Under vehicle-mounted working conditions, precision equipment is highly susceptible to vibrations induced by road roughness. Therefore, the base must provide effective vibration isolation and damping to prevent damage to precision components. To address this issue, a magnetorheological elastomer (MRE) semi-active vibration absorber for broadband damping is designed according to structural and magnetic circuit requirements. Different from traditional single-parameter design, this design adopts an integrated design approach combining dynamic modeling and magnetic circuit simulation by establishing a two-degree-of-freedom dynamic model under road excitation. It realizes broadband adjustment of the absorber stiffness, which can adapt to broadband road excitations in the range up to 10 Hz in vehicle-mounted environments. The damping performance is evaluated through magnetic circuit simulation and experimental tests on a dedicated platform. The results show that, compared with the passive vibration absorber, the proposed MRE vibration absorber reduces the vibration amplitude of the primary system by 81.8

Specular reflection is a prevalent disturbance factor in both leaf-scale and canopy-scale vegetation remote sensing. It depends on leaf surface properties and does not provide information about internal leaf composition, thereby affecting the inversion of biochemical parameters based on spectral indices. Traditional methods often fail to adequately address this issue, as they struggle to decouple specular reflection from diffuse scattering without compromising vital spectral and structural details. To overcome this critical limitation, this study introduces a novel specular reflection removal method based on the fusion of Mueller matrix polarization parameters and spectral information. A ground-based, time-sequential Mueller matrix multispectral system was constructed to acquire multi-polarization and multi-band data. By analyzing the Mueller matrix's differential response to specular and diffuse reflection, highlight-sensitive and scatter-robust elements were selected to construct Mueller Matrix Polarization Parameters (MMPs). These were combined with red and near-infrared a priori spectral information to develop the specular reflection removal index-Integrated NDVI-Mueller Vegetation Index (INMVI). This index effectively suppresses surface reflection while preserving spectral detail and textural structure. Leaf-scale experiments validated the method across different health levels and two morphologically distinct plant species (Aucuba japonica var. variegata and the highly glossy Philodendron selloum Koch), as well as under varying illumination intensities from 8 to 125 lx. INMVI achieved high accuracy in estimating relative chlorophyll content (Soil and Plant Analysis Development, SPAD) (R-2 = 0.9058, RMSE = 5.6753) and demonstrated exceptional illumination-invariant stability (R-2 > 0.87 across all light intensities). Results indicate that the proposed method effectively eliminates specular reflection under diverse geometric, lighting, and surface conditions. Compared to traditional spectral indices, it better preserves leaf texture and detail while improving the SPAD estimation performance. This provides a robust specular reflection removal strategy for precise vegetation health monitoring under complex conditions.

Monitoring changes in plant chlorophyll content is crucial for understanding plant growth, detecting vegetation pests and diseases, and assessing vegetation feedback to global climate change. However, Specular reflections from leaf surfaces often complicate these measurements, reducing the accuracy of chlorophyll content inversion. Vegetation indices are widely used for chlorophyll content inversion, and when the effect of specular reflection is not correctly considered, the vegetation indices may inaccurately estimate chlorophyll content. In this paper, to address the challenge of removing the interference of vegetation specular reflection under different health states, we analyzed the interference mechanism of 15 vegetation indices under different health states by vegetation specular reflection and proposed a DoLP-based specular reflection removal vegetation index (DSRVI) for removing the interference of specular reflection under different health states. The results showed that NRI was weakly affected by specular reflection, and SR was more sensitive to specular reflection. Specular reflection removal in different health states was carried out using DSRVI, and it was seen that DSRVI correlated well with SPAD in both the healthy state (coefficient of determination (R2) = 0.915, RMSE = 5.606) and the Stressed grade-2 state (coefficient of determination (R2) = 0.891, RMSE = 5.529), thus highlighting the importance of DSRVI in removing the potential of DSRVI in eliminating specular reflection and recognizing plant health status.

In the realm of underwater detection technologies, reconstructing the three-dimensional structure of underwater objects is crucial for applications such as underwater target tracking, target locking, and navigational guidance. As a primary tool for underwater detection, acoustical imaging faces significant challenges in recovering the three-dimensional structure of objects from two-dimensional images. Current 3-D reconstruction methods mainly focus on reconstructing objects at the riverbed, overlooking the reconstruction of objects in the water in the absence of shadows. This study introduces a multiangle shape and height recovery method for such specific situations. By fixing the sonar detection angle and utilizing ViewPoint software to measure the contours of objects at different depths, a superimposition technique for two-dimensional sonar images was developed to achieve three-dimensional reconstruction of shadowless sonar image data. The proposed method is specifically designed for scenarios with diffuse echoes, where the sound waves scatter from rough surfaces rather than reflect specularly from smooth surfaces. This limitation ensures the method's applicability to objects lacking strong mirror-like reflections. This technique has been validated on three different categories of targets, with the reconstructed 3-D models accurately compared to the actual size and shape of the targets, demonstrating the method's effectiveness and providing a theoretical and methodological foundation for the 3-D reconstruction of underwater sonar targets.

