Search Results (870)

We design a one-dimensional magnetoelastic phononic crystal slab composed of the smart magnetostrictive material Terfenol-D and pure tungsten. Band inversion and topological phase transitions are achieved by modifying the geometric parameters of the non-magnetic medium within the unit cell. The emergence of topological interface states within overlapping bandgaps, exhibiting distinct topological properties, along with their robustness against interfacial structural defects, is confirmed. The coupling effects between adjacent topological interface states in a sandwich-like supercell configuration are investigated, and their tunability under external magnetic fields is demonstrated. A Su-Schrieffer-Heeger (SSH) phononic crystal slab system under gradient magnetic fields is proposed. Critically, and in stark contrast to previous static or structurally graded designs, we achieve reconfigurable rainbow trapping of topological interface states solely by reprogramming the gradient magnetic field, leaving the physical structure entirely unchanged. This highly localized, compact, and broadband-tunable topological rainbow trapping system design holds significant promise for applications in elastic energy harvesting, wave filtering, and multi-frequency signal processing. Full article

Perfect absorbers operating in the terahertz (THz) band are key enablers for next-generation wireless systems. However, conventional metal–dielectric designs suffer from Ohmic losses and limited reconfigurability. Here, we propose an all-dielectric indium antimonide (InSb) cylindrical pillar metasurface that achieves near-unity absorption at $f_0=1.83$ THz with a high quality factor of $Q=72.3$. Critical coupling between coexisting electric and magnetic dipoles enables perfect impedance matching, while InSb’s low damping minimizes energy loss. The resonance is tunable via temperature and magnetic bias at sensitivities of $S_T\approx 2.8\mathrm{GHz}·{\mathrm{K}}^{-1}$, $S_B^{\mathrm{TE}}\approx -132.7\mathrm{GHz}·{\mathrm{T}}^{-1}$, and $S_B^{\mathrm{TM}}\approx -34.7\mathrm{GHz}·{\mathrm{T}}^{-1}$, respectively, without compromising absorption strength. At zero magnetic bias ($B=0$), the metasurface is polarization-independent under normal incidence; under magnetic bias ($B\ne 0$), it maintains near-unity absorbance for both TE and TM, while the resonance frequency becomes polarization-dependent. Additionally, the 90% absorptance bandwidth ($\Delta f_{A\ge 0.9}$) can be modulated from 8.3 GHz to 3.3 GHz with temperature, or broadened from 8.5 GHz to 14.8 GHz under magnetic bias. This allows gapless suppression of up to 14 consecutive 1 GHz-spaced channels. This standards-agnostic bandwidth metric illustrates dynamic spectral filtering for future THz links and beyond-5G/6G research. Owing to its sharp selectivity, dual-mode tunability, and metal-free construction, the proposed absorber offers a compact and reconfigurable platform for advanced THz filtering applications. Full article

With the booming development of the 5G market in recent years, super-high frequency (SHF) resonators will play an increasingly critical role in 5G and future communication systems. Facing the growing market demand for miniaturized, high-bandwidth, and low insertion loss filters, the design of SHF resonators and filters with a high effective electromechanical coupling coefficient (K²_eff) and quality factor, low insertion loss, high passband flatness, strong out-of-band rejection, and high power handling capacity has placed high demands on piezoelectric material preparation, process optimization, and resonator design. The polarity-inverted Al(Sc)N multilayer substrate has become one of the key solutions for SHF resonators. This review provides a comprehensive overview of the recent advances in SHF Al(Sc)N bulk acoustic wave (BAW) resonators. It systematically discusses the device design methodologies, structural configurations, and material synthesis techniques for high-quality Al(Sc)N thin films. Particular emphasis is placed on the underlying mechanisms and engineering strategies for polarity control in Al(Sc)N-based periodically poled multilayer structures. The progress in periodically poled piezoelectric film (P3F) BAW resonators is also examined, with special attention to their ability to significantly boost the operating frequency of BAW devices without reducing the thickness of the piezoelectric layer, while maintaining a high K²_eff. Finally, the review outlines current challenges and future directions for achieving a higher quality factor (Q), improved frequency scalability, and greater integration compatibility in SHF acoustic devices, paving the way for next-generation radio frequency (RF) front-end technologies in 5G/6G and beyond. Full article

