Search Results (2,284)

Virtual reality offers unique opportunities to personalize learning by adapting instructions to individual learning styles. This study explores the relationships between learning styles, cognitive load, and learning outcomes in a virtual reality environment designed for engineering education. Drawing on Kolb’s experiential learning theory, the research investigates how immersion and flow, in relation to learning styles, influence learning outcomes within the Submarine Simulator, an educational tool for underwater engineering. To enhance instructional design in virtual reality, this study proposes to aggregate existing and validated models, such as Kolb’s framework, to develop new models tailored specifically for learning environments in virtual reality. This research aims to highlight the interplay of these variables in a learning process focused on acquiring knowledge in the Science, Technology, Engineering, and Mathematics fields, specifically hydrodynamics, through designing and operating a simulated submarine model in virtual reality. A cohort of 26 students from MINES Paris—PSL participated in a three-phase testing process to evaluate the effectiveness of original virtual reality software designed to support learning in underwater engineering. The findings enhance our understanding of how learning styles influence learner engagement and performance and how virtual reality environments can be optimized through adaptive instructional design guided by these novel models tailored specifically for such immersive settings. Full article

The architecture, engineering, and construction (AEC) industry is highly fragmented, yet decisions made during the design phase critically shape downstream sustainability performance. Unlike prior research that primarily weighted interactions by frequency, this study introduces an Interaction-Quality Index that evaluates the quality of design team interactions. This represents a novel approach, as it combines Social Network Analysis with Monte Carlo simulation to quantify how collaboration, coordination, and trust influence sustainable outcomes in construction projects. Through a structured literature review, three systemic interaction drivers; collaboration, coordination, and trust were identified. An interaction-quality index was then formulated, weighting each driver according to its relative impact on sustainable outcomes. Social Network Analysis coupled with Monte Carlo simulation validated the index in a real-world building project, demonstrating its usefulness in identifying critical interaction nodes and highlighting how improvements in collaboration, coordination, and trust can strengthen network cohesion and enhance sustainability-oriented decision-making. The proposed index offers construction managers a quantitative tool to integrate social dynamics into holistic sustainability strategies, advancing practice in line with systems-thinking approaches to sustainable construction management. Full article

Background/Objectives: This scoping review aims to map existing AI applications in dental education, in student learning, assessment, and diagnostic training, identifying key limitations and challenges. Methods: Following the Arksey and O’Malley framework and PRISMA-ScR guidelines, six databases were searched in March 2025 using combinations of the following search words: “dental education,” “artificial intelligence,” “machine learning,” and “student assessment”. Inclusion was limited to English-language empirical studies focused on dental student education. Of 547 identified studies, 17 met the inclusion criteria. They were categorized into four domains: (1) Preclinical Training, (2) AI in Clinical, Diagnostic Training, and Radiographic Interpretation, (3) AI as an Assessment Tool and Feedback System, and (4) AI in Content Generation for Dental Education. Results: AI has positively influenced various domains, enhancing procedural accuracy, diagnostic confidence, assessment efficiency, and content delivery. However, it struggles to assess nuanced competencies like dexterity and clinical judgment. The challenges faced include disparate definitions of AI, ethical and privacy concerns, model variability, and a deficiency of dental leadership in AI development. At present, most tools are engineered by computer scientists and may not align effectively with the priorities of dental education. Conclusions: AI holds significant potential to enhance dental education outcomes. However, to guarantee its relevance and reliability, it requires standard frameworks, ethical oversight, and clinician-led development. Future research should concentrate on implementing real-time AI-driven feedback systems during preclinical training and advocate for more precise definitions to support consistent AI application and evaluation in dental education. Full article