We propose and experimentally demonstrate an economical optical tweezers probe based on the fusion of several commercial optical fibers. By optimizing the structural parameters of the probe, non-contact active capture and manipulation of single or multiple biological particles were achieved. First, the probe structural parameter range was analyzed theoretically, and the theory was cross-verified by the finite element method. Second, the influence of the probe structure and length parameters on the laser focusing performance and particle capture ability was studied, and the optimal structural parameters of the probe in particle capture were determined. The measured capture distance exceeded 50 mu m, and the movement velocity of the particle during manipulation was measured. Finally, the capture performance before and after parameter optimization was compared with the dynamic effect of the particles, and the generation mechanism of multiple light traps and the mechanical properties of multi-particles during multi-particle capture were studied. The results indicate that this probe is expected to be used in biological or chemical micromanipulation research. (c) 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

A non-contact inspection method incorporating acoustic-optical fusion is proposed in this paper to detect hollowing defects in external wall tiles in order to overcome the practical problems of traditional contact detection methods. Based on laser speckle interferometry (LSI) technology, this approach employs audio loading to detect hollowing in the wall structure. In this paper, the ceramic tile above the hollowing is equivalent to a circular thin plate with peripheral fixed support. Following Kirchhoff’s classical theory of the circular plate, the circular plate displacement function based on the improved Fourier series is employed for theoretical modelling. The theoretical natural frequencies of the circular plate under peripheral fixed support boundaries are derived and compared with finite element simulation results, a theoretical mapping model of the structure vibration signals and the laser speckle signal is established and the phase difference change diagram and Bessel interference fringe pattern are derived. The result indicates the accuracy of the vibration theoretical model based on the classical Kirchhoff circular plate theory. Subsequently, an experimental system is established and non-destructive testing experiments for hollowing defect inspection are conducted based on theoretical predictions. Different acoustic parameters are used to excite the wall sample and interference fringe patterns are obtained through use of a laser speckle interferometer. The results indicate that the experiment result is consistent with the theoretical result and the fringe pattern near the theoretical solution value of the natural frequency is more pronounced, confirming the effectiveness and feasibility of the non-destructive testing technique for characterising hollowing defects based on laser speckle interferometry.

In order to solve the problems of low image exposure,low contrast and difficulty of feature extrac-tion in real-time animal monitoring at night,we proposed a lightweight self-supervised deep neural network Zero-Denoise and an improved YOLOv8 model for image enhancement and accurate recognition of nocturn-al animal targets.The first stage of rapid enhancement was performed by lightweight PDCE-Net.A new lighting loss function was proposed,and the second stage of re-enhancement was carried out in PRED-Net based on the Retinex principle and the maximum entropy theory,using the original image and fast enhance-ment image corrected by the parameter adjustable Gamma.Then,the YOLOv8 model was improved to re-cognize the re-enhanced image.Finally,experimental analysis was conducted on the LOL dataset and the self-built animal dataset to verify the improvement of the Zero-Denoise network and YOLOv8 model for nocturnal animal target monitoring.The experimental results show that the PSNR,SSIM,and MAE indicat-ors of the Zero-Denoise network on the LOL dataset reach 28.53,0.76,and 26.15,respectively.Combined with the improved YOLOv8,the mAP value of the baseline model on the self-built animal dataset increases by 7.1%compared to YOLOv8.Zero-Denoise and improved YOLOv8 can achieve good quality images of nocturnal animal targets,which can be helpful in further study of accurate methods of monitoring these targets.

