Search Results (6,719)

This study focuses on a comprehensive analysis of the common methods for road infrastructure monitoring, as well as the perspective of various fiber-optic sensor (FOS) realization solutions in road monitoring applications. Fiber-optic sensors are a topical technology that ensures multiple advantages such as passive nature, immunity to electromagnetic interference, multiplexing capabilities, high sensitivity, and spatial resolution, as well as remote operation and multiple physical parameter monitoring, hence offering embedment potential within the road pavement structure for needed smart road solutions. The main key factors that affect FOS-based road monitoring scenarios and configurations are analyzed within this review. One such factor is technology used for optical sensing—fiber Bragg grating (FBG), Brillouin, Rayleigh, or Raman-based sensing. A descriptive comparison is made comparing typical sensitivity, spatial resolution, measurement distance, and applications. Technological approaches for monitoring physical parameters, such as strain, temperature, vibration, humidity, and pressure, as a means of assessing road infrastructure integrity and smart application integration, are also evaluated. Another critical aspect concerns spatial positioning, focusing on the point, quasi-distributed, and distributed methodologies. Lastly, the main topical FOS-based application areas are discussed, analyzed, and evaluated. Full article

This study explores the effectiveness of 3D Digital Image Correlation (DIC) for measuring displacement and strain of a propeller undergoing angular motion. Traditional methods, such as strain gauges, face limitations including physical interference, technical difficulties in sensor connections, and restricted measurement points, leading to inaccuracies in capturing true conditions. To overcome these challenges, this research utilizes non-contact 3D DIC technology, enabling measurement of surface displacements and deformations without interfering with the tested component. Experiments were conducted using the model aircraft propellers mounted on a custom-built test stand for partial angular motion. The 1 Mpx high-speed cameras captured strain and displacement data across the propeller blades during motion. The DIC strain measurements were then compared to strain gauge data to evaluate their accuracy and reliability. The results demonstrate that 3D DIC enables precise displacement measurements, while strain measurements are subject to certain limitations. Displacement measurements were achieved with a noise level of ±10 μm, while strain measurement noise ranged from 26 to 174 µm/m depending on direction. Strain gauge measurements were also performed for verification of the DIC measurements and calibration of the filtering procedure. Two types of non-metallic materials were used in the study: Nylon LGF60 PA6 for the propeller and 3D-printed PC ABS for the cantilever beam used in strain measurement validation. This study underscores the potential of DIC for monitoring rotating components, with a particular focus on measuring strains that are often overlooked in publications addressing similar topics. Additionally, it focuses on comparing DIC strain measurements with strain gauge data on rotating components, addressing a critical gap in existing literature, as strain measurement in rotating structures remains underexplored in current research. Full article

Pipelines play a vital role in material transportation within industrial settings. This review synthesizes detection technologies for early-stage small gas leaks from pipelines in the industrial sector, with a focus on acoustic-based methods, optical gas imaging (OGI), and multimodal fusion approaches. It encompasses detection principles, inherent challenges, mitigation strategies, and the state of the art (SOTA). Small leaks refer to low flow leakage originating from defects with apertures at millimeter or submillimeter scales, posing significant detection difficulties. Acoustic detection leverages the acoustic wave signals generated by gas leaks for non-contact monitoring, offering advantages such as rapid response and broad coverage. However, its susceptibility to environmental noise interference often triggers false alarms. This limitation can be mitigated through time-frequency analysis, multi-sensor fusion, and deep-learning algorithms—effectively enhancing leak signals, suppressing background noise, and thereby improving the system’s detection robustness and accuracy. OGI utilizes infrared imaging technology to visualize leakage gas and is applicable to the detection of various polar gases. Its primary limitations include low image resolution, low contrast, and interference from complex backgrounds. Mitigation techniques involve background subtraction, optical flow estimation, fully convolutional neural networks (FCNNs), and vision transformers (ViTs), which enhance image contrast and extract multi-scale features to boost detection precision. Multimodal fusion technology integrates data from diverse sensors, such as acoustic and optical devices. Key challenges lie in achieving spatiotemporal synchronization across multiple sensors and effectively fusing heterogeneous data streams. Current methodologies primarily utilize decision-level fusion and feature-level fusion techniques. Decision-level fusion offers high flexibility and ease of implementation but lacks inter-feature interaction; it is less effective than feature-level fusion when correlations exist between heterogeneous features. Feature-level fusion amalgamates data from different modalities during the feature extraction phase, generating a unified cross-modal representation that effectively resolves inter-modal heterogeneity. In conclusion, we posit that multimodal fusion holds significant potential for further enhancing detection accuracy beyond the capabilities of existing single-modality technologies and is poised to become a major focus of future research in this domain. Full article

