Search Results (411)

UAV-enabled Integrated Sensing and Communication (ISAC) systems simultaneously support target sensing and communication and, combined with their abilities in autonomy and control situations, they have the potential to be deployed for search and rescue tasks that were, previously, challenging or impossible. However, the limited apertures of UAV-mounted physical arrays restrict angular resolution and multi-target sensing capability. This work proposes a method for implementing virtual arrays in UAV-assisted MIMO-OFDM ISAC systems to enhance the multi-target sensing capability. With a range of possibilities including transmit–receive channel pairings and two virtual-array configurations, Virtual-7 and Virtual-10 are developed to form greater effective apertures out of a $4\times 4$ ISAC transceiver. A sensing model based on virtual arrays and the corresponding signal-processing procedure are established for angle estimation and for sensing-performance investigation. Simulation results show that ISAC systems with virtual arrays perform better in terms of multi-target detection. The proposed method for virtual-array establishment can, potentially, be applied in UAV-ISACs for high-resolution sensing with a low-profile configuration requirement. Full article

This work presents a spatial multi-feed beam steering reflectarray concept intended for compact small satellite payloads with adapted field of view (FoV) coverage. Unlike conventional reflectarray beam steering approaches based on tunable unit cells or mechanical reconfiguration, the proposed approach exploits the controlled displacement of the phase center of a digital planar feed array to illuminate a passive reflectarray surface from different spatial positions, enabling beam steering without tunable unit cells or mechanical reconfiguration. First, the beam steering mechanism is analyzed through the phase gradients induced by feed displacement, including the impact of amplitude illumination and incidence angle-dependent unit cell response. Then, the concept is experimentally validated at 30 GHz using a developed reflectarray and a 2 × 2 patch array feed repositioned over a multi-position interface to emulate overlapping subarrays of a virtual 4 × 4 feed array. The measured radiation patterns show good agreement with simulations, confirming the predicted beam pointing trends with measured gains between 26.57 and 27.91 dBi for the evaluated subgroups. Finally, a mission-oriented architecture for the UPMSat-4 scenario is analyzed, considering a reflectarray surface up to 600 mm × 400 mm integrated into solar panels and a 16-element linear array feed. The results demonstrate the feasibility of generating a linear multibeam FoV, achieving beam overlap and a minimum carrier-to-noise ratio (C/N) of approximately 32 dB in the considered link budget scenario. The proposed architecture provides a scalable and low-complexity alternative for flexible smallsat antenna payloads. Full article

Objective: To estimate the frequency and potential impact of genetic variants involved in metformin pharmacokinetics, including gastrointestinal absorption, renal elimination, and hepatic transport in the Chilean population. Subjects and methods: The frequency of metformin-related gene variants was estimated using data from a genome-wide, exome-focused genotyping array in 918 participants of the Chilean Growth and Obesity Cohort Study (GOCS). Allele frequencies in Chileans were compared with those published worldwide, and the degree of Amerindian/European ancestry was assessed. A predictive bioinformatic analysis was performed on relevant genetic variants using PolyPhen-2. Results and Discussion: The genetic polymorphism (p.Leu125Phe; p.L125F; rs77474263; C>T) in the SLC47A1 gene (MATE1 transporter) showed a much higher frequency of the 125Phe (T-allele) in the Chilean population (15.3%) than in non-American populations, being virtually absent in Africa, Europe, or Asia. The 125Phe variant was associated with a higher percentage of Amerindian ancestry in the Chilean population. This result is consistent with a previous report indicating that this variant is enriched in Native American populations, given its high frequency among Mestizo and Indigenous populations in Mexico. The functional variant p.125Phe has been previously suggested to promote plasma metformin accumulation, mitochondrial dysfunction, and increased plasma lactate concentrations by altering renal metformin elimination. Conclusions: The missense variant p.Leu125Phe (rs77474263) in SLC47A1 is frequent in Chile and Mexico, and apparently absent in non-American populations. In homozygosis, the p.125Phe variant has been previously associated with impaired renal drug elimination, metformin systemic accumulation, and hyperlactatemia. Full article

