Search Results (1,082)

This paper presents a comparative analysis of three magnetic-integrated LCL-derived filter configurations for suppressing high-frequency switching harmonics in avionics power-conversion systems: the integrated LLCL filter, the magnetic-integrated multi-trap LCL filter, and the magnetic-integrated trapped-LCL filter. The high-frequency harmonics considered in this study originate primarily from the pulse-width-modulated (PWM) switching process and can increase current distortion, electrical and magnetic losses, component stress, and the potential for electromagnetic interference in aircraft electrical systems. To enable a consistent comparison, the three filter configurations are evaluated within a unified analytical framework under common system-level operating conditions, while retaining their topology-specific passive and magnetic parameters according to their respective design requirements. The framework distinguishes aggregate total harmonic distortion (THD) from attenuation at targeted switching-frequency bands and incorporates the effects of resonant branches and magnetic coupling. The simulated current THD values of the LLCL, multi-trap LCL, and trapped-LCL filters are 0.82%, 0.84%, and 1.13%, respectively, while their estimated total filter losses are 24.98 W, 59.74 W, and 40.49 W. At the 1 kW operating point, these losses correspond to 2.50%, 5.97%, and 4.05% of rated power, respectively. The results show that the LLCL filter achieves the lowest aggregate THD and estimated loss under the investigated conditions, whereas the multi-trap and trapped-LCL configurations provide additional capability for targeted attenuation of selected switching-frequency components through their resonant structures. Hardware-in-the-loop (HIL) results further support the electrical filtering and dynamic behavior of the investigated concepts. The comparison demonstrates that minimum THD, minimum loss, targeted switching-harmonic attenuation, and magnetic integration are distinct design objectives; therefore, topology selection should be based on the specific requirements and constraints of the intended avionics application. Full article

External steep-front transient overvoltages may introduce high-frequency electromagnetic disturbances into modular multilevel converter-based high-voltage direct current (MMC-HVDC) systems, resulting in additional transient voltage stresses on converter valves and their sub-modules. This paper investigates the propagation, coupling, and transient voltage distribution characteristics of external high-frequency disturbances in MMC converter valves using a multi-scale wideband equivalent model covering the “sub-module–converter valve–converter station” hierarchy. A wideband equivalent model of a 4.5 kV/3 kA press-pack insulated gate bipolar transistor (IGBT)-based sub-module is developed and integrated with the distributed parasitic parameters of the valve tower and the high-frequency characteristics of converter-station components. To investigate the converter-valve response under different transient conditions, a representative lightning impulse is considered as an engineering transient condition, while a controlled fast-front impulse is employed to investigate the intrinsic high-frequency propagation and resonance characteristics of the distributed converter-valve network. Simulation results demonstrate that external transient disturbances can propagate into MMC converter valves through grounding parasitic capacitances and distributed coupling paths, resulting in additional differential-mode transient voltage stresses at sub-module terminals. Sub-modules closer to the disturbance source experience higher transient voltage peaks and larger dv/dt values. Moreover, multiple local resonance bands are identified within the valve tower, with high-frequency oscillatory components above 10 MHz being strongly influenced by the distributed parasitic network. Parameter analysis further indicates that the sub-module stray inductance has an important influence on the magnitude and oscillatory characteristics of the induced transient voltage. The proposed multi-scale modeling approach provides a practical method for evaluating high-frequency transient voltage stresses in MMC-HVDC converter valves and provides theoretical support for insulation coordination, converter-valve structural optimization, and transient reliability design of HVDC transmission systems. Full article

