For Poisson problems with periodic boundary conditions, the use of the traditional SOR solution algorithm does not permit the rapid convergence of the Poisson solver. To address this limitation, a novel multigrid iterative Poisson solver (Poisson-SOR-MG) based on finite difference methods was developed, leveraging multigrid acceleration techniques to overcome the drawbacks of SOR. Additionally, a 3D Fourier spectral transform algorithm was designed by coupling 1D Fast Fourier Transform (FFT) with 3D parallel communication algorithms, eliminating cumbersome transpose techniques. Building on this, a standard 2π-periodic Poisson-Fourier solver was developed and validated, achieving spectral accuracy. However, the standard 2π-periodic Poisson-Fourier solver cannot be directly applied to general engineering problems. To resolve this, theoretical analysis based on coordinate stretching transformations was conducted, leading to the further development and validation of a generalized arbitrary-periodic Poisson-Fourier solver.

To address the degradation in path tracking accuracy caused by conflicts between speed maintenance and turning capability in differential-drive robots operating in complex environments, a combined control strategy integrating active speed adjustment and adaptive-preview Linear Model Predictive Control (AP-LMPC) is proposed. Based on the kinematic model of the robot, a coupling constraint equation between path curvature and feasible longitudinal velocity is first derived, and an active speed adjustment strategy tailored to curvature features is designed. Then, a mapping between driving speed and optimal preview distance is constructed to enable the adaptive-preview mechanism. These components are integrated into an AP-LMPC-based control system to enable adaptive path tracking with active speed regulation. Experimental results demonstrate that the proposed strategy can significantly reduce displacement and heading errors. Specifically, the peak displacement and heading errors are maintained within 0.05 m and 0.09 rad under complex S-shaped and double-lane-change trajectories. Compared with fixed-preview LMPC (FP-LMPC) and nonlinear MPC (NMPC), the displacement error is reduced by over 68% and 48%, respectively.

his paper proposes a novel medical image segmentation framework — Anatomy-Guided Implicit Representation Attention Network (AIRA-Net) — designed to address the challenges posed by the complex and variable anatomical structures of the nasal cavity and its subregions. AIRA-Net leverages an implicit neural representation to extract global geometric features and employs a dedicated cross-attention module to effectively fuse multi-scale local and global features. Furthermore, a boundary-weighted loss function based on anatomical priors is integrated to enhance segmentation precision in regions with sparse features, particularly at the cavity boundaries. Extensive experiments on a dataset comprising 128 3D head CT volumes demonstrate that AIRA-Net achieves a DSC of 91.66% in nasal cavity segmentation, surpassing the second-best method nnU-Net by 4.5 percentage points. Additionally, AIRA-Net attains a HD95 of 10.75 mm, which is 2.82 mm lower than that of the second-best method U_a-Net.

In order to improve the reliable operation capability of a combined heat and power microgrid (CHP-MG) in a harsh environment, a fuzzy economic dispatching strategy of CHP-MG considering the double uncertainty of source and load is proposed based on the typical scenarios of wind, light, electricity and heat. Firstly, a combination method of Latin Hypercube Sampling (LHS) and K-means clustering is used to generate typical scenarios of predicted values of wind, light, electricity and heat. Secondly, triangular or trapezoid fuzzy parameters are used to represent the uncertainty of wind, light, electricity and heat prediction errors, and the certainty constraints of CHP-MG are transformed into fuzzy chance constraints based on credibility theory. Thirdly, according to the clear equivalence class of fuzzy chance constraints, the chance constraints with triangular or trapezoidal fuzzy parameters are clarified, and the corresponding deterministic mixed integer programming model is formed. Finally, the rationality of the proposed model and method is verified by Matlab/Cplex simulation, which provides a reliable economic scheduling scheme for CHP-MG. 

