Competition for shared limiting resources within and between species is a powerful force in biological communities. Modern coexistence theory predicts that higher intra-specific, relative to inter-specific, competition results in species coexistence. However, resource use is rarely constant across animal development, whereby many species experience ontogenetic dietary shifts, suggesting that the relative strengths of competition may change throughout ontogeny. To quantify potential competition between invasive and native stream fishes throughout ontogeny, we measured isotopic niche overlap of individual lifetime trophic trajectories constructed using fish eye lens stable isotope analysis coupled with otolith growth measurements. Overlap of stable isotope ratios between individuals offers a proxy measurement for competition in resource space. We found that invasive green sunfish (Lepomis cyanellus) exhibited higher intra-specific isotopic niche overlap across ontogeny than inter-specific overlap with three native fish species (Gila robusta, Catostomus insignis, Catostomus clarkii) in Burro Creek, Arizona. These native fish species exhibited the highest isotopic niche overlap with green sunfish; a known superior competitor due to their generalist feeding habits and high rates of resource exploitation. The degree of resource overlap experienced by native species increased throughout ontogeny, while invasive green sunfish were freed from high interspecific resource overlap at older ages. Our results suggest that the native species are vulnerable to competitive exclusion by green sunfish. As invasive species continue to spread, contemporary ecological communities are increasingly being managed for coexistence, rather than invader eradication. Understanding how relative competition transforms throughout ontogeny supports the persistence of native species within mixed native-nonnative communities.

A Maxwell fish-eye lens in a Bose–Einstein condensate

Fisheye lenses can capture surrounding spatial information at once, making them widely applied in various fields. However, the imaging principle of fisheye lenses does not satisfy the collinearity equation, so the theory of orthorectification using traditional differential orthorectification is no longer applicable for a fisheye image in practice. Therefore, this paper develops a single-spherical-geometry-transformation model for fisheye image orthorectification. This model directly establishes the relationship between spatial ground points and image plane coordinates through spherical geometry, and then combines the digital surface model (DSM) to correct points in the fisheye image to their correct positions on a pixel-by-pixel basis, thereby achieving fisheye image orthorectification. To validate the feasibility of the proposed orthorectification model, an indoor calibration field was established. Experimental validation was then conducted using two fisheye image datasets: an indoor dataset acquired in the calibration field with a digital single-lens reflex (DSLR) camera and an outdoor dataset acquired with an unmanned aerial vehicle (UAV). The results of the two groups of experiments demonstrate that the proposed model can effectively orthorectify fisheye images with ground accuracies of 0.055 m and 0.097 m in x and y direction, respectively.

Enhanced elastic wave imaging with asymmetric Maxwell fish-eye lens

Image stitching is a computational technique designed to align and seamlessly fuse multiple overlapping images into a single panoramic image with an extended field of view. It plays a critical role in diverse domains, including mobile photography, autonomous navigation, and visual perception systems. However, most conventional image stitching pipelines implicitly assume that the input images have been pre-corrected for geometric distortions, particularly radial distortion inherent to wide-angle and fisheye lenses. This assumption often fails in practice, as many consumer-grade cameras lack built-in correction or calibration support. Consequently, applying standard image stitching methods to the uncorrected imagery frequently degrades feature correspondence reliability and introduces visible geometric misalignments and seam discontinuities in the final panorama. To overcome these limitations, this paper introduces a task-driven joint iterative optimization framework for image stitching that unifies unsupervised radial distortion correction, distortion-aware feature registration, and seam-aware blending within a single cohesive optimization objective. Specifically, lens distortion parameters are explicitly modeled as learnable variables and embedded into both the geometric registration and seam optimization sub-problems. An efficient closed-loop optimization strategy is then employed to jointly refine distortion parameters, homography estimates, and optimal seam paths in an alternating, mutually reinforcing manner. Implementation-wise, we first propose a calibration-free initial radial distortion estimation method which leverages intrinsic image gradients and epipolar consistency to provide physically plausible initialization for subsequent optimization. During iteration, distortion parameters are progressively refined by integrating robust geometric constraints derived from current feature matches (via RANSAC-based consensus filtering) with photometric consistency cues. Extensive experiments on multiple public benchmarks featuring pronounced radial distortion demonstrate that our method achieves superior stitching fidelity using metrics including PSNR and SSIM. It also confirms enhanced feature matching stability, which outperforms both distortion-agnostic approaches and two-stage pipelines that decouple distortion correction from registration. Furthermore, comprehensive ablation studies quantitatively and qualitatively validate the functional necessity and synergistic contribution of each core module, confirming the design rationale and effectiveness of the proposed joint optimization architecture.

