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One of the major challenges in the design of thermal equipment is to minimize the entropy production and enhance the thermal dissipation rate for improving energy efficiency of the devices. In several industrial applications, the structure of thermal device is cylindrical shape. In this regard, this paper aims to explore the impact of isothermal cylindrical solid block on nanofluid (Ag – H₂O) convective flow and entropy generation in a cylindrical annular chamber subjected to different thermal conditions. Furthermore, the present study also addresses the structural impact of cylindrical solid block placed at the center of annular domain.

The alternating direction implicit and successive over relaxation techniques are used in the current investigation to solve the coupled partial differential equations. Furthermore, estimation of average Nusselt number and total entropy generation involves integration and is achieved by Simpson and Trapezoidal’s rules, respectively. Mesh independence checks have been carried out to ensure the accuracy of numerical results.

Computations have been performed to analyze the simultaneous multiple influences, such as different thermal conditions, size and aspect ratio of the hot obstacle, Rayleigh number and nanoparticle shape on buoyancy-driven nanoliquid movement, heat dissipation, irreversibility distribution, cup-mixing temperature and performance evaluation criteria in an annular chamber. The computational results reveal that the nanoparticle shape and obstacle size produce conducive situation for increasing system’s thermal efficiency. Furthermore, utilization of nonspherical shaped nanoparticles enhances the heat transfer rate with minimum entropy generation in the enclosure. Also, greater performance evaluation criteria has been noticed for larger obstacle for both uniform and nonuniform heating.

The current numerical investigation can be extended to further explore the thermal performance with different positions of solid obstacle, inclination angles, by applying Lorentz force, internal heat generation and so on numerically or experimentally.

A pioneering numerical investigation on the structural influence of hot solid block on the convective nanofluid flow, energy transport and entropy production in an annular space has been analyzed. The results in the present study are novel, related to various modern industrial applications. These results could be used as a firsthand information for the design engineers to obtain highly efficient thermal systems.

This study aims to elucidate the role of curved walls in the presence of identical mass of porous bed with identical heating at a wall for two heating objectives: enhancement of heat transfer to fluid saturated porous beds and reduction of entropy production for thermal and flow irreversibilities.

Two heating configurations have been proposed: Case 1: isothermal heating at bottom straight wall with cold side curved walls and Case 2: isothermal heating at left straight wall with cold horizontal curved walls. Galerkin finite element method is used to obtain the streamfunctions and heatfunctions associated with local entropy generation terms.

The flow and thermal maps show significant variation from Case 1 to Case 2 arrangements. Case 1 configuration may be the optimal strategy as it offers larger heat transfer rates at larger values of Darcy number, Da_m. However, Case 2 may be the optimal strategy as it provides moderate heat transfer rates involving savings on entropy production at larger values of Da_m. On the other hand, at lower values of Da_m (Da_m ≤ 10⁻³), Case 1 or 2 exhibits almost similar heat transfer rates, while Case 1 is preferred for savings of entropy production.

The concave wall is found to be effective to enhance heat transfer rates to promote convection, while convex wall exhibits reduction of entropy production rate. Comparison between Case 1 and Case 2 heating strategies enlightens efficient heating strategies involving concave or convex walls for various values of Da_m.

In the competitive business world, companies strive to be innovative, and to do so, they try to implement innovative human resource practices. Therefore, the authors propose an association between innovative human resource practice, organizational commitment, innovation performance and transformational leadership.

This study gathered data from 1,037 small- and medium-sized enterprises and implied partial least square structural equation modeling PLS-SEM using Smart PLS was adopted to test the hypotheses.

The findings reveal positive direct relationships between innovative human resource practices, organizational commitment and innovation performance. Moreover, organizational commitment positively mediates and transformational leadership significantly and positively moderates the relationship. Companies should use innovative recruitment and selection, performance management, and innovative compensation to enhance organizational commitment and innovation performance. In addition, the optimized organizational commitment aids in strengthening the connection between innovative human resource practices and firms' innovation performance.

Managers should also develop a sense of affiliation and attachment to increase innovation performance. The study contributes empirically to the literature on innovative human resource practices and their effect on organizational commitment and innovation performance.

There is an ever-increasing number of patients suffering from various forms of acute and chronic pain and getting treatment for such ailments is a basic human right. Opioid analgesics remain one way of managing and attending to such patients. However, due to the prevalence of opiophobia, many doctors avoid prescribing opioid-based medicines, even at the cost of patients suffering leading to a hindrance in providing optimal health care. Up till now, there has been no reliable and valid instrument to measure the severity of opiophobia in doctors. For this reason, the purpose of this study is to represent the construction of a precise and reliable instrument for measuring opiophobia along with its validation for doctors in Pakistan.

Interviews and theoretical knowledge relating to opiophobia were used as the basis for the purpose of generating an item pool. The generated item pool was evaluated by subject matter experts for content validity and inter-rater reliability, followed by Velicer’s minimum average partial method and maximum likelihood factor analysis for establishing the factorial structure of the scale. As opiophobia in doctors prevails the most and causes a lower ratio of prescription of opioid analgesics. The present sample selected for the study was that of n = 100 doctors (men = 50; women = 50) from various hospitals, treating patients with chronic pain, in Rawalpindi and Islamabad.

