Search Results (4,095)

Enhancing the real-world performance of sustainably designed and certified green buildings remains a significant challenge, particularly in hot climates where efforts to improve thermal comfort often conflict with energy efficiency goals. In the United Arab Emirates (UAE), even newly constructed facilities with green building certifications present opportunities for retrofitting and performance optimization. This study investigates the energy and thermal comfort performance of a LEED Gold-certified, mixed-use university campus in Dubai through a calibrated digital twin developed using IES thermal modelling software. The analysis evaluated existing sustainable design strategies alongside three retrofit energy conservation measures (ECMs): (1) improved building envelope U-values, (2) installation of additional daylight sensors, and (3) optimization of fan coil unit efficiency. Simulation results demonstrated that the three ECMs collectively achieved a total reduction of 15% in annual energy consumption. Thermal comfort was assessed using operative temperature distributions, Predicted Mean Vote (PMV), and Predicted Percentage of Dissatisfaction (PPD) metrics. While fan coil optimization yielded the highest energy savings, it led to less favorable comfort outcomes. In contrast, enhancing envelope U-values maintained indoor conditions consistently within ASHRAE-recommended comfort zones. To further support energy reduction and progress toward Net Zero targets, the study also evaluated the integration of a 228.87 kW rooftop solar photovoltaic (PV) system, which offset 8.09% of the campus’s annual energy demand. By applying data-driven thermal modelling to assess retrofit impacts on both energy performance and occupant comfort in a certified green building, this study addresses a critical gap in the literature and offers a replicable framework for advancing building performance in hot climate regions. Full article

Background: School-based tobacco control policies are critical for preventing youth tobacco use. While many districts adopt formal policies to create smoke- and vape-free environments, the degree to which these policies are enforced at the school level may vary, influencing their effectiveness. Little is known about how consistently such policies are implemented across schools within urban school districts. Objectives: This study aimed to examine the existence and enforcement of school-level tobacco control policies in an urban public school system, using Baltimore City schools as a case example. Methods: We conducted a survey of school personnel from 20 high schools in Baltimore City in 2024. The survey instrument assessed the presence and enforcement of policies related to tobacco use prevention, communication, signage, disciplinary actions, and institutional support. Descriptive statistics (frequencies and percentages) were used to summarize responses. Spearman correlations were also used for bivariate correlations. Additional school-level and neighborhood-level contextual data were collected from the internet (neighborhood socioeconomic status and school performance). Results: While many policies existed across the 20 participating schools, their enforcement was widely inconsistent. Most schools reported the existence of policies prohibiting tobacco use in school buildings (60%) and vehicles (55%). However, few schools had visible tobacco-free signage (35%) or offered cessation programs (15%). Communication of policies to students (70%) and staff (65%) was the most commonly enforced aspect of tobacco control policies. Conclusions: Findings suggest that while tobacco control policies may be adopted across urban school systems, their enforcement at the school level remains uneven. Greater attention may be needed to support policy implementation and to reduce variability in school-level practices. Baltimore City serves as a useful case study to understand these challenges and identify opportunities for strengthening school-based tobacco prevention efforts. Full article

Green buildings are recognised for their potential to reduce energy consumption, minimise environmental impact, and improve occupants’ well-being, benefits that are especially critical in rapidly urbanising regions. However, questions remain about whether these buildings fully meet occupant comfort expectations while delivering energy efficiency. This is particularly relevant in Africa, where climate conditions and energy infrastructure challenges make sustainable building operation essential. Although interest in sustainable construction has increased, limited research has examined the real-world performance of green buildings in Africa. This study helps address that gap by evaluating indoor thermal comfort in a green-certified office building and two conventional office buildings in Abuja, Nigeria, through post-occupancy evaluation (POE). The Predicted Mean Vote (PMV) and Thermal Sensation Vote (TSV) were used to assess comfort, revealing discrepancies between predicted and actual occupant responses. In the green building, PMV indicated near-neutral conditions (0.28), yet occupants reported a slightly cool sensation (TSV: −1.1). Neutral temperature analysis showed that the TSV-based neutral temperature (26.5 °C) was 2.2 °C higher than the operative temperature (24.3 °C), suggesting overcooling. These findings highlight the importance of incorporating occupant feedback into HVAC control. Aligning cooling setpoints with comfort preferences could improve satisfaction and reduce unnecessary cooling, promoting energy-efficient building operation. Full article