This study proposes a novel SSA-EMS framework that integrates Singular Spectrum Analysis (SSA) with Effect-Matched Spatial Filtering (EMS), combining the noise-reduction capability of SSA with the dynamic feature extraction advantages of EMS to optimize cross-subject EEG-based emotion feature extraction. Experiments were conducted using the SEED dataset under two evaluation paradigms: “cross-subject sample combination” and “subject-independent” assessment. Random Forest (RF) and SVM classifiers were employed to perform pairwise classification of three emotional states—positive, neutral, and negative. Results demonstrate that the SSA-EMS framework achieves RF classification accuracies exceeding 98% across the full frequency band, significantly outperforming single frequency bands. Notably, in the subject-independent evaluation, model accuracy remains above 96%, confirming the algorithm’s strong cross-subject generalization capability. Experimental results validate that the SSA-EMS framework effectively captures dynamic neural differences associated with emotions. Nevertheless, limitations in binary classification and the potential for multimodal extension remain important directions for future research. Full article

Due to the “low damping” characteristics of the DC distribution system, the traditional passive scheme is not suitable for DC fault detection and positioning. Therefore, this paper proposes an active injection fault identification method suitable for DC feeder line under single-pole grounding faults. Based on the high controllability of converters, this method uses the oscillation circuit characteristics of the DC side single-pole grounding fault to superimpose the harmonics of fixed frequency into the converter modulated wave, and derives the selection principles of harmonic amplitude and frequency. After the fault, the positive and negative current signals are extracted from the feeder lines, and the zero-mode current components are extracted by the Karrenbauer transformation and band-pass filter, the current phases are compared to achieve the fault feeder line selection. According to simulation verification, the power quality of the actively injected harmonics is within the standard range under the condition of global injection, and the single-pole grounding faults in each feeder line can be identified. Full article

In marine seismic surveys, the indistinguishability of subsurface boundaries caused by the superimposition of the acoustic signals reflected from it, particularly at specific frequency ranges characterized by strong spectral interference, reduces the resolution of the seismic record. We processed sub-bottom profiler data, acquired using a Bubble Pulser (nominal central frequency: ~400 Hz; effective bandwidth extending to ~1 kHz), (i) by extracting continuous wavelet transform (CWT) coefficients at the dominant energy scale to form the envelope and (ii) by applying Hilbert-based instantaneous frequency analysis to characterize medium-dependent spectral shifts. Envelope accuracy was benchmarked against four conventional filters using the sum of squared error (SSE) relative to a cubic-spline reference. CWT yielded the lowest SSE, outperforming low-pass 1 kHz and band-pass 400–1000 Hz; band-pass 400–650 Hz and low-pass 650 Hz were the least effective. Instantaneous-frequency trends differentiated rock, sand, and mud layers. Thus, compared to fixed-band filters, the scale-adaptive CWT envelope replicates raw energy more faithfully, while frequency attributes improve sediment classification. Low-pass filtering at 1000 Hz provides a more accurate representation of energy distribution than does bandpass filtering, particularly in the 400–650 Hz range. The integrated workflow—a robust, parameter-light alternative for high-resolution stratigraphic interpretation—enhances offshore engineering safety. Full article

This paper offers a comprehensive methodology for the synthesis and analysis of active filters, including low-pass, high-pass, and band-pass configurations, utilizing operational amplifiers and multi-loop negative feedback systems. The approach involves deriving explicit analytical expressions for the design and optimization of eight distinct filter circuit solutions: one low-pass, one high-pass, and six band-pass filters with varying specifications. These derivations include the calculation of normalized and denormalized component values (resistors and capacitors), enabling precise tuning and practical implementation of the filters. Furthermore, the methodology encompasses the determination of key filter parameters such as passband gain, pole quality factor (Q-factor), and cut-off/center frequency, after selecting standard resistor and capacitor values suitable for the target application. The analytical framework facilitates a systematic approach to filter design, ensuring that the resulting circuits meet specific frequency response criteria while maintaining optimal stability and performance. The proposed methodology can be effectively applied in the development of various active filtering systems for signal processing, communication, and instrumentation, offering engineers a reliable foundation for designing high-performance, tailored filter solutions. Full article

