Search Results (762)

The electrification of regional railway lines using battery-electric trains requires accurate simulation tools to support energy management and thermal control design. This paper presents an integrated dynamic simulation model of the traction system of a Hitachi Caravaggio ETR 521 regional train operating in battery-electric mode, developed in MATLAB/Simulink 2024b. The model incorporates all key drivetrain components, including a train reference generator, speed controller, motor controller, three-phase inverter, induction motor, a Kokam Co., Ltd. lithium-ion battery pack, and a detailed battery thermal management system. The proposed framework enables simultaneous evaluation of traction performance, battery state of charge (SOC) evolution, and thermal behavior under realistic conditions. To validate the model, simulations of the Treviso–Vicenza route were conducted under two scenarios: traction-only operation and operation with a 160 kW auxiliary load. Simulation results demonstrate that auxiliary loads significantly affect energy consumption and battery thermal behavior, with energy consumption increased by 50%. The results highlight the importance of integrating thermal effects into energy management and sizing decisions for battery-electric regional trains. The developed model provides a practical tool for optimizing battery sizing, thermal management strategies, and overall energy performance, supporting the planning and design of sustainable electric railway solutions. The modular MATLAB/Simulink architecture is designed to be route-agnostic; extension to other regional lines with different gradients, speed profiles, or extreme climate conditions (e.g., alpine routes or high-temperature regions) requires only updated route data and adjusted ambient boundary conditions, demonstrating the model’s broad applicability beyond the Treviso–Vicenza case study. Full article

Gait impairment is a common motor manifestation of Parkinson’s disease (PD), which is also frequently accompanied by other motor abnormalities such as bradykinesia, rigidity, postural instability, and movement asymmetry. These motor impairments are closely associated with reduced mobility and increased fall risk. Although wearable plantar insole sensing provides a promising basis for objective gait assessment, existing studies have mainly focused on conventional time- or frequency-domain descriptors, whereas the nonlinear complexity of gait, laterality-related imbalance, and deviation from normal gait patterns remain insufficiently characterized in an integrated manner. To address this gap, this paper proposes FID-Gait, which is a three-domain fusion framework for PD identification using instrumented insole data. The framework combines automated gait-cycle segmentation with multidomain feature modeling, including a fractal domain for nonlinear gait complexity, a plantar-loading–phase imbalance (PLPI) domain for loading asymmetry and temporal disturbance, and a covariance-adjusted deviation (CAD) domain for measuring deviation from normal gait patterns. Experiments on the PhysioNet Gait in Parkinson’s Disease dataset showed that FID-Gait achieved strong discriminative performance under multiple evaluation protocols. At the gait-cycle level, the selected MLP classifier achieved an accuracy of 99.11% and an F1-score of 99.47%. At the subject level, the selected AdaBoost classifier achieved the highest accuracy of 90.22% and the best F1-score reached 93.02%. Five-fold cross-validation further supported the robustness of the proposed representation, and leave-one-subject-out evaluation provided preliminary evidence of subject-independent generalization. Overall, FID-Gait provides an effective and interpretable framework for PD gait characterization and identification in offline experimental settings. Full article

Background: Arginase 1 deficiency (ARG1-D) is an ultra-rare urea cycle disorder characterized by hyperargininemia and progressive neurological impairment, including spasticity, loss of motor function, and reduced quality of life. Conventional management based on dietary protein restriction and ammonia scavengers rarely achieves adequate metabolic control or prevents neurological deterioration. Pegzilarginase, a recombinant human arginase 1 enzyme, is the first disease-modifying therapy for ARG1-D. Methods: We report the first Italian real-world experience with pegzilarginase in three pediatric patients with genetically confirmed ARG1-D enrolled in the phase 3 PEACE trial. Clinical, biochemical, functional, nutritional and quality-of-life data were retrospectively collected over a long-term follow-up (2003–2025). Outcomes were evaluated across three phases: treatment initiation (Start), a 13-month treatment interruption due to trial closure (Stop), and therapy re-initiation through an early access program (Restart). Results: Pegzilarginase rapidly normalized plasma arginine levels and was associated with improvements in motor function, spasticity, walking endurance, dietary protein tolerance, bone mineral density, and quality of life. During treatment interruption, all patients experienced biochemical worsening and clinical deterioration, including increased spasticity, reduced mobility, and emotional distress. Re-initiation of pegzilarginase restored metabolic control and led to progressive neurological and functional recovery, including partial reversal of long-standing motor deficits. Conclusions: This real-world experience supports pegzilarginase as a disease-modifying therapy for ARG1-D. Sustained normalization of plasma arginine, rather than subthreshold biochemical control, correlates with functional and neurological improvement and may partially reverse non-lesional metabolic brain injury. Early initiation of pegzilarginase, including in newborn-screened patients, may further modify the natural history of ARG1-D. Full article

