This study proposes and numerically investigated a high-sensitivity two-dimensional photonic crystal temperature sensor using a hexagonal silicon lattice. The design features a resonant microcavity coupled with two quasi-linear waveguides to enhance light-matter interactions and optimise the thermo-optic response. Rigorous finite-difference time-domain (FDTD) simulations indicate that the sensor achieves a high thermal sensitivity of S_T = 105 pm/° C, accompanied by an excellent linear fitting coefficient. Furthermore, the optimised cavity demonstrates a high quality factor of Q =7739.5 and a narrow resonant linewidth, resulting in an ultra-low detection limit. With an ultra-compact footprint of 62.73 μm², the sensor is fully compatible with standard silicon-on-insulator (SOI) CMOS fabrication processes. These attributes render the proposed device a promising candidate for high-precision, dense thermal monitoring in integrated photonic circuits, lab-on-chip devices, and environmental sensing applications.

This paper describes the design methodology of a compact multiband microstrip patch antenna intended for next-generation wireless communication applications. The proposed antenna operates over seven distinct frequency bands: 1.25-1.32 GHz, 2.30-2.44 GHz, 2.50-2.75 GHz, 2.92-3.25 GHz, 3.40-3.65 GHz, 3.70-4.23 GHz, and 4.70-6.0 GHz. These operating bands support a wide range of wireless services, including LTE, 5G communications, Wi-MAX, ISM applications, radar systems, and broadband wireless communications. Multiband performance is achieved through the incorporation of three strategically placed slits in the radiating patch along with a square split-ring resonator (SSRR). By adjusting the dimensions of the slits and the position of the SSRR, the operating frequency bands can be effectively tuned. The proposed antenna occupies a compact footprint of 40 × 40 mm² and consists of a radiating patch, a partial ground plane, and an SSRR structure. Simulation results demonstrate resonant frequencies at 1.3, 2.38, 2.66, 3.0, 3.5, 4.2, 4.9, and 5.7 GHz. Owing to its compact size, multiband capability, and simple structure, the proposed antenna offers advantages in terms of reduced cost, lower system complexity, and miniaturization, making it suitable for modern wireless communication systems.

Due to the high electrical conductivity, relative permittivity, and magnetic permeability of seawater, the propagation behavior of electromagnetic fields differs significantly from that in air. The conductive nature of seawater causes strong eddy current loss and magnetic field attenuation, thereby reducing the effective coupling coefficient and resulting in frequency detuning between the transmitter and receiver coils. Moreover, the marine environment introduces parasitic impedance paths and additional energy dissipation due to the conductive medium, which further decreases transmission efficiency. These unique electromagnetic characteristics make the design and optimization of wireless power transfer (WPT) systems in seawater more complex and challenging than in air, motivating this study to develop and analyze a dual-receiver WPT architecture that improves midrange transmission efficiency under underwater conditions. To address this issue, a single-transmitter dual-receiver (1TX-2RX) WPT system operating in the 300-550 kHz frequency range is designed and implemented. Experimental results demonstrate that, under midrange transmission in seawater, the efficiency of the proposed 2RX architecture improves markedly from 12% in the 1RX system to 25%, while maintaining stable output performance under various receiver coil misalignment conditions. In addition, compared with operation in air, the optimal operating frequency of the 2RX system in seawater shifts leftward from approximately 460 kHz to 410 kHz. To better characterize the impact of seawater on transmission performance, complex impedance and mutual inductance parameters are incorporated into the conventional circuit model, enabling effective representation of the additional losses and coupling attenuation induced by the conductive medium. The predicted load voltage is consistent largely with the experimental measurements, validating the accuracy and applicability of the proposed modeling approach. Overall, this study not only verifies experimentally the feasibility of improving midrange transmission efficiency through a dual-receiver architecture but also establishes theoretically a circuit modeling method suited better for seawater environments, providing useful insights for the design and optimization of marine WPT systems.

