Search Results (89)

The increasing frequency and severity of wildfires pose growing challenges to ecological security in remote forest regions. In road-sparse primeval forests, wildfire prevention and ground emergency response are constrained not only by fire-prone environmental conditions, but also by limited tactical access routes. Existing wildfire susceptibility studies can identify areas with higher fire occurrence potential, whereas route planning studies often optimize access without explicitly considering where fires are more likely to occur. This study developed a GIS-based decision-support framework linking wildfire susceptibility modelling with firefighting access route planning in the northern primeval forest region of the Greater Khingan Mountains, China, to improve the efficiency of wildfire prevention and response in areas with sparse road networks. Using 887 historical fire points and nine environmental and anthropogenic predictors, Logistic Regression (LR), Random Forest (RF), and Extreme Gradient Boosting (XGBoost) models were compared to identify relatively wildfire-prone areas. High-susceptibility locations were grouped into operational management zones using K-means clustering. A generalized forest traversal cost surface was constructed by integrating terrain, vegetation, land cover, water constraints, and existing-road accessibility, and a hybrid simulated annealing and 2-opt algorithm was used to design candidate access corridors. Results show that the RF model achieved the best internal-validation performance (AUC = 0.948; overall accuracy = 0.873), and feature-importance comparison showed that land surface temperature, proximity to roads, and NDVI were the most influential predictors. In total, 386 target points extracted from the high- and extreme-susceptibility classes were grouped into 12 spatial clusters. The optimized network identified 1008.46 km of candidate corridors and reduced the mean nearest-access distance for 13 historical wildfire events by 53.7% after the planned network was incorporated. After incorporating the planned corridors into the existing road system, the road-network density increased from 0.96 to 2.015 m/hm². These findings demonstrate that susceptibility-driven route planning can translate predicted fire-prone areas into prioritized management units and candidate access corridors, thereby reducing spatial accessibility gaps and supporting phased patrol deployment and emergency-resource allocation in road-sparse primeval forests. Full article

Aerial tiny objects naturally possess conjugate symmetry in the frequency domain, yet complex scenarios, heavy clutter, and frequent rotation/occlusion lead to severe detail loss, inaccurate contour modeling, and high false/miss rates in existing detectors. Current Fourier-based methods neither leverage object symmetry nor coordinate with Fourier analysis to jointly enhance contour representation and spatial-frequency feature learning, suffering from weak fusion, phase-sensitive coefficient regression, and poor discriminability. To fill this gap, we propose the Frequency-Aware Fourier Series Detection Network (FAFSDet), which explicitly exploits the inherent symmetry of tiny objects and their frequency-domain representations. Specifically, FAFC (Frequency-Aware Feature Fusion) employs conjugate-symmetry-guided dynamic low-pass filtering, similarity-based rearrangement, and adaptive high-frequency enhancement to recover degraded symmetric patterns. FSPRM (Fourier Series Profile Representation) utilizes the symmetric positive–negative frequency distribution to achieve compact parametric contour encoding and normalized centroid-shape description. FSDIM (Fourier Series Detection Inference) incorporates symmetric multi-scale branches, a rolling-optimization loss that eliminates phase interference while preserving coefficient-regression symmetry, and inverse Fourier transform for precise contour reconstruction and end-to-end detection. Extensive experiments on DOTA, AI-TOD, and UCAS-AOD demonstrate that our method achieves superior performance (mAP 82.18%, 51.2%, and 90.70%, respectively) and strong generalization, particularly in scenarios where symmetry is most severely compromised, confirming that exploiting these symmetry properties substantially boosts detection accuracy. Full article

