A genetic algorithm for the automated generation of small organic molecules: Drug design using an evolutionary algorithm

Rational drug design involves finding solutions to large combinatorial problems for which an exhaustive search is impractical. Genetic algorithms provide a novel tool for the investigation of such problems. These are a class of algorithms that mimic some of the major characteristics of Darwinian evolution. LEA has been designed in order to conceive novel small organic molecules which satisfy quantitative structure-activity relationship based rules (fitness). The fitness consists of a sum of constraints that are range properties. The algorithm takes an initial set of fragments and iteratively improves them by means of crossover and mutation operators that are related to those involved in Darwinian evolution. The basis of the algorithm, its implementation and parameterization, are described together with an application in de novo molecular design of new retinoids. The results may be promising for chemical synthesis and show that this tool may find extensive applications in de novo drug design projects.     

Application of recombinant phage display antibody system in study of Codakia orbicularis gill proteins

We used the recombinant phage display antibody system (RPAS) to obtain chimeric single-chain fragment variable (ScFv) antibodies to gill proteins of the white clam Codakia orbicularis (Linné, 1758). After three rounds of selection on immunotubes loaded with total gill protein extract, recombinant phages exhibiting antibodies to gill proteins were isolated and tested by enzyme-linked immunosorbent assay (ELISA). Clones exhibiting a high affinity for the mollusk proteins were selected for production of soluble ScFv antibodies, which were purified for subsequent analysis. ScFv antibodies exhibited a reaction specific for a protein whose molecular mass was about 15,000 Daltons and that was detected by the antigen capture technique followed by sodium dodecyl sulfate polyacrylamide gel electrophoresis and Western blotting.     

Bonferroni-type inequalities; Chebyshev-type inequalities for the distributions on [0, n]

An elementary majorant-minorant method to construct the most stringent Bonferroni-type inequalities is presented. These are essentially Chebyshev-type inequalities for discrete probability distributions on the set {0, 1,..., n}, where n is the number of concerned events, and polynomials with specific properties on the set lead to the inequalities. All the known results are proved easily by this method. Further, the inequalities in terms of all the lower moments are completely solved by the method. As examples, the most stringent new inequalities of degrees three and four are obtained. Simpler expressions of Mrgritescu's inequality (1987, Stud. Cerc. Mat., 39, 246–251), improving Galambos' inequality, are given.     

在非时齐马氏决策过程中的动态贝叶斯网络研究

提出了用动态贝叶斯网络（DBN）对非时齐马氏决策系统进行建模的改进方法，使动态贝叶斯网络能被更广泛地应用于各种复杂的真实系统中．该方法的基本思路是，将扩展后的隐藏变量引入DBN的演化过程来建立假设条件所要求的马尔可夫模型，给出从不完整的样本数据集以及存在隐藏变量时来学习DBN结构的算法，进而用贝叶斯概率统计方法对后来的时间片的充分统计因子进行估计，并通过当前已存在的和估计的充分统计因子对基于时间变化的转移概率进行学习，以解决假设条件要求的转移概率的时不变性．原理性分析和仿真实验结果也验证了改进方法的有效性．     

韧性材料的细观力学实验和数值模拟研究

引入能够定量描述内界面的细观统计参量-形状因子,定义了基于内界面形状因子的损伤变量,建立了相应的细观力学模型,探索细观组织演化和材料宏观响应关系的力学问题。通过宏细观相结和的方法,对韧性金属材料的内界面进行实验研究和数值计算。通过对比试验和数值计算结果,认为可以用形状因子能够反映材料细观组织的演化情况,用损伤变量能够表征材料的损伤程度。并得到了内界面演化随应变发展的演化方程。对于发展和应用宏-细观相结合的损伤力学理论,对阐明韧性材料的变形、损伤、破坏机制有重要意义。     

二元函数图形绘制及特征分析实验设计

介绍了二元函数及图形的相关数学知识和mathematica软件平台的相关知识，给出了二元函数及图形特征研究的内容与要求，完成了空间图形及交线、截面、相交面的图形的绘制及相关特征分析的实验设计。     

服务时间依赖于已服务过的顾客数的M[X]/G/1排队系统

研究了每个忙期开始后的前N个顾客接受特别服务M^[x]／G／I排队系统。通过采用补充变量法，推导出系统稳态队长概率母函数的迭代公式。更进一步，得到了系统的平均队长。     

模糊信息静态伯特德双寡头博弈分析

在分析了厂商的市场信息具有模糊性的基础上,分别给出了2个模糊信息静态伯特德双寡头博弈模型,并运用模糊数学理论及方法,分别求出了这两种情形下博弈的均衡解.     

浅析C语言指针的灵活运用及常见错误

针对学生在学习指针过程中遇到的困难及使用指针过程中出现的常见错误,讨论指针的概念、指针与数组的关系、指针与函数的关系、指针作为函数参数的实质,帮助学生克服困难和错误。     

非线性拟双曲方程的特征变网格有限元方法和分析

对神经传播过程中的一类非线性拟双曲方程的初边值问题的三维情形应用常规变换，提出了特征变网格有限元格式，最后通过细致的分析和估计得到了最佳阶的L^2模误差估计结果。