Dual three-phase interior permanent magnet synchronous motors (DT-IPMSMs) are widely used in high-power and high-reliability applications, and accurate rotor polarity identification at startup is a critical prerequisite for their stable and efficient operation. This study aims to address the problem of initial position acquisition during the startup of DT-IPMSMs by proposing a simple and fast rotor polarity identification method. The proposed method is based on the high-frequency square-wave voltage injection (HFSWVI) in the vector space decomposition (VSD) space, where both the current and voltage are injected into the d-axis. The single-pulse direct current (DC) injection is used to alter the magnetic saturation. Then, the change rates of the d-axis high-frequency response current are compared before and after DC injection to identify the rotor magnetic polarity. In addition, a moving average filter (MAF) is applied to suppress the fluctuations in the current change rate, which increases the accuracy of polarity identification. Moreover, a simple compensation technique is designed to make the estimated d-axis current change smoothly when the estimated angle changes from N-pole to S-pole. The effectiveness of the proposed method is proved by the experimental results in both standstill and free-running states for the prototyped DT-IPMSMs. This method provides a practical and efficient solution for initial position identification of DT-IPMSMs, contributing to the advancement of control technology for dual three-phase motor systems in related fields. Full article

Vulnerable road users in informal urban environments confront a distinct set of hazards that standard computer vision datasets are ill-equipped to represent: artisanal speed bumps constructed without regulatory compliance, deteriorated road markings, and the mototaxi—a three-wheeled motorized vehicle that constitutes the primary informal transport mode in intermediate Andean cities yet is absent from all major international repositories. This paper presents QHAWAY—from Quechua qhaway, a transitive verb meaning “to look; to observe”—an Advanced Driver Assistance System (ADAS) predicated on instance segmentation, monocular distance estimation via the pinhole camera model, and Time-to-Collision (TTC) computation, developed for the road environment of Ayacucho, Peru (2761 m a.s.l.), a city recognised by UNESCO as a Creative City of Crafts and Folk Art since 2019. A hybrid dataset comprising 25,602 images with 127,525 annotated instances across 12 classes was assembled by combining an original local collection of 4598 images (10,701 instances) captured through four complementary acquisition methods across the five urban districts of the Huamanga province with three established international datasets (BDD100K, BSTLD, RLMD; 21,004 images, 116,824 instances). A three-phase progressive training strategy with monotonically increasing resolution (640, 800, and 1024 pixels) was evaluated as an ablation study. A multi-architecture comparison spanning YOLOv8L-seg and the YOLO26 family (nano, small, large) identified YOLO26L-seg as the best-performing model, attaining mAP50 Box of 0.829 and mAP50 Mask of 0.788 at epoch 179. The integration of ByteTrack multi-object tracking with the pinhole equation $D=(H_{\mathrm{real}}\times f)/h_{\mathrm{px}}$ delineates operational risk zones aligned with the NHTSA forward collision warning standard (danger: <3 m; caution: 3–7 m; TTC threshold ≤ 2.4 s). The system sustains processing rates of 19.2–25.4 FPS on an NVIDIA RTX 5080 GPU. A systematic field survey established that 96% of the audited speed bumps fail to comply with MTC Directive No. 01-2011-MTC/14, constituting the first quantitative record of informal road infrastructure non-compliance in the Andean region. Validation was conducted under naturalistic driving conditions without staged scenarios. Grad-CAM explainability analysis, encompassing three complementary visualisation algorithms (Grad-CAM, Grad-CAM++, and EigenCAM), confirmed that model attention concentrates consistently on safety-critical objects. Full article

