Search Results (139)

This research presents the development and management principles of mobile resonant electrical systems designed for high-voltage generation, intended for non-destructive diagnostics of insulation in high-power electrical equipment. The core of the system is a series inductive–capacitive (LC) circuit characterized by a high quality (Q) factor and operating at high frequencies, typically in the range of 40–50 kHz or higher. Practical implementations of the LC circuit with Q-factors exceeding 200 have been achieved using advanced materials and configurations. Specifically, ceramic capacitors with a capacitance of approximately 3.5 nF and Q-factors over 1000, in conjunction with custom-made coils possessing Q-factors above 280, have been employed. These coils are constructed using multi-core, insulated, and twisted copper wires of the Litzendraht type to minimize losses at high frequencies. Voltage amplification within the system is effectively controlled by adjusting the current frequency, thereby maximizing voltage across the load without increasing the system’s size or complexity. This frequency-tuning mechanism enables significant reductions in the weight and dimensional characteristics of the electrical system, facilitating the development of compact, mobile installations. These systems are particularly suitable for on-site testing and diagnostics of high-voltage insulation in power cables, large rotating machines such as turbogenerators, and other critical infrastructure components. Beyond insulation diagnostics, the proposed system architecture offers potential for broader applications, including the charging of capacitive energy storage units used in high-voltage pulse systems. Such applications extend to the synthesis of micro- and nanopowders with tailored properties and the electrohydropulse processing of materials and fluids. Overall, this research demonstrates a versatile, efficient, and portable solution for advanced electrical diagnostics and energy applications in the high-voltage domain. Full article

Transcranial direct current stimulation (tDCS) is a safe, well-tolerated method of non-invasively eliciting cortical neuromodulation. It has gained recent interest, especially for its positive clinical outcomes in neurodegenerative diseases such as multiple sclerosis (MS). However, its simultaneous (during tDCS) and cumulative effects (following repeated tDCS sessions) on the regional brain activity during rest need further investigation, especially in MS. This study aims to elucidate tDCS’ underpinnings, alongside its therapeutic impact in MS patients, using concurrent tDCS-MRI methods. In total, 20 MS patients (age = 48 ± 12 years; 8 males) and 28 healthy controls (HCs; age = 36 ± 15 years; 12 males) were recruited. They participated in a tDCS-MRI session, during which resting-state functional MRI (rs-fMRI) was used to measure the levels of the fractional amplitude of low-frequency fluctuations (fALFFs), which is an index of regional neuronal activity, before and during left anodal dorsolateral prefrontal cortex (DLPFC) tDCS (2.0 mA for 15 min). MS patients were then asked to return for an identical tDCS-MRI visit (follow-up) after 20 identical at-home tDCS sessions. Simultaneous tDCS-induced changes in fALFF are seen across cortical and subcortical areas in both HC and MS patients, with some regions showing increased and others decreased brain activity. In HCs, fALFF increased in the right pre- and post-central gyrus whilst it decreased in subcortical regions. Conversely, MS patients initially displayed increases in more posterior cortical regions but decreases in the superior and temporal cortical regions. At follow-up, MS patients showed reversed patterns, emphasizing significant cumulative effects of tDCS treatment upon brain excitation. Such long-lasting changes are further supported by greater pre-tDCS fALFFs measured at follow-up compared to baseline, especially around the cuneus. The results were significant after correcting for multiple comparisons (p-FDR < 0.05). Our study shows that tDCS has both simultaneous and cumulative effects on neuronal activity measured with rs-fMRI, especially involving major brain areas distant from the site of stimulation, and it is responsible for fatigue and cognitive and motor skills. Full article

This work proposes two voltage-controlled oscillators using noise-filtering technique. The first one is a 24-GHz voltage-controlled oscillator, and the second one is based on a push–push architecture with a $\mathsf{\lambda }$/4 transmission line to further increase the frequency up to 48 GHz. The designs are implemented and verified in a standard 90-nm CMOS process. Typically, the current mirror transistor in the tail current has a nonlinear effect. When the transistor operates in the nonlinear region, noise will be introduced. Therefore, a set of LC filters with a resonant frequency at 2$f_0$ are added to the design of this section to filter the noise at 2$f_0$ through the capacitor to the ground. The measurement results show that the design of a single oscillator has an oscillation frequency of 24.37 GHz, a tuning range of 6.5%, and a phase noise of −97.19 dBc/Hz @1MHz. The measurement results of the push–push architecture show that the double oscillation frequency is 49.8 GHz, the tuning range is 7.2%, and the phase noise is −80.52 dBc/Hz @1MHz. The chip areas of 24-GHz LC VCO and 48-GHz push–push LC VCO are 0.68 mm × 0.69 mm and 0.7 mm × 0.7 mm, respectively. Full article