To solve the problems with the existing methods for detecting hollowing defects, such as inconvenient operation, low efficiency and intense subjectivity, and to improve the efficiency of the acoustic-optic fusion method for detecting hollowing defects, in this paper the vibration characteristics of hollowing defects are measured and analyzed using a laser self-mixing interferometer. The ceramic tile above the hollowing defect is equivalent to a thin circular plate with peripheral fixed support. According to Kirchhoff's classical circular plate theory and the circular plate displacement function based on the improved Fourier series, a theoretical model of a circular plate is established. By solving the characteristic equation, the theoretical modal parameters of hollowing defects are obtained. Subsequently, an experimental system based on a laser self- mixing interferometer is built, and modal experiments are carried out using the hammering method. The experimental modal parameters are obtained with a professional modal analysis software. Through comparative analysis between the theoretical and experimental modal parameters, the error of the natural frequency results is found to be tiny and the mode shapes are consistent. These results provide theoretical guidance for a practical non-destructive acoustic-optic fusion method for detecting hollowing defects.

The use of projection to spread landmines in predetermined areas (i.e., scattered landmines) is a commonly used method of landmine deployment in modern warfare. Due to the complex battlefield environment, scattered landmines are usually hidden in jungle and grassland environments, and are of the same color as the surrounding environment. Detecting camouflaged scattered landmines hidden in vegetation environments is challenging. Therefore, a camouflage scattered landmine detection algorithm based on polarization spectrum fusion is proposed to solve the problem of difficulty in effectively detecting camouflage scattered landmines in vegetation environments. The algorithm is divided into three steps: 1) obtaining the polarized hyperspectral dataset of the landmines and identifying the sensitive bands of the landmines; 2) Calculate the characteristic spectral image X of the landmines based on the sensitive band of the landmines, and calculate the DoLP λ and AOP λ images based on polarization data; 3) Transform the X, DoLP λ , and AOP λ images from RGB to HSV space, separate the H, S, and V components, and then replace the V component with the X image. Finally, perform the HSV inverse transformation to obtain the fused image F. The experimental results show that the algorithm effectively improves the contrast of the landmines (contrast: 0.97). The Receiver operating characteristic (ROC) shows that when Pfa (probability of false alarm) =0.065 (6.5%), the fused image F has the highest landmine detection rate Pd (probability of detection) = 0.95 (95%), with almost no false positives.

The study presents a method for designing phase masks, specifically the ring-shaped segmentation method, which can be employed in creating the modulation phase for specialized point spread functions (PSFs), such as multi-focus PSFs and those with axial encoding functions. An algorithm for phase inversion optimization is introduced to enhance the optical transfer function efficiency of the designed phase mask, which is based on the Fresnel approximation imaging inverse operation and iterative Fourier transform algorithm. The ring-shaped segmentation phase design approach effectively combines individual phases, resulting in unified PSFs with unique properties. The promising outcomes demonstrated by the designed PSFs are truly remarkable. The refined phase masks and experimental verification further validate the effectiveness of this groundbreaking approach. This advancement in ring-shaped segmentation method development has significant potential for real-world applications, representing a noteworthy contribution to the field of optical imaging.

On-chip structured light, with potentially infinite complexity, has emerged as a linchpin in the realm of integrated photonics. However, the realization of arbitrarily tailoring a multitude of light field dimensions in complex media remains a challenge1, Through associating physical light fields and mathematical function spaces by introducing a mapping operator, we proposed a data-driven inverse design method to precisely manipulate between any two structured light fields in the on-chip high-dimensional Hilbert space. To illustrate, light field conversion in on-chip topological photonics was achieved. High-performance topological coupling devices with minimal insertion loss and customizable topological routing devices were designed and realized. Our method provides a new paradigm to enable precise manipulation over the on-chip vectorial structured light and paves the way for the realization of complex photonic functions.

This paper proposes a straightforward method for measuring micro-displacement synchronously along two orthogonal axes. A single structure consists of a pair of two-dimensional gratings and a quadrant detector aligned with a collimated laser is used to detect the micro-displacement. The crosstalk and the common-mode noise are eliminated through a two-step differential process. Experimental results demonstrate that the displacement measurement resolution can reach 40 nm with a sensitivity of 0.483 V/µm within the linear range. The accuracy obtained is 0.29% on the X-axis and 0.31% on the Y-axis within a 500 µm range. The signal-to-noise ratio is improved by 4.56 dB after differential. The simplicity and high compactness of this measurement structure make it suitable for fabrication and alignment using microfabrication processes, which show great potential in many applications such as gyroscopes, accelerators, and multi-dimensional displacement measurements.

