Search Results (26)

This paper presents a comparative analysis of electric field (E-field) mitigation in inductive power transfer (IPT) systems. It focuses on how distributed capacitor placement interacts with coil topology to influence E-field emissions. The study compares traditional sequential-winding coils and the alternating voltage phase coil (AVPC), which employs a sequential inversion winding (SIW) structure to enforce a 180° phase voltage opposition between adjacent turns. While capacitor segmentation is a known method for E-field reduction, this work is the first to systematically evaluate its effects across both conventional and phase-inverted coils. The findings reveal that capacitor placement serves as a topology-dependent design parameter. Finite Element Method (FEM) simulations and experimental validation show that while capacitor placement has a moderate influence on traditional coils due to in-phase voltage relationships, AVPC coils are highly sensitive to segmentation patterns. When capacitors align with the SIW phase structure, destructive interference significantly reduces E-field emissions. Improper capacitor placement disrupts phase cancellation and negates this benefit. This study resolves a critical design gap by establishing that distributed compensation acts as a tuning mechanism in conventional coils but becomes a primary constraint in phase-inverted topologies. The results demonstrate that precise capacitor placement aligned with the coil topology significantly enhances E-field mitigation up to 60% in AVPC coils, greatly outperforming traditional coil configurations and providing actionable guidance for high-power wireless charging applications. Full article

Ant venoms are rich sources of bioactive molecules, including peptide toxins with potent and selective activity on ion channels, which makes them valuable for pharmacological research and therapeutic development. Voltage-dependent potassium (Kv) channels, critical for regulating cellular excitability or cell cycle progression control, are targeted by a diverse array of venom-derived peptides. This study focuses on MYRTX_A4-Tb11a, a peptide from Tetramorium bicarinatum venom, which was previously shown to have a strong paralytic effect on dipteran species without cytotoxicity on insect cells. In the present study, we show that Tb11a exhibited no or low cytotoxicity toward mammalian cells either, even at high concentrations, while electrophysiological studies revealed a blockade of hKv1.3 activity. Additionally, Ta11a, an analog of Tb11a from the ant Tetramorium africanum, demonstrated similar Kv1.3 inhibitory properties. Structural analysis supports that the peptide acts on Kv1.3 channels through the functional dyad Y21-K25 and that the disulfide bridge is essential for biological activity, as reduction seems to disrupt the peptide conformation and impair the dyad. These findings highlight the importance of three-dimensional structure in channel modulation and establish Tb11a and Ta11a as promising Kv1.3 inhibitors. Future research should investigate their selectivity across additional ion channels and employ structure-function studies to further enhance their pharmacological potential. Full article

This study investigated the influence of different functional groups on the electro-optical properties of polymer-dispersed liquid crystal (PDLC) films. Twelve acrylate monomers with functional groups like amino, halogen, and double-bond were introduced into PDLC films, and twelve samples were prepared. The electro-optical properties and microstructure of the films were characterized. The results show that compared to films with amino and halogen groups, those with hydroxyl groups have the best balance of driving voltage and contrast, achieving higher contrast at lower driving voltage, making this preparation scheme ideal for low-voltage, high-contrast PDLC films. Also, in the presence of hydroxyl groups, introducing double bonds increases saturation voltage and decreases saturation. Hydrogen-bond engineering through strategically positioned hydroxyl groups in acrylate monomers optimizes PDLC performance by enabling compact polymer networks and controlled phase separation, achieving superior contrast ratios (163) and low saturation voltages (15.8 V), while amino groups induce steric limitations and dual-bond systems that disrupt hydrogen-bond efficacy, highlighting hydroxyl spatial design as critical for electro-optical optimization. Full article