A two-factor structure was suggested by Velicer’s minimum average partial method and maximum likelihood factor analysis, which were labeled as fear of opioid analgesics and justified acceptance of opioids. The developed opiophobia questionnaire along with its subscales displayed appropriate levels of reliability α = 0.733, α = 0.760 and α = 0.725, respectively, suggesting the scale to be reliable.

Like any other study, this study also tried to address every essential aspect, but still lacked at some places which should be considered and catered for in future studies. In the first place the sample size was very limited which was due to the fact, the study was conducted during a pandemic and physically going for data collection was unavailable, thus leading to consequent sample size. It is recommended a correspondent study can be conducted with larger sample size, so they can get more reliable results with greater precision and power. Then, they will have the advantage of a small margin of error. The second limitation was the study involved only doctors as that was the main focus of the present study. However, other hospital staff such as nurses should also be incorporated to assess their level of opiophobia. The current scale suggests the severity of opiophobia with higher scores though no cutoff point has been suggested. Future studies should try and incorporate a cutoff point to assess the difference between doctors who have conventional levels of reservations against opioids and those suffering from opiophobia. Another limitation was that the present scale did not establish additional validities such as convergent and divergent validity. Future studies should collect data from a larger sample to establish these validities to further refine the scale.

This instrument can be immensely effective in identifying doctors who have concerns and fears about prescribing opioids to patients with chronic pain. The findings acquired on such a scale can help in developing appropriate academic and psychological interventions which can help such doctors to overcome their opiophobia. This can enable more doctors to prescribe appropriate medicine to their patients instead of letting them suffer from pain. Additionally, researchers can equally benefit from the instrument as it can enable them to investigate opiophobia with other possible variables.

Developing such a scale about the fear faced by doctors while treating patients would be very useful as it is not possible to take such fear when it comes to a patient’s life. This fear is also common among patients where they have a fear about the undesirable effects, addiction of drugs and fear of dying. Better awareness should be given to them which will be helpful for successful and less painful treatment in hospitals.

This scale is an original work with the aim of accessing opiophobia among doctors toward (chronic) patients with severe pain. There was a lot of research work that has been done on opiophobia in developed countries and few Pakistani researchers have also worked on opiophobia and its impact on pain management but still, no scale has been developed to measure the extent or tendency of opiophobia among doctors or patients. This scale can be used globally on both men and women doctors to access the tendency of opiophobia among them.

The environment of uncertainty that emerged due to COVID-19 brought the need for the creation of new policies and strategies. In this aspect, it has been observed that various recovery strategies have been adopted by policymakers. Thus, this study aimed to investigate the efforts of destinations for senior tourism and to determine the development and change in the academic studies and related strategies. The methodology was based on a literature review and examining policy documents linking senior tourism, tourism destinations, and post-COVID-19 strategies. In this vein, this study is exploratory and displays a conceptual foundation for future research.

The current situation is changing rapidly in terms of technology, politics, economy and society. Every child could become a child with special educational needs should they no longer be fit to join a future world. In this sense, to survive in the world of next normality, an era in which the playing field for all children is levelled, it is thought-provoking to consider how the new way of special and inclusive education should be designed to close the inequality gap and create an equilibrium. This chapter focuses on describing how special and inclusive education in the next world with the inevitable high inequality gap should be designed.

The study aims to validate a mobile learning readiness scale through the technology readiness and acceptance model (TRAM), thereby assessing students' readiness to adopt m-learning in teaching and learning, including its acceptance.

A structured questionnaire was administered to open and distance learning (ODL) students in Odisha, India, to assess their readiness and acceptance of m-learning. 665 valid responses were collected, and collected data was analysed using statistical packages for social sciences (SPSS) and SmartPLS.

The findings of the study reveal that optimism contributes positively to perceived ease of use (PEOU) and perceived usefulness (PU) of m-learning (β = 7.921, p < 0.001; β = 2.123, p < 0.05), whereas innovativeness positively contributes to PEOU of m-learning (β = 2.227, p < 0.05), but not PU of m-learning. ODL student's optimism improves his/her PEOU and PU of m-learning, but innovativeness improves only his/her PEOU. Further, the impact of innovativeness is higher than that of optimism in the TRAM and innovativeness is the strong predictor to adopt m-learning. It also shows that the PU of m-learning positively influences behavioural intention to use m-learning (β = 4.757, p < 0.001). Integrating technology readiness (TR) with technology acceptance model (TAM) to predict students' acceptance of m-learning is very useful.

The paper will help decision-makers to adopt and use m-learning in higher educational institutions.

This paper is the first to explore the readiness and acceptance of m-learning in higher education in India.

Mega-infrastructure development plans pave the way for policies to upgrade the infrastructure, environmental management and different aspects of locals’ well-being. These developmental dynamics can positively affect rural tourism including heritage sites destinations. The quality of life of local people can be linked to this positive developmental change through long-term and sustainable economic revitalization projects. In terms of this process, developing large-scale infrastructure and incorporating tourism sustainability can improve the quality of life-related to different dimensions that are critical to the community's well-being. Therefore, researchers have attempted to address this issue.

