基于经济的网格资源调度算法研究

网格使构建虚拟组织,在全世界范围内共享资源成为现实.但是,在网格环境下的资源管理和调度是一项相当复杂的工作,这主要是由于资源分布在世界各地,隶属于不同的组织,各个资源拥有者都有不同的使用和访问策略、开销模型、不断变化的负载和可用性.为了满足网格计算环境中资源调度的复杂需要,可以将现实世界中的经济原理和模型应用到网格环境下的任务调度中,并据此提出了几种经济资源调度算法.     

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。     

Two-dimensional Kerr-Fourier imaging of translucent phantoms in thick turbid media

Translucent scattering phantoms hidden inside a 5.5-cm-thick Intralipid solution were imaged as a function of phantom scattering coefficients by the use of a picosecond time- and space-gated Kerr-Fourier imaging system. A 2-mm-thick translucent phantom with a 0.1% concentration (scattering coefficient) difference from the 55-mm-thick surrounding scattering host can be distinguished at a signal level of ~10(-10) of the incidence illumination intensity.     

2D Bi2O2Te Semiconductor with Single-Crystal Native Oxide Layer

Following logic in the silicon semiconductor industry, the existence of native oxide and suitable fabrication technology is essential for 2D semiconductors in planar integronics, which are surface-sensitive to typical coating technologies. To date, very few types of integronics are found to possess this feature. Herein, the 2D Bi₂O₂Te developed recently is reported to possess large-area synthesis and controllable thermal oxidation behavior toward single-crystal native oxides. This shows that surface-adsorbed oxygen atoms are inclined to penetrate across [Bi₂O₂]_n²ⁿ⁺ layers and bond with the underlying [Te]_n²ⁿ⁻ at elevated temperatures, transforming directly into [TeO₄]_n²ⁿ⁻ with the basic architecture remaining stable. The oxide can be adjusted to form in an accurate layer-by-layer manner with a low-stress sharp interface. The native oxide Bi₂TeO₆ layer (bandgap of ≈2.9 eV) exhibits visible-light transparency and is compatible with wet-chemical selective etching technology. These advances demonstrate the potential of Bi₂O₂Te in planar-integrated functional nanoelectronics such as tunnel junction devices, field-effect transistors, and memristors.     

Voltage Decay of Li-Rich Layered Oxides: Mechanism,Modification Strategies,and Perspectives

Li-rich layered oxides (LLOs) have been considered as the most promising cathode materials for achieving high energy density Li-ion batteries. However, they suffer from continuous voltage decay during cycling, which seriously shortens the lifespan of the battery in practical applications. This review comprehensively elaborates and summarizes the state-of-the-art of the research in this field. It is started from the proposed mechanism of voltage decay that refers to the phase transition, microscopic defects, and oxygen redox or release. Furthermore, several strategies to mitigate the voltage decay of LLOs from different scales, such as surface modification, elemental doping, regulation of components, control of defect, and morphology design are summarized. Finally, a systematic outlook on the real root of voltage decay is provided, and more importantly, a potential solution to voltage recovery from electrochemistry. Based on this progress, some effective strategies with multiple scales will be feasible to create the conditions for their commercialization in the future.     

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.     

Finite-time optimal tracking control for a class of nonlinear systems with prescribed performance

In this paper, a finite-time optimal tracking control scheme based on integral reinforcement learning is developed for partially unknown nonlinear systems. In order to realize the prescribed performance, the original system is transformed into an equivalent unconstrained system so as to a composite system is constructed. Subsequently, a modified nonlinear quadratic performance function containing the auxiliary tracking error is designed. Furthermore, the technique of experience replay is used to update the critic neural network, which eliminates the persistent of excitation condition in traditional optimal methods. By combining the prescribed performance control with the finite-time optimization control technique, the tracking error is driven to a desired performance in finite time. Consequently, it has been shown that all signals in the partially unknown nonlinear system are semiglobally practical finite-time stable by stability analysis. Finally, the provided comparative simulation results verify the effectiveness of the developed control scheme.     

跨谱段SAR散射中心多维参数解耦和估计方法

微波光子雷达发射大带宽跨谱段的信号,为目标的精细电磁特性描述和准确识别提供基础的同时,也亟需与之相应的大带宽大转角情况下的电磁模型参数提取方法.相比窄带条件,跨谱段信号数据量大,所含物理量信息维度高且复杂,大转角情况下距离和方位向耦合.该文提出跨谱段SAR散射中心多维参数解耦和估计方法,首先结合极坐标格式算法(PFA)和属性散射中心模型构造2维解耦波数域散射中心模型,再结合坐标下降法(CDA)将复杂的高维耦合参数估计方法简化为循环迭代的1维参数估计方法,有效降低字典维度和估计复杂度,并引入Hooke-Jeeves算法提高估计精度.最后根据各个散射中心的参数估计结果对它们的结构和位置进行识别,对仿真数据的处理实验验证了该文方法的有效性.     

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...