Search Results (673)

Mixed structures with lightweight steel added stories are particularly vulnerable to damage and failure at the joints during seismic events. To evaluate the secondary seismic behavior of the joints in lightweight steel added stories after seismic damage repair, a low-cycle load test was conducted in this study. Following the initial damage, carbon fiber-reinforced polymer (CFRP) was applied for reinforcement, along with epoxy resin for the repair of concrete cracks. The experimental analysis focused on the structural deformation, failure characteristics, and energy dissipation capacity in both the original and repaired joint states. On the basis of the experimental findings, finite element analysis was carried out to examine the influence of varying CFRP layer configurations on the seismic performance of the repaired joints. The results revealed a significant change in the damage pattern of the repaired specimen, shifting from secondary surface damage to significant concrete deterioration localized at the bottom of the column. The failure mechanism was characterized by the CFRP-induced tensile forces acting on the concrete at the column base, following considerable deformation at the beam’s end. When compared to the original joint, the repaired joints exhibited markedly improved performance, with a 33% increase in horizontal ultimate strength and an 85% increase in energy dissipation capacity at failure. Additionally, the rotation angle between the beams and columns was effectively controlled. Joints repaired with two layers of CFRP demonstrated superior performance in contrast to those with a single layer. However, once the repaired joints met the required strength, further increasing the number of CFRP layers had a minimal influence on the mechanical properties of the joints. The proposed CFRP-based seismic retrofit method, which accounts for the strength degradation of concrete in damaged joints due to earthquake-induced damage, has proven to be both feasible and straightforward, offering an easily implementable solution to improve the seismic behavior of structures. Full article

Accurate forecasting of residential heating loads is crucial for guiding heating system control strategies and improving energy efficiency. In recent years, research on heating load forecasting has primarily focused on continuous district heating systems, and it often struggles to cope with the abrupt load fluctuations and irregular on/off schedules encountered in intermittent heating scenarios. To address these challenges, this study proposes a hybrid convolutional long short-term memory (ConvLSTM) model that replaces the conventional batch normalization layer with a Dynamic Tanh (DyT) activation function, enabling dynamic feature scaling and enhancing responsiveness to sudden load spikes. An improved channel–temporal attention mechanism, CBAM(T), is further incorporated to deeply capture the spatiotemporal relationships in multidimensional data and effectively handle the uncertainty of heating start–stop events. Using data from two heating seasons for households in a residential community in Dalian, China, we validate the performance of ConvLSTM-DyT-CBAM(T). The results show that the proposed model achieves the best predictive accuracy and strong generalization, confirming its effectiveness for intermittent heating load forecasting and highlighting its significance for guiding demand-responsive heating control strategies and for energy saving and emissions reduction. Full article

The increasing frequency and intensity of wildfires pose severe risks to ecosystems, infrastructure, and human safety. In wildland–urban interface (WUI) areas, nearby vegetation strongly influences building ignition risk through flame contact and radiant heat exposure. However, limited research has leveraged Unmanned Aerial Systems (UAS) remote sensing (RS) to capture species-specific vegetation geometry and predict thermal responses during ignition events This study proposes a two-stage framework integrating UAS-based multispectral (MS) imagery, LiDAR data, and Fire Dynamics Simulator (FDS) modeling to estimate the maximum temperature (T) and heat flux (HF) of outdoor vegetation, focusing on Syzygium smithii (Lilly Pilly). The study data was collected at a plant nursery at Queensland, Australia. A total of 72 commercially available outdoor vegetation samples were classified into 11 classes based on pixel counts. In the first stage, ensemble learning and watershed segmentation were employed to segment target vegetation patches. Vegetation UAS-LiDAR point cloud delineation was performed using Raycloudtools, then projected onto a 2D raster to generate instance ID maps. The delineated point clouds associated with the target vegetation were filtered using georeferenced vegetation patches. In the second stage, cone-shaped synthetic models of Lilly Pilly were simulated in FDS, and the resulting data from the sensor grid placed near the vegetation in the simulation environment were used to train an XGBoost model to predict T and HF based on vegetation height (H) and crown diameter (D). The point cloud delineation successfully extracted all Lilly Pilly vegetation within the test region. The thermal response prediction model demonstrated high accuracy, achieving an RMSE of 0.0547 °C and R² of 0.9971 for T, and an RMSE of 0.1372 kW/m² with an R² of 0.9933 for HF. This study demonstrates the framework’s feasibility using a single vegetation species under controlled ignition simulation conditions and establishes a scalable foundation for extending its applicability to diverse vegetation types and environmental conditions. Full article

