This study to examine associations between cardiorespiratory fitness (CRF), 24-hour movement components, and cardiometabolic risk factors in children from southern Brazil, emphasizing the critical variables in these relationships. The sample included 186 schoolchildren (6–11 years, 8.57±1.56). Waist circumference (WC) and CRF were assessed using PROESP-Br protocols, while physical activity (moderate to vigorous–MVPA, and light–LPA) was measured via accelerometers. Sleep and screen time were reported by parents, and fasting blood samples provided data on triglycerides, HDL cholesterol, glucose, insulin, and HOMA-IR. Network analysis highlight WC, systolic blood pressure, and MVPA as central variables with significant connectivity. MVPA emerged as central among 24-hour movement behaviors, with CRF playing an intermediary role. Results underscore WC and MVPA’s relationship on cardiometabolic health, supporting interventions targeting MVPA to prevent early cardiometabolic risks in children.

Metallic nanoparticles with virucidal properties dispersed in a polymeric matrix have gained prominence in the scientific community as a rapid and effective alternative that employs the additive manufacturing (AM) or 3D printing method. This study aims to produce filaments for 3D printing using polymer nanocomposites based on polylactic acid (PLA) and copper nanoparticles (CuNPs) in different proportions. The virucidal activity of various proportions of nanoparticles in PLA was investigated. The composites were produced following a mixture design (DOE) with concentrations ranging from 1% to 2% copper nanoparticles, which were blended with PLA using a single-screw extruder. The samples were characterized by thermogravimetry (TG), differential scanning calorimetry (DSC), tensile strength testing, and fracture analysis using scanning electron microscopy (SEM). A thermal analysis of the composites indicated that the CuNPs contributed to an increase in the degradation temperature and crystallization of the PLA. Sample S7 (1.25% of CuNPs) exhibited a 4% increase in the degradation temperature compared to pure PLA. The best tensile strength results were observed in sample S7 (1.25% of CuNPs), 30% more than sample S3 (1.33% of CuNPs) due to good material cohesion, as evidenced by microscopy analyses. Regarding virucidal analyses, most composites demonstrated virus inhibition activity.

Determining a fair trading price is challenging, and this complexity is further heightened in power systems as the price must consider network constraints, fluctuating and endogenous electricity prices, and generation cost. This paper proposes a novel Nash-in-Stackelberg model designed to coordinate a collection of independently operated microgrids. Within this framework, the microgrids engage in a bargaining game to collectively decide a fair trading price as well as other operational decisions. We use the Nash bargaining solution (NBS) to model this interaction. Microgrids’ trading decisions impact the locational marginal prices of the main power grid. Hence, a Stackelberg game is used to determine these prices. The Stackelberg model considers microgrids as leaders (upper-level problem) and the independent system operator as follower (lower-level problem). The NBS guarantees a fair allocation of the generated profit based on individual characteristics of the microgrids. In specific, in scenarios of higher generation, we achieve a cost reduction of $884 and $904 per microgrid compared with a grand coalition where only one microgrid receives the total cost reduction ($1788). Also we noticed that increasing the amount of solar-generated electricity reduces the nodal price in 1.53% and consequently the trading price in 1.27%.

The implementation of UAVs (unmanned aerial vehicles) as an operational tool in the AECO (architecture, engineering, construction, operation) sector has significantly changed structural inspection tasks. To harness the potential of cutting-edge technology, this research compared the performance of conventional and immersive drone technology (FPV (first-person view) goggles and motion control) in simulated scenarios. 28 engineering students participated in two activities that recreated realistic structural inspection environments: detecting structural anomalies and flying through an aerial obstacle course. The results showed that the immersive drone outperformed the conventional drone in terms of efficiency and effectiveness, yielding more findings, fewer collisions and more accurate flight paths. Suggesting that the learning curve of the immersive interface provided advantages in control and spatial perception tasks, projecting its potential benefits for the industry.

