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Recently, researchers have demonstrated, both theoretically and experimentally, that low-dimensional version of conventional leaky waves, known as "flatland leaky waves" (FLWs). FLWs can be supported by planar junctions of metasurfaces and are completely confined to a plane. Here, we design a structure that places an equivalent reactance surface near the transmission line to excite the FLWs. By properly designing the geometry of the unit cell, conditions can be created for faster surface waves (SWs) to excite slower SWs on the surface, resulting in the desired form of two-dimensional (2D) leaky-wave radiation. A sample was fabricated and measured, and both the simulation results and the experimental results yielded the desired results. Finally, we design the equivalent impedance surface model on which we can also observe the 2D FLWs. Our research not only deepens the understanding of the phenomenon of FLWs but also brings the application of equivalent reactance surfaces in the field of electromagnetic phenomena research to a higher level. [ABSTRACT FROM AUTHOR]

This paper proposes a trajectory-optimization problem for spacecraft close proximity to a noncooperative target, aiming at the generation of a six-degree-of-freedom (DOF) trajectory with the fuel-optimal objective value and considering multiple constraints on the control magnitude, line-of-sight, and glide-slope. The line-of-sight and glide-slope constraints are coupled between translational and rotational motions. The dual quaternion is an effective method for establishing the translationally and rotationally coupled model, because it can represent the translation and rotation in an integrated manner. Therefore, in this study, the trajectory-optimization problem of spacecraft close proximity coupled with position and attitude is established using dual quaternions. Next, the close-proximity trajectory-optimization problem is converted into a nonlinear programming problem, which can be solved efficiently using well-developed algorithms such as convex optimization. However, the zero-order hold used in the discrete method of convex optimization is an equidistant dispersion, which cannot guarantee the satisfaction of constraints between discrete points. Therefore the pseudospectral convex method is proposed using nonequidistant collocation points to mitigate the problem of constraint violation between discrete points and improve the accuracy and computational efficiency of the algorithm. The proposed algorithm can be applied to tasks such as rendezvous and docking with noncooperative targets and close proximity. Finally, the effectiveness of the proposed method was validated via numerical simulation, and the results were compared with those of the existing approach, GPOPS. The results indicate that the proposed algorithm is superior to GPOPS in computational efficiency and objective values. [ABSTRACT FROM AUTHOR]

Photocatalytic technology, which is regarded as a green route to transform solar energy into chemical fuels, plays an important role in the fields of energy and environmental protection. An emerging S-scheme heterojunction with the tightly coupled interface, whose photocatalytic efficiency exceeds those of conventional type II and Z-scheme photocatalysts, has received much attention due to its rapid charge carrier separation and strong redox capacity. This review provides a systematic description of S-scheme heterojunction in the photocatalysis, including its development, reaction mechanisms, preparation, and characterization methods. In addition, S-scheme photocatalysts for CO2 reduction are described in detail by categorizing them as 0D/1D, 0D/2D, 0D/3D, 2D/2D, and 2D/3D. Finally, some defects of S-scheme heterojunctions are pointed out, and the future development of S-scheme heterojunctions is proposed. [ABSTRACT FROM AUTHOR]

Nowadays, deep representations have gained significant attention due to their outstanding performance in a wide range of tasks. However, the interpretability of deep representations in specific applications poses a significant challenge. For instances where the generated quantity matrices exhibit symmetry, this paper introduces a variant of deep matrix factorization (deep MF) called deep L p smooth symmetric non-negative matrix factorization (DSSNMF), which aims to improve the extraction of clustering structures inherent in complex hierarchical and graphical representations in high-dimensional datasets by improving the sparsity of the factor matrices. We successfully applied DSSNMF to synthetic datasets as well as datasets related to post-traumatic stress disorder (PTSD) to extract several hierarchical communities. Specifically, we identified non-disjoint communities within the partial correlation networks of PTSD psychiatric symptoms, resulting in highly meaningful clinical interpretations. Numerical experiments demonstrate the promising applications of DSSNMF in fields like network analysis and medicine. [ABSTRACT FROM AUTHOR]