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The purpose of this paper is to identify and prioritize the key food safety practices among street food handlers that lead to microbial contamination in selected street foods of Hyderabad, India. These key food safety practices will help develop and design tailor-made training material for street food vendors in future.

It is a cross-sectional study conducted in south Indian city of Hyderabad. Stratified random sampling method was employed. A total of 463 samples of street foods were collected from five zones of Hyderabad. They included 163 salad toppings, 150 fresh fruit juices and 150 panipuri samples. Identification and enumeration of foodborne pathogens and indicator organisms (S. aureus, E. coli, Salmonella spp., Shigella spp., Bacillus cereus, Yersinia spp.) were performed as described by USFDA-BAM. Information on food safety knowledge and handling practices from street vendors were collected using a structured questionnaire. Associations between hygiene practices and bacterial pathogens were done using ANOVA. Risk estimation of food safety practices was assessed by calculating odds ratio.

Microbiological analysis indicated that a large number of carrot (98.1 percent) and onion (75.5 percent) samples were contaminated with E. coli. Peeled and cut fruits left uncovered have 13.4 times risk (OR: 2.40-74.8) of E. coli contamination compared to the covered ones. Panipuri samples picked from the vendors who did not have soap at the vending unit had significantly (p<0.001) higher contamination of fecal coliforms than those who had.

This study is the first of its kind in the study area.

The research paper examines the complex relationship between gamification, student engagement and academic performance in educational environments. The study employed a structural equation model that highlights important connections among key constructs within the educational setting.

This research aims to explore the connection between gamification, student engagement and academic performance in educational settings. The study employs various statistical techniques such as factor analysis, Kaiser–Meyer–Olkin (KMO), Bartlett’s test, component transformation matrix, correlation and regression analysis, descriptive statistics, ANOVA, coefficients and coefficient correlations, residual statistics and confirmatory factor analysis (CFA) to analyze the data.

It was found that active participation by the instructor and good time management skills have a positive impact on student engagement levels (β = 0.380, p < 0.001; β = 0.433 and p < 0.001). However, peer interaction does not significantly predict student engagement (β = −0.068 and p = 0.352). Additionally, there is a positive correlation between student engagement and performance (β = 0.280 and p < 0.001).

The study highlights the importance of innovative design to fully utilize gamification. Future research should consider design, user characteristics and educational context. The findings can guide informed decisions about gamification in education, fostering motivation and learning objectives.

The study presents a reliable tool for assessing student engagement and performance in educational settings, demonstrating high Cronbach’s alpha and robust reliability. It identifies student engagement and time management as significant predictors of Global Learning Outcome. The findings can inform decisions on implementing gamification in educational settings, promoting intrinsic motivation and aligning with learning objectives.

The research highlights the transformative impact of gamification on educational practices, highlighting its potential to enhance student experiences, motivate, promote diversity and improve long-term academic performance, highlighting the trend of integrating technology into education.

In today’s ever-changing education landscape, it is essential to incorporate innovative techniques to keep students engaged and enthusiastic about learning. Gamification is one such approach that has become increasingly popular. It is a concept that takes inspiration from the immersive world of games to enhance the overall learning experience.

The purpose of this paper is to review the nature and extent of foodborne diseases in India due to chemical and microbial agents.

The scientific investigations/reports on outbreak of foodborne diseases in India for the past 29 (1980‐2009) years due to adulteration, chemical, and microbiological contamination have been reviewed. Reported scientific information on foodborne pathogens detected and quantified in Indian foods has also been reviewed.

A total of 37 outbreaks involving 3,485 persons who have been affected due to food poisoning have been reported in India. Although the common forms of foodborne diseases are those due to bacterial contamination of foods, however, higher numbers of deaths have been observed due to chemical contaminants in foods.

A national foodborne disease surveillance system needs to be developed in India in order to enable effective detection, control and prevention of foodborne disease outbreaks.

The purpose of this paper is to contribute to the literature on secondary equity offerings (SEOs) by examining the impact of the Black Economic Empowerment (BEE) policy on secondary equity offering (SEO) pricing dynamics of South African Real Estate Investment Trusts (REITs).

