Search Results (275)

To enable accurate evaluation of satellite laser communication terminals under solar outage interference, this paper presents the design and implementation of a solar radiation simulation system targeting the 1540–1560 nm communication band. The system reconstructs co-propagating interference conditions through standardized and continuously tunable output, based on high irradiance and spectral uniformity. A compound beam homogenization structure—combining a multimode fiber and an apodizator—achieves 85.8% far-field uniformity over a 200 mm aperture. A power–spectrum co-optimization strategy is introduced for filter design, achieving a spectral matching degree of 78%. The system supports a tunable output from 2.5 to 130 mW with a 50× dynamic range and maintains power control accuracy within ±0.9%. To suppress internal background interference, a BRDF-based optical scattering model is established to trace primary and secondary stray light paths. Simulation results show that by maintaining the surface roughness of key mirrors below 2 nm and incorporating a U-shaped reflective light trap, stray light levels can be reduced to 5.13 × 10⁻¹² W, ensuring stable detection of a 10⁻¹⁰ W signal at a 10:1 signal-to-background ratio. Experimental validation confirms that the system can faithfully reproduce solar outage conditions within a ±3° field of view, achieving consistent performance in spectrum shaping, irradiance uniformity, and background suppression. The proposed platform provides a standardized and practical testbed for ground-based anti-interference assessment of optical communication terminals. Full article

The rapid advancement of genomic technologies has significantly transformed biomedical research and clinical applications, particularly in oncology. Identifying patient-specific genetic mutations has become a crucial tool for early cancer detection and personalized treatment strategies. Detecting tumors at the earliest possible stage provides critical insights beyond traditional tissue analysis. This paper presents a novel cyber-physical system that combines high-resolution tissue scanning, laser microdissection, next-generation sequencing, and genomic analysis to offer a comprehensive solution for early cancer detection. We describe the methodologies for scanning tissue samples, image processing of the morphology of single cells, quantifying morphometric parameters, and generating and analyzing real-time genomic metadata. Additionally, the intelligent system integrates data from open-access genomic databases for gene-specific molecular pathways and drug targets. The developed platform also includes powerful visualization tools, such as colon-specific gene filtering and heatmap generation, to provide detailed insights into genomic heterogeneity and tumor foci. The integration and visualization of multimodal single-cell genomic metadata alongside tissue morphology and morphometry offer a promising approach to precision oncology. Full article

Accurate land-use classification is critical for urban planning and environmental monitoring, yet effectively integrating heterogeneous data sources such as hyperspectral imagery and laser radar (LiDAR) remains challenging. To address this, we propose MixtureRS, a compact multimodal network that effectively integrates hyperspectral imagery and LiDAR data for land-use classification. Our approach employs a 3-D plus heterogeneous convolutional stack to extract rich spectral–spatial features, which are then tokenized and fused via a cross-modality transformer. To enhance model capacity without incurring significant computational overhead, we replace conventional dense feed-forward blocks with a sparse Mixture-of-Experts (MoE) layer that selectively activates the most relevant experts for each token. Evaluated on a 15-class urban benchmark, MixtureRS achieves an overall accuracy of 88.6%, an average accuracy of 90.2%, and a Kappa coefficient of 0.877, outperforming the best homogeneous transformer by over 12 percentage points. Notably, the largest improvements are observed in water, railway, and parking categories, highlighting the advantages of incorporating height information and conditional computation. These results demonstrate that conditional, expert-guided fusion is a promising and efficient strategy for advancing multimodal remote sensing models. Full article