In medium- and low-voltage three-phase distribution networks, the load imbalance among the phases may compromise the network voltage symmetry. Inverter-interfaced distributed energy resources (DERs) can contribute to compensating for such imbalances by sharing the required negative sequence current while providing active power synchronized with the positive sequence voltage. However, positive and negative sequences are conventionally defined in a steady state and are not directly observed from the instantaneous voltage and current measurements at the DER unit’s point of connection. In this article, an estimation algorithm for sequence separation based on the Kalman filter is proposed. Furthermore, the proposed filter uses a complex vector representation of the asymmetric three-phase signals in synchronous coordinates to allow for the implementation of the Kalman filter in its stationary form, resulting in a simple dynamic filter able to estimate positive and negative sequences even during transient operation. The proposed stationary complex Kalman filter performs better than state-of-the-art techniques like DSOGI and very similarly to other Kalman filter implementations found in the literature but at a fraction of its computational cost (23.5%).

Construction remains one of the most hazardous industries, with high accident rates driven by insufficient planning, coordination, and safety training. While extended reality (XR) technologies, encompassing virtual, augmented, and mixed reality, have shown promise in improving safety outcomes, existing applications are typically isolated, lacking integration across the project lifecycle and alignment with digital methodologies such as those found in Construction 4.0. This study proposes a comprehensive workflow and framework for the integration of XR technologies into construction safety management, grounded in Building Information Modelling, Lean Construction, and Prevention through Design. This methodology structures the use of XR to support safety planning, training, inspection, and control, with a focus on lifecycle integration and proactive risk mitigation. Implementation examples are presented to illustrate the framework’s applicability and scalability. These demonstrate how XR can support immersive walkthroughs, synchronisation with BIM data, and simulation of human–machine interactions. This study contributes a structured, replicable approach that addresses the current fragmentation of XR safety applications, offering both a theoretical basis and practical guidance for adopting XR in construction safety workflows.

This paper provides a comprehensive review of Partial Power Converter (PPC) topologies and control methods for fast electric vehicle (EV) charging applications. Partial Power Converters are gaining traction to enhance converter efficiency, reduce power losses, and minimize component sizes by processing only a portion of the total power. This review covers key PPC topologies, including different partial power converters, and highlights their advantages and limitations in the context of EV charging. Various control methods that optimize the performance of these converters are also discussed. The paper presents a comparative analysis between partial power and full power converters. Finally, this review synthesizes the main findings and proposes guidelines for selecting appropriate PPC architectures for future fast EV charging stations.

Main conclusion: This review discusses the molecular modifications of grapevines by arbuscular mycorrhizal fungi, increasing anthocyanins and other phenolic molecules, potentially improving wine quality and plant stress tolerance. Abstract: Grapevines are naturally associated with arbuscular mycorrhizal fungi (AMF). These fungi, as obligate symbionts, are capable of influencing molecular, biochemical, and metabolic pathways, leading to alterations in the concentrations of various molecules within the host plant. Recent studies have addressed the transcriptomic and metabolic modifications triggered by AMF in grapevines. These AMF-induced alterations are involved in cell transport, sugar metabolism, plant defense mechanisms, and increased tolerance to both biotic and abiotic stressors. Notably, the shikimate pathway exhibits heightened activity following AMF inoculation in grapevines, resulting in the accumulation of anthocyanins, flavonols, phenolic acids, and stilbenes. Phenolic compounds are the main metabolites influencing grape and wine quality attributes, such as color, flavor, and potential health benefits. This review aims to provide an updated overview of current research on the transcriptomic and metabolic aspects of AMF–grapevine interactions, focusing on their impact on plant performance and quality traits. Graphic abstract: (Figure presented.)