Abstract Contemporary security systems integrate object detection algorithms with surveillance cameras to identify and localize objects. While object detection systems are widely used in surveillance applications, their application to screen capture prevention faces practical limitations due to restricted camera field of view. This paper presents a geometric modeling and experimental evaluation framework to mitigate these coverage limitations using cost-effective hardware configurations for preventing smartphone-based data leakage. We derive a mathematical model to determine the optimal number and placement of conventional webcams required to minimize blind regions. In addition, we conduct a systematic comparative analysis of four camera architectures: traditional webcams, multi-camera networks, multilens modules, and fisheye systems. While fisheye lenses provide broader angular coverage, their radial distortion degrades detection performance if not properly addressed. To improve robustness, we introduce a heterogeneous training strategy based on mixed conventional and fisheye image datasets. Experimental results using a YOLOv4-based detector show that the model trained on the mixed dataset achieves 94.6% mAP@0.5, significantly outperforming models trained on single-source datasets in wide-angle deployment scenarios. The findings provide practical guidelines for jointly optimizing camera configuration and model training, demonstrating that combining mixed-dataset learning with wide-angle optics offers a cost-effective and technically robust solution for large-scale corporate display protection.

This brief report describes the incidence and characteristics of ocular abnormalities in healthy term newborn infants (HTNI) in 5,000 consecutive eye examinations from a database of 32,000 infants from 17 hospitals in São Paulo, Brazil. Imaging consisted of five views of the retina (optic nerve center, superior, inferior, nasal, temporal) with 130° wide-angle lens and one view of the anterior segment in each eye. These images were curated on four separate occasions for the presence or absence of ocular abnormality by a pediatric retina specialist. All images were obtained within 72 hours of birth. A total of 59,792 images were curated: Right Eye Normal (21,473 images), Left Eye Normal (21,983 images), Right Eye Abnormal (8,397 images), Left Eye Abnormal (7,939 images). An ocular abnormality appeared in 37.7% of patients; 4.88% showed a referral-warranted pathology. Based on these data, it is not unreasonable to consider instituting universal newborn eye screening in HTNI.

Purpose: To describe a simple, inexpensive, 3D-printed holder for a high-resolution, wide-angle contact lens compatible with the Resight 700 system. Methods: This study introduces a contact lens system for use in vitreoretinal surgery. Comprising an aspheric pan fundoscopic lens and an adaptive lens holder designed for easy integration with existing surgical setups, the system is compatible with popular noncontact systems, such as Resight 700, offering flexibility between the 2 modalities. Results: The new system allows seamless switching between noncontact and contact modes, providing a wide field of view with enhanced resolution and stereopsis to overcome the optical limitations of noncontact systems. The design ensures minimal interference with surgical instruments and has been successfully used in more than 500 vitreoretinal surgeries, including complex procedures, without any complications. Conclusions: This hybrid system offers a wide field of view and high-resolution imaging of contact systems, mitigating the need for an assistant and reducing the risk of corneal injury.

