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The purpose of this study is to perform a detailed review on the numerical modeling of multiphase and multicomponent flows in microfluidic system using phase-field method. The phase-field method is of emerging importance in numerical computation of transport phenomena involving multiple phases and/or components. This method is not only used to model interfacial phenomena typical to multiphase flows encountered in engineering and nature but also turns out to be a promising tool in modeling the dynamics of complex fluid-fluid interfaces encountered in physiological systems such as dynamics of vesicles and red blood cells). Intrinsically, a priori unknown topological evolution of interfaces offers to be the most concerning challenge toward accurate modeling of moving boundary problems. However, the numerical difficulties can be tackled simultaneously with numerical convenience and thermodynamic rigor in the paradigm of the phase field method.

The phase-field method replaces the macroscopically sharp interfaces separating the fluids by a diffuse transition layer where the interfacial forces are smoothly distributed. As against the moving mesh methods (Lagrangian) for the explicit tracking of interfaces, the phase-field method implicitly captures the same through the evolution of a phase-field function (Eulerian). In contrast to the deployment of an artificially smoothing function for the interface as used in the volume of a fluid or level set method, however, the phase-field method uses mixing free energy for describing the interface. This needs the consideration of an additional equation for an order parameter. The dynamic evolution of the system (equation for order parameter) can be described by Allen–Cahn or Cahn–Hilliard formulation, which couples with the Navier–Stokes equation with the aid of a forcing function that depends on the chemical potential and the gradient of the order parameter.

In this review, first, the authors discuss the broad motivation and the fundamental theoretical foundation associated with phase-field modeling from the perspective of computational microfluidics. They subsequently pinpoint the outstanding numerical challenges, including estimations of the model-free parameters. They outline some numerical examples, including electrohydrodynamic flows, to demonstrate the efficacy of the method. Finally, they pinpoint various emerging issues and futuristic perspectives connecting the phase-field method and computational microfluidics.

This paper gives unique perspectives to future directions of research on this topic.

The central purpose of this study is to investigate the relative effects of leadership styles, i.e. transactional leadership and transformational leadership, and achievement motivation on the entrepreneurial potential of MBA and engineering students. This study also examines whether the MBA and engineering students differ in terms of their entrepreneurial potential.

This study has used a cross-sectional research design along with a quasi-experimental research method to investigate the study's objectives on a sample consisting of 952 engineering and business students. The study has also used the PLS-SEM approach to carry out the data analysis, and to evaluate the group differences among MBA and engineering students concerning the relationships investigated, i.e. leadership motivation-entrepreneurial potential, and achievement motivation-entrepreneurial potential.

This research has primarily made four findings. First, the study has found that there are statistically significant differences between students pursuing a business education, and those students who are seeking management education about their entrepreneurial potential. Second, this study demonstrates that leadership and achievement motivation are strongly associated with entrepreneurial potential. Third, this research shows that the achievement motivation-entrepreneurial potential is more substantial among engineering students than among business students. However, the leadership-entrepreneurial potential relationship is more influential among MBA students than among engineering students. Lastly, the effect size of leadership is small in comparison with the effect size of achievement motivation, which is substantially healthy.

This research has attempted to address the riddle of a leadership attribution error in the context of entrepreneurship. Accordingly, this study has demonstrated that the idea of leadership attribution error has empirical evidence in the context of entrepreneurship also. Further, this study has tried to address the “behavior-motive preeminence” dichotomy. The results of this research show that internal motivation is more reliable than external leadership behavior in cultivating the entrepreneurial potential of students.

In this paper, we present a modified k‐ε model capable of addressing turbulent weld‐pool convection in the presence of a continuously evolving phase‐change interface during a gas tungsten arc welding (GTAW) process. The phase change aspects of the present problem are addressed using a modified enthalpy‐porosity technique. The k‐ε model is suitably modified to account for the morphology of the solid‐liquid interface. The two‐dimensional mathematical model is subsequently utilised to simulate a typical GTAW process with high power, where effects of turbulent transport can actually be realised. Finally, we compare the results from turbulence modelling with the corresponding results from a laminar model, keeping all processing parameters unaltered. The above comparison enables us to analyse the effects of turbulent transport during the arc welding process.