The SCN9A gene, a critical regulator of pain perception, encodes the voltage-gated sodium channel Nav1.7, a key mediator of pain signal transmission. This study conducts a multimodal assessment of SCN9A, integrating genetic variation, structural architecture, and molecular dynamics to elucidate its role in pain regulation. Using advanced computational methods, I-TASSER simulations generated structural decoys of the SCN9A homology domain, producing an ensemble of conformational states. SPICKER clustering identified five representative models with a C-score of −3.19 and TM-score of 0.36 ± 0.12, reflecting moderate structural similarity to experimental templates while highlighting deviations that may underpin functional divergence. Validation via ProSA-web supported model reliability, yielding a Z-score of −1.63, consistent with native-like structures. Central to the analysis was the R1150W non-synonymous variant, a potential pathogenic variant. Structural modeling revealed localized stability in the mutant conformation but disrupted hydrogen bonding and altered charge distribution. Its pathogenicity was underscored by a high MetaRNN score (0.7978498) and proximity to evolutionarily conserved regions, suggesting functional importance. Notably, the variant lies within the Sodium-Ion-Transport-Associated Domain, where perturbations could impair ion conductance and channel gating—mechanisms critical for neuronal excitability. These findings illuminate how SCN9A variants disrupt pain signaling, linking genetic anomalies to molecular dysfunction. While computational insights advance mechanistic understanding, experimental validation is essential to confirm the variant’s impact on Nav1.7 dynamics and cellular physiology. By refining SCN9A’s molecular blueprint and highlighting its therapeutic potential as a target for precision analgesics, this work provides a roadmap for mitigating pain-related disorders through channel-specific modulation. Integrating structural bioinformatics with functional genomics, this study deciphers SCN9A’s role in pain biology, laying the groundwork for novel strategies to manage pathological pain. Full article

Disruptive events and the rapid evolution of urban energy systems highlight the need for robust methods to reconstruct critical infrastructure networks. Comprehensive, up-to-date power grid representations are essential for both researchers developing methods for analysing and optimising power systems and first responders requiring approximate data for urgent decisions. However, traditional grid reconstruction approaches often rely on incomplete data, expert knowledge, or closed datasets, limiting their utility during emergencies. This study proposes a novel automated method for reconstructing medium-voltage (MV) power grids. The novelty of the proposed method lies in combining OpenStreetMap energy and land-use data in a unified and automated framework, thereby reducing the need for expert input. The proposed method employs a systematic aggregation of data, an estimation of energy demand, and the application of algorithmic techniques to generate synthetic MV grid models that functionally represent real networks, capturing key topological features. The resulting outputs include visual representations to support decision-makers in simulating "what-if” scenarios and ensuring rapid operational awareness. In a step toward eliminating reliance on proprietary data, our approach broadens access to critical infrastructure insights across diverse urban contexts, contributing to critical infrastructure resilience and potentially supporting both energy system research and crisis management. A case study demonstrates that a medium-sized city’s MV grid can be reconstructed in minutes without expert knowledge or geographically constrained datasets, underscoring the method’s deployment potential and practical value for emergency scenarios. Full article

As renewable energy sources (RES) continue to expand and the use of power inverters has surged, inverters have become crucial for converting direct current (DC) from RES into alternating current (AC) for the grid, and their security is vital for maintaining stable grid operations. This paper investigates the security vulnerabilities of photovoltaic (PV) inverters, specifically focusing on their internal sensors, which are critical for reliable power conversion. It is found that both current and voltage sensors are susceptible to intentional electromagnetic interference (IEMI) at frequencies of 1 GHz or higher, even with electromagnetic compatibility (EMC) protections in place. These vulnerabilities can lead to incorrect sensor readings, disrupting control algorithms. We propose an IEMI attack that results in three potential outcomes: Denial of Service (DoS), physical damage to the inverter, and power output reduction. These effects were demonstrated on six commercial single-phase and three-phase PV inverters, as well as in a real-world microgrid, by emitting IEMI signals from 100 to 150 cm away with up to 20 W of power. This study highlights the growing security risks of power electronics in RES, which represent an emerging target for cyber-physical attacks in future RES-dominated grids. Finally, to cope with such threats, three detection methods that are adaptable to diverse threat scenarios are proposed and their advantages and disadvantages are discussed. Full article

