Spherical harmonics are classical analysis tools in many science and engineering domains. For analyzing the electromagnetic fields of antennas in the frequency domain, the mostly used formulation is the one proposed by Hansen. This article proposes an alternative solution, relying on spin spherical harmonics. On a sphere, the tangential components of the electric and magnetic fields are represented by means of harmonics of spin ±1. Then new closed-form relations are established between the spin spherical harmonics and the ones formulated by Hansen. A sampling theorem and fast transforms that are consistent with spin spherical harmonics are used. The radiations of spin spherical harmonics of order 1 are related to elementary dipoles and Huygens sources in circular polarization. Finally, numerical experiments are performed with a horn antenna and a GNSS antenna installed on an aircraft. They show that a very large radiating system with a band-limit of 2048 can be efficiently analyzed by means of fast spin spherical harmonic transforms, with a computation time of 2 minutes, approximately.

This paper presents a numerical approach for solving the magnetic diffusion equation using structure-preserving discretization methods, like Discrete Exterior Calculus (DEC) and Finite Element Exterior Calculus (FEEC). A detailed derivation of the DEC operators is provided, also their geometric foundation and relevance for discretizing differential forms on meshes. Furthermore, the paper includes an explicit introduction to the finite element exterior calculus framework, with a concise overview of the underlying functional spaces. The proposed formulations aim to preserve the topological and metric structure inherent in Maxwell's equation system. Numerical examples illustrate the stability and convergence of both methods, while also comparing their treatment of boundary conditions and discrete Hodge star construction which makes DEC and FEEC solvers spurious free and efficient useful for complex geometries.

Severe pneumonia poses a significant threat to public health. Delayed diagnosis is a core challenge in treatment. This study uses two rapid, low-cost spectroscopic fingerprinting techniques - Raman spectroscopy and attenuated total reflectance Fourier transform infrared (ATR-FTIR) absorption spectroscopy - to analyze biofluids such as blood and bronchoalveolar lavage fluid (BALF). In contrast to our earlier work which combined infrared spectra with clinical biochemical test results, this paper focuses solely on the spectral data to validate a fast and label-free diagnostic method. We used a spectral transformer network (STNetwork) to perform AI-based classification of severe pneumonia from the spectral fingerprints of blood and BALF. While both modalities are effective, FTIR spectroscopy exhibits superior diagnostic precision (97.78% test accuracy) and stability (SD < 0.0139) for blood samples. BALF offers a unique window into the local lung microenvironment, and both metabolomic analysis and spectral fingerprint classification were performed. The classification results for BALF Raman spectra (enhanced with surface-enhanced Raman spectroscopy) gave a training accuracy of 96.71%±1.86% and a testing accuracy of 90.62%±3.95%, better than the classification results for BALF FTIR spectra. The present study provides a reliable technical foundation for developing rapid and high-accuracy screening solutions for severe pneumonia.

This article proposes a miniaturized dual notched ultrawide bandpass filter (BPF) for ultra-wideband (UWB) indoor applications. The initial operational spectrum recognition is realized through the resonances of multiple mode resonator (MMR). Then both the passband and stopband characteristics are improved substantially by mounting distinctly shaped meander resonators cascaded with open loop ring resonator on the MMR. Further, the interdigital coupled lines are also meandered to contribute in filter size reduction along with tightening the coupling between the effective filter structure and input/output ports. The elimination of interfering signals within the passband caused by C-band satellite downlink and fixed satellite service uplink is facilitated by two sharp notches at 3.76 GHz and 6.82 GHz frequencies. Concurrently, this miniaturized filter is also characterized by its wide passband of 6.42 GHz with fractional bandwidth (FBW) 110.88%, good selectivity of 0.85, minimal insertion loss differing between 0.44 dB and 0.85 dB, wide upper stopband of 5.11 GHz, etc. ensuring its suitability as a practical UWB filter. The design is fabricated and measured to compare with the simulated outcomes and validated by the obtained resemblance between the measured and simulated filter outputs.

