Dominant Factors Affecting the Chromatographic Behaviour of Bile Acids

With the aim of optimizing the chromatographic process by avoiding any preliminary derivatizing step, we examined the chromatographic behaviour of a selected set of unconjugated bile acids looking at the dominant factors that affect the performances of three different stationary phases: RP-8, RP-18 and RP-18 Base Deactivated (RP-18-BD). Accordingly to its structural peculiarity, the RP-18-BD column combined with a specific mobile phase has proved to be the most suitable one, in enhancing both separation factor α and resolution R _S within the selected set of analytes. Pronounced changes in the chromatographic profiles by only slightly changing the mobile phase composition (pH, buffer concentration, percentage and kind of organic modifier) prompted us to achieve satisfactory results in the separation and resolution of the selected set of bile acids.Presented at: CE in the Biotechnology & Pharmaceutical Industries: 7th symposium on the practical applications for the analysis of proteins, nucleotides and small molecules, Montreal, Canada, August 12–16, 2005.An erratum to this article can be found at     

Metastable systems driven by colored noise: The stationary state

The influence of the Bardeen-Herring back-jump correlations on the Fermi-Dirac statistics of the one-dimensional nonhomogeneous fermionic lattice gas is studied by the Monte Carlo simulation technique and semianalytically. The resulting distribution is obtained, exhibiting increased population of the lower levels in comparison to the Fermi-Dirac statistics.     

Estimating reaction parameters in mechanism-enabled population balance models of nanoparticle size distributions: A Bayesian inverse problem approach

In order to quantitatively predict nano- as well as other particle-size distributions, one needs to have both a mathematical model and estimates of the parameters that appear in these models. Here, we show how one can use Bayesian inversion to obtain statistical estimates for the parameters that appear in recently derived mechanism-enabled population balance models (ME-PBM) of nanoparticle growth. The Bayesian approach addresses the question of “how well do we know our parameters, along with their uncertainties?.” The results reveal that Bayesian inversion statistical analysis on an example, prototype nanoparticle formation system allows one to estimate not just the most likely rate constants and other parameter values, but also their SDs, confidence intervals, and other statistical information. Moreover, knowing the reliability of the mechanistic model's parameters in turn helps inform one about the reliability of the proposed mechanism, as well as the reliability of its predictions. The paper can also be seen as a tutorial with the additional goal of achieving a “Gold Standard” Bayesian inversion ME-PBM benchmark that others can use as a control to check their own use of this methodology for other systems of interest throughout nature. Overall, the results provide strong support for the hypothesis that there is substantial value in using a Bayesian inversion methodology for parameter estimation in particle formation systems.     

可分解均衡函数均衡力度分析

证明了惩罚力度越大的均衡函数得到的变权向量构建的变权决策模型越偏于保守;而激励力度越大的均衡函数得到的变权决策模型越偏于乐观,这些结果与均衡函数的原始含义是一致的.最后,详细分析了几类常见的可分解均衡函数的惩罚力度和激励力度随着参数的变化情况.     

对探究影响摩擦力大小因素实验的分析及改进

对传统的影响滑动摩擦力大小因素的实验进行改进,把物块的运动变换成下面木板的运动,并用定滑轮改变拉力的方向.使用改进后的装置不但可以降低操作的难度,还可提高实验的准确性.     

Shock waves for the hyperbolic balance laws with discontinuous sources

In this paper, we are concerned with the behavior of shock waves in a 2 × 2 balance law with discontinuous source terms. We obtain the existence of a local shock wave solution of this problem and deduce that the discontinuous source terms create a weak discontinuity in this solution. Copyright © 2013 John Wiley & Sons, Ltd.     

Study on the Agglomeration Kinetics of Uranium Peroxide

Considering the previous study dealing with thermodynamic and kinetic phenomena (nucleation and crystal growth) during the uranium peroxide precipitation, this work focuses on the agglomeration mechanism. It provides the results obtained from the experiments carried out in a MSMPR reactor operating at steady state. The influence of the operating parameters on the uranium peroxide agglomerates was studied in order to identify the agglomeration kernel. The method is based on the resolution of the population balance equation using the method of moments and the experimental particle size distributions. The results lead to a size-independent kernel directly proportional to the crystal growth rate. Under the stirring conditions studied, the agglomeration appears to be significantly reduced by mixing which results in a kernel inversely proportional to the average shear rate. The agglomeration kinetic law obtained in this study will be used for the process modelling in a further study.     

