Influence of polymer modulus on the percolation threshold of latex-based composites

Monodispersed copolymer emulsions with different glass transition temperatures were synthesized to investigate the effect of room temperature polymer matrix modulus on the electrical properties of carbon black (CB) filled segregated network composites. The emulsion with the highest modulus at room temperature produced composites with the lowest percolation threshold. The threshold for a composite made from a copolymer latex containing an equal ratio of butyl acrylate and methyl methacrylate (BA5) is 1.5 vol%, while the percolation threshold for the much lower modulus BA7 (7:3 BA/MMA ratio) is 4.93 vol%. The microstructure of each composite shows significant differences in the level of CB dispersion within the polymer matrix. Higher modulus polymer particles push the CB more efficiently into the interstitial space between them, resulting in a lower percolation threshold. This modulus effect was confirmed by increasing the drying temperature, where the moduli of latexes (BA5, BA5.5, and BA6) were more similar and the percolation thresholds for three composites also become closer to one another.     

邯钢西区煤气管网改造及效果分析

介绍了邯钢为减少煤气放散，节约能源，采用环网供应混合煤气的有效方法。提高了供气可靠性，取得了很好的经济效益。     

Memory of Distributed Computer Systems: Distinctive Features of Their Architectural-Structural Organization and Use

Distinctive features of architectural-structural organization and use of memory networks are considered with the aim of choosing an optimal configuration in designing distributed computer systems.     

Improving Neural Networks for Mechanism Kinematic Chain Isomorphism Identification

Detection of isomorphism among kinematic chains is essential in mechanical design, but difficult and computationally expensive. It has been shown that both traditional methods and previously presented neural networks still have a lot to be desired in aspects such as simplifying procedure of identification and adapting automatic computation. Therefore, a new algorithm based on a competitive Hopfield network is developed for automatic computation in the kinematic chain isomorphism problem. The neural approach provides directly interpretable solutions and does not demand tuning of parameters. We have tested the algorithm by solving problems reported in the recent mechanical literature. Simulation results show the effectiveness of the network that rapidly identifies isomorphic kinematic chains.     

永州电力通信交换网集中操作和维护的实现

分析实现永州电力通信交换网集中操作和维护的必要性，介绍了实现程控交换机远程操作和维护的两种方式，总结在实践过程中所得到的经验和教训。     

广播电视发射台技术指标集中自动测试系统

本文介绍了利用计算机技术、网络技术、三遥技术对广播电视发射技术指标进行实时自动测试的系统，以便进一步为安全优质播出提供技术保证。     

网络管理体系间迁移方法的探讨

本文提出了在异质型互连网络环境下为实现统一的网络管理可能出现的管理信息共享问题。为此，作者深入探讨，分析了目前国外为实现这种管理信息共享所采用的几种迁移方法；协议迁移，接口迁移和ＭＩＢ迁移。     

基于神经网络的智能检索系统

文章首先概述了当前大多数的搜索引擎的主要的弊端；然后着重介绍了智能检索系统的运行基本思路和售用算法，以及该算法在检索领域中运用的优点；最后指出，神经网络运用在检索领域，可解决网络管理中的诸多难题。     

Artificial Neural Network Modeling of Osmotic Dehydration Mass Transfer Kinetics of Fruits

Artificial neural network (ANN) models were developed for the prediction of transient moisture loss (ML) and solid gain (SG) in osmotic dehydration of fruits using process kinetics data from the literature. ANN models for ML and SG were developed based on data over a broad range of operating conditions and ten common processing variables: temperature and concentration of osmotic solution, immersion time, initial water and solid content of the fruit, porosity, surface area, characteristic length, solution-to-fruit mass ratio, and agitation level. The trained models were able to accurately predict the outputs with associated regression coefficients (r) of 0.96 and 0.93, respectively, for ML and SG. These ANN models performed much better than those obtained from linear multivariate regression analysis. The large number of process variables and their wide ranges considered along with their easy implementation in a spreadsheet make them very useful and practical for process design and control.