Uncertainty quantification (UQ) is an important means of characterizing how input-parameter fluctuations affect electromagnetic responses, and it provides a theoretical basis for performance prediction, reliability evaluation, and robust optimization in computational electromagnetics. For high-cost full-wave electromagnetic simulations, the least-squares support vector regression (LSSVR) surrogate model can improve the efficiency of computational electromagnetics UQ within a reasonable accuracy range because of its small-sample learning and nonlinear fitting capabilities. However, the sampling strategy directly affects the accuracy of the surrogate model. Conventional Latin hypercube sampling (LHS) allocates sampling resources equally among all dimensions, which may waste computational resources in LSSVR-based UQ. The paper proposes an LSSVR surrogate-model-based UQ method incorporating a hierarchical dimensionality reduction sparse grid strategy (LSSVR-DRSG-H) to prioritize the allocation of computational resources to highly sensitive input parameters. Validation results from a case study on human head electromagnetic exposure demonstrate that, compared with the conventional LSSVR, which achieves an MEAM of 0.8391 using 100 full-wave simulations, the proposed LSSVR-DRSG-H attains a higher MEAM of 0.8530 with only 85 full-wave simulations.

The black-box nature of machine learning (ML) models limits their adoption in industrial terahertz (THz) inspection systems where decision transparency is mandatory. We present a SHAP-based explainability framework for THz classification of five insulating materials using a 636-dimensional feature set (625 spectral channels plus 11 morphological descriptors) benchmarked across 11 classifiers. LightGBM achieved the highest performance (Macro F1 = 86.84%, Accuracy = 87.18%) and was selected for in-depth SHAP analysis and four validation experiments. SHAP-guided feature selection showed that 50 features (7.9% of the space) already match the full baseline and are the smallest tested subset that does so. Cross-model analysis showed Gradient_Std to be the single highest-ranked SHAP feature for LightGBM, XGBoost, and Random Forest alike, confirming its discriminative role to be a property of the data rather than of a single learner. Four SHAP-identified spectral windows (113 channels, 18.1%) combined with morphological features retained 95.7% of full-spectrum performance (F1 = 83.07%). A noise robustness sweep from 60 dB to 5 dB SNR, assessed against an explicit reliability criterion (Macro F1≥95% of each subset's own noise-free value), places the minimum usable SNR at 30 dB for the full feature set, shows that the morphological descriptors degrade first (falling below their criterion at 50 dB when used alone), and supports a 40 dB design margin. Engineered morphological descriptors contributed 39.8× more per feature than raw spectral channels. These results provide actionable guidance for compact narrowband sensor design and edge deployment in industrial insulation inspection.

To improve prediction accuracy for lower band-edge frequencies of ultra-wideband (UWB) printed monopole antennas, we propose a knowledge-based artificial neural network (KBANN) method. This approach uses antenna geometric parameters as inputs and introduces the lower band-edge frequency calculated from empirical formulas as prior knowledge into the neural network, integrating electromagnetic knowledge with machine learning. We construct a simulation dataset by performing electromagnetic simulations on antennas with various shapes and feed locations for model training and evaluation. Experimental comparisons show that the proposed knowledge-based artificial neural network achieves higher prediction accuracy and faster convergence than the empirical formula and data-driven models without prior knowledge, while maintaining lower prediction errors under limited-data conditions. Shapley additive explanation (SHAP) analysis further shows that prior knowledge contributes to the model predictions with the dominant antenna geometric parameters. The proposed method provides an efficient approach for lower band-edge frequency prediction of ultra-wideband antennas.

To effectively improve the dynamic prediction efficiency of external interference coupling at the airborne antenna end of the quadrotor unmanned aerial vehicle (UAV), and realize the dynamic analysis of electromagnetic interference (EMI) of the quadrotor UAV, we proposed a novel two-dimensional dynamic electromagnetic interference (2D-DEMI) prediction method based on bi-cubic interpolation. By using bicubic interpolation to restore the interference-coupling voltage at the antenna end, the number of samples can be reduced effectively, and prediction can be accelerated. Then, the coupling-voltage database at the antenna end is established by predicting the results. Finally, we evaluated the effectiveness and accuracy of the proposed method through experiments. The results show that the CPU time can be reduced by more than 80% using bi-cubic interpolation algorithm. According to the measured results, the prediction root mean squared error (RMSE) of dynamic electromagnetic interference is just 1.6. The results indicate that the proposed method can rapidly predict the dynamic electromagnetic interference of the quadrotor UAV.