We developed a mathematical model to examine the scattering of radiation by a periodic structure of circular and elliptical microcavities formed in a planar optical waveguide. The waveguide simulates the behaviour of a 62.5/125 µm multimode optical fibre. The calculations focused on the intensity distribution of scattered light with a wavelength of 1310 nm along the periodic structure, i.e., along the side surface of the waveguide, as a function of the microcavity dimensions and their spatial arrangement within the waveguide core. The optimal geometrical parameters of the microstructure, ensuring the most uniform light scattering, were identified. The model is valid for multimode optical fibres containing strictly periodic structures of microcavities with spherical or elliptical cross-sections that scatter laser radiation in all directions. One potential application of such fibres is as light sources in medical probes for surgical procedures requiring additional illumination and uniform irradiation of affected tissues. Furthermore, the findings of this study offer significant potential for the development of sensing elements for fibre-optic sensors. The findings of this study will facilitate the design of scattering structures with microcavities that ensure a highly uniform scattering pattern. Full article

The Zhurong rover of the Tianwen-1 mission has detected sulfates in its landing area. The analysis of these sulfates provides scientific evidence for exploring past hydration conditions and atmospheric evolution on Mars. As a non-contact technique with long-range detection capability, Laser-Induced Breakdown Spectroscopy (LIBS) is widely used for elemental identification on Mars. However, quantitative analysis of anionic elements using LIBS remains challenging due to the weak characteristic spectral lines of evaporite salt elements, such as sulfur, in LIBS spectra, which provide limited quantitative information. This study proposes a quantitative analysis method for sulfur in sulfate-containing Martian analogs by leveraging spectral line correlations, full-spectrum information, and prior knowledge, aiming to address the challenges of sulfur identification and quantification in Martian exploration. To enhance the accuracy of sulfur quantification, two analytical models for high and low sulfur concentrations were developed. Samples were classified using infrared spectroscopy based on sulfur content levels. Subsequently, multimodal deep learning models were developed for quantitative analysis by integrating LIBS and infrared spectra, based on varying concentrations. Compared to traditional unimodal models, the multimodal method simultaneously utilizes elemental chemical information from LIBS spectra and molecular structural and vibrational characteristics from infrared spectroscopy. Considering that sulfur exhibits distinct absorption bands in infrared spectra but demonstrates weak characteristic lines in LIBS spectra due to its low ionization energy, the combination of both spectral techniques enables the model to capture complementary sample features, thereby effectively improving prediction accuracy and robustness. To validate the advantages of the multimodal approach, comparative analyses were conducted against unimodal methods. Furthermore, to optimize model performance, different feature selection algorithms were evaluated. Ultimately, an XGBoost-based feature selection method incorporating prior knowledge was employed to identify optimal LIBS spectral features, and the selected feature subsets were utilized in multimodal modeling to enhance stability. Experimental results demonstrate that, compared to the BPNN, SVR, and Inception unimodal methods, the proposed multimodal approach achieves at least a 92.36% reduction in RMSE and a 46.3% improvement in R². Full article

In this work, we propose a geolocation framework for distant ground targets integrating laser rangefinder sensors with multimodal visual servo control. By simulating binocular visual servo measurements through monocular visual servo tracking at fixed time intervals, our approach requires only single-session sensor attitude correction calibration to accurately geolocalize multiple targets during a single flight, which significantly enhances operational efficiency in multi-target geolocation scenarios. We design a step-convergent target geolocation optimization algorithm. By adjusting the step size and the scale factor of the cost function, we achieve fast accuracy convergence for different UAV reconnaissance modes, while maintaining the geolocation accuracy without divergence even when the laser ranging sensor is turned off for a short period. The experimental results show that through the UAV’s continuous reconnaissance measurements, the geolocalization error of remote ground targets based on our algorithm is less than 7 m for 3000 m, and less than 3.5 m for 1500 m. We have realized the fast and high-precision geolocalization of remote targets on the ground under the high-altitude reconnaissance of UAVs. Full article

