催化褪色法测定痕量硒（Ⅳ）的研究

本研究发现，在盐酸介质中，Ｓｅ（Ⅳ）作活化剂，Ｐｄ~（２＋）催化次磷酸钠与甲基红的褪色反应。同时研究了反应动力学条件，建立了测定痕量Ｓｅ（Ⅳ）的新方法。方法检测限为４．８×１０~（－５）μｇ／ｍＬＳｅ（Ⅳ），测定范围为０～０．０１μｇ／ｍＬＳｅ（Ⅳ）。用于测定人发中的痕量Ｓｅ（Ⅳ），获得了满意结果。     

小波潜变量回归和广义回归神经网络同时测定三组分混合物

本文采用小波潜变量回归（WLVR）方法，同时测定重叠的光谱信号。结合小波阈值法和主组分分析（PCA）改进除噪质量。八个误差判据用于推断因子数目。潜变量由小波处理过的信号投影到正交基矢量而获得。广义回归神经网络（GRNN）被应用于多组分同时测定。依据算法原理编制了三个程序（PWMRA、PWLVR和PGRNN）执行有关计算。三个方法（WLVR、LVR（潜变量回归）和GRNN）同时测定三组分混合物，获得满意的结果。     

催化动力学光度法同时测定痕量铅和镉

在十六烷基三甲基溴化铵（CTAB）存在下，痕量的Pb(Ⅱ）和Cd(Ⅱ）在硼酸－氯化钾－氢氧化钠缓冲体系中，能同时催化过硫酸铵氧化焦锫酚红（PR）而发生褪色指示反应，通过研究该反应的最佳反应条件以及将多元线性回归（MIR）用于数据处理，建立了同时测定铅和镉的新方法，方法已用于废水及铜混中铅和镉的同时测定。     

两次双波长分光光度法测定铅和汞

基于卟啉试剂ＴＡＰＰ与Ｐｂ￣（２＋）、Ｈｇ￣（２＋）在碱性介质中有灵敏的显色反应，建立了两次双波长分光光度法同时测定Ｐｂ、Ｈｇ的新方法，摩尔吸光系数分别为４．５９×１０￣５和４．３２×１０￣５ｍｏｌ￣（－１）·ｃｍ￣（－１）·Ｌ；可同时测定１：５～１０：１范围内的Ｐｂ和Ｈｇ，用于水中Ｐｂ和Ｈｇ的同时测定，结果满意。     

停流流动注射—动力学方法多组份同时测定的研究：铁（Ⅱ）,钛（Ⅲ）和…

依据诱导反应原理，提出了同时测定多组份的动力学方法，并以停流流动注射分析研究了Ｆｅ（Ⅱ），Ｔｉ（Ⅲ）及Ｖ（Ⅳ）诱导的Ｃｒ（Ⅵ）－Ｉ＾－反应体系，建立了铁，钛和钒同时测定的条件。对铁，钛和钒测定的线性范围分别为０－２．２μｇ／ｍｌ，０－３．１μｇ／ｍｌ及０－１．８μｇ／ｍｌ，检测限分别为０．０１２，０．０２０和０．０１８μｇ／ｍｌ。     

同时测定丁二酸,戊二酸和己二酸的两种数据处理方法比较

同时测定丁二酸、戊二酸和己二酸的两种数据处理方法比较董慧茹，董吉源（辽阳石油化工高等专科学校，辽宁１１１００３）（大连港务局）相互干扰的多组分体系，不经分离而应用电位滴定，数学计算法同时测定，已引起了分析工作者的重视，目前已有多篇文献报道了这方面的工...     

流通池—介质交换—阳极溶出伏安法同时测定铜,锑,铋

本文研究了同时测定Ｃｕ（Ⅱ）Ｓｂ（Ⅲ）Ｂｉ（Ⅲ）的方法。在盐酸溶液中对Ｃｕ（Ⅱ），Ｓｂ（Ⅲ），Ｂｉ（Ⅲ）进行预电解富集，经介质交换在选定的丙二酸－盐酸溶液中进行了差示脉冲阳极溶出伏安法（ＤＰＡＳＶ）测定，相邻溶出峰的△Ｆｐ＞８０ｍＶ，波形完好。     

简易电解池—改换介质—阳极溶出伏安法

采用自制的简易电解池，以圆盘旋转玻碳电极为工作电极，用于阳极溶出伏安法改换溶出介质的可行性研究。以同时测定Ｃｕ（Ⅱ），Ｓｂ（Ⅲ）为例，试验了改换溶出介质的条件。此方法用于矿样中铜和锑的同时测定，结果满意。     