With a sample of 152 SEOs of South African REITs from 2010 to 2020, ordinary least squares (OLS) models, fixed effect models, parametric and non-parametric tests were applied to test for the impact of BEE on the underpricing of SEOs.

Significant underpricing is discovered in highly compliant (BEE) REITs; in other words, SEOs pricing of BEE compliant REITs are more underpriced compared to non-compliant BEE REITs. With this, BEE compliant REITs and more so, highly compliant BEE REITs in particular leave more money on the table.

The government is therefore aware of the impact policy interventions play when REITs raise financing through SEOS. With these, highly compliant BEE REITs will need to be more strategic when making BEE compliance decisions as this is shown in our study to impact the underpricing of SEOs.

This is the first study to investigate SEO underpricing for the BEE policy using the South African REITs context.

The purpose of this paper is to showcase the utilization of the magnetohydrodynamics-microrotating Casson’s nanofluid flow model (MHD-MRCNFM) in examining the impact of an inclined magnetic field within a porous medium on a nonlinear stretching plate. This investigation is conducted by using neural networking techniques, specifically using neural networks-backpropagated with the Levenberg–Marquardt scheme (NN-BLMS).

The initial nonlinear coupled PDEs system that represented the MRCNFM is transformed into an analogous nonlinear ODEs system by the adoption of similarity variables. The reference data set is created by varying important MHD-MRCNFM parameters using the renowned Lobatto IIIA solver. The numerical reference data are used in validation, testing and training sets to locate and analyze the estimated outcome of the created NN-LMA and its comparison with the corresponding reference solution. With mean squared error curves, error histogram analysis and a regression index, better performance is consistently demonstrated. Mu is a controller that controls the complete training process, and the NN-BLMS mainly concentrates on the higher precision of nonlinear systems.

The peculiar behavior of the appropriate physical parameters on nondimensional shapes is demonstrated and explored via sketches and tables. For escalating amounts of inclination angle and Brinkman number, a viable entropy profile is accomplished. The angular velocity curve grows as the rotation viscosity and surface condition factors rise. The dominance of friction-induced irreversibility is observed in the vicinity of the sheet, whereas in the farthest region, the situation is reversed with heat transfer playing a more significant role in causing irreversibilities.

To improve the efficiency of any thermodynamic system, it is essential to identify and track the sources of irreversible heat losses. Therefore, the authors analyze both flow phenomena and heat transport, with a particular focus on evaluating the generation of entropy within the system.

The study examines the IPO resilience grounded on the firm’s intrinsic factors.

We examine the association of IPO performance and post-listing firm’s performance with issuers' pre-listing financial and qualitative traits using panel data regression.

IPOs floated in the Indian market from July 2009 to March 31, 2022, evince the notable influence of issuers' pre-IPO fundamentals and legitimacy traits on IPO returns and post-listing earning power. Where the pandemic’s favorable impact is discerned on the post-listing year earning power of the issuer firms, the loss-making issuers appear to be adversely affected by the Covid disruption. Perhaps, the successful listing equipped the issuers with the financial flexibility to combat market challenges vis-à-vis failed issuers deprived of desired IPO proceeds.

High initial returns followed by a declining pattern substantiate the retail investors to be less informed vis-à-vis initial investors, valuers and underwriters, who exit post-listing after profit booking. Investing in the shares of the newly listed ventures post-listing in the secondary market can shield retail investors from the uncertainty losses of being uninformed. The IPO market needs stringent regulations ensuring the verification of the listing valuation, the firm’s credentials and the intent of utilizing IPO proceeds. Healthy development of the IPO market merits reconsidering the listing of ventures with weak fundamentals suspected to withstand the market challenges.

Given the tremendous rise in the new firm venturing into the primary market and the spike in IPOs countering the losses immediately post-opening, the study examines the loss-making and young firms IPOs separately, adding novelty to the study.

This study aims to analyze the Prandtl fluid flow in the presence of better mass diffusion and heat conduction models. By taking into account a linearly bidirectional stretchable sheet, flow is produced. Heat generation effect, thermal radiation, variable thermal conductivity, variable diffusion coefficient and Cattaneo–Christov double diffusion models are used to evaluate thermal and concentration diffusions.

