Entropic criterion for model selection

Model or variable selection is usually achieved through ranking models according to the increasing order of preference. One of methods is applying Kullback–Leibler distance or relative entropy as a selection criterion. Yet that will raise two questions, why use this criterion and are there any other criteria. Besides, conventional approaches require a reference prior, which is usually difficult to get. Following the logic of inductive inference proposed by Caticha [Relative entropy and inductive inference, in: G. Erickson, Y. Zhai (Eds.), Bayesian Inference and Maximum Entropy Methods in Science and Engineering, AIP Conference Proceedings, vol. 707, 2004 (available from arXiv.org/abs/physics/0311093)], we show relative entropy to be a unique criterion, which requires no prior information and can be applied to different fields. We examine this criterion by considering a physical problem, simple fluids, and results are promising.     

几种改进的CoMFA方法比较研究血小板活化因子拮抗剂

由于传统的比较分子场分析(CoMFA)方法本身存在一些缺陷，使得分子的叠合 规则以及叠合分子的空间取向和空间位置等因素对q~2的影响很大，因此相继提出 了几种改进的CoMFA方法。为了优化CoMFA结果，应用传统的CoMFA方法和交叉验证 的R~2引导的区域选择法(q~2-GRS)、全取向搜索法（AOS）、全空间搜索法（APS） 以及比较分子相似性指数(CoMSIA)等四种改进的CoMFA方法，对18个pinusolide类 衍生物这类新发现的血小板活化因子（PAF）拮抗剂进行了比较研究。结果表明四 种改进的CoMFA方法得到的q~2值均比传统CoMFA的高。q~2-GRS方法得到的q~2值有 所提高，但综合结果并不理想，AOS与APS得到的q~2较为理想，而在CoMSIA中， q~2几乎不受空间取向或空间位置的影响。同时我们引人基于样本的偏最小二乘法 （SAMPLS）取代原AOS／APS程序中的传统PLS进行统计分析，明显提高了其运行速 度。最后，根据q~2最高的CoMFA模型和CoMSIA模型设计了几个预测活性更高的 pinusolide类似物。     

一种模拟沸石分子筛扩散反应的Monte Carlo方法

在考虑了沸石分子筛中吸附、脱附、扩散和反应的特点的基础上，发展了一种模拟沸石分子筛中扩菜反应的ＭｏｎｔｅＣａｒｌｏ方法。用Ｌａｎｇｍｕｉｒ吸附等温式验证了该方法的合理性，并证明了轰击频率λ代表了反应物气相压力，而吸附、脱附几率之比即为吸附平衡常数。同时，通过改变轰击频率λ和反应几率Ｐｔ，得到了吸附等温线和有效因子随Ｔｈｉｅｌｅ模数变化的曲线。     

Diffusion in organic solvents: Interdiffusion coefficient of 1,1,2,2-tetrabromoethane

Interdiffusion coefficient have been measured for 1,1,2,2-tetrabromoethane in 21 organic solvents in order to ascertain the influence of shape, size, viscosity, nature and degree of branching, of the solvent molecules on transport properties. None of the existing correlations for diffusion in binary liquid systems appear to fit all the experimental data. Steric effects due to the solvent molecules are shown to be very important in the interpretation of the diffusion process.     

载铂铝交联蒙脱土的烷烃芳构化特性──Ⅰ．载铂铝交联蒙脱土对烷烃的择形芳构化作用

对比考察了Ｐｔ／ＫＬ沸石，Ｐｔ／Ａｌ２Ｏ３和载铂铝交联蒙脱土（Ｐｔ／Ａｌ－ＣＬＭ）催化剂对不同碳原子数烷烃的芳构化特性．脉冲微反的评价结果表明：Ｐｔ／Ａｌ－ＣＬＭ比Ｐｔ／Ａｌ２Ｏ３和Ｐｔ／ＫＬ具有较高的转化ｎ－Ｃ８，ｎ－Ｃ９为其对应芳烃的选择性，在转化ｎ－Ｃ８时，产物中的间、对位二甲苯收率很高，而转化ｎ－Ｃ９时有高的正丙苯收率．采用１２９Ｘｅ－ＮＭＲ、ＸＲＤ和孔分布测定考察了Ｐｔ／Ａｌ－ＣＬＭ和Ｐｔ／ＫＬ、Ｐｔ／Ａｌ２Ｏ３之间孔结构的差异．结果表明：由于ｎ－Ｃ８，ｎ－Ｃ９在反应过程中其过渡态的极限尺寸与Ｐｔ／Ａｌ－ＣＬＭ０．９ｎｍ左右的层间域相匹配，因而它对ｎ－Ｃ８，ｎ－Ｃ９具有择形芳构化作用．     

Molecular shape effects and quantum theory

Certain features of the chemist's molecular structure model, viz. size and shape, are retrieved even in the best non-adiabatic variational calculations thus far carried out for ground states of H ₂ ⁺ and H₂. Those features do not conflict with the full symmetry of exact molecular eigenstates, once they are properly understood as correlation effects.     

Phase Relations in the Ni–Mn–Ga Ternary System and Aging Effect on Shape Memory Properties of Ferromagnetic Ni<Subscript>2</Subscript>MnGa Sputtered Films

Summary. Isothermal sections of the Ni–Mn–Ga ternary phase diagram at 1073 and 1273 K were investigated over a wide range of alloy compositions. The range of the β-Ni₂MnGa phase, its equilibria with the γ-(Mn, Ni), α′-Ni₃Ga, and γ-Ni₃Ga₂ phases, and the liquidus and solidus lines were determined experimentally. The aging effect on the shape memory effect (SME) of Ni₂MnGa sputtered films was also investigated. The two-way SME of the constraint-aged films was confirmed by the temperature change.     

双头基两亲分子研究进展

本文介绍了双头基两亲分子的结构特征与性质, 概述了由双头基两亲分子在气液界面形成的单分子膜以及在体相中形成的囊泡的特征, 并介绍了这类两亲分子在催化、生物矿化、药物缓释、膜破解以及纳米材料等方面的应用研究。对其研究前景进行了展望。     

A combination of modified particle swarm optimization algorithm and support vector machine for gene selection and tumor classification

In the analysis of gene expression profiles, the number of tissue samples with genes expression levels available is usually small compared with the number of genes. This can lead either to possible overfitting or even to a complete failure in analysis of microarray data. The selection of genes that are really indicative of the tissue classification concerned is becoming one of the key steps in microarray studies. In the present paper, we have combined the modified discrete particle swarm optimization (PSO) and support vector machines (SVM) for tumor classification. The modified discrete PSO is applied to select genes, while SVM is used as the classifier or the evaluator. The proposed approach is used to the microarray data of 22 normal and 40 colon tumor tissues and showed good prediction performance. It has been demonstrated that the modified PSO is a useful tool for gene selection and mining high dimension data.