Search Results (1,463)

As a critical component of electric railways, catenary systems are prone to cracks, loosening, corrosion, and wear under long-term vibration, fatigue, and environmental erosion. However, ambiguous fault boundaries, large inter-component variations, and tiny defects severely hinder reliable anomaly detection and condition assessment. To address these challenges, this paper proposes a vision-based intelligent fault assessment framework for railway catenary components based on a novel Railway Diffusion-based Anomaly Detection (Rail-DiffAD) model. Specifically, Rail-DiffAD combines residual feature mapping, a Multi-scale Partial Convolutional Spatial-Channel Attention (MPSCA) module with Log-Barrier Bi-directional Constraint Loss (LBBCL), and conditional diffusion-based distribution modeling to achieve robust anomaly localization in complex industrial scenarios. Furthermore, a severity-aware diffusion representation is introduced to characterize structural defect evolution, and a multi-physics fault assessment framework integrating mechanical response, corrosion evolution, and stress concentration analysis is established for quantitative fault grading and maintenance decision-making. Experiments on a real catenary dataset covering 10 component categories demonstrate that the proposed framework achieves a 0.953 image-level AUROC and a 0.957 pixel-level AUROC, outperforming existing methods while maintaining strong cross-component generalization and providing quantitative fault grading support for intelligent railway catenary maintenance. Full article

Photosynthetic water oxidation is catalyzed by the Mn₄CaO₅ oxygen-evolving complex (OEC) of photosystem II (PSII), where hydrogen-bonding and ion-binding networks regulate proton transfer, substrate-water delivery, and S-state advancement. Acetate binding inhibits oxygen evolution, competes with chloride, and stabilizes the $S=5/2$ spin isomer of the S₂ state, but its donor-side binding site remains unresolved. Here, we combine EPR spectroscopy, pH-dependent oxygen-evolution measurements, mutagenesis, and QM/MM calculations to support a donor-side acetate-binding model and determine how acetate perturbs the OEC environment. Acetate increases the ratio of the $g=4.1$ to $g=2$ S₂-state EPR signals in spinach PSII membranes and cyanobacterial PSII core complexes, with stronger stabilization persisting to higher pH in spinach PSII. The D1-N87A Synechocystis PSII variant exhibits spinach-like acetate sensitivity and pH-dependent oxygen-evolution behavior, with an effective acidic $p{K}_a$ of approximately 5.3, versus 4.2 for wild-type cyanobacterial PSII, implicating long-range perturbations of the narrow-channel hydrogen-bonding network. QM/MM calculations support acetate binding near the D1-D61/W1 region, where the acetate-bound $S=5/2$ isomer is only 1.0 kcal mol⁻¹ higher in free energy than the $S=1/2$ isomer, consistent with the observed spin-isomer equilibrium shift. These results reveal how acetate perturbs proton-transfer and chloride-binding processes in PSII. Full article

Automatic Identification System (AIS)-based vessel trajectory prediction is essential for maritime traffic management and navigation safety. Existing deep learning methods typically model vessel motion within a unified temporal representation space, which may entangle long-term navigation trends with local maneuvering behaviors. However, vessel trajectories inherently exhibit heterogeneous dynamics, including steady route evolution and non-stationary maneuver perturbations. To address this issue, this paper proposes MD-EDTCNFormer, a motion-decoupled dual-stream framework for vessel trajectory prediction. A Global Navigation Dynamics Encoder is designed to capture dominant route-level temporal evolution from raw AIS sequences, while a Residual Maneuver Dynamics Encoder explicitly models maneuver-related local perturbations through state transition residual representations. In addition, a state-adaptive motion aggregation mechanism is introduced to dynamically balance global navigation dependencies and local maneuver-aware dynamics under different navigation states. Depthwise separable temporal convolution and efficient channel attention are further integrated to suppress redundant temporal-channel coupling and emphasize dynamically dominant motion cues. Experiments on a real-world AIS dataset from the Zhoushan coastal area demonstrate the effectiveness of the proposed framework under coastal traffic conditions, and show improvements in prediction accuracy and trajectory stability compared with representative baseline methods. Full article

