Search Results (63)

Existing CNN-based visual malware classification methods are often constrained by inductive bias mismatch: standard isotropic convolution kernels and global pooling operations neglect the inherent structural anisotropy of malware images, and these methods struggle to address the spatial rearrangement of code blocks caused by obfuscation, which we term the “Malware Picasso Problem”. To overcome these limitations, we propose AD-CapsFPN, an end-to-end framework representing a significant step toward spatial reasoning over texture memorization, with a synergistic “Rectification–Fusion–Inference” mechanism. Our approach rectifies anisotropic inductive biases in the feature extraction stage, dynamically aggregates cross-scale discriminative features in intermediate layers, injects row-aware spatial biases, and adopts a global pooling-free spatial routing strategy in the classification stage, effectively reconstructing logical associations between obfuscated and scattered code blocks. Experiments on the large-scale Fusion dataset and the obfuscated Androdex dataset demonstrate significant performance improvements: our method achieves a 16.22% boost in macro F1-score over the MobileNetV4 baseline on the Fusion dataset (reaching 97.98%), and hits 92.45% macro F1-score on the highly challenging Androdex-Set1, outperforming state-of-the-art methods such as MDC-RepNet (88.97%) and TAEfficientNet (88.15%). This work confirms that embedding malware domain priors into architecture design is the key to robust malware classification. Full article

Electroencephalography records brain electrical activity arising from synchronized synaptic activity of neurons in the cerebral cortex, as measured at the scalp surface. In this work, neural activity is modeled as an equivalent current dipole with arbitrary orientation located within the innermost conductive layer. To represent the head anatomy, the volume conductor is modeled as a central brain compartment enclosed by concentric spherical shells representing the cerebrospinal fluid (CSF), skull, and scalp, with different conductivity values. The present study incorporates anisotropic conductivity with distinct radial and tangential components within a multilayer spherical head model by extending existing analytical formulations. While analytical solutions for isotropic spherical models are well established, anisotropic formulations are typically addressed using numerical or approximate methods. By applying spherical harmonics to the Poisson equation in layered anisotropic media, analytical expressions are derived for the electric potential generated by dipole sources. The forward model is evaluated using electrode positions $\left(\theta ,\phi \right)$ defined according to the EEGLAB layout, for a representative configuration with a head radius of $9.2 \mathrm{c}\mathrm{m}$. Quantitative comparisons are performed using MAG and RDM metrics for homogeneous and inhomogeneous anisotropic conductivity models. The results indicate that conductivity anisotropy significantly influences both the magnitude and spatial distribution of scalp potentials, particularly due to attenuation and spatial smoothing effects introduced by the skull layer. The analytical expressions derived contribute to the theoretical study of EEG forward modeling in anisotropic layered media and may serve as reference solutions for the assessment of numerical formulations. Full article

Accurate prediction of natural gas dispersion from buried pipelines is critical for risk assessment and emergency response. However, conventional numerical simulations often simplify soil as a homogeneous isotropic porous medium, which deviates significantly from real-world conditions characterized by stratification, anisotropy, and spatial heterogeneity. This study systematically investigates the effects of these non-ideal soil characteristics on methane diffusion behavior using computational fluid dynamics (CFD). Four distinct soil models—a baseline homogeneous model, a layered model, an anisotropic model, and a spatially heterogeneous model—were constructed and compared under identical leakage scenarios. Key risk indicators, including First Danger Time (FDT), Farthest Danger Range (FDR), Ground Danger Range (GDR), and leakage mass flow rate, were quantitatively evaluated. Results indicate that soil layering enhances vertical migration and expands horizontal hazard ranges, reducing FDT by approximately 8%. Anisotropy introduces a pronounced directional dependence in gas migration, with horizontal-preferred permeability leading to severe underestimation of lateral risk by homogeneous assumptions. The spatially heterogeneous model exhibits reduced hazard ranges compared to the homogeneous case but accelerates early breakthrough. Comprehensive evaluation reveals that the homogeneous model systematically underestimates lateral diffusion distances and delays alarm times. This study provides a quantitative basis for selecting appropriate soil modeling strategies, emphasizing that incorporating soil heterogeneity is essential for reliable safety assessments of buried gas pipelines. Full article