Lightning pulses are characterized by a wide coverage range, short duration, and high intensity. They can induce transient electromagnetic interference (EMI) on sagging high-voltage lines above the ground, posing a serious threat to the secure operation of power systems. In this paper, a random rough ground surface is simulated using the Monte Carlo method. The catenary function is employed to model the geometry of sagging high-voltage lines. The time-domain waveform of the lightning pulse is obtained based on the discharge current of a multi-component lightning cloud-to-ground stroke. The transient induced currents and power responses of three-phase transmission lines and connected loads under lightning excitation are numerically calculated. The effects of rough surfaces with different root-mean-square heights and tower heights configurations on electromagnetic interference characteristics are investigated. The broadband lightning interference characteristics are comprehensively obtained, providing a theoretical basis for the electromagnetic protection design of transmission lines above practical ground surfaces.

This study proposes an input-output waveform-synthesis method for high-efficiency power amplifiers (PAs) operating at multiple power levels. A power-dependent complex input-nonlinearity factor captures gate-voltage distortion caused by the nonlinear gate-source capacitance, linking input second-harmonic impedance to conduction interval and drain-current harmonics. The theoretical high-efficiency load-impedance regions are derived from the prescribed waveforms at selected input-power levels within 27-30 dBm. Their intersection defines common impedance targets for synthesizing a fixed harmonic-control network. To validate the proposed method, this work designs and fabricates a hybrid continuous mode (HCM) power amplifier centered at 3.5 GHz. Under continuous-wave (CW) excitation at 3.5 GHz, the power amplifier achieves a drain efficiency (DE) of 78.2%, a power-added efficiency (PAE) of 72.2%, an output power of 40.1 dBm, and a gain of 11.1 dB. Over 3.35-3.65 GHz, the measured DE ranges from 68.8% to 78.2%.

The proposed CP antenna element employs a microstrip feed and a 45° rectangular slot to excite two orthogonal modes with an approximately 90° phase difference, realizing circular polarization. Based on this element, a four-port CP MIMO antenna is constructed, and a 5 × 5 metasurface array (M-array) is integrated into the ground plane to suppress mutual coupling between adjacent antenna elements. The introduced M-array provides additional electromagnetic-wave control paths and suppresses surface-wave propagation between adjacent antenna elements, reducing mutual coupling and improving the radiation performance of the CP MIMO antenna. At 10.8 GHz, the dimensions of the CP MIMO antenna are 32 mm × 32 mm × 1.6 mm. Simulated results show that the CP MIMO antenna with the M-array offers a frequency range of 20.6% (10.5 to 12.7 GHz), an inter-port isolation exceeding 40 dB with a peak value of approximately 64 dB, a 4.7% overlapping 3 dB axial ratio bandwidth from 10.5 to 11 GHz, and a high gain of 9.75 dBi. Diversity metrics ensure good diversity performance, including an envelope correlation coefficient (ECC) below 0.001, a diversity gain (DG) of approximately 10 dB, a channel capacity loss (CCL) below 0.2 bits/Hz, and a total active reflection coefficient (TARC) below -10 dB. The proposed CP MIMO antenna operates over the 10.5-12.7 GHz frequency range, which spans the upper portion of the X-band and the lower portion of the Ku-band. The measured results show good agreement with the simulated ones, validating the proposed CP MIMO antenna for radar applications.

