relationships between physical environmental features—and their combinations—in natural playgrounds and children’s emotional perceptions. Using the Yunhu Natural Playground in Fuzhou, China, as a case study, we selected seven typical behavior setting units. Environmental features were assessed through UAV imagery and on-site observations, while PAD-based visual questionnaires were employed to collect emotional responses from 159 children. By applying correlation analysis, random forest, and regression tree models, this study identified key environmental predictors of children’s emotional responses and revealed heterogeneous mechanisms across the three emotional dimensions. The results indicated that seasonal flowering/fruiting plants, accessible lawns, and structured play facilities were critical in supporting children’s pleasure, arousal, and dominance. Specifically, pleasure was primarily associated with sensory enjoyment and contextual aesthetics, arousal favored open grassy areas, and dominance was linked to environments with clear structure and manipulability. Based on these findings, this study proposes a spatial configuration strategy characterized by “nature as foundation, play encouraged, and structure clarified” to promote the positive development of children’s multidimensional emotional experiences. This research contributes empirical evidence on the role of physical environmental features in supporting children’s play behaviors and expands the theoretical understanding of the “emotional effects” of green spaces. While the findings are exploratory and context-specific, they emphasize the critical role of the sensory–behavioral–emotional chain in shaping children’s well-being and provide theoretical and practical guidance for the design of emotionally supportive, child-friendly, natural play environments in schools, parks, and residential areas. Full article

This paper introduces the Construction 4.0 Value Proposition Score (CVPS4.0)—a structured framework that enables Architecture, Engineering, and Construction (AEC) organizations to evaluate and communicate the value proposition of Construction 4.0 decisions. Grounded in the “Futures Triangle” theory, the study draws on existing research to identify three key dimensions: past barriers constraining AEC organizations, current trends driving industry change, and future transformations toward which the sector is evolving. In total, 45 barriers, 13 trends, and four transformations were identified as the foundation of the scoring framework. The model assesses how a decision influences each dimension, producing a composite score that reflects its overall value proposition. This score incorporates three considerations: the applicability of each factor to the organization, the degree of impact the decision has on it, and the relevance of the factor to the decision. The framework was validated through proof-of-concept with a subject-matter expert, who confirmed its value in supporting strategic, data-informed decision-making. As one of the first studies to evaluate the value proposition of Construction 4.0, this research offers both a practical decision-support tool and a consolidated reference on the forces shaping organizational change. CVPS4.0 provides AEC organizations with a proactive means to guide decisions, mitigate risks, and enhance long-term value creation. Full article

Background/Objectives: Social sciences have described the 21st century as the ‘era of loneliness’, a time marked by the subjective and often distressing experience of lacking meaningful social connections. While loneliness has been linked to poorer health outcomes, its relationship with dietary practices remains underexplored. Methods: This ethnographic study examines the impact of loneliness on the eating habits of older adults, based on fieldwork conducted in Galicia and Extremadura (Spain) between November 2024 and April 2025. Using semi-structured interviews (n = 25) and participant observation in domestic settings, we examined everyday food practices. Data were examined using thematic analysis. Results: Participants acknowledged the connection between diet and health, although their dietary practices often failed to meet nutritional recommendations. Loneliness and social isolation influenced food choices and cooking routines, often leading to less nutritious diets. These effects were shaped by gender and social class. Many participants associated the decline of shared meals and food-related sociability with a diminished quality of life. The absence of a meaningful companion was experienced as a profound loss, prompting various coping strategies. Conclusions: The findings highlight that food holds both nutritional and symbolic value. Health promotion strategies should address the social and emotional dimensions of eating. Loneliness disrupts food practices at multiple levels, calling for public health responses that integrate biological, cultural, and care perspectives. Full article

