规整填料塔精馏的Marangoni效应

选用 6种代表性物系对陶瓷板波纹和不锈钢丝网规整填料进行全回流精馏实验 ,考察Marangoni效应对规整填料液体流动分布及传质的影响 .结果表明 :对纯有机体系 ,Marangoni效应影响较小 ;而对有机物的水溶液 ,Marangoni效应严重影响着填料的润湿和传质效率     

珍珠岩助滤剂在天然卤水精制中的应用

通过实验 ,得出在天然卤水制小苏打的生产过程中 ,使用珍珠岩助滤剂对天然卤水精制是可行的。     

填料并用对双组分室温硫化导热硅橡胶性能的影响

以α,ω-二羟基聚二甲基硅氧烷为基胶,Si3N4、AlN、Al2O3为导热填料,制备了填充型双组分室温硫化（RTV-2）导热硅橡胶.研究了填料Si3N4/Al2O3或AlN/Al2O3并用对RTV-2硅橡胶导热性能、工艺性能及力学性能的影响.结果表明,当填料的总体积分数为0.45时,对于Si3N4/Al2O3填充体系,随着体系中Al2O3体积分数的增加,RTV-2导热硅橡胶的热导率先升后降、拉伸强度先增后减,而扯断伸长率则呈逐渐升高的趋势,基料的粘度先减后增;当Al2O3的体积分数为0.14时,RTV-2导热硅橡胶的热导率最高、拉伸强度最大,基料的粘度最小,综合性能最佳.对于AlN/Al2O3填充体系,随着体系中Al2O3的体积分数的增加,RTV-2导热硅橡胶的热导率先升后降、拉伸强度及扯断伸长率先减后增,基料的粘度呈上升趋势;当Al2O3的体积分数为0.07时,RTV-2导热硅橡胶具有较好的导热性能和工艺性能,但力学性能偏低.     

Change of short-term memory effect in acute ischemic ventricular myocardium: A computational study

The ionic mechanism of change in short-term memory (STM) during acute myocardial ischemia has not been well understood. In this paper, an advanced guinea pig ventricular model developed by Luo and Rudy was used to investigate STM property of ischemic ventricular myocardium. STM response was calculated by testing the time to reach steady-state action potential duration (APD) after an abrupt shortening of basic cycling length (BCL) in the pacing protocol. Electrical restitution curves (RCs), which can simultaneously visualize multiple aspects of APD restitution and STM, were obtained from dynamic and local S1S2 restitution portrait (RP), which consist of a longer interval stimulus (S1) and a shorter interval stimulus (S2). The angle between dynamic RC and local S1S2 RC reflects the amount of STM. Our results indicated that compared with control (normal) condition, time constant of STM response in the ischemic condition decreased significantly. Meanwhile the angle which reflects STM amount is less in ischemic model than that in control model. By tracking the effect of ischemia on intracellular ion concentration and membrane currents, we declared that changes in membrane currents caused by ischemia exert subtle influences on STM; it is only the decline of intracellular calcium concentration that give rise to the most decrement of STM.     

A resource-aware scheduling algorithm with reduced task duplication on heterogeneous computing systems

To satisfy the high-performance requirements of application executions, many kinds of task scheduling algorithms have been proposed. Among them, duplication-based scheduling algorithms achieve higher performance compared to others. However, because of their greedy feature, they duplicate parents of each task as long as the finish time can be reduced, which leads to a superfluous consumption of resource. However, a large amount of duplications are unnecessary because slight delay of some uncritical tasks does not affect the overall makespan. Moreover, these redundant duplications would occupy the resources, delay the execution of subsequent tasks, and increase the schedule makespan consequently. In this paper, we propose a novel duplication-based algorithm designed to overcome the above drawbacks. The proposed algorithm is to schedule tasks with the least redundant duplications. An optimizing scheme is introduced to search and remove redundancy for a schedule generated by the proposed algorithm further. Randomly generated directed acyclic graphs and two real-world applications are tested in our experiments. Experimental results show that the proposed algorithm can save up to 15.59  % resource consumption compared with the other algorithms. The makespan has improvement as well.     

Approximate inference for dynamic Bayesian networks: sliding window approach

Dynamic Bayesian networks (DBNs) are probabilistic graphical models that have become a ubiquitous tool for compactly describing statistical relationships among a group of stochastic processes. A suite of elaborately designed inference algorithms makes it possible for intelligent systems to use a DBN to make inferences in uncertain conditions. Unfortunately, exact inference or even approximation in a DBN has been proved to be NP-hard and is generally computationally prohibitive. In this paper, we investigate a sliding window framework for approximate inference in DBNs to reduce the computational burden. By introducing a sliding window that moves forward as time progresses, inference at any time is restricted to a quite narrow region of the network. The main contributions to the sliding window framework include an exploration of its foundations, explication of how it operates, and the proposal of two strategies for adaptive window size selection. To make this framework available as an inference engine, the interface algorithm widely used in exact inference is then integrated with the framework for approximate inference in DBNs. After analyzing its computational complexity, further empirical work is presented to demonstrate the validity of the proposed algorithms.     

基于海量搜索历史数据的用户兴趣模型

针对互联网搜索引擎环境中,基于海量搜索历史数据分析用户兴趣的问题,提出一种改进的用户兴趣模型。该模型根据用户搜索的历史数据,结合向量空间模型（ VSM ）和TF-IDF算法,递归地回溯出用户兴趣权重列表。为解决用户兴趣变化和时间性能的问题,该模型引入时间遗忘机制进行动态更新,并在Hadoop分布式系统架构下利用MapReduce分布式编程模型进行实现。实验结果表明,改进的用户兴趣模型的查准率和召回率都能达到50',具有较好的可行性和可用性。     

工业有害废物填埋场渗析液处理设计

根据工业有害废物填埋场渗析液中含有多组份重金属以及水量的不连续性和出水回用的特点 ,采用化学处理法与过滤、吸附相结合的方法处理此渗析液 ,使出水达到国标“农业浇灌用水”标准的要求     

用混合式遗传算法进行给水管网现状分析

将广义简约梯度法(GRG)思想应用于传统遗传算法,提出一种新的混合式遗传算法(HGA),此方法具有很强的全局和局部搜索能力,并且无需复杂的编码、解码过程,可以准确解决多变量、多峰值的给水管网现状分析问题。采用此算法,绝大多数的计算值与实测值的误差可减小到1%以下,能准确反映管网的实际工况。     

Polyesterification and isomerization of maleic anhydride and 1,6-hexane diol as studied by 1H and 13C n.m.r.

The polyesterification and isomerization reaction of 1,6-hexane diol and maleic anydride in a melt without catalyst was studied by ¹³C and ¹H n.m.r. spectroscopy. The structure and concentration of oligoester species during the polyesterification and isomerization were determined depending on the reaction temperature and time. According to the number and configuration of repeating units determined from ¹H n.m.r. spectra kinetics of both reactions were also considered. The degree of isomerization is continuously increasing in the investigated reaction range.