Search Results (3,758)

Aiming at addressing the defect of the data blindness of a LiDAR point cloud in transparent media such as glass in low illumination environments, a new method is proposed to realize covert target reconnaissance, identification and ranging using the fusion of a shimmering polarized image and a laser LiDAR point cloud, and the corresponding system is constructed. Based on the extraction of pixel coordinates from the 3D LiDAR point cloud, the method adds information on the polarization degree and polarization angle of the micro-light polarization image, as well as on the reflective intensity of each point of the LiDAR. The mapping matrix of the radar point cloud to the pixel coordinates is made to contain depth offset information and show better fitting, thus optimizing the 3D point cloud converted from the micro-light polarization image. On this basis, algorithms such as 3D point cloud fusion and pseudo-color mapping are used to further optimize the matching and fusion procedures for the micro-light polarization image and the radar point cloud, so as to successfully realize the alignment and fusion of the 2D micro-light polarization image and the 3D LiDAR point cloud. The experimental results show that the alignment rate between the 2D micro-light polarization image and the 3D LiDAR point cloud reaches 74.82%, which can effectively detect the target hidden behind the glass under the low illumination condition and fill the blind area of the LiDAR point cloud data acquisition. This study verifies the feasibility and advantages of “polarization + LiDAR” fusion in low-light glass scene reconnaissance, and it provides a new technological means of covert target detection in complex environments. Full article

Free-space optical (FSO) communications have emerged as a promising complement to conventional radio-frequency (RF) systems due to their high bandwidth, low interference, and license-free spectrum. Visible-light FSO communication, using laser diodes or LEDs, offers potential for short-range data links, but performance is highly wavelength-dependent under varying atmospheric conditions. This study presents an experimental evaluation of three visible laser diodes at 650 nm (red), 532 nm (green), and 405 nm (violet), focusing on their optical output power, quantum efficiency, and modulation behavior across a range of driving currents and frequencies. A custom laboratory testbed was developed using an Atmega328p microcontroller and a Visual Basic control interface, allowing precise control of current and modulation frequency. A silicon photovoltaic cell was employed as the optical receiver and energy harvester. The results demonstrate that the 650 nm red laser consistently delivers the highest quantum efficiency and optical output, with stable performance across electrical and modulation parameters. These findings support the selection of 650 nm as the most energy-efficient and versatile wavelength for short-range, cost-effective visible-light FSO communication. This work provides experimentally grounded insights to guide wavelength selection in the development of energy-efficient optical wireless systems. Full article

Rock bolts are crucial components in the subterranean support systems in underground mines that provide adequate structural reinforcement to the rock mass to prevent unforeseen hazards like rockfalls. This makes frequent assessments of such bolts critical for maintaining rock mass stability and minimising risks in underground mining operations. Where manual surveying of rock bolts is challenging due to the low-light conditions in the underground mines and the time-intensive nature of the process, automated detection of rock bolts serves as a plausible solution. To that end, this study focuses on the automatic identification of rock bolts within medium- to large-scale 3D point clouds obtained from underground mines using mobile laser scanners. Existing techniques for automated rock bolt identification primarily rely on feature engineering and traditional machine learning approaches. However, such techniques lack robustness as these point clouds present several challenges due to data noise, varying environments, and complex surrounding structures. Moreover, the target rock bolts are extremely small objects within large-scale point clouds and are often partially obscured due to the application of reinforcement shotcrete. Addressing these challenges, this paper proposes an approach termed DeepBolt, which employs a novel two-stage deep learning architecture specifically designed for handling severe class imbalance for the automatic and efficient identification of rock bolts in complex 3D point clouds. The proposed method surpasses state-of-the-art semantic segmentation models by up to 42.5% in Intersection over Union (IoU) for rock bolt points. Additionally, it outperforms existing rock bolt identification techniques, achieving a 96.41% precision and 96.96% recall in classifying rock bolts, demonstrating its robustness and effectiveness in complex underground environments. Full article

Aiming to address the problems of asynchronous acquisition time of multiple sensors in the crop phenotype acquisition system and high cost of the acquisition equipment, this paper developed a low-cost crop phenotype synchronous acquisition system based on the PTP synchronization protocol, realizing the synchronous acquisition of three types of crop data: visible light images, thermal infrared images, and laser point clouds. The paper innovatively proposed the Difference Structural Similarity Index Measure (DSSIM) index, combined with statistical indicators (average point number difference, average coordinate error), distribution characteristic indicators (Charm distance), and Hausdorff distance to characterize the stability of the system. After 72 consecutive hours of synchronization testing on the timing boards, it was verified that the root mean square error of the synchronization time for each timing board reached the ns level. The synchronous trigger acquisition time for crop parameters under time synchronization was controlled at the microsecond level. Using pepper as the crop sample, 133 consecutive acquisitions were conducted. The acquisition success rate for the three phenotypic data types of pepper samples was 100%, with a DSSIM of approximately 0.96. The average point number difference and average coordinate error were both about 3%, while the Charm distance and Hausdorff distance were only 1.14 mm and 5 mm. This system can provide hardware support for multi-parameter acquisition and data registration in the fast mobile crop phenotype platform, laying a reliable data foundation for crop growth monitoring, intelligent yield analysis, and prediction. Full article

