Search Results (735)

Shearer trailing cable faults are difficult to distinguish from terminal measurements because their signatures coexist with changes in load, source imbalance, cable temperature, and sensor error. This study presents a physics-guided categorical Mamdani framework supported by a distributed-parameter source, cable, and load model. A total of 180 simulations cover normal operation, phase-to-ground faults, A–B inter-phase short circuits, conductor-resistance degradation, and insulation-path deterioration over multiple severities, locations, motor loads, source imbalance levels, and temperatures. Paired pre-fault and post-fault changes in load-terminal voltage unbalance, source-terminal zero-sequence current ratio, and source-to-load voltage attenuation are mapped to fault path-based membership functions and diagnostic rules. Twenty repeated 70/30 holdouts grouped by base operating condition compare the proposed method with a deterministic threshold tree, radial-basis-function support vector machine, and k-nearest-neighbor classifier. Across these repeated grouped holdouts, the proposed method achieves 99.80% mean accuracy with a standard deviation of 0.63 percentage points on noise-free test cases. Accuracy remains 81.12% and 74.71% under 1% and 2% RMS waveform noise, respectively. These results demonstrate the effectiveness of the proposed framework for interpretable diagnosis of shearer power-core cable faults across the investigated simulated operating conditions and waveform-noise levels. Full article

Dance and rhythmic physical activity may support motor and cognitive development in children, but the magnitude and consistency of these effects remain uncertain, and individual trials frequently contribute multiple statistically dependent outcomes. Five electronic databases and ClinicalTrials.gov were searched from inception to May 2026. Executive function (EF) and motor competence (MC) were analyzed as separate primary domains using multilevel random-effects models with an estimated sampling variance–covariance structure and trial-clustered CR2 robust inference. Cluster-randomized designs, shared controls, and overlapping reports were explicitly accounted for. Twenty-two reports representing 21 unique trials and 2496 unique children were included. The primary EF model included 34 core-EF effect sizes from seven trials and yielded g = 0.50 (95% CI [−0.04, 1.04], p = 0.063; 95% PI [−1.24, 2.24]). The MC model included 103 effect sizes from 17 trials and showed a positive average effect (g = 0.95, 95% CI [0.39, 1.52], p = 0.003; 95% PI [−1.43, 3.34]). Trial-clustered dose–response models did not identify statistically supported associations for intervention duration, total minutes, weekly frequency, or session duration. Certainty of evidence was very low for EF and low for MC. Dance and rhythmic physical activity may improve motor competence in children on average, although effects vary substantially across settings. Executive-function findings remain preliminary and statistically uncertain. Current evidence does not support causal recommendations for longer interventions or higher total doses. Full article

With the rapid development of autonomous systems, there is a growing need for versatile yet low-cost platforms that integrate perception, decision-making, and control in real-time environments. This study presents the design and implementation of a multi-functional intelligent car system based on the STM32F103C8T6 microcontroller. The system integrates an OPENMV camera for visual recognition, a DY-SV8F voice module, a dual 4-channel grayscale sensor array for high-precision path tracking, and a PS2 remote controller. A hierarchical control architecture is adopted. The core role of the actuators, which drives the vehicle’s motion in response to visual and sensory feedback, is emphasized through a tightly coupled control loop that translates perceptual data into precise PWM signals for motor speed and direction regulation. The core contribution lies in the design of a novel path tracking algorithm featuring Gaussian-weighted sensor fusion, a finite-state machine for path feature recognition, and an adaptive PID controller with curvature-based feedforward compensation. Furthermore, this paper provides a detailed exposition of a lightweight color marker recognition algorithm operating in the hue, saturation, value (HSV) color space, including its mathematical formulation and system-level integration with the motion control loop for event-triggered multi-modal task execution. Experimental results demonstrate that the proposed system achieves a mean absolute path tracking deviation of 2.1 mm, a color detection accuracy of 100% under controlled lighting, and flawless execution of complex, event-driven task sequences. Full article

