On some qualitative behaviors of certain differential equations of fourth order with multiple retardations

In this paper, we give sufficient conditions to guarantee the asymptotic stability and boundedness of solutions to a kind of fourth-order functional differential equations with multiple retardations. By using the Lyapunov-Krasovskii functional approach, we establish two new results on the stability and boundedness of solutions, which include and improve some related results in the literature     

Determination of Naphthazarin Derivatives in 16 Alkanna Species by RP-LC Using UV and MS for Detection

As part of our ongoing studies, a new and validated method for analysis of isohexenyl-naphthazarines in Turkish Alkanna species was developed. By using reversed phase material (Synergi MAX RP) it was possible to determine four known isohexenylnaphthazarin-derivatives, namely alkannin, acetylalkannin, deoxyalkannin, and β,β-dimethylacrylalkannin within 25 min in n-hexane extracts of the roots. The quantification of these compounds in 16 Anatolian Alkanna species is described for the first time. In order to assure peak identity LC-MS experiments were performed. Quantitative results revealed that the most dominant compound in the extracts was β,β-dimethylacrylalkannin.     

On locally closedness and continuity

The aim of this paper is to introduce new classes of sets called δ-semi-generalized closed sets, locally δ-semi-generalized closed, lδsgc^*-sets, lδsgc^**-sets. Also, we introduce several forms of LδSGC-continuous functions. We discuss their properties and several examples are provided to illustrate the behaviour of these new types of sets and functions.     

Mathematical algorithms applied to the multi-linear regression functions for the multicomponent determination of pharmaceutical dosage form containing three-component mixtures

In the presence of closely overlapping spectra, the quantitative multiresolution of ternary mixtures of three active compounds paracetamol (PAR), caffeine (CAF) and acetylsalycilic acid (ASP) in tablets, without using pretreatment such as separation step and graphical procedure of spectra was accomplished by the multivariate spectral calibration models, tri-linear regression calibration (TLRC), multi-linear regression calibration (MLRC) and Cramer's rule solution (CRS) of three linear equation functions in the matrix form. In the first two models, TLRC and MLRC are based on the use of the linear regression functions at selected wavelength sets in the spectral region of 210-300 nm. In the case of CRS model, A1(1) (1%, 1 cm) were used to obtain three linear equation functions and this linear equation system was resolved by the Cramer's rule for the prediction of PAR, CAF and ASP in samples. In the TLRC and CRS models, the selection of the appropriate wavelength set was performed by the Kaiser's technique. The algorithms of these mathematical calibration models were briefly described. The validation of TLRC, MLRC and CRS models was carried out by analyzing various synthetic ternary mixtures and by using the standard addition technique. These three calibration approaches were applied to the analysis of the real pharmaceutical tablets containing PAR, CAF and ASP. The obtained results were statistically compared with each other by using experimental and statistical tests. In the comparison of TLRC and MLRC models to the classical approach, CRS technique, the successful assay results were observed for the quantitative multiresolution of ternary mixture of the subject active compounds.     

Determination of trace cadmium in waters by flame atomic absorption spectrophotometry after preconcentration with 1-nitroso-2-naphthol-3,6-disulfonic acid on Ambersorb 572

A procedure for the determination of trace amount of cadmium after adsorption of its 1-nitroso-2-naphthol-3,6-disulfonic acid chelate on Ambersorb 572 has been proposed. This chelate is adsorbed on the adsorbent in the pH range 3-8 from large volumes of aqueous solution of water samples with a preconcentration factor of 200. After being sorbed, cadmium was eluted by 5 mL of 2.0 mol L(-1) nitric acid solution and determined directly by flame atomic absorption spectrophotometery (FAAS). The detection limit (3sigma) of cadmium was 0.32 microg L(-1). The precision of the proposed procedure, calculated as the relative standard deviation of recovery in sample solution (100 mL) containing 5 microg of cadmium was satisfactory (1.9%). The adsorption of cadmium onto adsorbent can formally be described by a Langmuir equation with a maximum adsorption capacity of 19.6 mg g(-1) and a binding constant of 6.5 x 10(-3) L mg(-1). Various parameters, such as the effect of pH and the interference of a number of metal ions on the determination of cadmium, have been studied in detail to optimize the conditions for the preconcentration and determination of cadmium in water samples. This procedure was applied to the determination of cadmium in tap and river water samples.     