Based on vertically observed spectrum data from ground-based Ka- and W-band dual-frequency radars, this study employs an optimal estimation method to retrieve the raindrop size distribution (DSD) and aerodynamic parameters of a stratiform precipitation event on July 11, 2024. The results show that: 1) The spectrum data enable accurate retrieval of the absolute number concentration of DSDs and associated aerodynamic parameters. 2) The retrieved DSDs for individual diameter classes exhibited good agreement with validation data from a ground-based disdrometer. 3) Distinct small-scale fluctuations within the precipitation and size-sorting phenomena during raindrop descent were observed, highlighting the existence of complex dynamic processes even in stratiform precipitation systems. 4) By tracking raindrop trajectories, significant evaporation was identified during periods of light rainfall.

To accurately assess the offshore wind power development potential in the southeastern coastal provinces of China, this study employs a farm-scale analytical approach, combining historical wind speed data, marine geographical information, and wind turbine layout optimization strategies. A suitability evaluation framework is established, incorporating factors such as wind speed, wave height, water depth, and protected area restrictions, along with a standardized wind turbine spacing layout scheme. Additionally, a Gaussian wake model is used to quantify wake effects at the wind farm level. The results indicate that the offshore wind potential in the five southeastern provinces can meet 77% of the regional electricity demand. Optimizing wind turbine row configurations and spacing can balance wake losses and overall power generation potential. The application of deep-sea floating wind turbines and large-capacity turbines will significantly improve resource utilization. These findings are of great significance for rational planning of regional wind power development and the optimization of construction decisions, providing a pathway for the low-carbon transformation of regional energy structures.

Taking shallow-water ocean-bottom seismometer (OBS) stations near the US West Coast as an example, using manually identified frequency-band results as a benchmark, this study compares the earthquake arrival-time picking performance of the Short-Term Average/Long-Term Average (STA/LTA) method and two machine learning models developed for OBS data (Blue-PhaseNet and Blue-EQTransformer). The results show that 1) Both Blue-PhaseNet and Blue-EQTransformer exhibit poor detection capability, with accuracies of 33.33% and 14.81%, respectively, which are 51.85% lower in accuracy than the traditional STA/LTA method. This is likely because the models have not been optimized for local datasets, resulting in insufficient generalization. Furthermore, this study uses large-magnitude earthquake data with high noise in shallow-water environments, whereas the training datasets consist predominantly of microseismic events from deep-water areas, leading to significant differences in data characteristics. 2) After denoising using hydrophone pressure records, the arrival time picking accuracy of the STA/LTA method improves significantly to 96.30%, and more seismic events are identified (29 events, compared with 27 in the raw data). Therefore, Blue-PhaseNet and Blue-EQTransformer cannot be directly applied to shallow-water observations. Denoising to improve the signal-to-noise ratio followed by STA/LTA processing represents a feasible automated approach for OBS earthquake arrival-time identification.

When a submarine earthquake occurs, pressure sensors deployed on the seafloor can record the pressure variations induced by the earthquake. Currently there is no quantitative application for utilizing earthquake-induced pressure variations. In this study, SPECFEM3D program was employed to construct a numerical model of a submarine earthquake, and simulate the rupture process and the associated seafloor pressure variations. The spatial distribution characteristics of the seafloor pressure signals were analyzed. The results indicate that at stations far from the source region, the low-frequency pressure p induced by the earthquake and vertical acceleration a of the seafloor satisfies the theoretical relationship p = ρha. In areas near the source, this theoretical relationship no longer holds, and the transition boundary between these two regimes is related to the earthquake source depth. If other source parameters are the same, such as magnitude and rake, the source depth determines the permanent seafloor deformation, which provides valuable insights for assessing tsunami threat potential. Additionally, it is found that Rayleigh waves can be recorded outside a certain range of the source region, and the pressure variations caused by Rayleigh waves exhibit an amplification effect compared with seismic body waves. The locations of stations where Rayleigh wave amplification occurs are also related to earthquake source depth, providing useful insights for tsunami early warning.