Arousal is essential for cognitive awareness, and it typically declines during prolonged tasks. Currently, mobile devices are frequently used during breaks to relax and counteract this decline. However, their impact on neurophysiological recovery remains poorly understood. Therefore, this study compared the effects of traditional quiet rest versus a mobile task break on cortical arousal using spectral analysis of electroencephalography (EEG) signals in twenty healthy young females (20–25 years). Raw EEG data were transformed using Fast Fourier Transform (FFT) to determine power spectral densities, with a state of physiological underarousal first induced via a prolonged eyes-closed condition. Results revealed that this state was characterized by reduced alpha/beta power and delta/theta synchronization starting at the 4th minute. Although traditional quiet rest suppressed delta/theta synchronization, it failed to sustain cortical arousal, with alpha and beta powers declining by the 8th minute. In contrast, passive social media browsing acted as a potent neurocognitive stimulant, not only sustaining arousal but markedly increasing high-frequency beta power by the 16th minute. Furthermore, preliminary network-level connectivity analysis using Phase Locking Value (PLV) revealed that mobile tasks induced widespread beta-band synchronization across frontal-midline regions, suggesting enhanced functional coupling within the executive control network. In conclusion, in healthy young females, while mobile tasks strategically counteract low arousal, they fail to facilitate the neurophysiological disengagement necessary for true recovery. These findings underscore the importance of digital hygiene, highlighting a distinction between alertness-boosting activities and recovery-focused rest. The results suggest that mobile tasks may create a subjective perception of rest despite objective signs of sustained cortical activation, implying that such activities may not facilitate genuine neurophysiological recovery within the context of short-term neurophysiological modulation. Full article

Motor imagery (MI)-based brain–computer interfaces (BCIs) have led to great interest as a result of their potential use in neurorehabilitation, assistive robotics, and human–computer interaction. However, decoding electroencephalographic (EEG) signals with high accuracy continues to be a difficult task due to the weak signal-to-noise ratio, differences among subjects, and the complicated temporal–spectral–spatial neural dynamics. Deep learning methods recently developed, such as convolutional neural networks, recurrent architectures, graph neural networks, and adversarial transfer learning, have enhanced MI decoding performance, yet many models are still concentrating on a single representation domain or they need costly adaptation phases in terms of computation. To tackle these shortcomings, we present NeuroCrossNet, a unified tri-modal deep learning model that is able to learn the temporal, spectral, and spatial EEG features jointly for robust and calibration-free MI decoding. The suggested network combines a Temporal HyperMixer Block for capturing long-range temporal dependencies, a wavelet transformer for learning localized time–frequency representation, and a Graph Attention Network for EEG topology-aware spatial reasoning. Additionally, a Dynamic Residual Attention Gate (DRAG) has been developed to adaptively merge heterogeneous feature streams, and a compact subject-aware normalization (SAN) method enhances cross-subject generalization without the use of labeled target-domain calibration data. Our proposed model was tested following the rigorous leave-one-subject-out (LOSO) approach on BCI Competition IV-2a and High-Gamma datasets. NeuroCrossNet reached a classification accuracy of 91.30%, surpassing several strong benchmark methods, including CNN-LSTM, EEGNet, DeepConvNet, spectral CNN, and graph-based EEG decoding frameworks. Furthermore, a large number of ablation studies reveal that the integration of temporally, spectrally, and spatially complementary representations considerably boosts robustness and inter-subject consistency. Full article

When poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) is employed as the hole transport layer in visible/near-infrared photodetectors, the extraction and transport of holes are hindered by the accumulation of the PSS insulating phase at the interface. This accumulation results in an increase in contact resistance and creates a potential barrier for hole injection. This study introduces a self-assembled monolayer, (2-(9H-carbazol-9-yl)ethyl)phosphonic acid (2PACz), to modify PEDOT:PSS, effectively optimizing the interface of the hole transport layer. Such improvements lead to a reduction in recombination losses during charge transfer, a lower dark current, and improved energy level alignment in the device, thereby boosting the performance of visible/near-infrared photodetectors. The fabricated double hole layer photodetector exhibits a low dark current of (1.4 ± 0.6) × 10⁻⁵ A at −1 V bias and a switching ratio of up to 7.62 × 10⁵ at 0 V bias. The device achieves a responsivity of 0.31 A/W and a high specific detection rate of 3.23 × 10¹² Jones at a wavelength of 780 nm, which corresponds to the peak responsivity, showcasing enhanced detection capabilities. In comparison to a reference device based on PEDOT:PSS, the response speed, cutoff frequency, and linear dynamic range of the double hole layer device have been enhanced by 400%, 213%, and 81%, respectively, thereby better aligning with practical application requirements. This research presents a novel approach for the development of high-performance organic visible/near-infrared photodetectors. Full article

