Search Results (21,863)

This study introduces a modified computational scheme for handling linear and nonlinear fractal time-dependent partial differential equations. The method is constructed using three different stages that provide third-order accuracy in the fractal time variable. The stability of the approach is examined using scalar fractal models and Fourier analysis, while convergence is established for coupled convection–diffusion systems. The numerical algorithm is applied to analyze the mixed convective flow of a Carreau–Yasuda non-Newtonian fluid over stationary and oscillating plates under the influence of viscous dissipation and magnetic field effects. For spatial discretization, the incompressible continuity equation is handled by a first-order difference scheme, whereas higher-order compact schemes are implemented for the momentum, thermal, and concentration equations. The numerical findings show that increasing the Weissenberg number and magnetic field inclination reduces the velocity distribution. An accuracy assessment against existing numerical techniques demonstrates that the present method yields smaller computational errors, particularly when central difference schemes are used in space. In addition, a surrogate machine learning model is developed to predict the skin friction coefficient and local Nusselt number using Reynolds, Weissenberg, Prandtl, and Eckert numbers as input features. The predictive capability of the model is validated through Parity plots, bar charts for sensitivity analysis, scatter visualization, and Taylor Diagrams, confirming strong agreement with the numerical results. Full article

Background/Objectives: Medial meniscus extrusion (MME) is a quantitative marker of altered meniscal containment and load sharing. Although ultrasonography enables dynamic assessment under functional loading, it remains unclear whether generalized ligamentous hypermobility influences physiologic extrusion behavior in healthy knees. The aim of this study was to quantify load-dependent MME in healthy adults and to determine whether generalized hypermobility is associated with greater physiologic extrusion under progressive loading conditions. Methods: In this prospective observational study, 106 healthy adults aged 18–40 years were evaluated between October and December 2025. Generalized joint hypermobility was defined as a Beighton score ≥ 5. MME was measured by standardized ultrasonography on the dominant limb in three conditions: sitting (unloaded), bipedal stance, and unipedal stance. Patellar tendon shear-wave elastography (SWE) was recorded in kilopascals (kPa). Interobserver reliability was assessed in the first 25 participants using ICC (2,1). Group comparisons, multivariable linear regression for loading-related Δ-extrusion (Unipedal−Sitting and Bipedal−Sitting), and a linear mixed-effects model for repeated MME measures, including a Position × Hypermobility interaction, were performed. Results: Twenty-eight participants (26.4%) were classified as hypermobile. The hypermobile group showed significantly lower patellar tendon SWE than controls (23.8 ± 7.0 vs. 37.6 ± 9.7 kPa, p < 0.001). MME increased stepwise with loading in both groups and remained consistently higher in hypermobile participants across sitting, bipedal, and unipedal conditions (all p < 0.001). Loading-related extrusion was also greater in the hypermobile group for both Bipedal−Sitting (p = 0.037) and Unipedal−Sitting (p = 0.002). In multivariable regression, lower patellar tendon SWE independently predicted greater loading-related extrusion, whereas hypermobility status did not remain an independent predictor. In the mixed model, the Position × Hypermobility interaction was significant and was most pronounced during the unipedal stance. Conclusions: In healthy adults, medial meniscus extrusion increases stepwise from unloaded sitting to bipedal and unipedal weight bearing. Participants with generalized hypermobility demonstrated higher physiologic MME values and a more pronounced load-dependent pattern, particularly during unipedal stance. However, in adjusted analyses, lower patellar tendon stiffness on SWE, rather than hypermobility status itself, independently predicted greater loading-related extrusion. These findings support a contextual interpretation of ultrasound-based MME measurements in relation to loading condition and hypermobility phenotype. Full article

