Search Results (8,074)

The construction industry is moving towards the era of industry 4.0; 5.0 with Building Information Modelling (BIM) as the tool gaining significant traction owing to its inherent advantages such as enhancing construction design, process and data management. However, the integration of BIM presents risks that are often overlooked in project implementation. This study aims to develop a novel amalgamated dimensional factor (Techno-organizational Aspect) that is set out to identify and align appropriate management strategies to these risks. Firstly, it encompasses an in-depth analysis of BIM and risk management, through an integrative review approach. The study utilizes an exploratory-based review centered around journal articles and conference papers sourced from Scopus and Google Scholar. Then processed using NVivo 12 Pro software to categorise risks through thematic analysis, resulting in a comprehensive Risk Breakdown Structure (RBS). Then qualitative content analysis was employed to identify and develop management strategies. Further data collection via online survey was crucial for closing the research gap identified. The analysis by mixed method research enabled to determine the risk severity via the quantitative approach using SPSS (version 29), while the qualitative approach linked management strategies to the risk factors. The findings accentuate the crucial linkages of key strategies such as version control system that controls BIM data repository transactions to mitigate challenges controlling transactions in multi-model collaborative environment. The study extends into underexplored amalgamated domains (techno-organisational spectrum). Therefore, a significant contribution to bridging the existing research gap in understanding the intricate relationship between BIM implementation risks and effective management strategies. Full article

Objectives: The aim of the study was to assess the utility of contrast-enhanced ultrasound (CEUS), using both qualitative and quantitative perfusion analysis, in differentiating subtypes of renal cell carcinoma (RCC). Methods: This prospective, single-center study includes 91 patients with histologically confirmed RCC. We performed a CEUS within one week prior to nephrectomy. Qualitative parameters (enhancement pattern, heterogeneity, pseudocapsule) and quantitative perfusion metrics were assessed. Logistic regression models were developed to evaluate the diagnostic performance of CEUS in differentiating high-grade (clear cell RCC) from low-grade RCC (papillary and chromophobe). Results: Qualitative CEUS findings showed that hyperenhancement and isoenhancement were significantly associated with high-grade RCC (OR = 38.3 and OR = 7.8, respectively; p < 0.001 and p = 0.014). Hypoenhancement was predominant in low-grade RCC (80.0%). Quantitative parameters, including peak enhancement and wash-in/wash-out area under the curve, significantly differed between tumor grades (p < 0.001). A model using qualitative parameters alone achieved an AUC of 0.847 and 81.9% accuracy. Adding quantitative metrics marginally improved performance (AUC 0.912, accuracy 86.2%), though not significantly. Conclusions: CEUS provides valuable diagnostic information in differentiating RCC subtypes, with qualitative parameters alone demonstrating strong predictive power. While quantitative analysis slightly enhances diagnostic accuracy, its added value may be limited by technical challenges. Full article

Using the s-d model and Green’s function theory, we investigated for the first time the electron and hole doping effects on the magnetic and optical properties of the double perovskites ${\mathrm{Ba}}_2{\mathrm{FeMoO}}_6$ (BFMO) and ${\mathrm{Sr}}_2{\mathrm{FeMoO}}_6$ (SFMO). Our aim was to find the doping ions that lead to an increase in Curie temperature $T_C$. On the basis of a competition mechanism between spin exchange and s-d interactions, we explain at a microscopic level the decrease in magnetization M and band gap energy $E_g$, as well as the increase in $T_C$ of BFMO and SFMO through substitution with rare earth ions at the Ba(Sr) sites. The influence of doping with K at the Ba(Sr) and Co at the Fe sites on the magnetic properties and the band gap is also discussed. A very good qualitative coincidence with the existing experimental data was observed. Moreover, we found that both M and $T_C$ decrease with decreasing the size of BFMO and SFMO nanoparticles. Full article

At present, the construction industry has not yet fully optimized the integration of the potential of big data. Past studies signaled the potential benefits of integrating building information management (BIM) and big data in the field of sustainable building management (SBM). However, these studies have a monotonous perspective in identifying the development of BIM and big data applications in SBM. Therefore, this paper aims to explore BIM and big data from various perspectives in the field of SBM to identify the aspects where additional efforts are required and provide insights into future directions, and it adopts a mixed method of quantitative and qualitative analysis, including bibliometric analysis and knowledge mapping, providing a macro-overview of the research status and development trends of BIM and big data integration for SBM from multiple bibliometric perspectives. The results indicate the following: (1) the current studies on BIM and big data integration (BBi)-aided SBM mainly focused on data integration and interoperability for collaboration, development of information technologies and emerging technologies, data analysis and presentation, and green building and sustainability assessment; (2) the longitudinal analysis of three time-slice phases (2010–2014, 2015–2018, and 2019–2024) over the past 15 years indicates that the studies on BBi-aided SBM have been expanded from the application of BIM in construction projects to the integration and interoperability of BIM with information technology, the integration of virtual models with physical buildings, and sustainable management throughout the building life cycle stages; and (3) key research gaps and emerging directions include data integration and model interoperability across the building life cycle, model transferability in the application of technology, and a comprehensive sustainability assessment framework based on the whole building life cycle stages. Full article