Suspended sediment concentration (SSC) is a critical proxy for coastal water quality, geomorphological evolution, and biogeochemical cycles. In shallow macro-tidal embayments like Sanmen Bay (SMB), China, surface SSC exhibits highly dynamic spatiotemporal variations driven by intense, multi-scale tidal forcing. Using Sentinel-2 MSI imagery processed with the ACOLITE Dark Spectrum Fitting (DSF) algorithm, this study reconstructs the spatial distribution of surface SSC across the embayment. We then introduce the normalized Suspended Sediment Concentration Asymmetry Index ($A_{ssc}$) to quantitatively diagnose asymmetrical sediment responses across spring–neap and flood–ebb cycles. The results reveal a spatially divergent, dual-control mechanism governing sediment transport across the embayment’s hydro-geomorphic gradients. Quantitative trend-surface fittings and stratified regressions demonstrate that net sediment transport in deep bedrock channels is primarily governed by tidal pumping. Conversely, sediment dynamics on intertidal mudflats and shallow subtidal shoals are modulated by geomorphic resistance, exhibiting high morphodynamic sensitivity to minute water depth variations. By bridging process-based estuarine tidal theory with discrete satellite observations, this reproducible framework transforms multi-temporal remote sensing snapshots into spatially continuous diagnostics, providing a practical decision-support paradigm for coastal engineering and ecosystem management in dynamically analogous macro-tidal environments. Full article

In this study, pure hydroxyapatite (HAp) was successfully produced by using eggshells. The eggshells were collected locally and calcined to get CaO from them. The CaO powder was reacted with diammonium hydrogen phosphate in a mechanochemical method using attritor milling. A portion of the synthesized samples was subjected to a second calcination process at 900 °C to investigate the thermal effects on the material. The structures of the samples were investigated by scanning electron microscopy, X-ray diffraction, and infrared spectroscopy. The as-prepared HAp appeared to be nanocrystalline with low-intensity reflections, which transformed into a highly crystalline hexagonal phase after heat treatment, as revealed by XRD analysis. Quantitative analysis revealed the thermal evolution of the secondary Ca(OH)₂ phase, due to the thermal decomposition into CaO without causing HAp decomposition into tricalcium phosphates. FTIR analysis showed characteristic phosphate bands for both samples, but the calcined sample displayed sharper peaks and a clear loss of residual water and carbonates. SEM observations also highlighted the major morphological transformation. The highly aggregated as-prepared nanoparticles formed larger, well-defined grains. Notably, the calcined sample also exhibited a rough, textured surface with a macroporous network with interconnected channels. EDS analysis confirmed a Ca-P-O-rich composition, where the elevated Ca/P ratio (Ca/P = 2.28) suggested the presence of secondary calcium-rich phases. These structural, chemical, and morphological characteristics suggest that eggshell-derived HAp, with or without a second heat treatment, has high potential and may be optimized for different applications in bone tissue engineering. However, biological performance was not evaluated in this study. Full article

We study the unsteady mechanical response of an incompressible viscoelastic polymeric fluid in a flat channel, governed by the Vinogradov–Pokrovskii rheological model. The motion arises from an electrohydrodynamic reduction of Poiseuille type, after which the mechanical subsystem decouples from the electric field; the velocity then depends on time and on the transverse coordinate only. Treating the rheological parameter as small, we reduce the governing system in the leading-order approximation to a non-autonomous second-order evolution equation whose stiffness coefficient relaxes exponentially in time, so that the nonstationarity is driven by the internal relaxation of the normal stress rather than by an external force. For spatially homogeneous initial normal stress, we diagonalize the Galerkin system in the sine basis and obtain an explicit modal representation in which each mode satisfies a Bessel equation whose order depends on the mode number. This yields a critical index that splits the modes into three regimes—real order, zero order, and purely imaginary order—a structure absent from the classical UCM and Oldroyd-B solutions. Using the explicit representation, we prove convergence of the modal series and show that the solution decays in the long-time limit, so that the rest state is asymptotically stable in the natural energy phase space. The analytical solution is confirmed numerically. Full article

