极限分析的无搜索数学规划算法

本文研究理想刚塑性介质极限载荷因子的计算方法。根据极限分权理论的上限定理,建立了计算极限载荷因子的一般数学规划有限元格式。针对这种格式的特点,提出了一个求解极限载荷因子的无搜索迭代算法。这个算法中采用逐步识别刚性、塑性分区,不断修正目标函数的方案,克服了目标函数非光滑所导致的困难。本文提出的算法建立于位移模式有限元基础上,有较广的适用范围,且具有计算效率高,稳定性好,格式简单易于程序实现等优点。     

Development of a fluorescence model for the determination of constants associated with binding,quenching, and Förster resonance energy transfer efficiency

Determining accurate dissociation constants for equilibrium processes involving a fluorescent mechanism can prove to be quite challenging. Typically, titration curves and nonlinear least squares fitting of the data using computer programs are employed to obtain such constants. However, these approaches only consider the total fluorescence signal and often ignore other energy transfer processes within the system. The current model considers the impact on fluorescence from equilibrium binding (viz., metal-ligand, ligand-substrate, etc.), quenching, and resonance energy transfer. This model should provide more accurate binding constant as well as insights into other photonic processes. The equations developed for this model are discussed and are applied to experimental data from titrimetric experiments. Since the experimental data are generally in excess of the number of parameters that are needed to define the system, fitting is operated in an overdetermined mode and employs error minimization (either absolute or relative) to define goodness of fit. Examples of how changes in certain parameters affect the shape of the titrimetric curve are also presented. The current model does not consider chelation-enhanced fluorescence.     

UV–vis absorption spectroscopic study for on-line monitoring of uranium concentration in LiCl–KCl eutectic salt

UV–vis absorption spectroscopy of uranium in LiCl–KCl eutectic salt at 773 K was studied for the on-site use in pyrochemical process. Uranium(III) chloride was electrochemically prepared from uranium metal in LiCl–KCl eutectic salt at 773 K by using chronopotentiometry. Three absorption peak positions were selected and calibrated for the quantitative analysis of uranium in the molten salt medium. The molar absorptivity and minimum detectable concentration for the selected wavelength were obtained with a confidence level of 99%.     

Determination of metabolites in Uncaria sinensis by HPLC and GC-MS after green solvent microwave-assisted extraction

Uncaria sinensis (Oliv.) Havil (Rubiaceae) has been used as an important Traditional Chinese Medicine (TCM) herb for the treatment of fevers and various nervous disorders. The major bioactive secondary metabolites from different classes of chemical compounds, i.e. organic acid, flavonoid and alkaloid, present in this TCM herb, namely catechin, caffeic acid, epicatechin and rhynchophylline, were extracted by microwave-assisted extraction (MAE) method with ultra-pure water as the extraction solvent. The optimal extraction conditions for this green solvent MAE method were found to be 100 °C for 20 min. The recoveries of the compounds were found to be comparable to that of heating under reflux using ultra-pure water for 60 min. The method precision (RSD, n = 6) was found to vary from 0.19% to 5.60% for the proposed method on different days for the secondary metabolites. Simultaneously, the key primary metabolites such as sucrose and phenylalanine for the biosynthesis of bioactive secondary metabolites were successfully characterized by GC-MS. Furthermore, an approach using the combination of primary and secondary metabolite profiling based on their chemical fingerprints with Principal Component Analysis (PCA) was successfully developed to evaluate the quality of U. sinensis obtained from different sources. This approach was shown to be feasible in discriminating U. sinensis from different origins and thus a potential application for the quality control of other medicinal herbs.     

素食人群尿液1H NMR代谢轮廓的多因素方差分析

结合方差分析(ANOVA)和偏最小二乘法判别分析(PLS-DA)两种分析技术,对素食和普食人群的尿液1H NMR谱进行分析.利用ANOVA方法将数据矩阵分解为几个独立因素矩阵,滤除干扰因素后,再利用PLS-DA对单因素数据进行建模分析.实验结果表明,ANOVA/PLS-DA方法可以有效地减少饮食因素和性别因素之间的相互...     

An adaptive network based fuzzy inference system–auto regression–analysis of variance algorithm for improvement of oil consumption estimation and policy making: The cases of Canada,United Kingdom,and South Korea

This paper presents an adaptive network based fuzzy inference system (ANFIS)–auto regression (AR)–analysis of variance (ANOVA) algorithm to improve oil consumption estimation and policy making. ANFIS algorithm is developed by different data preprocessing methods and the efficiency of ANFIS is examined against auto regression (AR) in Canada, United Kingdom and South Korea. For this purpose, mean absolute percentage error (MAPE) is used to show the efficiency of ANFIS. The algorithm for calculating ANFIS performance is based on its closed and open simulation abilities. Moreover, it is concluded that ANFIS provides better results than AR in Canada, United Kingdom and South Korea. This is unlike previous expectations that auto regression always provides better estimation for oil consumption estimation. In addition, ANOVA is used to identify policy making strategies with respect to oil consumption. This is the first study that introduces an integrated ANFIS–AR–ANOVA algorithm with preprocessing and post processing modules for improvement of oil consumption estimation in industrialized countries.     

Decomposing profit inefficiency in DEA through the weighted additive model

An issue that has received little attention in the Data Envelopment Analysis literature is the decomposition of profit inefficiency by means of measures that account all sources of technical inefficiency. In this paper we introduce a new way to measure and decompose profit inefficiency through weighted additive models. All our results are derived from a new Fenchel-Mahler inequality using duality theory.     

Forensic examination of ink by high-performance thin layer chromatography--the United States Secret Service Digital Ink Library

Forensic examinations of ink have been performed since the beginning of the 20th century. Since the 1960s, the International Ink Library, maintained by the United States Secret Service, has supported those analyses. Until 2009, the search and identification of inks were essentially performed manually. This paper describes the results of a project designed to improve ink samples' analytical and search processes. The project focused on the development of improved standardization procedures to ensure the best possible reproducibility between analyses run on different HPTLC plates. The successful implementation of this new calibration method enabled the development of mathematical algorithms and of a software package to complement the existing ink library.     

PLS分析与RBF神经网络耦合环境模型

鉴于城市大气环境质量受到诸多复杂因素影响,且各因素间存在多重相关性,本文将偏最小二乘(PLS)分析与人工神经网络径向基网络(RBF)耦合,建立偏最小二乘径向基神经网络模型(PLSRBF),应用于贵阳大气环境质量的检验和预测。实例表明:PLSRBF模型可对原多自变量模型进行降维简化,并可有效提取解释变量信息,防止信息丢失,且具有较强的拟合能力。     

对主成分分析法三个问题的剖析

从主成分分析法的基本原理入手,针对教学过程中学生对主成分分析法感到费解的三个问题进行了逐一剖析:1.为什么主成分系数是经标准差标准化后原始变量的协方差矩阵的特征向量?2.特征向量正负号如何选取?对进一步的研究如计算综合得分和聚类分析有何影响?3.主成分载荷值是如何得来的?同时指出有些教材在计算主成分得分时混淆了主成分载荷和特征向量的概念,以致造成错误的结果.