This study examines how the vertical spacing of a multi-height 360° camera array affects novel-view synthesis quality in indoor scenes reconstructed with 3D Gaussian splatting (3DGS). Although 3DGS enables high-quality real-time scene representation, its output depends on the geometric arrangement of the input views, which single-lens workflows secure through repeated captures at several heights. A rig of three vertically arranged 360° cameras was evaluated in four indoor spaces differing in ceiling height, structure, and capture path. Three spacing conditions were applied in each space, denoted as Set-L, Set-D, and Set-H. These are ordinal positions within the vertical range each space allows rather than fixed absolute distances, since an identical spacing sits differently in rooms of different scale. The 360° footage was stitched into equirectangular video and reframed into multi-view image sequences, yielding 120 datasets from four spaces × three conditions × ten repeated captures. Novel-view synthesis quality was measured with the PSNR, SSIM, and LPIPS on validation views withheld from training. Because normality and homogeneity of variance were not satisfied, a robust two-way factorial analysis of variance based on 20% trimmed means was used, with robust post hoc comparisons. Spacing, spatial characteristics, and their interaction were significant for all three metrics, so no single spacing was preferable across every space. The wide setting performed best in the low-ceiling repetitive space, the narrow setting in the open space, and the baseline setting in the largest space with variable ceiling height. In one space, comprising stepped, near-symmetric seating, no condition was distinguishable, and dispersion across repeated captures was an order of magnitude larger than elsewhere, indicating that, where a repetitive structure is extensive, the limiting factor is capture stability rather than the choice of spacing. The findings are consistent with a trade-off between vertical viewpoint separation and inter-view overlap, and provide exploratory, space-conditional reference points for indoor 3DGS capture rather than a standardized specification, with relevance to virtual exhibitions, architectural visualization, and digital-twin construction. Full article

As the photovoltaic (PV) generation sector expands, ensuring reliable maximum power point tracking (MPPT) in embedded controllers becomes increasingly important. However, many MPPT studies rely on idealized simulation assumptions that neglect practical sensing limitations, including ADC quantization, finite measurement resolution, sensor noise, offset, ripple, and scaling constraints. This paper presents a sensing-aware simulation-based digital twin framework for photovoltaic arrays that integrates dynamic environmental excitation with a virtual instrumentation layer and firmware-level execution on an ESP32 microcontroller (Espressif Systems, Shanghai, China). Unlike conventional model-in-the-loop simulations, the proposed framework ensures that the embedded control algorithm operates on reconstructed and quantized measurements rather than on ideal internal model states. The platform is evaluated using an Incremental Conductance MPPT implementation as a representative embedded workload. The results demonstrate that the proposed simulation-based digital twin framework enables repeatable firmware-level experimentation while exposing instrumentation-induced effects on tracking stability, control dynamics, and measurement-driven behavior under non-ideal sensing conditions. Furthermore, it provides structured datasets to support early-stage development, tuning, and validation of embedded MPPT algorithms before physical laboratory deployment. Full article

High-speed airborne platforms impose stringent aerodynamic constraints that restrict traditional planar antenna designs. Concurrently, multi-component echoes from extended targets and complex propagation environments induce strong signal coherence, severely degrading spatial angle estimation. To address these dual challenges, this paper proposes a straight-curved hybrid L-shaped asymmetric conformal array hardware topology tailored for cylindrical radomes. Building upon this, a millimeter-wave radar 3D point cloud imaging framework is developed for coherent targets. An orthogonal virtual manifold transformation is first devised to effectively compensate for the non-linear phase distortion induced by the conformal topology. Subsequently, a cascaded Forward-Backward Spatial Smoothing (FBSS) and Root-MUSIC framework is used for efficient signal decoherence. To resolve angle mismatches, a global cost function based on the cross-covariance Frobenius norm is formulated, which pairs independent angles and significantly suppresses spatial ghost targets. Systematic evaluations using 3D computer vision metrics demonstrate that the proposed method achieves accurate geometric restoration of aircraft targets with coherent signals. In the representative simulation, the method obtains a median point-wise localization error of 0.3986 m, a Chamfer Distance (CD) of 0.9695 m², an Earth Mover’s Distance (EMD) of 1.9504 m, and a spatial angular resolution of 1.0° under the stated test conditions. Under the stated simulation assumptions, boundary analyses indicate stable reconstruction around a post-pulse-compression SNR of −8.0 dB and a conformal curvature of 12.50 m⁻¹ ($r=0.08$ m), providing simulation-based design references for conformal radar 3D imaging. Full article

