Identification and determination of aminopeptidase activities secreted by lemon balm

Using synthetic substrates, an uncomplicated and sensitive procedure for the identification and determination of extracellular aminopeptidase was developed. The β-naphthylamides of the amino acids were applied for the identification of extracellular aminopeptidase, whereas the 4-(phenylazo) phenylamides of the amino acids were used for the determination of intra-and extracellular aminopeptidase activity. The results show a 81.8–88.9% intracellular and 11.1–18.2% extracellular distribution of the studied enzyme activity. Published in Khimiya Prirodnykh Soedinenii, No. 2, pp. 167–169, March–April, 2007.     

用峰鉴别技术反相高效液相色谱法测定火锅汤料中微量吗啡

本文报道了以峰鉴别技术为定性依据的测定火锅汤料中微量吗啡的反相高效液相色谱法。本法采用改良的Ｓｔａｓ－ｏｔｔｏ法分离提取复杂样品中的微量吗啡。由于采用峰鉴别技术，增加了定性参数，大大提高了定性方法的准确性。本法简便、快速。最低检出浓度为０．０４ｍｇ／Ｌ。在数十例样品分析中，与其它仪器分析结果比照，非常符合。     

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.     

Fuzzy theory in analytical chemistry

The concept of fuzzy theory is described in order to provide the analyst with the means for dealing with vague statements, uncertain observations or the fuzziness of human perception and interpretation, in general. In a theoretical part, basic notions of fuzzy theory are given, such as types of membership functions, operations with fuzzy sets, definitions of fuzzy numbers, points, functions, and relations, and the use of linguistic variables. The difference between fuzziness and probability is outlined. The applications section demonstrates advantages of fuzzy theory methods compared to common mathematical methods with respect to data handling for calibration of analytical methods, to classification of Chromatographie and spectroscopic patterns, to component identification and multicomponent analysis, and to designing fuzzy expert systems for selection of analytical procedures.     

The use of ATR-IR to identify the components separated by paper chromatography

Summary A modified procedure for the identification of separated components in paper chromatography using attenuated total reflection infrared spectroscopy is described. This combined method, though inferior in sensitivity and resolution to the modern separation systems interfaced with sophisticated analytical instruments, is simple, relatively less expensive and suitable for routine analysis of components like polymer additives.     

鲨鱼软骨质量的聚类分析法

用电感耦合等离子体原子发射光谱法（ＩＣＰ－ＡＥＳ）测定了１８个鲨鱼软骨真品中１３个元素含量，对测定结果进行分析和变量聚类分析，抽提５个特征指标，并以谱系数聚类建立了鉴别鲨鱼软骨真伪的数学模式，用３个假冒产品和一个鲨鱼软骨胶囊对其进行检验，结果表明，用无机元素所建立的数学模式不仅能鉴别鲨鱼软骨的真伪，还能区分鲨鱼软骨的部分及不同部位的混合物。     

Real-time onboard wind and windshear determination,part 2: Detection

This paper is concerned with windshear detection in connection with real-time wind identification (Ref. 1). It presents a comparative evaluation of two techniques, one based on the shear/downdraft factor and one based on the wind difference index. The comparison is done with reference to a particular microburst, that which caused the 1985 crash of Flight Delta 191 at Dallas-Fort Worth International Airport.The shear/downdraft factor has the merit of combining the effects of the shear and the downdraft into a single entity. However, its effectiveness is hampered by the fact that, in a real situation, the windshear is accompanied by free-stream turbulence, which tends to blur the resulting signal. In turn, this results in undesirable nuisance warnings if the magnitude of the shear factor due to free-stream turbulence is temporarily larger than that due to true windshear. Therefore, proper filtering is necessary prior to using the shear/downdraft factor in detection and guidance. One effective way for achieving this goal is to average the shear/downdraft factor over a specified time interval . The effect of on the average shear/downdraft factor is studied.     

Real-time onboard wind and windshear determination,part 1: Identification

Standard wind identification techniques employed in the analysis of aircraft accidents are post-facto techniques; they are processed after the event has taken place and are based on the complete time histories of the DFDR/ATCR data along the entire trajectory. By contrast, real-time wind identification techniques are processed while the event is taking place; they are based solely on the knowledge of the preceding time histories of the DFDR/ATCR data.In this paper, a real-time wind identification technique is developed. First, a 3D-kinematic approach is employed in connection with the DFDR/ATCR data covering the time interval preceding the present time instant. The aircraft position, inertial velocity, and accelerometer bias are determined by matching the flight trajectory computed from the DFDR data with the flight trajectory available from the ATCR data. This leads to a least-square problem, which is solved analytically every seconds, with / small.With the inertial velocity and accelerometer bias known, an extrapolation process takes place so as to predict the inertial velocity profile over the subsequent -subinterval. At the end of this subinterval, the extrapolated inertial velocity and the newly identified inertial velocity are statistically reconciled and smoothed. Then, the process of identification, extrapolation, reconciliation, and smoothing is repeated. Subsequently, the wind is computed as the difference between the inertial velocity and the airspeed, which is available from the DFDR data. With the wind identified, windshear detection can take place (Ref. 1).As an example, the real-time wind identification technique is applied to Flight Delta 191, which crashed at Dallas-Fort Worth International Airport on August 2, 1985. The numerical results show that the wind obtained via real-time identification is qualitatively and quantitatively close to the wind obtained via standard identification. This being the case, it is felt that real-time wind identification can be useful in windhsear detection and guidance, above all if the shear/downdraft factor signal is replaced by the wind difference signal (Ref. 1).This paper and its companion (Ref. 1) are based on Refs. 2–4.This research was supported by the Aviation Research and Education Foundation and by Texas Advanced Technology Program, Grant No. TATP-003604020.     

Fastiterative methods for least squares estimations

Least squares estimations have been used extensively in many applications, e.g. system identification and signal prediction. When the stochastic process is stationary, the least squares estimators can be found by solving a Toeplitz or near-Toeplitz matrix system depending on the knowledge of the data statistics. In this paper, we employ the preconditioned conjugate gradient method with circulant preconditioners to solve such systems. Our proposed circulant preconditioners are derived from the spectral property of the given stationary process. In the case where the spectral density functions() of the process is known, we prove that ifs() is a positive continuous function, then the spectrum of the preconditioned system will be clustered around 1 and the method converges superlinearly. However, if the statistics of the process is unknown, then we prove that with probability 1, the spectrum of the preconditioned system is still clustered around 1 provided that large data samples are taken. For finite impulse response (FIR) system identification problems, our numerical results show that annth order least squares estimator can usually be obtained inO(n logn) operations whenO(n) data samples are used. Finally, we remark that our algorithm can be modified to suit the applications of recursive least squares computations with the proper use of sliding window method arising in signal processing applications.Research supported in part by HKRGC grant no. 221600070, ONR contract no. N00014-90-J-1695 and DOE grant no. DE-FG03-87ER25037.     

新型尾式硫代苯并噻唑基卟啉化合物的合成与表征

通过不对称的单羟基卟啉化合物、溴代烷烃和巯基苯并噻唑合成了一系列新型硫代苯并噻唑基尾式卟啉化合物, 并采用核磁共振氢谱、碳谱、红外光谱、质谱和元素分析对卟啉化合物的结构进行了表征.