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The study aims to profile the scientific retractions in the top five global universities and provide descriptive statistics on specific subjects.

The data for reasons behind retractions is manually extracted from the Retraction Watch Database. The top five global universities according to the Times Higher Education global ranking of 2024 are selected for this study.

The study found that Stanford University emerged with the highest number of retractions in the assessment across institutions in the field of basic life sciences and health sciences. Notably, the predominant reasons for these retractions were identified, with “unreliable results” being the most prevalent, accounting for 53 retractions. Following closely was the category of “errors in results and/or conclusions”, contributing to 51 retractions. MIT has the longest time between publication and retraction of any subject group, with an average of 1,701 days.

This study has some limitations, as it only analysed the retractions of the top five global universities.

The study provides a comprehensive analysis of retractions in academic publishing, focusing on reasons, time gaps, article types and accessibility categories across prestigious universities. The paper underscores the critical role of retractions in maintaining the integrity of scientific literature, emphasizing the importance of transparent correction and responsible peer review to ensure the reliability and trustworthiness of published research. Results show that common reasons for retractions include duplication, fake peer review and plagiarism, underlining the need for ethical research standards.

The stock market generates massive databases of various financial companies that are highly volatile and complex. To forecast daily stock values of these companies, investors frequently use technical analysis or fundamental analysis. Data mining techniques coupled with fundamental and technical analysis types have the potential to give satisfactory results for stock market prediction. In the current paper, an effort is made to investigate the accuracy of stock market predictions by using the combined approach of variables from technical and fundamental analysis for the creation of a data mining predictive model.

We chose 381 companies from the National Stock Exchange of India's CNX 500 index and conducted a two-stage data analysis. The first stage is identifying key fundamental variables and constructing a portfolio based on that study. Artificial neural network (ANN), support vector machines (SVM) and decision tree J48 were used to build the models. The second stage entails applying technical analysis to forecast price movements in the companies included in the portfolios. ANN and SVM techniques were used to create predictive models for all companies in the portfolios. We also estimated returns using trading decisions based on the model's output and then compared them to buy-and-hold returns and the return of the NIFTY 50 index, which served as a benchmark.

The results show that the returns of both the portfolios are higher than the benchmark buy-and-hold strategy return. It can be concluded that data mining techniques give better results, irrespective of the type of stock, and have the ability to make up for poor stocks. The comparison of returns of portfolios with the return of NIFTY as a benchmark also indicates that both the portfolios are generating higher returns as compared to the return generated by NIFTY.

As stock prices are influenced by both technical and fundamental indicators, the current paper explored the combined effect of technical analysis and fundamental analysis variables for Indian stock market prediction. Further, the results obtained by individual analysis have also been compared. The proposed method under study can also be utilized to determine whether to hold stocks for the long or short term using trend-based research.

Molten sulphate-vanadate induced hot corrosion is the main reason of failure of boiler tubes used at high temperatures in thermal power plants. The hot corrosion can be encountered by applying thermal spray coatings on the alloy steels. In this perspective, this paper aims to attempt to investigate the effect of carbon nanotubes reinforcement on Cr₂O₃ composite coatings on hot corrosion behaviour of ASTM-SA213-T22 steel in a corrosive environment of Na₂SO₄ – 60%V₂O₅ at 900^°C for 50 cycles.

The coatings have been deposited with high velocity oxy fuel process. The samples were exposed to hot corrosion in a Silicon tube furnace at 900^°C for 50 cycles. The kinetics of corrosion behaviour were analysed by the weight gain measurements after each cycle. Corrosion products were analysed with X-ray diffraction, scanning electron microscopy, energy dispersive and cross-sectional analysis techniques.

During investigations, the carbon nanotubes (CNT) reinforced Cr₂O₃ composite coatings on T22 steel were found to provide better corrosion resistance in the molten salt environment at 900^°C. The coatings showed lower weight gain along with formation of protective oxide scales during the experiment. Improvement in protection against hot corrosion was observed with increase in CNT content in the coating matrix.

The addition of CNT has resulted in reduction in porosity by filling the voids in chromium oxide coating, with interlocking of particle and has blocked the penetration of corroding species to enhance the corrosion resistance of the composite coatings. The corrosion rate was found to be decreasing with increase in CNT content in coating matrix.

