MH对EBA阻燃及热降解行为影响

采用极限氧指数法、热重分析和差示扫描量热分析等技术和手段研究了氢氧化镁（MH）对乙烯-丙烯酸丁酯共聚物（EBA）的阻燃性能、力学性能及热降解行为的影响。结果表明：EBA／MH复合材料的拉伸强度、断裂伸长率和熔体流动速率均随着MH用量的增加而降低；当MH的质量分数为60％时，复合材料的极限氧指数可达34．3％；MH通过分解吸热可提高EBA的热稳定性；MH表面羟基与EBA的反应性基团发生相互作用，以及EBA发生酯裂解后形成的羧酸与MH反应形成热稳定性更高的离聚物，均可提高EBA在高温下的热稳定性，并改变EBA的热降解历程。MH的“热阱”机理对EBA的阻燃起着很重要的作用。     

MPaaS: Mobility prediction as a service in telecom cloud

Mobile applications and services relying on mobility prediction have recently spurred lots of interest. In this paper, we propose mobility prediction based on cellular traces as an infrastructural level service of telecom cloud. Mobility Prediction as a Service (MPaaS) embeds mobility mining and forecasting algorithms into a cloud-based user location tracking framework. By empowering MPaaS, the hosted 3rd-party and value-added services can benefit from online mobility prediction. Particularly we took Mobility-aware Personalization and Predictive Resource Allocation as key features to elaborate how MPaaS drives new fashion of mobile cloud applications. Due to the randomness of human mobility patterns, mobility predicting remains a very challenging task in MPaaS research. Our preliminary study observed collective behavioral patterns (CBP) in mobility of crowds, and proposed a CBP-based mobility predictor. MPaaS system equips a hybrid predictor fusing both CBP-based scheme and Markov-based predictor to provide telecom cloud with large-scale mobility prediction capacity.     

变电站典型光通信模式研究

目前,通信条件已发生了革命性的变化,由早期的载波、微波和电缆等通信介质发展成为以光缆为主的通信网络.电力系统以OPGW光缆、ADSS光缆为主,已覆盖了几乎所有的输变电场所.因此,应建立与之适应的通信模式.通过研究现代通信条件、变电站通信的需求,提出了统一化的、简单的变电站通信模式.     

共振瑞利散射测定痕量甲胎蛋白研究

磷钼杂多酸与甲胎蛋白(AFP)结合,会引起共振瑞利散射(RRS),最大RRS峰均位于480 nm,在一定浓度范围内,AFP浓度与散射强度成正比。本文对该反应体系的适宜反应条件、主要影响因素、散射强度与AFP浓度的关系、方法的灵敏度等进行了比较研究。发现不同的杂多酸对于甲胎蛋白的检出限(3σ)在5.2-78 ng/mL之间,其中以磷锑钼酸体系灵敏度最高,对于甲胎蛋白(AFP)的检出限为2.5 ng/mL。该方法具有操作简便、灵敏度高、线性范围宽等优点。考察了共存物质的干扰影响,获得了满意的结果。     

国内外注塑机液压系统现状及其发展趋势──兼论二通插装比例控制技术在注塑机中的应用

本文叙述了注塑成型工艺对液压系统的要求，注塑机液压系统的分类和比较；并着重论述了具有八十年代世界先进水平的二通插装比例问的结构和特点及其在注塑机中的应用。     

Fast online acquisition and analysis for parison swell and sag in blow molding

It is critical to quantitatively and reliably characterize the effects of swell and sag phenomena on the final parison dimensions in extrusion blow molding. To achieve this goal, an online image acquisition and analysis technique was developed. The successive images of parison were automatically taken using the online acquisition apparatus. These images were then analyzed by the combined use of the conventional digital image processing method and the new one developed by the authors. So the development of parison diameter and thickness swells with the extrusion time could be determined online. On the basis of the online obtained actual swell values, the pure swell and sag components were quantitatively determined. The developed technique was tested through a series of experiments using several resins under different processing parameters and die types. Shown in the present article were the results for a converging die under three different die gaps and a high‐density polyethylene. Some new phenomena were observed using the proposed technique. The results showed that the technique yields fast and accurate determination of the evolution of diameter, thickness, and length of parison during its extrusion. The technique can be employed as a part of the closed loop control for blow molded part thickness. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 101: 2399–2406, 2006     

基于多径路由负载均衡的动态源路由协议*

提出了一种DSR的改进多径路由协议（LBDSRM）。采用开销小的综合链路状态路由判据算法,协议具有链路状态实时监控与适时调整路由功能,在链路变化较大的情况下,主动通知有路由冗余的源节点改用或重点使用次选路由;而且协议提出了适时退避算法,解决了多径任务与单径任务争用链路时网络公平性问题。仿真结果表明新协议能有效避免节点拥塞,达到较好的动态负载均衡,实现网络资源的充分利用。     

单周控制光伏并网系统的最大功率控制研究

单周控制的单级全桥光伏并网系统具有容量大、效率高、成本低等优点.但现有基于单周控制的光伏电池最大功率跟踪存在着难以搜索最大功率点、难以稳定工作在最大功率点以及搜索精度差等缺点.针对以上不足,提出了基于增量电导的光伏电池最大功率跟踪算法,该算法将光伏电池输出功率引入到单周控制的输入量中,同时优化了光伏电池输出电压的给定量.该算法在硬件上实现简单,仿真和实验结果表明该算法能够准确跟踪光伏电池最大功率点,并具有较高的精度和稳定性.     

涵洞工程软弱地基处理中松木桩的应用

介绍赤天化纸业公司涵洞工程软弱地基的处理,针对软弱地基的不同构成需采取不同的处理方法,结合工程实践,对特殊环境下采用松木桩处理软弱地基的问题作了一些探讨。     

Correlations between characteristics of maximum influence and degree distributions in software networks

Software systems can be represented as complex networks and their artificial nature can be investigated with approaches developed in network analysis.Influence maximization has been successfully applied on software networks to identify the important nodes that have the maximum influence on the other parts.However,research is open to study the effects of network fabric on the influence behavior of the highly influential nodes.In this paper,we construct class dependence graph(CDG)networks based on eight practical Java software systems,and apply the procedure of influence maximization to study empirically the correlations between the characteristics of maximum influence and the degree distributions in the software networks.We demonstrate that the artificial nature of CDG networks is reflected partly from the scale free behavior:the in-degree distribution follows power law,and the out-degree distribution is lognormal.For the influence behavior,the expected influence spread of the maximum influence set identified by the greedy method correlates significantly with the degree distributions.In addition,the identified influence set contains influential classes that are complex in both the number of methods and the lines of code(LOC).For the applications in software engineering,the results provide possibilities of new approaches in designing optimization procedures of software systems.