From Petrov-Einstein-Dilaton-Axion to Navier-Stokes equation in anisotropic model

In this paper we generalize the previous works to the case that the near-horizon dynamics of the Einstein-Dilaton-Axion theory can be governed by the incompressible Navier-Stokes equation via imposing the Petrov-like boundary condition on hypersurfaces in the non-relativistic and near-horizon limit. The dynamical shear viscosity $\eta$ of such dual horizon fluid in our scenario, which isotropically saturates the Kovtun-Son-Starinet (KSS) bound, is independent of both the dilaton field and axion field in that limit.Comment: 13 pages,no figures; v2: 15 page, Equation.(33), some discussions and references added, minor corrections , Version accepted for publication in Physics Letters

Structural Prior Guided Generative Adversarial Transformers for Low-Light Image Enhancement

We propose an effective Structural Prior guided Generative Adversarial Transformer (SPGAT) to solve low-light image enhancement. Our SPGAT mainly contains a generator with two discriminators and a structural prior estimator (SPE). The generator is based on a U-shaped Transformer which is used to explore non-local information for better clear image restoration. The SPE is used to explore useful structures from images to guide the generator for better structural detail estimation. To generate more realistic images, we develop a new structural prior guided adversarial learning method by building the skip connections between the generator and discriminators so that the discriminators can better discriminate between real and fake features. Finally, we propose a parallel windows-based Swin Transformer block to aggregate different level hierarchical features for high-quality image restoration. Experimental results demonstrate that the proposed SPGAT performs favorably against recent state-of-the-art methods on both synthetic and real-world datasets

Magnetosome Gene Duplication as an Important Driver in the Evolution of Magnetotaxis in the Alphaproteobacteria

The evolution of microbial magnetoreception (or magnetotaxis) is of great interest in the fields of microbiology, evolutionary biology, biophysics, geomicrobiology, and geochemistry. Current genomic data from magnetotactic bacteria (MTB), the only prokaryotes known to be capable of sensing the Earth’s geomagnetic field, suggests an ancient origin of magnetotaxis in the domain Bacteria. Vertical inheritance, followed by multiple independent magnetosome gene cluster loss, is considered to be one of the major forces that drove the evolution of magnetotaxis at or above the class or phylum level, although the evolutionary trajectories at lower taxonomic ranks (e.g., within the class level) remain largely unstudied. Here we report the isolation, cultivation, and sequencing of a novel magnetotactic spirillum belonging to the genus Terasakiella (Terasakiella sp. strain SH-1) within the class Alphaproteobacteria. The complete genome sequence of Terasakiella sp. strain SH-1 revealed an unexpected duplication event of magnetosome genes within the mamAB operon, a group of genes essential for magnetosome biomineralization and magnetotaxis. Intriguingly, further comparative genomic analysis suggests that the duplication of mamAB genes is a common feature in the genomes of alphaproteobacterial MTB. Taken together, with the additional finding that gene duplication appears to have also occurred in some magnetotactic members of the Deltaproteobacteria, our results indicate that gene duplication plays an important role in the evolution of magnetotaxis in the Alphaproteobacteria and perhaps the domain Bacteria

A novel rapid method for viewshed computation on DEM through max-pooling and min-expected height

Viewshed computation of a digital elevation model (DEM) plays an important role in a geographic information system, but the required high computational time is a serious problem for a practical application. Hitherto, the mainstream methods of viewshed computing include line-of-sight method, reference planes method, etc. Based on these classical algorithms, a new algorithm for viewshed computation is proposed in this paper: the Matryoshka doll algorithm. Through a pooling operation, the minimum expected height of the DEM is introduced as max-pooling with minimum expected height in the viewshed computing optimization. This is to increase the efficiency and adaptability of the computation of the visibility range. The experimental results demonstrate that the algorithm has obvious advantages in computing speed, but with the accuracy only slightly reduced

Camera geolocation using digital elevation models in hilly area

he geolocation of skyline provides an important application in unmanned vehicles, unmanned aerial vehicles, and other fields. However, the existing methods are not effective in hilly areas. In this paper, we analyze the difficulties to locate in hilly areas and propose a new geolocation method. According to the vegetation in hilly area, two new skyline features, enhanced angle chain code and lapel point, are proposed. In order to deal with the skyline being close to the camera, we also propose a matching method which incorporates skyline distance heatmap and skyline pyramid. The experimental results show that the proposed method is highly effective in hilly area and has a robust performance against noise and rotation effects