农户信用评估系统的设计与运用研究

农户信用评估的研究对推动农村消费信用的发展，促进农村经济良好运行十分重要。本在构造农户信用评估的指标体系的基础上，提出了农户信用评估神经网络模型的算法，利用实际搜集到的农户资料进一步建立了农户信用评估模型，继而构造了农户信用评估系统，并举例说明了该系统的实际运用，以期能为农村经济发展中的农户信用评价及相关研究提供一丝基础性启发。     

基于几何不变量的蛋白质三维分子结构比对

为了解决蛋白质三维结构比对需要处理大量的旋转、平移变换，直接用动态规划将变得十分繁琐这一问题，在保留蛋白质空间结构属性特征的基础上，对蛋白质三维数据进行了预先的处理．通过计算蛋白质结构在旋转和平移下的几何不变量，将蛋白质的三维结构坐标变换为具有旋转、平移不变性的一维序列．进一步给出了“距离”以及“相似得分”的定义．在此基础上采用动态规划方法给出了新的蛋白质结构比对算法．对专家分类的蛋白质结构数据库进行测试，结果显示准确、快速．     

基于人工神经网络的商业银行信用风险模型

在对人工神经网络的基本原理进行简要介绍的基础上 ,着重对构建商业银行信用风险的人工神经网络模型进行了研究 ,实证结果表明 ,人工神经网模型具有很高的预测精度     

A simple Markov chain structure for the evolution of credit ratings

We focus on continuous Markov chains as a model to describe the evolution of credit ratings. In this work it is checked whether a simple, tridiagonal type of generator provides a good approximation to a general one. Three different tridiagonal approximations are proposed and their performance is checked against two generators, corresponding to a volatile and a stable period, respectively. Copyright © 2007 John Wiley & Sons, Ltd.     

价格与隐含远期违约概率

如同根据布莱克-斯科尔斯模型从欧式看涨期权市场价格中反求隐含波动率一样,从信用违约互换的价格中提取隐含违约概率在理论上和实践上都存在很多困难.传统的自助法存在很大的缺点,并有可能得出不符合现实的结果.本文采用基于一段时期的条件违约概率的新的优化方法来替代基于自助法的瞬时远期违约概率,该方法有很多优良特性,会得出比传统方法好得多的结论.     

Reverse-docking as a computational tool for the study of asymmetric organocatalysis

A novel methodology for 'reverse-docking' a cationic peptide-based organocatalyst to a rigid anionic transition state (TS) model for the conjugate addition of azide to alpha,beta-unsaturated carbonyl substrates is described. The resulting docking poses serve as simplified TS models for enantioselective catalysis. Molecular mechanics-based scoring and ranking of the docking poses, followed by clustering and structural analysis, reveal a clear energetic preference for docking to the S-enantiomeric azidation TS model, in agreement with experiment. Clear energetic trends emerged from docking the catalyst to both enantiomers of all six azidation TS models of this study. Structural analysis of the most favorable pose suggests a mechanism for enantioselective catalysis that is consistent with principles of molecular recognition, catalysis, and experimental data.     

绿色供应链中消费者信用支付策略研究

本文考虑了一个由单一供应商和单一电商平台组成的绿色供应链,分析了三种不同支付策略(立即支付策略、分期付款策略以及最低还款策略)对供应链成员最优决策和利润的影响。研究表明:(1)免息期敏感系数对绿色营销水平和供应链成员利润均有正向影响。(2)信用支付会使产品产生溢价现象。但在一定条件下,信用支付策略可同时提高供应链成员利润和绿色营销水平,实现经济绩效和环境绩效的双赢。(3)手续费率较高时,若信用期限系数较小,立即支付策略最优;若信用期限系数适中,分期付款策略最优;否则最低还款策略最优。手续费率较低且信用期较小时,最低还款策略最优,否则立即支付策略最优。在此基础上,针对两种信用支付模型设计了成本分担和收益共享的组合契约,实现了供应链协调。     

Evaluation of docking/scoring approaches: A comparative study based on MMP3 inhibitors

An increasing number of docking/scoring programs are available that use different sampling and scoring algorithms. A reliable scoring function is the crucial element of such approaches. Comparative studies are needed to evaluate their current capabilities. DOCK4 with force field and PMF scoring as well as FlexX were used to evaluate the predictive power of these docking/scoring approaches to identify the correct binding mode of 61 MMP-3 inhibitors in a crystal structure of stromelysin and also to rank them according to their different binding affinities. It was found that DOCK4/PMF scoring performs significantly better than FlexX and DOCK4/FF in both ranking ligands and predicting their binding modes. Most notably, DOCK4/PMF was the only scoring/docking approach that found a significant correlation between binding affinity and predicted score of the docked inhibitors. However, comparing only those cases where the correct binding mode was identified (scoring highest among sampled poses), FlexX showed the best `fine tuning' (lowest rmsd) in predicted binding modes. The results suggest that not so much the sampling procedure but rather the scoring function is the crucial element of a docking program.     

Modified AutoDock for accurate docking of protein kinase inhibitors

Protein kinases are an important class of enzymes controlling virtually all cellular signaling pathways. Consequently, selective inhibitors of protein kinases have attracted significant interest as potential new drugs for many diseases. Computational methods, including molecular docking, have increasingly been used in the inhibitor design process [1]. We have considered several docking packages in order to strengthen our kinase inhibitor work with computational capabilities. In our experience, AutoDock offered a reasonable combination of accuracy and speed, as opposed to methods that specialize either in fast database searches or detailed and computationally intensive calculations.However, AutoDock did not perform well in cases where extensive hydrophobic contacts were involved, such as docking of SB203580 to its target protein kinase p38. Another shortcoming was a hydrogen bonding energy function, which underestimated the attraction component and, thus, did not allow for sufficiently accurate modeling of the key hydrogen bonds in the kinase-inhibitor complexes.We have modified the parameter set used to model hydrogen bonds, which increased the accuracy of AutoDock and appeared to be generally applicable to many kinase-inhibitor pairs without customization. Binding to largely hydrophobic sites, such as the active site of p38, was significantly improved by introducing a correction factor selectively affecting only carbon and hydrogen energy grids, thus, providing an effective, although approximate, treatment of solvation.     

Reverse fragment based drug discovery approach via simple estimation of fragment contributions

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