This paper proposes a novel two-stage phase-shift optimization strategy to reduce DC bus ripple current in a two-phase cascaded boost converter. Conventional 180° interleaving causes frequency mismatch between the front-end and back-end stages, degrading ripple cancellation. To address this, the proposed method first derives an optimal front-end phase angle (α_opt) to match stage frequencies and shape the current waveform. Subsequently, an optimal back-end phase angle (β_opt) aligns the back-end input current peak with the center of the shaped front-end current’s high interval, achieving precise synchronization. This minimizes instantaneous current deviation and cancels charge variations. Experiments on a 1 kW prototype demonstrate a 21.2% reduction in RMS ripple current compared to conventional methods. System efficiency improved by 0.42–0.49% due to reduced capacitor losses. The strategy enhances reliability by alleviating thermal stress while contributing to high efficiency and power density in power conversion systems. Full article

Carbon Fiber Reinforced Polymers (CFRP) are extensively utilized in high-performance engineering, yet localized structural discontinuities can severely compromise their integrity. This paper aims to achieve high-sensitivity characterization of such anomalies using a proposed acoustic shearography technique based on continuous acoustic excitation. A comprehensive finite element model (FEM) was developed to clarify the mechanical-energy coupling between the acoustic fields and localized surface strain field modulations. By exploiting ultrasonic energy coupling, the localized features of discontinuities were identified through full-field, non-contact optical measurement of localized phase distortions. Key parameters, including shearing amount, excitation frequency, driving voltage, and geometric characteristics of blind flat-bottom holes (BFBH), were systematically investigated. The results demonstrate a high correlation between FEM simulations and experimental observations quantitatively elucidating how defect diameter and hole depth modulate surface strain distributions. The proposed hybrid acoustic optical approach achieves near-instantaneous full field imaging within a millisecond timeframe typically under 200 ms. Additionally, the methodology leverages localized acoustic resonance to significantly boost the signal-to-noise ratio (SNR) resulting in highly quantified phase map contrast. Full article

This paper explores a new switching strategy for a recently proposed quadratic boost converter. The topology under study is a high-step-up DC–DC converter with a configuration that allows a portion of the processed energy to be used in what we call a non-series transfer. This characteristic reduces the amount of power processed redundantly. This converter, called a Quadratic Boost Converter based on Non-Series Energy Transfer (QBC-NSET), also has a non-pulsating input current, which is especially desirable for applications like photovoltaic and fuel-cell sources. This paper proposes a different switching strategy that reduces the output voltage ripple without increasing the switching frequency and without increasing the stored energy (inductance in inductors or capacitance in capacitors). The converter has two transistors, originally operated with synchronized signals; the proposed strategy provides independent switching signals with a phase shift between them. This enables the output capacitor to charge in a different switching state, producing a smaller voltage ripple while preserving the advantages of the topology originally presented. Steady-state analysis and voltage gain derivations confirm that the fundamental conversion characteristics remain unchanged. Experimental results obtained from a laboratory prototype validate the effectiveness of the proposed approach, demonstrating the reduction in the output voltage ripple. Full article