This paper introduces a new optimization problem-solving method based on how the stingless bee Tetragonula carbonaria builds and regulates temperature in the hive. The Tetragonula carbonaria Optimization Algorithm (TGCOA) models three different behaviors: strengthening the structure’s hive when it is cold, building combs in a spiral pattern at medium temperatures, and stabilizing the hive when it is hot. These temperature-dependent strategies dynamically balance global exploitation and local exploration within the solution space, enabling a more efficient search. To validate the efficiency and effectiveness of the proposed method, the TGCOA algorithm was tested using ten unimodal and ten multimodal benchmark functions, twenty-eight constrained problems with dimensions set to 10, 30, 50, and 100 taken from the IEEE CEC 2017, and seven real-world engineering design challenges. Furthermore, it was compared with ten algorithms from the literature. Wilcoxon signed-rank and Friedman statistical tests were performed to assess the outcomes. The results on the benchmark problems showed that the approach outperformed 80% of the algorithms at a 5% significance level in the Wilcoxon signed-rank test and ranked first overall according to the Friedman test. Additionally, in multidimensional problems, the TGCOA was ranked first in dimensions 30, 50, and 100. Moreover, in engineering problems, the approach demonstrated a high capacity to solve constraint problems, obtaining better results than the algorithms that were compared. Full article

The construction industry is the biggest consumer of raw materials, and there is growing pressure for this industry to reduce its environmental footprint through the adoption of sustainable solutions. Waste plastic in a recycled form can be used to produce valuable products that can decrease dependence on natural resources. Despite the growing trend of exploring the potential of recycled plastics in construction through composite manufacturing and nonstructural products, to date no scientific data is available about converting waste plastic into recycled plastic to manufacture interlocking hollow blocks (IHBs) for construction. Thus, the current study intended to fill this gap by investigating the dynamic, mechanical, and physicochemical properties of engineered IHBs made out of recycled plastic. Engineered IHBs are able to self-center via controlled tolerance to lateral displacement, which makes their design novel. High-density polyethylene (HDPE) waste was considered due to its anticipated material properties and abundance in daily-use household products. Mechanical recycling coupled with extrusion-based pressurized filling was adopted to manufacture IHBs. Various configurations of IHBs and prism samples were tested for compression and shear strength, and forensic tests were conducted to study the physicochemical changes in the recycled plastic. In addition, to obtain better dynamic properties for energy dissipation, the compressive strength of the IHBs was 30.99 MPa, while the compressive strength of the prisms was 34.23 MPa. These values are far beyond the masonry strength requirements in applicable codes across the globe. In-plane shear strength was greater than out-of-plane shear strength, as anticipated. Microstructure analysis showed fibrous surfaces with good resistance and enclosed unburnt impurities. The extrusion process resulted in the elimination of contaminants and impurities, with limited variation in thermal stability. Overall, the outcomes are favorable for potential use in house construction due to sufficient masonry strength and negligible environmental concerns. Full article

Chronic pancreatitis (CP) precipitates complex malnutrition through synergistic mechanisms: exocrine pancreatic insufficiency–driven maldigestion, duodenal or pancreatobiliary strictures limiting nutrient flow, cholestasis impairing micelle formation, alcohol-related anorexia, pain-induced hypophagia, proteolytic catabolism from type 3c diabetes, and a chronic inflammatory milieu that accelerates sarcopenia and bone demineralisation. Consequent calorie–protein depletion, micronutrient and fat-soluble vitamin deficits, and metabolic derangements markedly amplify morbidity. Pancreatic enzyme replacement therapy (PERT) with targeted micronutrient repletion is foundational; high-protein regimens co-administered with PERT curb muscle loss, and medium-chain triglycerides (MCTs) can augment caloric delivery by bypassing lipase dependence, although their benefit over personalised dietetic counselling is marginal. Optimal dietary fat thresholds and timing of escalation from oral to enteral or parenteral feeding remain unresolved. Comprehensive care also demands alcohol abstinence, effective analgesia and stringent glycaemic control. Serial monitoring—biochemical indices, densitometry, dual-energy X-ray absorptiometry and imaging-based body-composition metrics—permits early detection of high-risk patients and precision tailoring of interventions. Intensified multidisciplinary programmes already improve prognostic endpoints and are unveiling biomarkers of nutritional resilience. A structured, evidence-based strategy integrating PERT, macronutrient engineering, micronutrient repletion and metabolic surveillance is essential to mitigate nutrition-related morbidity, enhance long-term outcomes and optimise quality of life in CP. Full article