Reservoirs and caprocks overlap with each other in heterogeneous carbonate rocks. The sealing capacity of caprocks and their controlling factors are not clear, which restricts the prediction, exploration, and development of carbonate hydrocarbon reservoirs. We selected core samples from the Ordovician reservoirs and caprocks in the Tarim Basin, China, for scanning electron microscopy, thin section, breakthrough pressure (BP), high-pressure mercury intrusion porosimetry (HMIP), and nitrogen adsorption method (N₂GA). The experimental results show that the reservoir and caprock can be distinguished by BP. The BP of the reservoir is less than 3.0 MPa, and the BP of the caprock is less than 3.0 Mpa. We analyzed the heterogeneity characteristics and differences in reservoirs and caprocks with different lithologies from the perspectives of monofractal and multifractal. The results indicate that the differences in pore structure of grainstone, dolomite, and micrite/argillaceous limestone result in significant heterogeneity differences between samples. The correlation analysis between the fractal parameters and BP indicates that the characteristics of reservoir microporous structures have a decisive impact on BP (correlation coefficient > 0.7). The pore structure of the carbonate reservoir–caprock system exhibits self-similarity. The heterogeneity of the caprock has no significant control effect on BP (correlation coefficient < 0.3), while the higher the heterogeneity of the reservoir, the greater the BP. The sealing capacity of the caprock depends on the heterogeneity differences in pore types and pore structures between the reservoirs and caprocks. When both the reservoir and the caprock are grainstone, the micropores in the reservoirs and caprocks are dispersed but evenly distributed, and little heterogeneous differences can achieve sealing. When the lithology of reservoirs and caprocks is different, the enhancement of heterogeneity differences in micropores will improve the sealing capacity of the caprock. In summary, fractal dimension is an effective method for studying the heterogeneous structure and sealing capacity of pore–throat in carbonate caprocks. This study proposes a new perspective that the difference between the heterogeneity of micropore structures of reservoirs and caprocks affects the sealing capacity of carbonate rocks, and provides a new explanation and model for the sealing mode of carbonate rock caprocks. Full article

Personalized learning environments increasingly rely on learner modeling techniques that integrate both explicit and implicit data sources. This study introduces a hybrid profiling methodology that combines psychometric data from an extended Felder–Silverman Learning Style Model (FSLSM) questionnaire with behavioral analytics derived from Moodle Learning Management System interaction logs. A structured mapping process was employed to associate over 200 unique log event types with FSLSM cognitive dimensions, enabling dynamic, behavior-driven learner profiles. Experiments were conducted across three datasets: a university dataset from the International Hellenic University, a public dataset from Kaggle, and a combined dataset totaling over 7 million log entries. Deep learning models including a Sequential Neural Network, BiLSTM, and a pretrained MLSTM-FCN were trained to predict student performance across regression and classification tasks. Results indicate moderate predictive validity: binary classification achieved practical, albeit imperfect accuracy, while three-class and regression tasks performed close to baseline levels. These findings highlight both the potential and the current constraints of log-based learner modeling. The contribution of this work lies in providing a reproducible integration framework and pipeline that can be applied across datasets, offering a realistic foundation for further exploration of scalable, data-driven personalization. Full article

Improving the innovation performance of mega projects has become a central concern in both engineering project management theory and practice. Organizational structure and culture are key contextual factors that can facilitate tacit knowledge sharing across organizations, thereby enhancing innovation outcomes. Based on the data of 243 questionnaires, this paper systematically analyzes the influence mechanism of organizational context factors on innovation performance by using the structural equation model (SEM). The results show that organizational structure exerts a significant negative effect on both tacit knowledge sharing and innovation performance. Among the dimensions of organizational culture, trust climate and organizational support have significant positive effects on both tacit knowledge sharing and innovation performance. While the level of cooperation enhances tacit knowledge sharing, its direct impact on innovation performance is not statistically significant. Furthermore, in the organizational context and innovation performance, tacit knowledge sharing also plays different mediating roles. The results can provide theoretical guidance for mega projects to break through the obstacle of technological transformation and enhance innovation efficiency. Full article

Aiming at the core problem of high false and missed alarm rate and insufficient interference resistance of existing smoke and fire detection algorithms in complex scenes, this paper proposes a target detection network based on improved feature pyramid structure. By constructing a Context Guided Convolutional Block instead of the traditional convolutional operation, the detected target and the surrounding environment information are fused with secondary features while reconfiguring the feature dimensions, which effectively solves the problem of edge feature loss in the down-sampling process. The Poly Kernel Inception Block is designed, and a multi-branch parallel network structure is adopted to realize multi-scale feature extraction of the detected target, and the collaborative characterization of the flame profile and smoke diffusion pattern is realized. In order to further enhance the logical location sensing ability of the target, a Manhattan Attention Mechanism Unit is introduced to accurately capture the spatial and temporal correlation characteristics of the flame and smoke by establishing a pixel-level long-range dependency model. Experimental tests are conducted using a self-constructed high-quality smoke and fire image dataset, and the results show that, compared with the existing typical lightweight smoke and fire detection models, the present algorithm has a significant advantage in detection accuracy, and it can satisfy the demand for real-time detection. Full article

