Testing procedures for detection of linear dependencies in efficiency models

The validity of many efficiency measurement methods rely upon the assumption that variables such as input quantities and output mixes are independent of (or uncorrelated with) technical efficiency, however few studies have attempted to test these assumptions. In a recent paper, Wilson (2003) investigates a number of independence tests and finds that they have poor size properties and low power in moderate sample sizes. In this study we discuss the implications of these assumptions in three situations: (i) bootstrapping non-parametric efficiency models; (ii) estimating stochastic frontier models and (iii) obtaining aggregate measures of industry efficiency. We propose a semi-parametric Hausmann-type asymptotic test for linear independence (uncorrelation), and use a Monte Carlo experiment to show that it has good size and power properties in finite samples. We also describe how the test can be generalized in order to detect higher order dependencies, such as heteroscedasticity, so that the test can be used to test for (full) independence when the efficiency distribution has a finite number of moments. Finally, an empirical illustration is provided using data on US electric power generation.     

Correlation lengths in quasi-one-dimensional systems via transfer matrices

ABSTRACT

Using transfer matrices up to next-nearest-neighbour interactions, we examine the structural correlations of quasi-one-dimensional systems of hard disks confined by two parallel lines and hard spheres confined in cylinders. Simulations have shown that the non-monotonic and non-smooth growth of the correlation length in these systems accompanies structural crossovers [Fu et al., Soft Matter 13, 3296 (2017)]. Here, we identify the theoretical basis for these behaviours. In particular, we associate kinks in the growth of correlation lengths with eigenvalue crossing and splitting. Understanding the origin of such structural crossovers answers questions raised by earlier studies, and thus bridges the gap between theory and simulations for these reference models.     

多目标模糊系数规划

在单目标模糊系数规划的理论基础上，对多目标模糊系数规划进行讨论，在以目标间的协调程度尽可能大为最优性条件的要求下提出多目标模糊系数规划最优解的定义，并给出一种可行的求解方法。     

Decay of correlations in one and two dimensions

An exposition of some methods of proving exponential (stretched exponential) decay of correlations is given. One-dimensional strictly hyperbolic and quadratic maps and two-dimensional piecewise smooth, uniformly hyperbolic maps are considered. The emphasis is on the fundamental constructions of the Markov sieve method due to Bunimovich-Chernov-Sinai and those of Liverani's Hilbert metric method.     

脏腑病变与寸关尺压力波的关系

该文根据波动理论，推证了脏腑病变对寸、关、尺压力波的 影响，分析了寸、关、尺部位的脉状与脏腑病变的关系。      

Correlation spectroscopy as a tool for detecting losses of ligand elements in laser welding of aluminium alloys

The plasma plume induced during laser welding of metals is a mixture of metal vapour, coming from the vaporised weld pool surface and shielding gas. The influence of the shielding gas on the welded joints quality is not yet well understood and very few investigations, to the best of our knowledge, were addressed to study its role in case of welding of aluminium–magnesium alloys. In this paper we present a study of the dynamics of plasma plume produced in laser welding of 5xxx aluminium alloys by means of correlation spectroscopy. By our results we can correlate the influence of the welding speed, in case of ineffective gas shielding, to the loss of alloying elements. Finally, the results obtained are consistent with the EDX analysis performed in post-processing on the welded joints.     

目标方位估计的相关矩阵最大特征值法

研究均匀线阵(ULA)波束形成时作者发现，当操纵线阵指向方位不断变化，相关矩阵的最大特征值也随着有规律地变化着。通过分析最大特征值的变化，能够估计目标方位和数目。本文从实验数据和计算机仿真两方面对单目标和多目标进行处理，验证上述方法的可行性。     

Correlation of infinite dilution activity coefficients of solvents in polymer solutions using connectivity indices

In this work, correlations for the estimation of the infinite dilution activity coefficients of non-polar solvents in polystyrene (PS), poly(vinyl acetate) (PVAc), poly(n-butyl methacrylate) (PBMA), poly(dimethyl siloxane), poly(methyl methacrylate) (PMMA), poly(ethylene oxide) (PEO), poly(vinyl chloride) (PVC), polyisobutylene and polyethylene (PE), and that of polar solvents in PS, PVAc, PBMA, PMMA, PEO, PVC and PE are proposed. A total of 205 polymer/non-polar solvent systems with 1708 data points, and 118 polymer/polar solvent systems with 695 data points were used to develop the correlations. The overall average errors were 9.6% and 11.3%, respectively, significantly lower than other predictive models. Since the new correlations require only the connectivity indices of the solvents in the calculations, and the connectivity indices can be calculated easily once the molecular structure of the substance in question is known, they are easy to apply, and are useful for process design and development.