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Stability-indicating densitometric determination of some angiotensin II receptor antagonists in presence of their degradation products

El-Shaboury S. R., Hussein A. S., Mohamed Niveen A., El-Sutohy Mohamed M.

Acta Chromatographica

2013

Vol. 25, no. 1

79--95

A simple, selective, precise, and stability-indicating thin-layer chromatographic method has been developed and validated for analysis of some angiotensin II receptor antagonists (AIIRAs), namely, Losartan potassium (Los-K), Irbesartan (Irb), and Candesartan cilexetil (Cand) in the bulk drug and in pharmaceutical formulations (tablets). The method was based on using TLC plates pre-coated with silica gel G 60 on aluminum sheets as stationary phase and the development system was performed using chloroform:methanol (9:1) giving well separated and compact spots for all the studied drugs (RF values 0.41–0.53). The separated spots were characterized by viewing under the UV lamp, then visualized as orange spots by spraying with Dragendorff’s reagent and measured by densitometry. Under the optimum chromatographic conditions, linear relationships were obtained between response and concentrations of each studied drug with high correlation coefficients (0.9985–0.9994). Good accuracy and precision were successfully obtained for the analysis of tablets containing each drug alone or combined with diuretic drug hydrochlorothiazide (HCTZ). No interferences could be observed from the co-formulated HCTZ, commonly encountered excipients present in tablets as well as the degradation products. The results were compared successfully with reported methods and can be used as a stability-indicating assay.

A System for Reconstruction of Solid Models from Large Point Clouds

Hussein A. S.

Machine Graphics and Vision

2009

Vol. 18, No. 3

321-344

This paper presents an integrated system for reconstructing solid models capable of handling large-scale point clouds. The present system is based on new approaches to implicit surface fitting and polygonization. The surface fitting approach uses the Partition of Unity (POU) method associated with the Radial Basis Functions (RBFs) on a distributed computing environment to facilitate and speed up the surface fitting process from large-scale point clouds without any data reduction to preserve all of the surface details. Moreover, the implicit surface polygonization approach uses an innovative Adaptive Mesh Refinement (AMR) based method to adapt the polygonization process to geometric details of the surface. This method steers the volume sampling via a series of predefined optimization criteria. Then, the reconstructed surface is extracted from the adaptively sampled volume. The experimental results have demonstrated accurate reconstruction with scalable performance. In addition, the proposed system reaches more than 80% savings in the total reconstruction time for large datasets of Ο (10⁷) points.