Transcranial magnetic stimulation (TMS) enables non-invasive, focal modulation of cortical circuits by inducing electric currents in the brain through electromagnetic induction, thereby influencing neuronal excitability and synaptic plasticity. High inter- and intra-individual variability has led, however, to moderate efficacy and reproducibility of stimulation and treatment protocols, motivating a shift toward brain-state-dependent stimulation. Over the past decade, real-time phase-triggered EEG-TMS has established the oscillatory phase—particularly focusing on the sensorimotor mu rhythm—as a key determinant of cortical excitability and plasticity modulation. The field, however, remains largely confined to univariate, sensor-space analyses of local mu-rhythm phase, missing large-scale network dynamics. Recent advances in online EEG source reconstruction and multivariate machine and deep learning (ML/DL) approaches have begun to move beyond local phase toward whole-brain, network-level state estimation, achieving encouraging preliminary accuracies in predicting trial-by-trial cortical excitability, with promising applications in network-dysregulation conditions such as chronic pain. Integrating source-space reconstruction and individual biological variability, and adaptive ML/DL pipelines into closed-loop frameworks promises to move beyond generic stimulation protocols toward selective, network-targeted neuromodulation tailored to the individual’s dynamic brain state. Against this background, this review provides a critical overview of current achievements and limitations, while highlighting emerging methodological directions toward fully brain-state-adaptive and network-targeted EEG-TMS. We further present an illustrative use case of adaptive EEG-TMS for pain modulation, where treatment responses remain heterogeneous and the relevant dynamics are distributed across networks, and which therefore stands to gain most from individualized, network-targeted protocols. Full article

Drive systems for robot joints must provide a high gear ratio within limited axial space. When two magnetic gears are axially stacked to form a two-stage transmission, the axial lengths of the individual stages accumulate. This paper therefore proposes a magnetically geared machine (MGM) comprising a radial-flux magnetic gear and an axial-flux magnetic gear. The permanent-magnet synchronous motor and the radial-flux magnetic gear occupy the inner space of the axial-flux magnetic gear, while shared rotors connect the three electromagnetic components. For this topology, the magnetic field modulation and torque relationships are derived, and the main design parameters are determined through two-stage optimization and three-dimensional transient finite-element analysis. The results show that the air gaps of both magnetic gears contain the required working harmonics and that the steady-state torques of the three rotors follow the two-stage transmission relationship. The optimized design achieves an overall gear ratio of 84.64 and a maximum transferable torque of $1098.97$ N m. At this operating point, the volumetric torque density based on the overall cylindrical envelope volume is $328.00$ N m L⁻¹. Full article

This paper develops a physics-informed neural network (PINN) framework for the lossy telegrapher equations and presents a coupled IEEE 738 thermal balance formulation intended as a structural blueprint for environmentally aware transmission-line digital twins. The baseline electromagnetic PINN maps $(x,t)\mapsto (\widehat{V},\widehat{I})$ and is empirically validated against a finite-difference time-domain (FDTD) reference solver. An augmented parametric framework ${\mathcal{N}}_{\mathit{\theta }}:(x,t,\mathbf{e})\mapsto (\widehat{V},\widehat{I},{\widehat{T}}_{\mathrm{line}})$ is mathematically derived, wherein the ambient vector $\mathbf{e}$ modulates a temperature-dependent resistance $R^{\prime }\left(T_{\mathrm{line}}\right)$ and couples to the telegrapher residuals via a non-linear thermal balance residual $r_T$. Two further constraints, a sag-tension consistency residual $r_S$ and a dynamic line rating (DLR) one-sided penalty $r_{\mathrm{DLR}}$, are formulated for completeness but are explicitly designated as architectural extension hooks running at zero weight (${\omega }_{\mathrm{th}}={\omega }_{\mathrm{sag}}={\omega }_{\mathrm{dlr}}=0$) within the reported microscale numerical benchmarks. Consequently, the empirical validation presented herein strictly concerns the baseline electromagnetic telegrapher PINN. The numerical results demonstrate robust $L^2$ field convergence against FDTD reference data, highly structured error accumulation along physical characteristic curves, and reliable recovery of strongly observable parameters $(L^{\prime },C^{\prime })$ from sparse, noisy terminal measurements. Conversely, the recovery of loss parameters $(R^{\prime },G^{\prime })$ exhibits a severe structural weak identifiability that precisely matches the analytical predictions of a comprehensive Fisher Information Matrix analysis. The core contributions of this work are primarily methodological: (i) a dimensionally consistent, corrected residual formulation for the lossy telegrapher equations; (ii) an explicit positioning of the proposed multi-physics framework within the parametric PINN literature; (iii) a Fisher information identifiability diagnostic illustrating the near-degeneracy of baseline parameter estimation; and (iv) a clean algorithmic separation of forward training, inverse parameter identification, and prospective online updates. Full article

