Search Results (3,647)

Multi-robot ensembles comprising several manipulators are commonly used in industrial settings to process non-deterministic flows of items loaded by an upstream source onto a shared transportation system. After the execution of a given task, the robots regularly deposit the items on a common output flow, which conveys the semi-finished material towards the downstream portion of the plant for further processing. The productivity and reliability of the entire process, which is affected by the plant layout, by the quality of the adopted scheduling and task assignment algorithms, and by the proper balancing of the input and output flows, may be degraded by random disturbances and transient conditions of the input flow. In this paper, a highly accurate event-based simulator of this kind of system is used in conjunction with a rollout algorithm to optimize the performance of the plant in all operating scenarios. The proposed method relies on a simulation of the plant that comprehensively considers the dynamic performance of the manipulators, their actual motion planning algorithms, the adopted scheduling and task assignment methods, and the regulation of the material flows. The simulation environment is built upon computationally efficient maps able to predict the execution time of the tasks assigned to the robots, considering all the determining factors, and on a representation of the manipulators themselves as finite state automata. The proposed formalization of the line balancing problem as a Markov Decision Process and the resulting rollout optimization method are shown to substantially improve the performance of the plant, even in challenging situations, and to be well suited to real-time implementation even on commodity hardware. Full article

To accurately evaluate the health condition of the cables of a cross-sea cable-stayed bridge under typhoon effects and to improve the efficiency of damage identification, an accurate bridge damage identification method combining convolutional neural network (CNN) and Bidirectional Long Short-Term Memory (BiLSTM) is proposed. A numerical model of the cable-stayed bridge was first established in ANSYS. Based on the monitoring data of Super Typhoon Mujigae, a three-dimensional fluctuating wind field was generated by harmonic synthesis. Through transient analysis, the static and dynamic responses of the cable-stayed bridge under typhoon loads were analyzed, and the critical cable locations most susceptible to damage were identified. Subsequently, the acceleration signals of the structural damage states under typhoon were extracted, and the damage-sensitive features were obtained through the Hilbert transform. Finally, an intelligent damage identification model for cable-stayed bridges was established by combining CNN and BiLSTM, and the identification results were compared with those obtained using CNN and BiLSTM individually. The results indicate that the neural network model combining CNN and BiLSTM performs significantly better than either CNN or BiLSTM alone in predicting both the location and degree of damage. Compared with the standalone CNN and BiLSTM models, the proposed hybrid CNN–BiLSTM network improves the accuracy of damage-location identification by 1.6% and 2.42%, respectively, and achieves an overall damage-degree identification accuracy exceeding 98%. The findings of this study provide theoretical and practical support for the intelligent operation and maintenance of cable-stayed bridges in coastal regions. The proposed approach is expected to serve as a valuable reference for evaluating large-span bridge structures under extreme wind conditions. Full article

The ability of Ribes species to survive the fluctuating winter and early spring conditions, relies on the regulation of transcription factors (TFs) and other key genes involved in the abiotic stress response. In this study, we developed specific primers for 33 stress-responsive genes, which may facilitate future functional studies in Ribes and other less-characterized lineages within the Saxifragales order. These genes were selected based on a comparative transcriptomic analysis of R. nigrum cv. Aldoniai and are known to function in cold acclimation and stress signaling pathways. We analyzed expression profiles of these 33 genes in R. aureum, R. hudsonianum, and R. nigrum microshoot cultures exposed to controlled cold stress, deacclimation and reacclimation treatments. Our results revealed species-specific genetic responses across acclimation cycles of varying durations (24–96 h). Cold stress induces molecular changes in three Ribes spp.; however, deacclimation triggered by transient warming significantly reduced freezing tolerance in R. nigrum, had a moderate effect on R. hudsonianum, and minor impact on R. aureum. Gene expression profiling revealed distinct, species-specific regulatory patterns among species during different stress cycles, highlighting conserved and specific genes in acclimation mechanisms within the Ribes spp. These findings contribute to a deeper understanding of transcriptional regulation under acclimation cycles in currants and provide molecular tools that may support breeding strategies aimed at enhancing cold tolerance in Ribes crops amid increasing climate variability. Full article