Postural control in curling is expressed during a dynamic, sport-specific delivery on a single sliding leg, yet it is still assessed almost exclusively with static single-leg force-plate protocols that poorly reflect on-ice demands. This study developed and validated a wearable multi-sensor system that fuses trunk and pelvis inertial measurement units (IMUs), instrumented plantar-pressure insoles and core-muscle surface electromyography (sEMG) to quantify dynamic postural stability during the simulated curling delivery in 110 young adult curlers (age range 18–24 years). A four-phase segmentation of the delivery was implemented, and a compact 28-feature set was extracted and combined through a complementary Kalman fusion scheme into a single Dynamic Stability Index (DSI). Validated against a reference force plate during static single-leg standing, the IMU-derived sway path showed a small bias (~0.4 cm) with 95% limits of agreement of approximately +4.4 to −3.6 cm, and between-day reliability of the fused DSI was excellent (ICC(3,1) = 0.90, 95% CI [0.82, 0.95]). A random-forest classifier discriminated high- from low-stability deliveries with 91.8% accuracy (95% CI [87.2%, 95.1%]; AUC = 0.92, 95% CI [0.87, 0.96]), outperforming any single-sensor or static force-plate baseline. Sensor-derived dynamic metrics correlated with external-oblique strength, trunk proprioceptive error and motor self-efficacy (Spearman ρ ranging from −0.55 to 0.51, all p < 0.001 after Holm–Bonferroni correction), and dynamic instability increased monotonically across descending self-efficacy tertiles. The proposed system provides a portable, context-relevant and interpretable tool for balance profiling in young curlers, and demonstrates that multi-sensor fusion substantially improves measurement fidelity over conventional single-modality assessment. Full article

This paper presents the integration and bench validation of a modular electric vehicle (EV) conversion kit, detailing the system architecture, communication interfaces, and real-time performance analysis of its core subsystems. The study systematically examines the key components of the propulsion system—including the electric motor and its associated motor control unit (MCU), the battery pack governed by a battery management system (BMS) with an integrated power distribution unit (PDU), and essential peripherals such as the DC-DC converter, 12 V auxiliary battery, and human–machine interfaces. The central focus is placed on the Controller Area Network (CAN) communication interfaces that enable seamless data exchange and coordinated control among the Vehicle Control Unit (VCU), MCU, and BMS. Through empirical data acquired from the integrated EV kit on a test bench, we conduct a real-time performance analysis to evaluate system responsiveness and drivability under various operating conditions. The findings validate the technical viability of the modular conversion kit and provide a practical reference framework for future EV conversion projects. Furthermore, the paper extends beyond technical integration to assess the economic benefits of EV conversion, comparing operational and maintenance costs against traditional internal combustion engine benchmarks. The study’s scope is limited to system integration and bench validation; vehicle-level integration (chassis mounting, mechanical adaptation, and road testing) is identified as a necessary next step. Full article

Plastic pollution has emerged as one of the most pressing environmental, health, and socio-economic challenges worldwide, driving rapid growth in scientific research over the last decade. This study presents a comprehensive bibliometric analysis of global research on plastic particles as environmental contaminants published between 2015 and 2025. The search expression employed was (*plastic) AND (pollut* OR contaminat*) to retrieve publications addressing plastic pollution and the occurrence of plastics as environmental contaminants. A total of 50,946 documents, including articles, reviews, and book chapters indexed in the Scopus database, were analyzed using VOSviewer 1.6.20 and Bibliometrix/Biblioshiny v. 2026.01.1 Build 403 to evaluate publication trends, collaboration networks, conceptual structure, and the bibliometric organization of the field. The analysis revealed a sustained increase in scientific production, led by China (15,667 publications), the United States (5540), and India (5374), with Environmental Science representing the dominant subject area (31.2%). To characterize the most recent thematic structure, keyword co-occurrence analysis was specifically performed using articles published during 2024–2025. Keyword co-occurrence and thematic mapping identified microplastics, nanoplastics, and adsorption as the principal motor themes, while circular economy, sustainability, biodegradation, and machine learning emerged as rapidly expanding research directions. Author-productivity and journal-dispersion analyses revealed a concentrated scientific structure, characterized by a relatively small group of highly productive authors and a core set of journals accounting for a substantial proportion of the literature but with significant deviations from the theoretical Lotka and Bradford distributions. Furthermore, the collaboration analysis revealed an irregular geographic distribution of publication output and international co-authorship, with the largest absolute contributions concentrated in China, the United States, India, and several European countries. By integrating bibliometric indicators with policy frameworks, funding patterns, and sustainability perspectives, this study provides a system-level understanding of the evolution of research on plastic pollution. It identifies strategic priorities to support evidence-based environmental governance, circular economy implementation, and future research agendas. Full article

