Search Results (282)

Freely meandering rivers flow through gently sloping plains composed of loess and fluvial sediments. Low-gradient alluvial plains are formed without the influence of landscape features such as rock outcrops or other features that distort the flow path. The channel configurations of such rivers, and in particular the size of meanders and oxbow lakes, depend on the average long-term water discharge. Large rivers form large meanders, while small rivers form correspondingly small ones. Morphological analysis of river channel configurations can offer a metric for estimating the average long-term water discharge of a river based solely on the sinuosity of its channel. The study examined six freely meandering rivers in Kazakhstan, with discharges ranging from 4.5 to 760 m³/s and channel slopes from 0.005 to 0.06%. The morphological analysis of river channels was based on the Relative Elevation Model, specifically its version based on the Copernicus Global Digital Elevation Model, with a spatial resolution of 30 m. River channel configurations were approximated using a set of inscribed circles, the diameters of which formed the basis for the river’s average long-term water discharge metric. The largest diameter circles, which could support the river channel with a sector of at least 135°, were expertly inscribed into river bends. The diameters of the inscribed circles within these sets varied from four times for small rivers to ten times for large rivers. These sets of circles, sorted by size, can characterize the average long-term water discharge of the analyzed rivers. For example, a sample of average median values of inscribed circle diameters has a high correlation with the average long-term water discharge, with a linear approximation reliability of R² = 0.997. The scope of the developed method for assessing the average long-term water discharge of freely meandering rivers includes retrospective analysis of changes in average long-term average long-term water discharge. This can provide significant historical depth of analysis, spanning centuries and millennia, since the analysis is based on describing the results of very slow processes of natural deformation of river channels. Thus, the method proposed in this study for assessing the average long-term water discharge of freely meandering rivers based on morphological analysis of their channel configurations expands the arsenal of tools for reconstructing certain paleoclimate elements related to the hydrology of territories. Full article

Urban intersection design generally assumes that drivers follow idealised turning paths defined by circular arcs and, in some cases, transition curves. In practice, however, observed left-turn trajectories often depart from these theoretical paths. This study proposes a curvature-based framework for quantifying such deviations at the movement level by directly comparing observed vehicle paths with theoretical design arcs derived from intersection geometry. Naturalistic traffic data were collected at five urban intersections in Thessaloniki, Greece, using elevated video cameras. Left-turn passenger-vehicle trajectories were extracted, georeferenced, and compared with corresponding theoretical paths. For each trajectory, a best-fit circular arc was estimated, and the deviation between observed and theoretical path geometry was quantified through radius- and curvature-based percentage indicators. These indicators were then aggregated at the intersection and movement level using medians, deciles and the relative shares of flatter-than-theoretical and tighter-than-theoretical trajectories. The results show that deviations from theoretical geometry are strongly movement-specific and that the strongest flattening and tightening patterns were statistically supported by movement-level Wilcoxon signed-rank tests. In some cases, drivers systematically opened the turn relative to the design path, with median curvature deviations reaching about −14% and flatter-than-theoretical shares as high as 94%. In other cases, the opposite pattern was observed, with median curvature deviations exceeding +37% and tighter-than-theoretical shares reaching 100%. Other movements remained close to the theoretical path or displayed substantial internal heterogeneity. Overall, the proposed framework offers a practical and interpretable way to screen left-turn movements for systematic departure from design intent. This is important because it allows the analysis to move from individual path overlays to a movement-level geometric reading that can support consistency checks, intersection review and future integration with speed- and conflict-based safety analyses. These results should nonetheless be regarded as exploratory and descriptive: neither the circle-fitting residuals nor the coordinate-level geometric accuracy of the extracted trajectories were formally validated in the present study, and the reported RDP/CDP values are, therefore, not intended for use as precision-survey quantities or as a stand-alone design basis. Full article