Quantum sensing based on NV-centers in diamonds has been demonstrated many times in multiple publications. The majority of publications use lasers in free space or lasers with fiber optics, expensive optical components such as dichroic mirrors, or beam splitters with dichroic filters and expensive detectors, such as Avalanche photodiodes or single photon detectors, overall, leading to custom and expensive setups. In order to provide an inexpensive NV-based magnetometer setup for educational use in schools, to teach the three topics, fluorescence, optically detected magnetic resonance, and Zeeman splitting, inexpensive, miniaturized, off-the-shelf components with high reliability have to be used. The cheaper such a setup, the more setups a school can afford. Hence, in this work, we investigated LEDs as light sources, considered different diamonds for our setup, tested different color filters, proposed an inexpensive microwave resonator, and used a cheap photodiode with an appropriate transimpedance amplifier as the basis for our quantum magnetometer. As a result, we identified cheap and functional components and present a setup and show that it can demonstrate the three topics mentioned at a hardware cost <EUR 100. Full article

Background: Previous research has demonstrated that 20 kHz probe or 37 kHz bath sonication of poloxamers comprising polypropylene glycol (PPG) and polyethylene glycol (PEG) blocks can generate degradation byproducts that are toxic to mammalian cells and organisms. Herein, an investigation of a PEGylated phospholipid micelle was undertaken to identify low-molecular-weight sonolytic degradation byproducts that could be cytotoxic. The concern here lies with the fact that sonication is a frequently employed step in drug delivery manufacturing processes, during which PEGylated phospholipids can be subjected to shear forces and other extreme oxidative and thermal conditions. Methods: Control and 20 kHz-sonicated micelles of DSPE-mPEG2000 were analyzed using dynamic light scattering (DLS) and zeta potential analyses to study colloidal properties, matrix-assisted laser desorption/ionization–time of flight (MALDI-TOF) mass spectroscopy (MS) and proton nuclear magnetic resonance (¹H-NMR) spectroscopy to study the structural integrity of DSPE-mPEG2000, and ¹H-NMR spectroscopy and high-performance liquid chromatography (HPLC) with ultraviolet (UV) detection to quantitate the formation of low-molecular-weight degradation byproducts. Results: MALDI-TOF-MS analyses of 20 kHz-sonicated DSPE-mPEG2000 revealed the loss of ethylene glycol moieties in accordance with depolymerization of the PEG chain; ¹H-NMR spectroscopy showed the presence of formate, a known oxidative/thermal degradation product of PEG; and HPLC-UV showed that the generation of formate was dependent on 20 kHz probe sonication time between 5 and 60 min. Conclusions: It was found that 20 kHz sonication can degrade the PEG chain of DSPE-mPEG2000, altering the micelle’s PEG corona and generating formate, a known ocular toxicant. Full article

Optical materials are widely used in large optical systems such as lithography machines and astronomical telescopes. However, optical materials inevitably produce subsurface damage (SSD) during lapping and polishing processes, degrading the laser damage threshold and impacting the service life of the optical system. The large surface roughness of the lapped optical materials further increases the difficulty of the nondestructive detection of SSD. Quantum dots (QDs) show great development potential in the nondestructive detection of SSD in lapped materials. However, existing QD-based SSD detection methods ignore the polarization sensitivity of QDs to excitation light, which affects the detection accuracy of SSD. To address this problem, this paper explores the fluorescence polarization properties of QDs in the SSD of optical materials. First, the detection principle of SSD based on the fluorescence polarization of QDs is investigated. Subsequently, a fluorescence polarization detection system is developed to analyze the fluorescence polarization properties of QDs in SSD. Finally, the SSD is detected based on the studied polarization properties. The results show that the proposed method effectively improves the detection rate of SSD by 10.8% and thus provides guidance for evaluating the quality of optical material and optimizing optical material processing technologies. The research paradigm is equally applicable to biomedicine, energy, optoelectronics, and the environment, where QDs have a wide range of applications. Full article