The acquisition of nighttime remote-sensing visible-light images is often accompanied by low-illumination effects and haze interference, resulting in significant image quality degradation and greatly affecting subsequent applications. Existing low-light enhancement and dehazing algorithms can handle each problem individually, but their simple cascade cannot effectively address unknown real-world degradations. Therefore, we design a joint processing framework, WFDiff, which fully exploits the advantages of Fourier–wavelet dual-domain features and innovatively integrates the inverse diffusion process through differentiable operators to construct a multi-scale degradation collaborative correction system. Specifically, in the reverse diffusion process, a dual-domain feature interaction module is designed, and the joint probability distribution of the generated image and real data is constrained through differentiable operators: on the one hand, a global frequency-domain prior is established by jointly constraining Fourier amplitude and phase, effectively maintaining the radiometric consistency of the image; on the other hand, wavelets are used to capture high-frequency details and edge structures in the spatial domain to improve the prediction process. On this basis, a cross-overlapping-block adaptive smoothing estimation algorithm is proposed, which achieves dynamic fusion of multi-scale features through a differentiable weighting strategy, effectively solving the problem of restoring images of different sizes and avoiding local inconsistencies. In view of the current lack of remote-sensing data for low-light haze scenarios, we constructed the Hazy-Dark dataset. Physical experiments and ablation experiments show that the proposed method outperforms existing single-task or simple cascade methods in terms of image fidelity, detail recovery capability, and visual naturalness, providing a new paradigm for remote-sensing image processing under coupled degradations. Full article

In this study, we investigate the dominant electromagnetic wave absorption mechanism–ferromagnetic resonance (FMR) loss versus quarter-wave cancellation in a novel PVDF-based polymer composite embedded with carbonaceous nanostructures incorporating FeCoCr ternary alloy. The majority of the nanoparticles are embedded at the terminal ends of the carbon nanotubes, while a small fraction exists as isolated core–shell, carbon-coated spherical particles. Overall, the synthesized material predominantly exhibits a nanotubular carbon morphology. High-resolution transmission electron microscopy (HRTEM) confirms that the encapsulated nanoparticles are quasi-spherical in shape, with an average size ranging from approximately 25 to 40 nm. The polymeric composite was synthesized via solution casting, ensuring homogenous dispersion of filler constituent. Electromagnetic interference (EMI) shielding performance and reflection loss characteristics were evaluated in the X-band frequency range. Experimental results reveal a significant reflection loss exceeding −20 dB at a matching thickness of 2.5 mm, with peak absorption shifting across frequencies with thickness variation. The comparative analysis, supported by quarter-wave theory and FMR resonance conditions, indicates that the absorption mechanism transitions between magnetic resonance and interference-based cancellation depending on the material configuration and thickness. This work provides experimental validation of loss mechanism dominance in magnetic alloy/polymer composites and proposes design principles for tailoring broadband microwave absorbers. Full article

This paper presents a long-range experimental demonstration of multi-mode multiple-input multiple-output (MIMO) transmission using orbital angular momentum (OAM) waves for Line-of-Sight (LoS) wireless backhaul applications. A 4 × 4 MIMO system employing distinct OAM modes is implemented and shown to support multiplexing data transmission over a single frequency band without inter-channel interference. In contrast, a 2 × 2 plane wave MIMO configuration fails to achieve reliable demodulation due to mutual interference, underscoring the spatial limitations of conventional waveforms. The results confirm that OAM provides spatial orthogonality suitable for high-capacity, frequency-efficient wireless backhaul links. Experimental validation is conducted over an 100 m outdoor path, demonstrating the feasibility of OAM-based MIMO in practical wireless backhaul scenarios. Full article

