Search Results (3,773)

The construction sector is undergoing a rapid transition toward more resilient, sustainable, and digitally connected systems, creating increasing demand for materials capable of providing functions beyond conventional structural performance. In this context, smart materials have emerged as promising solutions due to their ability to respond to mechanical, thermal, chemical, or electromagnetic stimuli through adaptive behaviors such as self-healing, structural sensing, energy regulation, vibration control, and reversible deformation. Despite growing scientific interest, available knowledge remains fragmented across specific material families and isolated application domains. Therefore, this study presents a PRISMA-based systematic review of smart materials in construction using peer-reviewed journal literature indexed in Scopus during the 2021–2026 period. The review examines the principal smart material families currently applied in construction, including self-healing concretes, self-sensing cementitious systems, Shape Memory Alloys (SMA), piezoelectric materials, phase change materials, adaptive coatings, conductive nanocomposites, and multifunctional geopolymers. Their engineering functions, structural and architectural applications, reported performance characteristics, sustainability contributions, digital integration potential, and implementation barriers are comparatively discussed and qualitatively synthesized based on the reviewed literature. The findings indicate that smart materials can improve durability, structural health monitoring, seismic resilience, thermal efficiency, lifecycle performance, and carbon reduction when properly integrated into buildings and infrastructure. However, large-scale adoption remains constrained by high initial costs, manufacturing scalability, regulatory uncertainty, long-term durability validation, and limited market confidence. The review further shows that the greatest future potential lies in combining material intelligence with IoT platforms, artificial intelligence, BIM environments, and digital twins. Overall, smart materials are positioned as strategic enablers of next-generation low-carbon, adaptive, and intelligent construction systems. Full article

Vernacular housing in the Andean region embodies long-standing building knowledge, environmental adaptation, and forms of social organization rooted in rural life. Over recent decades, these dwellings have undergone visible transformations linked to migration, changing aspirations, and the growing presence of industrialized construction materials. Rather than disappearing, vernacular forms have increasingly merged with contemporary solutions, producing hybrid architectural landscapes whose local dynamics are still insufficiently documented. This study analyzes the material, typological, and functional transformation of rural housing in Las Lagunas and Quisquinchir, two Indigenous communities located in Saraguro, Loja, Ecuador. A total of 192 houses were recorded through field observation and a structured digital survey implemented with KoBoCollect. The information was processed in R using descriptive statistics, contingency tables, chi-square tests, Cramér’s V, and standardized residual analysis. The findings show that architectural change in both communities does not occur through a simple replacement of traditional housing by modern models. Instead, vernacular, hybrid, and modern/eclectic typologies coexist within the same rural setting, revealing uneven and locally specific processes of transformation. The clearest differences emerge in construction materiality. Las Lagunas preserves a stronger presence of traditional wall systems, especially adobe and bahareque, while Quisquinchir shows a broader incorporation of industrialized materials, particularly concrete block. Statistical analysis confirmed significant associations between community and wall material, as well as between typology and wall material, whereas the relationship between community and architectural typology was comparatively weaker. Functional changes were also identified through the reduction or reconfiguration of intermediate spaces such as portals, patios, and corridors, suggesting a gradual shift toward more enclosed and specialized domestic environments. These results contribute empirical evidence for understanding architectural hybridization in Indigenous rural territories and support conservation and planning approaches capable of recognizing continuity, adaptation, and change within evolving Andean built landscapes. Full article

