Search Results (2,284)

Kerf bending, achieved through precisely patterned cuts, enables the transformation of rigid plywood into flexible, adaptive surfaces for advanced design and ergonomic applications. This preliminary, exploratory study systematically investigates 56 laser-cut kerf geometries—spanning both traditional and novel parametric patterns—in birch plywood sheets of two thicknesses. Mechanical performance was evaluated via standardised testing, with statistical analyses (including Weibull and coefficient of variation) employed to interpret the pronounced variability observed in maximum load (Fmax) values, even among geometrically similar patterns. Due to the limitation of single-specimen destructive testing per pattern, the results should be understood as indicative trends within this experimental set, not as definitive rankings. Observed results suggest that kerf geometry and arrangement—rather than thickness or gross material removal—are the primary determinants of flexibility and strength. Notably, specific parametric and meander-type patterns demonstrated promising balances of deformation capacity and mechanical reliability within this limited dataset. The inherent limitations of experimental replication and natural material heterogeneity are explicitly acknowledged, and the findings are intended as a foundation for future, more statistically robust investigations. This work provides a comparative framework and initial design guidance for kerf-based plywood structures and identifies key priorities for further research in replication, material selection, and real-world applications. Full article

In this study, we examined how disinformation and trustworthy news differ in their narrative construction across nine theoretically motivated dimensions. We address the following research question: how do disinformation and trustworthy news differ in narrative organisation and epistemic grounding? We analysed 610 English-language news articles (308 pro-Kremlin disinformation and 302 trustworthy articles) covering selected international events from 2015 to 2023, using data derived from the EUvsDisinfo dataset. Narrative elements were extracted using a hybrid pipeline combining large language models and knowledge graphs, resulting in article-level representations for comparative analysis. Ordinal scores (1–5) were assigned for emotional intensity, cultural complexity, conspiracist structure, source diversity, crisis intensity, evidence support, media control, solutions orientation and memory work. Non-parametric comparisons showed significant differences in eight of these nine dimensions. Disinformation articles revealed stronger conspiracist structuring and greater meta-media hostility, as well as significantly lower source diversity, evidence support, cultural complexity and weaker memory work. Emotional intensity did not differ reliably across disinformation and trustworthy news. A simple additive NarrativeRisk score, which we designed as a transparent and interpretable summary measure, showed between-group differences in both parametric and non-parametric tests. As a univariate discrimination indicator, NarrativeRisk achieved ROC AUC ≈ 0.84. Cluster analysis identified three recurrent narrative profiles, including one dominated by disinformation, one by trustworthy news and one mixed profile. These findings indicate that disinformation is distinguished not only by factual unreliability but also by different patterns in narrative organisation. Full article

The literature identifies concrete and steel as the primary contributors to embodied carbon in building structures and highlights a strong relationship between sustainability and structural system geometry. However, existing studies predominantly focus on one-way systems and flat slabs, while research on two-way joist slabs remains limited and often centred on strength optimisation. In particular, there is a lack of systematic life cycle comparisons of alternative beam configurations within this system. This gap is critical, as early-stage design decisions largely determine the environmental impact of structural systems. This study presents a comprehensive, span-dependent evaluation of four beam configurations, namely Without Beam, Internal Beam, Perimeter Beam, and Full Beam, for reinforced concrete two-way joist slabs used in office buildings. A parametric framework was developed using Eurocode-compliant structural design and nonlinear finite element modelling to assess 36 span combinations ranging from 4 × 4 m to 14 × 14 m. Material quantities were extracted from the final designs and converted into embodied carbon values using cradle-to-gate (A1–A3) emission factors derived from the ICE database. The results demonstrate that beam configuration has a significant influence on embodied carbon and construction cost. For spans below approximately 8 m, beamless systems provide the most material-efficient solution. For spans exceeding approximately 10 m, full-beam configurations offer improved structural efficiency and reduced embodied carbon due to enhanced stiffness and load distribution. Full article