The 15-minute life circle has become a critical planning paradigm for developing age-friendly cities; however, its implementation in small and medium-sized cities (SMSCs) is often constrained by topographical heterogeneity and the oversimplified use of facility density as a proxy for service efficiency. This study challenges the conventional assumption that a higher facility density automatically leads to better service outcomes and proposes a dynamic “space–demand–policy” analytical framework to identify the mechanisms underlying spatial mismatch. Using Zhifu District, Yantai, a rapidly aging urban area with complex topography, as a case study, we integrated kernel density estimation (KDE), slope-adjusted network analysis, a modified Gaussian-based two-step floating catchment area (2SFCA) method, and standard deviational ellipse (SDE) analysis. Our results reveal three key findings. First, a “high-density, low-efficiency” paradox is prevalent: older urban cores contain clusters of facilities but have supply–demand ratios below 0.5 because of limited service diversity and slope-induced reductions in accessibility, with the effective service radius decreasing to 750 m. Second, newly developed areas achieve service coverage rates below 50% when terrain constraints are considered, highlighting the limitations of static planning radii. Third, a 90% overlap between the directional distributions of residential areas and elderly care facilities, as indicated by their SDE major axes, supports the spatial feasibility of community-embedded aging-in-place models; however, physical proximity alone does not guarantee effective service delivery. By adapting generic spatial algorithms to create a terrain-sensitive planning tool, this study provides a transferable framework for evidence-based and targeted elderly care planning in SMSCs facing similar demographic and geographic constraints. The proposed framework contributes to the global sustainability agenda and advances SDG 11 (Sustainable Cities and Communities) and SDG 3 (Good Health and Well-being) by promoting more equitable resource allocation and supporting the development of age-friendly, walkable, and sustainable communities in topographically complex urban areas. Full article

Oxford Nanopore technology enables cost-effective, portable, long-read analyses of pathogen genomes. Accurate detection and interpretation of small circular viral genomes, including Anelloviridae, remain challenging due to limited base-level error quantification in rolling-circle amplification (RCA)-derived datasets. Here, we characterized read-level sequencing error profiles using M13mp18, a 7.2 kb circular phage genome, subjected to 1X and 3X shearing during library preparation. M13mp18 DNA was serially diluted into pooled anellovirus-positive plasma DNA extracts. Using custom error-analysis pipelines, we quantified mismatch, insertion, and deletion rates and evaluated consensus reconstruction accuracy across simulated sequencing depths. Since metagenomic viromes contain mixtures of related genomes and uneven coverage across taxa, depth-normalized subsampling was used to assess the precision of read-level error estimates under heterogeneous coverage. Across four benchmarked datasets, per-base error rates ranged from 0.018 to 0.022 errors per aligned base. Complete M13mp18 reference reconstruction was achieved at input levels ≥ 4.6 log₁₀ copies, and consensus sequences reached 100% identity at depths ≥ 15X when sufficient reads were available. Below 4.6 log₁₀ input copies, recovery was inconsistent. These findings provide a controlled empirical characterization of read-level error behavior in RCA-derived nanopore sequencing and support the interpretation of circular DNA virome data generated in complex metagenomic backgrounds. Full article

In this paper, we describe a method for computing calendar time forecasts in a local area for large earthquakes of a target magnitude M_T using a count of small earthquakes in the magnitude range M_S to M_T in the area. Using the idea that the Gutenberg–Richter (GR) relation is valid throughout the surrounding region, we define an ensemble of earthquakes in larger surrounding regions to be used in computing the forecast. What follows is simple data mining. “Local” is defined by the probability of a large earthquake occurring within a defined circle of arbitrary radius surrounding a point of interest. The main (and for that matter, the only) assumption for all these works is that the GR magnitude–frequency relation holds. The method has significant skill, as defined by the Receiver Operating Characteristic (ROC) test, which improves as the time since the last major earthquake increases. The probability is conditioned on the number of small earthquakes n(t), with M ≥ M_S = 3.49, that have occurred since the last large earthquake. The probability is computed directly as the Positive Predictive Value (PPV) associated with the ROC curve. The method is compared with the UCERF3 forecasts for the UCERF3-defined geographic boxes centered on Los Angeles and San Francisco and serves as an indicative benchmark. The method is then applied to a 125 km radius circular area around Los Angeles, California, following the 17 January 1994 magnitude M6.7 Northridge earthquake, and short-term forecasts (1-year and 5-year) are computed. We further apply the method to six additional geographic regions with validation by comparison with an estimate of the time-independent conditional Poisson probability. These regions are Athens, Greece; Chengdu, China; Jakarta, Indonesia; Lima, Peru; Santiago, Chile; and Tangshan, China. Full article