This paper presents the design and optimization of a wideband filtering antenna (filtenna) for UWB applications. The design combines a wideband antenna and a feed-line-mounted band-stop filter (BSF) to suppress Wi-Fi (5-6 GHz) interference while keeping the design compact and simple. This antenna is built on a 32 × 32 mm² FR4 substrate with a partial ground plane and is embedded with a circular ring resonator in the feed line to obtain the desired rejection characteristics. The antenna was designed and simulated using CST Studio Suite. The outcome revealed that the designed filtenna has a wide operating range of 2.78-11.79 GHz with a targeted rejection band around 5-6 GHz. deep resonances are observed at 3.35 GHz and 7.40 GHz, with reflection coefficient of -23.85 dB and -55.14 dB, respectively indicating good impedance matching outside the rejected band. The filtenna was fabricated and experimentally characterized in terms of S₁₁, showing the intended band-rejection behavior with some differences between the simulated and measured response. A parametric study of the ring dimensions shows how the position and bandwidth of the rejection band can be tuned while the UWB response outside the notch is preserved. The filtenna was fabricated, and its measured S₁₁ confirms the band-rejection behavior, with some differences from the simulated response. The results show that a compact feed-line ring resonator is a simple way to introduce WLAN rejection into a UWB antenna, making the design a candidate for sub-6 GHz and IoT applications.

Accurate photovoltaic (PV) power forecasting requires both meteorological information and a representation of inverter operating states. This study develops a physics-informed DT-LSTM framework in which a reduced-order thermoelectric digital twin converts measured PV power, ambient temperature, wind speed, and irradiance into estimated loss power, thermal load, equivalent temperature, and temperature rise. Field power and weather records from January to June 2024 are aligned causally and divided chronologically into training (January 1-April 15), validation (April 16-30), main testing (May), and external testing (June) periods. At a 5 min resolution over the extended 07:00-22:00 window, DT-LSTM achieves MAE/RMSE values of 65.90/132.12 kW in the main test and 67.07/124.52 kW in the external test, compared with 72.57/137.77 kW and 73.10/130.12 kW for LSTM. The estimated thermal states are model-derived variables rather than measured device temperatures; accordingly, the results demonstrate forecasting utility and physical consistency, not direct temperature-field validation. The study provides a physics-informed virtual-sensing forecasting framework and identifies controlled multi-seed ablation and measured thermal validation as future work.

The highly accurate and computationally advantageous nonstandard finite difference time domain (NS-FDTD) method is extensively used to study wave propagation through low-loss media. While applying this method in high-loss cases like metals, it is found that the algorithm fails to converge properly. In the present study, we address these convergence-related issues by analyzing the stability function for a fixed discretization of the computational domain. This novel approach to the NS-FDTD method is verified by exposing a metallic reflector slab to an incident sinusoidal electromagnetic wave, and the results are compared with those of the S-FDTD method. This approach provided a well-defined field distribution at a much lower discretization than that of the S-FDTD algorithm, giving a great advantage of much reduction in computational cost. Hence, this method finds application in simulating, accurately and precisely, composite high-loss media, including trending negative medium parameter structures like metamaterials.

Unimodal remote-sensing data is susceptible to interference such as illumination changes and texture loss. Visible and infrared images have respective limitations in object detection, which multimodal fusion can address. To address these challenges, this study proposes a Triple-stage Mamba Cross-modal Fusion Network (TMCFNet) for cross-modal remote-sensing object detection. The model performs cross-modal image fusion at the input stage to preserve each modality's inherent information while keeping computational cost low. It consists of three key components: the Adaptive Multi-scale Convolution Module (AMC), Cross-Modal Shared Mamba Interaction Module (SMIM), and Dual-Global Pooling Enhanced Multimodal Feature Fusion Module (G2MFF). They are responsible for unimodal feature enhancement, cross-modal information alignment, and in-depth feature fusion, which effectively improve the model's detection accuracy and generalization ability in complex scenarios. To comprehensively evaluate the model performance, we conducted experiments on multiple public real-world multimodal datasets and dedicated remote sensing datasets. Compared with state-of-the-art unimodal and multimodal detection methods, the proposed model achieved mean average precision mAP@0.5:0.95 values of 58.5% and 69.0% on the DroneVehicle and LLVIP datasets, respectively. Results demonstrate that deep multimodal feature fusion can remarkably boost object detection performance in complex environments.

