Phosphorus‐containing polyaryloxydiphenylsilanes with high flame retardance arising from a phosphorus–silicon synergistic effect

Polyaryloxydiphenylsilanes were prepared from phosphorus‐containing diols and diphenydichlorolsilane through solution polymerization. With a stoichiometric imbalance in feed monomers, the resulting polymers exhibited moderate melting points and good processing properties. The polymers prepared showed initial decomposition temperatures above 340 °C, excellent thermal stability, high char yields at 850 °C and very high limited oxygen index values of 56–59. The polymers' char yields and their (P + Si) contents showed linear relationships. © 2003 Society of Chemical Industry     

A Neural Network Approach for Signal Detection in Digital Communications

In this paper, we propose a new approach for signal detection in wireless digital communications based on the neural network with transient chaos and time-varying gain (NNTCTG), and give a concrete model of the signal detector after appropriate transformations and mappings. It is well known that the problem of the maximum likelihood signal detection can be described as a complex optimization problem that has so many local optima that conventional Hopfield-type neural networks fail to solve. By refraining from the serious local optima problem of Hopfield-type neural networks, the NNTCTG makes use of the time-varying parameters of the recurrent neural network to control the evolving behavior of the network so that the network undergoes the transition from chaotic behavior to gradient convergence. It has richer and more flexible dynamics rather than conventional neural networks only with point attractors, so that it can be expected to have much ability to search for globally optimal or near-optimal solutions. After going through a transiently inverse-bifurcation process, the NNTCTG can approach the global optimum or the neighborhood of global optimum of our problem. Simulation experiments have been performed to show the effectiveness and validation of the proposed neural network based method for the signal detection in digital communications.     

无机高分子絮凝剂聚硫酸铁合成条件的研究

实验研究了以工业硫酸亚铁及废硫酸为原料,分别采用NaClo_3、KClO_3、H_2O_2及(o_2+NaNO_2)为氧化剂成聚硫酸铁的条件。在以(O_2+NaNO_2)为氧化剂的合成过程中,发现添加微量助催化剂(型号为HG-1、HG-2和HG-3),对提高合成速度及反应过程的稳定性具有重大作用。     

软X射线对血液有形成分表面电荷的影响——2、淋巴细胞和血小板膜电荷的变化

软X射线不仅能引起红细胞表面电荷的变化,同时也能导致淋巴细胞和血小板表面电荷下降,表现为照射后它们的电泳率下降。低剂量范围内,这种电荷的变化是暂时性的,照后4小时降到最低点,24小时后恢复到对照的水平。细胞电泳率的下降与辐射剂量相关。淋巴细胞是一个复杂的细胞群,正常状态下,按细胞在电场中泳动速度的快慢,可分为两个组分:快峰为T细胞,慢峰为B细胞。软X射线照射以后,T和B细胞的电泳率皆减慢,频数分布峰值下降,离散度加大。血小板成分单一,电泳率较一致。 从照射浓集的血小板再加回自身血浆中电泳率的下降较照射血浆再加到血小板中的电泳率下降大得多;受照射的血小板在磷酸缓冲液中电泳率下降较在血浆悬液中严重得多;2000 rad照后,悬浮于血浆中的血小板电泳率能恢复,而悬浮于磷酸缓冲液中则不能恢复,三个方面来看,血浆中可能存在抗辐射因子。超氧化物岐化酶能有效地预防血小板电泳率的下降,从而可阻止血小板的凝聚。     

DCS在50MW供热机组上的应用

介绍I/A’S系统在巨化热电厂八号50MW供热机组上应用实例,并从DCS系统的整体设计到实现的功能、控制效果等多方面进行了分折,总结了调试和运行经验。     

Effect of surfactants and liquid hydrocarbons on gas hydrate formation rate and storage capacity