Emotional well-being has become a central concern in contemporary educational research, particularly in contexts shaped by social and cultural diversity. However, dominant approaches to educational assessment continue to prioritize cognitive outcomes, often overlooking the affective dimensions of children’s everyday experiences. In this context, play emerges as a key yet underexplored process through which emotional well-being is constructed in childhood. This study aimed to analyze the role of play in the configuration of emotional well-being in sociocultural educational contexts from a sociocultural and relational perspective. A qualitative multiple-case study was conducted in two rural schools located in Mapuche territories in southern Chile, involving students, teachers, caregivers, and Mapuche knowledge holders (kimches). Data were generated through semi-structured interviews and focus groups and analyzed using inductive coding procedures supported by qualitative data analysis software. The findings indicate that play operates as a socioemotional ecology through which children participate in collective forms of life, construct relationships, and experience emotional well-being in interaction with others, territory, and culturally meaningful practices. Three interconnected dimensions emerged. First, play was experienced as a relational, territorialized, and culturally situated practice sustained through participation, collective interaction, and intergenerational transmission. Second, emotional well-being emerged through enjoyment, companionship, belonging, and opportunities for social participation. Third, well-being appeared as a situated experience dependent on access to meaningful spaces, material conditions, cultural repertoires, and opportunities for play. Participants also identified tensions associated with technological change, the reduction in free play opportunities, and transformations in community life, while highlighting the potential role of schools in revitalizing culturally significant play practices such as palín and linao. These findings suggest that emotional well-being is not simply an individual psychological state but a relational and sociocultural accomplishment emerging through participation in meaningful play practices. The study contributes to interdisciplinary debates on childhood, emotional well-being, intercultural education, and sociocultural approaches to development by proposing the concept of play as a socioemotional ecology. Full article

Floods remain among the most devastating natural disasters globally, disproportionately impacting low-resource regions where real-time flood forecasting is constrained by limited computational infrastructure and the scarcity of fine-resolution predictive models. Although state-of-the-art global climate models achieve high predictive accuracy, their scale and computational complexity restrict their applicability in localized and resource-constrained settings. This study proposes a deep climate model distillation framework that transfers knowledge from a high-capacity Fourier Neural Operator (FNO)-based global climate model inspired by FourCastNet into lightweight, regionally adaptive student networks suitable for edge deployment. The framework combines climate variables, satellite observations, and hydrological measurements to improve localized flood prediction. Knowledge transfer is achieved through a multi-objective distillation strategy that combines supervised learning, soft-target alignment, and intermediate feature matching. Experimental evaluation across multiple flood-prone regions in Sub-Saharan Africa and South Asia shows that the distilled student model achieves an average classification accuracy of 0.89, an AUC of 0.91, and an F1-score of 0.88, retaining approximately 96.7% of the teacher model’s predictive performance. In continuous discharge estimation, the model attains a mean absolute error of 0.17, RMSE of 0.24, and an R² score of 0.85. The proposed distillation approach yields an 8× reduction in inference latency and over a 20× reduction in model size, enabling real-time execution on low-power edge devices such as the Raspberry Pi 4 and NVIDIA Jetson Nano. The student model further demonstrates robust regional and temporal generalization, with limited performance degradation in unseen geographic areas and during extreme flood years. Full article

Edge vision systems require convolutional neural networks (CNNs) that preserve recognition accuracy under strict storage, computation, and latency constraints. Although ResNet18 is a compact residual backbone, direct deployment on resource-constrained devices remains costly, whereas simple channel reduction weakens representation capacity. This study aims to build a deployable ResNet18-based classifier that reduces model complexity while recovering the accuracy lost during compression. We propose a lightweight framework that combines global channel scaling, a re-parameterized attention residual block, and teacher–student knowledge distillation. The proposed block uses multi-branch convolution and squeeze-and-excitation attention during training, then folds the linear branches into a single 3-by-3 convolution for inference. Experiments on CIFAR-100 show that the final model reduces parameters from 11.220 M to 2.841 M, retains comparable Top-1 accuracy (0.7579 vs. 0.7606), improves Top-5 accuracy (0.9340 vs. 0.9253), and reduces graphics processing unit (GPU) batch inference latency from 3.279 ms to 2.161 ms. Deployment on PYNQ-Z2 verifies the complete camera-based CPU-side inference workflow, with an average end-to-end latency of 421.467 ms/frame. The results indicate that residual topology preservation, re-parameterized feature enhancement, and distillation form a practical route for edge-oriented lightweight CNN deployment. Full article