Background/Objectives: Although both the MEL90 (Carl Zeiss Meditec AG, Jena, Germany) and WaveLight EX500 (Alcon Laboratories, Inc., Fort Worth, TX, USA) are two widely used excimer lasers, comparisons between the two remain limited. This study evaluates visual and refractive outcomes from the U.S. Food and Drug Administration (FDA) premarket approval trials of these platforms in the treatment of myopia with and without astigmatism, hyperopia with and without astigmatism, and mixed astigmatism. Methods: Clinical outcomes from FDA premarket approval trials were compared between the recently approved MEL90 and the WaveLight (now termed EX500) excimer lasers. Results: A total of 714 eyes (358 patients) from MEL90 and 1353 eyes (706 patients) from EX500 were analyzed up to 6 months postoperatively. In the hyperopia/hyperopic astigmatism cohort, the EX500 demonstrated greater efficacy relative to MEL90, with more eyes achieving a postoperative uncorrected distance visual acuity (UDVA) of 20/20 or better (48.6% vs. 68.7%, respectively; p < 0.001). In both the MEL90 and EX500, at least 85% of eyes with myopia/myopic astigmatism and 68% with mixed astigmatism achieved a postoperative UDVA of 20/20 or better. For all refractive cohorts, more than 95% of eyes achieved a UDVA of 20/40 or better at 6 months (all p > 0.05). The EX500 was more likely to demonstrate an improvement of more than two lines of UDVA compared to baseline CDVA (all p < 0.05). In contrast, the MEL90 showed greater predictability of spherical equivalent within ±0.50 D and ±1.00 D for the hyperopia/hyperopic astigmatism cohort (both p = 0.007), as well as within ±0.50 D for the myopia/myopic astigmatism cohort (p < 0.001). Postoperatively, both platforms were associated with decreased glare and halos, although findings were variable in the EX500 mixed astigmatism cohort. Conclusions: Both excimer lasers demonstrated safe and effective outcomes that exceed the threshold set by the FDA. Full article

Silicon-based microcavity quantum dot lasers are attractive candidates for on-chip light sources in photonic integrated circuits due to their small size, low power consumption, and compatibility with silicon photonic platforms. However, integrating components like quantum dot lasers and photodetectors on a single chip remains challenging due to material compatibility issues and mode field mismatch problems. In this work, we have demonstrated monolithic integration of an InAs quantum dot microdisk light emitter, waveguide, and photodetector on a silicon platform using a shared epitaxial structure. The photodetector successfully monitored variations in light emitter output power, experimentally proving the feasibility of this integrated scheme. This work represents a key step toward multifunctional integrated photonic systems. Future efforts will focus on enhancing the light emitter output power, improving waveguide efficiency, and scaling up the integration density for advanced applications in optical communication. Full article

Pesticide residues in fruits and vegetables pose a serious threat to food safety. Traditional detection methods have defects such as complex operation, high cost, and long detection time. Therefore, it is of great significance to develop rapid, non-destructive, and efficient detection technologies and equipment. In recent years, the combination of spectroscopic techniques and imaging technologies with machine learning algorithms has developed rapidly, providing a new attempt to solve this problem. This review focuses on the research progress of the combination of spectroscopic techniques (near-infrared spectroscopy (NIRS), hyperspectral imaging technology (HSI), surface-enhanced Raman scattering (SERS), laser-induced breakdown spectroscopy (LIBS), and imaging techniques (visible light (VIS) imaging, NIRS imaging, HSI technology, terahertz imaging) with machine learning algorithms in the detection of pesticide residues in fruits and vegetables. It also explores the huge challenges faced by the application of spectroscopic and imaging technologies combined with machine learning algorithms in the intelligent perception of pesticide residues in fruits and vegetables: the performance of machine learning models requires further enhancement, the fusion of imaging and spectral data presents technical difficulties, and the commercialization of hardware devices remains underdeveloped. This review has proposed an innovative method that integrates spectral and image data, enhancing the accuracy of pesticide residue detection through the construction of interpretable machine learning algorithms, and providing support for the intelligent sensing and analysis of agricultural and food products. Full article

Background/Objectives: Magnetic iron oxide nanoparticles (IONPs), human serum albumin (HSA) and folic acid (FA) are prospective components for hybrid nanosystems for various biomedical applications. The magnetic nanosystems FA-HSA@IONPs (FAMs) containing IONPs, HSA, and FA residue are engineered in the study. Methods: Composition, stability and integrity of the coating, and peroxidase-like activity of FAMs are characterized using UV/Vis spectrophotometry (colorimetric test using o-phenylenediamine (OPD), Bradford protein assay, etc.), spectrofluorimetry, dynamic light scattering (DLS) and electron magnetic resonance (EMR). The selectivity of the FAMs accumulation in cancer cells is analyzed using flow cytometry and confocal laser scanning microscopy. Results: FAMs (d_N~55 nm by DLS) as a drug delivery platform have been administered to cancer cells (human breast adenocarcinoma MCF-7 and MDA-MB-231 cell lines) in vitro. Methylene blue, as a model photosensitizer, has been non-covalently bound to FAMs. An increase in photoinduced cytotoxicity has been found upon excitation of the photosensitizer bound to the coating of FAMs compared to the single photosensitizer at equivalent concentrations. The suitability of the nanosystems for photodynamic therapy has been confirmed. Conclusions: FAMs are able to effectively enter cells with increased folate receptor expression and thus allow antitumor photosensitizers to be delivered to cells without any loss of their in vitro photodynamic efficiency. Therapeutic and diagnostic applications of FAMs in oncology are discussed. Full article