Objective: Oral lichen planus (OLP) is a chronic immune-mediated condition of the oral mucosa, commonly associated with pain and burning sensations that impair quality of life. This study aimed to compare the efficacy of photodynamic therapy with 5-aminolevulinic acid (ALA-PDT) and topical glucocorticosteroids (CT) in the treatment of OLP, considering lesion location on keratinized and non-keratinized mucosa. Materials and Methods: A randomized clinical trial was conducted on 90 patients with histologically confirmed OLP. Participants were allocated to receive either ALA-PDT in addition to novel oromucosal emulgel containing 5% ALA (five weekly sessions) or clobetasol propionate applied twice daily for two weeks. Lesion area, clinical severity (Reticulation, Erythema, Ulceration—REU index), and subjective symptoms (Visual Analog Scale—VAS) were evaluated before treatment, immediately after, and six months after therapy. Results: ALA-PDT achieved significantly greater and more durable reductions in lesion area, REU scores, and VAS values compared to CT, particularly on non-keratinized mucosa (mean lesion reduction from 2.64 to 0.56 cm² at six months; p < 0.0001). CT therapy showed initial improvement but was followed by relapse at six months. Both treatments were well tolerated, with only mild transient adverse effects reported. Conclusions: ALA-PDT, especially when applied to non-keratinized oral mucosa, provides superior and longer-lasting therapeutic outcomes than topical CT. The application of novel ALA-loaded emulgel enhances treatment efficacy and tolerability, supporting PDT as a promising alternative for OLP management. Full article

Reliable multilevel inverter IGBT modules require precise loss and heat management, particularly in severe traction applications. This paper presents a comprehensive modeling framework for three-level T-type neutral-point clamped (TNPC) inverters using a high-power Insulated Gate Bipolar Transistor (IGBT) module that combines model predictive control (MPC) with space vector pulse width modulation (SVPWM). The particle swarm optimization (PSO) algorithm is used to methodically tune the MPC cost function weights for minimization, while achieving a balance between output current tracking, stabilization of the neutral-point voltage, and, consequently, a uniform distribution of thermal stress. The proposed SVPWM-MPC algorithm selects optimal switching states, which are then utilized in a chip-level loss model coupled with a Cauer RC thermal network to predict transient chip-level junction temperatures dynamically. The proposed framework is executed in MATLAB R2024b and validated with experiments, and the SemiSel industrial thermal simulation tool, demonstrating both control effectiveness and accuracy of the electro-thermal model. The results demonstrate that the proposed control method can sustain neutral-point voltage imbalance of less than 0.45% when operating at 25% load and approximately 1% under full load working conditions, while accomplishing a uniform junction temperature profile in all inverter legs across different working conditions. Moreover, the results indicate that the proposed control and modeling structure is an effective and common-sense way to perform coordinated electrical and thermal management, effectively allowing for predesign and reliability testing of high-power TNPC inverters. Full article

Mismatch repair (MMR) system alterations can trigger transient hypermutation, promoting adaptive mutations under stress, such as antibiotic exposure. While most organisms use MutS and MutL protein families for MMR, many archaea and actinobacteria, including the major human pathogen Mycobacterium tuberculosis, lack these components and instead rely on NucS, a structurally distinct enzyme driving a non-canonical MMR pathway. Given the role of MMR in mutation control, understanding how nucS expression is regulated could be essential for uncovering the molecular basis of antibiotic resistance development in mycobacteria. In this study, we characterized the nucS promoter and transcription start site in Mycobacterium smegmatis. We found that nucS expression declines during the stationary phase in both M. smegmatis and M. tuberculosis, paralleling replication activity and canonical MMR downregulation. Our data suggest that the alternative sigma factor σ^B may negatively regulate nucS expression during this phase. Additionally, we identified candidate compounds that may modulate nucS expression, underscoring its responsiveness to environmental cues. These findings enhance our understanding of mycobacterial stress responses and lay the groundwork for exploring antibiotic resistance mechanisms. Strikingly, our work reveals a case of double convergent evolution: both canonical (MutS/MutL) and non-canonical (NucS) pathways have independently evolved not only the same DNA repair function, but also similar regulatory frameworks for genome integrity preservation under stress conditions. Full article