The rising demand for cooling in hot semi-arid cities like Jaipur is putting increasing pressure on energy infrastructure and urban resilience. This study investigates the potential of Jaali, a traditional perforated screen used in Indian architecture, as a passive strategy to reduce energy demand in a contemporary office building through data-driven optimisation and computational analysis. Using detailed energy simulations in DesignBuilder, this research explores how variations in orientation, cavity depth, perforation ratio and screen thickness affect cooling performance during the summer months through a systematic parametric study generating 84 simulation configurations. The model is based on a 12-storey office building designed according to local energy codes. The results show that the optimal configuration differs by orientation. On the south façade, the optimal combination is a 100 mm Jaali with 20% perforation and a 1.5 m cavity, which delivers the best performance. The west façade performs best with a thicker 150 mm screen, the same 20% perforation ratio, and a 1.0 m cavity depth. On the east façade, the strongest performance is achieved with a 150 mm Jaali, 50% perforation, and a 1.5 m cavity, with cooling demand reduction of up to 8.71%. These findings demonstrate that traditional design elements, when optimised for modern use, can offer measurable energy savings through predictive modelling frameworks. More importantly, their widespread adoption could support urban cooling strategies, reduce peak electricity loads and contribute to sustainable development across rapidly growing cities in hot climates. The comprehensive dataset generated provides a foundation for future AI-enhanced building energy optimisation applications. Full article

Background: Interactive learning resources developed with the H5P platform have been progressively adopted to support autonomous learning and conceptual consolidation. However, empirical evidence regarding their impact on academic performance in theoretically demanding university courses remains limited. The primary aim of this study was to examine the effect of the structured integration of an interactive digital pedagogical resource developed with multiple-choice H5P on the academic performance of higher education students enrolled in a Motor Control course. Methods: A quasi-experimental study was conducted to compare two independent groups: a control group (CG; n = 90) and an intervention group (IG; n = 115), which had access throughout the semester to a multiple-choice interactive resource developed using the H5P platform. Academic performance was operationalized as the score obtained on a written summative assessment. Baseline equivalence between groups was assessed using an initial diagnostic test. Between-group comparisons were performed using robust non-parametric statistical procedures and further examined using a linear regression model adjusted for relevant covariates. Results: No statistically significant differences were found between groups in the baseline diagnostic test (p > 0.05), indicating comparable starting levels. At the end of the intervention period (≈2 months), the intervention group obtained significantly higher scores in the summative assessment (p < 0.001), with a large effect size (d = 0.87). Conclusions: The findings suggest that the structured integration of multiple-choice H5P resources may positively contribute to academic performance when used as a complementary tool alongside traditional teaching. These results reinforce the pedagogical potential of multiple-choice H5P to support autonomous learning and conceptual consolidation, while also highlighting the need for future research employing more rigorous experimental designs and process-based measures to better understand the underlying learning mechanisms. Full article

This study aims to identify and characterize the financial profiles of tourism-sector firms in Barranquilla through the application of unsupervised Machine Learning techniques, with the purpose of analyzing patterns of financial behavior based on profitability, capital structure, and liquidity. The research adopts a quantitative and descriptive design, using secondary financial data for fiscal year 2024 obtained from the Barranquilla Chamber of Commerce. The initial sample comprised 563 active tourism firms. Based on basic accounting variables, normalized financial indicators were constructed through a feature engineering process that included correlation analysis, variable selection, and robust scaling. A range of clustering algorithms representing different methodological paradigms as partitional, hierarchical, density-based, and probabilistic, were evaluated using a multicriteria validation framework combining internal cluster quality metrics and cluster size balance. The OPTICS algorithm was selected as the most suitable method for the final segmentation. The results revealed two regular financial clusters and a group of atypical firms. One cluster corresponds to firms with no observable financial activity, characterized by zero profitability, absence of leverage, and exclusive reliance on equity financing. The second cluster groups financially active firms exhibiting high indebtedness, low equity participation, negative profitability, and liquidity constraints, reflecting conditions of financial distress. Non-parametric statistical tests confirmed significant differences between clusters, primarily in indicators related to capital structure and profitability, while firm size did not account for the observed segmentation. Overall, the findings demonstrate that behavior-based financial segmentation supported by unsupervised Machine Learning and normalized financial ratios enables the identification of robust and interpretable financial archetypes, with capital structure and profitability emerging as the main differentiating factors. Full article