This study focuses on the cooperative formation control problem of six-degree-of-freedom (6-DOF) fixed-wing unmanned aerial vehicles (UAVs) under constraints of limited communication resources and strict time requirements. The core innovation of the proposed framework lies in the deep integration of a dynamic self-triggered communication mechanism (DSTCM) with a prescribed-time control strategy. Furthermore, a fuzzy control strategy is designed to effectively suppress system disturbances, enhancing the robustness of the formation. The designed DSTCM not only retains the adaptive triggering threshold characteristic of dynamic event-triggered communication, significantly reducing communication frequency, but also completely eliminates the need for continuous state monitoring required by traditional event-triggered mechanisms. As a result, both communication and onboard computational resources are effectively conserved. In parallel, a novel time-varying unilateral constrained performance function is introduced to construct a prescribed-time controller, which guarantees that the formation tracking error converges to a predefined residual set within a user-specified time. The convergence process is independent of initial conditions and strictly adheres to full-state constraints. A rigorous Lyapunov-based stability analysis demonstrates that all signals in the closed-loop UAV velocity and attitude system are semi-globally uniformly ultimately bounded (SGUUB). Furthermore, the proposed DSTCM ensures the existence of a strictly positive lower bound on the inter-event triggering intervals of the UAVs, thereby avoiding the occurrence of Zeno behavior. Numerical simulation results are provided to verify the effectiveness and superiority of the proposed control scheme. Full article

The rising urbanization and climate change have increased pluvial flood risks, especially in highly urbanized areas. This study focuses on the Lake Ganzirri area in Messina, Italy, where street-level floods have raised concerns for infrastructure resilience and public safety. This study aims to explore how to effectively represent key urban features, emphasizing buildings and low-impact development/sustainable urban drainage systems (LID/SUDS). For the buildings, a combination of referred approaches to represent buildings is compared against the widely used method to represent buildings as voids in a 2D mesh, ignoring them in the water balance calculations. For the LID/SUDS control elements, a 2D representation is presented and compared against the widely used 1D approach to model such elements. The study uses three well-known software packages—EPA-SWMM 5.2, HEC-RAS 6.2, and InfoWorks ICM 2021.9—applied to the Lake Ganzirri area, to explore the representation of buildings using the building void method (available in InfoWorks ICM 2021.9) against the proposed method (in HEC-RAS 6.2) to replicate runoff flow over a 2D model of a highly urbanized area. From scenario S0, three more scenarios were derived: S1 (S0 with pluvial drainage network), S2 (S1 with LID/SUDS control elements), and S3 (S0 with 2D representation of LID/SUDS), which were then compared against using four comparison schemes. Results show that the proposed method for representing buildings computed the propagation of the runoff comparable to when the building void method is used, with some shortcomings regarding mesh adjustments and computational times. Regarding the 2D representation of LID/SUDS, the effects were unperceivable on water depth maps (reduction in water depths of 1.5 mm on average for all the rainfall events). Still, they were reflected in the increase of 62% of the infiltration volume on average of all the rainfall scenarios and a decrease of 9.1% of water flowing outside the 2D area, therefore replicating the effect of capturing water. Full article

The integration of distributed energy resources into distribution networks creates operational challenges, including voltage instability and power quality issues. While battery energy storage systems (BESSs) can address these challenges, research has focused primarily on transmission-level applications or single services. This paper bridges this gap through a comprehensive review of BESS technologies and control strategies for multi-service ancillary support in distribution networks. Real-world case studies demonstrate BESS effectiveness: Hydro-Québec’s $1.2$ MW system maintained voltage within 5% and responded to frequency events in under 10 ms; Germany’s hybrid 5 MW M5BAT project optimized multiple battery chemistries for different services; and South Africa’s Eskom deployment improved renewable hosting capacity by 15–70% using modular BESS units. The analysis reveals grid-forming inverters and hierarchical control architectures as critical enablers, with model predictive control optimizing performance and droop control ensuring robustness. However, challenges like battery degradation, regulatory barriers, and high costs persist. This paper identifies future research directions in degradation-aware dispatch, cyber-resilient control, and market-based valuation of BESS flexibility services. By combining theoretical analysis with empirical results from international deployments, this study provides utilities and policymakers with actionable insights for implementing BESS in modern distribution grids. Full article