Inclusive growth is a buzzword among all nations. Poverty alleviation programmes are vital part of inclusive growth. Hence, the potential role of social protection in the development process has received heightened recognition in recent years. Poverty alleviation through government schemes or programmes is an important part of all nations’ inclusive growth. The explanation of social protection has varied across different development agencies, namely the World Bank, the Inter-American Development Bank, the International Labour Organization (ILO), etc. But the basic thrust of such definitions has involved what the Asian Development Bank (ADB) described in its 2001 Social Protection Strategy as enabling ‘vulnerable groups to prevent, reduce and/or cope with risks’ (ADB, 2001). Hence, it is vital to stress that social protection can help or cover vulnerable non-poor vis-á-vis poor groups. In some cases, such as in East Asia, the poor benefit more from social assistance (SA). This is attributable, no doubt, to the impact of cash- or food-for-work programs (ADB, 2009). This chapter seeks to determine or identify the impact of Social Protection Index (SPI) on inclusive growth through poverty alleviation in a few Asian countries using secondary data (ADB, 2009, 2016, 2019) on government social protection programs in some countries in Asia. It is obtained that the impact of components of SPI, such as social insurance (SI) programs, SA programs and labour market programs (LMP), is playing a vital role in eradication of poverty and attaining inclusive growth.

The purpose of this paper is to carry out a systematic energy analysis for predicting the first and second law efficiencies and the entropy generation during a laser surface alloying (LSA) process.

A three‐dimensional transient macroscopic numerical model is developed to describe the turbulent transport phenomena during a typical LSA process and subsequently, the energy analysis is carried out to predict the entropy generation as well as the first and second law efficiencies. A modified k–ε model is used to address turbulent molten metal‐pool convection. The phase change aspects are addressed using a modified enthalpy‐porosity technique. A kinetic theory approach is adopted for modelling evaporation from the top surface of the molten pool.

It is found that the heat transfer due to the strong temperature gradient is mainly responsible for the irreversible degradation of energy in the form of entropy production and the flow and mass transfer effects are less important for this type of phase change problem. The first and second law efficiencies are found to increase with effective heat input and remain independent of the powder feed rate. With the scanning speed, the first law efficiency increases whereas the second law efficiency decreases.

The top surface undulations are not taken care of in this model which is a reasonable approximation.

The results obtained will eventually lead to an optimized estimation of laser parameters (such as laser power, scanning speed, etc.), which in turn improves the process control and reduces the cost substantially.

This paper provides essential information for modelling solid–liquid phase transition as well as a systematic analysis for entropy generation prediction.

This paper aims to examine how interfirm transactional and relational assets drive firm performance (FP) in digitally integrated supply chains.

The authors combine the Transaction Cost Economics (TCE) and Relational Exchange Theory (RET) frameworks to hypothesize that FP will be a function of Asset Specificity (AS), Digital Technology Usage (DTU) and Collaborative Information Sharing (CIS). In addition, the authors hypothesize that Supply Chain Integration (SCI) will partially mediate the effect of DTU and fully mediate the impact of AS and CIS on FP. A cross-sectional survey of supply chain managers is used to test the hypotheses.

Findings indicate that specific investments in digitally integrated supply chains would increase FP. In addition, SCI fully mediates the relationships between AS and FP and CIS and FP, while SCI partially mediates the influence of DTU on FP.

Managers could strategically engage in the technologies that effectively fit within the firm’s supply chain strategies and seek to develop a pragmatic expertise that enables the effective use of technology in a comprehensive setting.

The study enriches the extant literature by incorporating TCE and RET as contradictory viewpoints on AS and investigating how transactional and relational assets affect FP in digitally integrated supply chains.

This paper aims to study the effect of orange peel and moringa leaves extracts on microbiological safety, sensory quality, lipid oxidation and color properties of chicken sausages under frozen storage.

