Examination of the ECG signal classification technique DEA-ELM using deep convolutional neural network features

Multimedia Tools and Applications - The accurate separation of ECG signals has become crucial to identify heart diseases. Machine learning methods are widely used to separate ECG signals. The aim...     

Perovskite catalysts for methane combustion: applications,design, effects for reactivity and partial oxidation

This review underlines the importance of the developments in perovskite catalysts for methane combustion from the past up to the present. In this review, after a general and brief introduction to perovskites, the mechanisms of catalytic combustion of methane have been included. Moreover, current studies on perovskites have been summarized including the effects of substitutions, doped perovskites, perovskite preparation methods, and the effect of sulfur presence on perovskite catalysts. Besides, recent studies on perovskite oxides and phenomenon of oxygen (O₂) deficiency, porous perovskite oxides, and nanostructured perovskites have been conducted. In addition, partial oxidation of methane (POM) has been reviewed. The loss of active component during the POM reaction can take place in the nickel catalyst, in particular. Since nickel has a lower melting point than noble metals and other active components, such as Co and Fe, in general, to deactivate nickel is easier. Compared with conventional structure, the porous structure with the unique morphology significantly enhances the catalytic activity through a much larger surface area (SA) and greater reactivity of the active sites. Furthermore, the monolithic nanoarrayed perovskite presents very good results in well‐defined faceted catalysts and takes part in porous channel hydrocarbon combustion. This review study is prepared as a guide to cover the profound knowledge of perovskite oxides catalysts, considering the methane combustion reaction mechanisms, and addresses prospective studies in this field for researchers.     

Ring Opening of Epoxidized Soybean Oil with Compounds Containing Two Different Functional Groups

Epoxidized vegetable oils are desirable chemicals due to their eco‐friendly characteristics and their being a major source of many green products. Ring opening is one of the ways to convert these epoxidized oils to some new intermediates. The use of mono‐functional amines, alcohols, acid anhydrides and thioethers for epoxy ring opening has been reported in the literature. In this study, thioglycolic acid (TGA) bearing thiol and carboxylic acid as two different functional groups and methyl ester of thioglycolic acid (TGAME) were used. Currently, there is no reported literature describing epoxy ring opening using chemicals bearing two different functional groups simultaneously. In this way, two new polyols were synthesized, one with TGA (polyol 1) and one with TGAME (polyol 2). FTIR and ¹H‐ and ¹³C‐NMR spectroscopy confirmed that the ring was opened by the carboxylic acid group of TGA, and the thiol group was not involved in the ring opening whereas the ring was opened by the thiol group in the case of TGAME.     

An Overview on SARS‑CoV‑2(COVID‑19)and Other Human Coronaviruses and Their Detection Capability via Amplification Assay,Chemical Sensing,Biosensing,Immunosensing,and Clinical Assays

A novel coronavirus of zoonotic origin(SARSCoV-2)has recently been recognized in patients with acute respiratory disease.COVID-19 causative agent is structurally and genetically similar to SARS and bat SARS-like coronaviruses.The drastic increase in the number of coronavirus and its genome sequence have given us an unprecedented opportunity to perform bioinformatics and genomics analysis on this class of viruses.Clinical tests like PCR and ELISA for rapid detection of this virus are urgently needed for early identification of infected patients.However,these techniques are expensive and not readily available for point-of-care(POC)applications.Currently,lack of any rapid,available,and reliable POC detection method gives rise to the progression of COVID-19 as a horrible global problem.To solve the negative features of clinical investigation,we provide a brief introduction of the general features of coronaviruses and describe various amplification assays,sensing,biosensing,immunosensing,and aptasensing for the determination of various groups of coronaviruses applied as a template for the detection of SARS-CoV-2.All sensing and biosensing techniques developed for the determination of various classes of coronaviruses are useful to recognize the newly immerged coronavirus,i.e.,SARS-CoV-2.Also,the introduction of sensing and biosensing methods sheds light on the way of designing a proper screening system to detect the virus at the early stage of infection to tranquilize the speed and vastity of spreading.Among other approaches investigated among molecular approaches and PCR or recognition of viral diseases,LAMP-based methods and LFAs are of great importance for their numerous benefits,which can be helpful to design a universal platform for detection of future emerging pathogenic viruses.     

Influence of Electron Beam Irradiation on High‐Temperature Mechanical Properties of Ethylene Vinyl Acetate/Carbon Fibers Composites

The purpose of this study was to investigate the effect of carbon fiber (CF) and electron‐beam (EB) radiation on high‐temperature mechanical properties of ethylene‐vinyl acetate (EVA). Polymer composites were prepared by mixing on a two‐roll mill. After compression molding, the samples were irradiated between 60 and 180 kGy, and dynamic mechanical analysis (DMA) was used to characterize physical properties. The effects of filler content and radiation level on the mechanical properties of EVA/CF were evaluated. The shear stress and modulus were observed to increase with increasing of the filler level. However, there was a dramatic decrease in creep compliance. It was also shown that introduction of irradiation on EVA composite increases the shear stress and the real part of the dynamic shear modulus G' due to the increase in molecular weight and cross‐linking of the polymer after irradiation. J. VINYL ADDIT. TECHNOL., 26:325–335, 2020. © 2019 Society of Plastics Engineers     

Determination of industrial pollution effects on citrus honeys with chemometric approach

The aim of this study was to determine the levels of essential, trace and toxic elements, such as K, Ca, Fe, Cu, Al, Ni, Sn, Pb and Cd in citrus honeys from different regions (industrialized and nonindustrialized) of Hatay, Turkey. K, Ca, Na and Mg were the most abundant elements, with mean contents of 363.5, 256.6, 88.1 and 37.7 mg/kg, respectively. The trace element mean contents ranged between 0.032 and 15.58 mg/kg. Significant differences in Fe, Cu, Al, Ni, Sn, Pb, Cd, Co and Sr levels were observed between two different regions. The findings that Fe, Cu, Al, Ni, Sn, Pb, Cd, Co and Sr contents in citrus honeys from industrialized regions were higher than citrus honeys from non-industrialized regions indicate that the honeys were affected by industrial pollution. Chemometric methods were applied to classify honey according to mineral content. Cluster analysis showed three clusters corresponding to the three different regions.     

Forecasting of entropy production due to buoyant convection using support vector machines (SVM) in a partially cooled square cross-sectional room

Forecasting of entropy generation of laminar natural convection in a partially cooled square cross-sectional room has been performed using support vector machines (SVM). The two-dimensional room was modeled as floor heating story with a window. Values of temperature and velocities were obtained by solving governing equations of natural convection with finite difference technique and using these values entropy generation was calculated with its definition. Forecasting of entropy generation due to fluid friction irreversibility (FFI) and heat transfer irreversibility (HTI) were made with known values for unknown parameters using SVM. Thus, calculation time was extremely reduced and values were obtained even for non-convergence cases. It was observed that the SVM was a strong method to predict the entropy generation without computational fluid dynamic analysis for all cases.     

A COMPARATIVE STUDY ON PARTICLE SWARM OPTIMIZATION AND GENETIC ALGORITHMS FOR TRAVELING SALESMAN PROBLEMS

This article deals with a performance evaluation of particle swarm optimization (PSO) and genetic algorithms (GA) for traveling salesman problem (TSP). This problem is known to be NP-hard, and consists of the solution containing N! permutations. The objective of the study is to compare the ability to solve the large-scale and other benchmark problems for both algorithms. All simulation has been performed using a software program developed in the Delphi environment. As yet, overall results show that genetic algorithms generally can find better solutions compared to the PSO algorithm, but in terms of average generation it is not good enough.