Search Results (32)

The Linfen–Yuncheng Basin is located on the southern edge of the Fenwei Fault Zone, influenced by intense tectonic activity, thick Quaternary sedimentation, and anthropogenic disturbance, it exhibits prominent characteristics of ground subsidence and fissure development. However, uncertainties still exist regarding the primary controlling factors of subsidence. This study employs multi-temporal InSAR data, combined with small baseline subset (SBAS–InSAR) technology to invert the high-precision ground line of sight deformation fields, and conducts time-series decomposition analysis using the Seasonal Trend Decomposition (STL) method. The results show that from 2017 to 2025, subsidence was mainly concentrated in the central and southern regions of the basin, with a maximum cumulative subsidence exceeding 200 mm and an average annual subsidence rate of −40 mm/year. Its spatial distribution is highly consistent with major structural zones such as the Zhongtiao Mountain Front Fault and the Linyi Fault, indicating that fault activity exerts a significant controlling effect on subsidence patterns. Groundwater level fluctuations are positively correlated with overall ground subsidence, and the response rate of different monitoring points is constrained by differences in aquifer depth and permeability. Groundwater aquifer points exhibit rapid and reversible subsidence response, while confined aquifer points are affected by low-permeability or compressible layers, showing a significant lag effect. The research results indicate that time-series analysis based on InSAR can not only effectively reveal the subsidence evolution process at different scales, but also provide a scientific basis for groundwater resource regulation, geological disaster prevention and control, and sustainable regional land utilization. Full article

Physics-informed neural networks (PINNs) have recently attracted considerable attention as a framework for solving partial differential equations. Underwater sound-field prediction fundamentally relies on solving acoustic wave equations, making PINNs a natural candidate for this application. This paper reviews recent developments in PINN-based modeling of underwater acoustic propagation, which we group into two main lines of research. The first introduces mathematically motivated simplifications of the governing equations and then employs PINNs as efficient solvers; examples include ray-based PINNs and PINN estimators of modal wavenumbers. The second focuses on improving computational performance by tailoring network architectures and hyperparameters, such as spatial domain-decomposition strategies. While PINNs demonstrate significant potential, challenges persist regarding computational efficiency and convergence in high-frequency regimes. Future research directions are identified, emphasizing a multi-faceted strategy that systematically addresses limitations at both the physical formulation level and the neural network architecture level. By integrating advanced hybrid physics-data modeling and scalable training algorithms, this review highlights the pathway toward bridging the gap between theoretical frameworks and realistic ocean applications. Full article

This review synthesizes the literature on the degradation and decomposition of holopelagic Sargassum, with a focus on process dynamics, including microbial contribution, process descriptions, and ecological impacts. Our objective is to consolidate a robust knowledge framework to inform and optimize management strategies in affected areas. Overall, we observed that the current literature relies primarily on isolated field ecological descriptions rather than a coherent, unified research line; mechanistic studies, including bacterial pathways and factors controlling degradation, remain scarce. At the fine scale, microbial community shifts during decomposition are strongly linked to the sequential utilization of distinct organic substrates, thereby favoring the proliferation of microorganisms capable of degrading complex organic molecules and of bacterial groups involved in sulfur respiration, methanogenesis, and nutrient recycling. In the case of sulfur respiration, groups such as Desulfobacterales and Desulfovibrionales may be responsible for the reported H₂S emissions, which pose significant public health concerns. At a broad scale, degradation occurs both on beaches during emersion and in the water column during immersion, particularly during massive accumulations. The initial stages are characterized by the release of organic exudates and leachates. Experimental and observational studies confirm a strong early-stage release of H₂S until the substrate is largely depleted. Depending on environmental conditions, a significant amount of biomass can be lost; however, this loss is highly variable, with notable consequences for contamination studies. Leachates may also contain low but ecologically significant amounts of arsenic, posing a potential contamination risk. Decomposition contributes to water-quality deterioration and oxygen depletion, with impacts at the individual, population, and ecosystem levels, yet many remain imprecisely attributed. Although evidence of nutrient enrichment in the water column is limited, studies indicate biological nutrient uptake. Achieving a comprehensive understanding of degradation and decomposition, including temporal and spatial dynamics, microbiome interactions, by means of directed research, is critical for effective coastal management, improved mitigation strategies, industrial valorization, and accurate modeling of biogeochemical cycles. Full article