Societal challenges are inherently complex and multi-tiered, arising from the interplay of diverse stakeholders with a spectrum of purposes and different perceptions and expectations, interdependent systems, and dynamic contextual factors that transcend single domains or disciplines. This paper presents a novel approach to developing a Reference Model of Governance tailored to a specific complex, multi-organisational enterprise facing socially complex challenges. Drawing on Angyal’s systems framework, the model introduces a three-dimensional structure with vertical, progression, and transverse dimensions, integrated within a holistic contextual whole. By mapping selected systems methodologies, including Soft Systems Methodology (SSM), Viable System Model (VSM), System Dynamics (SD), and dependency modelling, to these dimensions, the model offers a pragmatic, structured way to explore and regulate complex organisational behaviour. It enables collaborative inquiry, supports adaptive governance, and enhances the enterprise’s ability to address dynamic societal problems such as health, education, and public service delivery. The result is a governance reference model that captures both the operational and contextual realities of the enterprise, providing actionable insight for strategic design or diagnostic intervention. The novel approach is grounded in systemic and critical systems thinking and emphasises the use of methods for understanding to develop a common and shared understanding of the enterprise context and to surface multiple stakeholder perspectives. Full article

Short-term dynamics in auction-based Day-Ahead electricity markets remain insufficiently studied. This paper investigates two such aspects in the Irish Day-Ahead market. First, we address an empirical gap by examining the extent of speculator (financial trader) participation and its evolution over time in a European Day-Ahead setting. Using granular participant-level order and trade data, we quantify speculators’ share of overall market activity and assess how often they are marginal in the auction. Although their share of orders and trades is relatively small, speculators are marginal in a substantial proportion of trading periods and their behaviour changes significantly following a Brexit-related structural shift in market coupling. Second, we introduce a sensitivity-based measure of price inertia defined as the resistance of prices to small changes in demand or supply, adapted to the Day-Ahead auction context, a dimension of market behaviour that has received little prior attention. We find that inertia levels vary considerably and also shift following the structural change. Taken together, these analyses provide empirical evidence that speculators play a non-negligible role in a European auction-based Day-Ahead market, while price inertia offers an additional lens through which to examine short-term market dynamics and their evolution under different market conditions. Full article

Despite a robust body of evidence supporting both the need for and the effectiveness of physical fitness interventions in children aged 5–11, global fitness levels in this age group continue to decline. This systematic scoping review interrogates a critical, often overlooked dimension of this paradox: the pedagogy of fitness-intervention design and delivery. By analysing 106 primary research studies, the review exposes a consistent pattern. Interventions are predominantly highly structured (89%), rarely foster a mastery-oriented motivational climate (only 11%), and fail to report practitioner behaviours (65%). While most interventions yielded positive fitness outcomes, these gains were achieved without the use of pedagogical strategies known to support engagement, autonomy, and long-term adherence in children. This suggests that current approaches may achieve short-term physiological improvements but are limited in cultivating the motivational and developmental conditions necessary for sustained impact. The findings underscore a pressing need for future research to move beyond the “what” of fitness programming and rigorously address the “how.” Embedding and explicitly reporting pedagogical elements—such as supportive practitioner behaviours, autonomy-supportive structures, and mastery climates—could transform fitness interventions into developmentally appropriate, engaging, and sustainable experiences for children. Without this shift, we risk perpetuating interventions that are effective in the lab but ineffective in life. Full article

Technological advancements are a key engine for improving productivity and are fundamental to enhancing the resilience of the agricultural economy by influencing production methods and driving structural transformation. The objective of this study is to analyze the impact of technological progress on agricultural economic resilience in China, with particular attention to (i) its direct effects on resistance, recovery, and reconstruction; (ii) its indirect effects through the upgrading of the agricultural industrial structure; and (iii) its potential nonlinear effects under different structural thresholds. To achieve this, a multidimensional evaluation framework has been developed to assess agricultural economic resilience through three distinct dimensions: resistance, recovery, and reconstruction. Using fixed effects, mediation, threshold and spatial Durbin models, we empirically analyze the impact pathways. The results suggest that technological progress significantly increases agricultural resilience, with robustness confirmed by various tests including model substitution and variable replacement. Furthermore, regional heterogeneity is evident, with the central region showing the strongest positive effect. The mediation analysis shows that modernization of industrial structure serves as an important transmission channel, while the threshold regression identifies nonlinear effects, with significant improvements occurring beyond certain structural thresholds. The results underline the importance of promoting technological innovation in agriculture, developing region-specific support measures and accelerating structural optimization to strengthen the resilience of agriculture. Full article