To address the challenge of transverse thickness consistency in wide-width electrode calendering, this study developed a flexible roll profile regulation technology based on electromagnetic induction heating. An axisymmetric electromagnetic–thermal–structural coupling finite element model is established and validated on a self-built experimental platform. Systematic simulations were conducted to investigate the influence of equivalent current density J_s, current frequency f, and coil turn n on the roll temperature and roll profile. The maximum temperature of the roll’s inner bore and the roll crown exhibit a positive correlation with J_s, f, and n. A cyclic heating strategy was developed to control and stabilize the roll profile. The stable crown C_W shows linear correlation with heating durations t₁ and a nonlinear trend with J_s. Under fixed J_s and t₁, further optimization of duty cycle and cooling conditions enables long-term stabilization of the roll profile. Full article

Magnetic hyperthermia is a promising cancer treatment technique that relies on Néel and Brownian relaxation mechanisms to heat superparamagnetic nanoparticles injected into tumor sites. Under low-frequency magnetic fields, nanoparticles generate localized heat, inducing controlled thermal damage to cancer cells. However, radio frequency coils used to generate alternating magnetic fields may suffer from excessive heating, leading to efficiency losses and unintended thermal effects on surrounding healthy tissues. This study proposes novel liquid cooling systems, leveraging the skin effect phenomenon, to improve thermal management and reduce coil size. Finite element method-based simulation studies evaluated coil electrical current and temperature distributions under varying applied frequencies, water flow rates, and cooling microchannel dimensions. A dataset of 300 simulation cases was generated to train a Gaussian Process Regression-based machine learning model. The performance index was also developed and modeled using Gaussian Process Regression, enabling rapid performance prediction without requiring extensive numerical studies. Sensitivity analysis and the ReliefF algorithm were applied for a thorough analysis. Simulation results indicate that the proposed novel liquid cooling system demonstrates higher performance compared to conventional systems that utilize direct liquid cooling, offering a computationally efficient method for pre-manufacturing design optimization of radio frequency coil cooling systems in magnetic hyperthermia applications. Full article

This study investigated the control of porosity during gas metal arc welding with pulsed arc (GMAW-P) of complex-phase 780 (CP780) galvanized steel. Due to the Zn coating on this type of steel, porosity forms during welding as a result of Zn vaporization. The objective was to optimize the welding parameters to minimize porosity with a design of experiments using an L9 orthogonal array to analyze the effects of peak current (I_p), pulse time (t_p), and pulse frequency (f) in high-speed welding conditions. The results showed that porosity was significantly reduced with a peak current of 313 A, a frequency of 10 Hz, and a pulse time of 10 ms, achieving ~0% porosity in the validation welding trials. A microstructural analysis identified allotriomorphic ferrite, Widmanstätten ferrite, acicular ferrite, bainite, and martensite in the heat-affected zone (HAZ). A predictive model to anticipate the percentage of porosity with an R² of 99.97% was developed, and an ANOVA determined the peak current as the most critical factor in porosity formation. Full article

The open-circuit fault diagnosis of switching devices in 3ϕ V/F-controlled voltage source inverters is critical, since diagnostic parameters change with varying load conditions and frequency. Park’s vector transform-based approaches depend on threshold values for fault diagnosis, demanding continuous modifications based on load variations, making them prone to improper diagnosis. Artificial intelligence-based methods give good accuracy, but they require extensive data collection under varying load conditions, creating implementation efforts that are considerably high. This paper focuses on optimizing threshold-independent methods and reducing data requirements for the artificial intelligence-based open-circuit fault diagnosis of 3ϕ V/F-controlled VSIs. To mitigate the problem of fault misclassification under variable load conditions at different frequencies, the stator current is normalized using Park’s vector transform. Normalized currents ensure that the extracted features remain the same under all load conditions while providing distinctive features for faulty and healthy conditions. Feature extraction is implemented using the wavelet transform, and feature selection is carried out using a ReliefF algorithm, which enhances classification by selecting key features. The selected features are then used to diagnose faults using an extreme gradient boosting algorithm. In XGBoost, a random search is preferred over a grid search to find the best hyperparameters for optimal performance, as it speeds up tuning, explores more options, and efficiently balances accuracy. The proposed system outperforms current open-switch fault diagnosis approaches by providing high effectiveness, strong resistivity, and a fast detection time. The results are presented for different combinations of single and multiple open-switch faults under variable load conditions at different frequencies. Full article

