Voltammetric determination of azithromycin at the carbon paste electrode

Azithromycin (AZ) is the first member of a class of macrolide azalides antibiotics called azolides. A simple and selective square-wave voltammetric (SWV) method has been developed for the determination of azithromycin in pure form, in pharmaceutical preparation and in biological samples. Determination of azithromycin was accomplished with hand-make carbon paste electrode (CPE) in oxidative screen mode. The counter and reference electrodes were a Pt wire and a Ag/AgCl, respectively. Various parameters that can influence the peak signal (effect of buffer, ionic strength, accumulation time, pH and the composition of the paste) have been scrutinized. The best results were obtained in acetonitrile—aqueous 1 M sodium acetate-acetic acid buffer (pH 4.6) containing 0.1 M KCl (1:9; v/v) using a 15% paraffin oil CPE. The limits of detection and quantification of the pure drug are 0.463 and 1.544 ppb (with the correlation coefficient, r=0.9785and the standard deviation, S.D.=0.1 (n=5), for the accumulation time of 60 s), respectively. The method was successfully applied to the determination of the drug in urine and two forms of pharmaceutical formulations. Recoveries were 99.2—100.5% with S.D.=0.1—and 0.8% (n=5).     

Conduction mechanism of metal-TiO2–Si structures

The conduction model has been proposed for the metal-TiO₂–Si (MIS) structures. Rutile films have been prepared on Si substrates by magnetron sputtering of TiO₂ target and annealing in the air at temperatures T?=?800 and 1050 K. The current-voltage (CVC) and capacitance-voltage characteristics of the structures have been measured over the range of T?=?283–363 K. At positive potentials on the gate, the conductivity of the MIS structures is determined by the space charge-limited current in the dielectric layer.     

Brownian motion with drift on spaces with varying dimension

Many properties of Brownian motion on spaces with varying dimension (BMVD in abbreviation) have been explored in Chen and Lou (2018). In this paper, we study Brownian motion with drift on spaces with varying dimension (BMVD with drift in abbreviation). Such a process can be conveniently defined by a regular Dirichlet form that is not necessarily symmetric. Through the method of Duhamel’s principle, it is established in this paper that the transition density of BMVD with drift has the same type of two-sided Gaussian bounds as that for BMVD (without drift). As a corollary, we derive Green function estimate for BMVD with drift.     

On the Motion of Substance in a Channel of a Network: Extended Model and New Classes of Probability Distributions

We discuss the motion of substance in a channel containing nodes of a network. Each node of the channel can exchange substance with: (i) neighboring nodes of the channel, (ii) network nodes which do not belong to the channel, and (iii) environment of the network. The new point in this study is that we assume possibility for exchange of substance among flows of substance between nodes of the channel and: (i) nodes that belong to the network but do not belong to the channel and (ii) environment of the network. This leads to an extension of the model of motion of substance and the extended model contains previous models as particular cases. We use a discrete-time model of motion of substance and consider a stationary regime of motion of substance in a channel containing a finite number of nodes. As results of the study, we obtain a class of probability distributions connected to the amount of substance in nodes of the channel. We prove that the obtained class of distributions contains all truncated discrete probability distributions of discrete random variable ω which can take values 0,1,⋯,N. Theory for the case of a channel containing infinite number of nodes is presented in Appendix A. The continuous version of the discussed discrete probability distributions is described in Appendix B. The discussed extended model and obtained results can be used for the study of phenomena that can be modeled by flows in networks: motion of resources, traffic flows, motion of migrants, etc.     

On the role of kinesthetic thinking in computational geometry

Computational geometry is a new (about 30 years) and rapidly growing branch of knowledge in computer science that deals with the analysis and design of algorithms for solving geometric problems. These problems typically arise in computer graphics, image processing, computer vision, robotics, manufacturing, knot theory, polymer physics and molecular biology. Since its inception many of the algorithms proposed for solving geometric problems, published in the literature, have been found to be incorrect. These incorrect algorithms rather than being ‘purely mathematical’ often contain a strong kinesthetic component. This paper explores the relationship between computational geometric thinking and kinesthetic thinking, the effect of the latter on the correctness and efficiency of the resulting algorithms, and their implications for education.