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For a nation to become a superpower, it's scientific and technological advancement is essential. Each country is exploring how to improve themselves in terms of science and technology. The authors analyzed the innovation capabilities of 35 OECD countries that have not recently joined Lithuania.

In recent years, a lot of research work has been done on trapezoidal interval type-2 fuzzy sets (TIT-2 FS), and many research works have been published. The trapezoidal interval type-2 fuzzy set helps effectively to represent the uncertainty comparatively than the type-1 fuzzy set. Taking advantage of this effectiveness, the authors extend the best multi-criteria decision making method (MCDM) for trapezoidal interval type-2 fuzzy sets. Here, ELimination and Choice Expressing REality III (ELECTRE III) method in the trapezoidal interval type-2 fuzzy set environment is proposed.

This analysis helps to the OECD countries to develop their level of innovation in the criteria. The authors are making this evaluation for the year 2018 based on the 31 criteria. Application of the proposed method expressed by evaluation of the national innovation capability problem. Based on the obtained results, the top five countries are United States, Switzerland, Canada, Germany and Japan.

The authors collected required data from different available data sources like OECD, IMD, USPTO, ITU and surveyed data reported by KISTEP. After collecting all the data from different sources, the authors calculated the standard values as KISTEP. After converting the standard values into trapezoidal interval type-2 fuzzy values, the authors construct a decision matrix based on these values. Then, the authors determined the possibility mean values and preference. Then, they calculated the concordance and discordance credibility degree values. Finally, they ranked OECD countries by the net credibility degree. The results are computed by using the MATLAB software.

This paper aims to apply several data mining techniques for predicting the daily precision improvement of Jakarta Islamic Index (JKII) prices based on big data of symmetric volatility in Indonesia’s Islamic stock market.

This research uses big data mining techniques to predict daily precision improvement of JKII prices by applying the AdaBoost, K-nearest neighbor, random forest and artificial neural networks. This research uses big data with symmetric volatility as inputs in the predicting model, whereas the closing prices of JKII were used as the target outputs of daily precision improvement. For choosing the optimal prediction performance according to the criteria of the lowest prediction errors, this research uses four metrics of mean absolute error, mean squared error, root mean squared error and R-squared.

The experimental results determine that the optimal technique for predicting the daily precision improvement of the JKII prices in Indonesia’s Islamic stock market is the AdaBoost technique, which generates the optimal predicting performance with the lowest prediction errors, and provides the optimum knowledge from the big data of symmetric volatility in Indonesia’s Islamic stock market. In addition, the random forest technique is also considered another robust technique in predicting the daily precision improvement of the JKII prices as it delivers closer values to the optimal performance of the AdaBoost technique.

This research is filling the literature gap of the absence of using big data mining techniques in the prediction process of Islamic stock markets by delivering new operational techniques for predicting the daily stock precision improvement. Also, it helps investors to manage the optimal portfolios and to decrease the risk of trading in global Islamic stock markets based on using big data mining of symmetric volatility.

This research is a pioneer in using big data mining of symmetric volatility in the prediction of an Islamic stock market index.

The paper aims to discuss the evaluation of anti-corrosive efficiency of conducting polymer, polypyrrole in water borne epoxy-polyamine coatings.

Polypyrrole (PPy) is synthesised by chemical oxidative polymerisation. The synthesised PPy is characterised by employing FT-IR, XRD, SEM and EDX analysis. The coatings are formulated using water borne epoxy cross-linked with aliphatic polyamine adduct and the effect of PPy on corrosion prevention is studied. PPy was used as anti-corrosive pigment in concentration varying from 1 to 5 wt.%. In addition to anti-corrosive property; mechanical properties, chemical resistance and weathering properties of the coatings containing PPy are studied, thereby obtaining a wholesome data about the quality and performance of these coatings.

The result obtained through various tests showed that the coating with 1 and 2% PPy exhibited excellent weathering resistance, mechanical properties and improved chemical resistance. Higher percentage loading of PPy (beyond 3 per cent) proves to be disastrous, as extended percolation networks are formed which results in rapid intense corrosion leading to fast coating breakdown.

The anti-corrosion property of the coating can be tested by means of atmospheric exposure such as Florida test which produces a real time evaluation of the anti-corrosive nature of the coating at natural condition rather than accelerated weathering, thereby providing more reliable performance data for intended application purpose.

The results find application in anti-corrosive/performance paints for industrial application.

This research paper presents the results of anti-corrosion behaviour of PPy in water borne epoxy-polyamide coating. Based on this result, a highly effective anti-corrosive coating can be formulated by the addition of small percentage of PPy in combination with other conventional pigments, thereby enhancing corrosion protection. But care must be taken so as to avoid formation of extended percolation network of PPy which leads to rapid coating breakdown.

The aim of this paper is to conduct a real time evaluation of polypyrrole as an anti‐corrosive pigment in epoxy polyamide coating.

This study deals with synthesis of polypyrrole (PPy) by chemical oxidative polymerisation in laboratory conditions. The synthesised PPy was characterised by employing FT‐IR, XRD, SEM and EDX analysis. Epoxy film of bisphenol type hardened with polyamide based curing agent was used as the binder. PPy was used as anti‐corrosive pigment in concentrations varying from 0 to 5 wt% in the coating. In addition to anti‐corrosive property, mechanical, chemical and weathering properties of the coating containing PPy were studied and compared with epoxy polyamide coating without PPy.