Dynamic and Adaptive solar systems demonstrate a greater potential to enhance the satisfaction of occupants, in terms of indoor environment quality and the energy efficiency of the buildings, than conventional shading solutions. This study has evaluated Dynamic and Adaptive Photovoltaic Shading Systems (DAPVSSs) through a comprehensive analysis of six shading designs in which their energy production and the comfort of occupants were considered. Energy generation, thermal comfort, daylight, and glare control have been assessed in this study, considering multiple orientations throughout the seasons, and a variety of tools, such as Rhino 6.0, Grasshopper, ClimateStudio 2.1, and Ladybug, have been exploited for these purposes. The results showed that the prototypes that were geometrically more complex, designs 5 and 6 in particular, had approximately 485 kWh higher energy production and energy savings for cooling and 48% better glare control than the other simplified configurations while maintaining the minimum daylight as the threshold (min DF: 2%) due to adaptive and control methodologies. Design 6 demonstrated optimal balanced performance for all the aforementioned criteria, achieving 587 kWh/year energy production while maintaining the daylight factor within the 2.1–2.9% optimal range and ensuring visual comfort compliance during 94% of occupied hours. This research has established a framework that can be used to make well-informed design decisions that could balance energy production, occupants’ wellbeing, and architectural integration, while advancing sustainable building envelope technologies. Full article

This study investigated the nuanced influence of urban morphology on the thermal performance of nine mass housing blocks (21–26, 28–30) in New Belgrade’s Central Zone. These blocks, showcasing diverse structures, provided a robust basis for evaluating the design parameters. ENVI-met simulations were used to assess two scenarios: an “asphalt-only” environment, isolating the urban structure’s impact, and a “real-world” scenario, including green infrastructure (GI). Overall, the findings emphasize that while GI offers mitigation, the inherent urban built structure fundamentally determines thermal outcomes. An urban block’s thermal performance, it turns out, is a complex interplay between morphological factors and local climate. Crucially, simple metrics like Green Area Percentage (GAP) and Building Coverage Ratio (BCR) proved unreliable predictors of thermal performance. This highlights the critical need for urban planning regulations to evolve beyond basic surface indicators and embrace sophisticated, context-sensitive design principles for effective heat mitigation. Optimal performance arises from morphologies that actively manage heat accumulation and facilitate its dissipation, a characteristic exemplified by Block 22’s integrated design. However, even the best-performing Block 22 remains warmer compared to denser central areas, suggesting that urban densification can be a strategy for heat mitigation. Given New Belgrade’s blocks are protected heritage, targeted GI reinforcements remain the only viable approach for improving the outdoor thermal comfort. Full article

Adversarial attacks in Natural Language Processing (NLP) present a critical challenge, particularly in sentiment analysis, where subtle input modifications can significantly alter model predictions. In search of more robust defenses against adversarial attacks on sentimental analysis, this research work introduces two novel defense mechanisms: the Lexicon-Based Random Substitute Model (LRSM) and the Word-Variant Voting Model (WVVM). LRSM employs randomized substitutions from a dataset-specific lexicon to generate diverse input variations, disrupting adversarial strategies by introducing unpredictability. Unlike traditional defenses requiring synonym dictionaries or precomputed semantic relationships, LRSM directly substitutes words with random lexicon alternatives, reducing overhead while maintaining robustness. Notably, LRSM not only neutralizes adversarial perturbations but occasionally surpasses the original accuracy by correcting inherent model misclassifications. Building on LRSM, WVVM integrates LRSM, Frequency-Guided Word Substitution (FGWS), and Synonym Random Substitution and Voting (RS&V) in an ensemble framework that adaptively combines their outputs. Logistic Regression (LR) emerged as the optimal ensemble configuration, leveraging its regularization parameters to balance the contributions of individual defenses. WVVM consistently outperformed standalone defenses, demonstrating superior restored accuracy and F1 scores across adversarial scenarios. The proposed defenses were evaluated on two well-known sentiment analysis benchmarks: the IMDB Sentiment Dataset and the Yelp Polarity Dataset. The IMDB dataset, comprising 50,000 labeled movie reviews, and the Yelp Polarity dataset, containing labeled business reviews, provided diverse linguistic challenges for assessing adversarial robustness. Both datasets were tested using 4000 adversarial examples generated by established attacks, including Probability Weighted Word Saliency, TextFooler, and BERT-based Adversarial Examples. WVVM and LRSM demonstrated superior performance in restoring accuracy and F1 scores across both datasets, with WVVM excelling through its ensemble learning framework. LRSM improved restored accuracy from 75.66% to 83.7% when compared to the second-best individual model, RS&V, while the Support Vector Classifier WVVM variation further improved restored accuracy to 93.17%. Logistic Regression WVVM achieved an F1 score of 86.26% compared to 76.80% for RS&V. These findings establish LRSM and WVVM as robust frameworks for defending against adversarial text attacks in sentiment analysis. Full article