The Chang-7 Member of the Yanchang Formation in the south-central Ordos Basin was selected as the research object. Based on the measured data from 41 wells, the Kriging interpolation and Partial Least Squares Regression (PLSR) were adopted to systematically analyze the main controlling factors of pore development under different geological conditions. The results show that when the Total Organic Carbon (TOC) content is less than 6%, the samples are mainly distributed at the lake basin margin, and the total content of the main brittle minerals (quartz and feldspar) exhibits a significant negative correlation with TOC. When the TOC content exceeds 6%, the samples are mainly distributed in the central lake basin, and there is no obvious correlation between the total quartz and feldspar content and TOC. There are remarkable differences in the main controlling factors of pore development in different regions of the lake basin around the TOC critical point (6%). Pore development in the central lake basin is mainly controlled by TOC and pyrite content, where the negative impact of TOC on pore development is manifested as pore filling by solid bitumen. In contrast, pore development at the lake basin margin is mainly dominated by the content of carbonate minerals and chlorite: the cementation of carbonate minerals damages reservoir pores, while chlorite protects reservoir pores by weakening cementation and enhancing the compaction resistance of rocks.

Aiming at the lack of quantitative interpretation of the operational scale of the maximum effective moment criterion, this study is carried out based on an elastoplastic beam model. First, using the analytical solution for the normal stress distribution in a homogeneous elastoplastic beam under pure bending, the unit length of the criterion is derived to be approximately equal to the beam height. Subsequently, the bending and yielding process of double- and triple-layer elastoplastic beams are simulated using COMSOL multiphysics software. The results confirm that the above theoretical relationship is also valid for laminated beams (representing sedimentary strata). Finally, by analyzing the geometric scaling relationship of the kink band-like plastic deformation zones in beams and combining with the measurement of kink band width in field outcrops, the thickness of strata governed by this criterion is quantitatively estimated, thereby achieving the quantification of the unit length in the maximum effective moment criterion. The results provide a theoretical basis for reconstructing stress-strain fields and analyzing deformation processes in related geological structures.

By comprehensive analysis of core, well logging, outcrop, and thin sections, this study identifies microfacies and microfacies associations within the Wusonggeer Formation in the central and northern Tarim Basin, establishes a sequence architecture, and analyzes the depositional evolution and controlling factors of the carbonate platform. The results show that 15 types of microfacies and 8 types of microfacies associations are identified in the Wusonggeer Formation in the study area and the depositional facies include evaporated platform (saline lagoon and gypsum dolomite flat), restricted platform (muddy dolomite flat, dolomite flat and intra-platform shoal), open platform (grain shoal and lime-dolomite flat), and platform margin reef. The Wusonggeer Formation can be divided into one composite sequence and three third-order sequences, corresponding to three evolutionary stages: ramp carbonate platform, weak-restricted carbonate platform, and weak-rimmed evaporative carbonate platform. The sequence architecture and depositional evolution of the carbonate platform were jointly controlled by the paleogeomorphic framework inherited from the Xiaoerbulake period, global sea-level fluctuations, relatively arid-hot climatic conditions, and elevated seawater temperatures.

Through permanent plot-based ecological monitoring of five representative mangrove communities (Kandelia obovata-Aegiceras corniculatum community, K. obovata community, K. obovata-Avicennia marina community, A. marina community, and artificial forest) in the Mangrove Nature Reserve of Shenzhen Bay, combined with measurements of leaf functional traits and sediment physicochemical parameters, this study elucidates the population distribution pattern, asexual reproduction dynamics and ecological strategies of the understory A. ilicifolius population under the background of terrestrialization. The results show that A. ilicifolius has become the dominant understory species (importance value: 85.38%), with an aggregated distribution pattern (K<0) and a uniform distribution (PAI=1, C<1). The population density of mature individuals showes slow expansion(1991–2011), rapid growth (2011–2019: 0.03→16.84±13.11 plants/m²), and stabilization by 2023 (17.26±7.03 plants/m²). Clonal reproduction is one of the key strategies for the A. ilicifolius population to dispersal. A. ilicifolius exhibits stoloniferous clonal growth with guerrilla architecture, characterized by a mean spacer length (41.26±32.92 cm) and monthly elongation rate (1.29±0.66 cm/month), reflecting an expansion-growth (escape strategy) under low-light understory habitats. High-sedimentation zones trigger an ecological strategy shift from CS to C or CR, manifested by increased canopy height and long-spacer stolon extension. This study provides early-warning data for mangrove ecological risks.

