Yarrowia lipolytica as an Alternative and Valuable Source of Nutritional and Bioactive Compounds for Humans

Yarrowia lipolytica, an oleagineous species of yeast, is a carrier of various important nutrients. The biomass of this yeast is an extensive source of protein, exogenous amino acids, bioavailable essenctial trace minerals, and lipid compounds as mainly unsaturated fatty acids. The biomass also contains B vitamins, including vitamin B12, and many other bioactive components. Therefore, Y. lipolytica biomass can be used in food supplements for humans as safe and nutritional additives for maintaining the homeostasis of the organism, including for vegans and vegetarians, athletes, people after recovery, and people at risk of B vitamin deficiencies.     

Empirical wavelet analysis of tail and memory properties of LARCH and FIGARCH models

Using computationally efficient wavelet methods, we study two nonlinear models of financial returns {r _t }: linear ARCH (LARCH) and fractionally integrated GARCH (FIGARCH). We estimate the tail index α and the long memory parameter d of the squared returns X_t = r_t²{X_t= r_t^2} of LARCH, and of the powers X _t = |r _t | ^p of FIGARCH. We find that the X _t have infinite variance and long memory, and show how the estimates of α and d depend on the model parameters. These relationships are determined empirically, as the setting is quite complex, and no suitable theory has been developed so far. In particular, we provide empirical relationships between the estimates [^(d)]{\hat d} and the difference parameters in LARCH and FIGARCH. Our computational work uncovers tail and memory properties of LARCH and FIGARCH for practically relevant parameter ranges, and provides some guidance on modeling returns on speculative assets including FX rates, stocks and market indices.     

X-ray emission spectroscopy of nitrogen-rich compounds

Nonresonant X-ray emission spectroscopy was used to compare the nitrogen-rich compounds ammonium nitrate, trinitrotoluene, and cyclotrimethylene-trinitramine. They are representative of crystalline and molecular structures of special importance in industrial and military applications. The spectral signature of each substance was analyzed and correlated with features in the electronic structure of the systems. This analysis was accomplished by means of theoretical simulations of the emission spectra and a detailed examination of the molecular orbitals and densities of states. We find that the two theoretical methods used (frozen-orbital density functional theory and real-space Green's function simulations) account semiquantitatively for the observed spectra and are able to predict features arising from distinct chemical complexes. A comparison of the calculations and the data provides insight into the electronic contributions of specific molecular orbitals, as well as the features due to bandlike behavior. With some additional refinements, these methods could be used as an alternative to reference compounds.     

Papierchromatographie der einwertigen Phenole als p-Nitrophenylazofarbstoffe

Zusammenfassung Mit der Papierchromatographie wurden einwertige Phenole in Form von p-Nitrophenylazofarbstoffen getrennt. Phenole mit substituierter p-Position wurden mit dem Laufmittel Paraffinöl/Eisessigsäure-Wasser Dimethylformamid oder Paraffinöl/Phenol-Ameisensäure-Wasser, Phenole mit unbesetzter p-Position mit Formamid/Kohlenstofftetrachlorid Hexan getrennt. Das Verfahren eignet sich besonders für die qualitative Bestimmung von einwertigen Phenolen in der Wasserchemie.

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Summary Monohydric phenols were separated as p-nitrophenylazo dyes by means of paper chromatography. Phenols with substituted p-position were separated in a paraffin oil/acetic acid-water-dimethylformamide or paraffin oil/phenol-formic acid-water system, phenols with free p-position with a formamide/carbontetrachloride-hexane system. The procedure is specially suitable for the qualitative determination of monohydric phenols in water analysis.

     

Numerical modeling of laser–matter interaction in the region of “low” laser parameters

The interaction of laser radiation with matter leads to the certain kinds of modelling of its surface or volume. These effects have been demonstrated for a lot of materials, even causing the formation of new scientific and industrial domain, which is undoubtedly laser material processing and as well as laser cleaning of artworks. Those applications lie in the so-called “low' region of laser energy densities, represented for short laser pulses by power densities below 10⁹ W/cm². Paper presents set of equations describing in one-dimensional (1D) model phenomena accompanying to laser–matter interaction. Target geometry includes two and four layers of different materials, irradiated by ns laser pulses. Effects of radiation absorption and transport, heat conductivity, target transit to plastic state, melting and evaporation are taken into consideration. The part of the paper is devoted to the discussion of numerical results, selected in such a way to illustrate the phenomenon of radiation interaction with materials as well as to show, in whole, possibilities of computer simulation methods.     

Robust Wavelet-Domain Estimation of the Fractional Difference Parameter in Heavy-Tailed Time Series: An Empirical Study

We investigate the performance of several wavelet-based estimators of the fractional difference parameter. We consider situations where, in addition to long-range dependence, the time series exhibit heavy tails and are perturbed by polynomial and change-point trends. We make detailed study of a wavelet-domain pseudo Maximum Likelihood Estimator (MLE), for which we provide an asymptotic and finite-sample justification. Using numerical experiments, we show that unlike the traditional time-domain estimators, estimators based on the wavelet transform are robust to additive trends and change points in mean, and produce accurate estimates even under significant departures from normality. The Wavelet-domain MLE appears to dominate a regression-based wavelet estimator in terms of smaller root mean squared error. These findings are derived from a simulation study and application to computer traffic traces.