The expressions of the transverse electric (TE) and transverse magnetic (TM) modes of the isosceles right triangular waveguides with unusual boundary conditions are discussed in this paper. Based on the initial solution formed using a finite sum of rectangular harmonics, boundary conditions are discussed, and TE and TM mode expressions are presented in this paper for the isosceles right triangular waveguides with all the possible boundary conditions. Transverse modal field distributions are given for the different isosceles right triangular waveguides.
Lithium is thought to be an excellent anode material for next-generation Li metal batteries (LMBs). However, some problems with lithium anodes often lead to serious safety concerns and catastrophic failures due to the huge volume change, Li dendritic growth, and related side reactions. Therefore, in order to manufacture stable rechargeable batteries, the abovementioned serious problems must be effectively solved. In this paper, a three-dimensional N,P-doped silicon-containing lithium anode is designed and prepared by in situ metallurgy using low-cost Si3N4. The 3D stable composite anode (DLi/LiSix CA) was prepared by adding a small amount of Si3N4 to molten lithium to form N-doped silicon-containing lithium metal which was supported on a polyaniline modified carbon cloth (PMCC). The results show that the DLi/LiSix CA not only has high Li affinity but can also effectively inhibit lithium nucleation and lithium dendritic growth, so as to maintain good structural stability in the process of Li plating/stripping. The new lithium metal anode based on doping and 3D carbon cloth shows good cycling stability and low polarizability in both symmetrical and full cells.
Model selection (MS) and model averaging (MA) are two popular approaches when many candidate models exist. Theoretically, the estimation risk of an oracle MA is not larger than that of an oracle MS because the former is more flexible, but a foundational issue is this: Does MA offer a substantial improvement over MS? Recently, seminal work by Peng and Yang (2022) has answered this question under nested models with linear orthonormal series expansion. In the current paper, we further respond to this question under linear nested regression models. A more general nested framework, heteroscedastic and autocorrelated random errors, and sparse coefficients are allowed in the current paper, giving a scenario that is more common in practice. A remarkable implication is that MS can be significantly improved by MA under certain conditions. In addition, we further compare MA techniques with different weight sets. Simulation studies illustrate the theoretical findings in a variety of settings.
The implementation of AI tools in education has become increasingly popular and brought transformative potential, particularly in the field of language education because of its powerful functions on designing immersive and personalized activities and offering real-time feedback. This study explores the role of AI tools in discourse analysis and the impact on enhancing bilingual skills among early childhood students. It investigates two key questions: (1) How do AI tools impact young childrens bilingual skills in early childhood classrooms? (2) How can discourse analysis of AI tools assist educators with bilingual teaching? A qualitative case study, including an in-depth interview with a bilingual educator, reveals insights into the effectiveness of AI tools in promoting bilingual language acquisition and engaging young learners in meaningful and enjoyable learning environment. Furthermore, the discourse analysis of AI tools offers immediate, actionable insights on each students academic performance, helping educators better understand the language learning process and the specific challenges students face. However, considerations and challenges of AI in education, such as privacy risks and misuse, still need to be considered. The findings of this study bridge the gap and highlight the potential for discourse analysis of AI tools in early childhood bilingual education. Further study can focus on exploring other AI tools in bilingual education and conducting long-term research with a large example size.
Abstract Topological photonics has emerged as an important branch of photonics for its excellent ability to robustly manipulate light. As a widely used topological photonic platform, valley photonic crystals have attracted great attention recently due to the unique opportunities the valley degree of freedom provides to potentially encode and process binary photonic information. However, an efficient and controllable way to generate pure valley current is still lacking. Here, a perfect photonic valley filter with on‐demand routing and switching functionalities by exploiting the unique physics of magneto‐optic and valley photonic crystal is proposed. Particularly, an additional width degree of freedom is introduced by inserting an intermediate layer with matched Dirac points at specific valleys between two domains of topologically distinct photonic crystals. The resultant three‐layer topological heterostructures support large‐area valley polarized states with tunable mode width. Moreover, perfect photonic valley filters to generate and guide the pure valley current through reconfigurable propagation paths by only changing the directions of external magnetic fields are also demonstrated. The work not only lays a solid foundation on the principle and design of photonic valley filters, the great reconfigurability of the design also provides broad application prospects in photonic integrated networks and on‐chip integrated communication systems.
Abstract Active manipulation of Fano resonance at visible and near-IR wavelengths in metal nanodevices is one of the important challenges for applications such as chemical and biological sensing. Here, we theoretically research an active manipulation of Fano resonance at visible and near-IR wavelengths in gold plasmonic nanodevices with graphene. The surface plasmon resonance of the gold plasmonic nanodevice with graphene has three resonance peaks, and this can be explained by the distribution of the electric field in the nanodevice. The Fano resonance wavelength of the gold plasmonic nanodevice with graphene has a significant blue-shift compared with the gold nanodevices without graphene. Moreover, the Fano resonance dependens on the length and position of Au nanorods and the environment refractive index. The figure of merit of the gold nanodevice with graphene can be as high as 41.3, which makes the system suitable for high sensitivity applications. Finally, we actively manipulate the absorption spectrum and the reflected light phase through changing the Fermi energy of graphene. These results suggest an original method for the design of an actively manipulated Fano resonance nanodevice.
The performance of adaptive beamforming degrades severely when the strong desired signal is present in training snapshots with model mismatch. A robust adaptive beamforming is proposed using interference covariance matrix reconstruction in this paper. In the proposed method, the eigenvalue and eigenvector of desired signal is determined by calculating the correlation coefficients between eigenvectors of sample covariance matrix and the presumed array steering vector. Subsequently, the covariance matrix is reconstructed after removing the desired signal component from signal subspace. Finally, the average noise power is computed by estimating the noise subspace dimensions indirectly, and added to the reconstructed matrix in order to prevent the matrix from being singular. Compared with the conventional robust adaptive beamforming methods, the proposed method has improved performance and less computational complexity. Simulation results demonstrate the robustness and effectiveness of the proposed method.
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