An extended hesitant fuzzy set using SWARA-MULTIMOORA approach to adapt online education for the control of the pandemic spread of COVID-19 in higher education institutions

The world has been challenged since late 2019 by COVID-19. Higher education institutions have faced various challenges in adapting online education to control the pandemic spread of COVID-19. The present study aims to conduct a survey study through the interview and scrutinizing the literature to find the key challenges. Subsequently, an integrated MCDM framework, including Stepwise Weight Assessment Ratio Analysis (SWARA) and Multiple Objective Optimization based on Ratio Analysis plus Full Multiplicative Form (MULTIMOORA), is developed. The SWARA procedure is applied to the analysis and assesses the challenges to adapt the online education during the COVID-19 outbreak, and the MULTIMOORA approach is utilized to rank the higher education institutions on hesitant fuzzy sets. Further, an illustrative case study is considered to express the proposed idea's feasibility and efficacy in real-world decision-making. Finally, the obtained result is compared with other existing approaches, confirming the proposed framework's strength and steadiness. The identified challenges were systemic, pedagogical, and psychological challenges, while the analysis results found that the pedagogical challenges, including the lack of experience and student engagement, were the main essential challenges to adapting online education in higher education institutions during the COVID-19 outbreak.

     

Use of hollow fibre-based liquid–liquid–liquid microextraction and high-performance liquid chromatography–diode array detection for the determination of phenolic acids in fruit juices

This paper describes a simple method based on three-phase hollow-fibre liquid-phase microextraction (HF-LPME) for the determination of phenolic acids in fruit juices. Analytes including gallic acid, p-hydroxy benzoic acid, caffeic acid, syringic acid, p-coumaric acid, ferulic acid, and cinnamic acid were separated and determined using high-performance liquid chromatography–photodiode array detection (HPLC–DAD). Parameters affecting the enrichment factors (EFs) were investigated. These compounds were extracted from 5 mL aqueous samples (pH 2) to a thin layer of organic solvent (hexyl acetate) phase impregnated into the pores of the polypropylene hollow fibre wall, and then back extracted to a basic acceptor solution (0.02 M NaOH). EFs ranged from 15 (gallic acid) to 408 (cinnamic acid). The RSD of the method for the analysis of spiked water and fruit juice samples varied from 3.1% to 11.3%. The LODs ranged from 0.01 (cinnamic acid) to 2.0 (caffeic acid) μg/L.     

Modified Screening Criteria of Potential Asphaltene Precipitation in Oil Reservoirs

Abstract

In this article, the De Boer method, the most widely used screening criteria for potential asphalt precipitation, is modified by specifying separate plots for each reservoir. The solubility parameter, which is the most important parameter in this method, is calculated by using the concept of refractive index. Accuracy of the predictions was confirmed by the colloidal instability index, asphaltene–resin ratio, and asphaltene instability trend techniques. Finally, the applicability of this approach was checked using six real cases of Iranian reservoirs. These cases were chosen to include oils with different API gravity, asphaltene content, and extremities (severe to no problem).