Large-diameter rescue shafts serve as critical infrastructure for emergency response in mining disaster scenarios, and their structural deformation directly affects the safe passage of rescue capsules. In this paper, we investigate three-dimensional (3D) reconstruction techniques for large-diameter rescue shaft environments and develop a Neural Radiance Fields (NeRF)-based reconstruction and deformation assessment scheme. The proposed workflow integrates no reference signal-to-noise-ratio (NR-SNR), image-quality filtering, SfM-based camera-pose estimation, Nerfacto reconstruction, point-cloud export, and circular-section fitting. The NR-SNR retention-ratio experiment shows that retaining approximately 35% high-quality images provides a practical efficiency–quality trade-off for the present dataset, reducing the computational burden of SfM pose estimation while preserving sufficient geometric information for subsequent reconstruction. The reconstructed radiance field is further exported as a dense point cloud and evaluated using relative radius error, circle-fitting residuals, and image-level rendering metrics. Experiments on a simulated large-diameter rescue shaft platform show that the proposed NeRF-based scheme provides favorable geometric measurement applicability and visual reconstruction quality under weak-texture and low-illumination conditions. Compared with conventional MVS and the tested 3DGS baseline, the proposed scheme produces a point-cloud output that is more suitable for subsequent circular-section fitting and deformation-related assessment. In addition, comparison with a representative SDF-based baseline indicates that direct implicit surface recovery remains challenging for the tested hollow cylindrical shaft-wall scene. The results demonstrate the potential of the proposed NeRF-based workflow for rescue-shaft inner-wall reconstruction and engineering-oriented deformation evaluation. Full article

This study examines the temporal evolution of low-carbon energy production in the European Union (EU27) using annual data for 1990–2022, focusing on the dynamic interaction between nuclear, renewable, and biofuel production at the EU aggregate level. After evaluating stochastic properties via Augmented Dickey–Fuller (ADF) tests and assessing long-run cointegration through the Johansen framework, short-run interactions are modeled using a Vector Autoregression (VAR) of order one. Dynamic responses and innovation variances are analyzed using impulse response functions (IRFs) and forecast error variance decomposition (FEVD). The Augmented Dickey–Fuller (ADF) results suggest both series are I(1). The Johansen test fails to reject the null of no cointegration, implying that there is no stable long-run equilibrium relationship between the two series over 1990–2022. VAR-based IRFs show small, short-lived cross-responses that dissipate within a few years. FEVD results indicate that variance shares are horizon-dependent and sensitive to the Cholesky ordering. Granger causality tests provide limited evidence of short-run directional predictability. A Zivot–Andrews test does not reject the unit-root-with-break null. These findings suggest that nuclear and renewables follow largely independent dynamics in the EU27 aggregate. A key limitation is that EU27 aggregation masks cross-country heterogeneity (e.g., Germany vs. France) and excludes policy variables, prices, and demand-side drivers. The estimated VAR(1) satisfies the stability condition: all eigenvalues of the companion matrix lie inside the unit circle (modulus < 1), confirming that the system is dynamically stable. Full article

Gondolas are a useful mode of transportation in the mountainous regions. In regions located at high altitudes, atmospheric icing is a significant safety hazard to gondola infrastructure. In this study, multiphase numerical simulations of ice accretion on the monopole gondola tower were performed and validated against experimental and analytical model results. An analytical model has limitations for calculating ice loads on large cylinder diameters, and conducting experiments on large cylinders is also challenging due to practical constraints. Ansys FENSAP-ICE 2025 R2, as the primary numerical simulation tool, appears to be an attractive alternative for better estimation of ice loads on structures with larger diameters. The numerical analysis demonstrates that the ice accretion on the access ladder of the gondola tower is more critical than its main structure. This is because the ice growth on the smaller components is higher than on the larger components. A solution based on passive structural design is suggested, in which a semi-circle-shaped wind shield is introduced along the windward side of the tower which successfully diverts the flow by creating a protective droplet shadow on the trailing components, significantly reducing the accreted ice loads. It can also serve as a safety barrier for maintenance personnel. The study also showed that increasing the shield diameter ultimately reduced overall ice accretion, due to the dominant droplet drag forces over inertial forces. Full article

