A 3D DC finite element method forward program is developed in this paper for anisotropic geoelectric media. Both total and secondary field approaches have been implemented. In this paper, we focused on the structured grid scheme. The modeling shows that the symmetry of the structure grid determines the symmetry of the response potential around the point source for an anisotropic half‐space. Through numerical modeling with three kinds of coarse meshes by the total field approach and secondary field approach separately, a higher accuracy can be achieved via the secondary field approach. And the relative error between the numerical solution and the analytical solution is less than 2%. Modeling results contrasting with previous scholars also verify the correctness of the algorithm. Then, the numerical results of 3D models with anisotropic properties were presented and compared to models with isotropic properties. These results clearly illustrated the strong effect of anisotropy and the problems in interpretation if anisotropy was not properly addressed. This work will establish the foundation for our future effort of building a 3D inversion program with arbitrary anisotropy.

In recent decades, differential evolution (DE) has been employed to address a diverse range of nonlinear, nondifferentiable, and nonconvex optimization problems. In this study, we introduce an enhanced adaptive differential evolution algorithm to address the inversion problem associated with magnetic data. The primary objective of the inversion process is to minimize the discrepancy between observed data and predicted data derived from the inverted model. So, the contributions of this paper include the following two points. First, a new mechanism for generating crossover rate (CR) is proposed, which tends to reduce the CR values corresponding to vectors with better objective function values. Second, a new mutation strategy with direction information is proposed to expedite convergence. Additionally, modifications were made to the adjustment of the regularization factor to prevent it from becoming too minimal, thereby preserving its efficacy. The proposed algorithm is validated through synthetic models and a field example. Results from synthetic models demonstrate that our method is superior to and competitive with the original adaptive DE in both solution quality and convergence velocity. For the field example, the Inverted models align closely with the drill-well information.

Ethnic minority embroidery from Guizhou is an important part of Chinese culture, reflecting the history, beliefs, and artistic traditions of the region’s diverse ethnic groups. However, challenges in automatic recognition arise due to data scarcity, complex textures, and the flexibility of handmade designs. This study constructs the Guizhou Province Intangible Cultural Heritage Embroidery dataset and proposes an improved MobileViT-DDC model to address the issues of complex textures and data scarcity. The model integrates Dilatefomer, Deformable Dilatefomer (DefDilatefomer), and Context Broadcasting Module (CBM) to capture local details and global information in embroidery patterns. Experimental results show that the MobileViT-DDC model achieves an accuracy of 98.40% on the Guizhou embroidery dataset (a 2.17% improvement over the original baseline model) with a 14% reduction in computational load; on the Pakistani National Dress Dataset, it reaches an accuracy of 79.07%, representing a 2.63% increase compared to the original baseline model of the same scale. This study is the first to apply a CNN-ViT hybrid model to ethnic embroidery recognition, providing a new solution for the digital preservation of cultural heritage. The model’s cross-cultural adaptability was further validated through its application to the Pakistani National Dress dataset.

We present a 2.5-dimensional (2.5-D) finite element algorithm for direct current (DC) resistivity modelling in anisotropic media with singularity removal. First, we provide the weak form of the integral equation for the boundary value problem and simplify the Euler angles while calculating the primary potential so that the Fourier transform of the background potential with the dip angle can be avoided because it is mathematically difficult. A two-layered model is then simulated when the first covering is anisotropic. The relative error between this numerical solution and the analytical solution is < 1%. We then model a number of more complicated scenarios, using the algorithm developed in this paper. We test the model response to a small body at depth whose resistivity is isotropic, and then test whether the longitudinal or transverse resistivities affect the final results more. Based on this analysis, we found that longitudinal resistivity has more of an effect on the apparent resistivity than transverse resistivity in collinear arrays, such as pole–pole, dipole–dipole and Wenner arrays. Finally, through calculation of the current density and anomalous current density of several arrays, we conclude that the causes of different responses of longitudinal and transverse resistivity by each array is the distribution of current density in the subsurface. We also show that the sensitivity of each array type to variations in longitudinal and transverse resistivity can be understood when looked at from the perspective of current density.

Magnetotelluric (MT) sounding is a geophysical technique widely utilized in mineral resource surveys, where conductivity and magnetic permeability serve as essential physical parameters for forward modeling and inversion. However, the effects of conductive anisotropy and non-zero magnetic susceptibility are usually ignored. In this study, we present a three-dimensional (3D) MT modeling algorithm using Coulomb-gauged electromagnetic potentials, incorporating a mixed nodal and edge-based finite element method capable of simulating MT responses for conductive anisotropic and magnetic anomalies. Subsequently, the algorithm’s accuracy was validated in two steps: first, it was compared with analytical solutions for a 1D magnetic model; then, a comparison was made with previously published numerical results for a 3D generalized conductive anisotropic model. The results of two tests show that the maximum relative error is below 0.5% for both models. Furthermore, representative models were computed to comprehensively analyze the responses of MT. The findings illustrate the relationship between anisotropic parameters and electric fields and emphasize the significance of considering the impact of magnetic susceptibility in magnetite-rich regions.