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The study of novel exponential heat source (EHS) phenomena across a flowing fluid with the suspension of nanoparticles over a rotating plate in the presence of Hall current and chemical reaction has been an open question. Therefore, the purpose of this paper is to investigate the impact of EHS in the transport of nanofluid under the influence of strong magnetic dipole (Hall effect), chemical reaction and temperature-dependent heat source (THS) effects. The Khanafer-Vafai-Lightstone model is used for nanofluid and the thermophysical properties of nanofluid are calculated from mixture theory and phenomenological laws. The simulation of the flow is also carried out using the appropriate values of the empirical shape factor for five different particle shapes (i.e. sphere, hexahedron, tetrahedron, column and lamina).

Using Laplace transform technique, exact solutions are presented for the governing nonlinear equations. Graphical illustrations are pointed out to represent the impact of involved parameters in a comprehensive way. The numeric data of the density, thermal conductivity, dynamic viscosity, specific heat, Prandtl number and Nusselt number for 20 different nanofluids are presented.

It is established that the nanofluid enhances the heat transfer rate of the working fluids; the nanoparticles also cause an increase of viscous. The impact of EHS advances the heat transfer characteristics significantly than usual thermal-based heat source (THS).

The effectiveness of EHS phenomena in the dynamics of nanofluid over a rotating plate with Hall current, chemical reaction and THS effects is first time investigated.

The purpose of this paper is to identify the antecedents of continued usage intentions in the connected devices ecosystem in health care by analyzing the users' and physicians' expectations in a new ecosystem where one prefers to connect digitally rather than physically.

This is a unique study in which data was collected from 242 doctors and 215 end-users to gauge the expectations from the connected devices in health care. Further, these responses were hypothesised using UTAUT-2 and ECT theories to analyze general users’ and professional users’ or doctors’ expectations for continued usage in connected devices ecosystem in the health-care ecosystem.

Performance expectancy, social influence, facilitating conditions and price value emerged as significant predictors of satisfaction in both user groups. But habit and hedonic motivation reflected an insignificant impact on user satisfaction. Surprisingly, effort expectancy emerged as a significant factor for end-user satisfaction, and this became insignificant for professional user satisfaction. Satisfaction was positively related to continued usage for both user groups, and app quality has a positive impact on all the predictors.

To the best of the authors’ knowledge, this is the first comparative study to understand the factors which influence consumer behavior leading to a holistic model and can be imbibed for creating a better customer experience in an era where we are more comfortable connecting digitally rather than physically.

This study has used the Unified Theory of Acceptance and Use of Technology-2 model and expectation confirmation theory to analyze the key factors influencing the intentions for continued usage of devices in the Internet of Medical Devices setup.

Cowpea‐amala was produced from yam flour and cowpea flour blends. Cowpea flour substitution was at 0, 10 per cent, 20 per cent and 40 per cent. All fortified samples showed better nutrient composition than the control. The protein (7.28 per cent), ash (3.58 per cent), Na (0.08 per cent), K (0.89 per cent), Zn (0.0025 per cent) Ca (0.11 per cent) and Mg (0.008 per cent) of cowpea flour substitution at 40 per cent was highest. Amala prepared from these blends was not significantly different in taste, flavour and texture from the control. Higher scores were given with regards to colour and general acceptability in all amala samples. Also none of the samples were rejected.

In heat transfer problems, if the temperature difference is not sufficiently so small then the linear Boussinesq approximation is not adequate to describe thermal analysis. Also, nonlinear density variation with respect to temperature/concentration has a significant impact on heat and fluid flow characteristics. Because of this reason, the impact of nonlinear density variation in the buoyancy force term cannot be neglected. Therefore in this paper, the unsteady flow and heat transfer of radiating magneto-micropolar fluid by considering nonlinear Boussinesq approximation is investigated analytically.

The flow is fully developed and time-dependent. Heat and mass flux boundary conditions are also accounted in the analysis. The governing equations of transport phenomena are treated analytically using regular perturbation method. To analyze the tendency of the obtained solutions, a parametric study is performed.

It is established that the velocity field is directly proportional to the nonlinear convection parameter and the same trend is observed with the increase of the value of Grashof number. The micro-rotational velocity profile decreases with increase in the nonlinear convection parameter. Further, the temperature profile increases due to the presence of radiative heat aspect.

The effectiveness of nonlinear Boussinesq approximation in the flow of micropolar fluid past a vertical plate in the presence of thermal radiation and magnetic dipole is investigated for the first time.