In this work, the volumetric properties of nine binary systems composed of ethyl propanoate and n-alkylcyclohexanes (from cyclohexane to decylcyclohexane) were investigated. Densities were measured at atmospheric pressure (101 kPa) over the entire composition range and at temperatures from 288.15 K to 328.15 K. A total of 525 density data points were obtained. Excess molar volumes were derived from the experimental densities and correlated using a Redlich–Kister equation, while mixture densities were modeled with the Jouyban–Acree model. All systems exhibit positive excess molar volumes over the studied temperature and composition ranges, indicating volume expansion upon mixing due to dominant repulsive interactions. The magnitude of the excess molar volume increases with increasing alkyl chain length of the branched naphthenic compound: for an equimolar mixture, V^E is about 0.65 cm³·mol⁻¹ for the methylcylohexane + ethyl propanoate mixture and reaches 0.83 cm³·mol⁻¹ for the heptylcylohexane + ethyl propanoate binary system, although a plateau tendency is observed for longer alkyl chains. Excess molar volumes increase linearly with temperature, with a more pronounced temperature effect for shorter-chain alkylcyclohexanes. The Jouyban–Acree model provides an excellent correlation of the density data, yielding average relative deviations between 0.02% and 0.04%, and allows reliable predictions within the investigated temperature range. Full article

Design coordination is a critical process for avoiding spatial conflicts and ensuring design alignment in large-scale construction projects. While Building Information Modelling (BIM) tools have improved coordination through 3D model integration and clash detection, inefficiencies persist due to fragmented workflows, frequent tool switching, and challenges with issue documentation. Cloud-based BIM collaboration tools offer a promising alternative by enabling real-time model sharing, centralized issue tracking, and enhanced stakeholder communication. However, empirical evidence on their practical implementation and effects on coordination processes remains limited. Unlike prior cloud-BIM reviews that focus on technical capabilities or adoption barriers in isolation, this study provides an empirically grounded framework that links specific tool features to observable workflow changes and their downstream impacts on coordination outcomes. This study investigates the impact of cloud-based BIM collaboration tools on the design coordination process, with a focus on issue identification, resolution, and documentation. A framework was developed using a mixed-methods approach comprising action research, an ethnographic case study, and comparative analysis of three large infrastructure projects to categorize workflow changes resulting from tool adoption. The findings indicate that cloud-based BIM tools streamline coordination by reducing manual transitions, automating documentation, and improving information accessibility during meetings. Nevertheless, their effectiveness is constrained by organizational structures and contract limitations. This study provides a validated process-change framework and practical insights for engineering managers seeking to align digital collaboration tools with project delivery strategies, contributing to both theory and practice in BIM-based coordination and digital transformation in the AEC industry. Full article

Industrial heritage in resource-depleted mining towns faces the dual challenge of physical decay and social severance. To achieve sustainable urban revitalization, adaptive reuse strategies must align with local collective memory and emerging experiential consumption trends. Adopting a Scene Theory perspective, this study constructs a multi-level analytical framework using Meitanba Town (Hunan, China) and its power plant as a case study. A mixed-methods approach was employed, combining semantic network analysis of 1582 online user comments with 61 offline questionnaires distributed to local residents to quantitatively diagnose current scene elements, functions, and features. The quantitative results reveal a significant imbalance: while “Functional Media” achieved the highest comprehensive score (10.0) due to strong historical recognition, “Diverse Groups” scored the lowest (3.4), indicating a lack of social inclusivity. Specifically, residents expressed the highest demand for sports facilities (31.2%) and cultural spaces (23.7%), identifying the main workshop (26.4%) and chimney as core carriers of industrial identity. Responding to these findings, the paper proposes three targeted strategies: (1) Activate: creating open-access recreation scenes to satisfy urgent sports demands; (2) Link: constructing immersive cultural scenes to narrate the “coal–electricity–life” history; and (3) Enhance: developing industry-powered commercial scenes to avoid homogenization. This study enriches the localized application of Scene Theory and provides a data-driven, context-adjustable analytical and strategic model that can inform the sustainable renewal of mining towns globally, with its specific implementation requiring adaptation to local social, economic, and cultural characteristics. Full article

Technological advances such as Vehicle-to-Grid (V2G) have the potential to support renewable energy integration and grid stability, but large-scale deployment depends on users’ willingness to participate, particularly in public charging environments. While prior research has examined V2G from technical feasibility and system-level perspectives, everyday public settings remain unexplored. This study investigates electric vehicle (EV) users’ willingness to engage in V2G services in public spaces, with a focus on incentives, expectations, and how participation aligns with existing routines and parking conditions. A mixed-method approach was applied, combining a survey of 544 car users with two waves of user-centered interviews. The survey data were analyzed using factor analysis and linear regression models, while the interview data were thematically analyzed. The results show that users’ evaluations of V2G are shaped by sustainability expectations, perceived efficiency, and uncertainties, and preferences for public V2G participation are strongly influenced by convenience, clarity of the offer, and perceived control. Home charging practices emerged as a key reference point shaping expectations of public V2G services. Across both methods, simple and transparent incentives, such as reduced charging or parking costs, were consistently preferred over more complex reward models, including point-based systems or dynamic energy trading. Concerns related to control over trips, battery degradation, trust in service providers, and added complexity remain important barriers to participation. The findings highlight the need for user-centered and socio-technical design of public V2G services that align with users’ everyday routines, parking conditions, and expectations to support broader adoption beyond the home context. Full article