Ultra-wideband (UWB) technology is a crucial facilitator for high-data-rate wireless communication due to its extensive frequency spectrum and low power consumption. Simultaneously, multiple-input multiple-output (MIMO) systems have garnered considerable attention owing to their capability to enhance channel capacity and link dependability. This article discusses the development of small, high-performance MIMO UWB antennas with mutual suppression capabilities to fully use the benefits of both technologies. Additionally, the suggested antenna features a straightforward design and dual-band-notched characteristics. The antenna structure includes two radiating elements measuring 85 × 45 mm². These elements use a rectangular patch provided by a coplanar waveguide (CPW). Double U-shaped slots are incorporated into the rectangular patch to introduce dual-band-notched properties, which help mitigate interference from WiMAX and WLAN communication systems. The antenna is fabricated on a Mylar^® polyester film substrate of 0.3 mm in thickness, with a dielectric constant of 3.2. According to the measurement results, the suggested antenna functions efficiently across the frequency spectrum of 2.29 to 20 GHz, with excellent impedance matching throughout the bandwidth. Furthermore, it provides dual-band-notched coverage at 3.08–3.8 GHz for WiMAX and 4.98–5.89 GHz for WLAN. The antenna exhibits impressive performance, including favorable radiation attributes, consistent gain, and little mutual coupling (less than −20 dB). Additionally, the envelope correlation coefficient (ECC) is extremely low (ECC < 0.01) across the working bandwidth, which indicates excellent UWB MIMO performance. This paper offers an appropriate design methodology for future flexible and compact UWB MIMO systems that can serve as interference-resilient antennas for next-generation wireless applications. Full article

With the increasing demand for high-performance ceramic guideways in precision industries, accurate flatness measurement of large-scale, rough ceramic surfaces remains challenging. This paper proposes a novel method combining oblique-incidence laser interferometry and sub-aperture stitching to overcome limitations of conventional techniques. The oblique-incidence approach enhances interference signal strength on low-reflectivity surfaces, while stitching integrates high-resolution sub-aperture measurements for full-surface characterization. Numerical simulations validated the method’s feasibility, showing consistent reconstruction of surfaces with flatness values of 1–20 μm. Experimental validation on a 1050 mm × 130 mm SiC guideway achieved a full-surface measurement with PV 2.76 μm and RMS 0.59 μm, demonstrating high agreement with traditional methods in polished regions. The technique enabled quick monitoring of a 39-h lapping process, converging flatness from 13.97 μm to 2.76 μm, proving its efficacy for in-process feedback in ultra-precision manufacturing. Full article

In this paper, a low loss and high polarization-maintaining single-mode hollow-core anti-resonant fiber (PM-HC-ARF) is designed. The elliptical core in the PM-HC-ARF is formed by strategically enlarging selected cladding air holes along the y-axis. Additionally, the variations in the wall thickness in both the x and y directions generate the distinct surface modes. By simultaneously employing an elliptical core and asymmetric core-wall thickness, we enhance the phase birefringence. Theoretical analysis results show that the proposed PM-HC-ARF achieves a transmission loss of 0.00082 dB/m at wavelength 1450 nm, along with a birefringence of 1.38 × 10⁻⁴; it demonstrates CL levels an order of magnitude below state-of-the-art polarization-maintaining HC-ARFs. Moreover, within the S+C+L+U communication bands, it achieves a bandwidth exceeding 380 nm (1420–1800 nm) while maintaining a birefringence of greater than 1.45 × 10⁻⁴. In particular, this PM-HC-ARF demonstrates a maximum higher-order mode extinction ratio of over 32,070; the single-mode transmission characteristics are excellent, along with exceptional bending resistance characteristics. When the bending radius exceeds 3 cm, the impacts on the loss and birefringence are negligible; this also demonstrates that the fiber structure shows good robustness when subjected to harsh environment interference. The proposed PM-HC-ARF is believed to have important applications in fiber optic gyroscopes, optical amplifiers, and hydrophones. Full article