Target recognition methods based on feature extraction of bistatic radar polarimetric characteristics face the challenge of feature variation caused by independent rotation of transmit and receive polarization bases. Based on Huynen decomposition and Cameron decomposition theories, this paper rigorously derives ten types of bistatic polarization roll-invariants covering scattering intensity, polarization modulation capability, scattering mechanism, symmetry and reciprocity. Simulations are systematically carried out on dihedral, sphere and trihedral structures, followed by anechoic chamber experimental verification using a self-built bistatic full-polarimetric electromagnetic scattering measurement system. Simulation and experimental results demonstrate that all proposed invariants strictly satisfy roll-invariance under independent rotation of transmit and receive polarization bases. Polarization roll-invariants of different structures exhibit distinct variation laws with bistatic angles, which can provide robust and reliable feature support for bistatic polarimetric radar target recognition. Full article

Glioblastoma multiforme (GBM) is an aggressive primary brain tumor characterized by dysregulated cellular signaling and resistance to apoptosis. Pulsed electromagnetic field (PEMF) exposure has been reported to modulate cancer-related cellular processes, while resveratrol (RES), a natural polyphenol, exhibits notable antiproliferative and pro-apoptotic actions. Here, we investigated whether 75 Hz PEMF potentiates RES-mediated apoptosis in human glioblastoma U87-MG cells by examining key molecules involved in apoptotic signaling and the transcriptional responses of PI3K/AKT/mTOR pathway-related genes. U87-MG glioblastoma cells and non-tumour human astroglial SVG-P12 cells were cultured and divided into the following six groups: (I) untreated cells; (II) RES-treated cells; (III) temozolomide (TMZ)-treated cells; (IV) PEMF-exposed cells; (V) cells treated with RES followed by PEMF exposure; and (VI) cells treated with TMZ followed by PEMF exposure. Cell viability was assessed in both cell lines by alamar blue assay, and selectivity indices were derived from the resulting IC50 values. Apoptotic responses and gene expression profiles were assessed in U87-MG cells by flow cytometry and qRT-PCR, while selected apoptosis-related proteins were evaluated by Western blotting. RES treatment induced stronger cytotoxic effects than TMZ in U87-MG cells, and this response was markedly enhanced following PEMF exposure, the IC₅₀ falling from 33.64 to 10.53 µg/mL. In SVG-P12 astroglia the IC₅₀ of RES rose from 17.95 to 98.31 µg/mL under the same exposure, so that the selectivity index of RES increased from 0.53 to 9.34, whereas that of TMZ remained essentially unchanged (1.54 versus 1.50). Combined RES and PEMF treatment significantly increased both early and late apoptosis. Molecular analyses revealed upregulation of pro-apoptotic markers accompanied by an increased Bax/BcL-2 ratio, consistent with protein-level changes. Transcripts of PI3K/AKT/mTOR pathway-related components were also elevated relative to untreated cells, but to a markedly lesser extent than the apoptotic markers. PEMF exposure significantly enhances the pro-apoptotic effects of RES in glioblastoma cells while relatively preserving SVG-P12 cell viability, supporting further investigation of this combination as a potential adjuvant approach. Full article