Coherent noise in digital holographic microscopy (DHM) seriously degrades the accuracy of quantitative phase imaging, limiting its applications in fields such as nondestructive testing. However, traditional numerical denoising methods struggle to achieve an ideal balance between noise suppression, detail preservation, and computational efficiency. To address this challenge, we propose a multi-scale attention efficient network (MAENet). This network employs a dual-encoder architecture to achieve complementary extraction of multi-scale features. To efficiently integrate the features from these two branches, a dual-branch dense attention fusion (DDAF) module is designed. It performs a weighted fusion of features from the dual branches via an adaptive attention mechanism and enhances feature representation via dense residual connections, significantly boosting the model’s denoising performance. Furthermore, a hierarchical fusion strategy is adopted to preserve high-frequency details in the shallow layers of the network while performing feature fusion in the deeper layers, thereby maximizing protection of image textures while effectively suppressing noise. To address the lack of paired training data in real-world scenarios, a DHM simulation system capable of simulating the key physical characteristics of coherent noise was constructed. Extensive experiments on the simulated dataset show that MAENet achieves a PSNR of 33.25 dB and an SSIM of 0.93042, outperforming various mainstream denoising algorithms and demonstrating its excellent performance in suppressing coherent noise, providing an effective solution for denoising in coherent imaging systems. Full article

This paper proposes a Cascode phase compensation network structure for controlling Buck–Boost converters to achieve wide-bandwidth and high-speed operation. The proposed scheme relocates the compensation capacitor (C_C) from the traditional position “across the first-stage output and the second-stage output” to a new position “between the source of the first-stage Cascode common-gate transistor and the second-stage output.” By integrating their high common-mode rejection ratio and power supply rejection ratio, a global system loop with robust interference immunity is constructed. The results indicate that a dominant-pole frequency of 10 kHz is achieved with our proposed structure compared to the circuit without Cascode compensation, representing a tenfold increase. As a result, a phase margin (PM) of up to 58.36° is achieved, which is improved by 9.1%. This work can provide an effective reference for achieving stable and rapidly responsive power conversion. Full article

Based on monolithic microwave integrated circuit (MMIC) technology, this paper presents the design and implementation of a low-cost, highly integrated Ka-band sixteen-channel transmit/receive (T/R) module, specifically tailored to meet the application requirements of phased array antennas in airborne and spaceborne radar systems, satellite communications, and 5G/6G millimeter-wave networks. The proposed module employs an MMIC-based single-channel dual-chip discrete architecture, optimally integrating amplitude-phase multifunction chips and transmit-receive multifunction chips in terms of both fabrication process and performance characteristics, achieving a favorable balance between high performance and high-integration density. Using low-cost, low-temperature co-fired ceramic (LTCC) substrates, full-silver conductive paste, and a nickel–palladium–gold plating process, a novel “back-to-back” thin-slice packaging technique is presented to improve integration, lower manufacturing costs, and boost long-term reliability. Furthermore, the design incorporates glass insulators and a direct array interconnection scheme, which significantly minimizes transmission losses and reduces interface dimensions. The final module measures 70.3 mm × 26.2 mm × 10.9 mm and weighs only 34 g. Experimental results demonstrate a transmit output power of at least 23 dBm, a receive gain exceeding 26 dB, and a noise figure below 3.5 dB, achieving a 22.5–58% reduction in volume per channel while maintaining competitive RF performance. To improve testing effectiveness and guarantee data consistency, an automated radio frequency (RF) test system based on Python 3.11.5 was also developed. This work provides a practical technical approach for the engineering realization of Ka-band phased array systems. Full article

This paper proposes a single-stage three-phase AC-DC converter based on an LLC resonant topology utilizing a front-end matrix switch. Unlike traditional two-stage solutions, the proposed topology synthesizes a fluctuating equivalent DC voltage from the three-phase input, achieving direct power conversion with high efficiency. To maintain a stable DC output voltage against the time-varying input, a trajectory-based Pulse Frequency Modulation (PFM) control strategy is developed. By employing State-Plane Analysis (SPA), the operational trajectory is divided into four calculation segments, allowing precise derivation of the switching frequency and duty cycles for both boost and buck modes within a single line cycle. Furthermore, to improve power density and reduce parasitic parameters, a high-frequency planar inductor with interleaved windings and a planar transformer are designed for 500 kHz operation. A pipeline control architecture based on a single DSP is implemented to handle the complex real-time computations. A 500 W prototype is built and tested under 100 V input and 130 V output conditions. Experimental results demonstrate that the converter achieves a peak efficiency of 97%, a power factor of 0.99, and a grid current Total Harmonic Distortion (THD) of 3.95%, validating the effectiveness of the proposed topology and control scheme. Full article