To solve the problems of rotor position estimation error caused by the installation deviation of Hall sensors and the increase in yarn amount detection error in complex environments, resulting in speed fluctuations and unstable yarn feeding in the traditional permanent magnet synchronous motor (PMSM) drive system for yarn feeder, a control method for yarn amount in yarn feeder PMSMs based on an improved dual second-order generalized integrator (DSOGI) and Kalman filter is proposed. Firstly, in order to reduce the influence of installation deviation of Hall sensors, the three-phase Hall signals are converted into two-phase orthogonal Hall vector signals. An improved DSOGI is used to filter out high-order harmonic components and specific harmonic components in the Hall vector signals, and a cross-coupled structure is constructed to further enhance the fundamental component and suppress high-order harmonic components of negative coefficients. Then, accurate motor rotor position information is extracted by a quadrature phase-locked loop; secondly, in order to obtain accurate information on yarn amount, a system state model based on yarn amount and its rate of change is established, and Kalman filtering is used for optimal estimation of the yarn amount; finally, the above methods are integrated into the PMSM control system of the yarn feeder. Experimental results show that, compared with traditional methods, the PMSM control system of the yarn feeder using the method proposed in this paper has a shorter startup time and smaller steady-state error in motor speed and yarn amount when conveying yarn at a constant speed; when transporting yarn at variable speed, the motor speed and yarn amount settling time are shorter, and the peak deviation is smaller. Full article

Aging is a progressive and heterogeneous biological process influenced by multiple factors that may compromise physical and cognitive capacities and increase the risk of frailty, functional decline, and falls in older adults. Falls represent a major public health concern due to their impact on independence and long-term care demand. Immersive virtual reality (IVR) delivered through active video games (exergames) has emerged as a preventive strategy that integrates sensory, motor, and cognitive stimulation within controlled and engaging environments, particularly where traditional programs face challenges related to adherence and individual adaptation. This study aims to determine the feasibility and implementation of an IVR-based program for falls prevention in older adults at risk of frailty in primary health care (PHC). A quasi-experimental pre–post design will be conducted with an intervention group (IVR/exergames) and a conventional control group, including a total sample of 40 participants (20 per group). The protocol comprises three phases: baseline assessment and IVR familiarization; a 12-week intervention delivered twice weekly; and post-intervention assessment. The primary outcome will be fall risk assessed using the Timed Up and Go (TUG) test. Secondary outcomes include physical performance (Short Physical Performance Battery, SPPB, and handgrip dynamometry) and psychological aspects related to falls (Falls Efficacy Scale International, FES-I, and Activities-specific Balance Confidence Scale, ABC). Feasibility indicators will include recruitment, adherence, retention, and cybersickness. A reduction in TUG time is expected, providing preliminary evidence on the feasibility of integrating IVR-based programs for falls prevention within PHC systems. Full article

Regarding the problems of fifth and seventh order characteristic harmonics existing in the operation of the dual three-phase permanent magnet synchronous motor, repetitive control is often used to improve the steady-state accuracy. However, traditional RC mostly adopts a fixed forward-learning gain and is set through trial-and-error methods, which requires a lot of time. Therefore, this paper proposes an improved repetitive control strategy based on fuzzy dynamic gain scheduling. This strategy precisely extracts the comprehensive distortion characteristic values of the target suppressed harmonics and the warning harmonics online; it designs a fuzzy adaptive adjustment mechanism to actively increase the gain to achieve rapid suppression when the target harmonic is severe, and rapidly reduce the gain to ensure the safety of operation when a low-frequency oscillation trend is detected. Simulation results show that the proposed method effectively reduces the total harmonic distortion of the current while maintaining the stability of the system and improves the harmonic suppression accuracy. Full article

Industrial predictive maintenance programs often rely on SCADA historian signals characterized by low-frequency sampling and asynchronous reporting intervals. These data constraints, specifically non-uniform scan rates and inter-tag time misalignment, limit the applicability of high-resolution or sensor-intensive prognostic models. This study proposes a lightweight, physics-informed health proxy, the temperature-weighted work (TWW) index, designed to monitor motor stator-winding degradation within these industrial limitations. The TWW index accumulates mechanical work derived from torque and speed measurements, weighted by an adaptive exponential temperature-emphasis function that penalizes operation at elevated temperatures. The formulation is inspired by practical thermal-aging heuristics such as Montsinger’s rule in the qualitative sense that higher temperatures are treated as disproportionately more damaging, but it is not intended as a direct implementation of a fixed absolute-temperature life law. Instead, it is designed as a lightweight adaptive index suitable for online SCADA-based implementation. To address SCADA-specific irregularities, the framework incorporates data synchronization and resampling techniques to align heterogeneous tags, alongside power-thresholding to isolate degradation-relevant load periods. The resulting cumulative index is mapped to a normalized health/RUL proxy using failure-referenced thresholds identified from historical events. Validation using field data from industrial three-phase motors demonstrates that the TWW index provides a monotonic degradation profile that is consistent with documented winding-related failures and proactive removals. Case studies confirm that the model enabled proactive maintenance interventions by signaling the terminal phase of insulation life before catastrophic breakdown, offering a hardware-free and scalable solution for real-time asset management. Full article