Pedestrian safety at urban crosswalks remains a major public concern, as both vehicle speeds and roadway characteristics strongly influence drivers’ behaviour when approaching these locations. This study investigates driver behaviour patterns when approaching pedestrian crossings by integrating operating speed with key road-layout features derived from a naturalistic driving experiment conducted in Florence. A dataset of 401 observations was analysed using an unsupervised clustering framework specifically designed to handle mixed numerical and categorical variables. After preprocessing, the optimal number of clusters was identified using an elbow-based model selection applied to the K-Prototypes algorithm. The analysis produced four distinct clusters, primarily differentiated by operating speed and secondarily by contextual variables such as lane number, lane width, and acceleration behaviour. Lower-speed clusters were associated with single narrow-lane configurations, whereas higher-speed clusters were characterised by wider or multilane segments and more frequent acceleration near crossings. Information Gain analysis confirmed the dominant role of lane-related attributes, while the presence of crosswalks alone did not systematically reduce speeds. Complementary clustering excluding speed resulted in fewer clusters, indicating that speed adds essential granularity to behavioural segmentation. These findings highlight the interplay between road design and driver behaviour and provide evidence-based insights to support crosswalk configurations that mitigate high-speed conflicts in urban settings. Full article

The reinforcement and renovation of existing buildings constitute an important component of the future development of the civil engineering industry. Such projects typically require the original construction drawings of the building. However, for older structures, the original paper-based drawings may be damaged or lost. Moreover, traditional manual surveying and mapping methods are time-consuming, labor-intensive, and limited in accuracy. To address these issues, this paper proposes a floor plan generation method for existing buildings that integrates deep learning and stereo vision based on a fusion of synthetic and real data. First, collaborative modeling and automated rendering between a large language model and Blender are implemented based on the Model Context Protocol (MCP), enabling indoor scene modeling and image acquisition to construct a synthetic dataset containing structural components such as doors, windows, and walls. Meanwhile, manually annotated real indoor images are incorporated. Synthetic and real data are mixed in different proportions to form multiple dataset configurations for model training and validation. Subsequently, the SegFormer model is employed to perform semantic segmentation of indoor components. Combined with stereo camera calibration results, disparity computation is conducted to extract the three-dimensional spatial coordinates of component corner points. On this basis, the architectural floor plan is generated according to the spatial geometric relationships among structural components. Experimental results demonstrate that the proposed method effectively reduces the need for manual annotation and on-site measurement, providing an efficient technical solution for indoor floor plan generation of existing buildings. Full article

The high viscosity of biodiesel fuel, caused by the presence of saturated fatty acid esters, limits its application, particularly at low temperatures. Supercritical fluid extraction (SFE) using carbon dioxide represents a promising method for selective fractionation, enabling the removal of high-viscosity saturated components and the enrichment of the fuel with less viscous unsaturated esters. However, the rational design of such processes requires a deep understanding of the interrelationship between flow hydrodynamics, thermodynamic conditions, and mass transfer in a supercritical medium. In this work, a comprehensive computational fluid dynamics (CFD) modeling study of the fractionation process was performed for a model ethyl oleate/ethyl palmitate mixture (25.28:74.72 wt.%) in supercritical CO₂ at pressures of 11 and 14 MPa and a temperature of 40 °C. A three-dimensional model of a laboratory-scale extractor was developed using the Ansys Fluent software version 2020 R1 environment. Since the target esters are absent from the standard material database, a custom property library and compiled User-Defined Function (UDF) routines were developed. These describe the temperature dependence of density, viscosity, heat capacity, and thermal conductivity for both the individual components and their mixture using established mixing rules. The calculations employed an Eulerian multiphase model, the realizable k–ε turbulence model, and species transport equations. The modeling revealed pronounced selectivity: under the chosen thermodynamic conditions, ethyl palmitate is extracted preferentially over ethyl oleate, with this difference becoming more pronounced as pressure increases. The developed and verified CFD model deepens the fundamental understanding of hydrodynamics and mass transfer during supercritical fractionation and serves as a basis for optimizing process parameters to produce biodiesel with reduced viscosity. The regime at P = 14 MPa and t = 40 °C provides the most favorable thermodynamic and hydrodynamic conditions for the selective removal of saturated esters. Full article