Data were collected between September and October 2020. The study sample size was the residents of Zhabagly village, including Zhabagaly, Abaiyl and 115 Railway settlements. Moreover, the residents were older than 18 years. A systematic random sampling technique was utilised to reach the targeted sample size and the researchers received 243 responses from the locals. Structural equation modelling (SEM) was used for analysis.

The findings from the structural equation modelling suggest that sustainable tourism increases due to the positive effect of mega-infrastructure development and positively impacts the locals' quality of life. Notably, no direct effect of mega-infrastructure development on quality of life reveals the pivotal role of sustainable tourism. Therefore, during the COVID-19 period, the dimensions of sustainable tourism – economic, market, socio-cultural and environmental – played a role in securing the positive impact of mega-infrastructure development on the locals’ quality of life.

This research highlighted the fact that when infrastructure projects are implemented to their full potential, they will generate sustainable tourism activities, provide eco-adventure activities, relax, treat signatories and boost the economy of all stakeholders. The study used AMOS to test the hypotheses. Qualitative research methods, including interviews with citizens, government officials and tourism managers, require further study.

The infrastructural development on a mega-scale means building an upscaling tourism ecosystem. This ecosystem is marked by the availability of drinking water, waste and energy management facilities that support the elevation of living material, community, health, safety and emotional well-being. It reflects the policy-level implications for future Belt and Road initiatives (BRIs). The tourism industry's resilience during COVID-19 has practical lessons for other industries.

Large-scale infrastructure construction must create favourable conditions for the rapid development of tourism. The availability of clean water, waste and energy management facilities contributes to the food production, social cohesion, physical and mental health and general well-being of the ecosystem. This is one of the few studies that used sustainable tourism as a mediator between the impact of large infrastructure projects and their impact on the quality of life of locals during the COVID-19 pandemic. Aksu-Zhabagly, a World Heritage Site in Kazakhstan, was the site of this field study.

This study provide an in-depth review on the knowledge structure of green information technology (GIT) adoption and behavior. Environmental degradation has escalated even further with information and digital technology development. Researchers have come up with a new concept of GIT to dampen the carbon emission due to the excessive use of IT in today’s everyday usage. A similar terminology, green information system (GIS), is a rather broad understanding of GIT, which relates to the environmental management system to improve operations in the organization and will be included in the scope of the study.

This study presents a science mapping analysis through a bibliometric review to explore emerging trends and predict future trends based on 293 publications in the Web of Science.

The bibliographic coupling analysis discovered five themes related to the theoretical foundation of GIT and the determinants of their adoption. The five themes are (1) theoretical foundation in GIT, (2) determinants of green IT and IS adoption, (3) fundamental of GIT and information science, (4) green technologies and green computing and (5) determinants of managers green IT adoption behavior. While co-word analysis presents the impact of GIT, driving performance and energy efficiency through the adoption of GIT producing four themes, (1) GIT acceptance through the theory of planned behavior, (2) impact of GIT’s: strategies for sustainable implementation, (3) driving sustainable performance through green innovation in information systems and technology and (4) energy efficiency and sustainability in green computing and cloud computing.

The finding is relevant to managers, researchers and stakeholders bounded by environmental responsibilities to mitigate its impact on the socioeconomic and environment through GIT adoption.

The contribution of this study is presenting an in-depth analysis of the knowledge structure through bibliometric analysis by providing network visualization on one of the crucial pro-environmental behavior.

This study aims to elucidate the dynamics of social media discourse during global health events, specifically investigating how users across different platforms perceive, react to and engage with information concerning such crises.

A mixed-method approach was employed, combining both quantitative and qualitative data collection. Initially, thematic analysis was applied to a data set of social media posts across four major platforms over a 12-month period. This was followed by sentiment analysis to discern the predominant emotions embedded within these communications. Statistical tools were used to validate findings, ensuring robustness in the results.

The results showcased discernible thematic and emotional disparities across platforms. While some platforms leaned toward factual information dissemination, others were rife with user sentiments, anecdotes and personal experiences. Overall, a global sense of concern was evident, but the ways in which this concern manifested varied significantly between platforms.

The primary limitation is the potential non-representativeness of the sample, as only four major social media platforms were considered. Future studies might expand the scope to include emerging platforms or non-English language platforms. Additionally, the rapidly evolving nature of social media discourse implies that findings might be time-bound, necessitating periodic follow-up studies.

Understanding the nature of discourse on various platforms can guide health organizations, policymakers and communicators in tailoring their messages. Recognizing where factual information is required, versus where sentiment and personal stories resonate, can enhance the efficacy of public health communication strategies.

The study underscores the societal reliance on social media for information during crises. Recognizing the different ways in which communities engage with, and are influenced by, platform-specific discourse can help in fostering a more informed and empathetic society, better equipped to handle global challenges.

This research is among the first to offer a comprehensive, cross-platform analysis of social media discourse during a global health event. By comparing user engagement across platforms, it provides unique insights into the multifaceted nature of public sentiment and information dissemination during crises.