线性迭代法同时测定小儿退热灵片中乙酰水杨酸和苯巴比妥的含量

本文利用线性迭代法同时测定了小儿退热灵片中乙酰水扬酸和苯巴比妥的含量。乙酰水杨酸的回收率为９９．６％（ＲＳＤ＝０．５８％，ｎ＝６），苯巴比妥的回收率为１００．４％（ＲＳＤ＝１．６６％，ｎ＝６）。本法测定结果与黑龙江省药品标准方法测定结果基本一致，本法简单，快速，适合该剂剂中两组份的同时测定。     

改良型比光谱-导数分光光度法在四元混合体系同时测定中的应用

提出了可应用于四元混合体系同时测定的比光谱-导数分光光度法，阐述了该方法的基本原理，并将其应用于氨基比林、苯巴比妥、咖啡因和非那西丁四元混合体系中各组分的同时测定。结果表明，氨基比林、笨巴比妥、咖啡因和非那西丁的回收率分别是109．3％（RSD=4．3％）、102．4％（RSD=6．6％）、108.7％（RSD=5．1％）、98．62％（RSD=3．2％）。方法的准确度和精密度都可以满足四组分同时测定的要求，方法简单、快速。     

Analysis of four PCR/SNaPshot multiplex assays analyzing 52 SNPforID markers

The SNPfor ID consortium identified a panel of 52 SNPs for forensic analysis that has been used by several laboratories worldwide. The original analysis of the 52 SNPs was based on a single multiplex reaction followed by two single‐base‐extension (SBE) reactions each of which was analyzed using capillary electrophoresis. The SBE assays were designed for high throughput genetic analyzers and were difficult to use on the single capillary ABI PRISM 310 Genetic Analyzer and the latest generation 3500 Genetic Analyzer, as sensitivity on the 310 was low and separation of products on the 3500 with POP‐7™ was poor. We have modified the original assay and split it into four multiplex reactions, each followed by an SBE assay. These multiplex assays were analyzed using polymer POP‐4™ on ABI 310 PRISM® and polymers POP‐4™, POP‐6™ and POP‐7™ on the 3500 Genetic Analyzer. The assays were sensitive and reproducible with input DNA as low as 60 pg using both the ABI 310 and 3500. In addition, we found that POP‐6™ was most effective with the 3500, based on the parameters that we assessed, achieving better separation of the small SBE products; this conflicted with the recommended use of POP‐7™ by the instrument manufacturer. To support the use of the SNP panel in casework in Malaysia we have created an allele frequency database from 325 individuals, representing the major population groups within Malaysia. Population and forensic parameters were estimated for all populations and its efficacy evaluated using 51 forensic samples from challenging casework.     

基于遗传进化的聚类分析新方法

提出了一种基于遗传进化策略的聚类分析新方法，将聚类问题转换为实数空间的优化问题．用遗传策略在连续的实数空间寻找最优类中心，既可避免求解组合优化问题，减少计算量，又可避免在优化过程中陷入局部最优．此遗传聚类方法用于对4组实际数据进行硬分类和模糊分类，结果令人满意．     

Experimental and theoretical studies of the thermal behavior of titanium dioxide-SnO2 based composites

In this paper we report experimental and theoretical studies concerning the thermal behavior of some organotin-Ti(IV) oxides employed as precursors for TiO(2)/SnO(2) semiconducting based composites, with photocatalytic properties. The organotin-TiO(2) supported materials were obtained by chemical reactions of SnBu(3)Cl (Bu = butyl), TiCl(4) with NH(4)OH in ethanol, in order to impregnate organotin oxide in a TiO(2) matrix. A theoretical model was developed to support experimental procedures. The kinetics parameters: frequency factor (A), activation energy, and reaction order (n) can be estimated through artificial intelligence methods. Genetic algorithm, fuzzy logic, and Petri neural nets were used in order to determine the kinetic parameters as a function of temperature. With this in mind, three precursors were prepared in order to obtain composites with Sn/TiO(2) ratios of 0% (1), 15% (2), and 30% (3) in weight, respectively. The thermal behavior of products (1-3) was studied by thermogravimetric experiments in oxygen.     