Objectives: The objective of this study is to evaluate the effect of 635 nm photobiomodulation on the rate and magnitude of maxillary canine distalization following extraction of the maxillary first premolars in adult patients. Materials and Methods: This randomized, controlled, split-mouth clinical trial included 18 adult patients undergoing extraction-based orthodontic treatment for Class II malocclusion. Maxillary first premolars were extracted, and canine distalization was performed using nickel–titanium closed-coil springs delivering a constant force of 150 g, supported by orthodontic mini-implants providing absolute anchorage. Photobiomodulation was applied on one randomized side using a 635 nm diode laser operating at 100 mW in continuous-wave mode, with an 8 mm handpiece diameter. Laser irradiation was delivered in contact mode to two application sites per session corresponding to the buccal and palatal aspects of the maxillary canine root, with an exposure time of 60 s per site. Irradiation was performed according to a predefined schedule over a 45-day observation period, while the contralateral side served as a sham-treated control. Tooth movement was assessed by repeated measurements of inter-bracket distance. A linear mixed-effects model was used to analyze the effects of treatment, time, and their interaction on tooth movement dynamics. Results: The linear mixed-effects model revealed a significant interaction between treatment and time (p < 0.001), indicating a greater rate of canine distalization on the photobiomodulation-treated side compared with the control side. Treatment and time also demonstrated significant main effects. After 45 days, the mean cumulative canine displacement was approximately 1.6 mm greater on the photobiomodulation side than on the control side. Age and sex did not significantly influence tooth movement. Conclusions: Photobiomodulation at a wavelength of 635 nm significantly increased the rate of maxillary canine distalization in adult extraction cases over a 45-day observation period. Full article

To address the issues of safety risk analysis and conflict assessment for integrated flight of manned aircraft and fixed-wing unmanned aerial vehicles (UAVs) in low-altitude mixed-operation airspace, this study enhances the foundational Event model. By incorporating UAV characteristics such as geometric features and aerodynamic mechanisms, alongside design dimensions and onboard performance metrics, an improved collision risk model is developed—the Enhanced Event-Based Framework for Multidimensional Geometry and Quasi-Monte Carlo Analysis of Flight Performance (EMGF-M). This enhancement rectifies the limitations of the basic model regarding parameter coverage and scenario adaptability, thereby improving the reliability and validity of the computational results. Experimental results demonstrate that, in accordance with the target safety level for airspace conflicts set by the International Civil Aviation Organization (ICAO), the application of the improved Event collision model yields quantifiable assessments of safety risks and safe separation distances for integrated operations in low-altitude mixed-use airspace. Utilizing these computational results for integrated flight procedure design at a general airport in Southwest China, the study shows that the air traffic flow in the low-altitude mixed-operation airspace increased from 9.2 to 20.9 operations per hour. The practical significance of this method lies in its guidance for accurately assessing safety risks in mixed airspace operations and for determining quantifiable separation minima for integrated flight trajectory planning. Full article

The specialty coffee sector faces increasing competitive and sustainability challenges and lacks structured innovation frameworks. This study proposes an Innovation Management Model (IMM) based on open innovation for specialty coffee value chains, applied to the agro-industrial chain in Quindío, Colombia. This research adopts a mixed-methods approach and model development to identify, prioritize, and validate key variables for an IMM based on open innovation. Among the data collection techniques and instruments used, the study incorporated, in its first phase, a literature review based on the PRISMA protocol and, in its second phase, validation through workshops with experts to identify key variables and select the proposed or winning IMM. As a result of this research process, three (3) Innovation Management Models were developed. It is concluded that the specialty coffee sector requires multiple interventions to consolidate the proposed IMM-3 as the winning model, emphasizing the imperative need for alignment with the concept of Open Innovation. The importance of this study lies in the practical recommendations for implementing MGI-3 within the studied chain, with potential applicability to other agro-industrial chains in different regions of Colombia. Full article