This study investigates the effectiveness of passive design in low-rise residential buildings located in arid desert climates, using the Dubai Solar Decathlon Middle East (SDME) competition as a case study. This full-scale experiment offers a unique opportunity to evaluate design solutions under controlled, realistic conditions; prescriptive, modeled performance; and monitored performance assessments. The prescriptive assessment reviews geometry, orientation, envelope thermal properties, and shading. Most houses adopt compact forms, with envelope-to-volume and envelope-to-floor area ratios averaging 1 and 3.7, respectively, and window-to-wall ratios of approximately 17%, favoring north-facing openings to optimize daylight while reducing heat gain. Shading is strategically applied, horizontal on south façades and vertical on east and west. The thermal properties significantly exceed the local code requirements, with wall performance up to 80% better than that mandated. The modeled assessment uses Building Energy Models (BEMs) to simulate the impact of prescriptive measures on energy performance. Three variations are applied: assigning minimum local code requirements to all the houses to isolate the geometry (baseline); removing shading; and applying actual envelope properties. Geometry alone accounts for up to 60% of the variation in cooling intensity; shading reduces loads by 6.5%, and enhanced envelopes lower demand by 14%. The monitored assessment uses contest-period data. Indoor temperatures remain stable (22–25 °C) despite outdoor fluctuations. Energy use confirms that houses with good designs and airtightness have lower cooling loads. Airtightness varies widely (avg. 14.5 m³/h/m²), with some well-designed houses underperforming due to construction flaws. These findings highlight the critical role of passive design as the first layer for improving the energy performance of the built environment and advancing toward net-zero targets, specifically in arid desert climates. Full article

Artificial intelligence has taken a seat at the executive table and is threatening the fact that human beings are the only ones who should be in a position of power. This article gives conjectures on the future of leadership in which managers will collaborate with learning algorithms in the Neural Adaptive Artificial Intelligence Leadership Model, which is informed by the transformational literature on leadership and socio-technical systems, as well as the literature on algorithmic governance. We assessed the model with thirty in-depth interviews, system-level traces of behavior, and a verified survey, and we explored six hypotheses that relate to algorithmic delegation and ethical oversight, as well as human judgment versus machine insight in terms of agility and performance. We discovered that decisions are made quicker, change is more effective, and interaction is more vivid where agile practices and good digital understanding exist, and statistical tests propose that human flexibility and definite governance augment those benefits as well. It is single-industry research that contains self-reported measures, which causes research to be limited to other industries that contain more objective measures. Practitioners are provided with a practical playbook on how to make algorithmic jobs meaningful, introduce moral fail-safes, and build learning feedback to ensure people and machines are kept in line. Socially, the practice is capable of minimizing bias and establishing inclusion by visualizing accountability in the code and practice. Filling the gap between the theory of leadership and the reality of algorithms, the study provides a model of intelligent systems leading in organizations that can be reproduced. Full article

This study synthesizes the rapidly expanding evidence on how digital technologies reshape international trade, with a particular focus on small and medium-sized enterprises (SMEs). Guided by two research questions—(RQ1) How do digital tools influence the volume and composition of cross-border trade? and (RQ2) How do these effects vary by countries’ development level and firm size?—we conducted a PRISMA-compliant systematic literature review covering 2010–2024. Searches across eight major databases yielded 1857 records; after duplicate removal, title/abstract screening, full-text assessment, and Mixed Methods Appraisal Tool (MMAT 2018) quality checks, 86 peer-reviewed English-language studies were retained. Findings reveal three dominant technology clusters: (1) e-commerce platforms and cloud services, (2) IoT-enabled supply chain solutions, and (3) emerging AI analytics. E-commerce and cloud adoption consistently raise export intensity—doubling it for digitally mature SMEs—while AI applications are the fastest-growing research strand, particularly in East Asia and Northern Europe. However, benefits are uneven: firms in low-infrastructure settings face higher fixed digital costs, and cybersecurity and regulatory fragmentation remain pervasive obstacles. By integrating trade economics with development and SME internationalization studies, this review offers the first holistic framework that links national digital infrastructure and policy support to firm-level export performance. It shows that the trade-enhancing effects of digitalization are contingent on robust broadband penetration, affordable cloud access, and harmonized data-governance regimes. Policymakers should, therefore, prioritize inclusive digital-readiness programs, while business leaders should invest in complementary capabilities—data analytics, cyber-risk management, and cross-border e-logistics—to fully capture digital trade gains. This balanced perspective advances theory and practice on building resilient, equitable digital trade ecosystems. Full article