Hydrate formation rate plays an important role in making hydrates for the storage and transport of natural gas. Micellar surfactant solutions were found to increase gas hydrate formation rate and storage capacity. With the presence of surfactant, hydrate could form quickly in a quiescent system and the energy costs of hydrate formation reduced. Surfactants (an anionic surfactant, a non‐ionic surfactant and their mixtures) and liquid hydrocarbons (cyclopentane and methylcyclohexane) were used to improve hydrate formation. The experiments of hydrate formation were carried out in the pressure range 3.69–6.82 MPa and the temperature range 274.05–277.55 K. The experimental pressures were kept constant during hydrate formation in each experimental run. The effect of anionic surfactant (sodium dodecyl sulphate (SDS)) on natural gas storage in hydrates is more pronounced compared to a non‐ionic surfactant (dodecyl polysaccharide glycoside (DPG)). The induction time of hydrate formation was reduced with the presence of cyclopentane (CP). Cyclopentane and methylcyclohexane (MCH) could increase hydrate formation rate, but reduced hydrate storage capacity The higher methylcyclohexane concentration, the lower the hydrate storage capacity. Copyright © 2003 John Wiley & Sons, Ltd.     

A distributed adverse drug reaction detection system using intelligent agents with a fuzzy recognition‐primed decision model

Discovering unknown adverse drug reactions (ADRs) in postmarketing surveillance as early as possible is highly desirable. Nevertheless, current postmarketing surveillance methods largely rely on spontaneous reports that suffer from serious underreporting, latency, and inconsistent reporting. Thus these methods are not ideal for rapidly identifying rare ADRs. The multiagent systems paradigm is an emerging and effective approach to tackling distributed problems, especially when data sources and knowledge are geographically located in different places and coordination and collaboration are necessary for decision making. In this article, we propose an active, multiagent framework for early detection of ADRs by utilizing electronic patient data distributed across many different sources and locations. In this framework, intelligent agents assist a team of experts based on the well‐known human decision‐making model called Recognition‐Primed Decision (RPD). We generalize the RPD model to a fuzzy RPD model and utilize fuzzy logic technology to not only represent, interpret, and compute imprecise and subjective cues that are commonly encountered in the ADR problem but also to retrieve prior experiences by evaluating the extent of matching between the current situation and a past experience. We describe our preliminary multiagent system design and illustrate its potential benefits for assisting expert teams in early detection of previously unknown ADRs. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 827–845, 2007.     

Data mining of resilience indicators

In recent years, the Asia-Pacific region has experienced several financial setbacks, including speculative attacks in 1998 and the SARS outbreak in 2003. Financial stresses of this nature are unanticipated, and not all of the dangers can be predicted by the examination of market information and macroeconomic indicators. The Early Warning System (EWS) that has been adopted by the International Monetary Fund may not be able to predict future financial crises for all possible scenarios, because shocks come in many different forms. To supplement the EWS, this paper proposes a data mining framework to measure the resilience of an economy. The resilience framework does not predict a crisis, but rather assesses the current state of health of an economy and its ability to withstand a financial shock should one occur. The framework is based on a feedback system consisting of two stages. The first stage assigns a resilience score to each economy based on a fuzzy logic scoring scheme that is built on the ambiguous reasoning of experts. The second stage uses the classification tree approach to estimate thresholds for each economic indicator, and examines the quality of the fuzzy score. The result from the second stage is then passed back to the first stage as feedback. The final result is obtained when the feedback system reaches its equilibrium state. The proposed resilience framework is applied to the external-sector and the public-sector economies of several countries to illustrate its applicability.     

Sol-Gel Synthesis of Palladium-Doped Silica Nanocomposite Fiber Using Triton X-100 Micelle Template and the Application for Hydrogen Gas Sensing

Palladium-doped silica nanocomposites were synthesized via a sol-gel technique combined with a template of Triton X-100 micelle. The freshly prepared sol sample of Pd-doped silica nanocomposites was investigated by TEM. Determined from the TEM image, the sizes of the Pd nanoparticles are narrowly distributed, which are around 30 nm in diameter. The prepared sol solution of the sample was injected into a Tygon Microbore Autoanalysis tubing. After 14 days gelatinization, a transparent porous optical fiber was obtained. The response of the fiber to hydrogen gas was tested by using a fiber-optic spectrometric method. The palladium-doped silica nanocomposite fiber is sensitive upon exposure to hydrogen gas and the response is reversible. This palladium-doped silica nanocomposite fiber can be applied as a new kind of hydrogen gas sensor