On-board precision equipment installed in vehicles is susceptible to vibrations caused by irregularities on the road surface, which may decrease accuracy and damage to components. Installing a vibration absorption system in the vehicle is necessary to mitigate the impact of vehicle vibrations on the equipment. Vibration systems widely use vibration absorbers based on magnetorheological elastomer (MRE). Previous research has mainly used Proportional-Integral-Derivative (PID), fuzzy control, and ON-OFF algorithms to control the vibration absorption system. However, these algorithms exhibit poor control accuracy and adaptability in uncertain environments. To enhance the adaptive capabilities of vibration absorbers in time-varying environments and to maximize their performance, this study explores the use of the Twin Delayed Deep Deterministic Policy Gradient (TD3) control algorithm. Additionally, we proposed an Immune Optimization Twin Delayed Deep Deterministic Policy Gradient (IO-TD3) control algorithm to address the low-efficiency issue in the initial training stages. Simulation results show that, compared to the TD3 algorithm, Double Q-Deep Deterministic Policy Gradient (Double Q-DDPG) algorithm, Deep Deterministic Policy Gradient (DDPG) algorithm, and Deep Q-Network (DQN) algorithm, the IO-TD3 algorithm significantly exhibits faster convergence speed and improved stability. Finally, we apply the IO-TD3 algorithm to the MRE absorber controller and verify the controller's performance using the Monte Carlo method. The results show that the controller using the IO-TD3 control algorithm has high control accuracy and stability.

We present a design approach for a symmetric power exponential phase, resulting in a phase-modulated point-spread function with two symmetrical mainlobes that can be steered toward the optical axis opposite the x axis. This design offers nanoscale 3D localization capabilities suitable for 3D single-molecule tracking and localization imaging. The axial probing depth of this symmetric power exponential point-spread function can be adjusted as needed by manipulating specific parameters. Optimization of the symmetric power exponential phase involves truncation filtering to reduce sidelobes and the utilization of a phase inversion-based optimization algorithm to enhance transfer function efficiency and localization precision. A successful multi-molecule 3D tracking experiment was conducted at a 10 µm axial depth using a numerical aperture of 1.4 to validate the efficacy of the proposed design methodology.

We proposed and experimentally validated an all-fiber probe based on the fusion splicing of multiple fibers, designed to capture the cells or microparticles. Introducing the 980 nm laser into the optical fiber and shaping the beam with the probe, which was fabricated by coaxially splicing the no-core fiber (NCF) with the graded-index (GRIN) fiber onto the single-mode fiber (SMF), created a light trap. (We took the first letters of three types of fibers and named it SNG probe.) The focusing effect of the Gaussian beam was tuned by matching the lengths of the NCF and GRIN to achieve optical trapping of particles. We simulated the optical field of the SNG all-fiber optical tweezers (AFOTs) and the dynamic force distribution of microparticles at different positions within the optical field. We also developed a numerical analytical model of the OTs to analyze the effect of fiber length on the capture performance. The output optical field distribution of the SNG AFOTs was experimentally tested, confirming the capability of this fiber tweezer for non-contact and long-distance capture of yeast cells (more than 240 mu m). This type of OTs has the potential to advance relevant research in biology and chemistry. (c) 2024 Society of Photo-Optical Instrumentation Engineers (SPIE)

Research the imaging detection technology of tiny fiber optic endoscope based on EMCCD low-light camera for narrow lumen and low-light imaging, build a test system and conduct performance test analysis. A bimodal endoscopic imaging detection system was set up with a colour camera and a low-light EMCCD camera. The method of combining visual cognition with the definition evaluation function based on discrete cosine transform, is employed to evaluate the performance of optical fiber endoscope detection system based on EMCCD camera. Then use EMCCD low-light camera to perform weak fluorescence imaging test of pig stomach tissue . The test results show that under the given experimental conditions, the minimum light intensity is 230 Lux required for the colour camera system, while the minimum light intensity is 40 Lux required for the EMCCD camera system, and the weak fluorescence signal can be well excited and displayed under low light conditions. Based on the low-light imaging performance of EMCCD, it can be used for better endoscope miniaturization.

The detection and analysis of circulating tumor cells (CTCs) would be of aid in a precise cancer diagnosis and an efficient prognosis assessment. However, traditional methods that rely heavily on the isolation of CTCs based on their physical or biological features suffer from intensive labor, thus being unsuitable for rapid detection. Furthermore, currently available intelligent methods are short of interpretability, which creates a lot of uncertainty during diagnosis. Therefore, we propose here an automated method that takes advantage of bright-field microscopic images with high resolution, so as to take an insight into cell patterns. Specifically, the precise identification of CTCs was achieved by using an optimized single-shot multi-box detector (SSD)–based neural network with integrated attention mechanism and feature fusion modules. Compared to the conventional SSD system, our method exhibited a superior detection performance with the recall rate of 92.2%, and the maximum average precision (AP) value of 97.9%. To note, the optimal SSD-based neural network was combined with advanced visualization technology, i.e., the gradient-weighted class activation mapping (Grad-CAM) for model interpretation, and the t-distributed stochastic neighbor embedding (T-SNE) for data visualization. Our work demonstrates for the first time the outstanding performance of SSD-based neural network for CTCs identification in human peripheral blood environment, showing great potential for the early detection and continuous monitoring of cancer progression.