Skin meshing is widely used to treat extensive burn injuries due to its cost-efficiency and capacity to cover large wound areas. As biomimetics focuses on deriving engineering principles from biological structure–function relationships, this review examines how to optimize skin-meshing expansion and investigates factors contributing to reported discrepancies between clinical and manufacturer-reported expansion ratios. The biology and mechanical behavior of skin layer are discussed, emphasizing the anisotropic properties govern by collagen fiber orientation associated with Langer’s lines in the dermis. The epidermis and hypodermis show isotropic properties and therefore have minimal influence on load-bearing capacity. Surveying 111 studies, the review evaluates which constitutive equations employed for skin modelling is suitable to replicate mechanical behavior of skin meshing undergoing large expansion. Elastic models fail to capture large expansion ratios. Viscoelastic and QLV are excluded due to negligible sliding of collagen fibers at slow strain rates and limited importance of hysteresis. Consequently, hyperelastic models are recognized as more suitable for predicting large deformations. Among these, the structural GOH model, which represents fiber dispersion through a probability-density function, demonstrates strong agreement with experimental data using few parameters; its damage extensions improve prediction of mesh tearing. Additionally, emerging auxetic mesh geometries with negative Poisson ratios are examined, highlighting their potential to achieve greater expansion when combined with suitable structural anisotropic constitutive models, e.g., GOH. Full article

The angular shape and breakage of particles for calcareous sand significantly influence its mechanical behavior and the safety of the engineering. Although previous studies have explored the impact of particle shape on the mechanical properties of calcareous sand, the effects of shape-induced stiffness anisotropy and particle breakage remain insufficiently investigated. This study employs the Yade open-source 3D discrete element platform to conduct a series of numerical simulations of isotropic compression and simple shear tests on calcareous sand, examining stiffness, deformation characteristics, microscopic behavior, anisotropic properties, and the influence of different particle breakage rates. The results reveal that particle shape-driven stiffness anisotropy in calcareous sand is obvious. The horizontal shear modulus is different from the vertical modulus by up to 15% under confining pressures of 50 kPa to 1200 kPa. Irregularly shaped particles tend to align in a layered fabric under gravitational deposition, resulting in spatial anisotropy in the distribution of contact normals. Strong contact forces concentrate in the direction of gravitational deposition (i.e., the vertical direction), leading to significant anisotropy in shear modulus, with the horizontal shear modulus being notably greater than the vertical one. The values of horizontal shear modulus ranging from 40 MPa for chunky particles to 120 MPa under high confining pressure. While increasing confining pressure generally enhances the shear modulus of calcareous sand, the concentration of strong contact forces in the vertical direction due to particle shape causes differential increments in shear modulus across directions, thereby altering anisotropy. Particle breakage under high confining pressure (10%) disrupts the concentration of strong contact forces in the vertical direction and triggers a “surrounding particle compensation” mechanism (accounting for >95% of cases), leading to homogenization of contact force distribution. This significantly reduces the shear modulus and diminishes the degree of anisotropy by up to 50% at breakage rates of 10%. The cross-scale relationship between particle morphology, breakage, and fabric evolution is quantified. Full article

Skin meshing facilitates the greater expansion of donor skin through patterned slits and is widely used for treating extensive burn injuries. However, the actual expansion often falls below manufacturers’ claims. Previous computational analyses using the isotropic Yeoh model have shown that Langer’s line orientation and slit direction significantly affect induced stress and meshing ratios, yet the use of nonlinear anisotropic models that represent collagen fiber alignment corresponding to Langer’s lines remains unexplored. This study employs a nonlinear anisotropic Gasser–Ogden–Holzapfel (GOH) model with slit orientations of 0°, 45°, and 90°, consistent with geometries reported in the literature, to quantify induced stress in skin meshing by incorporating collagen fibers within the dermis layer. The GOH parameters were calibrated to human back skin data uniaxially stretched parallel and perpendicular to Langer’s lines using Levenberg–Marquardt optimization in the GIBBON toolbox (MATLAB R2023a) coupled with FEBio v4.0, achieving a standard deviation of 3% relative to experimental data. The GOH model predicted the highest induced stress at 100% strain for the 45° slit parallel to Langer’s lines and the lowest for the 90° slit perpendicular, exceeding 40 MPa due to absence of damage and rupture modeling but accurately representing anisotropic mesh behavior. Full article