Background/Objectives: This study evaluates photon-counting CT (PCCT) for the imaging of mouse femurs and investigates how APOE genotype, sex, and humanized nitric oxide synthase (HN) expression influence bone morphology during aging. Methods: A custom-built micro-CT system with a photon-counting detector (PCD) was used to acquire dual-energy scans of mouse femur samples. PCCT projections were corrected for tile gain differences, iteratively reconstructed with 20 µm isotropic resolution, and decomposed into calcium and water maps. PCD spatial resolution was benchmarked against an energy-integrating detector (EID) using line profiles through trabecular bone. The contrast-to-noise ratio quantified the effects of iterative reconstruction and material decomposition. Femur features such as mean cortical thickness, mean trabecular spacing (TbSp_mean), and trabecular bone volume fraction (BV/TV) were extracted from calcium maps using BoneJ. The statistical analysis used 57 aged mice representing the APOE22, APOE33, and APOE44 genotypes, including 27 expressing HN. We used generalized linear models (GLMs) to evaluate the main interaction effects of age, sex, genotype, and HN status on femur features and Mann–Whitney U tests for stratified analyses. Results: PCCT outperformed EID-CT in spatial resolution and enabled the effective separation of calcium and water. Female HN mice exhibited reduced BV/TV compared to both male HN and female non-HN mice. While genotype effects were modest, a genotype-by-sex stratified analysis found significant effects of HN status in female APOE22 and APOE44 mice only. Linear regression showed that age significantly decreased cortical thickness and increased TbSp_mean in male mice only. Conclusions: These results demonstrate PCCT’s utility for femur analysis and reveal strong effects of sex/HN interaction on trabecular bone health in mice. Full article

To improve the efficiency of multi-region multi-unmanned aerial vehicle (UAV) inspection, this paper proposes a composite task planning strategy integrating the K-Means++ genetic algorithm (KMGA) and the multi-neighborhood iterative dynamic programming (MNIDP) method. Firstly, the multi-region multi-UAV inspection problem is modeled as a multiple traveling salesmen problem with neighborhoods (MTSPN). Then, this problem is decomposed into two interrelated subproblems to mitigate the complexity inherent in the solution process: that is, the multiple traveling salesmen problem (MTSP) and multi-neighborhoods path planning (MNPP) problem. Based on this decomposition, the MTSP is solved by the KMGA by converting it into m spatially non-overlapping traveling salesmen problems (TSPs) and then these TSPs are solved to obtain the approximate optimal visiting sequences for the nodes in each TSP in a short time. Subsequently, the MNPP can be efficiently solved by an MNIDP which plans the paths between the corresponding neighborhood of each node based on the node visiting sequences, thus obtaining the approximate optimal path length of the MTSPN. The simulation results demonstrate that the proposed composite strategy exhibits advantages in computational efficiency and optimal path length. Specifically, compared to the baseline algorithm, the average tour length obtained by the KMGA decreased by 23.24%. Meanwhile, the average path lengths computed by MNIDP in three instances were reduced from 8.00% to 11.41% and from 6.46% to 10.08% compared to two baseline algorithms, respectively. It provides an efficient task and path planning solution for multi-region multi-UAV operations in power transmission line inspections, thereby enhancing inspection efficiency. Full article

To elucidate the food–energy–water (FEW) nexus, in this paper, a food–energy–water–carbon (FEWC) measurement method is established, and the evolutionary mechanisms within the nexus are determined to optimize crop production systems (CPSs). A quantitative assessment of the trade-offs and synergies among the constituent sub-nexuses is presented. This assessment is achieved through carbon footprint analysis of CPSs. In addition to examining FEW resource interactions, we employ the logarithmic mean divisia index methodology—a tool well-suited for practical energy decomposition—to explore the nexus interrelationships. This research further accounts for anthropogenic inputs in CPSs, specifically using blue water and energy consumption as key indicators for characterizing water and energy dynamics, respectively. Five crops are selected for CPS carbon emissions analysis to inform cropping structure optimization. The results show that during 2000–2022, greenhouse gas (GHG) emissions from China’s CPSs exhibited significant fluctuations characterized by a concentrated–dispersed–concentrated distribution pattern: the food system’s carbon footprint decreased notably, the food–energy (FE) system’s impact increased substantially, and the food–water (FW) system’s footprint fluctuated before decreasing. The spatial diversity in the FE system’s provincial carbon footprint increased over time, while the FW nexus exhibited fluctuating yet significant efficiency gains, indicating movement toward more balanced spatial distribution along the Hu Huanyong Line and Botai Line. The net effect of the FEW nexus interactions on GHG emissions exhibited a slight mitigating influence. Full article