Purpose: To evaluate the effectiveness of serious games, including virtual reality-based interventions, in improving clinical skills acquisition among undergraduate and postgraduate health science students. Methods: This systematic review was prospectively registered in PROSPERO (CRD42024589035) and conducted in accordance with PRISMA 2020 guidelines. PubMed, Scopus, Web of Science, and ScienceDirect were searched from inception to 31 August 2025. Eligible studies examined serious games, simulation-based platforms, or immersive and non-immersive virtual reality interventions designed to support clinical skills development. Outcomes were classified using a predefined hierarchical framework aligned with Miller’s pyramid, distinguishing performance-based clinical competence, clinical reasoning, and secondary educational outcomes. Owing to substantial heterogeneity in interventions, comparators, and assessment methods, a narrative synthesis was performed. Results: Thirteen studies involving 892 participants were included. Serious games and virtual reality-based interventions were associated with generally favorable outcomes for knowledge acquisition, self-efficacy, motivation, satisfaction, and anxiety reduction. Improvements in clinical reasoning were reported in several studies, and some studies demonstrated benefits in performance-based clinical competence, particularly in simulation and virtual reality settings. However, findings for objective performance-based outcomes were mixed, with some studies reporting no statistically significant between-group differences. Heterogeneity in outcome definitions and limited reporting of standardized effect sizes reduced cross-study comparability. Conclusions: Serious games, including virtual reality-based interventions, may serve as complementary, scenario-based learning strategies in health sciences education. The most consistent effects were observed for cognitive and learner-centered outcomes, whereas evidence for objective gains in performance-based clinical competence remains variable. Further high-quality studies using standardized outcome frameworks, validated performance-based assessments, effect sizes, confidence intervals, and longer follow-up are needed. Full article

Human activities and economic development require large amounts of water and energy. The analysis of the nexus between water and energy flows can improve the understanding of the quantitative relationship between the two resources and guide actions and policies to obtain better results with lower risks. This article aimed to analyse and evaluate the use of rainwater in urban environments and its relationship with the water–energy nexus through a literature review. The PRISMA guidelines were used to structure the research, and the RStudio programme was used for the bibliometric analysis. A total of 118 articles published between 2013 and 2023 were identified in the Scopus and Web of Science databases, of which 30 met the eligibility criteria and were included in the review. The risk of bias in the studies included was assessed by two independent reviewers, and disagreements were resolved by consensus. The results were synthesized in a narrative and descriptive way, and organized in a table containing the authors, year, country, and main findings. The studies were grouped according to the theme addressed and the results related to the use of rainwater and the water–energy nexus were compared. The results indicate that the main use of rainwater is for non-drinkable purposes, to reduce the demand for potable water, lessen the pressure on water resources and contribute to environmental sustainability. Climate change can affect rainfall regimes and, consequently, the feasibility of systems. By decentralizing water supply services, the use of rainwater can save drinking water. When assessing energy savings, the use of rainwater is not always the best option, as system configurations and pump specifications are determining factors. Regarding the environmental impacts, all stages of the urban water cycle consume energy for their operation, and the environmental impact is directly related to the energy source used. Policies and regulations focused on rational use, water conservation, demand reduction, and tax incentives for the installation of rainwater harvesting systems, together with awareness campaigns, are necessary for the widespread adoption of rainwater harvesting systems. Finally, there is consensus regarding saving drinking water, but there is still a lack of studies and specifications regarding energy savings. The findings highlight the need for future longitudinal and simulation-based studies to strengthen knowledge of water–energy nexus dynamics in buildings. Full article

Background/Objectives: In interceptive sports like volleyball, the ability to accurately time an action relative to a moving object (Coincidence Anticipation Timing—CAT) is critical. This study investigated the effects of a structured 8-week deliberate practice intervention on CAT accuracy and its long-term retention in young female athletes. Methods: Thirty-two female volleyball players (aged 8–10 years) were randomly assigned to an Experimental Group (EG, n = 16) and a Control Group (CG, n = 16). The EG underwent a specialized 8-week training program focusing on progressive cognitive load and immediate knowledge of results, while the CG followed standard volleyball training. A single-blind assessor measured CAT at two velocities (5 mph and 10 mph) using the Bassin Anticipation Timer at three time points: pre-test, post-test, and a 2-month retention test. Results: ANCOVA revealed a significant group-by-time interaction (p < 0.001), with the EG demonstrating a substantial reduction in absolute timing error. The effect size was markedly higher at 10 mph (partial η² = 0.400) compared to 5 mph (partial η² = 0.197). Crucially, the EG maintained their performance gains during the retention test (p < 0.05), whereas the CG showed no significant improvement over time. Conclusions: Targeted deliberate practice effectively enhances temporal prediction accuracy in children, likely by facilitating a shift from reactive to predictive motor control. The robust retention of these skills underscores the significant neuroplasticity of the 8–10 age window, suggesting that early foundational timing interventions provide long-lasting benefits for athletic development. Full article