Plasma power supplies find extensive applications across industrial, energy, environmental, and medical domains. This study addresses limitations of conventional plasma power supplies, including high harmonic current content, neutral-point potential imbalance, and manufacturing complexity. A novel design approach for high-frequency, high-voltage plasma power supplies is proposed, based on three-level sinusoidal pulse width modulation (SPWM) technology. First, the design distinctions between the input-side Boost power factor correction circuit and Diode Rectifier circuits are analyzed. Subsequently, an integrated SPWM driver-controller architecture and a design methodology for high-frequency transformers are introduced. A single-phase three-level SPWM modulation strategy is then presented. Based on this modulation technique, a high-frequency, high-voltage plasma power supply prototype incorporating air pumps and rotary motors was developed. Experimental validation demonstrated stable generation of plasma gas at a frequency of 25 kHz, with an output voltage of 10.79 kV and an output power of 1.75 kW. Results indicate that the refined power supply enhances electrical utilization efficiency, resolves neutral-point imbalance issues, and simplifies manufacturing through its integrated driver-controller design. This work offers a valuable reference for advancing high-frequency, high-voltage plasma technologies. Full article

We investigate a double-probe-field-driven cavity optomechanical system with a degenerate optical parametric amplifier (OPA). When the system is in a mechanical PT-symmetric case, we study the generation mechanism of the sum sideband and how to enhance the generation efficiency of the sum sideband by controlling parametric interactions. Our model consists of two directly coupled PT-symmetric mechanical resonators, which are coupled to a Fabry–Pérot cavity equipped with an optical parametric amplifier. Research indicates that in a PT-symmetric mechanical resonator, there exist special exceptional points (EPs). Near EPs, the generation efficiency of the sum sideband is significantly enhanced. Notably, the introduction of an OPA can remarkably boost the efficiency of sum sideband generation (SSG) and establish a new sideband matching condition for the upper sum sideband. We conduct a detailed analysis of the dependence of SSG on system parameters, such as mechanical coupling strength, OPA nonlinear gain, OPA pump light field phase, and probe field frequency detuning. The research reveals that even with a weak driving field, a significantly enhanced efficiency of SSG can be achieved by adjusting the OPA gain coefficient and phase. This research offers new insights into enhancing or regulating light propagation in nonlinear optomechanical devices and holds potential for applications in high-precision measurement and optical communication. Full article

In multi-module boost power factor correction (PFC) systems, current ripple is commonly mitigated by applying fixed 180° interleaving between modules; however, this approach relies on matched inductors and ideal symmetry. In practical implementations, inductor mismatch and duty-cycle variations prevent full cancellation, leading to residual ripple that increases losses and electromagnetic interference. To address this issue, several research works have proposed centralized coordination or high-speed communication among units. However, an explicit converter model is necessary, which makes the system more complicated and expensive. To resolve this problem, this paper presents an extremum seeking optimization method for reducing high-frequency ripple in multi-module PFC systems without requiring explicit converter models. The ripple minimization problem is formulated as a nonlinear, time-varying optimization task, where the relative switching phases of the modules are adaptively tuned. The proposed extremum seeking algorithm perturbs the phase shift, evaluates a ripple-based cost function, and updates the phases iteratively. A harmonic analysis is developed to characterize the dependence of ripple on duty ratio, inductor values, and phase displacement. Simulation results show that the method effectively reduces the RMS ripple current across balanced and mismatched operating conditions. In a three-unit system, applying the proposed technique lowered the current THD to 1.29% compared to 1.44% achieved with a fixed phase-shift approach. These findings demonstrate that extremum seeking optimization provides a mathematically rigorous and practically implementable solution for decentralized ripple minimization in multi-module boost PFC systems. Full article