Urban areas are increasingly exposed to water-related challenges, including flood risk and water scarcity, amplified by climate change, population growth, and extensive soil sealing. Addressing these pressures requires integrated stormwater management (SWM) strategies that balance hydraulic, environmental, and social objectives. This study introduces a novel, replicable Key Performance Indicator (KPI)-based assessment framework for 36 green–blue and grey sustainable stormwater management systems (SWMSs), designed to enable cross-typology, multiscale comparison. Six KPIs, encompassing flood regulation, water consumption, water quality, air quality, environmental amenity, and biodiversity potential, are derived through a critical synthesis and harmonisation of the literature and complemented with new parameters and sub-parameters to address existing methodological gaps. The framework structures evaluations into six analytical tables and one summary table, ensuring transparent, systematic, and comparative assessment of heterogeneous solutions. Application to a pilot project in Rome demonstrates how integrating KPI evaluation with parametric hydraulic modelling provides actionable insights for solution selection. It also facilitates identification of potential synergies between performance dimensions, enhancing its value as a decision-support tool in preliminary design. Overall, the study demonstrates the research value of multi-scalar, performance-based approaches for urban water planning, highlights the transferability of resilient stormwater strategies in climate-sensitive contexts, and identifies promising avenues for future research, including multi-sectoral integration, trade-off analysis, and cross-platform application. Full article

Background/Objectives: Knowledge of plant-based diets is gaining increasing significance in adolescents due to the growing popularity of vegetarian and vegan dietary patterns. To date, there has been limited research examining the level of awareness and understanding of these diets among secondary school students, as well as the factors influencing their knowledge. The aim of the study was to determine the prevalence of plant-based diets and to assess knowledge regarding these dietary patterns among high school students, as well as to identify factors associated with both diet adherence and achieving sufficient nutritional knowledge. Methods: A cross-sectional study was conducted among 341 high school students. Data were collected using a self-administered paper questionnaire that included demographic information, self-reported body weight and height, adherence to plant-based diets, and knowledge of vegetarian and vegan nutrition. Nutritional knowledge was assessed using a structured 19-item questionnaire (25 scorable items) and verified for reliability (test–retest, Krippendorff’s alpha = 0.88). Based on a 25-point scale, a score of >60% (16–25 points) was categorized as ‘sufficient’ knowledge. Statistical analyses included the chi-square test, Mann–Whitney and Kruskal–Wallis non-parametric tests, and multivariable logistic regression to estimate adjusted odds ratios (aOR) for factors associated with sufficient knowledge. Results: The prevalence of plant-based diets in the study group was 16.1% (n = 55), with a significantly higher frequency observed among female students and those with sufficient nutritional knowledge. The majority of students (81.2%) achieved sufficient knowledge. Higher scores were observed among female students, those in higher grade levels, and those individuals adhering to plant-based diets (p < 0.05). Multivariate regression analysis indicated that male sex (aOR = 0.38 compared to females), higher grade level (aOR = 3.66 for grade 3 vs. grade 1; aOR = 3.62 for grade 4 vs. grade 1), residence in a rural area (aOR = 0.50), and non-adherence to a plant-based diet (aOR = 0.32) were independently associated with sufficient knowledge. Conclusions: The majority of high school students demonstrate sufficient knowledge regarding plant-based diets, with significant variations associated with sex, grade level, place of residence, and experience with plant-based diets. These findings underscore the need for targeted educational interventions, particularly among male students, those in lower grade levels, and individuals residing in rural areas. Full article

