Search Results (156)

Acoustic sensing is a passive and cost-effective option for unmanned aerial vehicle detection, where both signal processing and microphone hardware jointly determine field performance. In this study, we focus on the hardware front-end as a foundation for improving the reliability of subsequent DSP- or AI-based detection methods. We present a detection-focused comparison of several microphones in outdoor tests, combining calibrated range measurements with spectral analysis of real unmanned aerial vehicle emissions from three platforms. We report hardware metrics only: signal-to-noise ratio, effective detection range, attenuation slope with distance, and the low-frequency background floor. Across wind conditions and source orientations, the RØDE NTG-2 with WS6 windshield delivered the most balanced performance: in strong wind, it extended the detection range over the bare NTG-2 by approximately 31–131% (depending on azimuth), lowered the low-frequency noise floor by about 2–3 decibels, and matched or increased the wideband signal-to-noise ratio by 1.8–4.4 decibels. A parabolic NTG-2 achieved very low background noise levels at low frequencies and strong on-axis reach but proved vulnerable to gust-induced transients. Based on this evidence, we propose an eight-channel, dual-tier array of NTG-2 + WS6 elements that preserves near-hemispherical coverage and phase coherence, establishing a practical hardware baseline for outdoor acoustic unmanned aerial vehicle detection and a reproducible platform for subsequent localization and classification studies. Full article

Agricultural soils near industrial parks in the Yellow River bend region face severe heavy metal pollution, posing a significant to human health. This study integrated field sampling with laboratory analysis and applied geostatistical analysis, positive matrix factorization (PMF) modeling, and health risk assessment models to systematically investigate the pollution levels, spatial distribution, sources, and ecological health risks of heavy metals in the area. The main findings are as follows: (1) The average concentrations of the eight heavy metals (Hg, Cr, Cu, Pb, Zn, As, Cd, and Ni) in the study area were 0.04, 48.3, 54.3, 45.7, 70.0, 22.9, 0.4, and 35.7 mg·kg⁻¹, respectively. The concentrations exceeded local background values by factors ranging from 1.32 to 11.2. Exceedances of soil screening and control values were particularly pronounced for Cd and As. Based on the geoaccumulation index, over 75% of the sampling sites for Cr, Pb, Zn, and Cd were classified as moderately to heavily polluted. Potential ecological risk assessment highlighted Cd as the significant ecological risk factor, indicating considerable heavy metal pollution in the region. (2) Kriging interpolation demonstrated elevated concentrations in the western (mid-upper) and eastern (mid-lower) subregions. Pearson correlation analysis suggested common sources for Cu-Pb-As-Cd and Cr-Zn-Ni. (3) PMF source apportionment identified four primary sources: traffic emissions (38.19%), natural and agricultural mixed sources (34.55%), metal smelting (17.61%), and atmospheric deposition (10.10%). (4) Health risk assessment indicated that the non-carcinogenic risk for both adults and children was within acceptable limits (adults: 0.065; children: 0.12). Carcinogenic risks were also acceptable (adults: 5.67 × 10⁻⁵; children: 6.70 × 10⁻⁵). In conclusion, priority should be given to the control of traffic emissions and agriculturally derived sources in the management of soil heavy metal contamination in this region, while the considerable contribution of smelting activities warrants heightened attention. This study provides a scientific basis for the prevention, control, and targeted remediation of regional soil heavy metal pollution. Full article

We develop a year-round, field-scale framework to retrieve soil moisture and map irrigation in an arid irrigation district where crop phenology and canopy dynamics undermine static, single-season approaches. However, the currently popular TVDI application is limited during non-growing seasons. To address this gap, we introduce a season-stratified TVDI scheme—based on the LST–EVI feature space with phenology-specific dry/wet edges—coupled with a non-growing-season inversion that fuses Sentinel-1 SAR and Landsat features and compares multiple regressors (PLSR, RF, XGBoost, and CNN). The study leverages 2023–2024 multi-sensor image time series for the Yichang sub-district of the Hetao Irrigation District (China), together with in situ topsoil moisture, meteorological records, a local cropping calendar, and district statistics for validation. Methodologically, EVI is preferred over NDVI to mitigate saturation under dense canopies; season-specific edge fitting stabilizes TVDI, while cross-validated regressors yield robust soil-moisture retrievals outside the growing period, with the CNN achieving the highest accuracy (test R² ≈ 0.56–0.61), outperforming PLSR/RF/XGBoost by approximately 12–38%. The integrated mapping reveals complementary seasonal irrigation patterns: spring irrigates about 40–45% of farmland (e.g., 43.39% on 20 May 2024), summer peaks around 70% (e.g., 71.42% on 16 August 2024), and autumn stabilizes near 20–25% (e.g., 24.55% on 23 November 2024), with marked spatial contrasts between intensively irrigated southwest blocks and drier northeastern zones. We conclude that season-stratified edges and multi-source inversions together enable reproducible, year-round irrigation detection at field scale. These results provide operational evidence to refine irrigation scheduling and water allocation, and support drought-risk management and precision water governance in arid irrigation districts. Full article