Ensuring the sustainability of deep coal mining requires a comprehensive understanding of hydrogeological risks, particularly fault-induced water inrush, which threatens human safety, depletes freshwater resources, and causes irreversible ecological damage. This study addresses the sustainability gap in managing heterogeneous fault fracture zones by conducting coupled loading–seepage experiments on representative limestone, sandstone, coal, and coal–rock mixtures from the Zhaogu No. 2 Mine. Results demonstrate that seepage behavior follows the Forchheimer non-linear regime (E = 0.2–0.95), deviating significantly from Darcy’s law. We quantified that effective stress induces particle crushing and rearrangement, leading to a drastic porosity reduction (up to 97.52% in coal). Crucially, lithology dictates permeability evolution: coal and mixtures exhibit exponential decay, whereas sandstone and limestone follow quadratic functions. The fractal dimension of particles correlates negatively with permeability (R² > 0.95). These findings provide a quantitative framework for predicting water inrush channels, enabling proactive strategies to prevent catastrophic groundwater loss and ensure the long-term viability of mining operations. This research supports SDG 6 (Clean Water) and SDG 12 (Responsible Consumption and Production) by offering scientific guidance for balancing resource extraction with hydrogeological integrity. Full article

Satellites are critical components of modern space information systems. During long-term on-orbit operation, satellite telemetry often exhibits multi-scale temporal dynamics, heterogeneous channel behavior, and time-varying inter-variable dependencies, which pose substantial challenges to anomaly detection. Existing methods remain limited in adaptively representing anomaly patterns across temporal scales, jointly modeling temporal evolution and dynamic asymmetric channel dependencies, and preventing over-generalized reconstruction of anomalous inputs. To address these limitations, this paper proposes MSGMamba, a multi-scale graph state space model for satellite telemetry anomaly detection. First, a multi-scale temporal patch decomposition and gated fusion mechanism partitions telemetry sequences into patches of different granularities and adaptively integrates their representations at each temporal position, enabling the joint modeling of short-term transients and relatively slow-varying patterns. Second, a graph–sequence alternating propagation mechanism couples selective state space updates with dynamic graph interaction. At each temporal patch, a directed and asymmetric dependency graph with self-connection priors is generated from the temporally encoded features, allowing temporal evolution and time-varying cross-channel dependencies to be modeled within a unified framework. Third, an orthogonal memory-augmented anomaly discrimination mechanism introduces an orthogonality-constrained memory bank to reduce redundancy among nominal prototypes and constrain the reconstruction space. A dual-pathway anomaly score further combines signal-space reconstruction error with encoder–memory discrepancy to improve the separability of nominal and anomalous samples. Experiments on the SMAP, MSL, and EIRSAT-1 datasets show that MSGMamba outperforms representative baseline methods in terms of average PA-F1 and AFF-F1. Full article

Channel time dispersion causes inter-symbol interference (ISI) which is mitigated by the Orthogonal Frequency Division Multiplexing (OFDM) symbol cyclic prefix (CP). However, CP is an overhead which reduces spectral efficiency and increases energy per delivered bit. In Long Term Evolution (LTE), the widely deployed normal CP corresponds to a fixed overhead of about 7% (4.69 $\mathsf{\mu }$s), which is conservative for many practical environments and is equivalent to path-length variations on the order of 1.4 km. This paper address CP sizing from an energy-efficiency viewpoint for OFDM-based 4G/5G radio networks. We combine an analytical model based on delay spread statistics with link-level simulations to determine a reduced CP that remains effective for ISI mitigation across indoor-to-urban scenarios. Optimal CP intervals are derived for the LTE M-ary Quadrature Amplitude Modulation formats (4-QAM, 16-QAM, and 64-QAM) and validated using standard delay-dispersive mobile radio channels. Results indicate that CP can be reduced by 70–95% relative to the LTE normal CP in typical deployments, yielding measurable net-throughput improvements and energy savings without compromising error-rate targets, supporting greener wireless communications. Full article