Fish is important for human health due to its high nutritional value. However, it is prone to spoilage due to its structural characteristics. Traditional freshness assessment methods, such as visual inspection, are subjective and prone to inconsistency. This study proposes a novel, cost-effective hybrid methodology for automated three-level fish freshness classification (Day 1, Day 2, Day 3) by integrating single-wavelength laser reflectance data with deep learning-based image features. A comprehensive dataset was created by collecting visual and laser data from 130 mackerel specimens over three consecutive days under controlled conditions. Image features were extracted using four pre-trained CNN architectures and fused with laser features to form a unified representation. The combined features were classified using SVM, MLP, and RF algorithms. The experimental results demonstrated that the proposed multimodal approach significantly outperformed single-modality methods, achieving average classification accuracy of 88.44%. This work presents an original contribution by demonstrating, for the first time, the effectiveness of combining low-cost laser sensing and deep visual features for freshness prediction, with potential for real-time mobile deployment. Full article

By measuring the transfer function of the single-mode multi-aperture vertical-cavity surface-emitting laser (SM MA VCSEL) transmitting over a long single-mode fiber at 850 nm, we confirm that the chirp of the SM MA VCSEL under study is dominated by transient chirp with an alpha value of −3.81 enabling a 19 GHz bandwidth over 10 km of single-mode fiber. The detailed measurement of the VCSEL with different bias currents also allows us to recover other key characteristics of the VCSEL, thereby enabling us to practically construct the optical eye diagrams that closely match the experimentally measured ones. The link-level transfer function can be obtained using an analytical equation including effects of modal dispersion and laser chirp–chromatic dispersion (CD) interaction for an MMF of a given length and bandwidth grade. The narrow linewidth and chirp characteristics of the SM MA VCSEL enable transmission performance that surpasses that of conventional MM VCSELs, achieving comparable transmission distances at moderate modal bandwidths for OM3 and OM4 fibers and significantly longer reaches when the modal bandwidth is higher. The transmission performance was also confirmed with the modeled eye diagrams using extracted VCSEL parameters. The chirp properties also provide sufficient bandwidth for SM MA VCSEL transmission over kilometer-scale lengths of single-mode fibers at a high data rate of 100G or above with sufficient optical power coupled into the fibers. Advanced transmission distances are possible over multimode and single-mode fibers versus chirp-free devices. Full article

The timely detection of delamination is essential for preventing catastrophic failures and extending the service life of carbon fiber-reinforced polymers (CFRP). Full wavefields in CFRP encapsulate extensive information on the interaction between guided waves and structural damage, making them a widely utilized tool for damage mapping. However, due to the multimodal and dispersive nature of guided waves, interpreting full wavefields remains a significant challenge. This study proposes an end-to-end delamination imaging approach based on UNet++ using 2D frequency domain spectra (FDS) derived from full wavefield data. The proposed method is validated through a self-constructed simulation dataset, experimental data collected using Scanning Laser Doppler Vibrometry, and a publicly available dataset created by Kudela and Ijjeh. The results on the simulated data show that UNet++, trained with multi-frequency FDS, can accurately predict the location, shape, and size of delamination while effectively handling frequency offsets and noise interference in the input FDS. Experimental results further indicate that the model, trained exclusively on simulated data, can be directly applied to real-world scenarios, delivering artifact-free delamination imaging. Full article

Visual impairment or even loss seriously affects quality of life. Benefited by the rapid development of sound/laser detection, Global Positioning System (GPS)/Beidou positioning, machine vision and other technologies, the quality of life of blind people is expected to be improved through visual substitution technology. The existing visual substitution devices still have limitations in terms of safety, robustness, and ease of operation. The remote companion system developed here fully utilizes multimodal navigation and remote communication technologies, and the positioning and interaction functions of commercial mobile phones. Together with the accumulated judgment of backend personnel, it can provide real-time, safe, and reliable navigation services for blind people, helping them complete daily activities such as independent travel, circulation, and shopping. The practical results show that the system not only has strong operability and is easy to use, but also can provide users with a strong sense of security and companionship, making it suitable for promotion. In the future, this system can also be promoted for other vulnerable groups such as the elderly. Full article