Information disorder has significant negative impacts on contemporary societies. This study presents a hybrid methodology that combines machine learning and natural language processing to analyze corpora of disinformation texts in Spanish. The approach not only adapts linguistic features originally developed for English to another major but less researched language, but also incorporates 251 features organized into six categories, surpassing previous methods in both the number and organization of features. Applied to the CLNews dataset of Spanish rumors, the analysis identified 17 features with statistically significant differences between false and real rumors. Linguistic analysis reveals that false rumors are characterized by more emotional language, greater sentence fragmentation, frequent use of auxiliary verbs, and lower information density, which creates an appearance of detail. Additionally, using BERT, a large language model (LLM), five topics were identified among false rumors, each exhibiting different strategies in terms of fragmentation, grammatical complexity, and information density. Given the above, linguistic features were employed to develop machine learning classifiers, with a linear SVM achieving 86% accuracy. This methodology offers a replicable framework for future research on disinformation and text analysis in Spanish, enhancing the interpretability of results. The methodology shows that classical machine learning models trained on carefully chosen linguistic features can deliver competitive results, surpassing BETO (57%) and RoBERTa-BNE (64%) in accuracy on the CLNews dataset. Moreover, these models demonstrate strong performance when the same features are applied to a different dataset and continue to perform well when the feature selection is adjusted to fit the new context.

Groundwater is an important resource that can help in climate change adaptation. However, the pollution of these aquifers with nitrate is a widespread problem of growing concern. Biological denitrification using inorganic electron donors shows significant advantages in treating nitrate-polluted groundwater where organic matter presence is negligible. However, mass transfer limitations and secondary contamination seem to be the major hinderance to spread the use of these technologies. This could be solved by the use of bioelectrochemical systems (BES), which emerge as an attractive technology to solve these problems due to the reported low energy demand and high denitrification rates. However, technical and operational issues must be considered to replicate these results at full-scale. This review summarizes the biological basis of autotrophic denitrification and the key aspects of its application in bioelectrochemical systems. In addition, an estimation of the capital costs required for the implementation of a BES considering different population sizes and initial nitrate concentration in the groundwater is made.

Technologies providing flexibility options to power systems, such as Power-To-X (PtX) technologies, have become more important with the increasing deployment of distributed energy resources, particularly microgrids. However, uncertainty in renewable resources creates ambiguity regarding the necessary PtX capacity to install. This paper proposes a two-stage stochastic Stackelberg approach for multi-energy microgrids, focusing on long-term investment decisions in PtX technologies and hourly operational strategies. The Stackelberg problem considers microgrids as leaders (upper level) and the independent system operator as a follower (lower level). In the first stage, investment levels for various PtX technologies are determined as one-time decisions. The second stage focuses on hourly operational decisions, including the integration of microgrids with the independent system operator with marginal endogenous prices. The results provide insights into how uncertainty in renewable generation and electric battery levels affect investment levels. Larger hydrogen and thermal storage volumes lead to more flexible and self-sufficient microgrid systems. In scenarios with higher flexibility, microgrids can: (1) satisfy up to 10% of the independent system operator demand using renewable electricity and (2) regulate supply variability by storing excess generation during peak periods and releasing it during low generation periods.

Intellectual precocity in children poses unique challenges and opportunities for educational systems. This systematic review aims to comprehensively analyze intellectual precocity in children until 6 years old, including its definition, manifestations, and various educational programs for intellectually precocious learners. Following PRISMA guidelines, a comprehensive search of electronic databases was conducted. The study included 26 articles published between 2013 and 2023 that provided a conceptualization of precocity or giftedness, and/or focused on characteristics of precocity, and/or investigated educational programs for intellectually precocious children. The authors’ conceptualizations of precocity varied, with some providing clear definitions based on a developmental view of precocity, while others merely mentioned the concept. Early indicators of superior traits have been observed in areas such as reading, math, problem-solving, and even in fields that have been traditionally disregarded, such as visual arts. Educational provisions varied widely, including approaches based on enrichment and project-based learning; however, interventions based on socioemotional elements are also highlighted. The findings emphasize the importance of early identification and targeted educational strategies to support the unique needs of intellectually precocious individuals. Future research should focus on longitudinal studies and the development of evidence-based interventions.