Conventional Pancharatnam–Berry (PB) phase metasurfaces operate within the two-dimensional SU(2) polarization space of the electric field, fundamentally limiting holographic multiplexing to two independent channels. Here, we propose and numerically demonstrate a four-channel holographic metasurface exploiting the recently discovered Riemann–Silberstein (RS) geometric phase arising from SU(4) polarization evolution in the full electromagnetic field space. The RS vector Ψ = E + icB unifies electric and magnetic fields into a four-dimensional polarization state space. By engineering bianisotropic Huygens meta-atoms with independently controllable electric-dipole orientation angle α and magnetic-dipole orientation angle ψ, four geometric-phase channels—labeled by the joint spin eigenstates |σ,κ⟩∈{|+,+⟩,|+,−⟩,|−,+⟩,|−,−⟩}—are simultaneously addressed from a single aperture. We develop the complete SU(4) transfer-matrix formalism and optimize four quasi-independent phase profiles using an extended Gerchberg–Saxton algorithm with a three-parameter (α,ψ,h) design library, where the pillar height h serves as a third degree of freedom to overcome the linear phase constraint inherent to the two-angle parameterization. Numerical simulations at 0.8 THz demonstrate simultaneous projection of four independent holographic images with mean diffraction efficiency 60.4% and inter-channel crosstalk below 3.2%, doubling the information capacity of conventional dual-channel PB holograms. An intrinsic ~24× common-mode noise suppression arising from electromagnetic duality symmetry is also demonstrated. This work establishes a direct link between fundamental electromagnetic symmetry and high-capacity wavefront engineering. Full article

The advancement of natural language processing (NLP), transformer architectures, and large language models (LLMs) has reshaped phishing detection research within business and enterprise environments. However, the structural evolution, thematic transitions, and collaboration patterns of this domain remain insufficiently mapped. This study conducts a bibliometric analysis of Scopus-indexed publications from 2020 to 2025. Using VOSviewer and Bibliometrix (RStudio), we perform performance analysis and science mapping, including co-authorship, co-citation, bibliographic coupling, and keyword co-occurrence analyses. The findings reveal a clear methodological shift from traditional machine learning toward deep learning and transformer-based architectures, particularly after 2023. Two dominant research clusters emerge: conventional feature-based phishing detection and NLP-driven AI security approaches. While large language models and multi-channel phishing detection are gaining prominence, enterprise-level implementation and interdisciplinary integration remain limited. This study identifies emerging trends, collaboration gaps, and underexplored themes, providing directions for future research and practical cybersecurity development. Full article

The anuran atlas represents one of the most structurally simplified cervical systems among tetrapods, consisting of a single vertebra that must simultaneously support the head, permit mobility, and withstand mechanical loads generated during locomotion and feeding. This unique configuration provides a compelling framework for investigating how structural constraint, allometry, and ecology interact to shape morphological evolution. Here, we examine atlas shape diversification across Hyloidea using geometric morphometrics and phylogenetic comparative methods on 421 specimens representing 133 species. We quantified shape variations in dorsal and ventral views and tested the relative contributions of body size, phylogenetic history, microhabitat, and locomotor mode to atlas morphology. Atlas shape exhibited significant phylogenetic signals and was predominantly structured by allometric scaling, with the atlas size (centroid size) explaining a significant proportion of variation in both anatomical views, particularly ventrally. Morphological differences were concentrated in atlas width and relative proportions, indicating that diversification occurs primarily through size-dependent remodeling rather than through major structural reorganization. In contrast, ecological variables explained little independent variation in atlas shape, although microhabitat modulated allometric trajectories in dorsal and ventral views. Together, these results indicate that atlas evolution in hyloid frogs is governed chiefly by size-related biomechanical demands operating within a phylogenetically structured and developmentally constrained system. More broadly, our findings suggest that extreme cervical simplification channels morphological diversification toward allometric modification, limiting the extent to which ecological specialization can drive anatomical divergence. Full article

The transition process from synchronous condenser pump (SCP) mode to pumping mode determines the response rapidity of the startup procedure and operational stability of pump-turbines; however, the complex gas–liquid interaction and transient hydraulic characteristics during this process remain insufficiently understood. To address this, this study develops a numerical framework for the SCP-to-pumping transition process, incorporating the full-passage system, a multiscale mesh strategy for coupling mainstream and clearance flow regions, and a gas–liquid two-phase flow model based on the Volume of Fluid (VOF) method. The reliability of the numerical model is verified through comparison with model experiments, demonstrating good agreement between simulations and experimental data. Based on the validated model, the transient evolution of hydraulic forces, pressure pulsations, and internal flow structures is systematically analyzed. Axial force analysis reveals a significant internal equilibrium; the crown bears a maximum instantaneous fluctuation of approximately 2800 kN. Conversely, the radial force is primarily dominated by blade hydraulic thrust (1294 kN), showing distinct anisotropic behavior. The runner blade channels and the upper draft tube region are identified as critical areas with intense pressure fluctuations, with peak-to-peak pressure amplitudes reaching 45~48 m and 54 m head, respectively. Furthermore, reducing the duration of the exhaust process constitutes the main strategy for accelerating the transition and mitigating prolonged high-amplitude force and pressure fluctuations. The findings provide new insights into the transient hydraulic mechanisms of SCP-to-pumping transitions and offer guidance for optimizing transition control strategies in pumped-storage units. Full article