The accumulation of blood toxins, including urea, uric acid, creatinine, bilirubin, p-cresyl sulfate, and indoxyl sulfate, poses severe health risks for patients with renal failure. Effective removal strategies are essential to mitigate complications associated with chronic kidney disease (CKD) and improve patient outcomes. Functional carbon-based materials, such as activated carbon (activated charcoal) and graphene oxide, have emerged as promising adsorbents due to their large surface area, adjustable porosity, and biocompatibility. This review comprehensively explores the latest advancements in carbon-based materials for blood purification across three key therapeutic modalities: (1) Hemoperfusion, where activated and modified carbonaceous materials enhance the adsorption of small-molecule and protein-bound toxins; (2) Hemodialysis, where functionalized carbon materials improve clearance rates and reduce treatment duration; and (3) Oral Therapeutics, where orally administered carbon adsorbents show potential in lowering systemic toxin levels in CKD patients. Furthermore, we present a comparative analysis of these approaches, highlighting their advantages, limitations, and future research directions for optimizing carbon-based detoxification strategies. The findings discussed in this review emphasize the significance of material engineering in advancing blood purification technologies. By enhancing the efficiency of toxin removal, carbon-based materials have the potential to revolutionize renal failure treatment, offering improved clinical outcomes and enhanced patient quality of life. Full article

Architecture, engineering, and construction (AEC) education requires a radical shift in pedagogical strategies to enhance knowledge retention, critical thinking, practical skills development, and student engagement. The integration of immersive tools such as virtual reality and augmented reality (VR/AR) into AEC curricula has shown enormous potential in enhancing learning outcomes. Despite the increasing popularity of these tools, their adoption for sustainable construction materials and systems such as mass timber building remains underexplored, especially for teaching and facilitating their curricula delivery. This study adopted a systematic review following PRISMA guidelines and a scientometric analysis across key AEC journals. The study synthesizes findings from 69 peer-reviewed articles across three databases. While the findings suggest that VR/AR significantly enhances learning outcomes, key gaps such as lack of standardized evaluation metrics, inadequate faculty training, and a lack of a robust integration framework persist, especially for mass timber and overall sustainability education. This study proposed a foundational framework for VR/AR integration in AEC curricula for mass timbers education and highlighted some pedagogical strategies for bridging the identified gaps. The insights establish the basis for future research that will develop and evaluate a VR-based instructional tool to teach mass timber and sustainable construction education. Full article

Osteochondral regeneration remains a major clinical challenge due to the complex architecture and biomechanical demands of the osteochondral unit. Bioactive hydrogels have emerged as promising materials capable of supporting repair through their capacity to mimic the extracellular matrix (ECM), enable cell encapsulation, and deliver bioactive cues. However, recent insights reveal that simply engineering hydrogels for structural and cellular support is insufficient. A new paradigm is emerging—one that embraces the complexity of the osteochondral niche by integrating immunomodulatory and mechanobiological cues into biomaterial design. In particular, the hydrogel’s capacity to modulate macrophage polarization and support the immunoregulatory function of mesenchymal stem cells (MSCs) is critical to orchestrate regenerative outcomes. Simultaneously, the mechanical properties of hydrogels—such as stiffness, porosity, and viscoelasticity—can profoundly influence stem cell fate and local tissue morphogenesis. This review discusses recent advances in hydrogel-based strategies for osteochondral repair, highlighting the interplay between immunological signals and the mechanical microenvironment, and calls for a shift from reductionist tissue-engineering approaches to systems-level design of tunable, immuno-mechanobiological microenvironments. Full article