The synergistic transition toward digital transformation and green development has been widely regarded as a core pathway to achieving sustainable development in knowledge production. Using balanced panel data from 39 economies covering 2018–2024, this study employed a two-way fixed-effects model to examine the associations of the energy efficiency of digital infrastructure and the energy structure with carbon intensity (CI). The findings showed that: (1) Reductions in Power Usage Effectiveness (PUE) values were significantly associated with higher macro-level CI (coefficient = −2.1564, p < 0.05), which is consistent with the possibility of a rebound effect in the digital sector. Further, time-series discontinuity tests further suggested that the surge in AI computing power, especially in 2023–2024, may have coincided with a structural shift in this relationship (Chow test, p < 0.05). (2) A Panel Threshold Regression (PTR) identified an optimal renewable energy threshold at 59.82%. Crucially, the carbon rebound effect remained highly significant across both high and low green power regimes, demonstrating that supply-side energy transition alone cannot fully absorb the exponential carbon footprint of digital expansion. Furthermore, Instrumental Variable (IV-2SLS) and Placebo Break Tests confirmed the strict validity of these findings. (3) The emission-reduction benefits related to digital knowledge spillovers appeared to be subject to time lags and a possible energy lock in effect, while current environmental policies and carbon pricing mechanisms appear to impose insufficient constraints. This study provides a crucial quantitative framework for monitoring and evaluating the environmental sustainability of the ICT sector. By highlighting the limitations of pure supply-side greening and the necessity of absolute carbon caps, our findings offer integrated policy approaches to align the exponential growth of Generative AI with global sustainable development goals. Full article

Background: Critical illness leads to profound metabolic, neuroendocrine and immune disorders that affect the prognosis of patients treated in intensive care units (ICUs). The ketogenic diet, a high-fat and low-carbohydrate eating model, is gaining increasing importance as a potential metabolic intervention in the ICU. Preliminary data suggest that the ketogenic diet (KD) may support the control of seizures in a super-refractive epileptic state (SRSE), stabilize glycemia, reduce insulin demand, and modulate the immune response in sepsis. The aim of this review was to present a synthetic presentation of the current state of knowledge regarding use of the KD in intensive care patients. Methods: The review was carried out in accordance with the guidelines of the Joanna Briggs Institute and PRISMA-ScR. PubMed, Scopus, EBSCO, Web of Science, Google Scholar and Cochrane Library databases were searched (10–19 April 2026) using the Population–Concept–Context model. Full-text observational studies, randomized trials and reviews of the use of KDs in ICU patients were included. Data extraction was performed independently by two reviewers. Results: Of the 42 publications identified, seven studies were included in the analysis. The KD was feasible and safe in both critically ill adults and children. In SRSE, most patients achieved stable ketosis within a few days, which often allowed for reduction or discontinuation of anesthetics. In sepsis, the KD led to glycemic stabilization, reduced insulin demand and reduced immune deregulation; in one study, “after day 4, none of the patients in the KD group required insulin treatment.” The KD also showed beneficial effects on cellular bioenergetics and mitochondrial function. The safety profile was acceptable and adverse reactions were manageable with appropriate monitoring. Conclusions: The KD represents a promising, non-pharmacological metabolic intervention in intensive care, particularly in the treatment of SRSE and in the stabilization of glucose metabolism in sepsis and other critical conditions. Despite the growing number of positive clinical observations, the available evidence remains limited due to small samples, heterogeneous protocols, and a lack of randomized trials. Further, well-designed prospective studies are needed to determine optimal KD implementation protocols and identify the patient populations that benefit most. Full article

