Search Results (460)

Soil-transmitted helminths (STHs) present a significant global health challenge, particularly in tropical and subtropical regions. The current diagnostic standard involves the microscopic examination of a stool smear but it lacks sensitivity to detect infections of low intensity. Innovative solutions like lab-on-a-disk (LoD) technologies are emerging, showing promise in detecting low-intensity infections. Field tests conducted using our SIMPAQ (single-image parasite quantification) LoD device have demonstrated its potential as a diagnostic tool, especially for such low-intensity infections. Nevertheless, the device’s efficiency has been limited by significant egg loss during sample preparation, low capture efficiency of eggs within the Field of View (FOV), and the presence of larger fecal debris that obstructs effective egg trapping and imaging. In this study, we conducted a set of laboratory experiments using model polystyrene particles and purified STH eggs to improve the sample preparation protocol. These experiments include the entire SIMPAQ procedure starting from sample preparation, infusing it into the LoD device, centrifugation, delivering the (model) eggs to the FOV, capturing an image, and analyzing it. We analyzed egg losses at each step of the procedure following the “standard” protocol, then elaborated and tested alternative, more efficient procedures. The resulting modified protocol significantly minimized particle and egg loss and reduced the amount of debris in the disk, thus enabling effective egg capture and clear images in the FOV, increasing the reliability of the diagnostic results. Full article

We propose a hybrid-integrated III–V-silicon optical-phased-array (OPA) based on passive alignment flip–chip bonding technology and provide new solutions for LiDAR. To achieve a large range of vertical beam steering in a hybrid-integrated OPA, a multi-lines OPA in a single chip is introduced. The system allows parallel hybrid integration of multiple dies onto a single wafer, achieving a multi-fold improvement in tuning efficiency. In order to increase the range of horizontal beam steering, we propose a half-wavelength pitch waveguide emitter with non-uniform width to reduce the crosstalk, which can remove the higher-order grating lobes in free space. In this work, we simulate OPA individually for four-lines and eight-lines. As a result, we simultaneously achieved a beam steering with nearly ±90° (horizontal) × 17.2° (vertical, when four-line OPA) or 39.6° (vertical, when eight-line OPA) field of view (FOV) and a high tuning efficiency with 1.13°/nm (when eight-line OPA). Full article

Stellar refraction autonomous navigation provides a promising alternative for cross-domain vehicles, particularly in near-space environments where traditional inertial and satellite navigation methods face limitations. This study develops a stellar refraction navigation system that utilizes stellar refraction angle observations and the Implicit Unscented Kalman Filter (IUKF) for state estimation. A representative orbit with altitudes ranging from 60 km to 200 km is designed to simulate cross-domain flight conditions. The navigation performance is analyzed under varying conditions, including orbital altitude, as well as star sensor design parameters, such as limiting magnitude, field of view (FOV) value, and measurement error, along with different sampling intervals. The simulation results show that increasing the limiting magnitude from 5 to 8 reduced the position error from 705.19 m to below 1 m, with optimal accuracy reaching 0.89 m when using a 20° × 20° field of view and a 3 s sampling interval. In addition, shorter sampling intervals improved accuracy and filter stability, while longer intervals introduced greater integration drift. When the sampling interval reached 100 s, position error grew to the kilometer level. These findings validate the feasibility of using stellar refraction for autonomous navigation in cross-domain scenarios and provide design guidance for optimizing star sensor configurations and sampling strategies in future near-space navigation systems. Full article

Optical systems with wide field-of-view (FOV) imaging capabilities are crucial for applications ranging from biomedical diagnostics to remote sensing, yet conventional wide-angle optics face integration challenges in compact platforms. Here, we present the design and experimental demonstration of a single-layer silicon carbide (SiC) metalens achieving a 90° total FOV, whose planar structure and small footprint address the challenges. This design is driven by a gradient-based numerical optimization strategy, Gradient-Optimized Phase Profile Shaping (GOPP), which optimizes the phase profile to accommodate the angle-dependent requirements. Combined with a front aperture, the GOPP-generated phase profile enables off-axis aberration control within a planar structure. Operating at 803 nm with a focal length of 1 mm (NA = 0.25), the fabricated metalens demonstrated focusing capabilities across the wide FOV, enabling effective wide-angle imaging. This work demonstrates the feasibility of using numerical optimization to realize single-layer metalens with challenging wide FOV capabilities, offering a promising route towards highly compact imagers for applications such as endoscopy and dermoscopy. Full article

