导热环氧树脂灌封料的研制

导热灌封料研制的重点是在导热性，绝缘性，除此之外，同时还要考虑工艺性等，显然，在这些性能中，导热性与绝缘性，耐开裂性与耐热性这两对矛盾的特性要兼容在技术上还是比较困难的，文中的目标是它们之间取得适当的平衡。     

三氯异氰尿酸技术现状和市场发展

介绍了国内外三氯异氰尿酸（TCCA）的生产现状及市场情况，并简要分析了两种主要生产工艺的特点。     

空气中~（131）Ⅰ宽量程连续监测仪

微机控制宽量程碘连续监测仪的原理是基于连续测量活性炭取样盒上累积放射性增长率，而算出碘的瞬时浓度。该监测仪采用井型取样盒，使其对元素碘和有机碘具有大致相同的探测效率。使用高、低量程组合探头，扩大测量范围以及采用特殊设计的运算模式，加热入口空气和稳峰等措施，提高监测仪性能。在测量周期２ｈ，取样流量２．２Ｌ／ｓ时，最低可探测浓度０．５ｍＢｑ／Ｌ，测量范围５×１０￣（－４）～２．５×１０￣４Ｂｑ／Ｌ，５００ｈ长期稳定性好于１％，并具有自动显示、打印、存储和报答等功能，可用于核设施正常运行及一般事故的监测。     

Gaussian mixture density modeling, decomposition, and applications

We present a new approach to the modeling and decomposition of Gaussian mixtures by using robust statistical methods. The mixture distribution is viewed as a contaminated Gaussian density. Using this model and the model-fitting (MF) estimator, we propose a recursive algorithm called the Gaussian mixture density decomposition (GMDD) algorithm for successively identifying each Gaussian component in the mixture. The proposed decomposition scheme has advantages that are desirable but lacking in most existing techniques. In the GMDD algorithm the number of components does not need to be specified a priori, the proportion of noisy data in the mixture can be large, the parameter estimation of each component is virtually initial independent, and the variability in the shape and size of the component densities in the mixture is taken into account. Gaussian mixture density modeling and decomposition has been widely applied in a variety of disciplines that require signal or waveform characterization for classification and recognition. We apply the proposed GMDD algorithm to the identification and extraction of clusters, and the estimation of unknown probability densities. Probability density estimation by identifying a decomposition using the GMDD algorithm, that is, a superposition of normal distributions, is successfully applied to automated cell classification. Computer experiments using both real data and simulated data demonstrate the validity and power of the GMDD algorithm for various models and different noise assumptions.     

Decision learning about production control as machines break down in a flexible manufacturing system

During manufacturing, there are many situations that can affect production performance. Such situations include machine breakdowns, rush orders, order changes, and order delays. When such issues occur, one has to make decisions to try to maintain production efficiency.Human decisions tend to be too late and incomplete in such contingencies. Thus a system that can make better decisions in time to maintain production performance is needed. To achieve this objective, the intelligent decision system described in this paper integrates artificial intelligence, an optimization technique, and simulation to solve such problems. The decision-making logic of the intelligent decision system is described by event graphs. It imitates the manner of human thinking.Self-learning of the decision-making process is used to strengthen the decision quality. In this study, a method of rule induction is applied to build up the self-learning system. There are two subsystems included in this system. One is rule generation and the other is knowledge management. A case for machine breakdowns is presented and discussed. A series of tests designed to validate the self-learning system are presented. These demonstrate that a rule induction method is suitable for constructing the self-learning.     

多个三维刚体运动参数的鲁棒估计算法

本文提出了一种估计多个三维刚体运动参数的鲁棒算法，可以处理包含高斯噪声和出格点的对应点数据，根据贝叶斯统计决策规则和蕴含在问题中的启发式规则，我们将运动参数估计问题转化为极大似然估计过程，实现部分模型拟合。因此，这种优化算法就是估计一组三维运动参数，使对应点数据最大限度地拟合似然函数，从而保证算法的鲁棒性。     

火药燃烧的不均一性引起的初速或然误差的密闭爆发器予估

实践表明,在火炮的装药结构、点大条件和射击条件严格控制下,初速或然误差主要决定于火药身的性能.根据内弹道势平衡理论,该文从理论上证实了初速的散布与火药在爆发器中的燃烧不均一性参量∑'/(1—∑')成正比,其中∑'= 误差主要决定于火药本身的性能.根据内弹道热平衡理论,该文从理论上证实了初速的散布与火药在爆发器中的燃烧不均一性参量∑'/(1—∑')成正比,其中∑'=Γ_0/Γ_0为p～t曲线拐点前,火药的平均燃烧猛度与初始燃烧猛度的比值.进而建立了初速或然误差的密闭爆发器模拟方法,经实际验证,该方法准确可行.     

季铵化壳聚糖催化环氧丙烷与CO2合成碳酸丙烯酯

采用化学键合法,将季铵盐分子负载到生物高分子壳聚糖上,制备了季铵化壳聚糖催化剂,并采用傅里叶变换红外光谱对催化剂进行了表征.表征结果显示,季铵盐羟丙基三甲基氯化铵通过共价键与壳聚糖氨基上的氮原子结合.将该催化剂用于催化环氧丙烷与CO2合成碳酸丙烯酯(PC),考察了反应时间、反应压力和反应温度对PC收率和选择性的影响.在反应温度160 ℃、反应时间6 h、催化剂用量1 mmol、环氧丙烷4 mL的条件下,PC的收率达98%、选择性达99%.反应压力对PC的收率和选择性影响不大.催化剂循环使用5次后,PC的选择性变化不大,PC的收率略有下降.     

Sequential increases and decreases in blood flow stimulates progressive intimal thickening

Exfoliative toxins of approximately 30 kDa produced by Staphylococcus hyicus strains NCTC 10350, 1289D-88 and 842A-88 were purified and specific polyclonal antisera were raised against each of the toxins. It was shown by immunoblot analysis and ELISA that three exfoliative toxins from S. hyicus were antigenically distinct. The three toxins were designated ExhA, ExhB and ExhC. From 60 diseased pigs, each representing an outbreak of exudative epidermitis, a total of 584 isolates of S. hyicus were phage typed and tested for production of exfoliative toxin. ExhA-, ExhB- and ExhC-producing S. hyicus isolates were found in 12 (20%), 20 (33%) and 11 (18%), respectively, of the 60 pig herds investigated. Production of the different types of exfoliative toxin was predominantly associated with certain phage groups. However, toxin production was found in all of the six phage groups defined by the phage typing system. Some changes in the distribution of isolates between phage groups were observed when the results of this study were compared to previous investigations. In this study two new antigenically distinct exfoliative toxins were isolated and tools for in vitro detection of toxin producing S. hyicus isolates and for further studies on the exfoliative toxins from S. hyicus have been provided.     

Non-linear learning control of robot manipulators without requiring acceleration measurement

A new class of non-linear learning control laws is introduced for a robot manipulator to track a given trajectory in performing a series of tasks. The learning control scheme is applicable to robots with both resolute and prismatic joints, requires only position and velocity feedback, and removes the acceleration measurement required by the existing results. It has been shown that under the proposed learning control the tracking errors are always guaranteed to be asymptotically stable with respect to the number of trials. The proposed control is robust in the sense that exact knowledge about the non-linear dynamics is not required except for bounding functions on the magnitudes. In addition, the new learning scheme can be used without assumptions such as repeatability of robot motion, repeatability of tasks and resetting of initial tracking errors.