Ultraviolet (UV) exposure accelerates skin aging through wavelength-dependent effects. Ultraviolet A (UVA) penetrates relatively deeply into the dermis and promotes oxidative stress and extracellular-matrix remodeling, whereas ultraviolet B (UVB) is absorbed predominantly in the epidermis and produces direct DNA damage and inflammation; nevertheless, UVB can also alter dermal fibroblast matrix metabolism in experimental models. The present study specifically used UVB irradiation (peak wavelength, 306 nm) to examine inflammatory collagen loss. UVB-induced cellular injury activates the NOD-like receptor family pyrin domain-containing 3 (NLRP3) inflammasome, leading to caspase-1-dependent maturation of interleukin-1β (IL-1β), activation of nuclear factor-κB (NF-κB), and matrix metalloproteinase (MMP)-associated collagen degradation. Pulsed electromagnetic field (PEMF) stimulation is a non-optical biophysical modality that may modulate inflammatory and matrix responses. Here, we characterized the effects of PEMF exposure using Corefacial on UVB-induced dermal collagen loss in association with the A2A adenosine receptor (A2AAR)/cyclic adenosine monophosphate (cAMP)/protein kinase A (PKA) signaling pathway. In UVB-exposed fibroblasts, PEMF restored A2AAR and PKA protein levels, cAMP levels, and the pNLRP3/NLRP3 ratio, similar to the effects of the A2AAR agonist CGS-21680. PEMF also reduced apoptosis-associated speck-like protein containing a caspase-recruitment domain (ASC), caspase-1 activation markers, IL-1β secretion, NF-κB nuclear translocation, and MMP2/MMP3/MMP9 expression and increased the levels of collagen I and collagen III. In the in vivo UVB model, PEMF similarly increased A2AAR and PKA protein levels, cAMP levels, and the pNLRP3/NLRP3 ratio, while attenuating IL-1β/NF-κB/MMP-associated responses and preserving dermal collagen. These findings are consistent with, but do not prove, involvement of A2AAR/cAMP/PKA-related signaling and inhibitory NLRP3 phosphorylation in the PEMF response. These results should be interpreted as evidence from a UVB-specific experimental model rather than a comprehensive model of solar photoaging. Full article

Introductory and intermediate electrical-engineering education commonly models fundamental circuit and device parameters, including inductance, capacitance, resistance, permeability, permittivity, conductivity, characteristic impedance, transformer turns ratio, machine constants, amplifier gain, resonant frequency, propagation velocity, and mutual inductance, as numerical constants. While this approximation is valid within the intended small-signal operating regime, it becomes methodologically incomplete when these coefficients exhibit measurable state dependence. This paper presents a comparative audit of thirteen such coefficients by systematically contrasting their textbook formulations with the established engineering literature and interpreting the results through two complementary frameworks: the JCGM GUM-6:2020 measurement-model methodology for omitted effects, and the Heckmann–Nye/Gasik multidomain coupling architecture for multi-axis physical interactions. The analysis demonstrates that mainstream engineering practice routinely exploits state-dependent coefficients without invoking new physical laws, and that relaxing the constant-coefficient assumption naturally introduces physically meaningful terms, including the inductive contribution $I\mathrm{d}L/\mathrm{d}t$, the capacitive counterpart $V\mathrm{d}C/\mathrm{d}t$, and the mutual-inductance term $i_2\mathrm{d}M/\mathrm{d}t$. The principal scientific contribution is the development and experimental validation of a unified theoretical and engineering framework for high-power resonant transformers and orthogonal Metglas AMCC-1000 paraformers. The proposed approach combines a new physics-based modal theory of octave ($2:1$) parametric excitation with simultaneous optimization of magnetic-core resonance, electrical resonance, nonlinear inductance modulation, resonant conductor lengths selected as integer multiples of the operating resonant wavelength, multi-stranded high-frequency Litz-wire windings, resonant capacitor synthesis, and the nonlinear magnetic characteristics of the AMCC-1000 amorphous core. The modal analysis demonstrates how coupled resonant eigenmodes and engineered state-dependent inductance can be used to satisfy the conditions for stable octave parametric excitation. Experimental results obtained from both the symmetric two-leg resonant transformer and the orthogonal paraformer are in close agreement with analytical predictions and numerical simulations, thereby validating both the proposed electromagnetic design methodology and the underlying modal theory. Full article