Objective: This ex vivo study aimed to evaluate the influence of different acquisition protocols, combining voxel size and field of view (FOV), across four cone-beam computed tomography (CBCT) systems, on the accuracy of alveolar bone level measurements for periodontal assessment. Materials and Methods: A dry human mandible was used, with standardized radiopaque markers placed on the cementoenamel junction (CEJ) of the buccal–mesial and buccal–distal aspects of teeth 34 and 43. CBCT scans were performed using four systems—Veraview^® X800, OP300 Pro^®, I-CAT Next Generation^®, and Orthophos XG^®—applying various combinations of field of view (FOV) and voxel resolution available in each device. Reference measurements were obtained in situ using a digital caliper. CBCT images were exported in DICOM format and analyzed with OnDemand3D software (version 4.6) to obtain paracoronal sections. Linear measurements from the CEJ to the alveolar crest were recorded in triplicate and compared to the gold standard using ANOVA and the Dunnett test (α = 0.05). Results: Protocols with smaller voxel sizes and limited FOVs generally yielded measurements closer to the gold standard. However, some larger-FOV protocols with intermediate voxel sizes also achieved comparable accuracy. Among the systems, the I-CAT showed lower agreement within in situ measurements, while others demonstrated reliable performance depending on the acquisition parameters. Conclusions: The findings suggest that CBCT protocols with smaller voxel sizes and reduced FOVs can enhance measurement accuracy in periodontal bone assessments. Nevertheless, intermediate protocols may offer a balance between diagnostic quality and radiation exposure, aligning with the ALADA principle. This study reinforces the need for standardized acquisition parameters tailored to periodontal imaging. Full article

Fusarium oxysporum f. sp. vasinfectum (Fov) is a devastating cotton pathogen. Australian Fov strains are distinguished by their ability to infect plants without nematode interaction and are genetically distinct from global Fov, classified into two vegetative compatibility groups (VCG-01111 and VCG-01112). Here, we present chromosome-level genome assemblies of a historical isolate for each Australian Fov VCG. The end-to-end gapless genome assemblies demonstrate high contiguity and completeness, with 97.7% BUSCO completeness for both isolates. Phylogenetic analysis indicates that the Australian Fov lineages diverged from other known Fov genomes over 3.6 million years ago, while VCG-01111 and VCG-01112 separated approximately 1.1 million years ago. Comparative genomics analysis identified four accessory chromosomes unique to the Australian isolates. Functional annotations revealed 14,495 and 15,342 genes in VCG-01111 and VCG-01112, respectively, with accessory chromosomes containing significantly fewer genes than core chromosomes. Ortholog analysis uncovered unique gene clusters enriched in key metabolic pathways, pathogenicity, and cell division processes. Additionally, we identified several novel lineage-specific peptides unique to each Australian isolate. This comprehensive genomic characterization provides the first insights into the unique evolutionary history of Australian Fov, distinguishing them from global Fov races. Our findings lay the foundation for understanding the genetic factors underlying their exceptional virulence, which makes Australian Fov among the most aggressive cotton pathogens worldwide. Full article

Integral imaging is a promising 3D sensing and visualization technique that enables full-parallax and continuous viewpoint reconstruction. However, challenges, such as depth distortion and a limited field-of-view (FoV), can compromise the quality of 3D visualization. This paper proposes a method to optimize the display of captured 3D scenes for integral imaging optical display systems. To achieve high-quality 3D visualization, the captured 2D images are processed to align the depth range and field-of-view with the specification of the display system. The proposed approach computationally scales the captured scene nonuniformly across three dimensions, integrating a depth scaling process and a scene resizing process. By generating synthetic 2D elemental images tailored to a specific 3D display system, the proposed method can enhance depth accuracy and display adaptability. Experimental results demonstrate that our method significantly improves 3D display quality, offering a more immersive and visually accurate representation. Full article

Panoramic 3D object detection is a challenging task due to image distortion, sensor heterogeneity, and the difficulty of combining information from multiple modalities over a wide field-of-view (FoV). To address these issues, we propose SMM-POD, a novel framework that introduces a spherical multi-stage fusion strategy for panoramic 3D detection. Our approach creates a five-channel spherical image aligned with LiDAR data and uses a quasi-uniform Voronoi sphere (UVS) model to reduce projection distortion. A cross-attention-based feature extraction module and a transformer encoder–decoder with spherical positional encoding enable the accurate and efficient fusion of image and point cloud features. For precise 3D localization, we adopt a Frustum PointNet module. Experiments on the DAIR-V2X-I benchmark and our self-collected SHU-3DPOD dataset show that SMM-POD achieves a state-of-the-art performance across all object categories. It significantly improves the detection of small objects like cyclists and pedestrians and maintains stable results under various environmental conditions. These results demonstrate the effectiveness of SMM-POD in panoramic multi-modal 3D perception and establish it as a strong baseline for wide FoV object detection. Full article