Background: The decline in physical activity during the transition to early adolescence poses a significant threat to lifelong health and well-being, directly impacting the targets of Sustainable Development Goal 3 (SDG 3). To design effective preventive interventions, researchers need developmentally appropriate tools to measure the psychological drivers of physical activity. Objectives: This study aimed to adapt the Attitude Towards Sport Scale (ATSS) for middle school students (ages 10–15) and evaluate its psychometric properties. Methods: We used a mixed-methods approach comprising a qualitative cognitive think-aloud phase (n = 27) and a quantitative cross-sectional validation phase (N = 531). Data were analyzed using robust Confirmatory Factor Analysis (CFA). Results: The results supported the structural model, demonstrating that the original three-factor structure fits the early adolescent sample acceptably. The scale demonstrated high composite reliability across all dimensions. Furthermore, the adapted ATSS-EA showed strong criterion-related validity through high correlations with perceived physical literacy and actual physical activity durations. It also successfully differentiated between licensed athletes and non-licensed students. Conclusions: The adapted ATSS-EA provides a developmentally appropriate tool for educators and researchers to monitor sport attitudes and identify students at risk of physical disengagement. Full article

Background: Large language models (LLMs) are being used by surgeons for education and reference yet concerns about hallucinations and reliability limit safe adoption. Retrieval-augmented generation (RAG) can offer a potential solution by grounding responses in a high-quality external database (e.g., medical textbooks) to enhance accuracy. However, performance tradeoffs across different RAG configurations—many of which exponentially increase computational cost—remain poorly characterized. Methods: In total, 120 lightweight, open-source RAG configurations were evaluated across 40 plastic surgery-focused question-answering tasks (20 single-hop, 20 multi-hop), spanning multiple subspecialties (4800 total evaluations). Configurations varied by base LLM (Phi-3-mini-128k-instruct vs. BioMistral-7B), embedding model, database size, chunk size, and query hop type. Performance was assessed using semantic similarity (Ragas) to physician-validated reference answers. Performance was analyzed using linear mixed-effects regression with query as a random effect and fixed and interaction effects selected via likelihood testing and AIC. Results: High performance was achievable using lightweight, open-source models. While BioMistral-7B had high mean sematic similarity under specific configurations (mean semantic similarity up to 0.786), Phi-3-mini-128k-instruct demonstrated more consistent performance across query complexity. Larger database sizes significantly improved semantic similarity, with the largest gain at intermediate sizes (e.g., size 5: +0.043, p = 0.001). Embedding choice had a strong effect, with bge-large-en-v1.5 improving performance (p = 0.0016) and Bio_ClinicalBERT markedly reducing it (p < 0.001). Multi-hop queries substantially reduced performance (p < 0.001), though this effect was attenuated for Phi-3-mini-128k-instruct via a strong model × hop-type interaction (p < 0.001). Conclusions: RAG systems for plastic surgery do not require large proprietary models, as performance depends on configuration choices and interaction effects rather than isolated components. With advancements, predictive modeling may enable resource-efficient, safe deployment of clinical RAG systems. Full article

Massive Open Online Courses (MOOCs) serve as catalysts for sustainable education by democratizing access to lifelong learning. While this potentially positions them as a key driver of the United Nations Sustainable Development Goal 4 (SDG 4), their long-term impact depends heavily on the implementation of inclusive design and ethical governance. This study evaluates the social sustainability of the AKADEMA platform—defined through equity of access, institutional trust, and long-term learner retention—using Badrul Khan’s e-learning framework. Employing a multi-layered mixed-methods design, the study triangulates subjective user perceptions—gathered via quantitative surveys (N = 209; a convenience sample of 6140 contacted users) and qualitative insights (n = 122)—with objective structural evidence from a technical accessibility audit. Although the results indicate high satisfaction with pedagogical quality, the findings reveal specific structural nuances regarding platform inclusivity and user diversity. Specifically, data triangulation highlights a notable ‘privacy awareness gap’—where working professionals demonstrate higher sensitivity regarding data governance than learners—alongside structural barriers hindering ‘Universal Design’ for learners with disabilities. Consequently, to strengthen the sustainability of open education models, future strategies should emphasize digital equity and institutional trust, ensuring that technical environments align with the promise of inclusive quality education. Full article