Geometry-processing and computational-imaging workflows combine heterogeneous data structures, topology-changing edits, dense numerical fields, visualization, and repeated experimental variation. These workflows are often clear as algorithms but obscured in software by traversal boilerplate, representation conversions, build-system boundaries, and ad hoc scripting conventions. This paper presents tgLang, a domain-specific language with explicit, runtime-enforced representation types that makes meshes, point clouds, curve networks, grids, two-dimensional images, and image stacks first-class executable values. The language combines manifest types, typed arrays, modules, deterministic parallel constructs, flow-oriented queries, and runtime-provided domain operations. Its current implementation uses a stack-based bytecode virtual machine for reference semantics and dispatches representation-heavy operations to optimized C++ kernels. The evaluation is organized around complete workflows: topological hole detection, distance-field-based mean camber line extraction, voxel downsampling of point clouds, curve-network generation, surface-mesh smoothing and remeshing, image-stack edge detection, morphological image processing, and image-stack surface extraction. These examples show that a domain-aware source language can express multi-representation geometry and imaging algorithms as compact, reproducible programs while preserving explicit representation choices and a path toward deployable implementations. Full article

Scientific visualization is changing from passive observation to active, AI-assisted collaboration. While Extended Reality (XR) has proven valuable for comprehending dense 3D arrays, traditional VR applications are typically deployed in rigid, single-purpose, and monolithic architectures. In this paper, we present the evolution of ASCRIBE-XR: a virtual reality platform backed by remote computation that has been re-engineered into a dynamic, service-oriented ecosystem. We introduce three core innovations that make immersive data analysis easier, faster, and more flexible when using multimodal scientific imaging. First, a lightweight Python REST interface decouples XR logic from the rendering engine, enabling real-time, programmable scene customization and on-demand data generation. Second, we present a Specimen Catalog architecture that lets the platform pivot between radically different disciplines, ranging from archaeological heterogeneous concrete and fuel-cell membranes to the root system of a bioenergy grass, by describing each dataset through portable metadata rather than hard-coded application logic. Finally, we introduce a prompt-driven layer powered by the Claude Agent SDK, allowing researchers to generate, segment, and manipulate volumetric and mesh data through natural language dialogue within the virtual space. For example, applying foundation models such as the Segment Anything Model (SAM) to perform zero-shot segmentation on demand. By bridging human intent with remote computation, ASCRIBE-XR relaxes the constraints of conventional visualization tools, offering a highly adaptable, conversational platform for scientific discovery with human auditing. Full article

Holographic stereograms record large sets of multi-view projection images into elementary hologram units (hogels), and their visual quality is governed primarily by the quality and inter-view consistency of the input multi-view imagery. Conventional photogrammetry-based pipelines for generating such imagery rely on surface meshes and require burdensome post-processing, which limits the fidelity of thin structures and view-dependent reflections. This paper proposes an integrated workflow that replaces the photogrammetric stage with Gaussian splatting and presents a controlled comparison of volumetric 3D Gaussian splatting (3DGS) and surface-aligned 2D Gaussian splatting (2DGS) for hogel-based digital hologram production. Using 397 drone-captured images of a 3 m bronze Pegasus statue, both representations were trained under identical input data, camera poses, and hyperparameters, and 119,808 full-parallax multi-view images (768 × 156 grid; 120° × 52° field of view) were rendered from each model, converted into hogel arrays by an identical ray-tracing transform, and printed onto Ultimate U04 silver halide plates under identical optical conditions. In the digital domain, 3DGS outperformed 2DGS on all three standard novel-view-synthesis metrics (PSNR 32.68 vs. 31.03 dB; SSIM 0.9281 vs. 0.9139; and LPIPS 0.1150 vs. 0.1406) while using approximately 1.67 times more Gaussians. Conversely, 2DGS produced superior results at viewpoints outside the training distribution, on thin structures such as wings and mane, and at the extremes (±60°) of the virtual camera array, and these differences propagated consistently to the printed holograms, whose edge sharpness was higher for 2DGS at every measured viewpoint (mean 39.6 vs. 23.8). Notably, 2DGS achieved this superior printed-output quality while using approximately 40% fewer Gaussians than 3DGS, combining model efficiency with the multi-view consistency that proved decisive for hogel-based printing. The results demonstrate that single-view metrics such as PSNR do not capture the multi-view consistency that dominates hogel-based output quality and provide practical guidance for representation selection in holographic-printing workflows. Full article