Medium voltage induction motors (MVIM) are a key component of numerous industries, such as water treatment plants, sewage discharge stations, and chilled water systems. The starting process for these MV motors is critical as it is associated with a major impact on both motor lifetime and power grid quality. In this article, a proposed modified and comprehensive starting scheme of MV three-phase induction motors driving pumps for water stations is introduced. Firstly, the starting performance and its impact on power grid quality will be discussed when all motors are normally started with direct on line connection (DOL), which is already the normal established status. A modified starting scheme based on an optimized coordination of motor starting methods in addition to variable voltage variable frequency drive (VVVFD) drive and control implementation will be discussed. A transition between the starting of variant MV induction motors as well as the starting event coordination principle will be discussed to improve the power quality relative to the obligatory time shift required for the operation. The coordination is based on an algorithm implementation which is achieved using different optimization concepts based on artificial intelligence techniques, properly conducting the transition time in addition to the power delivered by the inverter unit rather than determining the number of DOL and VVVF-implemented motors. A comparison between using the optimized VVVFD soft-starting and the proposed modified scheme is performed, focusing on the power quality improvement rather than optimizing the cost function. The modified scheme is simulated using ETAP power station for brief analysis and study of load flow rather than the complete inspection and power quality assessment. Full article

This paper presents the design, simulation, and experimental validation of a novel type of pneumatic rotary positioner that is based on a three-cylinder radial mechanism driven by independently controlled pressures. The system uses standard off-the-shelf industrial components, including pneumatic cylinders, proportional pressure regulators, and a programmable logic controller. In order to obtain angular positioning, a three-phase sinusoidal pressure commutation scheme is adopted, similar to the three-phase electrical motors. Analytical expressions for piston kinematics and torque generation are derived and used to design direct open-loop, open-loop with friction compensation, and closed-loop position control strategies. The technical implementation, with the prototype tested unloaded, can achieve accurate positioning (±3° in open-loop mode with feedforward to ±0.3° in closed-loop mode with PD controller), with very good repeatability on average (<0.5°) and smooth theoretical torque (average 1.4 Nm, with 0.51% ripple) at low speeds (<60 rpm). The experimental prototype was designed as a compact device, having approx. 94 mm diameter and 110 mm depth. When used in open-loop mode, the actuator is connected to the control system using just three pneumatic tubes and thus is completely free of any electromagnetic fields, making it suitable for some environment-critical applications. These advantages promote the proposed positioner as a practical rotary actuator in specialized automation and robotics applications where established electrical servomotors cannot be used. Full article

Pulse Width Modulated (PWM) voltage source inverters are widely used to power induction motors in industrial applications. However, they generate common-mode voltage (CMV), which induces high shaft voltages and bearing currents, leading to premature motor failures. This paper proposes a novel active cancellation method to compensate for the CMV in high-voltage induction motor drives. The method utilizes Y-configured resistors for CMV detection and a push–pull amplifier with MOSFETs to generate reproduced CMV (RCMV). The RCMV is applied to the motor frame via an isolation transformer, effectively reducing the CMV-induced common-mode current (CMC). The proposed method achieves a significant reduction in the CMC, from 1.5 A to 4 mA peak-to-peak in a simulation and from 2.7 A to 57 mA peak in experiments with a 1.1 kW, 415 V/60 Hz motor. This cost-effective approach enhances motor drive reliability and mitigates electromagnetic interference (EMI), making it suitable for high-voltage applications. Full article