This paper proposes a novel convention-based subgrid scale (SGS) model for large eddy simulation (LES) by using the Liutex concept. Conventional SGS models typically rely on the eddy viscosity assumption, which uses the linear eddy viscosity terms to approximate the nonlinear effects of unresolved turbulent eddies, that should be measured by unresolved Liutex. However, the eddy viscosity assumption is empirical but lacks a scientific foundation, which limits its predictive accuracy. The proposed model in this paper directly models the convective terms and demonstrates several key advantages: (1) the new model gets rid of isotropic assumption for the unresolved SGS eddies which are, in general, anisotropic, (2) the new model contains no empirical coefficients which need to be adjusted case by case, (3) the new model explicitly captures nonlinear convective effects by the SGS eddies and (4) the new model is consistent with the physics for boundary layer as the model becomes zero in the laminar sublayer, where Liutex becomes zero automatically. This new model has been applied in the flat plate boundary transition flow, and the results show that it outperforms the popular and widely adopted wall-adapting local eddy (WALE) model. This new model is a conceptual breakthrough in SGS modeling and has the potential to open a new direction for more accurate SGS models and future LES applications. Full article

Fracture systems critically govern coal seam permeability, influencing hydrocarbon migration pathways and well placement strategies. We established a predictive framework for fracture characterization in thin-interbedded coal reservoirs by integrating seismic response analysis with multi-domain validation. Utilizing borehole log statistics and staggered-grid wave equation modeling, we first decode azimuthal amplitude anisotropy patterns in fractured coal seams under varying lithological contexts. Key findings reveal that (1) isotropic thick surrounding rocks yield distinct fracture symmetry axis alignment (ellipse long-axis orientation shifts with layer velocity), while (2) anisotropic thin-interbedded host strata amplify azimuthal anisotropy ratios at mid–far offsets but induce prediction ambiguity under comparable fracture intensities. By applying azimuthally partitioned OVT data with optimized mid–long offset stacking, our amplitude ellipse fitting method demonstrates unique fracture solutions validated against structural, logging, and production data. This workflow resolves the multi-solution challenges in thin-layered systems, enabling precise fracture parameter prediction to optimize coalbed methane development in geologically complex basins. Full article

In the simulation of 3C-SiC strain gauges in dynamic environment—particularly those involving vibrations and wave propagation—the accurate representation of energy dissipation is essential for reliable predictive modeling. This paper discusses the implementation of both isotropic and anisotropic damping models within COMSOL Multiphysics. In particular, it focuses on the use of an anisotropic loss factor, represented either as a scalar (η_S) for isotropic cases or as a symmetric 6 × 6 loss factor matrix (${\mathsf{\eta }}_{\mathrm{D}}$) for anisotropic dissipation. This formulation enables the directional dependence of damping behavior to be captured, which is particularly important in composite materials, layered media, and metamaterials where energy dissipation mechanisms vary with orientation. The paper also explores the numerical implications of using anisotropic damping, such as its influence on eigenfrequency solutions, frequency response functions, and transient dynamic simulations. Furthermore, it highlights how the inclusion of directional damping can improve the correlation between simulated and experimental results in scenarios where standard isotropic models fail to capture key physical behaviors. Full article