Sparse arrays can effectively reduce antenna cost and implementation complexity. However, most existing research in sparse array design mainly focuses on far-field scenarios, which cannot be directly applied to near-field (NF) source localization, where the delay term and source incident parameters exhibit a nonlinear relationship. In this paper, employing a symmetric enhanced nested array, a high-precision underdetermined three-dimensional (3D) NF localization method is proposed. Firstly, the symmetry of the array and the fourth-order cumulant are utilized to construct the equivalent virtual far-field (FF) received data. Then, a gridless, sparse, and parametric approach combined with an l₁-singular value decomposition-based pairing procedure is employed to obtain estimates of two paired angles. Finally, a one-dimensional (1D) spectral estimator is applied to obtain the estimate of the range parameter. By analyzing the virtual aperture, the optimal parameter configuration for a given number of elements is obtained. As shown by simulation results, the proposed method can handle underdetermined estimation. Compared with the other algorithms, the proposed algorithm achieves significant improvements in both angular and distance accuracy, with enhancements of 65% and 61.7%, respectively. Full article

This paper investigates the near-field source localization of multiple narrowband signals in the presence of unknown nonuniform noise with an arbitrary diagonal covariance matrix. From a covariance-fitting perspective, we reformulate the near-field localization problem as a joint symmetric matrix factorization and the estimation of nonuniform noise variances. This reformulation explicitly accounts for noise heterogeneity in the covariance structure, thereby avoiding noise mismodeling and enabling robust near-field localization for nonuniform noise. To solve the intractable symmetric matrix factorization problem, we develop a computationally efficient iterative algorithm based on the block majorization–minimization principle. The proposed algorithm has light per-iteration complexity and admits a closed-form iteration update. Furthermore, we also derive the Cramér–Rao bound (CRB) for near-field localization under nonuniform noise. Extensive numerical experiments demonstrate that the proposed approach outperforms the existing state-of-the-art near-field localization methods and closely matches the CRB while maintaining strong robustness against severe nonuniform noise. Full article

To reveal the influence mechanisms of seasonal climatic factors (wind speed, wind direction, temperature) and leakage direction on hydrogen dispersion and explosion behavior from single-source leaks at typical risk locations (hydrogen storage tanks, compressors, dispensers) in hydrogen refueling stations (HRSs), this work established a full-scale 1:1 three-dimensional numerical model using the FLACS v22.2 software based on the actual layout of an HRS in Xichang, Sichuan Province. Through systematic simulations of 72 leakage scenarios (3 equipment types × 4 seasons × 6 leakage directions), the coupled effects of climatic conditions, equipment layout, and leakage direction on hydrogen dispersion patterns and explosion risks were quantitatively analyzed. The key findings indicate the following: (1) Downward leaks (−Z direction) from storage tanks tend to form large-area ground-hugging hydrogen clouds, representing the highest explosion risk (overpressure peak: 0.25 barg; flame temperature: >2500 K). Leakage from compressors (±X/−Z directions) readily affects adjacent equipment. Dispenser leaks pose relatively lower risks, but specific directions (−Y direction) coupled with wind fields may drive significant hydrogen dispersion toward station buildings. (2) Southeast/south winds during spring/summer promote outward migration of hydrogen clouds, reducing overall station risk but causing localized accumulation near storage tanks. Conversely, north/northwest winds in autumn/winter intensify hydrogen concentrations in compressor and station building areas. (3) An empirical formula integrating climatic parameters, leakage conditions, and spatial coordinates was proposed to predict hydrogen concentration (error < 20%). This model provides theoretical and data support for optimizing sensor placement, dynamically adjusting ventilation strategies, and enhancing safety design in HRSs. Full article