This qualitative case study explores Missouri-based consumers’ ethical beliefs regarding restaurant sourcing from minority farmers. Guided by the Hunt–Vitell theory of ethics (H-V model), it applies the model in a new context: culturally inclusive restaurant sourcing. Based on 15 semi-structured interviews conducted between September 2024 and October 2024, the study explores how ethical beliefs shape dining intentions. Participants generally viewed support for minority farmers as ethically appropriate. Thematic analysis revealed six key themes: (1) community-oriented social values (e.g., social responsibility toward local businesses); (2) cultural identity (e.g., traditional farming methods); (3) consumer values—food-oriented (e.g., quality); (4) consumer values—people-oriented (e.g., financial support for ethical sourcing); (5) trust-building mechanisms (e.g., sourcing transparency); and (6) barriers (e.g., lack of awareness). These findings highlight limited consumer awareness of minority farmers and the need for transparent communication and cultural education. The study contributes theoretically by extending the H-V model to the intersection of ethics, culture, and restaurant sourcing. Practically, it offers guidance for restaurant managers, marketers, and policymakers to support minority farmers, build trust, and promote inclusive and socially responsible dining. One key limitation of this study is its reliance on a small, Missouri-based consumer sample, which limits generalizability and excludes perspectives from other stakeholders. However, as a regional case study, it provides important depth and contextual insight into an underexplored aspect of sustainable sourcing. This study also highlights the need for multi-stakeholder engagement to advance equity in the food system. Full article

Background: Childhood hearing loss is a public health problem of critical importance associated with speech development, academic achievement, and quality of life. Parents’ awareness and knowledge about risk factors contribute to early detection and timely intervention.  Objective: This study aims to examine Jordanian mothers’ knowledge of childhood hearing loss risk factors and investigate the impact of education level and socioeconomic status (SES) on the accuracy and comprehensiveness of this knowledge with the moderating effect of health literacy. Material and Methods: The approach employed an embedded mixed-methods design with a dominant quantitative strand supported by qualitative data, utilizing quantitative surveys (n = 250), analyzed using structural equation modeling (SEM) in SmartPLS, and qualitative interviews (n = 10), analyzed thematically to expand upon the quantitative findings by exploring barriers to awareness and healthcare-seeking behaviors. Results: The accuracy and comprehensiveness of knowledge of hearing loss risk factors were also positively influenced by maternal knowledge of hearing loss risk factors. Maternal knowledge was significantly associated with both education level and socioeconomic status (SES). Furthermore, maternal knowledge and accuracy were significantly moderated by health literacy, such that mothers with higher health literacy exhibited a stronger relationship between knowledge and accuracy. Qualitative findings revealed that individuals encountered barriers to accessing reliable information and comprehending medical advice and faced financial difficulties due to limited options for healthcare services. Conclusions: These results underscore the need for maternal education programs that address specific issues, provide simplified healthcare communication, and enhance access to pediatric audiology services. Future research should explore longitudinal assessments and intervention-based strategies to enhance mothers’ awareness and detect early childhood hearing loss. Full article

Background/Objectives: Family self-care (FSC) is increasingly recognized as a vital aspect of caregiving in pediatric chronic conditions. However, its development in families of children with intellectual disabilities (IDs) remains underexplored. This study aimed to examine how families construct and sustain FSC, and to identify factors that shape its development across four domains: physical, cognitive, psychosocial, and behavioral. Methods: A qualitative study was conducted using an abductive approach, combining inductive thematic analysis with a deductively applied theoretical framework. Semi-structured interviews were carried out with nine families of children with ID in southern Portugal. The children ranged in age from 4 to 15 years, and the parents were aged between 29 and 53 years. The data was analyzed using Bardin’s content analysis, supported by NVivo software, and organized according to the FSC framework. This study followed COREQ guidelines. Results: The families described a range of self-care strategies, including environmental adaptations, experiential learning, emotional regulation, and long-term planning. These practices were shaped by contextual factors such as access to healthcare, relationships with professionals, emotional support networks, and socioeconomic conditions. Four emergent conclusions illustrate how structural and relational dynamics influence FSC in daily caregiving. Conclusions: FSC is a dynamic, multidimensional process shaped by lived experience, family interactions, and systemic support. The findings support inclusive, family-centered care models and inform clinical practice, training, and policy in pediatric IDs. Full article