To reveal the influence of water accumulation in open pits on the stability of boundary coal–rock pillars, this study investigates a boundary coal–rock pillar between an underground coal mine and an adjacent open pit in western China. Coal–rock physical property tests, hydrochemical analysis, permeability tests, and theoretical calculations of water-resisting coal–rock pillars were conducted to examine seepage channel formation, physical property changes, and stability evolution under long-term water accumulation. The results show that the mechanical strength of coal and rock specimens decreases under the saturated state. The uniaxial compressive strength of rock specimens decreases by 8.75–50.64%, while that of No.2⁻² and No.3⁻¹ coal specimens decreases by 17.72% and 25.01%, respectively. The tensile strength decreases by 24.59–59.11%, and the shear strength decreases by 4.36–45.96%. The hydraulic conductivity of intact specimens is mostly 10⁻⁴~10⁻³ m/d, whereas that of fractured specimens increases to 10⁻³~10⁻² m/d. The calculated width of water-resisting coal pillars increases by 19.7~21.9% under long-term water accumulation. Long-term water accumulation in the open pit changes the external hydraulic boundary of the boundary coal–rock pillar, allowing water to migrate inward along bedding planes, joints, primary fractures, mining-induced fractures, and coal seam pores. This process promotes the connection of pre-existing pore–fracture structures and seepage channel formation, weakens particle cementation and structural-plane shear resistance, and reduces the structural integrity, bearing capacity, and water-resisting capacity of the coal–rock pillar. Therefore, the stability deterioration of boundary coal–rock pillars is a continuous process involving channel formation, sustained seepage, strength degradation, enhanced pore–fracture connectivity, permeability enhancement, and further stability reduction. Full article

China hosts abundant coal-rock gas (CRG) resources, which have become a critical unconventional natural gas contributor to national reserve expansion and production increment. Supercritical carbon dioxide (ScCO₂) fracturing is recognized as a green and efficient stimulation technology, exhibiting great potential for high-efficiency CRG exploitation. To clarify the effects and intrinsic mechanisms of ScCO₂ treatment on coal fracture initiation, propagation, and CRG recovery enhancement, true triaxial fracturing and CO₂-CH₄ displacement experiments were performed in combination with multiple microscopic characterization methods, including X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), and Scanning electron microscopy (SEM). The multi-scale experimental investigation systematically revealed the fracture development mechanism, permeability variation characteristics, and microstructural evolution of coal reservoirs under ScCO₂ interactions. The results indicate that ScCO₂ fracturing significantly lowers the coal fracture initiation threshold compared with conventional hydraulic fracturing, with the breakdown pressure reduced by 26.2% and the initiation time shortened by 37.5%. Such advantages facilitate coal fracture activation and the development of complex fracture networks. Long-term ScCO₂ soaking induces the dissolution of inorganic minerals (e.g., calcite, plagioclase, and clay minerals) and the extraction of inherent organic matter within coal matrices. The coupled hydro-chemical reactions reconstruct the coal pore structure, enlarge pore throats, and improve reservoir permeability, achieving a maximum permeability enhancement of approximately 1.6 times. Meanwhile, ScCO₂ displacement yields a prominent CRG recovery performance, with an ultimate gas recovery factor up to 93.85%. The CRG enhancement mechanism of ScCO₂ fracturing is comprehensively attributed to three core coupled effects. First, ScCO₂ dynamic fracturing generates intricate fracture networks, which greatly optimize reservoir seepage channels and flow space. Second, the ScCO₂–formation water–coal interaction modifies coal physical properties via mineral dissolution and organic matter extraction, thereby improving reservoir permeability. Third, the preferential adsorption of CO₂ over CH₄ triggers effective competitive adsorption and gas displacement, further promoting adsorbed methane desorption and elevating CRG recovery efficiency. This study provides a solid theoretical foundation for the field application of ScCO₂ fracturing technology and offers valuable insights into the green, efficient, and sustainable development of deep coal-rock gas resources. Full article