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This study investigates the effect of astragalus polysaccharides (APS) in protecting against thapsigargin-induced endoplasmic reticulum (ER) stress in HT29 cells by suppressing the PERK-eIF2a signaling pathway.

On the basis of Euler-Bernoulli beam theory, surface elastic theory, the strain equivalent assumption and modiffed couple stress theory, the nonlinear governing equations of the nano-beam are derived. In addition, the Galerkin method and the Harmonic Balance Method are adopted so as to give a solution to the equations. In the example, the effects of nano-beam length, nano-beam thickness, damage factor and surface efect to curves of amplitude-frequency response of the nano-beam are discussed. The results show that damage effects should be taken into consideration and the frequency can be controlled by load and structure size of nano-beam.

A theoretical research of structural evolution, electronic properties, and photoelectron spectra of selenium-doped boron clusters SeBn0/− (n = 3–16) is performed using particle swarm optimization (CALYPSO) software in combination with density functional theory calculations. The lowest energy structures of SeBn0/− (n = 3–16) clusters tend to form quasi-planar or planar structures. Some selenium-doped boron clusters keep a skeleton of the corresponding pure boron clusters; however, the addition of a Se atom modified and improved some of the pure boron cluster structures. In particular, the Se atoms of SeB7−, SeB8−, SeB10−, and SeB12− are connected to the pure quasi-planar B7−, B8−, B10−, and B12− clusters, which leads to planar SeB7−, SeB8−, SeB10−, and SeB12−, respectively. Interestingly, the lowest energy structure of SeB9− is a three-dimensional mushroom-shaped structure, and the SeB9− cluster displays the largest HOMO–LUMO gap of 5.08 eV, which shows the superior chemical stability. Adaptive natural density partitioning (AdNDP) bonding analysis reveals that SeB8 is doubly aromatic, with 6 delocalized π electrons and 6 delocalized σ electrons, whereas SeB9− is doubly antiaromatic, with 4 delocalized π electrons and 12 delocalized σ electrons. Similarly, quasi-planar SeB12 is doubly aromatic, with 6 delocalized π electrons and 14 delocalized σ electrons. The electron localization function (ELF) analysis shows that SeBn0/− (n = 3–16) clusters have different local electron delocalization and whole electron delocalization effects. The simulated photoelectron spectra of SeBn− (n = 3–16) have different characteristic bands that can identify and confirm SeBn− (n = 3–16) combined with future experimental photoelectron spectra. Our research enriches the geometrical structures of small doped boron clusters and can offer insight for boron-based nanomaterials. [ABSTRACT FROM AUTHOR]

Urban areas 3D model reconstruction is one of the major fields of application of 3D scanning technologies. In the future, vehicle-based laser scanning, here called mobile laser scanning system, should see considerable use for 3D road environment modelling in urban areas. In this context, one of the main limitations perceived by the mobile laser scanning system is the incompleteness of the sampling. Whenever we scan urban area road environment, the produced sampling usually presents a large number of missing regions. Many algorithmic solutions exist to close those gaps from specific hole filling algorithms to the drastic solution of using water-tight reconstruction methods. In this paper, a method for filling holes of road surface point clouds and generating 3D model of road surface from mobile laser scanning data is developed. The data is classified into road surface, on-road and off-road surface point clouds. Many large holes in the road surface point clouds are filled by using data assimilation algorithm. Then, the road surface is 3D modeled as a triangulated irregular network. It is shown that the whole road surface 3D model is integrated after data processing. The above mentioned steps are applied to a large set of mobile laser scanning data of urban area road environment, in order to obtain the whole urban road surface 3D model.