ABSTRACT Isotope values in fish eye lenses may be useful in differentiating rearing origins. We compared eye lens isotopic values of fall fingerling age‐0 walleye ( Sander vitreus ) reared in a hatchery pond, a recirculating aquaculture system (RAS), and a natural lake. Using 10 fish per rearing source, we delaminated layers from one eye lens per fish to assess temporal changes in carbon (δ 13 C) and nitrogen (δ 15 N) and pulverized the whole second eye lens for δ 13 C, δ 15 N, and sulfur (δ 34 S). RAS‐reared walleye values exhibited high precision among individuals and were δ 34 S enriched. Pond‐reared walleye had lower δ 13 C and δ 15 N core values compared to other rearing sources. For δ 13 C and δ 15 N, values remained consistent among layers for RAS‐reared walleye, δ 15 N slightly increased for pond‐reared and lake‐reared walleye, and δ 13 C increased substantially among subsequent layers in pond‐reared walleye. Bayesian 95% ellipses did not overlap among rearing sources. These results demonstrate that eye lens stable isotope analysis may be a useful tool for differentiating hatchery‐reared and wild large fingerling walleye, specifically from RAS‐ and pond‐reared sources.

Clear civil twilights often exhibit a range of pastel purples, but the combined angular and temporal distributions of this purple light are unknown. Such distributions can now be measured by using a hyperspectral camera fitted with a fisheye lens, which gives new insights into the spread and evolution of purple-light spectra and colors during ordinary (i.e.,nonvolcanic) clear twilights. Because the purple light lacks clear-cut borders, a first step is to develop a perceptually based definition of its angular extent. Surprisingly, this leads to the discovery that colorimetrically distinct purples (1) sometimes appear in both the solar and antisolar skies and (2) change in markedly different ways with sun elevation.

Three dimensional wide-angle broadband acoustic metamaterial Luneburg lens for detecting weak signals

Broadband enhanced-resolution imaging based on solid immersion square Maxwell’s fish-eye lens

Wide-angle Multibeam Lens Antenna Illuminated by Rectangular Horn with Phase Centers Separated in E/H-Plane

This paper presents the phase tracing method (PTM), an analytical framework for the direct synthesis of graded-index (GRIN) lens antennas. PTM employs an inverse formulation of geometrical optics (GO) principles to derive isotropic refractive index profiles directly from user-specified ray trajectories. By circumventing the computational expense and convergence challenges of numerical optimization, and relaxing the constraints of classical analytical approaches, PTM enables deterministic control over both phase and amplitude transformations at the aperture. Its core innovation lies in establishing explicit relationships between ray curvature, phase evolution, and refractive index gradients under strict power conservation, allowing for analytically tractable designs. The method further leverages clothoid trajectories, characterized by linearly varying curvature, to produce smooth, bounded refractive index gradients conducive to fabrication. The versatility of PTM is demonstrated through five examples: (a) exact analytical retrieval of the Maxwell Fish-Eye lens, (b) a telescopic GRIN lens achieving 2× aperture magnification, (c) a flat-top beam generator with uniform ±15° coverage, (d) a Bessel beam launcher for non-diffracting radiation, and (e) a GRIN lens transforming a rectangular waveguide mode into a uniform circular aperture. The designs are validated via full-wave simulations, GO analysis, and theoretical benchmarks, confirming exceptional performance. PTM establishes a new paradigm for efficient, wideband GRIN lens design, combining analytical rigor with practical manufacturability for microwave and millimeter-wave applications.

Abstract This paper presents a novel square Maxwell fish-eye lens (SMFEL), designed using the Schwarz–Christoffel conformal transformation method, aimed at effectively controlling the propagation of flexural waves and achieving high-resolution imaging. Traditional Maxwell fish-eye lenses, due to their unique refractive index distribution, can focus waves from any point without aberrations to their antipodal point. However, in practical applications, they often encounter impedance mismatch issues at the boundary. To address this issue, the proposed SMFEL resolves the impedance mismatch induced by boundary effects in conventional lens designs by leveraging a thin plate structure with varying thickness—all while preserving outstanding imaging capabilities. To explore the lens’s imaging traits under different excitation positions and frequency conditions, researchers carried out numerical simulations and experimental verifications. The results show that the SMFEL can achieve subwavelength resolution imaging over a wide frequency range (10–30 kHz) and demonstrates good focusing effects at various frequencies. Further experimental verification reveals that the imaging performance of the SMFEL is highly consistent with the numerical simulation results, proving its potential applications in fields such as structural health monitoring, non-destructive testing, and high-resolution acoustic imaging. This study provides a new approach to flexural wave control and demonstrates the broad application prospects of square lens designs in flexural wave imaging.