Background: Early childhood is a critical period for the development of motor competence, which is closely related to later physical activity, educational readiness, and broader developmental outcomes. However, the temporal dynamics of motor skill acquisition in preschool children, particularly the time required to reach initial and early refinement phases of learning, remain insufficiently described. The aim of this study was to examine whether different levels of previous participation experience in an organized kinesiology program are associated with differences in the speed and quality of novel motor skill acquisition in preschool children, and to explore the relationship between baseline motor proficiency and phase-based indicators of motor learning. Methods: A total of 161 preschool children aged 5–6 years participated in the study and were grouped according to their previous participation experience in an organized kinesiology program (0 h, ~120 h, ~350 h, and ~470 h). Following BOT-2 assessment, all participants completed a standardized 7-week motor learning program that included nine previously unfamiliar motor tasks. Using a phase-based video analysis protocol, three learning indicators were recorded: time to Phase 1 (F1; first successful execution), time to Phase 2 (F2; initial refinement of performance), and final performance quality (K). Group differences and associations were first examined descriptively and correlationally, after which additional multivariable regression models were performed to determine whether previous participation experience and baseline motor proficiency were independently associated with motor learning outcomes. Results: The findings showed consistent differences across groups, with children who had greater previous participation experience generally reaching F1 and F2 more rapidly and achieving higher final performance quality scores. Higher BOT-2 scores were also associated with shorter learning times and better final performance quality. In the multivariable models, both previous participation experience in an organized kinesiology program and BOT-2 total score were independently associated with Phase 1 attainment time and final performance quality, whereas only previous participation experience remained independently associated with Phase 2 attainment time. The applied phase-based observational protocol demonstrated good to excellent inter-rater reliability across the evaluated motor learning variables. Conclusions: These findings provide phase-based temporal indicators of motor learning progression in preschool children and suggest that previous participation experience in an organized kinesiology program and baseline motor competence are meaningfully associated with the speed and quality of acquiring new motor tasks. The findings also demonstrate the potential of phase-based approaches for quantifying motor learning dynamics in early childhood settings. Such indicators may offer useful reference information for instructional pacing and the planning of motor learning activities, while also serving as practically relevant predictors for adapting future kinesiology programs to children’s motor readiness. Future research should further examine these relationships using longitudinal and analytically expanded designs. Full article

This paper presents an efficient stand-alone photovoltaic water pumping system (PVWPS) intended for agricultural irrigation applications, operating without energy storage. The system employs a three-phase induction motor supplied by a three-level neutral point clamped (NPC) inverter. The proposed control strategy integrates the advantages of two distinct controllers to enhance both energy extraction and drive performance. On the photovoltaic side, a fuzzy logic-based maximum power point tracking (MPPT) algorithm is implemented to ensure continuous operation at the global maximum power point under rapidly varying irradiance conditions. On the motor drive side, a direct torque control (DTC) scheme is combined with the multilevel NPC inverter to regulate electromagnetic torque and stator flux. The use of a multilevel inverter significantly mitigates the inherent drawbacks of conventional DTC, notably torque and flux ripples, as well as stator current harmonic distortion. The overall control architecture maximizes power transfer from the photovoltaic generator to the pumping system, resulting in improved dynamic response and energy efficiency. The proposed system is validated through detailed MATLAB/Simulink simulations under abrupt irradiance variations and a realistic daily solar profile corresponding to August conditions in Kairouan, Tunisia. Simulation results demonstrate substantial performance improvements, including an 88% reduction in torque ripples, a 50% decrease in flux ripple, a 77.9% reduction in stator current THD, and a 33.3% enhancement in speed transient response compared to conventional DTC-based systems. Full article

Background/Objectives: Stroke is among the leading causes of disability in adults, as hemiparesis affects motor function and daily activities. Constraint-induced movement therapy (CIMT) has proven effective in functional recovery through intensive use of the affected limb. This study aimed to assess the impact of CIMT on upper limb (UL) rehabilitation in stroke patients, with a focus on motor recovery, integration into activities of daily living (ADLs), and overcoming clinical implementation barriers. Methods: A systematic review was conducted by searching PubMed, Scopus, and Web of Science from their inception to March 2026. Systematic reviews and meta-analyses evaluating the effectiveness of CIMT in adult patients after stroke were included. The outcome variables included motor function, movement quality, independence in ADLs, and quality of life (QoL). Results: Twenty-five systematic reviews and sixteen meta-analyses were included. The participants were adults who had suffered a stroke at acute, subacute, or chronic stages and were aged between 18 and 95 years. With respect to upper limb motor function, ten studies reported statistically significant results in favor of CIMT. With respect to ADLs, four studies reported significant differences in favor of CIMT, with strong effects in intensive interventions. With respect to QoL, three studies reported significant improvements after the intervention. Conclusions: The results of this umbrella review support the effectiveness of CIMT in UL rehabilitation after stroke, especially in the subacute and chronic phases. CIMT, alone or in combination with adjuvant therapies, contributes to improving motor function, independence in ADLs, and QoL in patients. Full article