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Structural Elucidation, Optical and Magnetic Properties of Tetraphenylborate Salt of 2,5-[1-Methyl-4-[2-(4-hydroxyphenyl)ethenyl)]pyridinium]-butane

Stoyanov S., Koleva B. B., Kolev T., Petkov I., Spiteller M.

Polish Journal of Chemistry

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2008

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Vol. 82, nr 11

2167-2178

EN

Structure, magnetic and optical properties of tetraphenylborate salt of 2,5-[1-methyl-4-[2-(4-hydroxyphenyl)ethenyl)]pyridinium]-hexane were performed for condensed phase by means of solution and solid-state conventional and linear-polarized IR-spectroscopy of oriented colloids in nematic host, UV-Vis and fluorescence methods, HPLC MS-MS tandem and ESI mass spectrometry, 1H-, 13C- and 1H-1H COSY NMR, TGV and DSC methods. Electronic structure and vibrational analysis were carried out by quantum chemical calculations at two levels of theory second-order Moller-Plesset perturbation theory (MP2) and density functional theory (DFT) using 6-31G* basis set. B3LYP method, which combines Becke's three-parameter non-local exchange functional with the correlation function of Lee, Yang and Parr, was applied.

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Asymptotic distribution of unbiased linear estimators in the presence of heavy-tailed stochastic regressors and residuals

Samorodnitsky G., Rachey S. T., Kurz-Kim J.-R., Stoyanov S.

Probability and Mathematical Statistics

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2007

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Vol. 27, Fasc. 2

275--302

EN

Under the symmetric а-stable distributional assumption for the disturbances, Blattberg and Sargent [3] consider unbiased line- ar estimators for a regression model with non-stochastic regressors. We study both the rate of convergence to the true value and the asymptotic distribution of the normalized error of the linear unbiased estimators. By doing this, we allow the regressors to be stochastic and disturbances to be heavy-tailed with either finite or infinite variances, where the tail-thickness parameters of the regressors and disturbances may be different.

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Computing the portfolio conditional value-at-risk in the α-stable case

Stoyanov S., Samorodnitsky G., Rachev S. T., Ortobelli S.

Probability and Mathematical Statistics

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2006

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Vol. 26, Fasc. 1

1--22

EN

The class of α-stable distributions is an attractive probabilistic model of asset returns distribution in the field of finance. When dealing with real issues, such as optimal portfolio selection, it is important that we can compute the Conditional Value-at-Risk (CVaR) accurately. The CVaR is also known as the expected tail loss (ETL) proposed in literature as a coherent risk measure. In our paper we propose an integral expression for the calculation of the CVaR of a stable law. We compare the current approach to some existing method and we demonstrate how to relate the derived result to some common multivariate distributional assumptions.

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Robust compensator control of aerobic continuous fermentation processes with state estimation

Simeonov I., Stoyanov S., Lubenova V.

Archives of Control Sciences

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2003

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Vol. 13, no. 1

5-18

EN

The paper deals with robust compensator control of continuous aerobic fermentation processes described by a set of non-linear differential equations. For design purposes the non-linear model is transformed into a linear one with interval parameters. the robust state-space compensator is designed according to the internal model principle. Biomass concentration is estimeted on-line by an observer. Substrate concentration is obtained by model-based or indirect measurement. The theoretical results are verified by simulations in different cases. Robustness and simple realisation are important features of the proposed algorithms.