Shallow underground target detection technology has received more and more attention, such as pipeline detection, cavity detection, underground military facility detection and underground archaeology. Based on the description of the acoustic-to-seismic coupling mechanism, the technology of laser speckle interferometry and its characteristics for acoustic-to-seismic coupling detection methods are summarized and analyzed. The subwoofer based on the sound catheter is used as the sound source excitation module, and the laser speckle interferometry system is used to conduct rapid detection experiments on the vibration characteristics of the ground surface coupled by sound waves, and the changes of laser speckle interference fringes are studied under different experimental conditions such as sound wave intensity and buried environment. Experimental results show that the laser speckle interferometry can be applied to the rapid measurement of acoustic-to-seismic coupling characteristic signals and has broad application prospects in the field of rapid non-destructive detection of flexible shallow buried objects.

A roller monitoring method based on a distributed fiber-optic acoustic sensor (DAS) is investigated to identify roller faults in a belt conveyor. Based on the principle of using a DAS to detect the fault vibration characteristic signal of an idler, a belt conveyor test system with a belt length of 30 m is constructed to simulate different fault conditions, such as idler jamming, no bearing, and fracture for experimental data collection. By analyzing the collected sound signals in the time and frequency domains, the characteristic quantities under different faults are extracted to identify the faults in the idler. The experimental results show that the DAS can detect the fault vibration characteristics of the belt conveyor idler and has application prospect in the fault monitoring of industrial belt conveyor idler.

Vegetation remote sensing monitoring has been widely used in various fields, such as crop disease and insect pest monitoring, forest coverage monitoring, and vegetation growth monitoring. Monitoring changes in plant chlorophyll content is of great significance for understanding plant growth, monitoring vegetation pests and diseases, and even monitoring vegetation feedback on global climate change. However, these monitoring are often disturbed by the specular reflection of leaves, which reduces the inversion accuracy of chlorophyll content. This paper aims to eliminate the specular reflection interference in remote sensing monitoring of plant health, a polarization multispectral imaging system was established, a specular reflection removal index (SRRI) was proposed. A fusion algorithm was proposed to detect plants based on the spectral and polarization characteristics of diffuse and specular reflection of vegetation. SRRI, degree of linear polarization (DoLP) and angle of polarization (AOP) are all calculated in the fusion algorithm to eliminate the interference of specular reflection and improve the accuracy of plant health status detection. In addition, a fusion algorithm based on SRRI, DoLP and AOP calculates a polarization fusion specular reflection removal index (PFSRRI). Correlation analysis was performed on relative chlorophyll content (SPAD), ratio vegetation index (SR), normalized vegetation index (NDVI), SRRISR, SRRINDVI, PFSRRISR and PFSRRINDVI to understand their ability to eliminate specular reflection interference. The results showed that SR and SPAD (R-2=0.012 8) and NDVI and SPAD (R-2=0.007 5) had the worst correlation, indicating that SR and NDVI had the highest sensitivity to mirror reflection. SRRISR and SPAD (R-2=0.818), and SRRINDVI and SPAD (R-2=0.889) had a good correlation. The correlation between PFSRRISR and SPAD (R-2=0.955) and PFSRRINDVI and SPAD (R2=0.948) was the best, which highlighted the potential of PFSRRI in eliminating mirror reflection interference and detecting plant health status. PFSRRISR and PFSRRINDVI 3d scatter plots show good discrimination ability for different health degrees of plants, with high sensitivity and specificity. The variation trend and classification status of vegetation health state can be intuitively seen through the color and trend of the surfaces. Among them, the sensitivity and specificity of PFSRRISR to classify specular leaves from stress level-1 was 100% and 100%, and the sensitivity and specificity of PFSRRINDVI to classify specular leaves from stress level-1 was 98% and 100%, indicating the excellent detection performance of PFSRRSR and PFSRRINDVI after removing specular interference. In summary, this method can effectively eliminate specular reflection interference and improve the detection accuracy of vegetation health status.