Nonlinear optimization exclusion tests for finding all solutions of nonlinear equations

Exclusion tests are a well known tool in the area of interval analysis for finding the zeros of a function over a compact domain. Recently, K. Georg developed linear programming exclusion tests based on Taylor expansions. In this paper, we modify his approach by choosing another objective function and using nonlinear constraints to make the new algorithm converges faster than the algorithm in [K. Georg, A new exclusion test, J. Comput. Appl. Math. 152 (2003) 147–160]. In this way, we reduce the number of subinterval in each level. The computational complexity for the new tests are investigated. Also, numerical results and comparisons will be presented.     

Recent experimental results from JLab

Preliminary results of a selected few recent experiments at JLab are presented.     

Assessing Local Influence in Canonical Correlation Analysis

The first order local influence approach is adopted in this paper to assess the local influence of observations to canonical correlation coefficients, canonical vectors and several relevant test statistics in canonical correlation analysis. This approach can detect different aspects of influence due to different perturbation schemes. In this paper, we consider two different kinds, namely, the additive perturbation scheme and the case-weights perturbation scheme. It is found that, under the additive perturbation scheme, the influence analysis of any canonical correlation coefficient can be simplified to just observing two predicted residuals. To do the influence analysis for canonical vectors, a scale invariant norm is proposed. Furthermore, by choosing proper perturbation scales on different variables, we can compare the different influential effects of perturbations on different variables under the additive perturbation scheme. An example is presented to illustrate the effectiveness of the first order local influence approach.     

High‐resolution mass spectrometry for bioanalytical applications: Is this the new gold standard?

Liquid chromatography coupled to quadrupole‐based tandem mass spectrometry (QqQ) is termed the “gold standard” for bioanalytical applications because of its unpreceded selectivity, sensitivity, and the ruggedness of the technology. More recently, however, high‐resolution mass spectrometry (HRMS) has become increasingly popular for bioanalytical applications. Nonetheless, this technique is still viewed, either as a screening technology or as a research tool. Although HRMS is actively discussed during scientific conferences, it is yet to be widely utilised in routine laboratory settings and there remains a reluctance to use HRMS for quantitative measurements in regulated environments. This paper does not aim to comprehensively describe the potential of the latest HRMS technology, but rather, it focuses on what results can be obtained and outlines the author's experiences over a period of many years of the routine application of various forms of HRMS instrumentation. Fifteen years ago, some nine different QqQ methods were used in the author's laboratory to analyse a variety of different veterinary drug resides. Today, many more analytes are quantified by seven HRMS methods and just three QqQ methods remain in use for the analysis of a small set of compounds yet to be upgraded to HRMS analysis. This continual upgrading and migration of analytical methods were accompanied by regularly participating in laboratory proficiency tests (PTs). The PT reports (covering a range of analytes and analytical methods) were used to compare the accuracy of HRMS‐ versus QqQ‐based measurements. In the second part of this paper, the particular strengths and limitations of HRMS for both method development and routine measurements are critically discussed. This also includes some anecdotal experiences encountered when replacing QqQ assays with HRMS methods.     

Mechanochemical reactions of some polyurethane elastomers. 3. Prediction of long-term uniaxial tensile creep using linear compliance as a basis

Based on isochronous tests the stress-strain curve for thermoplastic polyurethane elastomers (Moldotan D) is plotted and used for correcting the tensile creep data.By plotting the -logD(t) master curve the experimental data obtained can be extrapolated to longer periods.     

LR Tests for Random-Coefficient Covariance Structures in an Extended Growth Curve Model

This paper is concerned with an extended growth curve model with two within-individual design matrices which are hierarchically related. For the model some random-coefficient covariance structures are reduced. LR tests for testing the adequacy of each of these random-coefficient structures and their asymptotic null distributions are derived.     

On Testing Variance Components in Unbalanced Mixed Linear Model

The paper presents some approximate and exact tests for testing variance components in general unbalanced mixed linear model. It extends the results presented by Seifert (1992) with emphasis on the computational aspects of the problem.     

Checking for normality in linear mixed models

Linear mixed models are popularly used to fit continuous longitudinal data,and the random effects are commonly assumed to have normal distribution.However,this assumption needs to be tested so that further analysis can be proceeded well.In this paper,we consider the Baringhaus-Henze-Epps-Pulley (BHEP) tests,which are based on an empirical characteristic function.Differing from their case,we consider the normality checking for the random effects which are unobservable and the test should be based on their predictors.The test is consistent against global alternatives,and is sensitive to the local alternatives converging to the null at a certain rate arbitrarily close to 1/√ n where n is sample size.Furthermore,to overcome the problem that the limiting null distribution of the test is not tractable,we suggest a new method: use a conditional Monte Carlo test (CMCT) to approximate the null distribution,and then to simulate p-values.The test is compared with existing methods,the power is examined,and several examples are applied to illustrate the usefulness of our test in the analysis of longitudinal data.     

Empirical Measures of Wettability in Porous Media and the Relationship between Them Derived From Pore-Scale Modelling

The wettability of a crude oil/brine/rock system is of central importance in determining the oil recovery efficiency of water displacement processes in oil reservoirs. Wettability of a rock sample has traditionally been measured using one of two experimental techniques, viz. the United States Bureau of Mines and Amott tests. The former gives the USBM index, I _USBM, and the latter yields the Amott–Harvey index, I _AH. As there is no well-established theoretical basis for either test, any relationship between the two indices remains unclear.Analytical relationships between I _AH and I _USBM for mixed-wet and fractionally-wet media have been based on a number of simplifying assumptions relating to the underlying pore-scale displacement mechanisms. This simple approach provides some guidelines regarding the influence of the distribution of oil-wet surfaces within the porous medium on I _AH and I _USBM. More detailed insight into the relationship between I _AH and I _USBM is provided by modelling the pore-scale displacement processes in a network of interconnected pores. The effects of pore size distribution, interconnectivity, displacement mechanisms, distribution of volume and of oil-wet pores within the pore space have all been investigated by means of the network model.The results of these analytical calculations and network simulations show that I _AH and I _USBM need not be identical. Moreover, the calculated indices and the relationship between them suggest explanations for some of the trends that appear in experimental data when both I _USBM and I _AH have been reported in the literature for tests with comparable fluids and solids. Such calculations should help with the design of more informative wettability tests in the future.     

On the testing of marginal homogeneity with a one-sided alternative in the analysis of variance

We consider a two-factor experiment in which the factors have the same levels with a natural ordering among the levels. Likelihood ratio tests for testing equality of the main effects with a one-sided alternative and for testing the one-sided hypothesis as a null hypothesis are studied. Closed form expressions for the maximum likelihood estimates under the various hypotheses are obtained. The null hypothesis distributions for these test statistics are derived.The efforts of the first author were supported by the NSERC of Canada. The efforts of the second author were supported by the Office of Naval Research under Contract ONR N00014-80-C-0321. The efforts of the third author were supported by the Office of Naval Research under Contract ONR N00014-80-C-0322.