Zur Gehaltsbestimmung alkaloidhaltiger Drogen

Ohne Zusammenfassung     

Neutron spectra at 0° from (p,n) reactions on 9Be, 12C,and 27Al at 647 and 800 MeV

The measured cross sections show a narrow high-energy peak (20–30 MeV/cFWHM) and a broad bump at lower momenta associated with pion production. Comparison is made to an intranuclear cascade calculation.     

Impact of molecular tilt angle on the absorption spectra of pentacene:perfluoropentacene blends

We investigate the relation between the optical properties and the average molecular tilt angle for blends of pentacene and perfluoropentacene, which can be considered as a prototypical donor–acceptor complex. Combining near‐edge X‐ray absorption fine‐structure spectroscopy and optical spectroscopy we study thin films of these compounds prepared at three different substrate temperatures T_sub. For T_sub =180 K we observe a larger average tilt angle than for blends prepared at higher substrate temperatures. This orientational change has significant impact on the uniaxial anisotropic optical properties of the mixed films which we measure post growth as well as in real‐time during growth. (© 2013 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Die elektroanalytische Bestimmung des Thalliums durch anodische Abscheidung von Thallium(III)-oxyd

Ohne Zusammenfassung     

Pion pair production in photon-photon collisions at spear

We report a measurement of the cross section for the process γγ→π⁺π^? at invariant masses 500 MeV/c² < m_ππ<2000 MeV/c². A value for the radiative width of the f(1270) tensor meson Γ_f→γγ = 3.6 ± 0.3 ± 0.5 KeV (helicity λ = 2) has been obtained from a fit to the observed ππ mass spectrum.     

Quantification of butanol and ethanol in aqueous phases by reflectometric interference spectroscopy--different approaches to multivariate calibration

This paper presents several methods for analysis of data from reflectometric interference spectroscopic measurements (RIfS) of water samples. The set-up consists of three sensors with different polymer layers. Mixtures of butanol and ethanol in water were measured from 0 to 12,000 ppm each. The data space was characterized by principal component analysis (PCA). Calibration and prediction were achieved by multivariate methods, e.g. multiple linear regression (MLR), partial least squares (PLS) with additional predictors, and quadratic partial least squares (Q-PLS), and by use of artificial neural networks. Artificial neural networks gave the best results of all the calibration methods used. Calibration and prediction of the concentration of the two analytes by artificial neural nets were robust and the set-up could be reduced to only two sensors without deterioration of the prediction.     

Different approaches to multivariate calibration of nonlinear sensor data

In this study, different approaches to the multivariate calibration of the vapors of two refrigerants are reported. As the relationships between the time-resolved sensor signals and the concentrations of the analytes are nonlinear, the widely used partial least-squares regression (PLS) fails. Therefore, different methods are used, which are known to be able to deal with nonlinearities present in data. First, the Box–Cox transformation, which transforms the dependent variables nonlinearly, was applied. The second approach, the implicit nonlinear PLS regression, tries to account for nonlinearities by introducing squared terms of the independent variables to the original independent variables. The third approach, quadratic PLS (QPLS), uses a nonlinear quadratic inner relationship for the model instead of a linear relationship such as PLS. Tree algorithms are also used, which split a nonlinear problem into smaller subproblems, which are modeled using linear methods or discrete values. Finally, neural networks are applied, which are able to model any relationship. Different special implementations, like genetic algorithms with neural networks and growing neural networks, are also used to prevent an overfitting. Among the fast and simpler algorithms, QPLS shows good results. Different implementations of neural networks show excellent results. Among the different implementations, the most sophisticated and computing-intensive algorithms (growing neural networks) show the best results. Thus, the optimal method for the data set presented is a compromise between quality of calibration and complexity of the algorithm.Electronic Supplementary Material Supplementary material is available for this article at     

Multiple inverse isotope dilution assay for the stereospecific quantitative determination of R(-) and S(+)-oxaprotiline in biological fluids

An isotope dilution assay for the determination of both oxaprotiline enantiomers in biological samples after administration of the racemic mixture has been developed. The enantiomers were reacted with synthetically prepared, optically pure N-trifluoroacetyl-S(-)-prolyl chloride, followed by high-performance liquid chromatographic separation of the diastereoisomers formed. Quantitation was performed by on-line UV detection at 260 nm and off-line radiometry by liquid scintillation counting. Endogenous compounds and metabolites do not interfere in the assay. Analysis of water and the blood and urine of rats spiked with [14C]oxaprotiline X HCl showed recoveries for S(+)-oxaprotiline X HCl (mean +/- coefficient of variation, n = 4-6) of 98.0 +/- 1.0% (water), 100.5 +/- 0.6% (blood) and 101.5 +/- 2.0% (urine), and for R(-)-oxaprotiline X HCl of 101.3 +/- 2.0% (water), 102.2 +/- 2.1% (blood) and 103.2 +/- 0.2% (urine). A pilot study to determine blood levels of the two enantiomers in two rats dosed with racemic [14C]oxaprotiline X HCl (10 mg/kg i.v.) was carried out to test the method. The results indicated stereoselective disposition of oxaprotiline enantiomers in the rat. The ratio of the areas under the blood concentration curves for R(-)-to S(+)-oxaprotiline X HCl was 1.14.