Micro-pulse photon-counting LiDAR has difficulty accurately extracting geophysical information in strong-noise environments, with solar noise interference being a key limiting factor. This study proposes a hierarchical coarse-to-fine denoising framework, combining grid-based pre-filtering with an optimized horizontal and vertical recursive division method using Otsu’s method to achieve high time efficiency and denoising accuracy. First, an adaptive meshing strategy is employed to remove most of the noise in the data while retaining more than 99.1% of the signal. Subsequently, an alternating horizontal and vertical recursive division algorithm with automatically selected parameters is applied for denoising; the method was validated on ICESat-2 ATL03 data, GlobeLand30 V2020 data, and USGS 3DEP airborne radar data, where the method achieved a classification accuracy of more than 91.2%, with a several-fold reduction in runtime compared to traditional clustering methods. The framework demonstrates high efficiency, robustness, and computational scalability across diverse terrains, including polar, forest, and plains. It can contribute to geographic mapping, environmental protection, and ecological monitoring. Full article

(1) Objective: This study is aiming at the key problems, such as insufficient detection accuracy of small targets and complex background interference in remote-sensing image target detection; (2) Methods: by optimizing the YOLOv10x model architecture, the YOLO-KRM model is proposed. Firstly, a new backbone network structure is constructed. By replacing the C2f of the third layer of the backbone network with the Kolmogorov–Arnold network, the approximation ability of the model to complete complex nonlinear functions in high-dimensional space is improved. Then, the C2f of the fifth layer of the backbone network is replaced by the receptive field attention convolution, which enhances the model’s ability to capture the global context information of the features. In addition, the C2f and C2fCIB structures in the upsampling operation in the neck network are replaced by the hybrid local channel attention mechanism module, which significantly improves the feature representation ability of the model. Results: In order to validate the effectiveness of the YOLO-KRM model, detailed experiments were conducted on two remote-sensing datasets, RSOD and NWPU VHR-10. The experimental results show that, compared with the original model YOLOv10x, the mAP@50 of the YOLO-KRM model on the two datasets is increased by 1.77% and 2.75%, respectively, and the mAP @ 50:95 index is increased by 3.82% and 5.23%, respectively; (3) Results: by improving the model, the accuracy of target detection in remote-sensing images is successfully enhanced. The experimental results verify the effectiveness of the model in dealing with complex backgrounds and small targets, especially in high-resolution remote-sensing images. Full article

Objectives: Chronic psychological stress among college students increases sensitivity to negative emotional stimuli. Emotion regulation, a critical coping mechanism, draws upon cognitive resources and may impair subsequent cognitive control. Physical exercise has been proposed as an effective intervention to enhance both emotional and cognitive functioning. This study investigated whether a 12-week structured exercise intervention could modulate emotion regulation outcomes and improve cognitive control in college students experiencing high psychological stress. Methods: Forty-seven college students, identified as highly stressed via the Chinese College Students Psychological Stress Scale, were randomly assigned to either an exercise group (n = 25) or a control group (n = 22). The exercise group participated in supervised rope-jumping sessions three times per week for 40 min, following ACSM guidelines, over 12 weeks. Before and after the intervention, participants completed tasks measuring two emotion regulation strategies—expressive suppression and cognitive reappraisal—and tasks assessing cognitive control. Results: A significant group × time × strategy interaction emerged for subjective emotional valence: following the intervention, the exercise group reported attenuated negative valence under expressive suppression. For subjective arousal, post-intervention ratings decreased under suppression but increased under reappraisal in the exercise group, suggesting strategy-specific modulation by physical activity. Regarding cognitive control, electrophysiological measures revealed that the P3 component showed a significant interaction: the exercise group exhibited enhanced P3 amplitudes in congruent versus incongruent conditions after the intervention. Moreover, P3 interference scores were significantly reduced post-intervention in the exercise group compared to both its pre-intervention baseline and the control group. Conclusions: A 12-week aerobic exercise intervention enhanced emotion regulation outcomes and improved cognitive control under high psychological stress. These findings underscore the utility of physical exercise as a non-pharmacological approach to bolster cognitive–affective resilience in young adults. Full article