The construction industry, a cornerstone of global economic growth, continues to struggle with entrenched inefficiencies, including low productivity, cost overruns, and fragmented project delivery. Addressing these persistent challenges requires more than incremental improvements, it demands a strategic unification of Lean Construction, Building Information Modeling (BIM), and Emerging Technologies. This systematic review synthesizes evidence from 64 academic studies to identify the most influential tools, techniques, and methodologies across these domains, revealing both their individual strengths and untapped synergies. The analysis highlights widely adopted Lean practices such as the Last Planner System (LPS) and Just-In-Time (JIT); BIM capabilities across 3D, 4D, 5D, 6D, and 7D dimensions; and a spectrum of digital innovations including Digital Twins, AR/VR/MR, AI, IoT, robotics, and blockchain. Crucially, the review demonstrates that despite rapid advancements, integration remains sporadic and unstructured, representing a critical research and industry gap. By moving beyond descriptive mapping, this study establishes an essential foundation for the development of robust, adaptable integration frameworks capable of bridging theory and practice. Such frameworks are urgently needed to optimize efficiency, enhance sustainability, and enable innovation in large-scale and complex construction projects, positioning this work as both a scholarly contribution and a practical roadmap for future research and implementation.

The rapid growth of complex textual data in domains such as medicine, law, and science has heightened the relevance of Long Document Summarization (LDS). Effective summarization not only requires advanced techniques but also robust evaluation metrics capable of capturing summary quality, coherence, and factual accuracy. We analyze 113 peer-reviewed studies from last two years, selected through comprehensive searches in SCOPUS, Web of Science, and PubMed, following PRISMA 2020 guidelines. We focus on LDS methods and the metrics used to evaluate them. Results indicate a rising adoption of hybrid models combining extractive and abstractive strategies, frequently powered by deep learning and optimization. Concurrently, evaluation practices have shifted from traditional overlap-based metrics (e.g., ROUGE) toward semantic measures such as BERTScore and MoverScore. However, these metrics still face challenges related to interpretability, domain adaptation, and computational cost. We advocate for the development of holistic, explainable, and reference-free evaluation frameworks aligned with human judgment to enhance the reliability and applicability of LDS systems across domains.

Personal Comfort Systems (PCS) are equipments that heat and/or cool occupants without affecting surrounding environments, ranging from commonly used devices to innovative technologies, and that tend to be controlled by people. These systems aim to address energy consumption and occupant satisfaction issues related to centralised air-conditioning. Although there are systematic studies on these systems, there is a lack of documentation regarding mediation characteristics between people and the built environment. This article presents a systematic review of PCS using a search of academic literature and patents, classifying PCS based on thermal categories and device typologies while introducing post-phenomenological mediation categories. The results show that most PCS fall into the thermal categories of ‘Heating’ and ‘Cooling and ventilation’. The review also presents a view of the PCS territory based on mediation attributes and technological complexity. Finally, the PCS’ characteristics are discussed based on the post-phenomenological concepts of Embodiment, Hermeneutic, and Background providing insights for future research opportunities and PCS development.

This study explores the passengers’ accessibility dilemma in Valparaíso, Chile, through field observations and laboratory experiments. The aim is to investigate the accessibility in metro stations based on the users’ emotional experience. Perceptions were reported through the emotions of passengers according to a circumplex psychological model and an accessibility ranking. Passengers reported their emotions (e.g., stress, sadness, relaxation, and happiness) during different trip moments. Results indicate that rearranging train seats parallel to movement creates a more spacious aisle, enhancing mobility and evoking positive emotions such as happiness. However, an unexpected rise in sadness suggests that social dynamics may influence emotional responses, warranting further investigation. Overcrowding increases stress and sadness, emphasizing the need for capacity management to improve passengers’ emotional experiences. Field observations reveal that early journey stages, such as walking to the station or waiting on the platform, are associated with unpleasant experiences due to poor infrastructure and accessibility barriers. In contrast, train rides foster more positive emotions, credited to better accessibility onboard. Passenger dissatisfaction arises from issues such as elevator malfunctions, inconsistent train schedules, and inadequate station accessibility. This study could help to understand passenger behavior when the accessibility conditions of metro stations and their surroundings are changed. Further studies will expand the concept of emotions by considering social and psychological factors and explore different types of stations and their surroundings considering a larger sample size in laboratory experiments and field studies.