Challenges are brought to high impedance fault (HIF) line selection in traditional distribution networks by the fault signals with short windows and weak characteristics provided by new energy power sources. A new method driven by the symmetry of current traveling wave spectrum is proposed in this paper. Frequency-domain features are extracted by using Pisarenko spectral decomposition, and the differences in amplitude, frequency, and polarity between faulted and healthy feeders are analyzed. A similarity matrix is constructed with the help of Manhattan distance, and an improved density-based spatial clustering of application with noise (DBSCAN) clustering is adopted to achieve intelligent fault line selection. Experimental results show that compared with the steady state component method and the transient component method, the accuracy of this method is increased to 97.5%, with an improvement of more than 12.5%. Quantitative thresholds are replaced by qualitative spectrum differences, and this method is not affected by weak signals, thus solving the problem of threshold setting caused by the access of new energy. The accuracy of this method under different fault types, phases, and resistances is verified by simulation, ensuring easy engineering implementation. Full article

There is an emerging consensus that numerical, executive function (EF), and spatial skills are foundational to children’s mathematical learning and development. Moreover, each skill has been theorized to relate to mathematics for different reasons. Thus, it is possible that each cognitive construct is related to mathematics through distinct pathways. The present study tests this hypothesis. One-hundred and eighty 4- to 9-year-olds (M_age = 6.21) completed a battery of numerical, EF, spatial, and mathematics measures. Factor analyses revealed strong, but separable, relations between children’s numerical, EF, and spatial skills. Moreover, the three-factor model (i.e., modelling numerical, EF, and spatial skills as separate latent variables) fit the data better than a general intelligence (g-factor) model. While EF skills were the only unique predictor of number line performance, spatial skills were the only unique predictor of arithmetic (addition) performance. Additionally, spatial skills were related to the use of more advanced addition strategies (e.g., composition/decomposition and retrieval), which in turn were related to children’s overall arithmetic performance. That is, children’s strategy use fully mediated the relation between spatial skills and arithmetic performance. Taken together, these findings provide new insights into the cognitive foundations of early mathematics, with implications for assessment and instruction moving forward. Full article

The primary objective of this study was to assess differential vertical and horizontal deformations for the offshore Kashagan oilfield located in the Northern Caspian Sea. Sentinel-1 (SNT1) and COSMO-SkyMed (CSK) synthetic-aperture radar (SAR) images (9 January 2018–6 April 2022) were processed using persistent scatterer interferometric SAR (PS-InSAR) technique with further 2D decomposition of line-of-sight (LOS) measurements to differential vertical and horizontal deformations. Differential vertical deformation velocity was observed to be between −4 mm/y and 4 mm/y, whereas horizontal was between −4 mm/y and 5 mm/y during 2018–2022. However, it was possible to observe the spatial deformation patterns with the subsidence hotspots reaching differential cumulative vertical displacement of −20 mm from both satellite missions. PS-InSAR differential vertical deformation measurements derived from SNT1 and CSK satellite images showed identical spatial patterns with moderate agreement, whereas poor agreement was observed for differential horizontal deformations. The differential vertical deformation hotspots were observed for the oilfield areas installed on piles with obviously higher vulnerability to dynamic movements. Through this study, based on the interferometric measurements, marine geotechnical expert feedback, and no reported deformation-related incidents since 2013, it was possible to conclude that the Kashagan oilfield had not been impacted by significant differential vertical and horizontal deformations on the oilfield. However, since long-term GPS measurements were not accessible from the oilfield to be used as the reference for PS-InSAR measurements, we were not able to judge the long-term displacements of the entire oilfield or possible oscillations, even though it is built on the artificial island. Considering the broad range of PS-InSAR measurements using time-series radar images, the interferometric measurements could play a significant role in the prioritization of insitu risk assessment activities, operational cost reduction, strengthening of safety factors, and planning of further targeted insitu measurements. Full article