A novel single-cavity triple-mode combined-type rectangular patch resonator (CRPR) is proposed in this paper, which is realized by integrating the rectangular patch structure with the rectangular substrate integrated waveguide (RSIW) structure. By cleverly designing the length-to-width ratios of both the RSIW structure and the patch structure, as well as the size ratio between them, the three higher-order modes of the CRPR can be resonance. Then, a highly selective bandpass filter (BPF) is realized through a special feeding structure. To demonstrate the method, an instance of a BPF is designed, synthesized, fabricated, and measured. The consistency of all results validates the effectiveness of the proposed design method. The proposed filter offers advantages such as relatively compact size, easy integration, and high selectivity.

Unmanned aerial FPV systems demand ultra-low latency, high-reliability communication. At high speeds and in cluttered environments, Doppler shifts and rapid multipath changes significantly increase packet error rates (PER). This paper introduces a novel solution: real-time geometry tuning of a circularly polarized helical antenna array to mitigate these effects in ExpressLRS (ELRS) long-range FPV control links. Using full-wave simulations (Ansys HFSS) and blind field trials, we validate system performance. A new analytical framework integrates Doppler-induced frequency offset into the antenna's radiation pattern and PER model. The adaptive array autonomously adjusts coil pitch and diameter based on velocity and attitude, reducing PER by 20% at speeds over 150 mph. It also maintains near-unity VSWR, preventing reflection spikes, and halves RSSI variation, indicating improved link stability. These results demonstrate that tunable helical antennas can effectively mitigate Doppler and multipath impairments in high-mobility UAV environments, informing future antenna designs and supporting the development of AI-integrated, adaptive RF systems for drone racing and autonomous swarms.

This paper presents the development of a low-frequency dual-port microwave sensor designed for permittivity detection in both solid and biological materials. The sensor integrates a circular split-ring resonator (CSRR) with an electric field coupled (ELC) structure on a planar dielectric substrate, resulting in a compact and simple architecture that supports ease of fabrication and low-cost implementation. Operating at a resonant frequency of 0.86 GHz, the sensor is particularly suitable for characterising biological samples such as meat, fish, squid, and chicken, as lower frequencies offer deeper penetration and better interaction with high-loss biological tissues. Validation through full-wave simulation and experimental measurement confirms the sensor's capability to detect permittivity variations across a wide range of materials. A polynomial fitting model is employed to extract permittivity values based on resonance frequency shifts, achieving accurate results with a maximum error below 7% and overall accuracy exceeding 93%. The device demonstrates reliable performance in estimating permittivity values from ε_r = 1-9.8, including unknown biological samples with normalized sensitivity of 0.02% and frequency detection resolution 0.019 GHz. Measurements show clear frequency shifts that correlate with dielectric changes, and the experimental results align closely with the simulation data. The simple structure of the sensor also supports straightforward integration with common measurement instruments such as vector network analysers, making it practical for real-time monitoring and portable applications. The low operating frequency combined with the straightforward design provides an effective solution for applications requiring permittivity detection of lossy, heterogeneous, or biological materials. This work contributes a feasible and efficient sensor platform for use in medical diagnostics, food quality inspection, and other industrial contexts where reliable, low-cost dielectric sensing is essential.

This article presents the first comprehensive retrospect on an innovative and emerging antenna technology termed antennaon-display (AoD) for wireless mobile devices of 5G and beyond 5G (B5G, including 6G). The main backgrounds, benefits, stack-ups, ingredients, performance requirements, and various representative types of AoD are systematically introduced, analyzed, and discussed. Beyond its original role in wireless communication applications, AoD is also highly suitable for radar-based sensing or even for integrated sensing and communication (ISAC) to enable and enrich human-device interactions for more powerful artificial intelligence (AI) devices. Furthermore, the prospect of integrated millimeter-wave and microwave AoD designs is proposed as a promising development trend for AoD. Finally, an on-site demonstration of a smartphone featuring an AoD solution for real-time wireless video transmission at 28.0 GHz is presented.