Highly directive antennas may be a key component in millimeter wave links to offset their inherently high path losses. In cluttered scenarios such as Non-Line-Of-Sight (NLOS) indoor settings, antenna gain is degraded by the interaction of the channel angular spread with the antenna pattern. We conducted extensive measurements at 60 GHz indoors to evaluate the effect of angular spread on antenna gain degradation and its relation to small-scale fades. Our empirical results, obtained in corridors using five antennas with azimuthal Half-Power Beam Widths (HPBW) ranging from 6° to 60°, characterize effective gain of antennas in both Line-Of-Sight (LOS) and NLOS conditions. We find that narrow beam antennas can experience substantial gain degradation in NLOS scenarios, up to 4.4 dB at the 90th percentile for a 6° HPBW antenna. Our results confirmed this effect is less severe for wider beam antennas, which will capture a larger proportion of incident energy. We found that a Rician model can explain gain degradation to within a fraction of 1 dB for LOS links. In contrast, for NLOS links, a diffuse model with Gaussian-shaped channel angular spectrum and no dominant components yields better results, with less than 1 dB gap from 10th to 90th percentile between the empirical and simulated CDFs of azimuthal gains. Taking into account the phase profile of the antenna is particularly important when using this model, in line with the hypothesis of constructive/destructive interference of multiple wavefronts in NLOS links.

Acidophiles comprise a group of microorganisms adapted to live in acidic environments. Despite acidophiles are usually associated with an autotrophic metabolism, more than 80 microorganisms capable of utilizing organic matter have been isolated from natural and man-made environments. The ability to reduce soluble and insoluble iron compounds has been described for many of these species and may be harnessed to develop new or improved mining processes when oxidative bioleaching is ineffective. Similarly, as these microorganisms grow in highly acidic media and the chances of contamination are reduced by the low pH, they may be employed to implement robust fermentation processes. By conducting an extensive literature review, this work presents an updated view of basic aspects and technological applications in biomining, bioremediation, fermentation processes aimed at biopolymers production, microbial electrochemical systems, and the potential use of extremozymes.

Carbon fiber-reinforced polymers (CFRP) are widely used composite materials in structural applications, where their mechanical performance is significantly influenced by interfacial shear strength (IFSS). The single fiber fragmentation test (SFFT) is a common technique for characterizing IFSS, but its reliance on optical microscopy makes it time-consuming and impractical for opaque matrices. This study presents an alternative methodology based on acoustic emission (AE) analysis, enabling the estimation of fragment lengths through statistical modeling. The AE technique captures the energy released during fiber fragmentation, represented as AE bursts, whose accurate detection is crucial. A signal-processing approach based on progressive simplification enhances burst detection. To refine the estimation of fragment lengths, a gamma distribution is fitted to experimental data, accounting for observed asymmetry in optical measurements. Results indicate that this approach achieves an IFSS determination error of 14.16% at a 95% confidence level. This study demonstrates the feasibility of using AE for IFSS characterization in SFFT and contributes to future research on AE applications in composite materials.

Background: Active parents may have more active children, as parents act as role models for their children’s physical activity (PA). Parents can facilitate access to PA, provide information, validate physical-sport behaviours, and offer emotional support. Also, the influence of parents’ PA on children’s PA in and out of the school context has not been well-established. Objective: This study aimed to examine the associations between parental PA and the PA levels of their children in both school and out-of-school settings, considering parental sex. Methods: A cross-sectional study was conducted in 2021 involving 1,030 parent-child dyads. Sociodemographic data and self-reported active behaviour measures were administered to both groups simultaneously. Multiple logistic regressions were performed to determine the associations. Results: A positive trend between parental and children’s PA was observed only out of school (Trend OR = 1.55, 95% CI = 1.25–1.95; p < 0.001). Maternal moderate-to-vigorous physical activity (MVPA) of 151–300 min per week was associated with MVPA in children on school days with physical education classes (OR = 3.48; 95% CI, 1.04–12.1). A trend was found in the maternal group for MVPA in children out of school (Trend OR = 1.57 [95% CI = 1.24; 2.01]). Conclusion: Positive associations between MVPA in children and more than 150 min of MVPA per week from parents were found. Also, a trend between maternal PA and their children’s out-of-school MVPA was identified, supporting future initiatives focused on family-based PA interventions.