Determination of thiamine HCl and pyridoxine HCl in pharmaceutical preparations using UV-visible spectrophotometry and genetic algorithm based multivariate calibration methods

Simultaneous determination of binary mixtures pyridoxine hydrochloride and thiamine hydrochloride in a vitamin combination using UV-visible spectrophotometry and classical least squares (CLS) and three newly developed genetic algorithm (GA) based multivariate calibration methods was demonstrated. The three genetic multivariate calibration methods are Genetic Classical Least Squares (GCLS), Genetic Inverse Least Squares (GILS) and Genetic Regression (GR). The sample data set contains the UV-visible spectra of 30 synthetic mixtures (8 to 40 microg/ml) of these vitamins and 10 tablets containing 250 mg from each vitamin. The spectra cover the range from 200 to 330 nm in 0.1 nm intervals. Several calibration models were built with the four methods for the two components. Overall, the standard error of calibration (SEC) and the standard error of prediction (SEP) for the synthetic data were in the range of <0.01 and 0.43 microg/ml for all the four methods. The SEP values for the tablets were in the range of 2.91 and 11.51 mg/tablets. A comparison of genetic algorithm selected wavelengths for each component using GR method was also included.     

An improvement of window factor analysis for resolution of noisy HPLC-DAD data

Window factor analysis (WFA) is a powerful tool in analyzing evolutionary process. However, it was found that window factor analysis is much sensitive to the noise involved in original data matrix. An error analysis was done with the fact that the concentration profiles resolved by the conventional window factor analysis are easily distorted by the noise reserved by the abstract factor analysis (AFA), and a modified algorithm for window factor analysis was proposed. Both simulated and experimental HPLC-DAD data were investigated by the conventional and the improved methods. Results show that the improved method can yield less noise-distorted concentration profiles than the conventional method, and the ability for resolution of noisy data sets can be greatly enhanced.     

Hexaene derivatives of nystatin produced as a result of an induced rearrangement within the nysC polyketide synthase gene in S. noursei ATCC 11455

Genetic manipulation of the polyketide synthase (PKS) gene nysC involved in the biosynthesis of the tetraene antifungal antibiotic nystatin yielded a recombinant strain producing hexaene nystatin derivatives. Analysis of one such compound, S48HX, by LC-MS/MS suggested that it comprises a 36-membered macrolactone ring completely decorated by the post-PKS modification enzymes. Further characterization by bioassay has shown that S48HX exhibits antifungal activity. Genetic analysis of the hexaene-producing mutant revealed an in-frame deletion within the nysC gene via recombination between two homologous ketoreductase domain-encoding sequences. Apparently, this event resulted in the elimination of one complete module from NysC PKS, subsequently leading to the production of the nystatin derivative with a contracted macrolactone ring. These results represent the first example of manipulation of a PKS gene for the biosynthesis of a polyene antibiotic.     

Electroanalysis of single-nucleotide polymorphism by hairpin DNA architectures

Genetic analysis of infectious and genetic diseases and cancer diagnostics require the development of efficient tools for fast and reliable analysis of single-nucleotide polymorphism (SNP) in targeted DNA and RNA sequences often responsible for signalling disease onset. Here, we highlight the main trends in the development of electrochemical genosensors for sensitive and selective detection of SNP that are based on hairpin DNA architectures exhibiting better SNP recognition properties compared with linear DNA probes. SNP detection by electrochemical hairpin DNA beacons is discussed, and comparative analysis of the existing SNP sensing strategies based on enzymatic and nanoparticle signal amplification schemes is presented.     

A modular microfluidic system for deoxyribonucleic acid identification by short tandem repeat analysis

Microfluidic technology has been utilized in the development of a modular system for DNA identification through STR (short tandem repeat) analysis, reducing the total analysis time from the ∼6 h required with conventional approaches to less than 3 h. Results demonstrate the utilization of microfluidic devices for the purification, amplification, separation and detection of 9 loci associated with a commercially-available miniSTR amplification kit commonly used in the forensic community. First, DNA from buccal swabs purified in a microdevice was proven amplifiable for the 9 miniSTR loci via infrared (IR)-mediated PCR (polymerase chain reaction) on a microdevice. Microchip electrophoresis (ME) was then demonstrated as an effective method for the separation and detection of the chip-purified and chip-amplified DNA with results equivalent to those obtained using conventional separation methods on an ABI 310 Genetic Analyzer. The 3-chip system presented here demonstrates development of a modular, microfluidic system for STR analysis, allowing for user-discretion as to how to proceed after each process during the analysis of forensic casework samples.     

Genetic programming as an analytical tool for non-linear dielectric spectroscopy.

By modelling the non-linear effects of membranous enzymes on an applied oscillating electromagnetic field using supervised multivariate analysis methods, Non-Linear Dielectric Spectroscopy (NLDS) has previously been shown to produce quantitative information that is indicative of the metabolic state of various organisms. The use of Genetic Programming (GP) for the multivariate analysis of NLDS data recorded from yeast fermentations is discussed, and GPs are compared with previous results using Partial Least Squares (PLS) and Artificial Neural Nets (NN). GP considerably outperforms these methods, both in terms of the precision of the predictions and their interpretability.