With the advent of the internet and communication technology, the penetration of e-learning has increased. The digital data being created by the educational and research institutions is also on the ascent. The growing interest in recent years toward big data, educational data mining and learning analytics has motivated the development of new analytical ways and approaches and advancements in learning settings. The need for using big data to handle, analyze this large amount of data is prime. This trend has started attracting the interest of educational institutions which have an important role in the development skills process and the preparation of a new generation of learners. “A real revolution for education,” it is based on this kind of terms that many articles have paid attention to big data for learning. How can analytics techniques and tools be so efficient and become a great prospect for the learning process? Big data analytics, when applied into teaching and learning processes, might help to improvise as well as to develop new paradigms. In this perspective, this paper aims to investigate the most promising applications and issues of big data for the design of the next-generation of massive e-learning. Specifically, it addresses the analytical tools and approaches for enhancing the future of e-learning, pitfalls arising from the usage of large data sets. Globally, this paper focuses on the possible application of big data techniques on learning developments, to show the power of analytics and why integrating big data is so important for the learning context.

Big data has in the recent years been an area of interest among innovative sectors and has become a major priority for many industries, and learning sector cannot escape to this deluge. This paper focuses on the different methods of big data able to be used in learning context to understand the benefits it can bring both to teaching and learning process, and identify its possible impact on the future of this sector in general. This paper investigates the connection between big data and the learning context. This connection can be illustrated by identifying the several main analytics approaches, methods and tools for improving the learning process. This can be clearer by the examination of the different ways and solutions that contribute to making a learning process more agile and dynamic. The methods that were used in this research are mainly of a descriptive and analytical nature, to establish how big data and analytics methods develop the learning process, and understand their contributions and impacts in addressing learning issues. To this end, authors have collected and reviewed existing literature related to big data in education and the technology application in the learning context. Authors then have done the same process with dynamic and operational examples of big data for learning. In this context, the authors noticed that there are jigsaw bits that contained important knowledge on the different parts of the research area. The process concludes by outlining the role and benefit of the related actors and highlighting the several directions relating to the development and implementation of an efficient learning process based on big data analytics.

Big data analytics, its techniques, tools and algorithms are important to improve the learning context. The findings in this paper suggest that the incorporation of an approach based on big data is of crucial importance. This approach can improve the learning process, for this, its implementation must be correctly aligned with educational strategies and learning needs.

This research represents a reference to better understanding the influence and the role of big data in educational dynamic. In addition, it leads to improve existing literature about big data for learning. The limitations of the paper are given by its nature derived from a theoretical perspective, and the discussed ideas can be empirically validated by identifying how big data helps in addressing learning issues.

Over the time, the process that leads to the acquisition of the knowledge uses and receives more technological tools and components; this approach has contributed to the development of information communication and the interactive learning context. Technology applications continue to expand the boundaries of education into an “anytime/anywhere” experience. This technology and its wide use in the learning system produce a vast amount of different kinds of data. These data are still rarely exploited by educational practitioners. Its successful exploitation conducts educational actors to achieve their full potential in a complex and uncertain environment. The general motivation for this research is assisting higher educational institutions to better understand the impact of the big data as a success factor to develop their learning process and achieve their educational strategy and goals. This study contributes to better understand how big data analytics solutions are turned into operational actions and will be particularly valuable to improve learning in educational institutions.

This paper aims to assess the effectiveness of Hall currents and power-law slip condition on the hydromagnetic convective flow of an electrically conducting power-law fluid over an exponentially stretching sheet under the effect of a strong variable magnetic field and thermal radiation. Flow formation is developed using the rheological expression of a power-law fluid.

The nonlinear partial differential equations describing the flow are transformed into the nonlinear ordinary differential equations by employing the local similarity transformations and then solved numerically by an effective numerical approach, namely, fourth-order Runge–Kutta integration scheme, along with the shooting iteration technique. The numerical solution is computed for different parameters by using the computational software MATLAB bvp4c. The bvp4c function uses the finite difference code as the default. This method is a fourth-order collocation method. The impacts of thermophysical parameters on velocity and temperature distributions, skin friction coefficients and Nusselt number in the boundary layer regime are exhibited through graphs and tables and deliberated with proper physical justification.

Our investigation conveys that Hall current has an enhancing behavior on velocity profiles and reduces skin friction coefficients. An increase in the power-law index is observed to deplete velocity and temperature evolution. The temperature for the pseudo-plastic (shear-thinning) fluid is relatively higher than the corresponding temperature of the dilatant (shear-thickening) fluid. The streamlines are more distorted and have low intensity near the surface of the sheet for the dilatant fluid than the pseudo-plastic fluid.

The study is pertinent to the expulsion of polymer sheet and photographic films, hydrometallurgical industry, electrically conducting polymer dynamics, magnetic material processing, solutions and melts of polymer processing, purification of molten metals from nonmetallic. The results obtained in this work can be relevant in fluid mechanics and heat transfer applications.