Satellite communications are pivotal to global Internet access, connectivity, and the advancement of information warfare. Despite these importance, the open nature of satellite channels makes them vulnerable to eavesdropping, making the enhancement of interception resistance in satellite communications a critical issue in both academic and industrial circles. Within the realm of satellite communications, polarization modulation and quadrature techniques are essential for information transmission and interference suppression. To boost electromagnetic countermeasures in complex battlefield scenarios, this paper integrates multi-parameter weighted-type fractional Fourier transform (MP-WFRFT) with directional modulation (DM) algorithms, building upon polarization techniques. Initially, the operational mechanisms of the polarization-amplitude-phase modulation (PAPM), MP-WFRFT, and DM algorithms are elucidated. Secondly, it introduces a novel variable polarization-amplitude-phase modulation (VPAPM) scheme that integrates variable polarization with amplitude-phase modulation. Subsequently, leveraging the VPAPM modulation scheme, an exploration of the anti-interception capabilities of MP-WFRFT through parameter adjustment is presented. Rooted in an in-depth analysis of simulation data, the anti-scanning capabilities of MP-WFRFT are assessed in terms of scale vectors in the horizontal and vertical direction. Finally, exploiting the potential of the robust anti-scanning capabilities of MP-WFRFT and the directional property of antenna arrays in DM, the paper proposes a secure transmission technique employing directional variable polarization modulation with MP-WFRFT. The performance simulation analysis demonstrates that the integration of MP-WFRFT and DM significantly outperforms individual secure transmission methods, improving anti-interception performance by at least an order of magnitude at signal-to-noise ratios above 10 dB. Consequently, this approach exhibits considerable potential and engineering significance for its application within satellite communication systems. Full article

The integration of Life Cycle Assessment (LCA) into Building Information Modeling (BIM) processes is becoming increasingly important for enhancing the environmental performance of construction projects. This scoping review examines how LCA methods and environmental data are currently integrated into BIM workflows, focusing on automation, data standardization, and visualization strategies. We selected 43 peer-reviewed studies (January 2010–May 2025) via structured searches in five major academic databases. The review identifies five main types of BIM–LCA integration workflows; the most common approach involves exporting quantity data from BIM models to external LCA tools. More recent studies explore the use of artificial intelligence for improving automation and accuracy in data mapping between BIM objects and LCA databases. Key challenges include inconsistent levels of data granularity, a lack of harmonized EPD formats, and limited interoperability between BIM and LCA software environments. Visualization methods such as color-coded 3D models are used to support early-stage decision-making, although uncertainty representation remains limited. To address these issues, future research should focus on standardizing EPD data structures, enriching BIM objects with validated environmental information, and developing explainable AI solutions for automated classification and matching. These advancements would improve the reliability and usability of LCA in BIM-based design, contributing to more informed decisions in sustainable construction. Full article

The dimensional accuracy of the intaglio surface of complete dentures fabricated using liquid crystal display (LCD) three-dimensional (3D) printing might be influenced by the build angle and post-processing storage conditions. This study evaluated the effect of build angle and natural light exposure duration on the intaglio surface trueness of maxillary complete denture bases. Standardized denture base designs (2 mm uniform thickness) were fabricated using an LCD 3D printer (Lilivis Print; Huvitz, Seoul, Republic of Korea) at build angles of 0°, 45°, and 90° (n = 7 per group). All specimens were printed using the same photopolymer resin (Tera Harz Denture; Graphy, Seoul, Republic of Korea) and identical printing parameters, followed by ultrasonic cleaning and ultraviolet post-curing. Specimens were stored under controlled light-emitting diode lighting and exposed to natural light (400–800 lux) for 0, 14, or 30 days. The intaglio surfaces were scanned and superimposed on the original design data, following the International Organization for Standardization 12836. Quantitative assessment included root mean square deviation, mean deviation, and tolerance percentage. Statistical analyses were performed using one-way analysis of variance and paired t-tests (α = 0.05). Build angle and light exposure duration significantly affected surface trueness (p < 0.05). The 90° build angle group exhibited the highest accuracy and dimensional stability, while the 0° group showed the greatest deviations (p < 0.05). These findings underscore the importance of optimizing build orientation and storage conditions in denture 3D printing. Full article