To ensure the reliability and security of Colombia’s national power system, there is an ongoing necessity for upgrades in monitoring and protection mechanisms. Approximately sixteen years ago, the introduction of synchrophasor measurements enabled the swift detection of potentially network-detrimental events. Subsequent advancements have seen the deployment of Phasor Measurement Units (PMUs), currently tallying 150 across 25 substations, facilitating real-time monitoring and analysis. The growth of the PMU network is pivotal for the modernization of the National Control Center, particularly in the face of complexities introduced by renewable energy sources. There is an increasing demand for data analytics platforms to support operators in responding to threats. This paper explores the development of the Colombian Wide-Area Measurement System (WAMS) network, highlighting its milestones and advancements. Significant contributions include the technological evolution of the WAMS for real-time monitoring, an innovative high-speed data analytics strategy, and tools for the monitoring of frequency, rate of change of frequency (RoCoF), angular differences, oscillations, and voltage recovery, alongside industry-specific criteria for real-time assessment. Implemented within an operational WAMS, these tools enhance situational awareness, thereby assisting operators in decision-making and augmenting the power system’s reliability, security, and efficiency, underscoring their significance in modernization and sustainability initiatives. Full article

Polymorphisms in the Toll-like receptor 4 (TLR4) and IL-17 cytokine genes play a role in liver fibrosis progression among patients with MASLD. The current study aimed to investigate whether the IL17 (A7448G and G197A) and TLR4 (Asp299Gly and Thr399Ile) gene polymorphisms are associated with increased liver fibrosis stages in MASLD patients. Genotyping for the IL17F-A7488G, IL17A-G197A, TLR4-Asp299Gly, and TLR4-Thr399Ile polymorphisms was performed on a sample of 42 MASLD patients and 39 healthy controls. Serum levels of IL17F, IL17A, and TLR4 were measured using ELISA techniques. Bivariate analysis revealed significant associations between glycemic levels (p = 0.006), lipid metabolism (total cholesterol, HDL cholesterol, triglycerides), and the severity of liver fibrosis (p < 0.05). The IL17A-G197A GA and AA genotypes were more frequent in patients with advanced liver fibrosis compared to those without fibrosis (GA genotype frequency: 42.9% vs. 7.7%; AA genotype frequency: 14.3% vs. 5.1%; adjusted p = 0.0423). In the multivariable ordinal logistic regression, the IL17A-G197A polymorphism remained significantly associated with higher liver fibrosis stages (adjusted p = 0.0155). Patients with the dominant genotype (GA + AA) of the IL17A-G197A polymorphism exhibited 3.91 times greater odds of experiencing at least a one-stage increase in liver fibrosis compared to those with the GG genotype (adjusted OR = 3.91, 95% CI: 1.33–12.34). This study indicates that IL17-related genetic polymorphisms and metabolic characteristics significantly affect liver fibrosis progression in MASLD patients, with the IL17A-G197A gene polymorphism identified as an independent multivariate predictor of fibrosis progression. Full article

In existing two-stage single-phase dynamic voltage restorer (DVR) voltage sag mitigation devices, the output-side power contains a pulsating component at twice the fundamental frequency (2f₀), leading to the presence of second-order ripple currents (SRCs) on the DC input side. This, to some extent, affects the reliability of the system and has a significant impact on the lifespan of energy storage devices. In this study, the dual-loop control method of the buck/boost converter is combined with the virtual impedance auxiliary control strategy to suppress SRCs. Compared to existing solutions, this method offers the advantages of being fast, stable, and reliable, while the virtual impedance auxiliary control strategy is flexible and easy to implement. The feasibility and stability of this strategy were verified using a 3 kW DVR prototype. When applying the two virtual impedance methods, the second harmonic content was reduced from 39.64% to 1.74% and 1.78%, respectively. The proposed control strategy demonstrates significant effectiveness in suppressing second harmonic currents. Full article