Power transformers are vital components of electrical power systems, ensuring reliable and efficient energy transfer between high-voltage transmission and low-voltage distribution networks. However, they are prone to various faults, such as insulation breakdowns, winding deformations, partial discharges, and short circuits, which can disrupt electrical service, incur significant economic losses, and pose safety risks. Traditional fault diagnosis methods, including visual inspection, dissolved gas analysis (DGA), and thermal imaging, face challenges such as subjectivity, intermittent data collection, and reliance on expert interpretation. To address these limitations, this paper proposes a novel distributed approach for multi-fault diagnosis of power transformers based on a self-organizing neural network combined with data augmentation and incremental learning techniques. The proposed framework addresses critical challenges, including data quality issues, computational complexity, and the need for real-time adaptability. Data cleaning and preprocessing techniques improve the reliability of input data, while data augmentation generates synthetic samples to mitigate data imbalance and enhance the recognition of rare fault patterns. A two-stage classification model integrates unsupervised and supervised learning, with k-means clustering applied in the first stage for initial fault categorization, followed by a self-organizing neural network in the second stage for refined fault diagnosis. The self-organizing neural network dynamically suppresses inactive nodes and optimizes its training parameter set, reducing computational complexity without sacrificing accuracy. Additionally, incremental learning enables the model to continuously adapt to new fault scenarios without modifying its architecture, ensuring real-time performance and adaptability across diverse operational conditions. Experimental validation demonstrates the effectiveness of the proposed method in achieving accurate, efficient, and adaptive fault diagnosis for power transformers, outperforming traditional and conventional machine learning approaches. This work provides a robust framework for integrating advanced machine learning techniques into power system monitoring, paving the way for automated, real-time, and reliable transformer fault diagnosis systems. Full article

Electric vehicles (EVs) are rapidly replacing fossil-fuel-powered vehicles, creating a need for a fast-charging infrastructure that is crucial for their widespread adoption. This research addresses this challenge by improving the control of dual active bridge converters, a popular choice for high-power EV charging stations. A critical issue in EV battery charging is the smooth transition between charging stages (constant current and constant voltage) which can disrupt converter performance. This work proposes a novel feedforward control method using a combination of droop-based techniques combined with a sophisticated linear active disturbance rejection control system applied to a single-phase shift-modulated dual active bridge. This combination ensures a seamless transition between charging stages and enhances the robustness of the system against fluctuations in both input voltage and load. Numerical simulations using MATLAB/Simulink R2024a demonstrated that this approach not only enables smooth charging but also reduces the peak input converter current, allowing for the use of lower-rated components in the converter design. This translates to potentially lower costs for building these essential charging stations and faster adoption of EVs. Full article

This study introduces a novel uninterruptible power supply (UPS) configuration that integrates active power filter (APF) capabilities within a single-phase matrix converter (SPMC) framework. Power disruptions, particularly affecting critical loads, can lead to substantial economic damages. Historically, conventional UPS systems utilized dual separate converters to function as a rectifier and an inverter, without incorporating any power factor correction (PFC) mechanisms. Such configurations suffered from diminished power density, compromised reliability, and spatial limitations. To address these issues, this research proposes an enhanced UPS design that incorporates APF features into the SPMC. The focus of this investigation is on the efficiency of alternating current (AC) to direct current (DC) conversion and the reverse process utilizing this advanced UPS model. The SPMC is selected to supplant the rectifier and inverter units traditionally employed in UPS architectures. A novel integrated switching strategy is formulated to facilitate the operation of the UPS in either rectifier (charging) or inverter (discharging) modes, contingent upon the operational state. The performance and efficacy of the devised circuit design and switching technique are substantiated through simulations conducted in MATLAB/Simulink 2019 and empirical evaluations using a test rig. The findings demonstrate that the voltage generated is sinusoidal and synchronized with the supply current, thereby minimizing the total harmonic distortion (THD) and enhancing both the power factor and the transition efficiency of the UPS system between its charging and discharging states. Full article

