Linear scaling local correlation approach for solving the coupled cluster equations of large systems

A linear scaling local correlation approach is proposed for approximately solving the coupled cluster doubles (CCD) equations of large systems in a basis of orthogonal localized molecular orbitals (LMOs). By restricting double excitations from spatially close occupied LMOs into their associated virtual LMOs, the number of significant excitation amplitudes scales only linearly with molecular size in large molecules. Significant amplitudes are obtained to a very good approximation by solving the CCD equations of various subsystems, each of which is made up of a cluster associated with the orbital indices of a subset of significant amplitudes and the local environmental domain of the cluster. The combined effect of these two approximations leads to a linear scaling algorithm for large systems. By using typical thresholds, which are designed to target an energy accuracy, our numerical calculations for a wide range of molecules using the 6-31G or 6-31G* basis set demonstrate that the present local correlation approach recovers more than 98.5% of the conventional CCD correlation energy.     

Molecular conformation search by distance matrix perturbations

Three-dimensional molecular structure is fundamental in chemical function identification and computer-aided drug design. The enumeration of a small number of feasible conformations provides a rigorous way to determine the optimal or a few acceptable conformations. Our contribution concerns a heuristic enhancement of a method based on distance geometry, typically in relation with experiments of the NMR type. Distance geometry has been approached by different viewpoints; ours is expected to help in several subtasks arising in the process that determines 3D structure from distance information. More precisely, the input to our algorithm consists of a set of approximate distances of varying precision; some are specified by the covalent structure and others by Nuclear Magnetic Resonance (NMR) experiments (or X-ray crystallography which, however, requires crystallization). The output is a valid tertiary structure in a specified neighborhood of the input. Our approach should help in detecting outliers of the NMR experiments, and handles inputs with partial information. Moreover, our technique is able to bound the number of degrees of freedom of the conformation manifold. We have used numerical linear algebra algorithms for reasons of speed, and because they are well-implemented, fully documented and widely available. Our main tools include, besides distance matrices, structure-preserving matrix perturbations for minimizing singular values. Our MATLAB (or SCILAB) implementation is described and illustrated.AMS subject Classification: 92E10 Molecular structure, 92C40 Biochemistry, molecular biology, 65F15 Eigenvalues, eigenvectors, 15A18 Eigenvalues, singular values, and eigenvectors     

A Novel Preprocessing Algorithm for Three-Way HPLC Data

Orthogonal signal correction (OSC) was a data preprocessing algorithm. It ensured that the filtered information was irrelevant to concentration data while using it to filter the noise from the original data. This paper extended the OSC application range from two-way data to three-way data. Two drug data sets, Enoxacin, Norfloxacin, Ciprofloxacin and Betamethasone, cortisone acetate, prednisone acetate, showed that the application of the OSC algorithm to three-way HPLC data was feasible and needed further research.     

Properties of a genetic algorithm extended by a random self-learning operator and asymmetric mutations: A convergence study for a task of powder-pattern indexing

Genetic algorithms represent a powerful global-optimisation tool applicable in solving tasks of high complexity in science, technology, medicine, communication, etc. The usual genetic-algorithm calculation scheme is extended here by introduction of a quadratic self-learning operator, which performs a partial local search for randomly selected representatives of the population. This operator is aimed as a minor deterministic contribution to the (stochastic) genetic search. The population representing the trial solutions is split into two equal subpopulations allowed to exhibit different mutation rates (so called asymmetric mutation). The convergence is studied in detail exploiting a crystallographic-test example of indexing of powder diffraction data of orthorhombic lithium copper oxide, varying such parameters as mutation rates and the learning rate. It is shown through the averaged (over the subpopulation) fitness behaviour, how the genetic diversity in the population depends on the mutation rate of the given subpopulation. Conditions and algorithm parameter values favourable for convergence in the framework of proposed approach are discussed using the results for the mentioned example. Further data are studied with a somewhat modified algorithm using periodically varying mutation rates and a problem-specific operator. The chance of finding the global optimum and the convergence speed are observed to be strongly influenced by the effective mutation level and on the self-learning level. The optimal values of these two parameters are about 6 and 5%, respectively. The periodic changes of mutation rate are found to improve the explorative abilities of the algorithm. The results of the study confirm that the applied methodology leads to improvement of the classical genetic algorithm and, therefore, it is expected to be helpful in constructing of algorithms permitting to solve similar tasks of higher complexity.     

Flotation-spectrophotometric method for the determination of mercury using iodide and brilliant green

This paper describes a sensitive spectrophotometric method for the determination of mercury, based on the flotation of a mercury iodide-brilliant green complex with cyclohexane at pH 5 and dissolution of the complex in acetone. The absorbance of the complex is measured at 625 nm. Beer's law is obeyed from 4–500 g/l of mercury. The method is highly sensitive ( = 5.96 × 10⁵ 1 mol^–1 cm^–1) and selective, as it is free from interferences by almost all cations and anions in the presence of EDTA. Furthermore, a two-level orthogonal array design as a chemometric method has been used for optimization of the various parameters involved. The method has been successfully applied to paper industry effluents.     