The result obtained through various tests showed that the coating with 1 and 2% PPy exhibited excellent weathering resistance, mechanical properties and improved chemical resistance.

The anti‐corrosion property of the coating can be tested by means of atmospheric exposure such as Florida test or by means of electrochemical impedance spectroscopy.

The results find application in anti‐corrosive paints for industrial application.

This research paper presents the results of anti‐corrosion behaviour of PPy in epoxy‐polyamide coating. Based on this result, a highly effective anti‐corrosive coating can be formulated by addition of small percentage of PPy in combination with other conventional pigments, thereby enhancing corrosion protection.

This paper aims to review comprehensively the different voltage-boosting techniques and classifies according to their voltage gain, stress on the semiconductor devices, count of the total components and their prominent features. Hence, the focus is on non-isolated step-up converters. The converters categorized are analyzed according to their category with graphical representation.

Many converters have been reported in recent years in the literature to meet our power requirements from mill watts to megawatts. Fast growth in the generation of renewable energy in the past few years has promoted the selection of suitable converters that directly impact the behaviour of renewable energy systems. Step-up converters are a fast-emerging switching power converter in various power supply units. Researchers are more attracted to the derivation of novel topology with a high voltage gain, low voltage and current stress, high efficiency, low cost, etc.

A comparative study is done on critical metrics such as voltage gain, switch voltage stress and component count. Besides, the converters are also summarized based on their advantages and disadvantages. Furthermore, the areas that need to be explored in this field are identified and presented.

Types of analysis usually performed in dc converter and their needs with the areas need to be focused are not yet completely reviewed in most of the articles. This paper gives an eyesight on these topics. This paper will guide the researchers to derive and suggest a suitable topology for the chosen application. Moreover, it can be used as a handbook for studying the various topologies with their shortfalls, which will provide a way for researchers to focus.

This paper aims to examine the influence of leaves of Cucurbita maxima (LCM) extract on the corrosion of mild steel (MS) in 1N H₂SO₄ by gravimetric measurement and electrochemical study. The inhibition efficiency increased with increase in concentration of LCM. The corrosion rate increased with increase in temperature and decreased with increase in concentration of inhibitor compared to blank. The maximum inhibition efficiency of 96 per cent was obtained at 3 per cent v/v LCM at 343K for 1 h. The inhibitory action was explained on the basis of adsorption of secondary metabolites in the plant extract on the mild steel surface. The adsorption process obeys Langmuir, El-Awady, Temkin and Freundlich adsorption isotherms and was best fitted by Langmuir adsorption isotherm. Some kinetic and thermodynamic parameters are also discussed.

Weight loss measurements were conducted under total immersion of already weighed mild steel coupons in 100 ml of the test solution containing 0.05, 0.5, 1, 1.5, 2, 2.5 and 3 per cent of LCM extract and in blank solution at different temperature range (303, 313, 323, 333 and 343 K) for 1h. The electrochemical experiments were conducted at room temperature and at various concentrations of LCM extract. The electrochemical experiments were performed using a potentiostat. A three-electrode cell was used for the impedance measurements conducted at open circuit potential.

The inhibitor (LCM) shows good inhibition performance for the corrosion of mild steel in 1N H₂SO₄ solution. The inhibition efficiency increased and the corrosion rate decreased with increasing concentrations of inhibitor.

The studied plant material is a new one in mild steel corrosion. The influence of the plant material is clearly explained in the submitted paper.

The COVID-19 has had a diversified and dynamic impact on the food and agricultural sector, particularly in the agri-food value chain. Although a good number of articles were published in various countries and continents covering various aspects of the impact of COVID-19 on the agri-food value chain, no significant studies were found related to the mapping of published literature to know about the scenario and current trend research. The study aims to perform a systematic review and bibliographic mapping in the agri-food value chain to provide insights into the same.

Articles included in the Scopus database from January 1, 2020 to July 10, 2021 are considered. After initial screening and inclusion criteria, 41 articles have been selected to perform a systematic review which is published in the agri-food value chain. In addition to this, by considering the growth of the online food market, systematic mapping with the application of bibliometric analysis is performed to know the trend of the publications. Co-occurrence analysis with VOS viewer software version 1.6.16 is used for making network maps and supports the visualization of these maps.

The synthesis of the findings reveals that four broad themes recur in the articles: namely, food security and crisis during the pandemic, food price fluctuations, the impact of COVID-19 and disruption in the agri-food value chain and resilience strategies to strengthen the value chain. Alongside, the synthesis of the findings, this study describes the geographical coverage, methodologies used, sector/industry-specific context of the articles and scope of future research. In co-occurrence analysis with keywords, four clusters are identified related to the online food market and are categorized as “COVID-19 and Online food delivery services,” “Consumer satisfaction to online food delivery services,” “Food delivery system” and “Demographic impact on online food market.”

The study considers only the article from the Scopus database and article published between January 1, 2020 and July 10, 2021. Future studies are encouraged related to impact analysis studies of resilient strategies suggested by various authors by considering multiple databases.

This study will be beneficial for scholars and policymakers to know what is trending in the agri-food value chain and policymakers can implement various resilience strategies as discussed to mitigate the impact. The future research scope highlighted in this paper will encourage scholars and academicians to explore this area and will provide in-depth understanding.