网络设备配置信息备份系统的设计与实现

提出了如何设计开发网络设备配置信息备份系统,实现各种网络设备配置信息的远程备份,并用VBScript语言进行了具体实现。     

A scalable kernel-based semisupervised metric learning algorithm with out-of-sample generalization ability

In recent years, metric learning in the semisupervised setting has aroused a lot of research interest. One type of semisupervised metric learning utilizes supervisory information in the form of pairwise similarity or dissimilarity constraints. However, most methods proposed so far are either limited to linear metric learning or unable to scale well with the data set size. In this letter, we propose a nonlinear metric learning method based on the kernel approach. By applying low-rank approximation to the kernel matrix, our method can handle significantly larger data sets. Moreover, our low-rank approximation scheme can naturally lead to out-of-sample generalization. Experiments performed on both artificial and real-world data show very promising results.     

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.     

Research on the Mechanical Properties of Magnetorheological Damping and the Performance of Microprobe Test Process

Journal of Electronic Testing - In order to control the stable and controllable loading of the wafer level microprobe test bench, the magnetorheological (MR) damper used in the existing research...     

The effect of curing on the crystallization of poly(phenylene sulfide)

Summary Poly(phenylene sulfide) (PPS) was cured in the melt and solid states under air and/or nitrogen environments. Crystallization behavior of such cured materials as a function of cure time at 320°C and 255°C was studied via differential scanning calorimetry. It was found, on general, that while short-time curing leads to an increase in crystallization rate, prolonged curing leads to a decrease in both crystallinity and crystallization rate. In contrast to the enhanced crystallization rate caused by curing in nitrogen at the melt state, no significant change of crystallization rate is observed while curing is done in the solid state (in nitrogen).     

一种基于自适应量化嵌入器的隐写方法

感知质量和容量一直是图像隐写算法设计中难以折中的两个要素,如何取得更好的综合性能已吸引了很多研究者的兴趣.提出一种基于自适应量化嵌入器的隐写方法.这一方法通过改变某一载体信号所在子空间的索引来调制秘密信息,自适应特性体现在决定着子空间尺寸的分割码本的设计上.将这种隐写方法用于以2×2图像块为单元的数字图像隐写算法设计中,并将分割码本设计得具备HVS特性以取得较好的折中效果.实验表明,算法在感知质量和容量方面具有较好的综合性能.     

C语言在化工原理离心泵特性曲线测定中的应用

离心泵特性曲线的测定是化工原理的重要内容,涉及到伯努利方程和连续性方程在流体流动中的实际应用,公式复杂,计算量大.本文利用C语言的强大结构化编程和计算功能,处理了“离心泵特性曲线的测定”实验数据,给出了程序设计的思路和方法,得到了离心泵的特性曲线.从曲线可以看出,随着流量的增大,离心泵的压头减少,轴功率升高,和教材完全一致.而离心泵的效率随流量增大而增大,并未出现先增大后减小的情况,可能是由于流量较小所导致.通过分析曲线可以得到离心泵操作相关的知识,离心泵必须在流量较小的区域工作才能获得较大的压头,大流量的离心泵需要配置大功率的电机,离心泵启动之前应关闭出口阀等.此外还发现压力表和真空表的读数随流量的增大而变小,解释了此现象.该程序结构简单,维护方便,通过简单修改可用于处理其它化工原理实验的数据,充分发挥了C语言的特长来解决化工原理计算复杂的特点.     

试论女性主义文化在产品设计中的符号化演绎

设计总是与文化的多样性有着错综复杂的关系,女性主义作为一种主体意识强烈、情感导向明确的文化,其在设计中的融入,是设计发展过程中的必然。本文从三个案例出发,尝试解读女性主义文化的部分内容在产品设计中的符号化演绎。     

Group interaction analysis in dynamic context.

Computer understanding of human actions and interactions is one of the key research issues in human computing. In this regard, context plays an essential role in semantic understanding of human behavioral and social signals from sensor data. This paper put forward an event-based dynamic context model to address the problems of context awareness in the analysis of group interaction scenarios. Event-driven multilevel dynamic Bayesian network is correspondingly proposed to detect multilevel events, which underlies the context awareness mechanism. Online analysis can be achieved, which is superior over previous works. Experiments in our smart meeting room demonstrate the effectiveness of our approach.