During the development of modern electric drives, vibroacoustic quality is one of the most critical parameters alongside motor performance and efficiency. One source of poor vibroacoustic characteristics is the inhomogeneity and imperfection of the soft magnetic materials found in the electrical machine. The primary indicators of these defects are the selected electrical steel and the machining processes used for the stator (waterjet cutting, laser cutting, punching). These inhomogeneities excite the mass-spring-damper oscillating system through higher-order harmonics induced in the air gap. The objective of the present research is the identification of these air-gap harmonics, for which this study aims to perform a systematic investigation chain starting from closed magnetic circuit measurements and building up to measurements loaded with an air gap. This is based on classical Epstein measurements, followed by induction measurements conducted in the air gap of a C-core. The test specimens were fabricated from M400-50A electrical steel using three different machining methods. The results show that the machining process has a significant impact on the magnetic characteristics, and the exit angle of the induction vectors measurable in the air gap also deviates from the ideal. Full article

The electrification of ground transport is advancing under a constraint that is as much geopolitical as technical: the rare-earth elements used in high-energy permanent magnets, and especially the heavy-rare-earth additions required for high-coercivity grades, come from a highly concentrated and recently restricted value chain. This review examines how the imperative to reduce or eliminate rare-earth permanent magnets is reshaping traction-machine design across ground-vehicle segments, from city cars and hypercars to racing prototypes, heavy-duty and mining trucks, and agricultural tractors. Adopting a design-oriented perspective, it links each segment’s torque–speed and cost envelope to coordinated choices of topology, magnet strategy, soft-magnetic and conductor materials, and winding architecture. The principal candidate topologies—interior and surface permanent magnet, induction, synchronous reluctance, permanent-magnet-assisted synchronous reluctance, wound-field synchronous, and emerging axial-flux machines—are compared quantitatively and selected topologies are illustrated through previously published design case studies. The picture is nuanced: permanent-magnet machines still dominate the market, yet in representative like-for-like studies the drive-cycle efficiency penalty of magnet-free machines can be small and wound-field machines are emerging as a leading magnet-free alternative within specific operating envelopes. Full article

The rhizosheath is a dynamic plant–soil interface in which root traits, microbial activity, and soil physical properties jointly regulate plant adaptation to drought and nutrient limitation. Despite the growing interest in this field, it remains conceptually fragmented. This study mapped the development, structure, and emerging directions of rhizosheath research at the intersection of microbiome interactions, stress adaptation, and root-trait genetics. Bibliometric and science-mapping analyses were performed on 136 publications (2015–2026) retrieved from the Web of Science Core Collection. Using the Bibliometrix framework, we examined publication dynamics, collaboration networks, citation patterns, keyword co-occurrence, and thematic structures. The dataset comprised 136 publications, 6366 cited references, and 723 authors, with 54.41% international co-authorship. Logistic modeling described the accumulation of publications through 2025, identifying a growth inflection at 2022.54; a reliable saturation level could not be estimated because the 2026 data cover only a partial year. Document coupling resolved nine clusters dominated by soil–root interface processes (n = 51; 1358 citations) and plant–microbe interactions (n = 18; 895 citations). Thematic analysis positioned soil and rhizosheath as central domains and identified water stress as a key motor theme, whereas mucilage, hydraulic functioning, and microbiome assembly emerged as recent trends. Rhizosheath research is transitioning from descriptive characterization toward more integrated, mechanistic perspectives linking root traits, soil processes, and microbial dynamics. Progress will depend on resolving genotype × soil × microbiome interactions and advancing field-based cross-scale phenotyping to support climate-resilient cropping systems. Full article

Thermal protection is critical for solid rocket motor safety, yet ablation prediction of insulation layers remains a core challenge. To achieve rapid and accurate prediction, this study develops a Physics-Informed Neural Network (PINN) model for EPDM-based insulation materials. The model is constructed based on three submodels (flow, heat transfer, and mass transfer in the surface boundary layer of thermal insulation layers; flow, heat transfer, and diffusion in porous media; thermal decomposition and thermochemical ablation of insulation layers) along with two external modules (gas and particle erosion). Results show a maximum prediction error of 10.76%, in good agreement with experiments. Compared with traditional ablation models, the proposed prediction model achieves faster prediction speed while maintaining good accuracy, which is conducive to providing suggestions for thermal protection design. Full article