On-machine measurement is a highly effective approach for enhancing machining accuracy and efficiency. A critical factor influencing the accuracy of on-machine measurements is the straightness error of the linear guideway. However, this error is significantly affected by environmental factors such as temperature, vibration, and gravity deformation. To improve the measurement accuracy of machine tools, this study investigates the impacts of these factors on straightness errors and proposes an innovative separation and compensation model for linear guideway straightness. A thermo-mechanical coupling simulation is employed to establish a model that quantifies the influence of thermal errors on straightness. The results demonstrate that thermal gradients cause the straightness error to bend to varying degrees, depending on the temperature distribution. Furthermore, a vibration error model is developed, revealing that the vibration period is approximately twice the ball diameter. Notably, vibration errors can be effectively mitigated using a band-stop filter to eliminate the corresponding frequency components. The study also addresses the effect of gravity deformation, comparing the deformation under different support conditions, highlighting the significance of precise support positioning. Through experimental validation of the straightness error separation and compensation model, it is shown that the straightness error of a conventional linear guideway can be reduced by 95%, and the compensated straightness error is less than 0.2 μm. This novel approach not only improves the accuracy of on-machine measurement but also provides valuable insights for optimizing machine tool performance under dynamic operating conditions. Full article

In this paper a new single-input independent multiple-output universal tunable filter employing second-generation current conveyors (CCII) and second-generation voltage conveyors (VCII) as active elements is presented. The proposed filter has been analyzed at transistor level, using a CMOS standard AMS 0.35 μm technology, and implemented using discrete components based on the commercially available AD844. A detailed mathematical analysis is carried out, considering also parasitic impedances and non-ideal parameters. The low-pass, band-pass, and high-pass responses are simultaneously obtained and experimentally verified at 10 kHz central frequency where the voltage gain is about 27 dB for each output. THD analysis has been performed to evaluate the proposed work. Full article

This paper introduces a compact analog configuration that concurrently realizes a mixed-mode biquadratic filter and a dual-mode quadrature oscillator (QO) by employing a single differential differencing gain amplifier (DDGA) and all-grounded passive components. The proposed design supports four fundamental operation modes—voltage-mode (VM), current-mode (CM), trans-impedance-mode (TIM), and trans-admittance-mode (TAM)—utilizing the same circuit topology without structural modifications. In filter operation, it offers low-pass, high-pass, band-pass, band-stop, and all-pass responses with orthogonal and electronic pole frequency and quality factor. In oscillator operation, it delivers simultaneous voltage and current quadrature outputs with independent tuning of oscillator frequency and condition. The grounded-component configuration simplifies layout and enhances its suitability for monolithic integration. Numerical simulations in a 0.18-μm CMOS process with ±0.9 V supply confirm theoretical predictions, demonstrating precise gain-phase characteristics, low total harmonic distortion (<7%), modest sensitivity to 5% component variations, and stable operation from −40 °C to 120 °C. These results, combined with the circuit’s low component count and integration suitability, suggest strong potential for future development in low-power IoT devices, adaptive communication front-ends, and integrated biomedical systems. Full article

A quad-channel diplexer is designed in this paper. The diplexer is composed of four stub-loaded step impedance resonators and a common feeder T-joint, which realizes four passbands with center frequencies of 2.6 GHz, 3.48 GHz, 4.8 GHz, and 6.3 GHz. The dual-band filter can be formed by coupling the stepped impedance resonator with the stub load, so two dual-band filters with good performance can be constructed. At the input and output end, a 0-degree feed is used to generate transmission zeros, which improves the high selectivity. When two dual-band filters are combined, a good impedance matching is obtained, and the |S₂₃| > 20 dB between the two dual-band filters achieves good isolation. The simulation results are consistent with the measured results. Full article

This work presents a high-common-mode-rejection-ratio (CMRR) and high-gain FinFET-based bio-potential amplifier with a novel CMRR reduction technique. In this paper, a feedback buffer is used alongside a capacitively coupled chopper-stabilized circuit to reduce the common-mode signal gain, thus boosting the overall CMRR of the circuit. The conventional pseudoresistor in the feedback circuit is replaced with a tunable parallel-cell configuration of pseudoresistors to achieve high linearity. A chopper spike filter is used to mitigate spikes generated by switching activity. The mid-band gain of the chopper-stabilized amplifier is 42.6 dB, with a bandwidth in the range of 6.96 Hz to 621 Hz. The noise efficiency factor (NEF) of the chopper-stabilized amplifier is 6.1, and its power dissipation is 0.92 µW. The linearity of the parallel pseudoresistor cell is tested for different tuning voltages (V_tune) and various numbers of parallel pseudoresistor cells. The simulation results also demonstrate the pseudoresistor cell performance for different process corners and temperature changes. The low cut-off frequency is adjusted by varying the parameters of the parallel pseudoresistor cell. The CMRR of the chopper-stabilized amplifier, with and without the feedback buffer, is 106.9 dB and 100.3 dB, respectively. The feedback buffer also reduces the low cut-off frequency, demonstrating its multi-utility. The proposed circuit is compatible with bio-signal acquisition and processing. Additionally, a machine learning-based arrhythmia diagnosis model is presented using a convolutional neural network (CNN) + Long Short-Term Memory (LSTM) algorithm. For arrhythmia diagnosis using the CNN+LSTM algorithm, an accuracy of 99.12% and a mean square error (MSE) of 0.0273 were achieved. Full article

