New insights on survivability in multi-domain optical networks

With the development of intelligent optical networks and the general multi-protocol label switching (GMPLS) technique, the seamless convergence between IP network and optical network is no longer be a dream but a practical reality. Similar to the Internet, current optical networks have been divided into multiple domains each of which has its own network provider and management policy. Therefore, the development of multi-domain optical networks will be the trend of new-generation intelligent optical networks, and GMPLS-based survivability for multi-domain optical networks will become a hot topic of research in the future. This paper provides a comprehensive review of the existing survivable schemes in multi-domain optical networks and analyzes the shortcomings of current research. Based on previous studies, we present possible challenges and propose new ideas to design efficient survivable schemes to guide the future work of researchers in multi-domain optical networks.     

模糊综合评判理论在研究性学习系统中的研究及应用

介绍了工程数学中的模糊综合评判理论以及相应树型向量推理算法,并将模糊综合推理机制运用到研究性学习系统中进行研究型应用。该系统中运用模糊综合评判对学习效果进行合理评判,得出综合成绩,以其作为改进研究性学习模式的参考评证,从而使研究性学习过程良性发展。     

面向业务问题求解的知识供应过程模型

为了满足企业在业务问题求解方面的实际需求,提出了一个面向业务问题求解的知识供应过程模型。该模型提出了知识供应过程中的问题空间、知识空间和流程空间的概念及其关联关系,并进一步给出了包含知识的获取、评价、存储和重用的知识供应过程的有关算法。该模型与算法将业务问题求解过程与知识供应过程进行了融合,通过关联关系实现了知识的主动供应,在优化了业务问题求解过程的同时,提高了知识积累的质量和知识重用的效率。基于该模型建立了知识管理问题求解的原型系统KMPSS,并得到了初步应用验证。     

一种新的覆盖粗糙集及其模糊性度量

在覆盖近似空间中定义了一类新的模糊集,给出了该类模糊集的模糊性度量,讨论模糊集及其模糊度量的性质,最后通过实例给出直观解释.     

基于LabVIEW 8.0测定纯液体蒸发焓的虚拟仪器

将常规的数字温度仪与压力计通过串行口和计算机连接,构建基于LabVIEW 8.0测定纯液体蒸发焓的虚拟仪器,实现实验数据的动态采集、实时显示、自动绘制p～T曲线并显示曲线方程、自动数据处理和写成结果报告等。应用结果表明:基于LabVIEW构建的测定纯液体蒸发焓的虚拟仪器,免除人工操作的繁琐和人为误差,测定乙醇和苯蒸发焓的相对误差分别为0.86%、-2.97%,提高了测量结果的准确度,且具有界面友好,操作简便和功能易扩展等诸多优点。     

A hybrid clustering and graph based algorithm for tagSNP selection

TagSNP selection, which aims to select a small subset of informative single nucleotide polymorphisms (SNPs) to represent the whole large SNP set, has played an important role in current genomic research. Not only can this cut down the cost of genotyping by filtering a large number of redundant SNPs, but also it can accelerate the study of genome-wide disease association. In this paper, we propose a new hybrid method called CMDStagger that combines the ideas of the clustering and the graph algorithm, to find the minimum set of tagSNPs. The proposed algorithm uses the information of the linkage disequilibrium association and the haplotype diversity to reduce the information loss in tagSNP selection, and has no limit of block partition. The approach is tested on eight benchmark datasets from Hapmap and chromosome 5q31. Experimental results show that the algorithm in this paper can reduce the selection time and obtain less tagSNPs with high prediction accuracy. It indicates that this method has better performance than previous ones.     

Control of frictional dynamics of a one-dimensional particle array

Control of frictional forces is required in many applications of tribology. While the problem is approached by chemical means traditionally, a recent approach was proposed to control the system mechanically to tune frictional responses. We design feedback control laws for a one-dimensional particle array sliding on a surface subject to friction. The Frenkel-Kontorova model describing the dynamics is a nonlinear interconnected system and the accessible control elements are average quantities only. We prove local stability of equilibrium points of the un-controlled system in the presence of linear and nonlinear particle interactions, respectively. We then formulate a tracking control problem, whose control objective is for the average system to reach a designated targeted velocity using accessible elements. Sufficient stabilization conditions are explicitly derived for the closed-loop error systems using the Lyapunov theory based methods. Simulation results show satisfactory performances. The results can be applied to other physical systems whose dynamics is described by the Frenkel-Kontorova model.     

白蚁提取液急性毒性及致突变性研究

本文采用大,小鼠急性经口毒性试验、Ａｍｅｓ试验、小鼠骨髓细胞微核试验及小鼠精子畸变试验对白蚁提取液的毒理学安全性进行了研究,结果表明,白蚁提取液大,小鼠急性经口ＬＤ５０均大于１０ｇ／ｋｇ体重,属“实际无毒”：体内（包括体细胞和生殖细胞）、体外致突变性试验系统均未检出其致突性。     

A preliminary attempt to use radiomic features in the diagnosis of extra-articular long head biceps tendinitis

Magnetic Resonance Materials in Physics, Biology and Medicine - This study aims to present a radiomic application in diagnosing the long head of biceps (LHB) tendinitis. Moreover, we evaluated...     

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.