to control the nonlinear numerical instability, throughout the time evolution of the eulerian form of the nonlinear rotating shallow water equations, it is necessary to add numerical diffusion to the solution. it is clear that, this extra numerical diffusion degrades the accuracy of the numerical solution and should be kept as small as possible. in a conventional approach a hyper-diffusion is u...

Atypical perceptual processing in autism spectrum disorder (ASD) is well documented. In addition, growing evidence supports the hypothesis that an excitatory/inhibitory neurochemical imbalance might underlie ASD. Here we investigated putative behavioral consequences of the excitatory/inhibitory imbalance in the context of visual motion perception. As stimulus size increases, typical observers e...

Background: Air pollution has become an important factor restricting China's economic development and has subsequently brought a series of social problems, including the impact of air pollution on the health of residents, which is a topical issue in China. Methods: Taking into account this spatial imbalance, the paper is based on the spatial panel data model PM2.5. Respiratory disease mortality...

We numerically and experimentally show the existence of multicolor vector spatial solitons in a Kerr planar waveguide through the combined effects of cross-phase modulation, four-wave mixing, and stimulated Raman scattering. Mutual spatial guiding of the Raman-Stokes, anti-Stokes, and pump waves is achieved in the high-conversion regime mainly by cross-phase modulation and phase-matched four-wa...

We have designed honeycomb lattices for microwave photons with a frequency imbalance between the two sites in unit cell. This is equivalent of mass term that breaks lattice inversion symmetry. At interface opposite imbalance, we observe topological valley edge states. By imaging spatial dependence modes along interface, obtain their dispersion relation compare to predictions an ab initio tight-...

Albeit hyperspectral image (HSI) classification methods based on deep learning have presented high accuracy in supervised classification, these traditional required quite a few labeled samples for parameter optimization. When processing HSIs, however, artificially are always insufficient, and class imbalance limited is inevitable. This study proposed Transformer-based framework of spatial–spect...