Opioid misuse continues to be a major public health issue in the United States. Older adults (≥65) are at particular risk of harm from opioids due to changes in opioid pharmacokinetics with age; however, healthcare professionals lack training and confidence in addressing opioid harm reduction strategies in this population. Therefore, the purpose of this study was to improve healthcare professional knowledge and beliefs regarding opioid harm reduction strategies amongst older adults. An 8 h interprofessional conference was conducted 1 May 2025 to educate healthcare providers about opioid misuse prevention strategies for older adults. This study utilized a quasi-experimental one-group pretest–posttest design to assess changes in healthcare professional knowledge and beliefs before and after the conference. Healthcare professionals in the U.S. were recruited to participate in the conference via email listservs with national reach, predominantly concentrated in Alabama. Data were collected at pre- and post-conference via an anonymous online survey informed by the Theory of Planned Behavior and Health Belief Model. Primary outcome measures included: (1) knowledge of opioid use and misuse in older adults (5 items); (2) prescribing and dispensing attitudes surrounding opioids and medications for opioid use disorder (MOUD) (5 items); (3) perceived susceptibility to harm from opioids (4 items); and (4) perceived barriers to opioid harm reduction in older adults (17-items). Constructs were measured using multiple-choice questions (knowledge) and Likert-type scales (1 = strongly disagree, 5 = strongly agree). Secondarily, intention to join a Microsoft Teams working group for ongoing collaboration was assessed through a single categorical (Yes/No/Unsure) multiple-choice question at post-conference. Data were analyzed using descriptive statistics, and differences in mean knowledge, attitudes, susceptibility, and barriers scale scores from pre- to post-conference were analyzed using Wilcoxon signed-rank tests (alpha = 0.05). Of N = 75 survey respondents, the majority were White (86.7%), female (74.7%), 50 years of age on average, and employed as pharmacists (68%). Overall, mean (SD) knowledge (83.73% [19.92] versus 90.67% [12.45]; p = 0.011) and perceived susceptibility (3.82 [0.63] versus 4.03 [0.63]; p = 0.002) increased from pre- to post-conference, while perceived barriers decreased (2.71 [0.54] versus 2.54 [0.58]; p = 0.001). Despite an upward trend, there was no statistically significant change in the mean prescribing and dispensing attitudes from baseline to post-conference. Additionally, 34.7% intended to join the Microsoft Teams working group at post-conference. Findings support the utility of interprofessional educational interventions to increase healthcare provider knowledge and beliefs regarding opioid harm reduction strategies amongst older adults. Full article

Accurately tracking the spatial and temporal variations of water vapor is indispensable for weather forecasting and climate adaptation, yet remains challenging due to the sparse coverage and discontinuity of ground-based observations. Satellite remote sensing, particularly from geostationary satellites like Meteosat Third Generation Imager-1 (MTG-I1), offers continuous, high-resolution data. To the best of our knowledge, MTG-I1 is the first geostationary satellite equipped with a near-infrared (NIR) spectral band specifically designed for detecting water vapor. To address the lack of precipitable water vapor (PWV) data derived from the Flexible Combined Imager (FCI) onboard MTG-I1, a novel semi-empirical (SE) algorithm optimized for PWV retrieval is proposed. Validation against ground-based PWV measurements using an initial test set and a temporally independent test set yielded relative errors of no more than 0.10, indicating stable retrieval performance outside the model-development period. The FCI-derived PWV retrievals were also more accurate than the corresponding MODIS PWV data. Compared to the traditional radiative transfer model (RTM)-based retrieval method, the SE method shows greater adaptability to systematic differences between the observed and RTM-simulated FCI reflectance. After correcting for radiometric degradation, the RTM-based algorithm achieves a 41% reduction in absolute error and a 47% reduction in relative error, bringing its accuracy in line with the SE algorithm. Overall, the proposed SE algorithm demonstrates superior robustness and adaptability, and can provide more reliable remote sensing PWV data to support weather forecasting and climate research. Full article