Improving only the speed-loop controller in a PMSM drive system is insufficient to address limitations in the current loops, such as integral saturation and severe oscillations. To achieve high-performance current control across the speed-current loop structure, this paper proposes an improved non-singular fast terminal sliding mode continuous composite control (INFTSMC) method, integrated with a fast super-twisting sliding mode observer (STSMO). First, a state-space model of the PMSM speed-current loops is established. Then, the speed and current loop controllers are designed using the STSMO within the INFTSMC framework. The fast super-twisting control law is adopted to reduce the number of observer parameters and to mitigate the severe oscillations caused by high gains in conventional sliding mode observers. Finally, the proposed composite control strategy is compared with conventional PI and SMC+SMO controllers through both simulation and RT-LAB experiments. The results demonstrate that the proposed approach significantly enhances the dynamic response performance of the PMSM drive system.

Electromagnetic inverse scattering (EIS) problem is challenging due to its properties of strong nonlinearity and ill-posedness, where existing deep learning approaches often lack systematic network refinement and comprehensive analysis of key factors affecting performance. This work introduces CAMO-Net, a U-Net-based framework for EIS that integrates a channel-attention mechanism and systematically optimizes architectural and training factors to address these limitations. By integrating channel attention into skip connections, adopting a multi-scale channel configuration, and fine-tuning key hyperparameters through controlled experiments, CAMO-Net achieves superior accuracy and robustness. Experimental results demonstrate that it reduces the mean relative error (MRE) by 32.5% and the mean squared error (MSE) by 34.1% compared to the baseline U-Net. Our results demonstrate that joint channel attention and multi-factor optimization provide an effective, reproducible pathway for high-precision EIS imaging, offering new insights for robust reconstruction in EIS problems.

Diffractive optical elements, including holograms and metasurfaces, are widely employed in imaging, display, and information processing systems. To enhance information capacity, various multiplexing techniques such as wavelength, polarization, and spatial multiplexing have been extensively explored. However, the angular optical memory effect induces strong correlations in the diffracted output under varying angles of incidence, thereby fundamentally limiting the use of illumination angle as an independent degree of freedom in multiplexing strategies. Here, we propose and experimentally demonstrate a globally designed angle-multiplexed metasurface hologram enabled by a diffractive neural network (DNN). Angular multiplexing in the DNN is realized by harnessing illumination angle-dependent phase delays across local units, rather than relying on complex local designs with intrinsic angular dispersion. The DNN is trained using the complex electric field distributions and corresponding target images for each incident angle, enabling end-to-end optimization of the entire metasurface phase profile to encode multiple angular channels simultaneously. Besides, phase modulation of circularly polarized transmitted waves is achieved via geometric phase engineering, using a single-layer and fabrication-compatible meta-atom design without relying on multilayer stacking or inter-resonator coupling. Experimental measurements validate the high-fidelity reconstruction of both images at their respective angles, consistent with numerical simulations. Furthermore, robustness studies confirm that the proposed metasurface can tolerate reasonable variations in incident magnitude, angle, and frequency, as well as fabrication-induced phase errors, while preserving imaging fidelity. The proposed metasurface and design strategy offer a scalable platform for high-density information encoding and multiplexed optical systems, with potential applications in augmented reality, secure communication, and multi-view display technologies.

The rapid development of wireless technology has increased interest in multiband reconfigurable antennas, especially as devices and satellites move toward miniaturization. Reconfigurable antennas must be capable of adapting to their environment by dynamically altering their operating frequency, polarization, and/or radiation pattern. The fifth generation (5G) of wireless communication represents a significant advancement over 4G networks, aiming to meet the growing demand for data and connectivity in today's digital world. To achieve the performance required for supporting a wide range of use cases across both local and global markets, 5G must integrate various existing communication technologies. This work presents a multiband double T shaped frequency reconfigurable antenna for 5G wireless communication on a Rogers RT5880 substrate, designed and simulated using the CST Microwave Studio. In this antenna, two MA4SPS402 PIN diodes are used to make the antenna reconfigurable. By using these PIN diodes, the antenna works on four different modes based on both the diodes ON/OFF conditions. By using this configuration of the PIN diodes, the presented antenna operates at five different operating frequencies 10.8 GHz, 16.47 GHz, 17.03 GHz, 17.07 GHz and 21.2 GHz. The presented antenna provides the best reflection coefficient |S₁₁| value which is -24.76 dB at 21.2 GHz, and peak gain is 7.81 dBi at 16.47 GHz. The measurements of the fabricated antenna are done using a Vector Network Analyzer (VNA) and an anechoic chamber, confirming its reflection coefficient (|S₁₁|) and gain, making it a reliable option for 5G applications.