This study focuses on the analysis of soliton solutions within the framework of the time-fractional cubic–quintic nonlinear Schrödinger equation (TFCQ-NLSE), a powerful model with broad applications in complex physical phenomena such as fiber optic communications, nonlinear optics, optical signal processing, and laser–tissue interactions in medical science. The nonlinear effects exhibited by the model—such as self-focusing, self-phase modulation, and wave mixing—are influenced by the combined impact of the cubic and quintic nonlinear terms. To explore the dynamics of this model, we apply a robust analytical technique known as the sub-ODE method, which reveals a diverse range of soliton structures and offers deep insight into laser pulse interactions. The investigation yields a rich set of explicit soliton solutions, including hyperbolic, rational, singular, bright, Jacobian elliptic, Weierstrass elliptic, and periodic solutions. These waveforms have significant real-world relevance: bright solitons are employed in fiber optic communications for distortion-free long-distance data transmission, while both bright and dark solitons are used in nonlinear optics to study light behavior in media with intensity-dependent refractive indices. Solitons also contribute to advancements in quantum technologies, precision measurement, and fiber laser systems, where hyperbolic and periodic solitons facilitate stable, high-intensity pulse generation. Additionally, in nonlinear acoustics, solitons describe wave propagation in media where amplitude influences wave speed. Overall, this work highlights the theoretical depth and practical utility of soliton dynamics in fractional nonlinear systems. Full article

This study examined the integraftion of airborne Light Detection and Ranging (LiDAR), Simultaneous Localization and Mapping (SLAM)-based handheld LiDAR, and iPhone LiDAR to inspect forest road networks following forest operations. The goal is to overcome the challenges posed by dense canopy cover and ensure accurate and efficient data collection and mapping. Airborne data were collected using the DJI Matrice 300 RTK UAV equipped with a Zenmuse L2 LiDAR sensor, which achieved a high point density of 285 points/m² at an altitude of 80 m. Ground-level data were collected using the BLK2GO handheld laser scanner (HPLS) with SLAM methods (LiDAR SLAM, Visual SLAM, Inertial Measurement Unit) and the iPhone 13 Pro Max LiDAR. Data processing included generating DEMs, DSMs, and True Digital Orthophotos (TDOMs) via DJI Terra, LiDAR360 V8, and Cyclone REGISTER 360 PLUS, with additional processing and merging using CloudCompare V2 and ArcGIS Pro 3.4.0. The pairwise comparison analysis between ALS data and each alternative method revealed notable differences in elevation, highlighting discrepancies between methods. ALS + iPhone demonstrated the smallest deviation from ALS (MAE = 0.011, RMSE = 0.011, RE = 0.003%) and HPLS the larger deviation from ALS (MAE = 0.507, RMSE = 0.542, RE = 0.123%). The findings highlight the potential of fusing point clouds from diverse platforms to enhance forest road mapping accuracy. However, the selection of technology should consider trade-offs among accuracy, cost, and operational constraints. Mobile LiDAR solutions, particularly the iPhone, offer promising low-cost alternatives for certain applications. Future research should explore real-time fusion workflows and strategies to improve the cost-effectiveness and scalability of multisensor approaches for forest road monitoring. Full article

Segregative phase separation technology demonstrates substantial potential for precise molecular fractionation in food and biomaterial applications. The investigation elucidates the causal relationship between viscosity variations and phase separation dynamics, which govern molecular fractionation in GA/HPMC composite systems. By conducting a comparative analysis of two GA subtypes (CGA and SGA) and three HPMC grades with controlled viscosity gradients, we utilized gel permeation chromatography-multi-angle laser light scattering (GPC-MALLS) coupled with rheological characterization to elucidate the critical relationship between continuous phase viscosity and fractionation efficiency. Notably, increasing HPMC viscosity significantly intensified phase separation, resulting in selective enrichment of arabinogalactan-protein complexes: from 6.3% to 8.5% in CGA/HPMC systems and from 27.3% to 36.5% in SGA/HPMC systems. Further mechanistic investigation revealed that elevated HPMC viscosity enhances thermodynamic incompatibility while slowing interfacial mass transfer, synergistically driving component redistribution. These findings establish a quantitative viscosity–fractionation relationship, offering theoretical insights for optimizing GA/HPMC systems in emulsion stabilization, microencapsulation, and functional biopolymer purification via viscosity-mediated phase engineering. Full article

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