To address the issues of incomplete virtual array utilization and direction of arrival (DOA) estimation performance degradation under noise interference in coprime array processing, this paper proposes the Toeplitz Assisted Subspace Projection enhanced Unitary Root Sparse Asymptotic Minimum Variance (TASP-URootSAMV) algorithm. First, trace regularized Toeplitz covariance completion is employed to fill aperture holes in the virtual domain by exploiting shift invariance structure, reconstructing the interpolated covariance matrix through convex optimization and Wiener prediction. Second, eigenspace projection is performed to suppress background noise through Toeplitz-averaged covariance estimation and signal/noise subspace separation. Third, unitary root SAMV is applied to perform grid-initialized off-grid DOA refinement through iterative polynomial rooting, thereby mitigating grid-induced modeling errors and reducing sensitivity to the initial angular grid. Algorithm performance is evaluated through two complementary experiments. Spatial spectrum and root mean square error (RMSE) analysis indicate that, at $T=200$ snapshots and $\mathrm{SNR}=-10$ dB, the proposed method reduces the RMSE by $47.86$–$56.47\%$ compared with the considered algorithms, with accuracy close to the Cramér–Rao bound (CRB) in the tested cases. Additionally, the algorithm maintains distinguishable spectral peaks for the tested source numbers. Grid-spacing analysis indicates relatively stable performance over the tested initialization-grid intervals, whereas the performance of the grid-dependent comparison method degrades as the grid spacing increases. The convergence experiments also show limited sensitivity to the tested initialization settings and comparable computational efficiency. Under the adopted simulation assumptions, these results indicate improved estimation accuracy under the tested noisy conditions. Full article

Direction-of-arrival (DOA) estimation with coprime arrays can synthesize an enlarged virtual aperture from a limited number of physical sensors. However, coherent incident sources lead to rank deficiency of the source covariance matrix, while unknown nonuniform sensor noise mainly contaminates the zero-lag component of the difference-coarray covariance. These two effects jointly degrade conventional Coarray Root-MUSIC, Coarray ESPRIT, and interpolation-based virtual-array methods. To address this problem, this paper proposes a Toeplitz–Hankel structured covariance reconstruction method for coherent-source DOA estimation with coprime arrays under unknown nonuniform noise. The method first performs redundancy-aware difference-coarray lag averaging. The zero-lag component is then suppressed during missing-lag interpolation to reduce the bias caused by sensor-dependent noise powers. A Toeplitz positive semidefinite projection is used to enforce covariance validity, and a relaxed Hankel truncated-singular-value-decomposition refinement is introduced to enhance the low-rank spectral structure of the reconstructed virtual covariance sequence. Finally, multi-scale forward–backward spatial smoothing MUSIC is applied for coherent-source DOA estimation. Simulation results with a coprime array of $M=4$ and $N=5$ show that the proposed method provides more accurate and stable DOA estimates than Coarray Root-MUSIC, Coarray ESPRIT, and RV-TSI. Compared with CVX-based THSCR, the proposed method avoids semidefinite programming and nuclear-norm optimization and reduces the average runtime from approximately $11.2$ s per trial to approximately $0.11$ s per trial under the tested setting. Full article

Synthetic aperture interferometric radiometers (SAIRs) have emerged as a promising technology for high-resolution remote sensing and target detection by synthesizing spatially distributed antenna elements into a large virtual aperture. To achieve high angular resolution and radiometric sensitivity, SAIR systems often employ sparse antenna arrays composed of antenna elements with large apertures and high gain, resulting in element spacings exceeding half a wavelength. Such undersampling violates the Nyquist sampling criterion, generating grating lobes in the array factor (AF) and resulting in spatial aliasing artifacts in reconstructed brightness temperature (TB) images, which degrade imaging and detection performance. To mitigate this problem, this paper proposes an aliasing suppression method based on a subarray-based antenna architecture. First, the grating lobe directions of the sparse array are identified through AF analysis. Each conventional antenna element is then replaced with a properly designed subarray antenna whose radiation pattern introduces nulls are placed near the grating lobe directions, thereby reducing the corresponding aliasing artifacts in reconstructed TB images. Simulation results and an equivalent experimental emulation demonstrate that the proposed method reduces aliasing artifacts while maintaining competitive spatial resolution and radiometric sensitivity. Additional analyses investigate the effects of subarray layout, the number of subarray elements, and wideband operation, as well as the direction dependence of grating lobe suppression, providing practical guidance for SAIR system design. Full article

