Preparation and characterization of fragrance by extracting the essential oils from different raw materials

The extraction is a simple process and it is widely used to extract the fragrances in fragrance industries from essential oils. There are number of compounds (i.e. flowers, oils, leaves etc.) from which we can prepare the fragrance by extracting the essential oils from them. In this work, we have prepared the fragrance from the essential oils by the liquid-liquid extraction process, where the essential oil presented as the concentrated hydrophobic liquid containing volatile aroma compounds. We used the combination of Gas chromatography and Mass spectrometry (GC/MS) characterization techniques to make our product more useful, convenient and compitative with the other fragrance available in the market. This study would be helpful to understand the preparation of the fragrance from the concentrated hydrophobic liquid type essential oils which contains volatile aroma compounds by using a significant liquid-liquid extraction process.     

Ffast Transient Fluorescence Technique to Study Critical Exponents at the Glass Transition

The fast transient fluorescence (FTRF) technique was used to study critical exponents at the glass transition in free-radical crosslinking copolymerization (FCC) for two different monomeric systems, methyl methacrylate (MMA) and styrene (S). Pyrene (P_y ) was used as a fluorescence probe. The fluorescence lifetimes of P_y from its decay traces were measured and used to monitor the gelation process. Changes in the viscosity of the pregel solutions due to glass formation dramatically enhance the fluorescent yield of aromatic molecules. This effect is used to study the glass transition upon gelation of MMA and S monomeric systems as a function of time, at various temperatures and crosslinker concentrations. The results are interpreted in the view of percolation theory. The gel fraction and weight average degree of polymerization exponents β and γ are found to be 0.37 ± 0.02 and 1.66 ± 0.07 in agreement with percolation results.     

A statistical model for global optimization by means of select and clone

A statistical model tor giobai optimization is constructed generalizing some properties ofthe Wiener process to the multidimensional case. A new approach, which is similar to the Branch and Bound approach, is proposed to the construction of algorithms based on statistical models. A two dimensional version of the algorithm is implemented, and test results are presented     

紫外分光光度法测定阿霉素聚乳酸微球的含量

采用复乳-溶剂挥发法制备阿霉素聚乳酸微球,通过扫描电镜观察微球的形态,采用紫外分光光度法测定徽球中阿霉素的含量.结果表明,所制备的阿霉素聚乳酸微球外形圆整,阿霉素溶液在1.70-34.1μg/mL浓度范围内线性良好,校准曲线回归方程为A=0.0422C+0.1845,相关系数r为0.9997,平均回收率为99.5%(R...     

Numerical methods for theoretical analysis of foil bearing dynamics

The bearing under consideration is a self-acting, gas bearing with a flexibly supported foil. In order to conduct the theoretical analysis, three systems were identified: a rotor, a gas film and a flexible structure. Each of these elements has been mathematically analysed and analytical equations have been formulated. It was found, that the gas flow in the bearing can be described by the Reynolds equation, whereas a spring-damper model was selected for the structural analysis. The Reynolds equation is a differential equation the exact solution to which is unknown. The work describes the finite difference method in detail, where the partial derivatives in the Reynolds equation are replaced by a system of algebraic equations. In order to solve the resulting system, the Alternating Direction Implicit method (ADI) was used. Based on that and on the analysis of interactions between the three systems the equations have been computed. The accuracy of methods has been verified by means of series of numerical tests. Chosen results are described in this paper.     

Combined neural network and reduced FRF techniques for slight damage detection using measured response data

Summary  This paper deals with structural damage detection using measured frequency response functions (FRF) as input data to artificial neural networks (ANN). A major obstacle, the impracticality of using full-size FRF data with ANNs, was circumvented by applying a data-reduction technique based on principal component analysis (PCA). The compressed FRFs, represented by their projection onto the most significant principal components, were used as the ANN input variables instead of the raw FRF data. The output is a prediction of the actual state of the specimen, i.e. healthy or damaged. A further advantage of this particular approach is its ability to deal with relatively high measurement noise, which is a common occurrence when dealing with industrial structures. The methodology was applied to detect three different states of a space antenna: reference, slight mass damage and slight stiffness damage. About 600 FRF measurements, each with 1024 spectral points, were included in the analysis. Six 2-hidden layer networks, each with an individually-optimised architecture for a specific FRF reduction level, were used for damage detection. The results showed that it was possible to distinguish between the three states of the antenna with good accuracy, subject to using an adequate number of principal components together with a suitable neural network configuration. It was also found that the quality of the raw FRF data remained a major consideration, though the method was able to filter out some of the measurement noise. The convergence and detection properties of the networks were improved significantly by removing those FRFs associated with measurement errors. Received 9 March 2000; accepted for publication 12 December 2000     

正交试验法优选山绿茶中乌苏酸提取工艺

筛选山绿茶中乌苏酸的最佳提取工艺。采用正交设计L9(34)考察液固比、提取时间、乙醇浓度和提取次数4个因素,用高效液相色谱法测定山绿茶中乌苏酸的含量。山绿茶中乌苏酸的最佳提取工艺为A2B3C3D1,即选择液固比(mL/g)10∶1、提取时间4h、乙醇浓度90%、提取次数1次。本法工艺合理,质量稳定,适宜于工业化生产。     

Effective Relaxations and Partitioning Schemes for Solving Water Distribution Network Design Problems to Global Optimality

In this paper, we address the development of a global optimization procedure for the problem of designing a water distribution network, including the case of expanding an already existing system, that satisfies specified flow demands at stated pressure head requirements. The proposed approach significantly improves upon a previous method of Sherali et al. (1998) by way of adopting tighter polyhedral relaxations, and more effective partitioning strategies in concert with a maximal spanning tree-based branching variable selection procedure. Computational experience on three standard test problems from the literature is provided to evaluate the proposed procedure. For all these problems, proven global optimal solutions within a tolerance of 10^–4% and/or within 1$ of optimality are obtained. In particular, the two larger instances of the Hanoi and the New York test networks are solved to global optimality for the very first time in the literature. A new real network design test problem based on the Town of Blacksburg Water Distribution System is also offered to be included in the available library of test cases, and related computational results are presented.     

Implicit Regularization and Renormalization of QCD

We apply the Implicit Regularization (IR) technique in a non-abelian gauge theory. We show that IR preserves gauge symmetry as encoded in relations between the renormalization constants required by the Slavnov–Taylor identities at the one-loop level of QCD. Moreover, we show that the technique handles divergencies in massive and massless QFT on equal footing.     

用金属钨平台石墨炉原子化器测定环境样品中的锶

使用新原子化器－金属钨平台和全热解石墨管测定环境样品中锶，其优点为：（１）避免锶和石墨管中碳形成化合物，有利提高峰高灵敏度和消除记忆效应。２．避免溶样用的硝酸和高氯酸对石墨管的腐蚀以及产生严重的基体效应，３；空白低。有