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We report on the development of a simple and cost-effective potentiometric sensor array that is based on manual "drawing" on the polymeric support with the pencils composed of graphite and different types of zeolites. The sensor array demonstrates distinct sensitivity towards a variety of inorganic ions in aqueous media. This multisensor system has been successfully applied to quantitative analysis of 100 real-life surface waters sampled in Mahananda and Hooghly rivers in the West Bengal state (India). Partial least squares regression has been utilized to relate responses of the sensors to the values of different water quality parameters. It has been found that the developed sensor array, or electronic tongue, is capable of quantifying total hardness, total alkalinity, and calcium content in the samples, with the mean relative errors below 18%.

Fast and inexpensive analytical tools for identification of the origin of pharmaceutical formulations are important to ensure consumers safety. This study explores the potential of potentiometric multisensor systems ("electronic tongues") in this type of application. 72 paracetamol samples purchased in different countries and produced by various companies were studied via infrared spectroscopy (IR), near infrared spectroscopy (NIR), nuclear magnetic resonance spectroscopy (NMR) and multisensor system (ET). A variety of chemometric tools was applied to explore and compare the information yielded by these methods. It was found that ET is capable of distinguishing paracetamol formulations from different producers. The chemical information derived from potentiometric sensor responses has something in common with that derived from NIR and IR; however, it is orthogonal to that from NMR. ET can be a valuable tool in express quality assessment of drugs., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

The paper describes a wide-range practical application of the potentiometric multisensor system (MS) (1) for integral safety evaluation of a variety of natural waters at multiple locations, under various climatic conditions and anthropogenic stress and (2) for close to real consistency evaluation of waste water purification processes at urban water treatment plants. In total, 25 natural surface water samples were collected around St. Petersburg (Russia), analyzed as is, and after ultrasonic treatment. Toxicity of the samples was evaluated using bioassay and MS. Relative errors of toxicity assessment with MS in these samples were below 20%. The system was also applied for fast determination of integral water quality using chemical oxygen demand (COD) values in 20 samples of water from river and ponds in Kolkata (India) and performed with an acceptable precision of 20% to 22% in this task. Furthermore, the MS was applied for fast simultaneous evaluation of COD, biochemical oxygen demand, inorganic phosphorous, ammonia, and nitrate nitrogen at two waste water treatment plants (over 320 samples). Reasonable precision (within 25%) of such analysis is acceptable for rapid water safety evaluation and enables fast control of the purification process. MS proved to be a practicable analytical instrument for various real-world tasks related to water safety monitoring., Competing Interests: The authors declare no conflict of interest.

In this paper, a new electronic system for gas detection is presented. Particular attention is focused on electronic noses that employ several resistive sensors. New resistive sensors may have high value due to new substances (TiO2) or to low-cost fabrication process and, supposing to use these sensors together with traditional ones (SnO2), a novel instrument to manage high-value resistive sensors varying over a wide range, from kilohms to gigohms is required. The proposed hardware approach is a modular architecture which takes advantage from an improved resistance-to-period converter, where sensors are DC powered. Experimental results show a relative standard deviation below 0.01% and a relative displacement to the reference line less than 1% over six decades if commercial resistors are considered. A prototype has been realized to manage up to eight sensors, detect and estimate substance concentrations, and communicate results to the Internet. [ABSTRACT FROM PUBLISHER]

Abstract: In this paper, a new variable selection technique inspired in sequential forward selection but specifically designed to work with support vector machines is introduced. The usefulness of the variable selection coupled to support vector machines for solving classification and regression problems is assessed by analysing two different databases. The first database corresponds to different concentrations of vapours and vapour mixtures measured with a metal oxide gas-sensor e-nose and the second database corresponds to different Iberian hams measured with a mass-spectrometry based e-nose. Using a reduced set of important variables (i.e. reducing the dimensionality of input space by the variable selection procedure) results in support vector machines with better performance. For example, the success rate in ham classification (11-class problem) rises from 79.91% (when all the variables available are used) to 90.30% (when a reduced set of input variables is used). Furthermore, a quantitative analysis of ham samples with good accuracy is shown to be possible: when the variable selection process introduced is coupled to support vector machine regression models, the correlation coefficients of actual versus predicted humidity, water activity and salt in ham samples are 0.975, 0.972 and 0.943, respectively. This compares favourably with the correlation coefficients obtained when no variable selection is performed (0.937, 0.924 and 0.894). [Copyright &y& Elsevier]

In the present work, the use of the cluster analysis method in the "fuzzy logic" concept for the optimization of the cross-selective sensor arrays ("electronic nose", EN) is considered. This approach enables to purposefully form the sensor arrays with definite chemical functionality optimized for the solution of the specific applied problems. The criteria of the optimization of the sensor response, number and type of the sensor elements are considered with the goal to improve the classification of widely used pharmaceutical products. The optimization of EN array in the kinetic mode and selection of the most informative part of the sensor response enabled to reduce the analysis time, and also the number of sensors in array, to improve the discriminatory capability of the whole array. Being based on the analysis of response kinetic peculiarities, the physical mechanisms determining the peculiarities of adsorption-desorption processes at the interface have been considered. [ABSTRACT FROM AUTHOR]