Achieving a balance between accuracy and computational efficiency in solar energy flux estimation models remains a key challenge in atmospheric radiative transfer research. Given the high computational cost of spectral models, a widely used simplification strategy consists of parameterizing atmospheric spectral transmittances through wavelength-averaging formulations. This study introduces a Clear-Sky Multivariable (CSMV) broadband parametric model derived from the Leckner spectral model for estimating the three components of solar irradiance under clear-sky conditions: direct normal irradiance (DNI), diffuse irradiance (Gd), and global irradiance (G). The model development follows a two-stage procedure. First, discrete broadband transmittances are obtained by applying an independent spectral integration scheme to the transmittances of the source spectral model. In the second stage, these discrete values are fitted with analytical functions expressed solely in terms of atmospheric state parameters, yielding wavelength-independent broadband formulations. While the overall development framework follows a classical parameterization approach, the calculation of the diffuse component introduces a novel way of estimating the fraction of aerosol scattering directed toward the ground. The model was tested against data collected from eight radiometric stations distributed across six continents and benchmarked against two well-established reference models. Overall, the results indicate a high level of accuracy and demonstrate the practical applicability of the model. Full article

This article investigates the response of an unprotected three-storey steel moment-resisting frame subjected to a suite of horizontally traveling fire scenarios. A series of multi-step finite-element simulations was conducted to analyze the impact of traveling fires on both the global and local responses of a low-rise building frame. The research considers a range of fire types, both uniform and spatially varying, as well as different locations, and sizes to capture a diverse array of fire scenarios. Non-uniform compartment fires are modeled using the improved traveling fire method (iTFM), while uniform fires are simulated using the Eurocode parametric (EC) fire model. Four traveling fire scenarios with floor area coverage ranging from 5% to 48% are examined. The resulting deformation patterns, along with bending moment and axial force distributions in critical beam and column sections within the fire compartments, are thoroughly evaluated. The findings reveal that, within the case study frame and the range of parametric analyses, a uniform compartment fire does not necessarily yield the worst-case scenario commonly assumed in design codes. Instead, global and local structural responses are primarily influenced by traveling fire scenarios. Full article

This paper presents a theoretical approach based on the FSDT to study the acoustic vibration performance of rib-stiffened PVC foam sandwich structures with reinforcing and weakening phases when submerged in water. The complex core layer with reinforcing and weakening phases is homogenized to an equivalent orthotropic layer. Building upon this framework, the governing equations of motion for rib-stiffened PVC foam sandwich structures under the boundary conditions of a simply supported type are derived, incorporating the coupling interaction between the reinforcing ribs and the sandwich plates. Considering the influence of the underwater environment, with the Helmholtz equation governing the continuity of the acoustic pressure field and the Euler equation regulating the fluid–structure interaction interface continuity, the Navier method is subsequently employed to solve for the natural frequencies and acoustic vibration responses. For the purpose of verifying the proposed approach, the predicted results are contrasted with both the literature-derived data and numerical simulation results. Finally, parametric research is further conducted to explore the effect of the parameters of the rib and core layers on the underwater acoustic vibration characteristics. The conclusions drawn from this study can provide meaningful guidance for engineering design and optimization of such rib-stiffened sandwich structures, incorporating both reinforcing and weakening phases in underwater engineering applications. Full article

Distance higher education places increased demands on instructors’ emotional and communicative competencies, as teaching and interaction occur in technologically mediated environments. This study examines the role of teachers’ emotional intelligence, empathy, and communication-related competencies in distance higher education, with particular emphasis on emotional management and instructor well-being. A quantitative research design was employed, using self-report instruments administered to higher education instructors engaged in distance teaching. Non-parametric statistical analyses revealed strong internal coherence among emotional intelligence dimensions and a pattern of functional empathy characterized by high perspective taking and low personal distress. Self-perceived communication was found to be consistent across interactional contexts, indicating a stable communicative disposition. Most notably, emotional management emerged as a key factor associated with positive work-related emotions among instructors. The findings highlight emotional management as a critical mechanism supporting both teaching effectiveness and emotional sustainability in online learning environments. The study contributes to the literature by integrating emotional intelligence, empathy, and self-perceived communication within a unified empirical framework and offers practical implications for professional development and institutional support in distance higher education. Full article