Chicken sausages were prepared by using orange peel, moringa leaves extracts and butylated hydroxytoluene (BHT). The sausages were stored in a freezer at −18°C. Samples were taken at a regular interval of 20 days from the day of production to spoilage of sausages and analyzed for microbiological safety, sensory quality, lipid oxidation and color properties.

In comparison to the control sausage, sausages having BHT, orange peel and moringa leaves extract had a significantly (p < 0.05) lower bacterial, yeast and mold count. All the sausages were microbiologically safe for consumption till the 100th day, and the results of the 120th day crossed the permissible limits. Sensory acceptability scores of sausages were good (>6) throughout the storage period. The color values of sausages were not affected by the addition of orange peel and moringa leaves extract. The extent of lipid oxidation increased during storage, and sausages with BHT, orange peel and moringa leaves extract had significantly (p < 0.05) lower values of thiobarbituric acid reactive substances and free fatty acids (FFAs) toward the end of the storage period.

The observations of this paper endorse the use of orange peel and moringa leaves extract in meat products formulation for acceptable storage stability under frozen conditions.

Intelligent real-time systems are significantly impacting several of the UN Sustainable Development Goals (SDGs) by revolutionising processes in several areas such as Industry 4.0, smart cities, transportation, agriculture, renewable energy, climate change and other economic activities. Given that much of the work to achieve the SDGs relies on information and communication technology, cybersecurity has a potentially immense role to play towards achieving these outcomes. Moreover, cyberattacks have emerged as a new functional threat for interconnected, smart manufacturers and digital supply networks, employed in intelligent real-time systems for the Fourth Industrial Revolution. The effects of cyberattacks can be much more widespread than ever before due to the interconnected nature of Industry 4.0-driven operations. Blockchain can be really useful in such situations as it provides edge protection and allows authentication of the machine-to-machine and human–machine operations, stable data share, life cycle management, access control compliance of devices and self-sustaining operations. Moreover, blockchain can be applied for tracking and tracing transactions through devices, which are performed during the operation, as well as to encrypt and transmit data securely. It is vital to establish complete trust in a technology that is being adopted so that its full potential can be exploited. It is consequently critical that the organisational and information technology strategy fully integrates secure, vigilant and resilient cybersecurity strategies such as blockchain. This will ensure that cyber risks are properly managed in the age of Industry 4.0. This chapter, therefore, analyses the application of blockchain in intelligent real-time systems such as Industry 4.0 so that the opportunities these systems present for the SDGs can be exploited safely with minimum risks to society.

There is an urgent need to develop climate-smart agrosystems capable of mitigating climate change and adapting to its effects. Conventional agricultural practices prevail in Mauritius, whereby synthetic chemical fertilizers, pesticides and insecticides are used. It should be noted that Mauritius remains a net-food importing developing country of staple food such as cereals and products, roots and tubers, pulses, oil crops, vegetables, fruits and meat (FAO, 2011). In Mauritius, the agricultural sector faces extreme weather conditions like drought or heavy rainfall. Moreover, to increase the crop yields, farmers tend to use 2.5 times the prescribed amount of fertilizers in their fields. These excess fertilizers are washed away during heavy rainfall and contaminate lakes and river waters. By using smart irrigation and fertilization system, a better management of soil water reserves for improved agricultural production can be implemented. Soil Nitrogen, Phosphorus and Potassium (NPK) content, humidity, pH, conductivity and moisture data can be monitored through the cloud platform. The data will be processed at the level of the cloud and an appropriate mix of NPK and irrigation will be used to optimise the growth of the crops. Machine learning algorithms will be used for the control of the land drainage, fertilization and irrigation systems and real time data will be available through a mobile application for the whole system. This will contribute towards the Sustainable Development Goals (SDGs): 2 (Zero Hunger), 11 (Sustainable cities and communities), 12 (Responsible consumption and production) and 15 (Life on Land). With this project, the yield of crops will be boosted, thus reducing the hunger rate (SDG 2). On top of that, this will encourage farmers to collect the waters and reduce fertilizer consumption thereafter sustaining the quality of the soil on which they are cultivating the crops, thereby increasing their yields (SDG 15).