Background: Age-related macular degeneration (AMD) is one of the leading causes of permanent vision loss in the elderly, particularly in higher-income countries. Fundus autofluorescence (FAF) imaging is a widely used, non-invasive technique that complements structural imaging in the assessment of retinal pigment epithelium (RPE) integrity. While optical coherence tomography (OCT) remains the gold standard for retinal imaging due to its high-resolution cross-sectional visualization, FAF offers unique metabolic insights. Among the FAF modalities, blue light FAF (B-FAF) is more commonly employed, whereas green light FAF (G-FAF) provides subtly different image characteristics, particularly improved visualization and contrast in the central macula. Despite identical acquisition times and nearly indistinguishable workflows, G-FAF is notably underutilized in clinical practice. Objectives: This narrative review critically compares green and blue FAF in terms of their diagnostic utility relative to OCT, with a focus on lesion detectability, macular pigment interference, and clinical decision-making in retinal disorders. Methods: A comprehensive literature search was performed using the PubMed database for studies published prior to February 2025. The search utilized the keywords fundus autofluorescence and age-related macular degeneration. The primary focus was on short-wavelength FAF and its clinical utility in AMD, considering three aspects: diagnosis, follow-up, and prognosis. The OCT findings served as the reference standard for anatomical correlation and diagnostic accuracy. Results: Both FAF modalities correlated well with OCT in detecting RPE abnormalities. G-FAF demonstrated improved visibility of central lesions due to reduced masking by macular pigment and enhanced contrast in the macula. However, clinical preference remained skewed toward B-FAF, driven more by tradition and device default settings than by evidence-based superiority. G-FAF’s diagnostic potential remains underrecognized despite its comparable practicality and subtle imaging advantages specifically for AMD patients. AMD stages were accurately characterized, and relevant images were used to highlight the significance of G-FAF and B-FAF in the examination of AMD patients. Conclusions: While OCT remains the gold standard, FAF provides complementary information that can guide management strategy. Since G-FAF is functionally equivalent in acquisition, it offers slight advantages. Broader awareness and more frequent integration of G-FAF that could optimize multimodal imaging strategies, particularly in the intermediate stage, should be developed. Full article

Vertical-cavity surface-emitting laser (VCSEL)-based transmission over multimode fiber (MMF) has achieved data rates of 100G per lane and is progressing towards 200G/lane, which demands more modal bandwidth from MMF to ensure adequate transmission reach. We address the needs of higher modal bandwidth from the point of view of engineering VCSEL launch conditions. We explore the options for using subsets of 10 standard-based launch conditions by analyzing the measured encircled fluxes from commercial VCSEL transceivers over two options. By utilizing experimentally measured MMF data, we demonstrated a significant improvement in modal bandwidth with these options. The launch conditions also impact the wavelength dependence of modal bandwidth for VCSELs operating at wavelengths longer than 850 nm. We conducted detailed Monte Carlo simulation of the wavelength dependence of modal bandwidth over MMFs. For one launch condition option using a smaller area, the modal bandwidths are improved over the effective modal bandwidth (EMB), and favor very high data rate transmission by allowing the use of a smaller area photodetector. Full article

Lasers are increasingly used in the biomedical field because of their concentrated energy, good stability, ease of use, and other advantages, promoting the development of precision medicine to a higher level. Medical laser equipment has transformed from a single therapeutic tool in an intelligent and precise diagnostic system. Existing clinical laser equipment has significant technical bottlenecks regarding soft-tissue ablation precision and multimodal diagnostic compatibility, which seriously restricts its clinical application. High-power thulium-doped fiber lasers with operating wavelengths of 1.9–2.1 μm provide a revolutionary solution for minimally invasive surgery due to their high compatibility with the absorption peaks of water molecules in biological tissues. This study reviews recent advances in high-power thulium-doped fiber lasers for minimally invasive therapies in the biomedical field. Breakthrough results in four major clinical application scenarios, namely, urological lithotripsy, tumor precision ablation, disfiguring dermatological treatment, and minimally invasive endovenous laser ablation, are also summarized. By systematically evaluating its potential for multimodal diagnostic and therapeutic applications and thoroughly exploring the technical challenges and strategies for clinical transformation, we aim to provide a theoretical basis and practical guidance for the clinical transformation and industrialization of new-generation medical laser technology. Full article