Accurate and non-invasive optical metrology of transparent objects is essential in several commercial and research applications, from fluid dynamics to biomedical imaging. In this work, a digital holography approach for thickness measurement of glass plate and temperature mapping of candle flame is presented that leverages a double-field-of-view (FOV) configuration combined with high spatial bandwidth utilization (SBU). By capturing a multiplexed hologram from two distinct objects in a single shot, the system overcomes the limitations inherent to single-view holography, enabling more comprehensive object information of thickness measurement and temperature-induced refractive index variations. The method integrates double-FOV digital holography with high SBU, allowing for accurate surface profiling and mapping of complex optical path length changes caused by temperature gradients. The technique exhibits strong potential for applications in the glass industry and microfluidic thermometry, convection analysis, and combustion diagnostics, where precise thermal field measurements are crucial. This study introduces an efficient holographic framework that advances the capabilities of non-contact measurement applications by integrating double-FOV acquisition into a single shot with enhanced spatial bandwidth exploitation. The approach sets the groundwork for real-time, volumetric thermal imaging and expands the applicability of digital holography in both research and industrial settings. Full article

Capsule endoscopy (CE) has revolutionized gastrointestinal (GI) diagnostics by providing a non-invasive, patient-centered approach to observing the digestive tract. Conceived in 2000 by Gavriel Iddan, CE employs a diminutive, ingestible capsule containing a high-resolution camera, LED lighting, and a power supply. It specializes in visualizing the small intestine, a region frequently unreachable by conventional endoscopy. CE helps detect and monitor disorders, such as unexplained gastrointestinal bleeding, Crohn’s disease, and cancer, while presenting a lower procedural risk than conventional endoscopy. Contrary to conventional techniques that necessitate anesthesia, CE reduces patient discomfort and complications. Nonetheless, its constraints, specifically the incapacity to conduct biopsies or therapeutic procedures, have spurred technical advancements. Five primary types of capsule endoscopes have emerged: steerable, magnetic, robotic, tethered, and hybrid. Their performance varies substantially. For example, the image sizes vary from 256 × 256 to 640 × 480 pixels, the fields of view (FOV) range from 140° to 360°, the battery life is between 8 and 15 h, and the frame rates fluctuate from 2 to 35 frames per second, contingent upon motion-adaptive capture. This study addresses a significant gap by methodically evaluating CE platforms, outlining their clinical preparedness, and examining the underexploited potential of artificial intelligence in improving diagnostic precision. Through the examination of technical requirements and clinical integration, we highlight the progress made in overcoming existing CE constraints and outline prospective developments for next-generation GI diagnostics. Full article

In this study, we propose a novel approach for dynamic micro-vibration measurement based on an interferometric system utilizing a fractional optical vortex (FOV) beam as the reference and a Gaussian beam as the measurement path. The reflected Gaussian beam encodes the vibration information of the target, which is extracted by analyzing the rotational behavior of the petal-like interference pattern formed through coaxial interference with the FOV beam. When the topological charge (TC) of the FOV beam is less than or equal to one, a single-petal structure is generated, significantly reducing the complexity of angular tracking compared to traditional multi-petals OAM-based methods. Moreover, using a Gaussian beam as the measurement path mitigates spatial distortions during propagation, enhancing the overall robustness and accuracy. We systematically investigate the effects of TC, CCD frame rate, and interference contrast on measurement performance. Experimental results demonstrate that the proposed method achieves high angular resolution with a minimum angle deviation of 18.2 nm under optimal TC conditions. The system exhibits strong tolerance to environmental disturbances, making it well-suited for applications requiring non-contact, nanometer-scale vibration sensing, such as structural health monitoring, precision metrology, and advanced optical diagnostics. Full article