In this study, the double-neutral (3P + 2N) configuration, considered a traditional solution for busbar systems subjected to overcurrent and thermal stresses under harmonic loads, and alternative cross-sectional expansion (from 6 mm × 55 mm to 6 mm × 65 mm) scenarios are investigated using a multidisciplinary approach. In this context, the electrical, electromagnetic, current density distributions, and magnetic flux densities (B_max) of the systems are modeled in the COMSOL Multiphysics® (AC/DC Module 6.2 version) environment; the obtained q″ (W/m³) loss maps were transferred to FLOEFD convective airflow (CFD) simulations as volumetric heat sources, and steady-state electro-thermal analyses were performed. Convergence tests were conducted with the BiCGStab solver to ensure numerical stability, solver convergence, and spatial grid independence, and high accuracy was obtained at a margin of error of 3.5222 × 10⁻⁴. The findings showed that the proximity effect, due to the close placement of the pair of neutral conductors at the 150 Hz harmonic frequency, increased the current density to 4.68 A/mm² and turned the neutral line into an additional heat source. In contrast, in the 4-conductor scheme where all conductor cross-sections were increased by 18.18%, the magnetic flux density at 150 Hz was suppressed from 27.21 mT to 23.50 mT, and the current density was distributed more homogeneously, optimizing the temperature rise limits (ΔT). Furthermore, the techno-economic cost analysis conducted revealed that, under premium scenarios for LME raw copper and processed bar copper, the application of increased cross-sectional area offered an optimization that was approximately 5.77% more economical per meter (approximately $36 USD for a standard 3 m length) compared to the double-neutral configuration. Consequently, it has been proven that in BTS designs, not only total harmonic distortion (THD) but also the triplen harmonic ratio, frequency-dependent AC resistance (R_ac) variations, and material mass–cost balance should be considered together. Full article

Advances in navigational bronchoscopy, robotic platforms, and intraprocedural imaging have transformed bronchoscopy from a diagnostic modality into a potential therapeutic platform for localized treatment of lung cancer. These developments are particularly relevant for patients who are medically inoperable, have limited pulmonary reserve, or require lung-sparing treatment strategies. This narrative review summarizes current evidence regarding bronchoscopic ablative technologies and intratumoral therapies for lung cancer. We discuss technological foundations including robotic bronchoscopy, electromagnetic and shape-sensing navigation, cone-beam computed tomography, augmented fluoroscopy, and radial endobronchial ultrasound. Available ablative modalities, including radiofrequency ablation, microwave ablation, cryoablation, photodynamic therapy, and pulsed electric field ablation, are reviewed alongside bronchoscopically delivered intratumoral chemotherapy, immunotherapy, and gene-based therapies. Early clinical studies demonstrate high technical success rates and favorable safety profiles for multiple bronchoscopic ablative approaches, with substantially lower rates of pleural complications compared with percutaneous techniques. Intratumoral therapies enable delivery of high local drug concentrations while minimizing systemic toxicity and may enhance antitumor immune responses through modulation of the tumor microenvironment. Emerging evidence suggests potential synergy between local ablation and immunotherapeutic strategies. However, available data remain limited by small sample sizes, heterogeneous treatment protocols, and a lack of randomized comparative studies. Bronchoscopic ablation and intratumoral therapies represent promising additions to the thoracic oncology armamentarium. Continued advances in navigation, imaging, and therapeutic delivery systems are enabling increasingly precise, minimally invasive interventions. Prospective clinical trials are needed to define optimal patient selection, procedural strategies, and integration with surgery, radiation, and systemic therapies within multidisciplinary lung cancer care. Full article

Active jamming in complex electromagnetic environments can severely degrade radar remote sensing imaging and target detection, especially when deceptive and suppressive jamming components coexist. Existing deep learning methods usually formulate jamming recognition as a closed set classification task, which provides limited information about component superposition, time-frequency localization, and physical jamming parameters. To address these limitations, this paper proposes a prior-guided lightweight dual-task network for structured composite active jamming cognition. The proposed framework extracts multi-domain handcrafted features and decision tree based coarse priors from the received signal, and fuses them with short-time Fourier transform (STFT) time-frequency images through a confidence-gated MobileViT_CA-based network. The recognition branch predicts the jamming family, fine-grained class, and composite attributes, while the segmentation branch estimates component masks for copy, convolution, and noise components. A FiLM-conditioned mask refinement module further improves mask continuity and boundary quality, enabling the extraction of physical parameters such as bandwidth, center frequency, coverage duration, delay, slice width, and repetition interval. Experiments on a 22-class active jamming dataset show that the proposed method, built on a 1.92 M-parameter MobileViT_CA backbone, achieves 93.78% overall classification accuracy, 96.49% jamming family accuracy, and 89.17% accuracy on the 12 composite classes. The FiLM-conditioned mask refinement module improves the test-set mIoU from 67.55% to 82.93%, and most representative physical parameters are estimated with relative errors below 15%. Full article