Survivin, a pivotal member of the inhibitor of apoptosis proteins (IAP) family, plays critical roles in cell cycle regulation and division. Survivin is overexpressed in most malignancies, making it an attractive therapeutic target. Due to its high specificity and potency, siRNA-based RNA interference (RNAi) has emerged as a powerful therapeutic strategy for effectively downregulating disease-related genes such as survivin in cancer therapy. However, naked siRNA suffers from rapid enzymatic degradation, poor cellular uptake, and off-target effects, severely limiting its therapeutic efficacy in vivo. Development of polymer-based nanocarriers for tumor-targeted delivery of survivin siRNA (siSurvivin) holds great potential to address these challenges. In this review, we first described the structure and function of survivin and summarized the survivin-targeted therapeutic strategy. Then, the siRNA delivery systems, particularly the polymeric nanocarriers, were introduced. Furthermore, a plethora of polymer-based nanocarriers for tumor-targeted siSurvivin delivery, including synthetic polymers (branched polymers, dendritic polymers, polymeric micelles), natural polymers (polysaccharides, proteins, and others), lipid-polymer hybrid nanoparticles, and polymer composite nanoparticles, were elaborated. Promising results underscore the potential of polymer-based nanocarriers for survivin siRNA delivery to enhance cancer therapy, providing a roadmap for future clinical translation. Full article

Background/Objectives: Current bone-based landmark approaches have shown variable accuracy and poor reproducibility. We validated a two-point “tuberculum sellae–anterior clinoid process” (TS–ACP) line traced on routine 3D-computed tomography angiography (CTA) for predicting distal dural ring (DDR) position and quantified the interobserver agreement. Methods: We retrospectively reviewed data from 85 patients (87 aneurysms) who were treated via clipping between June 2012 and December 2024. Two blinded neurosurgeons classified each aneurysm as extradural, intradural, or straddling the TS–ACP line. The intraoperative DDR inspection served as the reference standard. Diagnostic accuracy, χ² statistics, and Cohen’s κ were calculated. Results: The TS–ACP line landmarks were identifiable in all cases. The TS–ACP line classification correlated strongly with operative findings (χ² = 138.3, p = 6.4 × 10⁻²⁹). The overall accuracy was 89.7% (78/87), and sensitivity and specificity for identifying intradural aneurysms were 94% and 82%, respectively. The interobserver agreement was substantial (κ = 0.78). Nine aneurysms were misclassified, including four cavernous-sinus lesions that partially crossed the DDR. Retrospective fusion using constructive interference in steady-state magnetic resonance imaging corrected these errors. Conclusions: The TS–ACP line represents a rapid, reproducible tool that reliably localizes the DDR on standard 3D-CTA, showing higher accuracy than previously reported single-landmark techniques. Its high accuracy and substantial inter-observer concordance support incorporation into routine preoperative assessments. Because the method depends on only two easily detectable bony points, it is well-suited for automated implementation, offering a practical pathway toward artificial intelligence-assisted stratification of paraclinoid aneurysms. Full article

Lidar has been extensively used in various applications, such as autonomous driving, robot navigation, and drone obstacle avoidance, due to its advantages of a high resolution, high-ranging accuracy, and strong anti-interference ability. The micro-electro-mechanical systems (MEMS) lidar technology approach has gained popularity due to its miniaturization and semi-solid state. However, the small scanning angle of the MEMS scanning micromirror and the associated radar system cause issues, such as a limited scanning range and low spatial resolution, which hinder the wider use of MEMS lidar. To address the problems caused by the small scanning angle of the MEMS micromirror and the limitations of the current optical system, this study suggests a new MEMS lidar transmitting optical system that offers a wide scanning angle and high spatial resolution. It is based on an array reflector group and a Fresnel lens, which enables the large-angle scanning of the target area while maintaining high spatial resolution. The scanning range is 120° × 60°, the spatial resolution is 0.05° × 0.25°, and the beam-filling ratio reaches 90.63%. Full article