Precise odor source localization in turbulent and sparse environments plays a vital role in enabling robotic systems for hazardous chemical monitoring and effective disaster response. To address this, we propose Cooperative Gravitational-Rényi Infotaxis (CGRInfotaxis), a distributed decision-optimization framework that combines multi-agent collaboration with hybrid cognitive strategy to improve search efficiency and robustness. The method integrates a gravitational potential field for rapid source convergence and Rényi divergence-based probabilistic exploration to handle sparse detections, dynamically balanced via a regulation factor. Particle filtering optimizes posterior probability estimation to autonomously refine search areas while preserving computational efficiency, alongside a distributed interactive-optimization mechanism for real-time decision updates through agent cooperation. The algorithm’s performance is evaluated in scenarios with fixed and randomized odor source locations, as well as with varying numbers of agents. Results demonstrate that CGRInfotaxis achieves a near-100% success rate with high consistency across diverse conditions, outperforming existing methods in stability and adaptability. Increasing the number of agents further enhances search efficiency without compromising reliability. These findings suggest that CGRInfotaxis significantly advances multi-agent odor source localization in turbulent, sparse environments, offering practical utility for real-world applications. Full article

This study investigates the effects of diffusion modeling and swirl intensity on flow fields and NO emissions in CH₄/NH₃ non-premixed swirling flames using large eddy simulations (LESs). Simulations are performed for a 50/50 ammonia–methane blend at three global equivalence ratios of 0.77, 0.54, and 0.46 and two swirl numbers of 8 and 12, comparing the unity Lewis number (ULN) and mixture-averaged diffusion (MAD) models against the experimental data includes OH-PLIF and ON-PLIF reported in a prior study by the KAUST group. Both models produce similar flow fields, but the MAD model alters the flame structure and species distributions due to differential diffusion (DD) and limitations in its Flamelet library. Notably, the MAD library lacks unstable flame branch solutions, leading to extensive interpolation between extinction and stable branches. This results in overpredicted progress variable source terms and reactive scalars, both within and beyond the flame zone. The ULN model better reproduces experimental OH profiles and localizes NO formation near the flame front, whereas the MAD model predicts broader NO distributions due to nitrogen species diffusion. Higher swirl intensities shorten the flame and shift NO production upstream. While a low equivalence ratio provides enough air for good mixing, lower ammonia and higher NO contents in exhaust gases, respectively. Full article

Strapdown gravity systems are increasingly employed in airborne geophysical exploration and geodetic studies due to advantages such as ease of installation, wide dynamic range, and adaptability to various platforms, including airplanes, helicopters, and large drones. This study presents results from an airborne gravity survey conducted over the northeastern sector of Sardinia (Italy), using a high-resolution strapdown gravity ensuring an accuracy of approximately 1 mGal. Data were collected at an average altitude of 1800 m with a spatial resolution of 3.0 km. The survey focused on the Sos Enattos area near Lula (Nuoro province), a candidate site for the Einstein Telescope (ET), a third-generation gravitational wave observatory. The ideal site is required to be geologically and seismically stable with a well-characterized subsurface. To support this, we performed a new gravity survey to complement existing geological and seismic data aimed at characterizing the mid-to-shallow crustal structure of Sos Enattos. Results show that the strapdown system effectively detects gravity anomalies linked to crustal sources down to ~3.5 km, with particular emphasis within the 1–2 km depth range. Airborne gravity data reveal higher frequency anomalies than those resolved by the EGM2008 global gravity model and show good agreement with local terrestrial gravity data. Forward modeling of the gravity field suggests a crust dominated by alternating high-density metamorphic rocks and granitoid intrusions of the Variscan basement. These findings enhance the geophysical understanding of Sos Enattos and support its candidacy for the ET site. Full article