An accumulating body of literature points to a link between spatial reasoning and mathematics learning. The present study contributes to this line of research by investigating sex differences both in spatial representations of magnitude and in the use of arithmetic strategies, as well as the relation between the two. To test the hypothesis that sex differences in spatial–numerical magnitude knowledge mediate sex differences in the use of advanced strategies (retrieval and decomposition), two studies were conducted. Study 1 included 96 US first graders (53% girls); Study 2 included 210 Russian first graders (49% girls). All participants completed a number line estimation task (a spatially based measure of numerical magnitude knowledge) and an arithmetic strategy task (a measure of strategy choice). The studies showed parallel results: boys produced more accurate numerical magnitude estimates on the number line estimation task and used advanced strategies more frequently on the arithmetic task. Critically, both studies provide support for the mediation hypothesis (although there were some differences in the pattern obtained for the two strategies). The results are discussed in the context of broader research about the relation between spatial and mathematical skills. Full article

Due to some limitations associated with the atmospheric residual phase in Sentinel-1 data interferometry during the Jiashi earthquake, the detailed spatial distribution of the line-of-sight (LOS) surface deformation field is still not fully understood. This study, therefore, proposes an inversion method of coseismic deformation field and fault slip distribution, taking atmospheric effect into account to address this issue. First, an improved inverse distance weighted (IDW) interpolation tropospheric decomposition model is utilised to accurately estimate the turbulence component in tropospheric delay. Using the joint constraints of the corrected deformation fields, the geometric parameters of the seismogenic fault and the distribution of coseismic slip are then inverted. The findings show that the coseismic deformation field (long axis strike was nearly east–west) was distributed along the Kalpingtag fault and the Ozgertaou fault, and the earthquake was found to occur in the low dip thrust nappe structural belt at the subduction interface of the block. Correspondingly, the slip model further revealed that the slips were concentrated at depths between 10 and 20 km, with a maximum slip of 0.34 m. Accordingly, the seismic magnitude of the earthquake was estimated to be Ms 6.06. Considering the geological structure in the earthquake region and the fault source parameters, we infer that the Kepingtag reverse fault is responsible for the earthquake, and the improved IDW interpolation tropospheric decomposition model can perform atmospheric correction more effectively, which is also beneficial for the source parameter inversion of the Jiashi earthquake. Full article

Toxic metals have attracted great concern worldwide due to their toxicity and slow decomposition. Although metal concentrations can be accurately obtained with chemical methods, it is difficult to map metal distributions on a large scale due to their inherently low efficiency and high cost. Moreover, chemical analysis methods easily lead to secondary contamination. To address these issues, 110 topsoil samples were collected using a soil sampler, and positions for each sample were surveyed using a global navigation satellite system (GNSS) receiver from a coal mine in northern China. Then, the metal contents were surveyed in a laboratory via a portable X-ray fluorescence spectroscopy (XRF) device, and GaoFen-5 (GF-5) satellite hyperspectral images were used to retrieve the spectra of the soil samples. Furthermore, a Savitzky–Golay (SG) filter and continuous wavelet transform (CWT) were selected to smooth and enhance the soil reflectance. Competitive adaptive reweighted sampling (CARS) and Boruta algorithms were utilized to identify the feature bands. The optimum two-stage method, consisting of the random forest (RF) and ordinary kriging (OK) methods, was used to infer the metal concentrations. The following outcomes were achieved. Firstly, both zinc (Zn) (68.07 mg/kg) and nickel (Ni) (26.61 mg/kg) surpassed the regional background value (Zn: 48.60 mg/kg, Ni: 19.5 mg/kg). Secondly, the optimum model of RF, combined with the OK (RFOK) method, with a relatively higher coefficient of determination (R²) (R² = 0.60 for Zn, R² = 0.30 for Ni), a lower root-mean-square error (RMSE) (RMSE = 12.45 mg/kg for Zn, RMSE = 3.97 mg/kg for Ni), and a lower mean absolute error (MAE) (MAE = 9.47 mg/kg for Zn, MAE = 3.31mg/kg for Ni), outperformed the other four models, including the RF, OK, inverse distance weighted (IDW) method, and the optimum model of RF combined with IDW (RFIDW) method in estimating soil Zn and Ni contents, respectively. Thirdly, the distribution of soil Zn and Ni concentrations obtained from the best-predicted method and the GF-5 satellite hyperspectral images was in line with the actual conditions. This scheme proves that satellite hyperspectral images can be used to directly estimate metal distributions, and the present study provides a scientific base for mapping heavy metal spatial distribution on a relatively large scale. Full article