Dissociation equilibrium between uncharged and charged local anesthetic lidocaine in a surface-adsorbed film

The dissociation equilibrium between uncharged local anesthetic lidocaine (LC) and charged local anesthetic LC (LCH⁺) in a surface-adsorbed film was investigated by measuring the surface tension and pH of aqueous solutions of a mixture of hydrochloric acid and LC. The surface tension values decreased slightly with increasing total molality m_t at 0X₂0.5, where X₂ is the mole fraction of LC in the mixture, while they decreased rapidly with increasing m_t at 0.5<X₂1. It was shown from the pH measurements that almost all LC molecules were changed into LCH⁺ ions by protonation at 0X₂0.5 and both forms coexisted only at 0.5<X₂1. The quantities of the respective LC and LCH⁺ transferred from the aqueous solution to the adsorbed film, i.e., their surface densities, were calculated by applying the thermodynamic equations derived to the surface tension and pH data. A greater quantity of LC than LCH⁺ existed in the adsorbed film at the coexisting composition. The partitioning behavior of LC and LCH⁺ in the adsorbed film was characterized by three composition regions: (1) slight partitioning of low surface-active LCH⁺ in the region at 0X₂0.5, (2) preferential partitioning of LC at 0.5<X₂<around 0.7, and (3) negative partitioning of LCH⁺ at around 0.7X₂1. The present results clearly indicate that uncharged local anesthetics transfer into hydrophobic environments such as cell membranes more than charged ones.     

多组分光谱相关色谱及其在中药色谱指纺图谱分析中的应用

基于正交投影理论和相关色谱方法提出多组分光色谱方法提出多组分光谱相关 色谱。为克服联用色谱仪器的不等性噪声影响，采用目标组分投影前后的光谱夹角 余弦判据，判断不同的中药色谱指纹图谱的相关组分色谱峰簇。该方法为中药指纹 图谱的数据处理、合理评价以及中药谱效学的基本理论研究提供一种实用的工具。     

Fermentation characteristics and the dynamic trend of chemical components during fermentation of Massa Medicata Fermentata

As a representative of traditionally fermented Chinese medicine, Massa Medicata Fermentata (MMF) shows the functions of invigorating the spleen and stomach and promoting digestion, which plays an important role in the treatment of gastrointestinal diseases. The fermentation mechanism and the key factors that affect the quality of MMF have not been revealed yet, which has become an urgent issue that limits its clinical application. This article aims to systematically and comprehensively reveal the transformation of physical properties and the dynamic trend of chemical components including substrate components, volatile components, and lactic acid as anaerobic fermentation product during MMF fermentation. Along with obvious hyphae growth observed for MMF, the weight of MMF decreased, and the moisture and temperature increased. Through the quantified 14 components from substrate, ferulic acid increased from 45.53 ± 6.94 to 141.89 ± 78.40 μg/g, while glycosides and phenolic acids declined except caffeic acid. Also, within the 66 volatile components analyzed, alcohols and acids increased, while aldehydes and ketones decreased. Lactic acid was not detected in the fermentation substrate, but an apparent increase in lactic acid content was observed along with the increased fermentation days, resulting in 2.54 ± 0.15 mg/g on day 8. Based on the tested components, the fermentation process of MMF was discriminated into three distinct stages by principal component analysis, and an optimal fermentation time of four days was proposed. The results of this study will be of great significance to clarify the characteristics of fermentation and conduce to improving quality standards of MMF.     

柠檬酸在D354树脂上的离子交换研究

研究了大孔型弱碱性阴离子交换树脂Ｄ３５４分离水中柠檬酸的相平衡和动力学。Ｌａｎｇｍｕｉｒ方程能够良好地关联等温线。建立了离子交换过程的孔扩散模型，并以正交配置法与Ｇｅａｒ法结合进行数据拟合。结果表明，液膜阻力对交换过程具有重大影响，简单线性推动力模型能够很好地描述液膜传质过程。     

军民融合背景下地方政府支持与民企参军行为的演化博弈研究

民参军是军民融合的重要组成内容,政府支持对于民参军的顺利进行发挥着关键作用。本文通过建立军民融合背景下的地方政府支持与民企参军行为的演化博弈模型,考察了参与者的决策演化过程,分析了参与者的进化稳定策略及影响因素。研究表明,增加地方政府对民企的资金奖励、加大民企参军税收优惠、民企资金收益率的提升,以及积极参军成本的降低,会使民企策略选择向积极参军方向演化,但却使地方政府行为向弱力度支持策略演化;而提升中央政府对地方政府的资金补助,降低地方政府支持民企积极参军的服务成本,不仅促使民企选择积极参军策略,还能促使地方政府选择强力度支持策略。最后,对模型结果进行算例分析,验证了结论的合理性。研究结果可以为当前民参军实践提供一定的理论指导。