This work presents a modified, wide-band, bow-tie antenna integrated with a Frequency Selective Surface (FSS) designed to enhance gain and significantly reduce the Specific Absorption Rate (SAR). The proposed antenna, with a compact profile of 0.47λ_g × 0.77λ_g, operates at a center frequency of 2.4 GHz and exhibits a high radiation efficiency. By employing a flared polygonal radiating element, the antenna achieves wide-band performance across an operational spectrum of 1.97 GHz to 3.09 GHz, yielding a fractional bandwidth of 46.7%. An FSS array, functioning as a spatial filter, was designed and positioned 39 mm from the antenna, thereby forming an integrated system. Through numerical simulations, this system shows the gain improvement of the antenna from 2.51 dBi to 6.5 dBi and simultaneously reduces the SAR from 3.9 W/kg to 1.6 W/kg per 10 g of tissue, falling well below the permitted safety limit. The antenna and FSS array prototypes were fabricated and tested for scattering parameters, gain improvement, and radiation pattern. The measured results were in close alignment with the simulations, demonstrating the efficiency of the antenna for safe and high-performance off-body biomedical applications.

To address the inherent trade-off between convergence speed and steady-state error in conventional least mean square (LMS) algorithms for inverter-driven six-pole active magnetic bearings (AMBs), this paper proposes an online adaptive vibration compensation control strategy. In this strategy, a fuzzy-optimized Rayleigh-distribution-curve hybrid-weighted coefficient LMS (RDC-HWCLMS) algorithm is integrated with the influence coefficient method (ICM). First, the rotor unbalance dynamic model is derived, and the LMS-based synchronous vibration extraction principle is analyzed. Second, a Rayleigh-based variable-step-size law is constructed to improve transient convergence, and a hybrid-weighted coefficient update is introduced to suppress steady-state weight fluctuations under noisy displacement measurements. Furthermore, a fuzzy inference system (FIS) is introduced to enhance self-adaptability by dynamically tuning the step-size scaling parameter according to real-time error states. The extracted synchronous vibration components are then used by the ICM to generate compensation current references, which are injected into the AMB control system through the three-phase inverter. Finally, comparative simulated and experimental results on a 4-DOF inverter-driven six-pole AMB platform verify that the proposed online adaptive compensation control method achieves faster convergence, lower residual vibration, and stronger dynamic tracking adaptability than conventional LMS algorithms.

This paper studies the changes in plasma discharge characteristics and thruster performance using a two-dimensional PIC-MCC model and performance testing experiments when adjusting the magnetic field configuration in the discharge channel through an additional excitation coil at a propellant flow rate of 5 mg/s and a discharge voltage range of 300-1000 V. The research results indicate that optimizing the magnetic field configuration in the discharge channel can improve the performance of the thruster under high discharge voltage, especially in the discharge voltage range of 600--1000\,V. The simulation results of plasma characteristics show that by adjusting the magnetic field configuration, the ion ionization efficiency can be improved; the wall loss of ions can be reduced; and the acceleration and focusing of ions can be improved. The simulation and experiments results of the thruster performance show that adjusting the magnetic field configuration can improve the efficiency of the thruster, avoid the decrease in thruster efficiency when the discharge voltage increases, and ensure high efficiency while achieving high specific impulse.

This study proposes a printed ultra-wideband (UWB) antenna based on a recursive semi-circular fractal topology. The radiating element is generated via the hierarchical decomposition of a primary semi-circular structure into self-similar conductive and void arc segments. This alternating conductive-void arrangement lengthens the effective current path and excites several closely spaced resonant modes that merge into a single continuous band. The antenna is printed on a Rogers RT/duroid 5880 substrate with a thickness of 0.508 mm, characterized by a relative permittivity of ε_eff = 2.2 and a loss tangent of tanδ = 0.0009, and excited by a 50-Ω microstrip feed line over a notched partial ground plane. Occupying 28 × 30 × 0.508 mm³, corresponding to 0.287λ₀ × 0.307λ₀ × 0.0052λ₀. The design achieves a simulated impedance bandwidth from 3.07 to 13.92 GHz (128% fractional bandwidth), and the measured impedance bandwidth extends from 3.03 to 14.05 GHz (129% fractional bandwidth). The simulated peak realized gain is 5.2 dBi, and the measured peak gain reaches 4.97 dBi. Simulated radiation efficiency above 93.8% across the entire operating band was obtained, and it reaches approximately 98.2% around 8 GHz. The measured radiation patterns show good agreement with simulated results at the investigated frequencies. The experimental validation of the proposed antenna with its thin, low-loss profile supports its potential use in diverse UWB wireless applications and sensing systems.

