Sampling theory for Sturm–Liouville problem with boundary and transmission conditions containing an eigenparameter

In this paper, we derive the sampling theorem associated with a Sturm–Liouville problem which has two points of discontinuity and contains an eigenparameter in a boundary condition and also two transmission conditions. We establish briefly spectral properties of the problem, and then, we prove the sampling theorem associated with the problem.     

A method for the quantification of biomarkers of exposure to acrylonitrile and 1,3-butadiene in human urine by column-switching liquid chromatography–tandem mass spectrometry

1,3-Butadiene and acrylonitrile are important industrial chemicals that have a high production volume and are ubiquitous environmental pollutants. The urinary mercapturic acids of 1,3-butadiene and acrylonitrile—N-acetyl-S-(3,4-dihydroxybutyl)cysteine (DHBMA) and MHBMA (an isomeric mixture of N-acetyl-S-((1-hydroxymethyl)-2-propenyl)cysteine and N-acetyl-S-((2-hydroxymethyl)-3-propenyl)cysteine) for the former and N-acetyl-S-2-cyanoethylcysteine (CEMA) for the latter—are specific biomarkers for the determination of individual internal exposure to these chemicals. We have developed and validated a fast, specific, and very sensitive method for the simultaneous determination of DHBMA, MHBMA, and CEMA in human urine using an automated multidimensional LC/MS/MS method that requires no additional sample preparation. Analytes are stripped from urinary matrix by online extraction on a restricted access material, transferred to the analytical column, and subsequently determined by tandem mass spectrometry using labeled internal standards. The limits of quantification (LOQs) for DHBMA, MHBMA, and CEMA were 10 μg/L, 2 μg/L, and 1 μg/L urine, respectively, and were sufficient to quantify the background exposure of the general population. Precision within series and between series for all analytes ranged from 5.4 to 9.9%; mean accuracy was between 95 and 115%. We applied the method on spot urine samples from 210 subjects from the general population with no occupational exposure to 1,3-butadiene or acrylonitrile. A background exposure of the general population to acrylonitrile was discovered that is basically influenced by individual exposure to passive smoke as well as active smoking habits. Smokers showed a significantly higher excretion of MHBMA, whereas DHBMA levels did not differ significantly. Owing to its automation, our method is well suited for application in occupational or environmental studies. Figure Boxplots of the results from LC/ESI-MS/MS analysis of urinary excretion of CEMA reveal a strong correlation with nicotine metabolite cotinine, indicating that exposure to passive smoke as well as active smoking is the main source of exposure to acrylonitrile in the general population     

Poisson Distribution Series for Analytic Univalent Functions

The main objective of the present paper is to investigate the Poisson distribution series for the function class \(T\left( \alpha ,\beta \right) \) of analytic functions. Moreover, we obtain necessary and sufficient conditions for the Poisson distribution series belonging to this class. We also consider an integral operator related to the Poisson distribution series.     

Stability of solutions for a class of nonlinear cone constrained optimization problems,part 2: Application to parameter estimation

In this paper we study a problem of parameter estimation in two point boundary value problems. Using a stability theorem for nonlinear cone constrained optimization problems derived in Part 1 of this paper we investigate stability properties of the solutions of the parameter estimation problem in the output-least-squares formulation.     

Proton-induced deuteron breakup reaction2H(p,pp)n

The screening and renormalization approach allows for a mathematically correct incorporation, in three-body scattering theory, of the long-ranged Coulomb interaction between charged particles. It is based on first calculating the transition amplitudes using screened Coulomb potentials. Then, after renormalization the zero-screening limit, leading to the amplitudes pertaining to unscreened Coulomb potentials, is performed numerically. Within this formalism the proton-induced breakup of deuterons is investigated, with the Coulomb repulsion between the two protons taken into account. Kinematically complete differential cross sections in various kinematic configurations are calculated and compared with the results of an identical calculation but for the neutron-induced reaction. In this way information on the size of the Coulomb effects in the proton-deuteron reaction can be extracted. Comparison is made with experimental data at 13.0 MeV projectile energy. In addition, the quality of approximate ways of including the Coulomb interaction is studied.Dedicated to Prof. Werner Sandhas on the occasion of his 60th birthday     

Parameter estimation of an agent‐based stock price model

The influence of the behavior and strategies of traders on stock price formation has attracted much interest. It is assumed that there is a positive correlation between the total net demand and the price change. A buy order is expected to increase the price, whereas a sell order is assumed to decrease it. We perform data analysis based on a recently proposed stochastic model for stock prices. The model involves long‐range dependence, self‐similarity, and no arbitrage principle, as observed in real data. The arrival times of orders, their quantity, and their duration are created by a Poisson random measure. The aggregation of the effect of all orders based on these parameters yields the log‐price process. By scaling the parameters, a fractional Brownian motion or a stable Levy process can be obtained in the limit. In this paper, our aim is twofold; first, to devise statistical methodology to estimate the model parameters with an application on high‐frequency price data, and second, to validate the model by simulations with the estimated parameters. We find that the statistical properties of agent level behavior are reflected on the stock price, and can affect the entire process. Moreover, the price model is suitable for prediction through simulations when the parameters are estimated from real data. The methods developed in the present paper can be applied to frequently traded stocks in general. Copyright © 2013 John Wiley & Sons, Ltd.