Silk fibroin, a biocompatible and flexible biopolymer derived from Bombyx mori silkworms, has shown promise in bioelectronics, due to its adjustable dielectric properties. This study investigates the influence of spin coating parameters on the optical, electrical, and dielectric properties of thin silk fibroin films. Silk fibroin solutions were spin coated onto indium tin oxide (ITO)/glass substrates at speeds ranging from 1000 to 7000 revolutions per minute (RPM), resulting in films with thicknesses that varied from 264.8 nm to 81.9 nm. Atomic force microscopy analysis revealed that the surface roughness remained consistent at approximately 1.5 nm across all the spin coating speeds, while the film thickness decreased with the increasing spin speed. Ultraviolet (UV)–visible spectroscopy showed that the transmittance at 550 nm increased from 81.2% at 1000 RPM to 93.8% at 7000 RPM, and the optical bandgap widened from 3.82 eV at 1000 RPM to 3.92 eV at 7000 RPM, which was attributed to reduced molecular packing and quantum confinement effects. Electrical characterization showed that thinner films (a spin speed of 5000–7000 RPM) exhibited a 15-fold increase in the leakage current, rising from 2.99 pA at 1000 RPM to 44.9 pA at 7000 RPM, and a decrease in resistance from 334 GΩ at 1000 RPM to 22.2 GΩ at 7000 RPM. The capacitance–voltage measurements indicated a 4-fold increase in voltage-dependent capacitance for thinner films, with capacitance values increasing from 36 pF at 1000 RPM to 176 pF at 7000 RPM. Dielectric loss analysis revealed that thinner films experienced higher energy dissipation at low frequencies (tan δ of 0.041 at 0.01 MHz for 7000 RPM), but lower losses at high frequencies (tan δ of 0.123 at 1 MHz for 7000 RPM). These findings emphasize the importance of film thickness control in optimizing the performance of silk fibroin-based bioelectronic devices. Full article

Background: Pain is prevalent in almost all populations and may often hinder visual, auditory, tactile, olfactory, and taste perception as it alters brain neural processing. The quantitative methods emerging to define pain and assess its effects on neural functions and perception are important. Identifying pain biomarkers is one of the initial stages in developing such models and interventions. The existing literature has explored chronic and experimentally induced pain, leveraging electroencephalograms (EEGs) to identify biomarkers and employing various qualitative and quantitative approaches to measure pain. Objectives: This systematic review examines the methods, participant characteristics, types of pain states, associated pain biomarkers of the brain’s electrical activity, and limitations of current pain studies. The review identifies what experimental methods researchers implement to study human pain states compared to human control pain-free states, as well as the limitations in the current techniques of studying human pain states and future directions for research. Methods: The research questions were formed using the Population, Intervention, Comparison, Outcome (PICO) framework. A literature search was conducted using PubMed, PsycINFO, Embase, the Cochrane Library, IEEE Explore, Medline, Scopus, and Web of Science until December 2024, following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines to obtain relevant studies. The inclusion criteria included studies that focused on pain states and EEG data reporting. The exclusion criteria included studies that used only MEG or fMRI neuroimaging techniques and those that did not focus on the evaluation or assessment of neural markers. Bias risk was determined by the Newcastle–Ottawa Scale. Target data were compared between studies to organize the findings among the reported results. Results: The initial search resulted in 592 articles. After exclusions, 24 studies were included in the review, 6 of which focused on chronic pain populations. Experimentally induced pain methods were identified as techniques that centered on tactile perception: thermal, electrical, mechanical, and chemical. Across both chronic and stimulated pain studies, pain was associated with decreased or slowing peak alpha frequency (PAF). In the chronic pain studies, beta power increases were seen with pain intensity. The functional connectivity and pain networks of chronic pain patients differ from those of healthy controls; this includes the processing of experimental pain. Reportedly small sample sizes, participant comorbidities such as neuropsychiatric disorders and peripheral nerve damage, and uncontrolled studies were the common drawbacks of the studies. Standardizing methods and establishing collaborations to collect open-access comprehensive longitudinal data were identified as necessary future directions to generalize neuro markers of pain. Conclusions: This review presents a variety of experimental setups, participant populations, pain stimulation methods, lack of standardized data analysis methods, supporting and contradicting study findings, limitations, and future directions. Comprehensive studies are needed to understand the pain and brain relationship deeper in order to confirm or disregard the existing findings and to generalize biomarkers across chronic and experimentally induced pain studies. This requires the implementation of larger, diverse cohorts in longitudinal study designs, establishment of procedural standards, and creation of repositories. Additional techniques include the utilization of machine learning and analyzing data from long-term wearable EEG systems. The review protocol is registered on INPLASY (# 202520040). Full article