The construction sector contributes to global CO₂ emissions and resource consumption, highlighting the need for sustainable design strategies. In this context, building envelope performance plays a key role, supported by digital technologies. This study proposes an automated BIM-MCDM workflow to select the optimal wall stratigraphy with Aerogel, EPS, and Rock Wool thermal insulation layers. The evaluation indicators are organized into three thematic clusters: Thermal Performance (TPI), Environmental Sustainability (ESI), and Economic Indicators (EI). Insulation alternatives and indicators are modeled in Autodesk Revit, enabling parametric variation in insulation layers and generating multiple stratigraphic configurations. Performance indicators are automatically calculated through a BIM-VPL integration using Dynamo, Microsoft Excel, and Tally. Fully interoperable parametric scripts enable data extraction from the BIM model, regulatory compliance verification, and the transfer of results back to the BIM model. Finally, indicator values are weighted and evaluated using an MCDM analysis based on the AHP method, fully implemented in Dynamo. The results indicate that EPS ranks first due to its strong performance in TPI and ESI, followed by Aerogel, influenced by EI, and Rock Wool, which shows a lower contribution to ESI. This research contributes to data-driven decision-making and the digitalization of sustainability-oriented performance assessment for building envelopes. Full article

With the rapid urbanization in China, the spatial interaction between newly constructed underground structures and existing transportation tunnels has become increasingly frequent and complex. However, studies on the dynamic response characteristics of underground pedestrian passages subjected to the combined effects of metro- and vehicle-induced vibrations remain relatively limited. This study takes the newly constructed underground pedestrian passage at Want Want Hospital in Hunan Province as the engineering background. The pedestrian passage features a unique structural configuration, in which it is jointly constructed with an overlying vehicular tunnel through a shared slab and simultaneously crosses above an existing metro tunnel. To explore the vibration research methods for this unique structure, a three-dimensional finite element model was developed using ABAQUS and validated through in situ vibration measurements. Based on the validated model, the dynamic response of the pedestrian passage was systematically investigated from two perspectives: traffic loading conditions and shared slab thickness. The results show that metro-induced loads dominate the vibration response of the pedestrian passage. Bidirectional (reversible) train operation produces significantly greater vibration levels than unidirectional operation, and the Z-direction vibration level increases with train speed, with local exceedances occurring at 80 km/h. Under vehicle loading, the vibration response of the passage exhibits a non-monotonic trend, first increasing and then decreasing within the speed range of 30–40 km/h. When metro and vehicle loads act simultaneously, the vibration level is further amplified and exceeds the allowable limit. In addition, a pronounced vibration energy concentration zone is identified on the pedestrian passage bottom slab directly beneath the tunnel sidewalls, highlighting the necessity for targeted vibration mitigation in this region. Parametric analysis demonstrates that appropriately increasing the thickness of the vehicular tunnel bottom slab does not effectively reduce the vibration response. The findings of this study provide a reliable numerical analysis framework and practical design guidance for vibration control of complex overlapping underground structures in urban environments. Full article

Additive manufacturing in construction is expanding production possibilities for housing, however its integration into architectural design workflows remains limited. This research proposes a computational workflow for the early-stage form-finding of housing volumes intended for additive construction. A parametric design system was developed to generate a wide range of residential volumetric configurations based on geometric parameters derived from conventional housing typologies and emerging 3D-printed construction practices. The design space was explored through user-driven experimentation and automated evolutionary optimization targeting predefined surface area conditions. Besides design alternatives were visualized using AI-assisted image generation to support comparative evaluation, translated into BIM models for further architectural development, and tested through physical 3D-printed scale models to assess material expression and constructability. Five design exploration activities involving architects and graduate students produced nearly 200 volumetric alternatives, in order to review its use and possibilities. The results show that the parametric system enables efficient exploration of both conventional and novel housing forms potentially compatible with additive construction. Vertically articulated volumes with curved envelopes and spatial variation emerged as promising alternatives. The study demonstrates the potential of integrating parametric modeling, evolutionary search, AI-assisted visualization, and physical prototyping to support architectural decision-making and facilitate the incorporation of 3D printing into housing design processes. Full article