FCC汽油降烯烃技术进展

介绍了近年来国内外FCC汽油降烯烃的技术进展，并对FCC汽油降烯技术及相关措施的未来应用前景进行了分析。     

过氧化脲牙齿美白剂开发及应用研究进展

过氧化脲可通过持续释放活性氧达到牙齿美白的目的，适用于各种原因引起的着色牙齿的美白。它可同时美白多个牙齿，美白效率高、费用低、使用方便和刺激性小，详细介绍了国内外专利配方及其使用效果；总结了国内外对过氧化脲牙齿美白剂的应用研究和对牙釉质、牙本质的影响；指出了国外研究的发展趋势，结合我国的实际情况对我国开发过氧化脲牙齿美白剂的方向提出了建议。     

Laboratory study of air-water-coal combustion product (fly ash and FGD solid) mercury exchange

Recent laboratory research has indicated that coal fly ash derived from subbituminous and bituminous type coals is a sink for atmospheric mercury (Hg), however lignite-based ash was found to emit Hg to the air. Solids collected from systems with components that enhance Hg removal (i.e. activated carbon injection (ACI), flue gas desulfurization (FGD), and selective catalytic reduction (SCR) or selective non-catalytic reduction (SNCR)) may have higher Hg concentrations and therefore a higher potential for Hg release. For this study we investigated the potential for Hg release to the air and water from coal combustion products (CCPs) collected from coal-fired units with FGD equipment, SCR and SNCR equipment, and sorbent injection for Hg removal. In the laboratory study, most dry samples acted as sinks for atmospheric Hg in the dark at 25 °C. When exposed to light or increased temperature (45 °C), deposition of Hg to the fly ash substrates in most cases continued but decreased. Wet FGD samples emitted Hg. However, they became a sink for atmospheric Hg or exhibited low Hg emission rates when dried. Mercury flux in the dark at 25 °C was correlated with fly ash carbon content (LOI). Most liquid extracts derived using the synthetic precipitation leaching procedure (SPLP EPA method 1312) had very low Hg concentrations (<13 ng/l).     

高效节能水力旋流器研究进展

综合介绍了国内外高效节能水力旋流器的研究进展,分析了影响旋流器分离性能和能耗的主要因素,介绍了针对不同问题提出的相应解决办法.对其迄今的研究成果进行了简要评述,并对其发展进行了展望。     

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.