Educational buildings, including schools, nurseries and universities, face stricter regulation and design control on indoor air quality (IAQ) and thermal conditions than other built environments, as these may affect children’s health and wellbeing. In this scoping review, wide-ranging health, performance, and absenteeism consequences of poor—and benefits of good—IAQ and thermal conditions are evaluated, focusing on source control, ventilation and air purification interventions. Economic impacts of interventions in educational buildings have been evaluated to enable the assessment of tangible building-related costs and savings, alongside less easily quantifiable improvements in educational attainment and reduced healthcare. Key recommendations are provided to assist decision makers in pathways to provide clean air, at an optimal temperature for students’ learning and health outcomes. Although the role of educational buildings can be challenging to isolate from other socio-economic confounders, secondary short- and long-term impacts on attainment and absenteeism have been demonstrated from the health effects associated with various pollutants. Sometimes overlooked, source control and repairing existing damage can be important cost-effective methods in minimising generation and preventing ingress of pollutants. Existing ventilation standards are often not met, even when mechanical and hybrid ventilation systems are already in place, but can often be achieved with a fraction of a typical school budget through operational and maintenance improvements, and small-scale air-cleaning and ventilation technologies, where necessary. Full article

Accurate prediction of landslide-induced displacement is essential for the structural integrity and operational safety of buildings and infrastructure situated in geologically unstable regions. This study introduces a novel hybrid predictive framework that synergistically integrates Gaussian Process Regression (GPR) with Temporal Convolutional Neural Networks (TCNs), herein referred to as the GTCN model, to forecast displacement at building monitoring points subject to landslide activity. The proposed methodology is validated using time-series monitoring data collected from the slope adjacent to the Zhongliang Reservoir in Wuxi County, Chongqing, an area where slope instability poses a significant threat to nearby structural assets. Experimental results demonstrate the GTCN model’s superior predictive performance, particularly under challenging conditions of incomplete or sparsely sampled data. The model proves highly effective in accurately characterizing both abrupt fluctuations within the displacement time series and capturing long-term deformation trends. Furthermore, the GTCN framework outperforms comparative hybrid models based on Gated Recurrent Units (GRUs) and GPR, with its advantage being especially pronounced in data-limited scenarios. It also exhibits enhanced capability for temporal feature extraction relative to conventional imputation-based forecasting strategies like forward-filling. By effectively modeling both nonlinear trends and uncertainty within displacement sequences, the GTCN framework offers a robust and scalable solution for landslide-related risk assessment and early warning applications. Its applicability to building safety monitoring underscores its potential contribution to geotechnical hazard mitigation and resilient infrastructure management. Full article

Background: Soft tissue sarcomas (STSs) are a rare and heterogeneous group of mesenchymal tumors with limited response to current therapies, particularly in advanced stages. STS tumors were traditionally considered “cold” tumors, characterized by limited immune infiltration and low immunogenicity. However, emerging evidence is challenging this perception, highlighting a potentially critical role for the immune system in STS biology. Objective: Building on our previous findings suggesting impaired natural killer (NK) cell activity in STS patients, we aimed to perform an in-depth characterization of peripheral NK cells in STS. Methods: Peripheral blood samples from STS patients and sex- and age-matched healthy donors were analyzed to assess NK cell degranulation, IFNγ production, and receptor repertoire. Results: Functional assays revealed a notable reduction in both degranulation and IFNγ production in NK cells from STS patients. STS patients also exhibited dysregulated expression of activating and inhibitory NK cell receptors. Principal component analysis (PCA) identified CD27 and NKp44 as critical markers for distinguishing STS patients from healthy donors. Increased CD27 expression represents a shift towards a more regulatory NK cell phenotype, and we found that CD27 expression was negatively correlated with NK cell degranulation and IFNγ production. ROC curve analysis demonstrated strong potential to distinguish between the groups for both CD27 (AUC = 0.85) and NKp44 (AUC = 0.94). Conclusion: In conclusion, STS patients exhibited impaired NK cell function, altered receptor repertoire, and a shift towards a less cytotoxic and more regulatory phenotype. Full article