Demyelinating Charcot–Marie–Tooth 4G (CMT4G) results from a recessive mutation in the 5′UTR region of the Hexokinase 1 (HK1) gene. HK participates in mitochondrial calcium homeostasis by binding to the Voltage-Dependent Anion Channel (VDAC), through its N-terminal porin-binding domain. Our hypothesis is that CMT4G mutation results in a broken interaction between mutant HK1 and VDAC, disturbing mitochondrial calcium homeostasis. We studied a cohort of 25 CMT4G patients recruited in the French gypsy population. The disease was characterized by a childhood onset, an intermediate demyelinating pattern, and a significant phenotype leading to becoming wheelchair-bound by the fifth decade of life. Co-IP and PLA studies indicated a strong decreased interaction between VDAC and HK1 in the patients' PBMCs and sural nerve. We observed that either wild-type HK1 expression or a peptide comprising the 15 aa of the N-terminal wild-type HK1 administration decreased mitochondrial calcium release in HEK293 cells. However, mutated CMT4G HK1 or the 15 aa of the mutated HK1 was unable to block mitochondrial calcium release. Taken together, these data show that the CMT4G-induced modification of the HK1 N-terminus disrupts HK1-VDAC interaction. This alters mitochondrial calcium buffering that has been shown to be critical for myelin sheath maintenance. Full article

Line outage contingencies in power distribution systems pose critical challenges, leading to disruptions, reduced reliability, and potential cascading failures. These problems include increased vulnerability, limited resilience, and the need for efficient mitigation strategies to enhance the overall system reliability and quality. This study aims to investigate, analyze, and evaluate the renewable distributed generator (RDG) allocation and sizing under N-1 line outage conditions in terms of the reliability and quality for the IEEE 30-bus benchmark power system as a case study. Under all possible N-1 line outage conditions, there were four critical N-1 line outage conditions, 19–20, 10–20, 27–29, and 27–30, which caused overloading on at least one line. The Severity Performance Index (SPI) recorded the highest value of 0.715 during the line 10–20 outage, followed by 0.683, 0.606, and 0.476 during the line F27–30 outage, line F19–20 outage, and line F27–29 outage, respectively. This indicates that the line 10–20 outage is the most critical among the line outages followed by the line 27–30 outage. During the line 10–20 outage, the crow search integrated with the particle swarm optimizer recommends allocating renewable distributed generators (RDGs) at optimal or feasible buses 14, 15, 17, 20, and 30, with suggested sizes of 26.8127 MW, 38.8986 MW, 27.9600 MW, 21.6300 MW, and 27.0184 MW, respectively. The obtained finding revealed that allocating five RDGs at optimal busbars helped keep the line loading below maximum limits and improved the voltage profiles during the N-1 line outages in the IEEE 30-bus benchmark power system. This approach enhanced the power system reliability and quality across all four N-1 scenarios. Full article

A balanced operating power system with all elements carrying normal currents and bus voltages within the prescribed limits can be disrupted due to faults within the system. Overhead transmission networks are vulnerable to the vagaries of the atmosphere and, therefore, statistically have the highest probability of fault occurrence. Quick and accurate fault detections assist in timely remedial action, offering significant economic and operational benefits. Maintaining continuous and uninterrupted supply functionality is one of the critical objectives of electric utilities for a reliable system operation. Also, identifying and locating faults is crucial to address them in time to avert the risk of cascading failures. During faults, fast electromagnetic transients associated with the current and voltage waveforms can provide valuable insights into identifying abnormal operating conditions. To analyze these non-stationary signals in both the time and frequency domains, wavelet transform (WT) has become an indispensable tool. Thanks to its ability to adapt to variable window sizes, WT provides a more accurate and detailed resolution, making it a highly useful technique for signal analysis. In this context, this paper presents the application of WT-based intelligent technique to detect and classify power system faults accurately. The transient disturbances caused by various faults are subjected to wavelet transform analysis to analyze the detail coefficients of phase currents. The maximum detail coefficients of phase currents, which differ significantly when the system experiences a fault, served as the distinguishing feature to identify different power system faults. The phase current signals are analyzed with one of the wavelets from the Daubechies 4 (db4) family to obtain detail coefficients, thus enabling the categorization of the faults. Extensive simulation tests for fault types have been conducted on the standard IEEE 5-Bus system to demonstrate the technique’s effectiveness and fault detection capability, allowing utilities to take timely protective actions. Full article

