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.     

分置式牛津型斯特林制冷机的数值分析与实验验证

对分置式牛津型斯特林制冷机进行了数值计算 ,介绍了计算模型考虑到的众多不可逆因素。通过对计算结果与实验结果的对比 ,验证了本文数值计算的准确性 ,说明本文计算模型与数值处理方法是切实可行的     

抗窄带干扰宽带中频数字接收机的设计与实现

讨论了存在强干扰条件下MSK中频数字接收机的频域窄带干扰抑制、伪码快速捕获、MSK相干解调等实现方法。具体实现中提出了基于功率估计的码捕获门限实时调整方案，解决了动态干扰条件下的快速码捕获问题。基于FPGA DSP硬件设计和软件可编程数字信号处理算法，接收机具有较强的适应性和稳定性。     

四川马海毛钢花呢的试制

根据四川马海毛原料资源的品质特性，运用精纺粗做的方法，成功地试制出手感滑糯而富有弹性、光泽明亮悦目，各项物理指标符合FZ/T24002-93标准的四川马海毛纯毛钢花呢，达到了马海毛产品的特殊风格。同时指出四川马海毛制成率偏低。     

建立预算资金行业财务管理中心的探索

会计集中核算制度是财政体制改革的一项重要举措,它对改变现行财政资金分散收付方式发挥了很大的作用.应在会计集中核算的基础上建立行业财务管理中心,并作为会计集中核算改革的进一步深入和补充.探讨了建立行业财务管理中心的重要性和必要性以及行业财务管理中心的模式,并在行业财务管理中心引入融资理念.     

Novel Hyperbranched predominantly Alternating Copolymers Made From A Charge Transfer Complex monomer pair of p-(chloromethyl)styrene and Acrylonitrile via Controlled Living Radical Copolymerization

Summary Novel hyperbranched copolymers were successfully synthesized by the controlled charge transfer complex inimer and living radical copolymerization of p-(chloromethyl)styrene (PCMS) and acrylonitrile (AN). The resulting copolymers were characterized by SEC, NMR, FTIR, DSC and elemental analysis etc.. The influences of reaction conditions, such as the polymerization temperature, the catalyst (CuBr) concentration and the monomer ratio, on the resulting copolymers were investigated in detail. The monomer reactivity ratios were evaluated to be r_PCMS=0.937 and r_AN=0.088 respectively by the Fineman-Ross method. The higher are the polymerization temperature and the ratio of catalyst to monomer, the higher is the branching degree of the resulting copolymer. When the amount of monomer AN was used in excess than that of the monomer PCMS in the raw feed, the hyperbranched predominantly alternating copolymers HP[PCMS-co-AN] could be obtained. These hyperbranched copolymers were successfully used as functional macroinitiators to synthesize the star-shaped poly(PCMS-co-AN)/poly(MMA) block copolymers.     

消减空压机气流脉动方法的探讨

根据气流脉动的机理，提出了解决空压机常见的机组枷管过振动问题的一些具体措施。     

Adaptive weighted outer-product learning associative memory

Associative-memory neural networks with adaptive weighted outer-product learning are proposed in this paper. For the correct recall of a fundamental memory (FM), a corresponding learning weight is attached and a parameter called signal-to-noise-ratio-gain (SNRG) is devised. The sufficient conditions for the learning weights and the SNRG's are derived. It is found both empirically and theoretically that the SNRG's have their own threshold values for correct recalls of the corresponding FM's. Based on the gradient-descent approach, several algorithms are constructed to adaptively find the optimal learning weights with reference to global- or local-error measure.