Severe bacterial pneumonia is a serious respiratory disease caused by bacteria, which is mainly transmitted through the respiratory tract. To achieve early recognition of severe pneumonia patients through images, this study collected the CT images of 180 patients diagnosed with bacterial infection in the lungs on the day of emergency admission to a large regional medical center (a Top-Tier (Grade 3 A) hospital). After classification by two deputy chief physicians of the respiratory department, 93 cases of severe bacterial infection were obtained and the rest 87 cases were identified as mild bacterial infection. The CT sequences were then preprocessed and annotated to obtain 599 images with annotated lung infection areas. Together with 107 normal (non-infected) images, these bacterial infection images were randomly divided into a training set of 447 and a test set of 259. In the experiment, four deep learning methods, namely, FCN, PSPNet, deeplabv3, and deeplabv3plus, were used for training and three-class classification (severe bacterial infection, mild bacterial infection, and normal). Deeplabv3plus showed the best performance, with an overall accuracy of 96.91% (including a sensitivity of 95.25%, a specificity of 97.24%, an accuracy of 86.96%, a recall rate of 95.24%, and an F1 score of 90.91%) for severe bacterial infection. Using deep learning technology to diagnose severe pneumonia as early as possible can produce valuable treatment time for patients, thereby significantly reducing mortality and complication rates.

This paper introduces a spatiotemporal encoding method based on metasurface that enables precise frequency control and functional switching of radiation beams. The metasurface is configured with subarrays, and each subarray is designed to reflect a specific frequency, thereby achieving unique multi-target signal diversity. By manipulating the spatiotemporal phase of subarray elements, the metasurface can generate far-field radiation patterns with beam characteristics of consistent beam angle at different distances, or beam characteristics of consistent distance with different beam angles. The radiation energy distribution at harmonic frequencies is verified to remain symmetry under various 1 bit spatiotemporal encoding matrices, while the symmetry is verified to be broken by 2 bit spatiotemporal encoding matrices. An optimization method of genetic algorithm (GA) improved binary particle swarm optimization (BPSO) based on 2-bit-coding is thus developed to optimize the spatiotemporal modulation of the metasurface subarray. The GA with the advantage of the crossover mutation operation is utilized to enhance population diversity and thus prevent the algorithm from falling into local optimality with improved search efficiency in high-dimensional discrete space. The optimization method balances different performance parameters and can achieve unique multi-target signal diversity, thereby improving the metasurface's ability to dynamically control and manipulate energy distribution. Using a 1-bit cross-switching mechanism with a duty cycle of 50%, the metasurface can suppress specific harmonic frequencies on the line of sight to less than -60 dBi while keeping the sidelobes below -20 dBi. The technology can precisely control the harmonic energy distribution while allowing beam at specific harmonic frequencies to be absorbed or reflected, which realize advanced breakthrough for effective selective stealth. Simulation results validate the proposed digital encoding optimization method, and the mainlobe gain of the metasurface harmonics is obtained to be more than 20 dBi. This paper algorithmically improves the beam gain of the metasurface and explores the versatile applications of spatiotemporal metasurfaces.

The use of additive manufacturing for the manufacturing of complex materials requires suitable characterization methods. A free-space measurement method is used for the real permittivity characterization. Depending on the considered printing pattern, the experimental result shows good agreement with theoretical values calculated using mixing laws. The setup gives promising results with characterizations of the permittivity, and it highlights the importance of taking into account the printing pattern used according to the desired effective permittivity.