A maximum-efficiency-first multi-path route selection strategy for optical burst switching networks

In this paper, the impact of a path selection on other existing paths in optical burst switching (OBS) networks is studied by analyzing the contention among different traffic streams and the interaction between the route selection and traffic load balance. The results show that there exists a mutual reinforcement interaction among the traffic load of a path, the path burst loss ratio and the contention ability of the path when burst loss ratio based multi-path selection strategies are adopted, which may increase the unbalance of traffic and lead to severe congestion further. A maximum-efficiency-first multi-path selection strategy, which considers the performance of the burst flows and the impact of a path selection on existing OBS paths at the same time by a combined metric of route efficiency, is proposed to maximize the utility of the burst flows and minimize the increment of lost throughput on the path. The performance of the proposed multi-path selection strategy is evaluated through simulation. The results show that the presented strategy obviously outperforms the least burst loss ratio strategy and shortest path first strategy in terms of the burst loss ratio in the practical unbalanced background traffic, especially when the network is heavily loaded.     

Simple Equations Method (SEsM): Algorithm,Connection with Hirota Method,Inverse Scattering Transform Method,and Several Other Methods

The goal of this article is to discuss the Simple Equations Method (SEsM) for obtaining exact solutions of nonlinear partial differential equations and to show that several well-known methods for obtaining exact solutions of such equations are connected to SEsM. In more detail, we show that the Hirota method is connected to a particular case of SEsM for a specific form of the function from Step 2 of SEsM and for simple equations of the kinds of differential equations for exponential functions. We illustrate this particular case of SEsM by obtaining the three- soliton solution of the Korteweg-de Vries equation, two-soliton solution of the nonlinear Schrödinger equation, and the soliton solution of the Ishimori equation for the spin dynamics of ferromagnetic materials. Then we show that a particular case of SEsM can be used in order to reproduce the methodology of the inverse scattering transform method for the case of the Burgers equation and Korteweg-de Vries equation. This particular case is connected to use of a specific case of Step 2 of SEsM. This step is connected to: (i) representation of the solution of the solved nonlinear partial differential equation as expansion as power series containing powers of a “small” parameter ϵ; (ii) solving the differential equations arising from this representation by means of Fourier series, and (iii) transition from the obtained solution for small values of ϵ to solution for arbitrary finite values of ϵ. Finally, we show that the much-used homogeneous balance method, extended homogeneous balance method, auxiliary equation method, Jacobi elliptic function expansion method, F-expansion method, modified simple equation method, trial function method and first integral method are connected to particular cases of SEsM.     

多孔活性自燃金属的光谱辐射特性研究

多孔活性金属材料因为内部存在大量的孔隙，大大地增加了与空气的接触面积，使得其在空气中的燃烧较为猛烈，燃烧温度迅速上升。其燃烧过程属于固体燃烧的范畴，较为复杂。以镁为例，通过建立燃烧模型，来研究多孔活性金属的光谱辐射特性。首先，建立氧气总消耗量与活性金属剩余质量的关系，研究氧气在活性金属孔隙内的扩散浓度关系，通过求解活性金属热平衡方程得到活性金属燃烧过程中温度与时间的关系式，进而得到活性金属的峰值光谱辐射强度表达式；然后，将模型计算的仿真结果与红外热像仪测得的实验结果对比，结果表明，模型的计算结果与实验结果相一致，误差在了10%以内；最后，通过建立的燃烧模型来研究活性金属燃烧规律以及其光谱辐射特性，解决了高空、高速下的活性金属光谱辐射强度难以实验获得的问题，大大减小了实验成本与时间。分别对比不同时间活性金属箔片在1～3，3～5以及8～12 μm波段下的辐射强度，得出活性金属燃烧时的辐射强度主要集中在3～5 μm波段的结论。研究结果表明：自燃金属最大燃烧温度随高度的增加逐渐下降，随气流速度的增加先增加后减小，在速度为30 m·s-1时，温度达到最大；自燃金属的光谱辐射强度在2～6 μm波段达到最大。该模型也可以用来研究其他活性金属的燃烧特性。