This study investigates pre-seismic ionospheric anomalies preceding the 2023 Jishishan Ms6.2 earthquake using total electron content (TEC) data derived from BDS geostationary orbit (GEO) satellites. Multi-scale analysis integrating Butterworth filtering and wavelet transforms resolved TEC disturbances into three distinct frequency regimes: (1) high-frequency perturbations (0.56–3.33 mHz) showed localized disturbances (amplitude ≤ 4 TECU, range < 300 km), potentially associated with near-field acoustic waves from crustal stress adjustments; (2) mid-frequency signals (0.28–0.56 mHz) exhibited anisotropic propagation (>1200 km) with azimuth-dependent N-shaped waveforms, consistent with the characteristics of acoustic–gravity waves (AGWs); and (3) low-frequency components (0.18–0.28 mHz) demonstrated phase reversal and power-law amplitude attenuation, suggesting possible lithosphere–atmosphere–ionosphere (LAI) coupling oscillations. The stark contrast between near-field residuals and far-field weak fluctuations highlighted the dominance of large-scale atmospheric gravity waves over localized acoustic disturbances. Geometry-based velocity inversion revealed incoherent high-frequency dynamics (5–30 min) versus anisotropic mid/low-frequency traveling ionospheric disturbance (TID) propagation (30–90 min) at 175–270 m/s, aligning with theoretical AGW behavior. During concurrent G1-class geomagnetic storm activity, spatial attenuation gradients and velocity anisotropy appear primarily consistent with seismogenic sources, providing insights for precursor discrimination and contributing to understanding multi-scale coupling in seismo-ionospheric systems. Full article

Understanding strain behavior near grain boundaries is critical for controlling structural distortions and oxygen vacancy migration in perovskite oxides. However, conventional techniques often lack the spatial resolution needed to analyze phase and domain evolution at the nanoscale. In this paper, polarization-dependent second-harmonic generation (SHG) imaging is employed as a tool to probe local symmetry breaking and complex domain structures in the vicinity of a low-angle grain boundary of SrTiO₃ (STO) bicrystals. We show that the anisotropic strain introduced by a tilted grain boundary produces strong local distortions, leading to the coexistence of tetragonal and rhombohedral domains. By analyzing SHG intensity and variations in the second-order nonlinear optical susceptibility, we map the distribution of strain fields and domain configurations near the boundary. In pristine samples, the grain boundary acts as a localized source of strain accumulation and symmetry breaking, while in samples subjected to intentional electrical stressing, the SHG response becomes broader and more uniform, suggesting strain relaxation. This work highlights SHG imaging as a powerful technique for visualizing grain-boundary-driven structural changes, with broad implications for the design of strain-engineered functional oxide devices. Full article

Anticyclonic mesoscale eddies are known to trap and modulate near-inertial kinetic energy (NIKE); however, the spatial distribution of NIKE within the eddy core and periphery, as well as the mechanisms driving its energy cascade to smaller scales, remains inadequately understood. This study analyzed the evolution of NIKE in anticyclonic eddies using satellite altimetry and field observations from four mooring arrays. By extracting near-inertial oscillations (NIOs) and subharmonic wave kinetic energy across mooring stations during the same period, we characterized the spatial structure of NIKE within the eddy field. The results revealed that NIKE was concentrated in the eddy core, where strong NIOs (peak velocity ~0.23 m/s) persisted for ~7 days, with energy primarily distributed at depths of 200–400 m and propagating inward from the periphery. Subharmonic waves fD1 generated by interactions between NIOs and diurnal tides highlighted the role of the vertical nonlinear term in energy transfer. A further analysis indicated that under vorticity confinement, NIKE accumulated in the core of the eddy and dissipated through shear instability and nonlinear wave interactions. The migrating anticyclonic eddy thus acted as a localized energy source, driving mixing and energy dissipation in the ocean interior. Full article

As a key technology for the fifth-generation of mobile communications, massive MIMO systems enable massive user access via large-scale arrays. However, their dense deployment extends the near-field (NF) region, introducing new localization complexities. Based on an exact spherical wavefront model, this paper proposes a multiple-cumulant-matrices-based method for NF source localization using a Co-centered Orthogonal Loop and Dipole (COLD) array. Firstly, following the physical numbering of array elements, we can construct multiple polarization cumulant matrices, which can then be cascaded into a long matrix. Next, the signal subspace can be obtained through eigen-decomposition of this long matrix, from which the horizontal and vertical components can be further separated. By applying ESPRIT, joint angle, range, and polarization parameters can be estimated. In addition, the asymptotic variances for joint spatial and polarization parameters are analyzed. Compared with existing NF polarization algorithms, the proposed method exhibits better parameter estimation and is consistent with a theoretical asymptotic performance. Full article