 To gain an in-depth understanding of the groundwater environmental quality and its dynamic changes in the Daqing River Basin, the detection and distribution of 20 heavy metals and 40 organic micropollutants in the groundwater of the basin were investigated. The results indicate that the overall groundwater quality in Daqing River Basin is relatively good, with 77.19% of the monitoring sites meeting the Class III groundwater quality standard. However, heavy metals and emerging organic compounds still pose potential threats to regional water security. There were 10 heavy metals exceeding the standard, with manganese and iron showing the highest exceedance rates, with concentration ranges of ND–1421.00 and ND–42300.00 μg/L, respectively. The major excessive emerging organic substances were 1,2-dichloroethane and atrazine, with concentration ranges of ND–90.00 and ND–2.86 μg/L, respectively. The concentration ranges of total volatile organic compounds, total polycyclic aromatic hydrocarbons, and total pesticides were ND–90.00, ND–0.01 and ND–3.91 μg/L. Significant differences were observed in the concentrations of certain heavy metals (such as silver and cadmium) in groundwater between piedmont and plain regions, as well as notable variations in pesticide and polycyclic aromatic hydrocarbon concentrations across different aquifer types (unconfined and confined groundwater). Natural environmental conditions, including soil properties and mineral distribution, are the primary factors influencing the presence of heavy metals in groundwater, while agricultural activities and domestic wastewater discharge are the main sources of organic micropollutants. Overall, the groundwater in plain regions exhibits a higher suitability for drinking purposes compared with mountainous areas. The findings of this study reveal the evolutionary characteristics of groundwater environments in typical urban agglomerations in China and emphasize the importance of protecting groundwater quality in key water source areas. 

This study investigates the Baini River Basin using the MixSIAR model to quantify nitrate contributions from wastewater effluent (M&S), sewer leakage (SL), agriculture (AG), soil nitrogen (SN), and urban runoff (UR), with flux calculation used to verify model reliability. Results show that wastewater effluent is the dominant source (67.5%), followed by soil nitrogen (13.7%), agriculture (12.6%), sewer leakage (4.7%), and urban runoff (1.1%). Source contributions show spatiotemporal variations. In the wet season, wastewater effluent accounts for 54.0%, while agriculture and soil nitrogen contribute 18.3% and 19.5%, respectively. In the normal season, wastewater effluent rises to 61.8%, while agriculture and soil nitrogen decline. Spatially, the main channel and downstream tributaries are dominated by wastewater effluent (55.4% and 57.1%), whereas agricultural input rises at the watershed boundary (25.7%). Isotopic and dissolved oxygen data indicate limited denitrification in the basin, and wastewater effluent and untreated sewage leakage are the main sources of riverine nitrogen. Therefore, sewer network maintenance, stormwater–sewage separation, and sewage overflow control should be strengthened.

A visual analysis of air-sea CO₂ flux literature (1980–2023) was conducted based on the Web of Science database using CiteSpace and VOSviewer. Three phases were identified in publication trends, which can be divided into the initial stage, the rapid growth stage, and the stable growth stage. The United States, Germany, England, France, and China are leading contributors. Research direction transitioned from single-factor analyses on flux to the coupling influence of multiple factors, expanded from regional to global scales, and shifted toward applied studies. Key points included spatial distribution patterns, dynamic mechanisms, and responses to climate change and anthropogenic impacts. Emerging frontiers involved machine learning and multi-source remote sensing integration for modeling partial pressure of sea surface CO₂, flux estimation, and climate response quantification. Future priorities emphasize high-resolution observations, interdisciplinary data fusion, regional/coastal studies, and feedback mechanisms between climate change and marine carbon cycles, while strengthening interdisciplinary collaboration and international cooperation. This synthesis provides critical insights for global carbon cycle understanding, climate projections, and carbon mitigation strategies.