Universities play a critical role in shaping sustainable mobility strategies, especially in urban contexts where the institutional transport system can influence environmental and social outcomes. This study integrates Environmental and Social Life Cycle Assessment (E-LCA and S-LCA) to evaluate the current university transport system from internal combustion engines, diesel, and compressed natural gas (CNG), focusing on the operation and maintenance phases. Also, it compares seven scenarios, including electric, renewable sources, and biodiesel technologies. Environmental impacts were assessed using the ReCiPe 2016 midpoint method, which considers the following impact categories: Global Warming Potential (GWP); Ozone Formation, Human Health (OfHh); Ozone Formation, Terrestrial Ecosystem (OfTe); Terrestrial Acidification (TA); and Fine Particulate Matter Formation (FPmf). The sensitivity analysis explores scenarios to assess the effects of technological transitions and alternative energy sources on the environmental performance. Social impacts are assessed through a Social Performance Index (SPI) and Aggregated Social Performance Index (ASPI), which aggregates indicators such as safety, travel cost, punctuality, accessibility, and inclusive design. Accessibility emerged as the lowest indicator (ranging from 0.61 to 0.67), highlighting opportunities for improvement. Our findings support decision-making processes for integrating sustainable transport strategies into a University Mobility Plan, emphasizing the importance of combining technical performance with social inclusivity. Full article

Industry 4.0 has intensified the skills gap in industrial automation education, with graduates requiring extended on boarding periods and supplementary training investments averaging USD 11,500 per engineer. This paper introduces VisFactory, a multimedia learning system that extends the cognitive theory of multimedia learning by incorporating haptic feedback as a third processing channel alongside visual and auditory modalities. The system integrates a digital twin architecture with ultra-low latency synchronization (12.3 ms) across all sensory channels, a dynamic feedback orchestration algorithm that distributes information optimally across modalities, and a tripartite student model that continuously calibrates instruction parameters. We evaluated the system through a controlled experiment with 127 engineering students randomly assigned to experimental and control groups, with assessments conducted immediately and at three-month and six-month intervals. VisFactory significantly enhanced learning outcomes across multiple dimensions: 37% reduction in time to mastery (t(125) = 11.83, p < 0.001, d = 2.11), skill acquisition increased from 28% to 85% (${\eta }_p^2=0.54$), and 28% higher knowledge retention after six months. The multimodal approach demonstrated differential effectiveness across learning tasks, with haptic feedback providing the most significant benefit for procedural skills (52% error reduction) and visual–auditory integration proving most effective for conceptual understanding (49% improvement). The adaptive modality orchestration reduced cognitive load by 43% compared to unimodal interfaces. This research advances multimedia learning theory by validating tri-modal integration effectiveness and establishing quantitative benchmarks for sensory channel synchronization. The findings provide a theoretical framework and implementation guidelines for optimizing multimedia learning environments for complex skill development in technical domains. Full article

As a rapidly developing and potent instrument for resolving practical issues, artificial intelligence (AI) has garnered considerable interest and has been widely used in many different domains. Diverse AI models have also been used in wastewater treatment (WWT) to optimize processes, forecast efficiency, and assess performance in order to explore high-efficiency and cost-effective solutions because of their remarkable learning and predictive capabilities. This review gathers the latest developments and applications of AI technologies in wastewater treatment plants and carefully examines the application and outcomes of various AI models, including artificial neural networks (ANN), support vector machines (SVM), decision trees (DT), and deep learning (DL), in domains such as water quality monitoring, process optimization, fault diagnosis, membrane fouling prediction and control, and resource recovery. This study examines the benefits of these models in real-world engineering applications through a comparison with traditional approaches, as well as current issues like data collection and model generalization. Additionally, it looks to the future, where AI will be used in conjunction with emerging technologies like cloud computing, big data, and the Internet of Things (IoT) to drive the automated and intelligent advancement of wastewater treatment. Full article