We investigate magnetic instabilities toward multiple-Q states in centrosymmetric bilayer triangular-lattice systems. By focusing on the interplay between the layer-dependent Dzyaloshinskii–Moriya interaction and layer-independent bond-dependent anisotropic interaction, both of which originate from the relativistic spin-orbit coupling, we construct a low-temperature phase diagram based on an effective spin model that also includes frustrated isotropic exchange interactions. Employing simulated annealing, we reveal the stabilization of three distinct double-Q phases in the absence of an external magnetic field, each characterized by noncoplanar spin textures with spatially modulated local scalar spin chirality. Under applied magnetic fields, we identify field-induced phase transitions among single-Q, double-Q, and triple-Q states, some of which exhibit a finite net scalar spin chirality indicative of topologically nontrivial order. These findings highlight centrosymmetric systems with sublattice-dependent Dzyaloshinskii–Moriya interactions as promising platforms for realizing a variety of multiple-Q spin textures. Full article

Multi-angle remote sensing observations play an important role in the remote sensing of solar radiation absorbed by land surfaces. Currently, the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) teams have successively applied the Ross–Li kernel-driven bidirectional reflectance distribution function (BRDF) model to integrate multi-angle observations to produce long time series BRDF model parameter products (MCD43 and VNP43), which can be used for the inversion of various surface parameters and the angle correction of remote sensing data. Even though the MODIS and VIIRS BRDF products originate from sensors and algorithms with similar designs, the consistency between BRDF parameters for different sensors is still unknown, and this likely affects the consistency and accuracy of various downstream parameter inversions. In this study, we applied BRDF model parameter time-series data from the overlapping period of the MODIS and VIIRS services to systematically analyze the temporal and spatial differences between the BRDF parameters and derived indices of the two sensors from the site scale to the region scale in the red band and NIR band, respectively. Then, we analyzed the sensitivity of the BRDF parameters to variations in Normalized Difference Hotspot–Darkspot (NDHD) and examined the spatiotemporal distribution of zero-valued pixels in the BRDF parameter products generated by the constraint method in the Ross–Li model from both sensors, assessing their potential impact on NDHD derivation. The results confirm that among the three BRDF parameters, the isotropic scattering parameters of MODIS and VIIRS are more consistent, whereas the volumetric and geometric-optical scattering parameters are more sensitive and variable; this performance is more pronounced in the red band. The indices derived from the MODIS and VIIRS BRDF parameters were compared, revealing increasing discrepancies between the albedo and typical directional reflectance and the NDHD. The isotropic scattering parameter and the volumetric scattering parameter show responses that are very sensitive to increases in the equal interval of the NDHD, indicating that the differences between the MODIS and VIIRS products may strongly influence the consistency of NDHD estimation. In addition, both MODIS and VIIRS have a large proportion of zero-valued pixels (volumetric and geometric-optical parameter layers), whereas the spatiotemporal distribution of zero-valued pixels in VIIRS is more widespread. While the zero-valued pixels have a minor influence on reflectance and albedo estimation, such pixels should be considered with attention to the estimation accuracy of the vegetation angular index, which relies heavily on anisotropic characteristics, e.g., the NDHD. This study reveals the need in optimizing the Clumping Index (CI)-NDHD algorithm to produce VIIRS CI product and highlights the importance of considering BRDF product quality flags for users in their specific applications. The method used in this study also helps improve the theoretical framework for cross-sensor product consistency assessment and clarify the uncertainty in high-precision ecological monitoring and various remote sensing applications. Full article

The crust and upper mantle structure of Mars is determined in the depth range of 0 to 100 km, by means of dispersion analysis and its inversion, which is performed for the surface waves present in the traces of the seismic event: S1094b. From these traces, Love and Rayleigh waves are measured in the period range of 4 to 40 s. This dispersion was calculated with a combination of digital filtering techniques, and later was inverted to obtain both models: isotropic (from 0 to 100 km depth) and anisotropic (from 0 to 15 km depth), which were calculated considering the hypothesis of the surface wave propagation in slightly anisotropic media. The seismic anisotropy determined from 0 to 5 km depth (7% of S-velocity variation and ξ ~ 1.1) could be associated with the presence of sediments or lava-flow layering, and wide damage zones surrounding the long-term fault networks. For greater depths, the observed anisotropy (17% of S-velocity variation and ξ ~ 1.4) could be due to the possible presence of volcanic materials and/or the layering of lava flows. Another cause for this anisotropy could be the presence of layered intrusions due to a single or multiple impacts, which could cause internal layering within the crust. Finally, the Moho depth is determined at 50 km as a gradual transition from crust to mantle S-velocities, through an intermediate value (3.90 km/s) determined from 50 to 60 km-depth. Full article