Traditional centralized highway energy systems exhibit significant resilience shortcomings in the face of climate change mitigation requirements and increasingly frequent extreme weather events. Meanwhile, prevailing microgrid control strategies remain predominantly focused on economic optimization under normal conditions, lacking the flexibility to address dynamic risks or the interdependencies between transportation and power systems. This study proposes an adaptive, risk-driven control framework that holistically coordinates power generation infrastructures, microgrids, demand-side loads, energy storage systems, and transport dynamics through continuous risk assessment. This enables the system to dynamically shift operational priorities—from cost-efficiency in stable periods to robustness during emergencies. A multi-objective optimization model is established, integrating infrastructure resilience, operational costs, and traffic impacts. It is solved using an enhanced evolutionary algorithm that combines the non-dominated sorting genetic algorithm II with differential evolution (NSGA-II-DE). Extensive simulations under extreme weather scenarios validate the framework’s ability to autonomously reconfigure operations, achieving 92.5% renewable energy utilization under low-risk conditions while elevating critical load assurance to 98.8% under high-risk scenarios. This strategy provides both theoretical and technical guarantees for securing highway renewable energy system operations. Full article

High photovoltaic (PV) penetration challenges grid frequency stability due to reduced system inertia. Virtual Synchronous Generators (VSGs), particularly when paired with Battery Energy Storage Systems (BESSs), can mitigate this by emulating synchronous machine dynamics. This study focuses on improving frequency response during PV power reductions through the adaptive tuning of an extensive set of VSG parameters. A double-phase Supervisory Controller is developed: in the first phase, Particle Swarm Optimization (PSO) computes multiple sets of optimal VSG parameters for various PV curtailment and load demand change scenarios; in the second phase, the system determines the most appropriate parameters based on current operating conditions to minimize frequency deviations, using the first phase as a foundation for adaptive decision making. The proposed Supervisory Controller reduced the Integral of the Absolute Error (IAE) of 151.55% in the case of a 65% irradiance drop. At 55%, the IAE decreased from 0.4605 to 0.2227, and at 25% from 0.0791 to 0.0546. In the low-disturbance scenario at a 25% drop, the IAE was maintained below 0.06. Supervisory Controller performance led to a reduced settling time and improved frequency recovery. These results demonstrate that the Supervisory Controller improves frequency regulation in both mild and severe irradiance reduction events. Full article

Background/Objectives: Outpatient stroke rehabilitation is expanding as inpatient episodes shorten. Virtual reality (VR) exergaming can extend practice and standardize progression, but setting-specific effectiveness and implementation factors remain unclear. This scoping review mapped VR exergaming in outpatient stroke care and identified technology typologies and functional outcomes. Methods: Guided by the JBI Manual and PRISMA-ScR, searches of MEDLINE, Embase, CENTRAL, Scopus, and Web of Science were conducted in April 2025. The study included adults post-stroke undergoing VR exergaming programs with movement tracking delivered in clinic-based outpatient or home-based outpatient settings. Interventions focused on functional rehabilitation using interactive VR. Results: Sixty-six studies met the criteria, forty-four clinic-based and twenty-two home-based. Serious games accounted for 65% of interventions and commercial exergames for 35%. Superiority on a prespecified functional endpoint was reported in 41% of trials, 29% showed within-group improvement only, and 30% found no between-group difference; effects were more consistent in supervised clinic programs than in home-based implementations. Signals were most consistent for commercial off-the-shelf and camera-based systems. Gloves or haptics and locomotor platforms were promising but less studied. Head-mounted display interventions showed mixed findings. Adherence was generally high, and adverse events were infrequent and mild. Conclusions: VR exergaming appears clinically viable for outpatient stroke rehabilitation, with the most consistent gains in supervised clinic-based programs; home-based effects are more variable and sensitive to dose and supervision. Future work should compare platform types by therapeutic goal; embed mechanistic measures; strengthen home delivery with dose control and remote supervision; and standardize the reporting of fidelity, adherence, and cost. Full article