A polarization reconfigurable metasurface broadband antenna has been proposed. A 2×2 metasurface was used to achieve circular polarization (CP) characteristics, and four resistors were embedded to achieve linear polarization (LP). Among them, characteristic mode analysis (CMA) was used to discover the CP characteristics of the metasurface. Adding resistors changed the direction of the mode current, which causes CP to switch to LP state. The design results were validated through fabrication and measurement. The measured results show that the impedance bandwidth (IBW) is 21.1%, the axial ratio bandwidth (ARBW) 12.9%, the peak gain (PG) 7.7 dBic at 6.8 GHz in the CP state, its IBW 21.0%, the PG 4.7 dBi at 7.0 GHz in the LP state. The proposed antenna has the characteristics of broadband, polarization reconfigurability, easy processing, and low cost, and its operating frequency can be used in the C-band of wireless communication.

A 2D flat, 2D curved, and 3D finite element method (FEM) implementation of the spatially-variant lattice (SVL) algorithm is presented. This powerful algorithm is used in electromagnetics to preserve the electromagnetic properties and geometry of periodic structures that are bent, twisted, conformed, or otherwise spatially varied. Applications of the SVL algorithm include photonic crystals, metamaterials, conformal frequency selective surfaces, cloaking devices, and volumetric circuits over complex geometries. The present work shows examples of SVLs over a planar surface lattice, a doubly-curved surface lattice, and a volumetric lattice.

This paper proposes a lumped parameter microwave dual frequency filter implemented using surface mount technology (SMT), which has low-pass and band-pass characteristics. We implement a dual-band response by integrating a matching network and harnessing the inherent parasitic inductance of SMT capacitors. This strategy generates transmission zeros (TZs) in the high-frequency band, significantly enhancing frequency selectivity. The performance of the filter was verified through odd-even mode analysis and validated through experimental measurement. The experiment measured that the low pass cut-off frequency of the filter is 360 MHz, and the second channel exhibits good band-pass characteristics at 800 MHz, with an insertion loss of -2.191 dB.

A high-impedance ground plane has been proposed that enables the reflection of magnetic fields within a frequency range of interest. When being combined with loop coil antennas or H-field-oriented structures, it can boost transmission efficiency by up to 3 dB. Although several approaches, such as mushroom-shaped protuberant surfaces paired with capacitive loading, have been described to suppress surface waves at certain frequency ranges, the shift to a desired frequency range (e.g., from 5 GHz to 1 GHz) is marginal, and their form factors make these methods less ideal for applications in power and data communication. Here, we describe new strategies for a low-profile high-impedance ground plane. The insertion of a metal ground plane between the top and bottom mushroom-shaped surfaces reinforces capacitive couplings between adjacent unit cells. When coupled with extended spiral paths, this configuration leads to an apparent change in the resonant frequency of the structure. Fabrication of the proposed structure demonstrates that the sandwiched metal ground plane, paired with extended spiral paths, leads to a noticeable shift in the resonant frequency toward lower sub-GHz ranges at given dimensions. Measurements are in good agreement with the results from the analytical model.

This article addresses the challenges associated with poor tunability and the single absorption function in absorbers. To address these challenges, we designed a dual-band switchable tunable absorber utilizing graphene and vanadium dioxide.The proposed absorber exploits the phase transition characteristics of vanadium dioxide to achieve absorption in the low-frequency band when it is in the dielectric state and absorption switching in the high-frequency band after phase transition. Furthermore, the Fermi level is altered by applying a bias voltage to the graphene, resulting in reduced square resistance. This mechanism allows tuning of the absorption frequency when the vanadium dioxide is in the dielectric state and adjustment of the absorption bandwidth when it is in the metallic state. Simulation results reveal that when the vanadium dioxide is in the dielectric state, the absorption rate exceeds 90% within the 20.0-27.7 GHz range. At this time, increasing the Fermi level of the graphene alters the absorption frequencies to 11 GHz and 42 GHz, respectively. Conversely, when the vanadium dioxide is in the metallic state, the absorption rate exceeds 90% within the 31.1-48.7 GHz range. Thus, elevating the Fermi level of the graphene leads to absorption band tuning at higher frequencies. This absorber demonstrates strong tunability and multifunctional absorption capabilities, offering outstanding practical application value.