This study explores the feasibility of using 3D printing technology to fabricate reference materials for validating compressive strength measurements in construction laboratories. Polylactic acid (PLA) and polyethylene terephthalate glycol-modified (PETG) were selected due to their widespread availability and use in fused deposition modeling (FDM). A series of cubic samples with varying infill levels and dimensions were printed and tested to evaluate the influence of infill density, temperature, and storage time on compressive strength. PLA samples exhibited higher compressive strength values (from 23.5 kN for 10% infill to 70.7 kN for 50% infill) and a steeper increase in strength with rising infill density compared to PETG (from 12.4 kN for 10% infill to 44.1 kN for 50% infill). However, PETG demonstrated superior stability over time, with significantly smaller increases in result variability after 31 days. The results confirm a strong linear correlation between infill level and compressive strength and indicate that even small fluctuations in ambient temperature can influence test outcomes. Despite PLA’s initial mechanical advantage, PETG’s aging resistance makes it a promising candidate for the development of durable and repeatable reference materials (increment of StD for PLA from 0.17 kN to 0.63 kN and 0.25 kN to 0.37 for PET-G). This research contributes to closing the gap in the availability of reliable mechanical reference materials for destructive testing, offering a novel application for 3D printing in quality control in civil engineering. Full article

Cracking is the most prevalent deterioration issue in historic masonry, and grouting represents one of the most effective intervention techniques. Superplasticizer-free Natural Hydraulic Lime (NHL) grout is recommended for heritage conservation due to its simple composition and compatibility with historic masonry in terms of strength, porosity, and other properties. However, grout shrinkage is frequently observed in practice, often leading to suboptimal reinforcement outcomes. This study focuses on the shrinkage characteristics of NHL grouts. Three sets of experiments were designed to investigate the influence: grout composition, expansive agents, and substrate properties. Using Taguchi’s method, an optimized combination of water, binder, and aggregate was identified. Shrinkage measurements after curing for 28 days demonstrated that calcium oxide (CaO)-based expansive agents was the best choice to compensate for NHL grout shrinkage. In addition, grouting simulation experiments evaluated suitable formulations for common masonry substrates and clarified the significant impact of substrate water absorption on the degree of shrinkage grout. For substrates with a capillary water absorption coefficient greater than 25 kg/m² h^1/2, the use of expansive agents should be strictly controlled. The findings can provide valuable insights for optimizing the grouting reinforcement of historic masonry structures and offer direct material design strategies for practical engineering applications. Full article

In the age of digital transformation, where students increasingly rely on technology for learning and communication, concerns arise regarding its potential association with academic outcomes. This study quantifies the relationship between Digital Behaviour (DB) and Academic Behaviour (AB) among engineering undergraduates at Misurata, Al-Asmarya Islamic, and Al-Marqab universities in Libya. DB is conceptualised as a spectrum ranging from excessive, compulsive device use (addictive behaviour) to purposeful academic technology use (digital immersion). Using a descriptive-analytical design, a convenience sample of 300 undergraduate engineering students completed a validated 20-item questionnaire (Cronbach’s α = 0.711–0.899 for subscales). Data were analysed using descriptive statistics, Pearson correlation, simple regression, and analysis of variance (ANOVA) in the Statistical Package for the Social Sciences (SPSS) v23. The analysis identified a weak but statistically significant positive correlation between students’ DB and their AB (r = +0.19, p = 0.002). Notably, AB scores increased in the senior study years, while digital engagement remained consistently high across all years, suggesting an evolving capacity among students to regulate their digital habits. ANOVA results revealed significant differences in AB by year of study, while gender showed no significant overall association. These findings contradict the conventional assumption that heavy digital use uniformly diminishes academic outcomes; instead, in digitally immersed learning environments, strategic DB may coexist with or support academic performance. The study concludes that DB is not inherently detrimental to AB and may provide benefits when managed effectively, especially among more advanced engineering students. It recommends early educational interventions that promote digital self-regulation and the strategic use of technology for academic purposes. Full article