Fine particulate matter (PM_2.5; aerodynamic diameter ≤ 2.5 µm) remains a challenging policy for industrialized coastal regions throughout East Asia. In this study, we present a multi-year chemical characterization of PM_2.5 and identify key factors contributing to extreme pollution events in Dangjin, a heavy-industry hub on Korea’s west coast. Between August 2020 and March 2024, 24-h gravimetric filters (up to n = 245; 127–280 valid analyses depending on constituent) were collected twice weekly in winter–spring and weekly in summer–autumn. Meteorological data and 48-h backward HYSPLIT trajectories guided source interpretation. The mean PM_2.5 concentration was 26.22 ± 15.29 µg/m³ (4.74–95.31 µg/m³). The mass was highest in winter (30.83 µg/m³). Secondary inorganic ions constituted 60.3% of the aerosol, with nitrate comprising 29.7%. A nitrate-to-sulfate ratio of 1.94 indicated a stronger influence from mobile NO_x emissions compared to that from coal combustion. The trajectory analysis showed north-easterly transport from Eastern China, followed by local stagnation, which promoted rapid ammonium-nitrate formation. Regional transport contributes to severe PM_2.5 episodes, with their magnitude increased by local NO_x and NH₃ emissions. Our findings suggest that effective mitigation strategies in coastal industrial corridors require coordinated control of long-range transport and domestic measures focused on vehicles and ammonia-rich industries. Full article

This study investigates the use of wheat straw ash (WSA) as a sustainable supplementary cementitious material, focusing on its mechanical performance optimization and environmental implications. WSA (ASTM C618, Class F), produced via controlled calcination at 700 °C, was used to replace cement at 2.5, 5, 7.5, 10% by mass. The optimal performance was observed at 5% substitution, achieving a 90-day compressive strength of 48.42 MPa (+4.7%) and a 28-day flexural strength of 7.93 MPa (+6.6%). To contextualize these findings, a multi-technique analytical approach was employed, including scanning electron microscopy (SEM), X-ray diffraction (XRD), thermogravimetric analysis (TGA), Fourier-transform infrared spectroscopy (FT-IR), and ultrasonic pulse velocity (UPV). These methods confirmed that WSA enhances portlandite consumption through pozzolanic reactivity and improves matrix densification via secondary C-S-H gel formation. Additionally, satellite (Sentinel-5P) and ground-based measurements during a severe stubble fire event in Diyarbakir (20–24 June 2024) documented a fourfold increase in PM₁₀ concentrations (157 μg/m³ compared to the June average of ≈35 μg/m³), alongside 23% and 41% rises in NO₂ and SO₂ levels, respectively. These findings demonstrate that wheat straw ash utilization can mitigate agricultural waste burning, improve air quality, and reduce the carbon footprint of cement production. The study highlights WSA’s potential as a high-performance, eco-efficient construction material aligned with circular economy principles. Full article

Clopidogrel is widely used as an antiplatelet therapy for acute coronary syndrome (ACS) patients undergoing percutaneous coronary intervention (PCI). Genetic factors influence variability in clopidogrel response, with non-functional CYP2C19 alleles increasing the risk of major adverse cardiovascular events (MACEs). While CYP2C19 genotype-guided therapy after PCI improves outcomes, MACEs persist at variable rates. Pharmacogenomics (PGx) has primarily focused on genes related to drug metabolism, but therapeutic failure may stem from individual disease predisposition. This study aims to identify novel genetic variants underlying adverse events after PCI despite PGx-guided therapy. A custom sequencing panel was analyzed in 244 ACS-PCI-stent patients and 99 controls without cardiovascular (CV) disease. Association analysis was performed independent of treatment and by prescribed treatment (clopidogrel or prasugrel), complemented by random forest models to predict risk during antiplatelet therapy. No polymorphism reached genomic significance, but in clopidogrel-treated patients, rs2472434 in ABCA1, related to altered lipid metabolism, was strongly associated with secondary CV events (p = 1.7 × 10⁻³). Variants in the clopidogrel pathway, including CYP2C19, ABCB1, and UGT2B7, were also identified and may influence clopidogrel response. Predictive models incorporating these variants effectively discriminated patients with and without events (p = 0.02445). Our findings support combined genotyping of CYP2C19 loss-of-function and ABCB1 C3435T variants to guide antiplatelet therapy and suggest additional targets, such as rs2472434 (ABCA1) and rs7439366 (UGT2B7), to improve risk prediction of adverse CV events. Therefore, the unexplained variability in clopidogrel response may be due to disease pathogenesis itself, highlighting the need for a paradigm shift in PGx studies. Full article