Background/Objectives: The scientific literature shows that new scientific and social priorities regarding social impacts and co-creation are leading to profound transformations in all scientific and social contexts. In the field of mental health, one dimension of this transformation is the increasing visibility of dialogic models that support the improvement of mental health. While this is very positive, it carries a risk of deformations that can lead to negative outcomes for both society and science. There is a lack of scientific research about the errors related to the new visibility of the Successful Dialogues in Mental Health (SDMH) model. The objective of this research is to clarify a certain type of error, namely when the excellent results obtained through the use of this model in particular contexts are attributed to a supposed dialogic approach of psychiatric rehabilitation, made by researchers without a degree in medicine. Methods: In order to clarify this error, we use a communicative methodology through a qualitative research design, oriented to unveil the main steps in the original development of the model. Results: The results show that the SDMH model has never presented itself as psychiatric, but instead as a social–dialogic collaboration with psychiatrists with the aim of helping individuals to overcome mental health problems. Conclusions: This study clarifies the purpose of the SDMH model which contributes to benefiting citizens, particularly those with mental health conditions. Full article

Adaptive reuse of Mediterranean earthen houses offers a unique opportunity to fuse heritage preservation with sustainable development. This study introduces a comprehensive, sustainability-driven framework that reimagines these vernacular structures as culturally rooted and socially inclusive assets for contemporary living. Moving beyond conventional restoration, the proposed framework integrates environmental, socio-cultural, and economic sustainability across six core dimensions: ecological performance and material conservation, respectful functional transformation, structural resilience, cultural continuity and community engagement, adaptive flexibility, and long-term economic viability. Four geographically and culturally diverse case studies—Alhambra in Spain, Ghadames in Libya, the UCCTEA Chamber of Architects Main Building in North Cyprus, and Sheikh Hilal Beehive Houses in Syria—serve as testbeds to examine how earthen heritage can be reactivated in sustainable and context-sensitive ways. Through qualitative analysis, including architectural surveys, visual documentation, and secondary data, the study identifies both embedded sustainable qualities and persistent barriers, such as structural fragility, regulatory constraints, and socio-economic disconnects. By synthesizing theoretical knowledge with real-world applications, the proposed framework offers a replicable model for policymakers, architects, and conservationists aiming to bridge tradition and innovation. This research highlights adaptive reuse as a practical and impactful strategy for extending the life of heritage buildings, enhancing environmental performance, and supporting community-centered cultural regeneration across the Mediterranean region. Full article

Background/Objectives: This exploratory study examined the potential effectiveness of cognitive enhancement interventions targeting basic cognitive prerequisites and communicative abilities in girls with Rett syndrome. Special attention was given to evaluating telerehabilitation as a feasible alternative to traditional in-person therapy, particularly for individuals with severe impairments and limited access to care. Methods: Twenty-four girls diagnosed with Rett syndrome (mean age = 13.7 years, SD = 7.1), all meeting the basic cognitive prerequisites defined by the GAIRS scale, were randomly assigned to two groups: a telerehabilitation group (n = 12) and an in-person rehabilitation group (n = 12). Interventions were delivered in school settings and focused on two core areas: basic cognitive skills (e.g., object recognition, spatial and temporal concepts, form and color discrimination, and cause–effect reasoning) and communication skills (e.g., comprehension and expression through gestures, images, or verbal output). Results: Both groups showed significant improvements in the cognitive and communicative domains, with generally comparable outcomes. Notably, the telerehabilitation group demonstrated relatively greater gains in verbal expression and cause–effect understanding. Correlational analyses indicated positive associations between the cognitive and communicative improvements, particularly between spatial understanding and expressive abilities. However, these findings should be interpreted with caution due to the sample size and study design limitations. Conclusions: These preliminary findings suggest that cognitive enhancement programs may support developmental gains in girls with Rett syndrome and that telerehabilitation could represent a viable alternative for those unable to access in-person care. Given the limited sample size and absence of qualitative measures, further research is necessary to validate its effectiveness and understand its role within comprehensive care models. Full article

The integration of shared autonomous vehicles into historic urban areas presents both opportunities and challenges. In heritage-rich environments like very old Asian (such as Suzhou old town, which serves as a use case example) or European (especially Mediterranean coastal cities) areas—characterized by narrow alleys, dense development, and sensitive cultural landscapes—shared autonomous vehicle adoption raises critical spatial and social questions. This study employs a qualitative, user-centered approach based on the ripple model to examine residents’ perceptions across four dimensions: residential patterns, parking land use, regional accessibility, and street-level infrastructure. Semi-structured interviews with 27 participants reveal five key findings: (1) public trust depends on transparent decision-making and safety guarantees; (2) shared autonomous vehicles may reshape generational residential clustering; (3) the short-term parking demand remains stable, but the long-term reuse of space is feasible; (4) shared autonomous vehicles could enhance accessibility in historic cores; (5) transport systems may evolve toward intelligent, human-centered designs. Based on these insights, the study proposes three strategies: (1) transparent risk assessment using explainable artificial intelligence and digital twins; (2) polycentric development to diversify land use; (3) hierarchical street retrofitting to balance mobility and preservation. While this study is limited by its qualitative scope and absence of simulation, it offers a framework for culturally sensitive, small-scale interventions supporting sustainable mobility transitions in historic urban contexts. Full article