Uniform circular arrays (UCAs) are widely used in underwater source localization due to their omnidirectional coverage. However, random sensor position errors caused by installation inaccuracies and environmental disturbances convert UCAs into non-uniform circular arrays (NCAs), severely degrading the performance of high-resolution direction of arrival (DOA) estimation algorithms. To address this issue, this paper proposes a robust DOA estimation method that integrates empirical mode decomposition (EMD) denoising with prior-weighted iterative least squares (PWLS) correction. The method first applies EMD to adaptively denoise received signals by selecting intrinsic mode functions based on a combined energy-correlation criterion. An initial DOA estimate is then obtained using the MUSIC algorithm. Finally, a PWLS correction algorithm leverages prior knowledge of deviated sensors to iteratively fit the circle center and gradually pull sensor positions toward the ideal circumference, using a differentiated relaxation mechanism to suppress outliers while preserving geometric features. Systematic Monte Carlo simulations compare five correction algorithms under multi-frequency and wideband signals. The results show that both multi-frequency and wideband signals reduce estimation errors to below 0.1°, with the proposed PWLS achieving the best accuracy under multi-frequency signals, while all algorithms approach zero error under wideband signals. The PWLS algorithm converges in about 10 iterations with high computational efficiency, providing a reliable solution for practical underwater NCA applications. Full article

This paper proposes a novel task assignment strategy for multiple fixed-wing loitering munitions, focusing on the kinematic capturability of maneuvering ground targets. Compared to rotary-wing UAVs, fixed-wing munitions are subject to significant turning radius constraints and limited maneuverability. Consequently, conventional assignment metrics based on relative distance or estimated time-to-go are insufficient to guarantee successful interception. To address this, we adopt a data-driven capturability prediction framework based on Gaussian Process Regression (GPR) and propose a novel task assignment strategy that leverages the predicted capture region as a decision-making criterion. Furthermore, a robustness-centric task assignment algorithm is proposed, which prioritizes interceptors based on the radius of the Maximum Inscribed Circle (MIC) within the predicted capture region. This metric quantifies the safety margin against target maneuvers and environmental uncertainties. Numerical simulations demonstrate that the proposed method significantly outperforms conventional distance-based and time-to-go-based approaches, achieving the highest interception success rate across all tested scenarios including maneuvering target conditions. The results validate that incorporating geometric capturability constraints is essential for the efficient operation of fixed-wing loitering munitions. Full article

Synthetic Aperture Radar (SAR) enables all-weather maritime surveillance, yet ship-oriented bounding box (OBB) detection remains challenging in complex scenes. Strong sea clutter and dense harbor scatterers often mask the slender characteristics of ships as well as the weak responses of small ships. Meanwhile, the periodicity of angle parameterization introduces regression discontinuities, and near-symmetric, bright-scatterer-dominated signatures further cause heading ambiguity, undermining the stability of orientation prediction. Moreover, in most detectors, multi-scale feature fusion and angle estimation lack explicit coordination, and rotated-box localization performance is often jointly affected by feature degradation and unstable orientation prediction. To this end, we propose a unified framework that simultaneously strengthens multi-scale representations and stabilizes orientation modeling. Specifically, we design a Gaussian-Guided Stage-Aware Deformable Feature Pyramid Network (GSDFPN) and a Coarse-to-Fine Unit-Circle Resolver (CF-UCR). GSDFPN enhances multi-scale fusion with two plug-in components: (i) a Gaussian-guided High-level Semantic Refinement Module (GHSRM) that suppresses clutter-dominated semantics while strengthening ship-responsive cues, and (ii) a Stage-aware Deformable Fusion Module (SDFM) for low-level features, which disentangles channels into a geometry-preserving spatial stream and a clutter-resistant semantic stream, and couples them via deformable interaction with bidirectional cross-stream gating to better capture the inherent slender characteristics of ships and localize small ships. For orientation, CF-UCR decomposes angle prediction into direction-cluster classification and intra-cluster residual regression on the unit circle, effectively mitigating periodicity-induced discontinuities and stabilizing rotated-box estimation. On SSDD+ and RSDD, our method achieves AP/AP₅₀/AP₇₅ of 0.5390/0.9345/0.4529 and 0.4895/0.9210/0.4712, respectively, while reaching AP_s75/AP_m75/AP_l75 of 0.5614/0.8300/0.8392 and 0.4986/0.8163/0.8934, evidencing strong rotated-box localization across target scales in complex maritime scenes. Full article

