Linearization of column responses by correlation chromatography. Separation improvement and reduction of undesired adsorption effects

Summary Experiments and simulations prove that correlation chromatography can greatly reduce the disadvantage of a non-linear response of the chromatographic column. A factor that has been accepted as being an important source of error in correlation or multiplex chromatography, has been shown not to be. Separations affected, improve dramatically when correlation chromatography is used, and a substantial amount of correlation noise only arises when there is a large difference in separation between a conventional chromatogram and a correlogram.A model has been developed for simulating these nonlinearities. It is shown that, especially for correlation chromatography, the simulation results match the practical measurements very well.     

对超重、失重演示实验的改进

对传统的超重、失重演示实验进行了改进,使弹簧秤的指针能静止在超重(或失重)的位置上,从而能准确地读出读数,提高演示效果.     

连续照明时成像对比度与气象条件的关系

 通过同轴激光连续照明成像模型分析了大气后向散射对成像对比度的影响，得出了考虑散射因素时成像对比度的计算公式。基于不同气象条件下大气粒子散射特点，讨论了霾和雾两种不同天气时成像对比度随照明距离的变化规律，并与实验结果进行了对比，计算结果与实验吻合较好。     

具连续分布滞量的非线性中立型抛物偏泛函微分方程的振动性

考虑一类具连续分布滞量的非线性中立型抛物偏泛函微分方程解的振动性,借助Green定理和时滞微分不等式获得了这类方程在Robin,Dirichlet边值条件下所有解振动的若干充分条件.     

A note on continuously decomposed evolving exchange economies

It is routine to demonstrate in the exchange economy framework that small changes of individual preferences and endowments always result in small changes of the derived excess demand functions as one should expect. Though being as desirable for reasons of the consistency of the whole approach, however, a precise proof of the converse direction so far is still open to question. The present paper shows that it is actually true. We use a decomposition method for aggregate excess demand functions developed by Mas-Colell which is derived from the well-known decomposition method developed by Sonnenschein and perfected by Debreu and Mantel. Our result fills in a notorious gap in the line of economic justification usually given for this decomposition, or disaggregation, method in that comparative static analysis would be restricted if the decomposition of excess demand functions would not be continuous.     

简析"静止液体内部压强公式验证"实验的设计策略

“静止液体内部压强公式验证”在现行教材中有两种实验方法。通过分析实验的设计策略，说明其作用、效果及操作上的困难，指出合理的与不合理诸因素，从而提出改进实验的方法，化难为易，提高实验教学效果。     

Global Optimization of Stochastic Black-Box Systems via Sequential Kriging Meta-Models

This paper proposes a new method that extends the efficient global optimization to address stochastic black-box systems. The method is based on a kriging meta-model that provides a global prediction of the objective values and a measure of prediction uncertainty at every point. The criterion for the infill sample selection is an augmented expected improvement function with desirable properties for stochastic responses. The method is empirically compared with the revised simplex search, the simultaneous perturbation stochastic approximation, and the DIRECT methods using six test problems from the literature. An application case study on an inventory system is also documented. The results suggest that the proposed method has excellent consistency and efficiency in finding global optimal solutions, and is particularly useful for expensive systems.     

Low noise double pass L-band erbium-doped fiber amplifier

A new double pass long wavelength band erbium-doped fiber amplifier with enhanced noise figure characteristics is demonstrated. The noise figure is improved by about 2.6 dB with the incorporation of broadband conventional-band fiber Bragg grating (FBG) in between the two segments of erbium-doped fiber. By incorporating both the pre-amplifier and the FBG, the noise figure is further improved, which varies from 4.0 to 5.0 dB in the flat gain region from 1570 to 1600 nm. The gain varies from 32.0 to 33.4 dB within this region. The new amplifier with high gain and low noise figure can be useful as an inline amplifier in a wavelength division multiplexing transmission system.     

Combinatorial Optimization by Dynamic Contraction

A heuristic optimization methodology, Dynamic Contraction (DC), is introduced as an approach for solving a wide variety of hard combinatorial problems. Contraction is an operation that maps an instance of a problem to a smaller instance of the same problem. DC is an iterative improvement strategy that relies on contraction as a mechanism for escaping local minima. As a byproduct of contraction, efficiency is improved due to a reduction of problem size. Effectiveness of DC is shown through simple applications to two classical combinatorial problems: The graph bisection problem and the traveling salesman problem.