This study updates the climatology of lake-effect (LE) snowfall over Lake Champlain by analyzing radar and surface data from nine winter seasons spanning 2015 to 2024. A filtering approach was applied to isolate periods with favorable LE conditions, and events were manually classified using criteria consistent with a previous climatology from 1997 to 2006. A total of 64 LE events were identified and compared across the two periods to evaluate potential changes associated with regional warming. Despite a substantial reduction in lake ice cover during the recent decades, no increase in LE frequency or duration was observed. Instead, warming has shifted the seasonal distribution of events, with fewer early-season cases and more late-season occurrences. LE events also exhibited shorter durations and higher minimum temperatures and dew points. These findings suggest that warming may constrain LE snowfall development over small lakes such as Champlain, in contrast to intensification trends reported for larger lake systems. The analysis also highlights a rarely documented transitional band type that migrated along the lake axis during synoptic shifts. Results underscore the value of observational climatologies for detecting emerging snowfall behaviors in response to climate variability. Full article

Image dehazing is critical for visual enhancement and a wide range of computer vision applications. Despite significant advancements, challenges remain in preserving fine details and adapting to diverse, non-uniformly degraded scenes. To address these issues, we propose a novel image dehazing method that introduces a contrastive learning framework, enhanced by the InfoNCE loss, to improve model robustness. In this framework, hazy images are treated as negative samples and their clear counterparts as positive samples. By optimizing the InfoNCE loss, the model is trained to maximize the similarity between positive pairs and minimize that between negative pairs, thereby improving its ability to distinguish haze artifacts from intrinsic scene features and better preserving the structural integrity of images. In addition to contrastive learning, our method integrates a multi-scale dynamic feature fusion with a hybrid attention mechanism. Specifically, we introduce dynamically adjustable frequency band filters and refine the hybrid attention module to more effectively capture fine-grained, cross-scale image details. Extensive experiments on the RESIDE-6K and RS-Haze datasets demonstrate that our approach outperforms most existing methods, offering a promising solution for practical image dehazing applications. Full article

Global Navigation Satellite System (GNSS) buoys are widely used to retrieve wave parameters such as significant wave heights (SWHs) and dominant wave periods. In addition to the statistical methods employed to estimate wave parameters, spectral-analysis-based approaches are also frequently utilized to analyze them. This study presents statistical and spectral methods for retrieving wave parameters at GNSS buoy positioning resolution in the Huanghai Sea area. To verify the method’s effectiveness, the zero-crossing method and three spectral analysis techniques (periodogram, autocorrelation function, and autoregressive model methods) were used to estimate wave height and period for comparison. The vertical positioning resolution was decomposed into low-frequency ocean-tide level information and high-frequency wave height and period information with the Complete Ensemble Empirical Mode Decomposition (CEEMD) method and moving average filtering. The horizontal positioning results and velocity parameters were used to determine the wave direction using directional spectrum analysis. The results show that the three spectral methods yield consistent effective wave heights, with a maximum difference of 0.02 s in the wave period. Compared with the zero-crossing method results, the wave height and period obtained through spectral analysis differ by 0.05 m and 0.79 s, respectively, while the average wave height and period differ by 0.09 m and 0.08 s, respectively. The GNSS-derived wave heights also closely match tidal gauge observations, confirming the method’s validity. Directional spectrum analysis indicates that wave energy is concentrated in the 0.2–0.25 Hz frequency band and within a directional range of 0° ± 30°, with a dominant northward propagation trend. These findings demonstrate that the proposed approach can provide high accuracy and physical consistency for GNSS-based wave monitoring under complex sea conditions. Full article