Precision irrigation requires reliable estimates of crop evapotranspiration (ET) using site-specific crop and weather data inputs. Such estimates are needed at high resolutions which have been minimally explored for heterogeneous crops such as orchards. In addition, weather information for estimating ET is very often selected from sources that do not represent conditions like heterogeneous site-specific conditions. Therefore, a study was conducted to map geospatial ET and transpiration (T) of a high-density modern apple orchard using high-resolution aerial imagery, as well as to quantify the impact of site-specific weather conditions on the estimates. Five campaigns were conducted in the 2020 growing season to acquire small unmanned aerial system (UAS)-based thermal and multispectral imagery data. The imagery and open-field weather data (solar radiation, air temperature, wind speed, relative humidity, and precipitation) inputs were used in a modified energy balance (UASM-1 approach) extracted from the Mapping ET at High Resolution with Internalized Calibration (METRIC) model. Tree trunk water potential measurements were used as reference to evaluate T estimates mapped using the UASM-1 approach. UASM-1-derived T estimates had very strong correlations (Pearson correlation [r]: 0.85) with the ground-reference measurements. Ground reference measurements also had strong agreement with the reference ET calculated using the Penman–Monteith method and in situ weather data (r: 0.89). UASM-1-based ET and T estimates were also similar to conventional Landsat-METRIC (LM) and the standard crop coefficient approaches, respectively, showing correlation in the range of 0.82–0.95 and normalized root mean square differences [RMSD] of 13–16%. UASM-1 was then modified (termed as UASM-2) to ingest a locally calibrated leaf area index function. This modification deviated the components of the energy balance by ~13.5% but not the final T estimates (r: 1, RMSD: 5%). Next, impacts of representative and non-representative weather information were also evaluated on crop water uses estimates. For this, UASM-2 was used to evaluate the effects of weather data inputs acquired from sources near and within the orchard block on T estimates. Minimal variations in T estimates were observed for weather data inputs from open-field stations at 1 and 3 km where correlation coefficients (r) ranged within 0.85–0.97 and RMSD within 3–13% relative to the station at the orchard-center (5 m above ground level). Overall, the results suggest that weather data from within 5 km radius of orchard site, with similar topography and microclimate attributes, when used in conjunction with high-resolution aerial imagery could be useful for reliable apple canopy transpiration estimation for pertinent site-specific irrigation management. Full article

This study combines field and laboratory analyses from seven shallow wells (ZK1 to ZK7) positioned perpendicular to the coastline to investigate groundwater discharge and dynamics in the coastal unconfined aquifer of the intertidal zone at Yazhou Bay, Sanya, Hainan Province. The research highlights spatial variations in N₂O concentration, temperature, electrical conductivity (EC), pH, and the distribution of CFCs and CCl₄ in shallow groundwater, utilizing samples from wells ZK1 to ZK7 and seawater collected near ZK1. Key findings indicate that groundwater temperature decreases toward the ocean, while EC exhibits a stepwise increase from land to sea, with a sharp transition near ZK3 marking the freshwater–saltwater mixing zone. pH values are lowest in ZK3 and ZK4, gradually rising both inland and seaward. N₂O concentrations in the shallow wells (ZK1–ZK7) are divided into two distinct groups: higher concentrations (9.69–57.77 nmol/kg) in ZK5–ZK7 and lower concentrations (6.63–23.03 nmol/kg) in ZK1–ZK4. Wells ZK3 and ZK4 show minimal variation in CFC-11 and CFC-113 concentrations, suggesting they represent a transition zone that likely delineates groundwater flow paths. In contrast, significant concentration differences in wells ZK5–ZK7 (north) and ZK1–ZK2 (south) reflect the influence of aquifer structure variability, recharge sources, and local hydrogeochemical conditions. CFC-12 concentrations exhibit a clear freshwater–saltwater mixing gradient between ZK3 and ZK1, with higher concentrations in freshwater-dominated areas (ZK3–ZK7) and lower concentrations near seawater (ZK1). CCl₄ concentrations at ZK7 and ZK3 differ markedly from other wells, indicating unique hydrogeochemical conditions or localized anthropogenic influences. A model for the formation of upper saline plumes (USP) under tidal forcing at the low tidal line was established previously. Here, we establish a new model that accounts for the absence of USP driven by hydrological processes influenced by artificial sandy beach topography, and a fresh groundwater wedge is identified, which can serve as a significant fast-flow pathway for terrestrial water and nutrients to the ocean. Full article