Aiming to address the problems of fewer related studies on autonomous navigation algorithms based on multi-sensor fusion in complex scenarios in pastures, lower degrees of fusion, and insufficient cruising accuracy of the operation path in complex outdoor environments, a multimodal autonomous navigation system is proposed based on a loosely coupled architecture of Cartographer–RTAB-Map (real-time appearance-based mapping). Through laser-vision inertial guidance multi-sensor data fusion, the system achieves high-precision mapping and robust path planning in complex scenes. First, comparing the mainstream laser SLAM algorithms (Hector/Gmapping/Cartographer) through simulation experiments, Cartographer is found to have a significant memory efficiency advantage in large-scale scenarios and is thus chosen as the front-end odometer. Secondly, a two-way position optimization mechanism is innovatively designed: (1) When building the map, Cartographer processes the laser with IMU and odometer data to generate mileage estimations, which provide positioning compensation for RTAB-Map. (2) RTAB-Map fuses the depth camera point cloud and laser data, corrects the global position through visual closed-loop detection, and then uses 2D localization to construct a bimodal environment representation containing a 2D raster map and a 3D point cloud, achieving a complete description of the simulated ranch environment and material morphology and constructing a framework for the navigation algorithm of the pushing robot based on the two types of fused data. During navigation, the combination of RTAB-Map’s global localization and AMCL’s local localization is used to generate a smoother and robust positional attitude by fusing IMU and odometer data through the EKF algorithm. Global path planning is performed using Dijkstra’s algorithm and combined with the TEB (Timed Elastic Band) algorithm for local path planning. Finally, experimental validation is performed in a laboratory-simulated pasture environment. The results indicate that when the RTAB-Map algorithm fuses with the multi-source odometry, its performance is significantly improved in the laboratory-simulated ranch scenario, the maximum absolute value of the error of the map measurement size is narrowed from 24.908 cm to 4.456 cm, the maximum absolute value of the relative error is reduced from 6.227% to 2.025%, and the absolute value of the error at each location is significantly reduced. At the same time, the introduction of multi-source mileage fusion can effectively avoid the phenomenon of large-scale offset or drift in the process of map construction. On this basis, the robot constructs a fusion map containing a simulated pasture environment and material patterns. In the navigation accuracy test experiments, our proposed method reduces the root mean square error (RMSE) coefficient by 1.7% and Std by 2.7% compared with that of RTAB-MAP. The RMSE is reduced by 26.7% and Std by 22.8% compared to that of the AMCL algorithm. On this basis, the robot successfully traverses the six preset points, and the measured X and Y directions and the overall position errors of the six points meet the requirements of the pasture-pushing task. The robot successfully returns to the starting point after completing the task of multi-point navigation, achieving autonomous navigation of the robot. Full article

Advanced packaging represents a crucial technological evolution aimed at overcoming limitations posed by Moore’s Law, driving the semiconductor industry from two-dimensional toward three-dimensional integrated structures. The increasing complexity and miniaturization of electronic devices have significantly heightened the challenges associated with failure analysis during process development. The focused ion beam–scanning electron microscope (FIB-SEM), characterized by its high processing precision and exceptional imaging resolution, has emerged as a powerful solution for the fabrication, defect localization, and failure analysis of micro- and nano-scale devices. This paper systematically reviews the innovative applications of FIB-SEM in the research of core issues, such as through-silicon-via (TSV) defects, bond interfacial failures, and redistribution layer (RDL) electromigration. Additionally, the paper discusses multimodal integration strategies combining FIB-SEM with advanced analytical techniques, such as high-resolution three-dimensional X-ray microscopy (XRM), electron backscatter diffraction (EBSD), and spectroscopy. Finally, it provides a perspective on the emerging applications and potential of frontier technologies, such as femtosecond-laser-assisted FIB, in the field of advanced packaging analysis. Full article