激光扫描车身测量传感器靶标识别体系的研究

介绍了四光束激光扫描测量车身三维坐标的系统构成和基本原理,从系统PIN预处理输出的靶标回射信号的特点出发,为汽车车身测量传感器设计了基于条形码识别原理的合作靶标识别体系,最多可同时对27个测量点进行有效识别,确保传感器的精度要求和效率要求,达到了很好的实验效果。     

Macrophage Membrane-Coated Nanoparticles Sensitize Glioblastoma to Radiation by Suppressing Proneural–Mesenchymal Transformation in Glioma Stem Cells

Radiotherapy is identified as a crucial treatment for patients with glioblastoma, but recurrence is inevitable. The efficacy of radiotherapy is severely hampered partially due to the tumor evolution. Growing evidence suggests that proneural glioma stem cells can acquire mesenchymal features coupled with increased radioresistance. Thus, a better understanding of mechanisms underlying tumor subclonal evolution may develop new strategies. Herein, data highlighting a positive correlation between the accumulation of macrophage in the glioblastoma microenvironment after irradiation and mesenchymal transdifferentiation in glioblastoma are presented. Mechanistically, elevated production of inflammatory cytokines released by macrophages promotes mesenchymal transition in an NF-κB-dependent manner. Hence, rationally designed macrophage membrane-coated porous mesoporous silica nanoparticles (MMNs) in which therapeutic anti-NF-κB peptides are loaded for enhancing radiotherapy of glioblastoma are constructed. The combination of MMNs and fractionated irradiation results in the blockage of tumor evolution and therapy resistance in glioblastoma-bearing mice. Intriguingly, the macrophage invasion across the blood-brain barrier is inhibited competitively by MMNs, suggesting that these nanoparticles can fundamentally halt the evolution of radioresistant clones. Taken together, the biomimetic MMNs represent a promising strategy that prevents mesenchymal transition and improves therapeutic response to irradiation as well as overall survival in patients with glioblastoma.     

A multi-agent model for decision making on environmental regulation in urban agglomeration

The Journal of Supercomputing - The incomplete enforcement of environmental regulation by local governments will lead to environmental degradation. While the strategy selection for local...     

Joint Classification and Regression for Visual Tracking with Fully Convolutional Siamese Networks

International Journal of Computer Vision - Visual tracking of generic objects is one of the fundamental but challenging problems in computer vision. Here, we propose a novel fully convolutional...     

Rejoinder on: Some recent work on multivariate Gaussian Markov random fields

I thank the discussants, Miguel A. Martinez-Beneito, Fedel Greco, Carlo Trivisano, Stephan R Sain, and Reinhard Furrer, for their insightful and stimulating commentary. The rejoinder is organized in five sections: (1) the M-based models, (2) posterior sensitivity to prior choices for \({\varvec{C}}\) and \({\varvec{\varSigma }}\), (3) stationary and non-stationary (M)GMRFs, (4) various approaches to model formulation and related applications, and (5) statistical computation.     

Electrochemical corrosion behavior of 2A02 Al alloy under an accelerated simulation marine atmospheric environment

The corrosion behavior of 2A02 Al alloy under simulated marine atmospheric environment has been studied using mass-gain, scanning electron microscope/energy dispersive spectroscopy (SEM/EDS), laser scanning confocal microscopy, X-ray diffraction spectroscopy and localized electrochemical methods. The results demonstrate that the relationship between the corrosion induced mass-gain and the corrosion time is in accordance with the power rule. The mass-gain increases gradually during the corrosion time, while the corrosion rate decreases. With ongoing of the corrosion, corrosion products film changed from a porous to a compact structure. The various spectroscopic data show that the corrosion products films composed mainly of Al(OH)₃, Al₂O₃ and AlCl₃. The electrochemical corrosion behavior of the 2A02 Al alloy was studied by electrochemical impedance spectroscopy (EIS).     

Erratum to: High-purity helical carbon nanotubes by trace-waterassisted chemical vapor deposition: Large-scale synthesis and growth mechanism

Nano Research - The first author, Fanbin Meng, and the second author, Ying Wang, contributed equally to this work was unfortunately forgotten to write on the first pages of the main text and the...     

Approximate dynamic programming solutions with a single network adaptive critic for a class of nonlinear systems

Approximate dynamic programming (ADP) formulation implemented with an adaptive critic (AC)-based neural network (NN) structure has evolved as a powerful technique for solving the Hamilton-Jacobi-Bellman (HJB) equations. As interest in ADP and the AC solutions are escalating with time, there is a dire need to consider possible enabling factors for their implementations. A typical AC structure consists of two interacting NNs, which is computationally expensive. In this paper, a new architecture, called the ‘cost-function-based single network adaptive critic (J-SNAC)’ is presented, which eliminates one of the networks in a typical AC structure. This approach is applicable to a wide class of nonlinear systems in engineering. In order to demonstrate the benefits and the control synthesis with the J-SNAC, two problems have been solved with the AC and the J-SNAC approaches. Results are presented, which show savings of about 50% of the computational costs by J-SNAC while having the same accuracy levels of the dual network structure in solving for optimal control. Furthermore, convergence of the J-SNAC iterations, which reduces to a least-squares problem, is discussed; for linear systems, the iterative process is shown to reduce to solving the familiar algebraic Ricatti equation.     

基于网络的多媒体课堂教学模式的研究与实践

计算机多媒体技术和网络技术应用于教学,给学生提供了一个开放的学习空间,使学生在新型学习环境中,不断充实自己、完善自我。本文从教学模式出发,探讨基于网络的多媒体课堂教学模式,并对该模式进行了分析。旨在将网络、多媒体这种现代教育技术运用于传统的课堂教学,提高素质教育水平。