It must be mentioned here that high temperature corrosion behaviour of thermally sprayed CNT-Cr₂O₃ composite coatings has never been studied, and it is not available in the literature. Hence, present investigation can provide valuable information for application of CNT-reinforced coatings in high temperature fuel combustion environments.

This paper aims to investigate the hot corrosion behavior of Ni-Cr and Cr3C2-NiCr coatings, deposited on T11, P91 boiler steels by detonation gun spray coating (D-Gun) process to enhance high temperature corrosion resistance.

Hot corrosion studies were conducted in secondary super heater zone of boiler at 900 °C for 10 cycles on bare and D-Gun coated steel specimens. The microhardness and porosity values of as-sprayed coatings were measured before exposing the specimens in the boiler environment. Each cycle consisted 100 h of heating in the boiler environment followed by 20 min of cooling in air. The weight change measurements were performed after each cycle to establish the kinetics of corrosion using thermogravimetric technique. X-ray diffraction, SEM techniques were used to analyze the corroded specimens.

Uncoated boiler steel experienced higher weight loss. The Cr3C2-NiCr coating was found to be more protective than Ni-Cr coating. The phases revealed the formation of oxide scale on coated specimens, mainly consist of nickel and chromium, which are reported to be protective against the hot corrosion.

There is very limited reported literature on hot corrosion behavior of Ni-Cr and Cr3C2-NiCr coatings deposited on the T11 and P91 substrates by detonation gun (D-gun) spray technique. T11 and P91 alloy steels have been chosen for this study because these two alloys are used to manufacture boiler tubes used in Indian thermal power plants.

The purpose of this paper is to study the status and trend of intellectual capital disclosures by selected companies in India. Three categories of intellectual capital disclosures across six industry groups were measured. The relation of the three categories of disclosures, i.e. human capital, relational capital and structural capital disclosures with the measures of organisational performance such as sales, R&D, R&D intensity, net profit and export intensity has also been studied.

Based on National Industrial Classification 2008, six sectors, namely pharmaceutical, basic metals, industrial manufacturing, energy, financial services and information technology were included in the study and 20 companies were selected from each sector based on the availability of data from 2004-2005 to 2013-2014, thus, making a sample of 1,200 firm-years. For collecting the data, a list of keywords related to various dimensions of intellectual capital was prepared and the count of keywords was searched in the annual reports of the companies.

Significant and positive trend coefficients were found in the majority of the sectors. Analysis revealed that trend coefficients differed across various sectors indicating the presence of sector specificity. Results of trend analysis reveal that structural capital-related disclosures have stagnated in case of pharmaceutical sector after hitting the peak. Significant variations were found across sectors in terms of all three types of intellectual capital disclosures. Results of study empirically support the fact that intellectual capital disclosures tend to increase with size of the organisation.

As data have been collected from annual reports of the companies, the accuracy of the findings is limited to the accuracy of the reported data.

The study is an original piece of work. This study provides an insight into the disclosure trend of intellectual capital in an emerging economy.

An attempt was made to explore the use of nutrition labelling in the Indian context. The purpose of this paper is to study the determinants of healthier food choices, as well as the role of label use in this context.

Data were collected from 150 respondents using the survey method and field experiment. The respondents were enquired about various aspects of label use and were asked to make a choice, from two products in three food product categories, on the basis of real information. Multivariate probit models were built for product choice situations.

Moderate to low use of nutrition labelling was found. Significant differences in label use were found on the basis of gender (Sugar (p = 0.011), Additives (p = 0.014), Proteins (p = 0.03)) and education (Additives (p = 0.002), Colouring agents (p = 0.003), Transfats (p < 0.001)). Higher label use was leading (p = 0.031) to more likelihood of choosing healthier potato chips. Women reported higher label use (p = 0.004) but were choosing relatively unhealthier health supplement (p = 0.003). Effect of price was not unidirectional in terms of making healthier food choices. It was observed that label use is not solely responsible for aiding the choice of healthier food products. Individual characteristics were playing important role in choice of food products.

Findings indicate that merely provision of label information is not adequate for the choice of better food options. Provision of labelling information in simple format and equipping the consumers to make effective use of the same carry importance.

The paper is original and makes an attempt to study the effect of label use, along with the individual characteristics, on healthier food choices. Given the availability of few studies in the domain from the emerging markets, the paper adds to the existing body of knowledge.