The governing partial differential equations (PDEs) have been made simpler using a boundary layer method. Strong nonlinear ordinary differential equations (ODEs) relate to appropriate non-dimensional similarity variables. The optimal homotopy analysis technique is used to develop solution.

Graphs analyze the impact of many relevant factors on temperature and concentration. The physical parameters, such as mass and heat transfer rates at the wall and surface drag coefficients, are also displayed and explained.

The reported work discusses the contribution of generalized flux models to note their impact on heat and mass transport.

This study aims to investigate the micropolar fluid flow through a moving flat plate containing CoFe₂O₄-TiO₂ hybrid nanoparticles with the substantial influence of thermophoresis particle deposition and viscous dissipation.

The partial differential equations are converted to the similarity equations of a particular form through the similarity variables. Numerical outcomes are computed by applying the built-in program bvp4c in MATLAB. The process of flow, heat and mass transfers phenomena are examined for several physical aspects such as the hybrid nanoparticles, micropolar parameter, the thermophoresis particle deposition and the viscous dissipation.

The friction factor, heat and mass transfer rates are higher with an increment of 1.4%, 2.2% and 1.4%, respectively, in the presence of the hybrid nanoparticles (with 2% volume fraction). However, they are declined because of the rise of the micropolar parameter. The imposition of viscous dissipation reduces the heat transfer rate, significantly. Meanwhile, thermophoresis particle deposition boosts the mass transfer. Multiple solutions are developed for a certain range of physical parameters. Lastly, the first solution is shown to be stable and reliable physically.

As far as the authors have concerned, no work on thermophoresis particle deposition of hybrid nanoparticles on micropolar flow through a moving flat plate with viscous dissipation effect has been reported in the literature. Most importantly, this current study reported the stability analysis of the non-unique solutions and, therefore, fills the gap of the study and contributes to new outcomes in this particular problem.

The purpose of this study is to examine the influence of earnings management during initial public offerings on the listing day returns.

The study collected data for 511 Indian IPOs that came between April 2003 and March 2019 for calculating earnings management. On the basis of the Cross Sectional Modified Jones Model 1995, the paper presents three proxies of earnings management as discretionary accruals (DA), discretionary current accruals (DCA) and discretionary long-term accruals (DLA). The study further used correlation and multiple regression analysis to assess the impact of earnings management on listing day returns.

The findings show that earnings management and listing day returns vary through issue-year and industry-type. Apart from it, the study reveals a greater contribution of short-term accruals in earnings management on the basis of higher DCA values. It also discloses that the aggregate level of earnings management (DA) influences listing returns, whereas DCA and DLA separately have no impact on the listing day returns of the Indian IPOs.

The findings are useful to potential investors and analysts to observe, assess and understand the quality of financial reports that are based on fallacious disclosure of accounting figures. The study also reflects the efficacy of Indian regulatory norms for IPOs in constraining earnings management and underpricing, thus providing meaningful insight to the policy makers and the regulators.

This study is distinguished by its focus on determining the influence of earnings management on listing day returns in Indian IPOs by using three earnings management proxies.

The academic research into underpricing of initial public offerings (IPOs) offers many explanations, i.e. signalling, financial and market hypothesis. However, another set of information, namely, “Qualitative Factors” (along with financial and others), are largely reported by the issuing firms in the prospectus. However, to the best of the authors’ knowledge no such systematic study has been carried out on how firms’ qualitative factors impact the IPO valuation. This paper aims to addresses this gap.

Using a sample of 82 IPOs issued from 2014 to 2020, we investigate the issuing firm’s pattern of reporting qualitative factors. These qualitative factors are subjected to factor analysis. The authors classify all reported factors across firms into a few categories using principal component analysis. The authors also investigate the impact of these factors on IPO underpricing using OLS regression.

The authors find that the qualitative information relating to market leadership, established brand image and modern scalable information technology infrastructure significantly influences underpricing. The authors also document that market leadership and brand image are the influential reported quality factors that reduce underpricing. Moreover, location advantage, good customer relationship, established relationship with a client, track record of growth and profitability, experienced promoter and management team failed to influence underpricing.

The outcome of this piece of research offers additional signalling as an attestation of quality for the issue. The authors further argue that the amount of qualitative information disclosed by the managers in the prospectus to support the pricing should not be ignored.