Chimeric antigen receptor (CAR)-T cell therapy has achieved remarkable success in hematologic malignancies, yet its efficacy in solid tumors remains limited by the immunosuppressive tumor microenvironment. The recent clinical breakthrough of GPC3-specific dnTGFβRII-armored CAR-T (C-CAR031) has demonstrated encouraging responses, but a substantial fraction of patients still fails to achieve durable remission. A key resistance mechanism is the overwhelming burden of TGF-β1 in the tumor microenvironment, which may overwhelm the dnTGFβRII ``armor'' and lead to CAR-T exhaustion. Here, we report a magnetic bead-amplified phase-interrogated surface plasmon resonance (SPR) biosensor for the quantitative detection of TGF-β1 on tumor-derived extracellular vesicles (TEVs) in patient plasma. The platform combines anti-TGF-β1 antibody-conjugated magnetic beads for EV enrichment with a ZnSe/GO SPR chip functionalized with anti-TGF-β1 for real-time, label-free detection. The assay achieved a limit of detection (LOD) of 0.051 pg/mL with a linear range spanning 10<sup>-1</sup>-10<sup>5</sup> pg/mL (R<sup>2</sup> = 0.9894). In vitro, CAR-T + Raji co-culture significantly increased TGF-β1<sup>+</sup> EVs compared with all control groups, peaking at 24 h. Orthogonal surface-enhanced Raman scattering (SERS) validation at 72 h independently confirmed this trend, exhibiting characteristic R6G reporter peaks at ~1367 cm<sup>-1</sup> and ~1520 cm<sup>-1</sup>, and strictly following the hierarchy of CAR-T + Raji > Raji > CAR-T > CT + Raji > Healthy controls. Clinically, four CAR-T patients showed marked elevations in plasma EV-associated TGF-β1 (7.2-21.3 fold over baseline), with peak concentrations of 77.97, 69.22, 49.02, and 57.30 pg/mL for P1-P4, respectively. This platform provides a companion diagnostic tool to identify patients with high TGF-β1<sup>+</sup> EV burden, specifically those whose ``armor'' is likely to be overwhelmed, thereby guiding combination therapy or EV clearance strategies. In this retrospective cohort of four patients who all developed Grade 1 CRS, the EV-associated TGF-β1 signal rose before clinical onset in the retrospectively aligned trajectories; prospective validation in larger, higher-grade CRS cohorts is required in future studies.

To address poor energy-transmission performance and weak anti-interference capability in wireless power and data transfer (WPDT) systems for implantable cardiac pacemakers, this study proposes an amplitude-shift-keying WPDT system for cardiac pacemakers based on a dual-strand hybrid magnetic metamaterial (DSH-MNG) array. First, we designed the DSH-MNG basic unit based on equivalent medium theory and the ohmic loss formula. We then analyze the influence of the metamaterial's structural parameters on the loss and optimize the number of turns and turn spacing of the basic unit to achieve optimal transmission efficiency. Next, an equivalent circuit model based on the DSH-MNG array system was derived. Finally, the improvement effect on the system's transmission performance is verified through simulation and experiments. The experimental results show that within a transmission distance of 20-40 mm, the system's transmission efficiency with the DSH-MNG array increased by 15.5% to 40.3%, and the modulation index has increased from 0.169-0.208 to 0.198-0.266. When the receiving coil is subjected to a horizontal offset of 5 mm to 15 mm and an angular offset of 15° to 45°, this system can still maintain a transmission efficiency of 24.8% to 66.3%, and the modulation index remains between 0.204 and 0.259.