This study addresses the critical challenge of food waste in the hospitality sector, directly contributing to Sustainable Development Goal (SDG) 12.3. We conducted an intervention at a community-based culinary innovation center involving 18 participants. The research integrated the Collaborative System Model (CSM)—a framework that facilitates multi-stakeholder co-creation through knowledge interaction and feedback loops—into a Participatory Design (PD) process. Results demonstrated that the intervention reduced fruit waste mass by 72% per session and increased byproduct reuse rates from 15% to 68%. Sensory evaluations confirmed that these waste-reduction practices did not compromise product quality (p > 0.05). This approach provides a behavior-anchored unit process for pre-consumer waste reporting. Full article

Brown macroalgae are a promising substrate for alginate production, yet the conventional acid–alkali route raises environmental and quality concerns due to its high reagent inventory, large saline effluents, and partial depolymerization of the polymer backbone. To address these limitations, we evaluated five extraction strategies on a single Saccharina latissima feedstock: conventional acid–alkali extraction as the reference, enzymatic hydrolysis (HE), extrusion combined with enzymatic hydrolysis (Ex-HE), sonication combined with enzymatic hydrolysis (S-HE), and the sequential combination of extrusion, sonication, and enzymatic hydrolysis (Ex-S-HE). The optimized HE process achieved an alginate yield of 34.08% on dry biomass. This value exceeds the conventional benchmark of 31.08%. Hydrolysis time and biomass loading governed the yield. Enzyme dose showed no significant effect within the studied range. Sonication alone yielded 14.55% under surface-limited kinetics, driven exclusively by acoustic amplitude. Scale-up of HE to a 150 L pilot bioreactor recovered 43% of total soluble solids through lyophilization. Ethanol precipitation at the 5 L scale delivered 26.87% of purified alginate. The two metrics describe distinct end products. They represent complementary outputs of a cascade biorefinery rather than competing routes. The HE-derived alginate matches commercial standards by FTIR, TGA, and viscosity. Its M/G ratio is expected to fall within the published range for S. latissima alginate (1.4 to 1.8). Ethanol precipitation of brown algal hydrolysates typically yields products with 80 to 95% uronic acid content. Quantitative techno-economic and environmental analysis indicates substantial reductions in CO₂-equivalent emissions and E-factor relative to the conventional route. Total cost becomes competitive when the cascade biorefinery is monetized through co-products such as mannitol, laminarin, and phlorotannins. These results position enzymatic hydrolysis as the most effective single-step strategy for alginate recovery from S. latissima. To our knowledge, this is the first study to couple face-centred central composite optimization of two pretreatment families on a single S. latissima biomass batch with a 30-fold pilot-scale validation from 5 L to 150 L and a comparative functional characterization of two recovery methods (ethanol precipitation and lyophilization). Full article

Acute ischemic stroke is one of the leading causes of mortality and disability globally, characterized by a complex and temporally structured cascade of cellular and molecular events. Although reperfusion therapies have improved outcomes, their narrow therapeutic window and limited availability leave many patients without effective treatment, highlighting the need for effective neuroprotective strategies capable of targeting multiple interconnected pathways. Melatonin has been proposed as a potential adjunctive neuroprotective agent based on its pleiotropic properties, modulating cellular signaling networks including antioxidant, anti-inflammatory, mitochondrial stabilizing, and BBB-preserving effects. Melatonin regulates key signaling pathways, thereby coordinating cellular responses to injury in multiple stages of ischemic pathophysiology, positioning it as a potential adjunctive therapy. Preclinical studies consistently demonstrate reductions in infarct volume, preservation of neuronal architecture, and improvements in neurological outcomes. However, clinical evidence remains limited to a small number of clinical trials, which suggest safety and possible early neurological benefit but are underpowered to determine long-term efficacy. Importantly, translational gaps persist regarding optimal dosing, duration of administration, and alignment with the temporal dynamics of post-ischemic injury. This review integrates current knowledge on the cellular and molecular mechanisms underlying the potential neuroprotective actions and its role as a pleiotropic modulator of ischemic injury. Full article