Based on water chemistry analysis, metagenomic techniques, and multivariate statistical analysis, this study systematically investigated the spatial distributions of nitrogen pollution, nitrogen metabolism genes, and bacterial communities, as well as their environmental drivers in Dianchi Lake. We found that the total dissolved nitrogen concentration in Caohai (4.09 mg/L) was significantly higher than that in Waihai (1.48 mg/L), with nitrate nitrogen (NO₃⁻-N) and dissolved organic nitrogen (DON) as the dominant forms, respectively. Nitrogen metabolism genes exhibited significant spatial heterogeneity, with higher relative abundances of dissimilatory nitrogen reduction and denitrification genes in Caohai, whereas genes related to assimilatory nitrogen reduction and ammonification were more dominant in Waihai. Nitrogen metabolism bacteria were mainly composed of Proteobacteria, Bacteroidota, and Cyanobacteria, with the toxin-producing cyanobacteria Planktothrix and Microcystis as the dominant genera. Mantel analysis and Spearman correlation analysis indicated that TDN, NO₃⁻-N, ammonium (NH₄⁺-N) and water temperature were the key environmental factors influencing nitrogen metabolism genes and bacteria. 

This study proposes a theoretical framework for the coordination between the transportation system and productive force layout. Based on multiple big data sources, it evaluates their coordination characteristics. The analysis reveals that China’s transportation system exhibits a low level of coordination with productive force layout in several aspects, including infrastructure construction, service volume, service benefits and service quality. In particular, the level is much lower in the northwestern, the southwestern and northeastern regions of China, but relatively higher in the eastern coastal regions and central regions (with mismatches remaining in some individual cities). The study also predicts transportation demand for 2030, and proposes coordination strategies between China’s transportation system and major productive force layout, namely “three belts and six zones, three types of multi-areas, four types of multi-networks, and five poles and nine axes”. The strategies aim to advance in-depth integration of transportation and productive forces across point, line, network and regional dimensions. These results contribute to policy-making for optimizing the national comprehensive three-dimensional transport network, shaping multi-center and networked territorial space, and building a new pattern of sea-land transportation corridors.

This study examined a cohort of 935 police officers in a city in Zhejiang Province using the short-form Depression Anxiety Stress Scales (DASS-21), the Work-Family Support Scale, and the Psychological Capital Questionnaire. Latent profile analysis (LPA) was employed to identify distinct patterns of work-family support among participants. We further investigated the associations between latent classes of work-family support and negative emotions, and explored the potential mediating role of psychological capital in the relationship. The results revealed that 1) LPA identified six subgroups of perceived work-family support (Entropy = 0.89, LMR p = 0.05, BLRT p < 0.001): low support (5.03%), moderate support (20.43%), moderately high support (43.00%), work-dominant support (5.24%), family-dominant support (7.81%), and high support (18.50%). 2) Higher levels of work-family support were significantly associated with lower levels of negative emotions (depression, anxiety, and stress). 3) Using the low-support group as the reference, psychological capital significantly mediated the relationship between work-family support and negative emotions.

A systematic review of the literature on the characteristics of plant phenology and its drivers in urban forests was conducted to reveal the impact of plant phenology on bird sound diversity under urbanization and to explore the ecological association therein. The relationship between plant phenology and the spatiotemporal patterns of bird sounds was analyzed to identify the mechanisms through which vegetation dynamics shape bird sound diversity in urban forests. The main findings were as follows. 1) Urban forest plant phenology directly or indirectly affects bird sound diversity by altering food resource dynamics, habitat characteristics and interspecific competition. 2) Urban forest birds adapt their phenotypic plasticity through vocal behaviors to cope with phenology-driven resource competition. Future studies on the effects of urban forest plant phenology on bird sound diversity should focus on seasonal variations. The application of emerging monitoring technologies and the construction of a composite phenology-acoustic monitoring network are expected to promote the in-depth analysis of the multidimensional mechanisms between plant phenology and biodiversity in urban forests. Multi-perspective and cross-disciplinary co-operation should be strengthened to address the complex challenges of biodiversity conservation during urbanization.