Rail expresses play a vital role in intracity and intercity transportations. For accommodating multi-source passenger traffic with different travel demand, while optimizing the energy consumption, we propose a multi-cycle train timetable optimization model and a decomposition algorithm. A periodized spatial-temporal network that can support the integrated optimization of passenger service satisfaction and energy consumption considering multi-cycles is studied as the basis of the modeling. Based on this, an integrated optimization model taking the planning of the train spatial-temporal path, cycle length and active lines as variables is proposed. Then, for solving the issues caused by the complex relationships among the cycle length, line and train spatial-temporal path in large-scale cases, a hybrid heuristic Lagrangian decomposition method is investigated. Numerical experiments under different passenger flow demand scenarios are performed. The results show that the more fluctuating the passenger flow is, the more obvious the advantage of a multi-cycle timetable is. For the scenario with two passenger flow peaks, compared to a single-cycle timetable, the demand satisfaction ratio of the multi-cycle timetable is 4.44% higher and the train vacancy rate is 11.49% lower. A multi-cycle timetable also saves 3.24 h running time and 15,553.6 kwh energy consumption compared to a single-cycle timetable. Large-scale real cases show that this advantage still exists in practice. Full article

Classification of airborne light detection and ranging (LiDAR) point cloud is still challenging due to the irregular point cloud distribution, relatively low point density, and the complex urban scenes being observed. The availability of multispectral LiDAR systems allows for acquiring data at different wavelengths with a variety of spectral information from land objects. In this research, a rule-based point classification method of three levels for multispectral airborne LiDAR data covering urban areas is presented. The first level includes ground filtering, which attempts to distinguish aboveground from ground points. The second level aims to divide the aboveground and ground points into buildings, trees, roads, or grass using three spectral indices, namely normalized difference feature indices (NDFIs). A multivariate Gaussian decomposition is then used to divide the NDFIs’ histograms into the aforementioned four classes. The third level aims to label more classes based on their spectral information such as power lines, types of trees, and swimming pools. Two data subsets were tested, which represent different complexity of urban scenes in Oshawa, Ontario, Canada. It is shown that the proposed method achieved an overall accuracy up to 93%, which is increased to over 98% by considering the spatial coherence of the point cloud. Full article

The present study was aimed at comparing vertical and horizontal surface displacements derived from the Cosmo-SkyMED, TerraSAR-X and Sentinel-1 satellite missions for the detection of oil extraction-induced subsidence in the Tengiz oilfield during 2018–2021. The vertical and horizontal surface displacements were derived using the 2D decomposition of line-of-sight measurements from three satellite missions. Since the TerraSAR-X mission was only available from an ascending track, it was successfully decomposed by combining it with the Cosmo-SkyMED descending track. Vertical displacement velocities derived from 2D Decomposition showed a good agreement in similar ground motion patterns and an average regression coefficient of 0.98. The maximum average vertical subsidence obtained from the three satellite missions was observed to be −57 mm/year. Higher variations and deviations were observed for horizontal displacement velocities in terms of similar ground motion patterns and an average regression coefficient of 0.80. Fifteen wells and three facilities were observed to be located within the subsidence range between −55.6 mm/year and −42 mm/year. The spatial analyses in the present studies allowed us to suspect that the subsidence processes occurring in the Tengiz oilfield are controlled not solely by oil production activities since it was clearly observed from the detected horizontal movements. The natural tectonic factors related to two seismic faults crossing the oilfield, and terrain characteristics forming water flow towards the detected subsidence hotspot, should also be considered as ground deformation accelerating factors. The novelty of the present research for Kazakhstan’s Tengiz oilfield is based on the cross-validation of vertical and horizontal surface displacement measurements derived from three radar satellite missions, 2D Decomposition of Cosmo-SkyMED descending and TerraSAR-X ascending line-of-sight measurements and spatial analysis of man-made and natural factors triggering subsidence processes. Full article