The growing demand for improved interruption performance characteristics in emerging aircraft high-voltage direct current (HVDC) electrical networks motivates the rapid development of solid-state power controllers (SSPCs). This article presents a comprehensive design procedure for a 270 V 300 A SSPC utilizing discrete SiC cascode devices. Due to the high fault current and limited power of single switches, parallel SiC FETs are essential for interrupting high fault currents in SSPCs. Consequently, the challenge of current balancing among parallel devices is addressed in this paper by adopting a passive current balancing strategy based on an irregular-shaped busbar. Furthermore, considering the voltage spikes arising from the power loop parasitic inductance and TVS characteristics during fault interruption, an RC-TVS-based transient voltage mitigation circuit is proposed to suppress these peak voltages. Moreover, thermal models for overload and short-circuit conditions were developed to optimize the thermal management system to ensure reliable operation of the SSPC. Finally, a prototype of 270 V/300 A SSPC has been built to validate the key characteristics of the proposed high power SSPC. Full article

High-efficiency power management is essential for silicon photomultiplier (SiPM)-based sensing systems, especially in portable radiation detectors that demand long battery life and stable operation. Conventional fixed-frequency, voltage-mode boost converters face two critical issues: efficiency degradation at light load due to dominant switching losses, and narrow loop bandwidth in discontinuous conduction mode (DCM), which limits transient response. This work proposes a boost converter IC that integrates a pulse-skipped switching (PSS) scheme with a Gm-boosted compensator to address these challenges. The PSS method adaptively suppresses unnecessary switching events, significantly improving light-load efficiency, while the Gm-boosted compensator enhances loop gain, expanding the bandwidth and enabling faster recovery under dynamic conditions. Implemented in a 250 nm BCD process, the converter provides up to 30 V output from a 3.3–5 V supply with load currents up to 10 mA. Simulation results show a peak efficiency of 86.3% at 1 mA and a loop bandwidth increase of more than 14 times compared with a conventional fixed-frequency, voltage-mode design. Beyond radiation applications, the proposed converter is broadly applicable to battery-powered IoT, medical monitoring, and portable energy systems requiring efficient high-voltage generation. Full article

The study investigates the electrical energy parameters in the distribution system of a mining facility located in Murmansk Oblast, Russia, focusing on power quality (PQ) issues arising substantially from mine hoist operation conditions. Despite compliance with Russian standards related to PQ, discrepancies were observed between PQ measurement results and problems inherent in the system, such as transformer failures. The research employed two instruments, Resurs-UF2M and Metrel MI2892, to conduct a PQ survey, comparing their data aggregation methods and measurement accuracy. Various data aggregation intervals were also used to evaluate the impact of resolution on PQ assessment. Results revealed significant discrepancies between the instruments, with Metrel MI2892 providing a more reliable and detailed dataset, while Resurs-UF2M failed to capture rapid transients and enable profound PQ analysis to be performed. The research identified eight PQ indices exceeding permissible levels, attributed to the electromagnetic influence of high-power mining equipment. The findings underscore the limitations of current regulatory frameworks and measurement methods, emphasizing the need for revised standards to improve diagnostic accuracy. The research highlights the importance of proper instrument selection and configuration to mitigate PQ disturbances, prevent equipment failures, and enhance power system reliability in mining facilities. Full article

