因素空间理论与知识表示的数学框架(XⅢ)──描述架中概念的结构(2)

本文是［１，１２］的继续，研究描述架中概念的结构；本文讨论后半部分，内容涉及概念内涵与外延的转换，清晰关系的内投影与内变换，概念的结构＊以及有关问题的注记。     

生物小分子与铜锌超氧化物歧化酶相互作用的波谱学研究及其应用

本工作以ESR和NMR为主要手段,并结合其它生化方法,考察了氨基酸、核酸碱基、糖等生命基本物质,和抗坏血酸等生命必需物质与钢锌超氧化物歧化酶的相互作用,实验观测到氨基酸、核酸碱基和抗坏血酸在水溶液中可以与酶中的Cu²⁺作用而使其脱离活性部位,以小分子络合物形式游离在溶液中,同时使酶失活,脱离活性部位的Cu²⁺的比例和酶的失活程度取决于小分子配体的加入量及其与Cu²⁺的络合能力。此外,首次尝试使用ESR方法,并借助氨基酸与酶的作用,考察了铜锌超氧化物歧化酶在盐酸胍变性和热变性过程中的构象变化行为,结果表明这一方法是直观而有效的。     

设备诊断专家系统的层次诊断模型

本文在讨论复杂机电系统故障特征之后,提出了诊断专家系统的层次诊断模型.该模型以对象系统的结构分级为基础,使用作者提出的征兆分析法、功能分析法和综合信号分析法等三种具体诊断方法,得到了分层适应诊断的层次诊断模型.最后介绍了以层次诊断模型为基础的汽车发动机诊断专家系统的概况.     

知识论域、知识拓扑与集合邻域

定义了知识论域和知识拓扑，组建了4种拓扑空间，分析了它们的联系．从拓扑算子与近似算子的复合、近似邻域、拓扑不变性质3个方面研究了各个拓扑空间的性质，提出了集合邻域的概念，研究了它与点邻域的深刻联系和对一般拓扑空间的作用，并以它为手段研究了新组建的拓扑空间．     

《高等数学》学习方法探讨

从高等数学的知识体系及其学习的特点与基本要求入手,论述了学习高等数学的基本方法,即阐述了如何接收信息、如何消化材料和所学知识如何运用等问题。     

A two-echelon base-stock inventory model with Poisson demand and the sequential processing of orders at the upper echelon

We consider a two-echelon inventory system with a number of non-identical, independent ‘retailers’ at the lower echelon and a single ‘supplier’ at the upper echelon. Each retailer experiences Poisson demand and operates a base stock policy with backorders. The supplier manufactures to order and holds no stock. Orders are produced, in first-come first-served sequence, with a fixed production time. The supplier therefore functions as an M/D/1 queue. We are interested in the performance characteristics (average inventory, average backorder level) at each retailer. By finding the distribution of order lead time and hence the distribution of demand during order lead time, we find the steady state inventory and backorder levels based on the assumption that order lead times are independent of demand during order lead time at a retailer. We also propose two alternative approximation procedures based on assumed forms for the order lead time distribution. Finally we provide a derivation of the steady state inventory and backorder levels which will be exact as long as there is no transportation time on orders between the supplier and retailers. A numerical comparison is made between the exact and approximate measures. We conclude by recommending an approach which is intuitive and computationally straightforward.     

Establishing structure-property correlations and classification of base oils using statistical techniques and artificial neural networks

The present paper describes various classification techniques like cluster analysis, principal component (PC)/factor analysis to classify different types of base stocks. The API classification of base oils (Group I-III) has been compared to a more detailed NMR derived chemical compositional and molecular structural parameters based classification in order to point out the similarities of the base oils in the same group and the differences between the oils placed in different groups. The detailed compositional parameters have been generated using and nuclear magnetic resonance (NMR) spectroscopic methods. Further, oxidation stability, measured in terms of rotating bomb oxidation test (RBOT) life, of non-conventional base stocks and their blends with conventional base stocks, has been quantitatively correlated with their NMR and elemental (sulphur and nitrogen) data with the help of multiple linear regression (MLR) and artificial neural networks (ANN) techniques. The MLR based model developed using NMR and elemental data showed a high correlation between the ‘measured’ and ‘estimated’ RBOT values for both training (R=0.859) and validation (R=0.880) data sets. The ANN based model, developed using fewer number of input variables (only NMR data) also showed high correlation between the ‘measured’ and ‘estimated’ RBOT values for training (R=0.881), validation (R=0.860) and test (R=0.955) data sets.     

Oligonucleotide Analogues with Integrated Bases and Backbone. Part 14

The self‐complementary tetrameric propargyl triols 8, 14, 18 , and 21 were synthesized to investigate the duplex formation of self‐complementary, ethynylene‐linked UUAA, AAUU, UAUA, and AUAU analogues with integrated bases and backbone (ONIBs). The linear synthesis is based on repetitive Sonogashira couplings and C‐desilylations (34–72% yield), starting from the monomeric propargyl alcohols 9 and 15 and the iodinated nucleosides 3, 7, 11 , and 13 . Strongly persistent intramolecular H‐bonds from the propargylic OH groups to N(3) of the adenosine units prevent the gg‐type orientation of the ethynyl groups at C(5′). As such, an orientation is required for the formation of cyclic duplexes, this H‐bond prevents the formation of duplexes connected by all four base pairs. However, the central units of the UAUA and AAUU analogues 18 and 14 associate in CDCl₃/(D₆)DMSO 10 : 1 to form a cyclic duplex characterized by reverse Hoogsteen base pairing. The UUAA tetramer 8 forms a cyclic UU homoduplex, while the AUAU tetramer 21 forms only linear associates. Duplex formation of the O‐silylated UUAA and AAUU tetramers is no longer prevented. The self‐complementary UUAA tetramer 22 forms Watson–Crick‐ and Hoogsteen‐type base‐paired cyclic duplexes more readily than the sequence‐isomeric AAUU tetramer 23 , further illustrating the sequence selectivity of duplex formation.