The strong electromagnetic interference environment on the battlefield has brought new challenges to the networking collaboration of jammers and the estimation of jamming effects. Traditional successful jamming indicators are difficult to meet the needs of continuous, low-power, and flexible jamming, causing difficulties in emergency scheduling of jamming resources. Aiming at the overall degradation of the communication party’s signal reception quality, this paper proposes the restrictive conditions of “overall limited jamming” and the analysis and evaluation index of “multistage jamming-to-signal ratio (J/S)”, which meets the scheduling requirements of distributed jamming resources in harsh environments. Based on the jammer layout that can achieve overall high-intensity jamming, the electromagnetic environment estimation, power scheduling, and collaboration strategies of jammers are designed, a communication countermeasure game algorithm under blocked networking collaboration is established, and the independent dynamic scheduling of jamming resources is realized. The experimental results show that the Concentric Circle Broadcasting Algorithm (CCBA) not only maintains effective communication jamming (the proportion of high-intensity jamming is no less than 50%, and the proportion of normal signal reception of communication nodes is no more than 6%), but also extends the system operation duration by 66.8–269.6% compared with the comparative algorithms for the 600 MHz fixed-frequency and 1 MHz bandwidth communication system. This work is limited to the line-of-sight (LOS) scenario, and future research will extend it to non-line-of-sight (NLOS) scenarios. Full article

To address the difficulty of accurately localizing automotive chassis bolts during the assembly process—caused by non-uniform illumination, limited camera installation space, and occlusions from the vehicle body structure—a fiducial-marker-based localization method is proposed. In this method, a concentric ring-shaped fiducial marker is affixed to the bottom of the assembly wrench, and its region of interest (ROI) is extracted using an HSV color space segmentation algorithm. To overcome interference from uneven lighting and insufficient brightness in industrial environments, an improved Retinex-based image enhancement algorithm is introduced, which significantly improves the robustness and accuracy of ROI extraction. The extracted ROI image is subjected to ellipse fitting, and the fitting process is optimized by incorporating the Leitz criterion. Experimental results show that the optimized ellipse fitting algorithm achieves higher accuracy and significantly enhances the reliability of fitting. Since perspective projection of spatial circles leads to displacement of the circle center, the actual projected center of the fiducial marker in the image is calculated by estimating the normal vector of the circular plane using vanishing lines and the ellipse parameter matrix. This enables spatial localization of the bolt end. The proposed method is validated by comparing the localization results with the theoretical coordinates of the bolt holes. Experimental results demonstrate that the method offers high localization accuracy and strong robustness, meeting the practical precision requirements for automatic bolt assembly in industrial applications. Full article

Aerial remote sensing efficiently surveys large areas, but accurate direct object-level measurement remains difficult in complex natural scenes. Advancements in 3D computer vision, particularly radiance field representations such as NeRF and 3D Gaussian splatting, can improve reconstruction fidelity from posed imagery. Nevertheless, direct aerial measurement of important attributes like tree diameter at breast height (DBH) remains challenging. Trunks in aerial forest scans are distant and sparsely observed in image views; at typical operating altitudes, stems may span only a few pixels. With these constraints, conventional reconstruction methods have inaccurate breast-height trunk geometry. TreeDGS is an aerial image reconstruction method that uses 3D Gaussian splatting as a continuous scene representation for trunk measurement. After SfM–MVS initialization and Gaussian optimization, we extract a dense point set from the Gaussian field using RaDe-GS’s depth-aware cumulative-opacity integration and associate each sample with a multi-view opacity reliability score. Then, we isolate trunk points and estimate DBH using opacity-weighted solid-circle fitting. Evaluated on 10 plots with field-measured DBH, TreeDGS reaches 4.79 cm RMSE (about 2.6 pixels at this GSD) and outperforms a LiDAR baseline (7.66 cm RMSE). This shows that TreeDGS can enable accurate, low-cost aerial DBH measurement. Full article

Subspace algorithms like canonical variate analysis (CVA) are regression-based methods for the estimation of linear dynamic state space models. They have been shown to deliver accurate (consistent and asymptotically equivalent to quasi-maximum likelihood estimation using the Gaussian likelihood) estimators for stably invertible stationary autoregressive moving average (ARMA) processes. These results use the assumption that there are no zeros of the spectral density on the unit circle corresponding to the state space system. In this technical study, we consider vector processes made stationary by applying differencing to all variables, ignoring potential co-integrating relations. This leads to spectral zeros violating the above mentioned assumptions. We show consistency for the CVA estimators, closing a gap in the literature. However, a simulation exercise shows that over-differencing (while leading to consistent estimation of the transfer function) also complicates inference for CVA estimators, not just maximum likelihood-based estimators. This is also demonstrated in a real-world data example. The result also applies to seasonal differencing. The present paper hence suggests working with original data, not working in differences. Full article