Understanding internal resonance phenomena in transformer windings is essential for evaluating insulation performance and preventing equipment failure under transient conditions. This study presents a measurement-based modeling approach to assess internal voltage distributions in a high-voltage transformer winding of a dry-type distribution transformer. Frequency-domain admittance and voltage transfer functions were experimentally obtained and approximated using vector fitting. The resulting models were employed to simulate time-domain responses through a two-step procedure that integrates electromagnetic transient simulations of the terminal circuit with frequency-derived internal voltage models. The validation was performed using a sinusoidal excitation at 51 kHz, corresponding to the first-mode resonance frequency. Simulated internal voltages and input currents showed close agreement with experimental measurements, confirming the model’s accuracy. The study identified two critical resonance frequencies at 51 kHz and 59 kHz, at which voltage amplification can become severe. At 51 kHz, the maximum overvoltage reached nearly seven times the applied voltage at the winding midpoint, indicating a substantial risk of dielectric failure. These findings highlight the importance of accurately characterizing internal resonances in transformer windings, especially during insulation coordination studies. The proposed methodology offers an effective tool for analyzing internal overvoltages and contributes to the development of more robust transformer design and protection strategies. Full article

Ensuring the structural integrity of mechanical components operating in fluid environments requires precise and reliable monitoring techniques. This study presents a methodology for reconstructing the full-field deformation of a flexible aluminium plate subjected to unsteady water flow in a water tunnel, using a structural modal reconstruction approach informed by experimental data. The experimental setup involves an aluminium lamina (200 mm × 400 mm × 2.5 mm) mounted in a closed-loop water tunnel and exposed to a controlled flow with velocities up to 0.5 m/s, corresponding to Reynolds numbers on the order of ${10}^4$, inducing transient deformations captured through an image-based optical tracking technique. The core of the methodology lies in reconstructing the complete deformation field of the structure by combining a reduced number of vibration modes derived from the geometry and boundary conditions of the system. The novelty of the present work consists in the integration of the Internal Strain Potential Energy Criterion (ISPEC) for mode selection with a data-driven machine learning framework, enabling real-time identification of active modal contributions from sparse experimental measurements. This approach allows for an accurate estimation of the dynamic response while significantly reducing the required sensor data and computational effort. The experimental validation demonstrates strong agreement between reconstructed and measured deflections, with normalised errors below 15% and correlation coefficients exceeding 0.94, confirming the reliability of the reconstruction. The results confirm that, even under complex, time-varying fluid–structure interactions, it is possible to achieve accurate and robust deformation reconstruction with minimal computational cost. This integrated methodology provides a reliable and efficient basis for structural health monitoring of flexible components in hydraulic and marine environments, bridging the gap between sparse measurement data and full-field dynamic characterisation. Full article

Magnetically controlled spinal growing rods, used for treating early-onset scoliosis (EOS), face a critical clinical limitation: insufficient distraction force. Compounding this issue is the inherent inability to directly monitor the mechanical output of such implants in vivo, which challenges their safety and efficacy. To overcome these limitations, optimizing the rotor’s maximum torque is essential. Furthermore, defining the “continuous rotation domain” establishes a vital safety boundary for stable operation, preventing loss of synchronization and loss of control, thus safeguarding the efficacy of future clinical control strategies. In this study, a transient finite element magnetic field simulation model of a circumferentially distributed permanent magnet–rotor system was established using ANSYS Maxwell (2024). The effects of the clamp angle between the driving magnets and the rotor, the number of pole pairs, the rotor’s outer diameter, and the rotational speed of the driving magnets on the rotor’s maximum torque were systematically analyzed, and the optimized continuous rotation domain of the rotor was determined. The results indicated that when the clamp angle was set at 120°, the number of pole pairs was one, the rotor outer diameter was 8 mm, the rotor achieved its maximum torque and exhibited the largest continuous rotation domain, while the rotational speed of the driving magnets had no effect on maximum torque. Following optimization, the maximum torque of the simulation increased by 201% compared with the pre-optimization condition, and the continuous rotation domain was significantly enlarged. To validate the simulation, a rotor torque measurement setup incorporating a torque sensor was constructed. Experimental results showed that the maximum torque improved from 30 N·mm before optimization to 90 N·mm after optimization, while the driving magnets maintained stable rotation throughout the process. Furthermore, a spinal growing rod test platform equipped with a pressure sensor was developed to evaluate actuator performance and measure the maximum distraction force. The optimized growing rod achieved a peak distraction force of 413 N, nearly double that of the commercial MAGEC system, which reached only 208 N. The simulation and experimental methodologies established in this study not only optimizes the device’s performance but also provides a viable pathway for in vivo performance prediction and monitoring, addressing a critical need in smart implantable technology. Full article

