A Simple Method for Melatonin Determination in the Presence of High Levels of Tryptophan using an Unmodified Carbon Paste Electrode and Square Wave Anodic Stripping Voltammetry

Electrochemical determination of melatonin in the presence of tryptophan is a challenge because of the coincidence of voltammetric signals of these compounds when executing a voltammetric technique. The new method for selective determination of melatonin based on the square wave anodic stripping voltammetry determination of an electroactive product of melatonin was suggested here. This product is produced by previously applied positive pre-potential to a carbon paste electrode, immersed in the test solution. By this means, the electrochemical signal of melatonin was separated effectively from that of tryptophan, making it possible to determine melatonin in the presence of a high concentration of tryptophan. The effect of important parameters on electrode performance was studied and optimized. The optimum response was obtained at pH=2 and utilizing the pre-potential magnitude of +0.8 V, applied for 10 s. A linear relationship was found between peak current intensity and melatonin concentrations over the range of 5.00×10⁻⁷ to 8.00×10⁻⁵ mol L⁻¹. A detection limit of 8.30×10⁻⁸ mol L⁻¹ was calculated for the method (S/N=3). The selectivity of the method was considerably high, because of the independence of melatonin signal to the presence of higher amounts of some potentially interfering agents such as ascorbic acid, tryptophane glucose, etc. As an analytical application, the proposed sensor was used for the determination of melatonin in pharmaceutical and food samples.     

Community detection and service discovery on Social Internet of Things

Due to the increasing growth of objects and problems such as increased traffic, overload, delay in response, and low search volume in the service discovery process in the complex Social Internet of Things (SIoT) environment, we provide an effective mechanism in the service discovery process by grouping objects based on common criteria that help us improve service search performance. In this article, we present a new method for clustering objects so that we can group objects that have common services and can work together. Hence, we create a set of different associations for the type of service and reciprocal cooperation of objects. With its help, instead of a global network search, we can perform service searches locally more efficiently and ensure the accuracy and correctness of searches and their answers. Then, we have provided a new mechanism for the service discovery process. In addition, we categorized communities based on their size to compare our proposed algorithm with other approaches using factors such as modularity in SIoT. Finally, we achieved sufficient efficiency in service discovery (86.81% and 88.28%) and demonstrated better performance of the proposed approach in identifying communities.