This research presents a comparative performance evaluation of two advanced maximum power point tracking (MPPT) methodologies, namely sliding mode control (SMC) and the Kalman filter (KF), specifically applied to a standalone photovoltaic water pumping system (PVWPS). To achieve economic viability, the system is designed for storage-less operation, driving a three-phase induction motor (IM) via a high-dynamic direct torque control (DTC) scheme and a three-level inverter. The core technical contribution addresses the critical challenge of maximizing energy yield under partial shading conditions (PSCs). PSCs result in a complex, non-convex power–voltage (P−V) characteristic, containing multiple peaks, where conventional MPPT algorithms fail to consistently locate the global maximum power point (GMPP). To overcome this deficiency, we implemented the SMC-based MPPT algorithm to exploit its inherent robustness and rapid dynamic response, and compared it with the Kalman filter MPPT, which relies on stochastic state estimation to achieve accurate tracking and effective disturbance rejection. MATLAB/Simulink analysis compares the proposed techniques with the perturb and observe (P&O) MPPT method. The comparison considers tracking efficiency, convergence speed, and steady-state ripple under various shading conditions to identify the most effective control strategy for improving PVWPS performances. The reported performance evaluations are based on numerical simulations conducted within the MATLAB/Simulink environment, using a validated system model. Full article

The Fe–6.5 wt.% Si alloy is a promising soft magnetic material for electric motor applications owing to its high electrical resistivity and low core loss. However, the intrinsic brittleness of this alloy precludes fabrication of thin laminates using conventional rolling processes. Laser Powder Bed Fusion (LPBF) has therefore been considered as an alternative manufacturing route, offering both geometric flexibility and the inherent advantages of additive manufacturing. Nevertheless, successful LPBF processing of Fe–6.5 wt.% Si has remained challenging due to its high-silicon content. In this study, the Fe–6.5 wt.% Si alloy was modified by introducing 1 wt.% Cr, and LPBF process variables were optimized to yield defect-free parts. The effect of Cr addition on suppressing the disorder–order phase transformation during solidification was investigated through Thermo-Calc^® thermodynamic simulations and quantified via X-ray diffraction phase analysis. Crack morphology analysis from optical micrographs revealed a marked reduction in both solidification and liquation cracks, attributed to the role of Cr in mitigating silicon segregation and consequently lowering the fraction of ordered phases. Preheating the build plate to 200 °C was found to effectively eliminate vertical cracks by reducing thermal stresses within the parts; however, a limited number of horizontal cracks initiated at the sample edges and propagated inward, likely due to elevated thermal gradients at the perimeter. To address this issue, sacrificial walls were introduced at distances of 1.0 mm and 0.2 mm from the cube edges, locally reducing the cooling rates and effectively increasing the primary dendrite arm spacing (PDAS). The reduced cooling rate also led to lower lattice misorientation, confirmed by electron backscatter diffraction (EBSD), and a significant decrease in the crack length from ~2 mm to ~0.7 mm. Full article

The global energy landscape is undergoing a low-carbon, diversified, and high-efficiency transition, creating an urgent need to develop intelligent operation and maintenance (O&M) technologies for critical nuclear power equipment to boost plant economic efficiency. As the core “heart” component of the primary loop, the reactor coolant pump (main pump) must meet extremely stringent reliability criteria to ensure safe and stable operation of nuclear facilities. Existing remaining useful life (RUL) prognostics for main pumps mostly output deterministic point estimates; they fail to quantify predictive uncertainties and cannot provide credible risk intervals to support maintenance decision-making. To fill this research gap, this study first performs coupled thermomechanical failure simulations for three vulnerable main pump components: the rotor shaft assembly, double-cone sealing structure, and motor shielding sleeve. Simulation results are validated via tests on a full-scale main pump prototype bench to extract sensitive degradation characteristic parameters. Accordingly, a hybrid Bayesian Transformer-LSTM prognostic framework is proposed for main pump RUL prediction with built-in uncertainty quantification. Data augmentation is utilized to expand multi-source degradation datasets of main pumps. The Mahalanobis distance is employed to build component-level health indicators (HIs), and a cloud barycenter weighted evaluation method fuses these sub-component HIs into a unified system-level comprehensive health index (CHI). Using the fused CHI as model input, the Bayesian Transformer-LSTM architecture incorporates probabilistic fully connected layers to simultaneously capture local time-series fluctuations and long-term global degradation trends, enabling joint RUL regression and uncertainty quantification. A full-scale main pump prototype from an in-service nuclear power plant is used to validate the multi-source data fusion strategy. Quantitative evaluation results show that the proposed method achieves a coefficient of determination R² = 0.997, root mean square error (RMSE) = 0.018, and prediction interval coverage probability (PICP) = 0.839. Comparative ablation experiments further confirm that the proposed model delivers outstanding fitting precision and reliable uncertainty quantification, enabling long-timescale full-lifecycle health characterization of main pumps. Full article