Thermal transport properties for the isotropic and anisotropic characterization of nanolayers have been a significant gap in the research over the last decade. Multiple studies have been close to determining the thermal conductivity, diffusivity, and boundary resistance between the layers. The methods detailed in this work involve non-contact frequency domain pump-probe thermoreflectance (FDTR) and photothermal radiometry (PTR) methods for the ultraprecise determination of in-plane and cross-plane thermal transport properties. The motivation of one of the works is the advantage of the use of amplitude (TR signal) as one of the input parameters along with the phase for the determination of thermal parameters. In this article, we present a unique strategy for measuring the thermal transport parameters of thin films, including cross-plane thermal diffusivity, in-plane thermal conductivity, and thermal boundary resistance as a comprehensively reviewed article. The results obtained for organic and inorganic thin films are presented. Precise ranges for the thermal conductivity can be across confidence intervals for material measurements between 0.5 and 60 W/m-K for multiple nanolayers. The presented strategy is based on frequency-resolved methods, which, in contrast to time-resolved methods, make it possible to measure volumetric-specific heat. It is worth adding that the presented strategy allows for accurate (the signal in both methods depends on cross-plane thermal conductivity and thermal boundary resistance) and precise measurement. Full article

A novel and efficient modeling approach has been developed for simulating the responses of triaxial induction logging (TIL) in layered biaxial anisotropic (BA) formations. The core of this innovative technique lies in analytically calculating the primary fields within a homogeneous medium and approximating the scattered fields within layered formations. The former involves employing a two-level subtraction technique. Initially, the first-level subtraction entails altering the direction of the Fourier transform to mitigate the integral singularity of the spectral fields, particularly in high-angle and horizontal wells. Conversely, the second-level subtraction aims to further optimize integral convergence by creating an equivalent unbounded transverse isotropic (TI) formation and eliminating the corresponding spectral fields. With the two-level subtractions, the convergence of the spectral field has been enhanced by more than six orders of magnitude. Additionally, a strict recursive algorithm and approximation method are developed to compute the scattered fields in layered biaxial anisotropic media. The rigorous algorithm is based on a modified amplitude propagator matrix (MAPM) approach and serves as the benchmark for the approximation method. In contrast, the approximation method exploits the similarity between the spectral scattered field of the TI medium and the BA medium, establishing corresponding equivalent layered TI models for each magnetic component. Since the scattered field in TI models only involves a one-dimensional semi-infinite integral, the computational complexity is significantly reduced. Numerical simulation examples demonstrate that the new simulation method is at least two orders of magnitude faster than the current modeling approach while maintaining computational precision error within 0.5%. This significantly improved simulation efficiency provides a solid foundation for expediting the logging data processing. Full article

Establishing accurate structure–property linkages and precise phase volume accuracy in 3D microstructure reconstruction of materials remains challenging, particularly with limited samples. This paper presents an optimized method for reconstructing 3D microstructures of various materials, including isotropic and anisotropic types with two and three phases, using convolutional occupancy networks and point clouds from inner layers of the microstructure. The method emphasizes precise phase representation and compatibility with point cloud data. A stage within the Quality of Connection Function (QCF) repetition loop optimizes the weights of the convolutional occupancy networks model to minimize error between the microstructure’s statistical properties and the reconstructive model. This model successfully reconstructs 3D representations from initial 2D serial images. Comparisons with screened Poisson surface reconstruction and local implicit grid methods demonstrate the model’s efficacy. The developed model proves suitable for high-quality 3D microstructure reconstruction, aiding in structure–property linkages and finite element analysis. Full article