In this article, an original method is proposed for address and covalent immobilization of anti-E. coli antibodies on a screen-printed electrode (SPE). The method is based on a copper-catalyzed “click” reaction between a polyvinylbenzylazide (PVBA) film electrochemically deposited on the electrode surface and acetylene fragments of propargyl-N-hydroxysuccinimide ester. The products of electrochemical oxidation of copper particles incorporated in the polymer film on the electrode were first used for catalysis of the click reaction. This approach allowed us to reduce the immobilization time from a few hours for conventional methods to just 30 min, and to prevent denaturation of the immunoreceptor. The modified electrodes were characterized by scanning electron microscopy (SEM), electrochemical impedance spectroscopy (EIS), and cyclic voltammetry (CV). Based on the results obtained, a label-free impedimetric immunosensor for E. coli detection was developed. The detection limit of the immunosensor was estimated as 6.3 CFU/ml, with a linear range of 103–106 CFU/ml. The immunosensor demonstrated good stability during 30 days of storage in phosphate buffer solution (PBS, pH 7) and selectivity toward excess Staphylococcus aureus bacteria.

Distributed automatic weather stations networks (AWSN) play an important role in modern weather forecasting and digitalization of agriculture. These networks allow to monitor various environment parameters and transmit actual data in real time to data centers, which makes possible to dramatically increase the efficiency of technical processes controlling farming. Since these networks may cover large areas, weather stations may use other stations to connect to gateways via multihop routes. The nodes are deployed outdoors and they are subject to failures due to harsh environment, deterioration of equipment, battery discharge, etc. If a station is used as a relay for other nodes, after its failure other stations may also become unavailable. To study the network reliability in this paper we propose a general methodology, consisting of six consolidated procedures, and apply the apparatus of the multidimensional alternating stochastic processes. We demonstrate the application of this analytical method for a special case of the minimal topology AWSN. General topology cases are studied with the use of the simulation approach. To study the numerical results, a discrete-event simulation model in Python language was developed. The paper presents numerical reliability analysis for three types of topologies: a simple network with three stations, a forest of ternary trees and random multihop networks with one or more gateways. In all scenarios we estimate reliability for the cases of static and dynamic routing. Different ways to enhance the distributed network reliability are discussed.

The paper briefly describes a mathematical model of multiservice traffic processing in a data network. Methods for the model’s quality indicator assessment based on working out a system of equilibrium equations and its subsequent solving by means of the iterative Gauss-Seidel method are proposed. The work presents numerical results and their usage for planning the values of the model’s structural parameters such as evaluation results of the rate in the cell providing the service of specified request flows of real time and non-real time traffic with the predetermined amount of maximum losses as well as results of the rate estimation in the cell, which provides the service of the specified requests flows of elastic traffic and real time services traffic, with the specified values of the maximum losses and the average elastic traffic transfer time.

Taking account for the graph randomness, our purpose is a node classification by their extremal indexes (EI) as the local dependence measure of node influence characteristics. The EI was calculated by node PageRanks of the local tree related to the node, which is a kind of Thorny Branching Tree (TBT). The blocks estimator was used for the EI estimation by sliding and disjoint block definitions. The classification by the node EI value and the average block size for the local node TBT was introduced for simulated graphs by the Forest Fire and Erdős-Rényi Models and the Berkeley-Stanford dataset as a real example. The new classification methodology is proposed irrespective on the graph structure.

We model the distribution tails of the end-to-end delay of services with the help of two-parameter Weibull-tail and log-Weibull-tail distributions. First we discuss the role of the Weibull-tail and log-Weibull-tail distributions in statistics of extremes. Then we propose the statistical procedure based on the largest observations of a sample to decide between these two tail models and to estimate the parameters of the selected model. The proposed procedure allows us to estimate the extreme quantiles from the Weibull-tail and log-Weibull-tail distributions in an unified way. The efficiency of the introduced methods is illustrated on a small simulation study.