The apical dendrite of a cortical projection neuron (CPN) is generated from the leading process of the migrating neuron as the neuron completes migration. This transformation occurs in the cortical marginal zone (MZ), a layer that contains the Cajal-Retzius neurons and their axonal projections. Cajal-Retzius neurons (CRNs) are well known for their critical role in secreting Reelin, a glycoprotein that controls dendritogenesis and cell positioning in many regions of the developing brain. In this study, we examine the possibility that CRNs in the MZ may provide additional signals to arriving CPNs, that may promote the maturation of CPNs and thus shape the development of the cortex. We use whole embryonic hemisphere explants and multiphoton microscopy to confirm that CRNs display intracellular calcium transients of <1-min duration and high amplitude during early corticogenesis. In contrast, developing CPNs do not show high-amplitude calcium transients, but instead show a steady increase in intracellular calcium that begins at the time of dendritic initiation, when the leading process of the migrating CPN is encountering the MZ. The possible existence of CRN to CPN communication was revealed by the application of veratridine, a sodium channel activator, which has been shown to preferentially stimulate more mature cells in the MZ at an early developmental time. Surprisingly, veratridine application also triggers large calcium transients in CPNs, which can be partially blocked by a cocktail of antagonists that block glutamate and glycine receptor activation. These findings outline a model in which CRN spontaneous activity triggers the release of glutamate and glycine, neurotransmitters that can trigger intracellular calcium elevations in CPNs. These elevations begin as CPNs initiate dendritogenesis and continue as waves in the post-migratory cells. Moreover, we show that the pharmacological blockade of glutamatergic signaling disrupts migration, while forced expression of a bacterial voltage-gated calcium channel (CavMr) in the migrating neurons promotes dendritic growth and migration arrest. The identification of CRN to CPN signaling during early development provides insight into the observation that many autism-linked genes encode synaptic proteins that, paradoxically, are expressed in the developing cortex well before the appearance of synapses and the establishment of functional circuits. Full article

Power system disruptions can be categorized as issues with the quality of electricity brought on by voltage sags, lightning strikes, and other system-related interferences. The static transfer switch (STS) has recently emerged as the most important technology for electric power transmission, distribution, and control systems to manage power supply during power system disruption issues, particularly in cost-effectively supplying power to critical loads and sensitive loads without interruption. In this paper, for the switching between the two AC sources during the voltage disruptions issue with low transfer time, a smart static transfer switch (SSTS) based on a digital switching algorithm and Triac semiconductor switch is proposed and experimentally tested. A digital switching algorithm based on online AC voltage sensing and zero-crossing detection is proposed and implemented inside a DSP MCU. The printed circuit board (PCB) of the proposed SSTS is designed and manufactured for the experimental performance investigation with different AC input voltage conditions. A comparative study based on the advantages and disadvantages of the proposed SSTS system with the previous works is also presented. A smart static transfer switch with a transition time of less than one cycle and a digital protection technique during fault conditions is obtained in this work. Full article

Our understanding of how osteocytes, the principal mechanosensors within bone, sense and perceive force remains unclear. Previous work identified “tethering elements” (TEs) spanning the pericellular space of osteocytes and transmitting mechanical information into biochemical signals. While we identified the heparan sulfate proteoglycan perlecan (PLN) as a component of these TEs, PLN must attach to the cell surface to induce biochemical responses. As voltage-sensitive calcium channels (VSCCs) are critical for bone mechanotransduction, we hypothesized that PLN binds the extracellular α₂δ₁ subunit of VSCCs to couple the bone matrix to the osteocyte membrane. Here, we showed co-localization of PLN and α₂δ₁ along osteocyte dendritic processes. Additionally, we quantified the molecular interactions between α₂δ₁ and PLN domains and demonstrated for the first time that α₂δ₁ strongly associates with PLN via its domain III. Furthermore, α₂δ₁ is the binding site for the commonly used pain drug, gabapentin (GBP), which is associated with adverse skeletal effects when used chronically. We found that GBP disrupts PLN::α₂δ₁ binding in vitro, and GBP treatment in vivo results in impaired bone mechanosensation. Our work identified a novel mechanosensory complex within osteocytes composed of PLN and α₂δ₁, necessary for bone force transmission and sensitive to the drug GBP. Full article