Spectrophotometric multicomponent determination of sunset yellow, tartrazine and allura red in soft drink powder by double divisor-ratio spectra derivative, inverse least-squares and principal component regression methods

Double divisor-ratio spectra derivative (graphical method), classical least-squares and principal component regression (two numerical methods) methods were developed for the spectrophotometric multicomponent analysis of soft drink powders and synthetic mixtures containing three colorants without any chemical separation. The graphical method is based on the use of derivative signals of the ratio spectra using double divisor. In this method, the linear determination ranges were 2-8 mug ml(-1) sunset yellow, 4-18 mug ml(-1) tartrazine and 2-8 mug ml(-1) allura red in 0.1 M HCl. In the numerical methods, a training set was randomly prepared by using 18 samples containing between 0 and 8 mug ml(-1) of sunset yellow, 0-18 mug ml(-1) of tartrazine and 0-8 mug ml(-1) of allura red. The chemometric calibrations were calculated by using the prepared training set and its absorbances at seven points (from 375.0 to 550.0 nm) in the spectral region 325-584 nm. The proposed methods were validated by using synthetic ternary mixtures and applied to the simultaneous determination of three colorants in soft drink powders. The obtained results were statistically compared with each other.     

Atomic absorption spectrophotometric determination of trace copper in waters, aluminium foil and tea samples after preconcentration with 1-nitroso-2-naphthol-3,6-disulfonic acid on Ambersorb 572

An atomic absorption spectrophotometric method for the determination of trace copper after adsorption of its 1-nitroso-2-naphthol-3,6-disulfonic acid chelate on Ambersorb 572 has been developed. This chelate is adsorbed on the adsorbent in the pH range 1–8. The copper chelate is eluted with 5 ml of 0.1 mol l⁻¹ potassium cyanide and determined by flame atomic absorption spectrometry (FAAS). The selectivity of the proposed procedure was also evaluated. Results show that iron(III), zinc(II), manganese(II) and cobalt(II) at the 50 μg l⁻¹ level and sodium(I), potassium(I), magnesium(II), calcium(II) and aluminium(III) at the 1000 μg l⁻¹ level did not interfere. A high enrichment factor, 200, was obtained. The detection limit (3σ) of copper was 0.34 μg l⁻¹. The precision of the method, evaluated by seven replicate analyses of solutions containing 5 μg of copper was satisfactory and the relative standard deviation was 1.7%. The adsorption of copper onto Ambersorb 572 can formally be described by a Langmuir equation with a maximum adsorption capacity of 14.3 mg g⁻¹ and a binding constant of 0.00444 l mg⁻¹. The accuracy of the method is confirmed by analysing tomatoes leaves (NIST 1573a) and lead base alloy (NBS 53e). The results demonstrated good agreement with the certified values. This procedure was applied to the determination of copper in waters (tap, river and thermal waters), aluminium foil and tea samples.     

The Semi-Infinite q-Boson System with Boundary Interaction

Upon introducing a one-parameter quadratic deformation of the q-boson algebra and a diagonal perturbation at the end point, we arrive at a semi-infinite q-boson system with a two-parameter boundary interaction. The eigenfunctions are shown to be given by Macdonald’s hyperoctahedral Hall–Littlewood functions of type BC. It follows that the n-particle spectrum is bounded and absolutely continuous and that the corresponding scattering matrix factorizes as a product of two-particle bulk and one-particle boundary scattering matrices.     

An approach to best proximity points results via simulation functions

In this paper, we investigate of the existence of the best proximity points of certain mapping defined via simulation functions in the frame of complete metric spaces. We consider the uniqueness criteria for such mappings. The obtained results unify a number of the existing results on the topic in the literature.     

Artificial neural network combined with principal component analysis for resolution of complex pharmaceutical formulations

A chemometric approach based on the combined use of the principal component analysis (PCA) and artificial neural network (ANN) was developed for the multicomponent determination of caffeine (CAF), mepyramine (MEP), phenylpropanolamine (PPA) and pheniramine (PNA) in their pharmaceutical preparations without any chemical separation. The predictive ability of the ANN method was compared with the classical linear regression method Partial Least Squares 2 (PLS2). The UV spectral data between 220 and 300 nm of a training set of sixteen quaternary mixtures were processed by PCA to reduce the dimensions of input data and eliminate the noise coming from instrumentation. Several spectral ranges and different numbers of principal components (PCs) were tested to find the PCA-ANN and PLS2 models reaching the best determination results. A two layer ANN, using the first four PCs, was used with log-sigmoid transfer function in first hidden layer and linear transfer function in output layer. Standard error of prediction (SEP) was adopted to assess the predictive accuracy of the models when subjected to external validation. PCA-ANN showed better prediction ability in the determination of PPA and PNA in synthetic samples with added excipients and pharmaceutical formulations. Since both components are characterized by low absorptivity, the better performance of PCA-ANN was ascribed to the ability in considering all non-linear information from noise or interfering excipients.