Multilayer graphene-coated Co-based amorphous wires were fabricated by repeated PMMA-assisted transfer processing. Torsional deformation was introduced at different stages of shell construction to investigate the influence of fabrication sequence on the giant magnetoimpedance (GMI) effect. For the non-torsion series, the maximum GMI ratio increased from 165% for the as-spun wire to 302% after three graphene-coating cycles. A further enhancement to 353% was achieved when torsion was introduced after partial shell formation, whereas only a marginal improvement was observed when torsion was applied to bare amorphous wires. Magnetic measurements revealed concurrent reductions in coercivity and peak field together with a systematic evolution of the optimal operating frequency. These correlated changes suggest that progressive shell construction modifies the near-surface magnetic state via electromagnetic boundary modulation, while torsion introduced after partial shell formation provides additional interfacial strain tuning of the graphene-modified near-surface magnetic state, further optimizing low-field circumferential permeability. The results indicate that fabrication-sequence control provides an effective approach for tailoring the GMI response of composite amorphous wires and offers potential for the development of high-sensitivity magnetic sensing devices. Full article

Existing metasurface-based radar countermeasures commonly manipulate echoes from metasurface-covered regions, whereas protecting exposed scattering centers that cannot accommodate metasurfaces remains challenging. This paper presents a multi-region time-coding metasurface (MRTCM) architecture for coherent target cancellation and deceptive jamming. The proposed system uses multiple independently controlled metasurface regions distributed over available platform surfaces. Each region generates zeroth-order and higher-order harmonic components through periodic phase modulation, and these components coherently combine with echoes from uncovered areas. The zeroth-order component is invariant under cyclic shifts of the coding sequence, enabling stable cancellation during multi-pulse coherent processing without locking radar-pulse arrival to the start of the coding cycle. Higher-order harmonics can shift the apparent range of the metasurface response and support cancellation at range-separated cells, but require accurate timing and synchronization. Numerical simulations demonstrate more than 40 dB suppression in high-resolution range profiles and validate the cancellation behavior under moving-target detection processing. The MRTCM architecture therefore provides a theoretically grounded framework for electromagnetic protection when full metasurface coverage is impractical. Full article

Unlike conventional models that typically rely on a single memristive synapse, this study uniquely proposes a novel 5D fractional-order memristive Hopfield neural network (FOMHNN) modulated by dual memristors to simultaneously emulate internal synaptic plasticity and external electromagnetic radiation effects in brain-like computing. Analytically, the FOMHNN features multiple parallel lines of equilibria with double-zero eigenvalues, rigorously proving the generation of hidden attractors. The continuous dynamical behaviors are systematically evaluated using the Adomian Decomposition Method (ADM), revealing rich phenomena including transient chaos, grid multi-scroll hidden attractors, and frequency-controllable extreme multistability with fractal-like basin boundaries. The theoretical model is physically validated on a Field Programmable Gate Array (FPGA) platform, demonstrating high precision and ultra-low power consumption. To bridge theoretical dynamics with cryptographic applications, a novel pseudo-random number generator is designed. By incorporating a chaotic derivative extractor, the generated sequences significantly reduce topological periodicity, successfully passing all rigorous NIST SP 800-22 statistical tests. Furthermore, an adaptive color image encryption scheme is developed, utilizing bidirectional feedback diffusion and least significant bit (LSB) key embedding. Security analyses confirm that the cipher, under the fractional order $q=0.95$, achieves near-ideal information entropy, optimal resistance against differential attacks, with NPCR and UACI values reaching 99.6114% and 33.4910%, both extremely close to their theoretical ideals (99.6094% and 33.4635%), and robust resilience against noise. Ultimately, the FOMHNN provides a highly secure and physically realizable chaotic source for advanced secure communications. Full article