The present problem has, to the authors' knowledge, not communicated thus far in the scientific literature. A comparative study with the published works is conducted to verify the accuracy of the present study. The results obtained in this analysis are significant in providing the standards for validating the accuracies of some numerical or empirical methods.

This report offers the detailed investigation of Couette–Poiseuille flow of nanoliquid with varying viscosity. The analysis is carried out by considering flow between two parallel plates in a rotating permeable channel with the aid of nonlinear thermal radiation and Hall effect. The predominant equations governing the physical phenomenon are demonstrated using the Buongiorno model.

Numerical computation for the demonstrated physical problem is achieved through the implementation of the Runge–Kutta–Fehlberg fourth–fifth-order method along with shooting technique.

The theoretical view of Brownian motion, nonlinear radiation, Hall effect and thermophoresis parameter is presented graphically.

It is revealed that flow velocity increases with the upper wall motion parameter and magnetic field. Also, it is established that an increase in the Nusselt number is achieved for increasing values of nonlinear radiation parameter.

This study aims to investigate the relationship between talent management, organizational commitment and turnover intention. The moderating role of gender and experience in relationships was explored.

A conceptual model was developed, and relationships were studied by collecting data from 392 faculty members working in higher educational institutions (HEIs) in southern India. After checking the instrument’s psychometric properties using the LISREL package of structural equation modeling, data were analyzed using Hayes’s PROCESS macros.

The results revealed that talent recruitment strategies positively predict organizational commitment and negatively predict turnover intention; organizational commitment mediates the relationship between talent management and turnover intention. Further, the results documented that experience (first moderator) and gender of faculty members (second moderator) influenced the relationship between talent management and organizational commitment and organizational commitment and turnover intention.

The outcomes of this research are helpful for the administrators of HEIs to strategize to attract and retain talented faculty to maintain sustained competitive advantage. This research also helps to understand gender differences that exist in talent management and retention and organizational commitment in HEIs.

The three-way interactions between talent management, gender and experience in influencing organizational commitment and turnover intentions is a novel idea that contributes to the talent management literature – the relationship between talent recruitment strategies and talent engagement. The implications for talent management theory and practice are discussed.

The primary purpose of this paper is to determine the role of behavioral characteristics of young adults on housing and real estate loan default intentions. The behavioral factors considered in this study are financial literacy, materialism, emotions, indebtedness and risk perception.

The sample frame comprises of young clients who have taken house loans and work in India’s metropolitan cities. These cities provide a higher quality of life, more employment possibilities and cheaper living costs. A systematic questionnaire was used, which was divided into six components. A total of 352 valid responses were collected and analyzed through a structural equation model.

The findings suggest that financial literacy, materialism and risk perception have a considerable impact on loan default intention among young adults. The results also ascertained that emotion and indebtedness do not have a considerable impact on loan default intention among young adults.

The scope of this study is limited to India’s metropolitan cities. Future studies can examine comparative examinations of young adults working in the public and private sectors and those working in different cities across India.

This paper contributes to a better understanding of behavioral variables which may lead to the creation of preventive measures for young defaulters. The findings of this study will help financial institutions to improve their credit-offering models.

To the best of the authors’ knowledge, this study is the first to determine the role of behavioral attributes of young adults on housing and real estate loan default intentions in India. This work will be executable to all the stakeholders of the housing and real estate industry altogether.

Indonesian law provides prisoners with basic rights, including access to education, health care and nutrition. Yet, structural and institutional limitations, notably overcrowding and under-resourcing, prohibits penal institutions from fulfilling these commitments for female prisoners. The purpose of this paper is to explore their health concerns.

Six prisons and one detention centre were researched, comprising: female prisoners (n=69); clinical officers (six); clinic heads (seven); wardens (seven); heads of prisons (seven); and a Directorate representative. Data were collected through observation, focus group discussions, in-depth interviews and a semi-structured questionnaire. Raw data were transcribed and analysed thematically, adopting the General Principles of Grounded Theory.

Both “formal” and “informal” health-coping strategies were dependent upon a range of factors which determined access to treatment, medicines and other items procured both inside and outside of the prison, as well as referral services. Informal systems of support existed for women, especially in regard to pregnancy and raising of babies born in detention. Systems that maintain harmony within cell blocks were identified as an important informal coping strategy.

This research is important in informing policy and practice. There is a clear need for gender-sensitive legislative frameworks, penal policies and prison rules to ensure women's needs are addressed. The identified coping strategies were considered viable, but do not replace the need for a health system providing women prisoners with levels of care as available in the community, including commensurate budgeting, personnel, access and referral to more specialised external health services.