Optical communication is a critical technology for future deep space exploration, offering substantial advantages in transmission capacity and spectrum utilization. This paper establishes a comprehensive theoretical framework for avalanche photodiode (APD)-based deep space optical uplink communication under combined channel impairments, including atmospheric and coronal turbulence induced beam scintillation, pointing errors, angle-of-arrival (AOA) fluctuations, link attenuation, and background noise. A closed-form analytical channel model unifying these effects is derived and validated through Monte Carlo simulations. Webb and Gaussian approximations are employed to characterize APD output statistics, with theoretical symbol error rate (SER) expressions for pulse position modulation (PPM) derived under diverse impairment scenarios. Numerical results demonstrate that the Webb model achieves higher accuracy by capturing APD gain dynamics, while the Gaussian approximation remains viable when APD gain exceeds a channel fading-dependent gain threshold. Key system parameters such as APD gain and field-of-view (FOV) angle are analyzed. The optimal APD gain significantly influences the achievement of optimal SER performance, and angle of FOV design balances AOA fluctuations tolerance against noise suppression. These findings enable hardware optimization under size, weight, power, and cost (SWaP-C) constraints without compromising performance. Our work provides critical guidelines for designing robust APD-based deep space optical uplink communication systems. Full article

As in-vehicle display environments become increasingly common, addressing motion sickness has become essential due to the intensified visual and vestibular discrepancies introduced by media experiences within vehicles. Prior research highlights that minimizing the conflict between vestibular signals and visual motion perception is crucial for reducing motion sickness. This study aims to identify optimal viewing conditions and simulation settings for motion sickness reduction by experimentally adjusting field of view (FOV) and screen brightness. Specifically, the FOV is narrowed according to vehicle acceleration and angular speed, aligning with simulated vehicle motion through a motion simulator connected to a head-mounted display (HMD). The experimental results indicate that this approach can reduce motion sickness by up to 40%. Additionally, integrating the generated motion data with VR motion data enables a realistic simulation of in-vehicle conditions, suggesting that this method may enhance comfort in actual in-vehicle media environments. Full article

Background/Objectives: Lutetium-177 is a widely used radioisotope in targeted radionuclide therapy, particularly for treating certain types of cancers relying on beta and low-energy gamma emissions, making it suitable for both therapeutic and post-therapy monitoring purposes. The purpose of this study was to evaluate the technical parameters for developing a prototype portable gamma camera dedicated to ¹⁷⁷Lu imaging applications. Methods: The well-validated GATE Monte Carlo toolkit was used to study the characteristics of the system and evaluate its performance in terms of spatial resolution, sensitivity, and image quality. For this purpose, a series of Monte Carlo simulations were executed, modeling a channel-edge aperture pinhole collimator incorporating a variety of computational phantoms. The final configuration of the prototype was standardized, incorporating the crystal size, collimator design, shielding, and the optimal FOV. After the development of the actual prototype camera, the system was also validated experimentally on the same setups as the simulations. Results: The final configuration of the prototype imaging system was standardized based on simulation results and then experimentally validated using physical phantoms under equivalent conditions. A minification of 1:5, spatial resolution of 1.0 cm, and sensitivity of 5.2 Cps/MBq at 10 cm distance source-to-collimator distance were assessed and confirmed. The experimental results agreed within 5% of simulated values. Conclusions: This study establishes the technical feasibility and foundational performance of a portable pinhole imaging system for potential clinical use in ¹⁷⁷Lu imaging workflows and thereby improving therapeutic effectiveness. Full article

To address the challenges of detection and acquisition caused by trajectory prediction errors during the midcourse–terminal guidance handover phase in cross-domain unmanned aerial vehicles (CDUAV), this study proposes a collaborative multi-interceptor detection coverage optimization method based on predictive error pipeline modeling. Firstly, we employ nonlinear least squares to fit parameters for the motion model of CDUAV. By integrating error propagation theory, we derive a recursive expression for error pipelines under t-distribution and establish a parametric model for the target’s high-probability region (HPR). Next, we analyze target acquisition scenarios during guidance handover and reformulate the collaborative detection problem as a field-of-view (FOV) coverage optimization task on a two-dimensional detection plane. This framework incorporates the target HPR and the seeker detection FOV models, with an objective function defined for coverage optimization. Finally, inspired by wireless sensor network (WSN) coverage strategies, we implement the starfish optimization algorithm (SFOA) to enhance computational efficiency. Simulation results demonstrate that compared to Monte Carlo statistical methods, our parametric modeling approach reduces prediction error computation time from 15.82 s to 0.09 s while generating error pipeline envelopes with 99% confidence intervals, showing superior generalization capability. The proposed collaborative detection framework effectively resolves geometric coverage optimization challenges arising from mismatches between target HPR and FOV morphology, exhibiting rapid convergence and high computational efficiency. Full article