To reduce the computational burden of conventional spectral search direction-of-arrival (DOA) estimation algorithms for acoustic vector sensor arrays (AVSAs), this paper proposes a low-complexity DOA estimation method based on semi-real-valued noise power invariance (SR-NPI). The proposed method is developed for centrosymmetric AVSAs under the required steering-vector parity and pressure-channel conjugate-symmetry conditions after pressure–velocity (PV) co-processing. The AVSA measurements are first preprocessed through PV co-processing, and a pseudo-data covariance matrix is then reconstructed by exploiting the complex conjugate relationship between the true DOAs and their symmetric virtual DOAs. By introducing a scanning source into the reconstructed covariance matrix, a DOA-dependent spatial spectrum is constructed according to the eigenvalue-ordering behavior. Since the reconstructed matrix contains both the true DOAs and the symmetric virtual DOAs, the angular search range can be reduced to one half of the original domain. Under the tested configuration, the proposed method reduces the computational cost to approximately 1.92% of that of the original NPI algorithm. Simulation and sea trial results indicate that SR-NPI can maintain competitive estimation accuracy while significantly reducing computational complexity under the centrosymmetric-array conditions. Full article

The introduction of a quantitative definition of fish freshness enables the determination of the remaining storage time of raw fish materials. To measure this value, a virtual array of electrochemical chemotransistor-based chemical sensors was developed. The electrolyte used to electrically connect the four measurement electrodes and the reference electrode was optimized. To achieve the high stability, high electrochemical activity of chemosensitive material, and reversible potential of the silver/silver chloride reference electrode, a chloride-containing ionic liquid and polymeric acid mixture was used as the electrolyte. Polyaniline in different redox states was applied as the chemosensitive material with electrically controlled affinity. First, the sensor was evaluated for trimethylammonium detection, and then it was applied to fish samples. Unlike the response observed for trimethylammonium, the sensor’s response to fish samples exhibited complex, non-exponential kinetics and a non-monotonic dependence on the storage duration of fish samples. To characterize these responses, a set of descriptors was introduced. The storage time was estimated by minimizing the Euclidean distance between the descriptors values obtained from fish samples and those determined during calibration. Based on the quantitative definition of freshness, this approach categorizes the current stage of fish products and predicts the remaining storage duration quantitatively. Full article

Virtually all spaceborne topographic lidars to date have used a single beam, with the exception of the ATLAS lidar on NASA’s ICESat-2 satellite, which split the beam into 3 “strong” and 3 “weak” beamlets distributed perpendicular to the along-track path of the satellite. This approach has provided high-resolution along-track surface measurements but relatively poor resolution cross-track measurementswithin a given surface area. The present paper attempts to resolve this discrepancy by (1) transmitting and scanning a single Gaussian beam and (2) imaging the return onto a 14 × 14 pixelated, single-photon sensitive, detector array, thereby providing between 100 and 196 measurements per pulse, depending on the solar background. Besides enhancing the lidar’s capability to penetrate tree canopies and water bodies, the proposed single-beam approach provides one to two orders of magnitude more measurements per pulse with equal spatial resolution in boththe along-track and cross-track directions. At the 10 kHz pulse rate of the ATLAS laser on NASA’s ICESat-2 satellite, this implies between 1 and 2 million topographic measurements per second. The maximum surface area observable by a single pulse increases with the laser peak power defined by the ratio of the pulse energy to the temporal pulsewidth. Larger surface areas per pulse result in more time for cross-track scanning while still maintaining contiguous along-track mapping. Two scanning methods appear to be feasible: (1) circular scans using individual but temporally coordinated wedge scanners for the transmitted and received beams, and (2) unidirectional linear scans utilizing Acousto-Optic Deflectors. The circular scan approach is probably easier to implement, but it also requires additional post-processing to obtain an accurate contiguous 3D image of the planetary terrain. Full article