In industries dealing with motor drive systems, the use of real-time simulators for validating control codes is becoming increasingly mandatory. This is particularly essential for systems with advanced control codes or complex microcontroller unit (MCU) register configurations, as this validation process helps prevent accidents and shorten development time. This study presents a validation process using a real-time simulator for the beatless control of six-step operation. Six-step operation, when applied to high-speed drives, has a limitation on the number of samples per electrical rotation, which causes voltage errors. A representative of these voltage error phenomena is the beat phenomenon, resulting in torque ripple at the first harmonic and high current ripple. To mitigate this beat phenomenon, a synchronous PWM method is sometimes used. However, in practical industrial systems, it may not be feasible to synchronously adjust the inverter’s switching frequency with the rotation speed. This study proposes a beatless control method to eliminate the voltage errors caused by the beat phenomenon during six-step operation at a fixed switching frequency. The specific implementation of this control method is explained based on MCU timer register settings. While previous studies have only proposed beatless control methods, this paper goes further by implementing the proposed beatless method using the MCU (TMS320F28335) to generate gating signals and validating the implementation through simulation on a permanent magnet synchronous motor using a real-time simulator (Typhoon HIL). Full article

Breast cancer survivors experience numerous chronic symptoms linked to autonomic dysfunction including anxiety, stress, insomnia, menopausal symptoms, and cognitive impairment. Effective non-pharmacological solutions to address these are currently lacking. Methods: Our three-armed longitudinal randomized controlled trial assessed the effectiveness of a 4-week remote smartphone-based heart rate variability biofeedback intervention which involved daily paced breathing at 6 breaths p/min; active (12 breaths p/min) and waitlist controls were included. Heart rate variability and self-reported cancer-related symptoms were assessed at baseline, post-, and 6 months-post intervention. Participants were 60 UK-based women with primary breast cancer history (6 to 60 months post-active treatment). Results: The intervention group showed significant increases in low-frequency heart rate variability over time (F (4, 103.89) = 2.862, p = 0.027, d = 0.33), long-lasting improvement in sleep quality (F (4, 88.04) = 4.87, p = 0.001, d = 0.43) and cessations in night sweats (X² (2, N = 59) = 6.44, p = 0.04, Cramer’s V = 0.33), and reduced anxiety post-intervention compared to the active and waitlist controls (F (4, 82.51) = 2.99, p = 0.023, d = 0.44). Other findings indicated that the intervention and active control participants reported lasting improvements in cognitive function, fatigue, and stress-related symptoms (all ps < 0.05). The waitlist group reported no symptom changes across time. Conclusion: Heart rate variability biofeedback is a feasible intervention for addressing diverse chronic symptoms commonly reported by breast cancer survivors. Full article

With the emphasis on energy conversion and energy-saving technologies, the single-phase pulse width modulation (PWM) rectifier method is widely used in urban rail transit because of its advantages of bidirectional electric energy conversion and higher power factor. However, due to the complex control and harsh environment, it can easily fail. Faults can cause current and voltage distortion, harmonic increases and other problems, which can threaten the safety of the power system and the train. In order to ensure the stable operation of the rectifier, incidences of faults should be reduced. A fault diagnosis technique based on Euclidean norm fusion multi-frequency bands and multi-scale permutation entropy is proposed. Firstly, by the optimal wavelet function, information on the optimal multi-frequency bands of the fault signal is selected after wavelet packet decomposition. Secondly, the multi-scale permutation entropy of each frequency band is calculated, and multiple fault feature vectors are obtained for each frequency band. To reduce the classifier’s computational cost, the Euclidean norm is used to fuse the multi-scale permutation entropy into an entropy value, so that each frequency band uses an entropy value to characterize the fault information features. Finally, the optimal multi-frequency bands and multi-scale permutation entropy after fusion are used as the fault feature vector. In the simulation system, it is shown that the method’s average accuracy is 78.46%, 97.07%, and 99.45% when the SNR is 5 dB, 10 dB, and 15 dB, respectively. And the fusion of multi-scale permutation entropy can improve the accuracy, recall rate, precision, and F1 score and reduce the False Alarm Rate (FAR) and the Missing Alarm Rate (MAR). The results show that the fault diagnosis method has high diagnosis accuracy, is a simple feature fusion method, and has good robustness to working conditions and noise. Full article