Background: Physical activity is relevant for physical and psychosocial development in children and adolescents with Down syndrome. However, evidence regarding the effects of structured physical activity interventions across different motor and psychosocial domains remains limited and heterogeneous. This systematic review aimed to examine the effects of structured physical activity interventions on motor and psychosocial outcomes in this population. Methods: The review was conducted according to PRISMA guidelines and registered in PROSPERO (CRD42025114068). Scopus, PubMed, and Web of Science databases were searched, with the final search conducted on 15 December 2025. Eligible studies were peer-reviewed articles published in English within the previous 10 years that investigated structured physical activity interventions in children and adolescents with Down syndrome and reported motor or psychosocial outcomes. Methodological quality was assessed using a modified Downs and Black Checklist. Due to substantial clinical and methodological heterogeneity across interventions, comparators, and outcome measures, findings were synthesized narratively. The certainty of evidence was assessed using the GRADE approach. Results: Five studies, including 186 participants, were included, of whom 166 had Down syndrome and 20 were typically developing children. The included studies reported improvements in motor skills, balance, coordination, and psychosocial outcomes. Interventions included Pilates, core stability and treadmill training, fundamental movement skills training, adapted football, and traditional Indian dance. Motor outcomes were generally associated with improvements in balance, postural control, coordination, and motor competence. Psychosocial outcomes were assessed in only two studies and showed preliminary improvements, including reductions in aggression, attention problems, anxiety/depression, and social problems. Overall, the certainty of evidence was rated as low across the assessed outcome domains. Conclusions: Structured physical activity interventions may be associated with improvements in motor development, while their effects on psychosocial outcomes appear encouraging but require further investigation. The findings should be interpreted cautiously because of the small number of studies, methodological limitations, and heterogeneity of interventions and outcome measures. Further high-quality randomized controlled trials with larger samples and standardized outcome measures are needed. Full article

Background/Objectives: Nursing research on children with disabilities spans diverse disability groups, care settings, and areas of practice; however, its development and structure have not been comprehensively examined. This study aimed to examine publication trends, major research themes, temporal development, and collaboration patterns. Methods: The Web of Science Core Collection was searched on 29 June 2026 without publication-year restrictions. English-language articles and reviews indexed in Science Citation Index Expanded (SCI-EXPANDED) and Social Sciences Citation Index (SSCI) were included, yielding 1915 publications from 1977 to 2026. VOSviewer and Biblioshiny were used to analyze publication trends, keyword co-occurrence, thematic structure and evolution, trend topics, and country and institutional collaboration. Results: Research output increased substantially, particularly during the last decade. Across the study period, the United States had the highest publication output and co-authorship connectivity, followed by England, Canada, and Australia. Nursing, children, autism spectrum disorder, intellectual disability, and cerebral palsy were among the largest nodes in the keyword network. The thematic map positioned the autism–pediatrics–developmental disability cluster slightly within the motor themes quadrant, while the disability–children with disabilities–qualitative research, adolescents–communication–transition, and children–nursing–intellectual disability clusters were positioned among the basic themes. Thematic evolution showed both continuity and diversification, with autism, nursing, children, and intellectual disability represented across multiple periods, while quality of life, education, and mental health were represented in the most recent period. Trend topic analysis further showed that well-being, implementation, pediatric nursing, anxiety, and mental health were among the topics with more recent median publication years. Conclusions: Nursing research on children with disabilities has expanded and diversified, with recurring disability-specific topics alongside more recent topics related to psychosocial issues, pediatric nursing, and implementation. Future research could build on the thematic patterns identified in this study through systematic reviews and primary nursing research, while bibliometric studies incorporating additional databases could provide a more comprehensive view of the field. Full article