The integration of artificial intelligence (AI) within the decision-making processes of small- and medium-sized enterprises (SMEs) presents both significant opportunities and substantial ethical challenges. The aim of this paper is to provide a theoretical model depicting the interdependence of organisational decision-making levels and decision-making styles, with an emphasis on exploring the role of AI in organisations’ decision making, based on selected process dimension of the MER model of integral governance and management, particularly in relation to routine, analytical, and intuitive decision-making capabilities. The research methodology employs a comprehensive qualitative analysis of the scientific literature published between 2010 and 2024, focusing on AI implementation in SMEs, ethical decision making in integral management, and regulatory frameworks governing AI use in business contexts. The findings reveal that AI technologies influence decision making across business policy, strategic, tactical, and operative management levels, with distinct implications for intuitive, analytical, and routine decision-making approaches. The analysis demonstrates that while AI can enhance data processing capabilities and reduce human biases, it presents significant challenges for normative–ethical decision making, requiring human judgment and stakeholder consideration. We conclude that effective AI integration in SMEs requires a balanced approach where AI primarily serves as a tool for data collection and analysis rather than as an autonomous decision maker. These insights contribute to the discourse on responsible AI implementation in SMEs and provide practical guidance for leaders navigating the complex interplay between (non)technological capabilities, ethical considerations, and regulatory requirements in the evolving business landscape. Full article

Metacognition and self-regulated learning are widely understood to offer significant benefits for pupils’ mathematical problem solving; however, the existing literature highlights that the under-representation of these concepts in curriculum, policy, and teacher professional development means that their potential for impact remains unfulfilled. This article, therefore, examines the potential value of an innovative fading professional development programme—“Stepping Stones”—in enhancing teachers’ understanding and use of metacognitive strategies for mathematical problem solving. Adopting a convergent mixed methods design, this pilot evaluation involved Year 2 teachers across five primary schools. The results from both qualitative and quantitative data demonstrate that, as the scaffolding provided by programme materials faded and teachers assumed greater responsibility for session planning, they incorporated metacognitive strategies into their planning and delivery with increased independence. The results also indicate the acceptability of this professional development model, suggesting that, when combined with peer collaboration, the fading design was associated with improvements in knowledge and confidence regarding both metacognition and mathematical problem solving, alongside increased ownership and buy in. The conclusions advocate further examination and implementation of fading models of professional development to promote the understanding and use of metacognition for mathematical problem solving and recommend exploration into different professional development contexts. Full article

To address the issues of modeling the relationships between multiple local region objects in images and enhancing local region features, as well as mapping global image semantics to global text semantics and local region image semantics to local text semantics, a novel image captioning method based on CLIP and integrating local feature enhancement and multi-scale semantic guidance is proposed. The model employs ViT as the global visual encoder, Faster R-CNN as the local region visual encoder, BERT as the text encoder, and GPT-2 as the text decoder. By constructing a KNN graph of local image features, the model models the relationships between local region objects and then enhances the local region features using a graph attention network. Additionally, a multi-scale semantic guidance method is utilized to calculate the global and local semantic weights, thereby improving the accuracy of scene description and attribute detail description generated by the GPT-2 decoder. Evaluated on MSCOCO and Flickr30k datasets, the model achieves a significant improvement in the core metric CIDEr over established strong baselines, with 4.7% higher CIDEr than OFA on MSCOCO, and 16.6% higher CIDEr than Unified VLP on Flickr30k. Ablation studies and qualitative analysis validate the effectiveness of each proposed module. Full article

This study proposes an interdisciplinary instructional model tailored for Functional Ecological Carbon (FEC) education, combining Electronic, Mobilize, and Ubiquitous (E/M/U) learning principles with the Practical Transformational Teaching Method (PTtM). The research adopts a mixed-methods framework, utilizing the Analytic Hierarchy Process (AHP) to prioritize teaching objectives and interpret student evaluations, alongside qualitative insights from reflective journals, open-ended surveys, and focus group discussions. The results indicate that hands-on experience, interdisciplinary collaboration, and context-aware applications play a critical role in fostering ecological awareness and responsibility among students. Notably, modules such as biosafety testing and water purification prompted transformative engagement with sustainability issues. The study contributes to sustainability education by integrating a decision-analytic structure with reflective learning and intelligent instructional strategies. The proposed model provides valuable implications for educators and policymakers designing interdisciplinary sustainability curricula in smart learning environments. Full article