Background/Objectives: Pain neuroscience education (PNE) has demonstrated efficacy in adults with chronic pain, but the pediatric evidence is still developing, despite its increasingly frequent use. Evidence for the effectiveness of PNE in pediatrics remains fragmented across settings and outcomes, which justifies a systematic evaluation focused on children and adolescents. Methods: Following PRISMA, two reviewers independently screened records (PubMed, Web of Science, PEDro; through 21 July 2025), extracted data, and assessed risk of bias (RoB 2 for randomized controlled trials; NIH/CASP for non-randomized studies). Given the heterogeneity, we conducted a structured narrative synthesis (SWiM) and rated the certainty of evidence with GRADE. PROSPERO: CRD420251062922. Results: Eleven studies met the inclusion criteria. PNE consistently improved pain-related knowledge, with effects maintained at follow-up (moderate certainty); effects on pain intensity, function, and emotional outcomes were small and inconsistent (low certainty), with more favorable patterns when PNE was combined with exercise and/or booster sessions. Digital and gamified formats proved feasible and engaging; parental outcomes showed small improvements where measured. Conclusions: PNE is a promising, low-cost, and scalable component of pediatric chronic pain care, strengthening self-efficacy and adaptive coping. Integration into biopsychosocial, multidisciplinary programs—particularly alongside exercise and family involvement—may optimize outcomes. Larger, standardized trials with long-term follow-up and systematic adverse-event reporting are needed to solidify guidance for clinical practice. Full article

Background: Neonatal seizures are critical neurological events with long-term implications for brain development. Standard antiseizure medications, such as phenobarbital, often yield suboptimal seizure control and may be associated with neurotoxicity. This narrative review explores the role of vitamin B6 as a precision therapy in neonatal seizure syndromes, particularly in pyridoxine-responsive conditions. Methods: We conducted a narrative review of the biochemical functions of vitamin B6, focusing on its active form, pyridoxal 5′-phosphate (PLP), and its role as a coenzyme in neurotransmitter synthesis. We examined the genetic and metabolic disorders linked to vitamin B6 deficiency, such as mutations in pyridox(am)ine 5’-phosphate oxidase (PNPO), Aldehyde Dehydrogenase 7 Family Member A1 (ALDH7A1), alkaline locus phosphatase (ALPL), and cystathionine β-synthase (CBS), and discussed the clinical rationale for empirical administration in acute neonatal seizure settings. Results: Vitamin B6 is essential for the synthesis of gamma-aminobutyric acid (GABA), dopamine, and serotonin, with PLP-dependent enzymes such as glutamic acid decarboxylase and aromatic L-amino acid decarboxylase playing central roles. Deficiencies in PLP due to genetic mutations or metabolic disruptions can result in treatment-resistant neonatal seizures. Early supplementation, especially in suspected vitamin B6-dependent epilepsies, may provide both diagnostic clarity and seizure control, potentially reducing exposure to conventional antiseizure medications. Conclusions: Vitamin B6-responsive epilepsies highlight the clinical value of mechanism-based, individualized treatment approaches in neonatology. Incorporating genetic and metabolic screening into seizure management may improve outcomes and aligns with the principles of precision medicine. Full article

Introduction: Vaccines are the most widely used public health measure to control the global COVID-19 pandemic. Most vaccines used in Europe and North America are mRNA-based. A mass vaccination campaign was carried out between 2021 and 2024. Some adverse events have been reported based on analogies with previous virus-attenuated vaccines. Objectives: Given the new mechanism inducing specific antibodies, we questioned the role of mRNA Spike vaccines and the significance of hyperproduction of anti-Spike antibodies in the emergence of early and late onset rheumatological manifestations observed after one or more injections. Material and Methods: A prospective observational study involving two cohorts was initiated. The first cohort was observed from 13 September 2021 to 30 September 2022, and the second cohort from 1 October 2022 to 30 September 2023. The study also focused on the interval between the last vaccine injection and the onset of rheumatic symptoms. None of the patients had a history of rheumatic or inflammatory diseases. We compared both cohorts and ankle arthritis case series to analyze the differences between early and late-onset adverse events. Results: In both cohorts and case series, the majority of patients were women. The most common symptoms included diffuse muscle pain, which mimics polymyalgia rheumatica, and ankle arthritis. Very high levels of anti-Spike antibodies (>2080 BAU/mL) were generally detected. The Pearson correlation coefficient between both cohorts and case series was very high, confirming the reproducibility of post-vaccine clinical and biological features. Conclusions: These rheumatological manifestations might be triggered by inappropriate individual immune responses to the vaccine’s Spike protein and/or the overproduction of Spike protein, which can mediate a pro-inflammatory reaction, explaining early and late-onset effects. Full article