Emptying pressure pipelines is a routine operation during pipeline maintenance. This study investigates the emptying characteristics of pressurized pipelines with air valves under unsteady flow conditions. A mathematical model for the emptying process is developed using the rigid water column theory, exploring the influence of drain valve opening, initial air pocket length, and valve opening patterns on the transient flow behavior. The results indicate that, compared with the linear valve opening pattern, a nonlinear power function opening increases the minimum air pocket pressure head by 0.1014 m and delays its occurrence by 0.655 s. The maximum emptying velocity rises by 0.48 m/s when the opening is increased from 10% to 30%, thereby shortening the emptying time by 65.4%. However, the pressure head inside the air pocket decreases accordingly. When the air valve diameter is enlarged from 0.003 mm to 0.008 mm, the pressure recovery time is markedly reduced and the initial pressure fluctuations are attenuated. Numerical simulations based on the Heihe emptying case demonstrate that a well-planned layout of multiple air valves effectively shortens the duration of negative pressure heads. Replacing the first air valve with a 50 cm diameter circular orifice significantly raises the minimum pressure head of the pipeline and dramatically enhances the stability of emptying pressurized pipeline. Full article

This study investigated bite force changes after botulinum toxin type A (BoNT-A) injection into different masticatory muscles. Thirty-five male participants were divided into three groups: masseter only (M), masseter and temporalis (MT), and masseter, temporalis, and medial pterygoid (MTP). Bite force was measured before and up to 6 months after injection with the Dental Prescale II system. Baseline values showed no significant group differences. Group M exhibited significant reduction at 1 and 2 weeks, with recovery within 1 month. Group MT showed a similar transient decrease, also recovering after 1 month. In contrast, Group MTP demonstrated a more pronounced and prolonged reduction, persisting up to 4 months before recovery. These results indicate that the extent and duration of BoNT-A effects depend on the number of muscles injected. Multi-muscle injections, including the medial pterygoid, provide more durable suppression. However, further research involving patient populations is needed to clarify whether multi-muscle injection strategies provide therapeutic benefits in clinical conditions such as temporomandibular disorders or oromandibular dystonia. Full article

Large-scale production systems (LSPS) operate under growing complexity driven by digital transformation, tighter environmental regulations, and the demand for resilient and resource-efficient operation. Conventional control strategies, particularly PID and isodromic regulators, remain dominant in industrial automation due to their simplicity and robustness; however, their capability to achieve near-optimal performance is limited under constraints on control amplitude, rate, and energy consumption. This study develops an analytical–computational approach for the approximate realization of optimal nonlinear control using standard regulator architectures. The method determines switching moments analytically and incorporates practical feasibility conditions that account for nonlinearities, measurement noise, and actuator limitations. A comprehensive robustness analysis and simulation-based validation were conducted across four representative industrial scenarios—energy, chemical, logistics, and metallurgy. The results show that the proposed control strategy reduces transient duration by up to 20%, decreases overshoot by a factor of three, and lowers transient energy losses by 5–8% compared with baseline configurations, while maintaining bounded-input–bounded-output (BIBO) stability under parameter uncertainty and external disturbances. The framework provides a clear implementation pathway combining analytical tuning with observer-based derivative estimation, ensuring applicability in real industrial environments without requiring complex computational infrastructure. From a broader sustainability perspective, the proposed method contributes to the reliability, energy efficiency, and longevity of industrial systems. By reducing transient energy demand and mechanical wear, it supports sustainable production practices consistent with the following United Nations Sustainable Development Goals—SDG 7 (Affordable and Clean Energy), SDG 9 (Industry, Innovation and Infrastructure), and SDG 12 (Responsible Consumption and Production). The presented results confirm both the theoretical soundness and practical feasibility of the approach, while experimental validation on physical setups is identified as a promising direction for future research. Full article