Abstract Estimating the position and orientation of a rigid object from an image is critical for situational awareness in robotics and autonomous systems. This study explores relative pose estimation using an ultra-wide fisheye camera for unmanned aircraft inspection vehicles. Ultra-wide fisheye lenses introduce radial distortion and capture features beyond the rectilinear image plane, rendering rectilinear Perspective-n-Point (PnP) algorithms inadequate. Designing a bespoke ultra-wide fisheye localization algorithm requires consideration of both the feature detection method and the pose estimator itself. This study proposes a novel method that combines (1) a fisheye-to-cubemap reprojection, (2) a You Only Look Once (YOLO) convolutional neural network trained for arbitrary airborne perspectives, and (3) an Angle-Agnostic and Multiple-Frame PnP (AMP) pose estimation algorithm. Our pipeline achieves a 97% success rate for valid pose estimates, with a mean absolute translational error of less than 12 cm on real ultra-wide fisheye imagery, outperforming conventional techniques, including OpenCV.

In panoramic images, the geometric distortion caused by wide-angle lenses makes traditional semantic segmentation methods difficult to accurately segment the glass areas. To address the challenges of capturing spatial features and integrating context information, we propose the Panoramic Glass Image Segmentation Network (PGISNet). This network integrates the Matrix Decomposition Base Module (MDBM), the Transparent Perception Consistency Module (TACM), the Context and Texture Compensation Module (CTCM), and the Multi-scale Gated Context Attention Module (MGCA), constructing a progressive feature processing flow. Experimental results on the PanoGlassV2 benchmark test show that PGISNet achieved 90.03% IoU, 94.76% F-score, and 94.0% PA, significantly outperforming existing methods, verifying its effectiveness and advancement in the panoramic image glass segmentation task.

Accurate sky-obstacle segmentation in hemispherical fisheye imagery is essential for solar irradiance forecasting, photovoltaic system design, and environmental monitoring. However, existing methods often rely on expensive all-sky imagers and region-specific training data, produce coarse sky-obstacle boundaries, and ignore the optical properties of fisheye lenses. We propose a low-cost segmentation framework designed for fisheye imagery that combines synthetic data generation, lens-aware augmentation, and a hybrid deep-learning pipeline. Synthetic fisheye training images are created from publicly available street-view panoramas to cover diverse environments without dedicated hardware, and lens-aware augmentations model fisheye projection and photometric effects to improve robustness across devices. On this dataset, we train a convolutional neural network (CNN) and refine its output with gradient-boosted decision trees (GBDT) to sharpen sky-obstacle boundaries. The method is evaluated on real fisheye images captured with smartphones and low-cost clip-on lenses across multiple sites, achieving an Intersection over Union (IoU) of 96.63% and an F1 score of 98.29%, along with high boundary accuracy. An additional evaluation on an external panoramic baseline dataset confirms strong cross-dataset generalization. Together, these results show that the proposed framework enables accurate, low-cost, and widely deployable hemispherical sky segmentation for practical solar and environmental imaging applications.

To meet the requirements for wide-angle lenses with a wide operating temperature range, high imaging quality, and a compact structure, this study presents a miniaturized wide-angle lens design based on a folded optical path. The optimized system employs a five-lens configuration. Simulation results show that the design achieves an overall optical length of less than 8mm and a field of view of 170°. At the Nyquist frequency, the modulation transfer function exceeds 0.3 across the full field, with maximum distortion below 25%, while maintaining stable performance over a temperature range from -60∘C to 85°C. Thermal and tolerance analyses confirm the robustness and practicality of the design. This work provides a valuable reference for the miniaturization of wide-angle lenses.

Design and motion analysis of a simple screw driven in-pipe inspection robot base on adaptive variable pitch