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Analyzing and reducing entropy generation is useful for enhancing the thermodynamic performance of engineering systems. This study aims to explore how polymers and nanoparticles in the presence of Lorentz forces influence the fluid behavior and heat transfer characteristics to lessen energy loss and entropy generation.

The dispersion model is initially used to examine the behavior of polymer additives over a magnetized surface. The governing system of partial differential equations (PDEs) is subsequently reduced through the utilization of similarity transformation techniques. Entropy analysis is primarily performed through the implementation of numerical computations on a non-Newtonian polymeric FENE-P model.

The numerical simulations conducted in the presence of Lorentz forces provide significant insights into the consequences of adding polymers to the base fluid. The findings suggest that such an approach minimizes entropy in the flow region. Through the utilization of polymer-MHD (magnetohydrodynamic) interactions, it is feasible to reduce energy loss and improve the efficiency of the system.

This study’s primary motivation and novelty lie in examining the significance of polymer additives as agents that reduce entropy generation on a magnetic surface. The author looks at how nanofluids affect the development of entropy and the loss of irreversibility. To do this, the author uses the Lorentz force, the Soret effect and the Dufour effect to minimize entropy. The findings contribute to fluid mechanics and thermodynamics by providing valuable insights for engineering systems to increase energy efficiency and conserve resources.

Financial and nonfinancial disclosures (sustainable accounting) are crucial in the annual financial reports of many firms. This study aims to explore the dynamic relationship between sustainability disclosure quality (SDQ) and financial performance (FP) within mandatory disclosure frameworks. SDQ is evaluated across six dimensions, encompassing both the quality and quantity of disclosures, aiming to understand their reciprocal influence.

Using the generalized method of moments (GMM), this research analyzes data from 2013 to 2019, focusing on 99 listed Indian firms within the S&P Bombay stock exchange (BSE) 500 index. The study uses rigorous measurement criteria to assess SDQ and uses statistical methods to unveil the causal link between SDQ and FP.

The results show a positive causal connection between SDQ and FP, where organizations with good FP make relatively higher disclosures across FP proxies than their counterparts. Additionally, the study investigates the impact of research and development (R&D) expenditure and dividend payments (DIVD) on SDQ. Notably, lower R&D spending is associated with higher quality SDs, and companies with superior SDQ exhibit increased DIVD.

The findings advocate for strengthened regulatory compliance, incentivized sustainable practices and heightened reporting standards for a transparent business environment and achieving the relevant United Nations Sustainable Development Goals.

This research contributes original insights by uncovering the intricate relationship between SDQ and FP, shedding light on the impact of R&D expenditure and DIVD on SDQ. These findings contribute to a nuanced understanding of the interplay between FP and sustainability reporting within the context of mandatory disclosure frameworks.

This chapter explored the community resilience among the river bank erosion affected people of the coastal area in Bangladesh. This chapter particularly looked at the affected people’s opinions and participation in the governmental organization (GO) and non-governmental organizations’ (NGO) relief and recovery process. This study employed a mixed-method approach, where a multimethod data collection procedure was used and data were from three Upazilas (sub-divisions) of the Bhola District in Bangladesh. Quantitative data were collected using a structured interview schedule from 371 household heads, while the qualitative data were generated from 30 relevant participants through in-depth case interviews, focus group discussions and key informants’ interviews. Results showed that a higher number of affected people did not get government relief and services though they were happy with the government’s permanent measures, that is, building embankment. The affected people gave a negative impression about the GO and NGOs’ initiatives in the recovery process such as awareness building, needs assessment and formation of community-based organizations. Most of the affected households did not participate in the decision-making process of the recovery and construction planning and programmes that were controlled by the local power politics. Findings would be an important guideline to the policy-makers, disaster managers and development practitioners.

The purpose of this study is to provide the full-state mathematical model and devise a nonlinear controller for a balloon-supported unmanned aerial vehicle (BUAV).

Newtonian mechanics is used to establish the nonlinear mathematical model of the proposed vehicle assembly which incorporates the dynamics of both balloon and quadrotor UAV. A controllable form of the nine degrees of freedom model is derived. Backstepping control is designed for the proposed model and simulations are performed to assess the tracking performance of the proposed control.

The results show that the proposed methodology works well for smooth trajectories in presence of wind gusts. Moreover, the final mathematical model is affine and various nonlinear control techniques can be used in the future for improved system performance.

Multi-rotor unmanned aerial vehicles (MUAVs) are equipped with controllers but are constrained by smaller flight endurance and payload carrying capability. On the contrary, lighter than air (LTA) aerial vehicles have longer flight times but have poor control performance for outdoor operations. One of the solutions to achieve better flight endurance and payload carrying capability is to augment the LTA balloon to MUAV. The novelty of this research lies in full-order mathematical modeling along with transformation to controllable form for the BUAV assembly.

Amid rising environmental concerns, Industry 4.0 and blockchain technology (BCT) are transforming circular economy practices and prevailing business models. Recognizing the same, the current study examines the role of advanced technology in circular practices and their impact on eco-environmental performance, which influences organizational performance. The study collects data from 185 food processing enterprises that are located in Malaysian territories. By employing CB-SEM modeling, the study provides three key findings. First, Industry 4.0 significantly improves the circular economy practices. Second, circular economy practices help to improve firms' environmental performance but did not stimulate operational performance. Third, higher eco-environmental performance significantly boosts organizational performance. This study set out the foundations for participating countries/firms that help to achieve sustainable goals through the integration of blockchain technology in circular economy practices.

The primary aim of this study is to examine the decision-making process of a reverse supply chain within a cooperative-competitive environment, with a particular emphasis on the incorporation of Internet of Things (IoT) technology in the recycling process.

The impact of IoT on recycling effectiveness, RF (refurbished) product demand and remanufacturing expenses is analyzed. The game-theoretic models are constructed to incorporate the co-competitive relationship between a IR (Internet Recycler) and a remanufacturer, with specific attention paid to the IR's application of IoT technology.

The results indicate that the use of IoT reduces the costs associated with remanufacturing, leading to an increase in the transfer price of pre-owned items procured from IRs. The efficacy of the reverse supply chain depends not only on its cost-saving capabilities but also on consumer preferences toward RF and remanufactured (RM) items.

IoT technology can benefit Internet recycling and remanufacturing by enhancing transparency, quality monitoring and automation of processes. It can also help reduce operating costs, improve customer engagement and incentivize cooperation between organizations.

This study examined the strategic decision-making processes in the context of cooperation and competition between IR and remanufacturers. In addition, this research makes a valuable contribution to the literature by elucidating the optimal conditions for the effective implementation of Internet of Things (IoT) technology in recycling operations.

Pakistan is one of the most climate change and natural disaster-affected countries in the globe, where the lives and livelihoods of people are repeatedly affected due to these natural disasters. Over the past few decades, the country has been impacted by numerous devastating floods, droughts, and storms. As a result, households face enormous complications, particularly those dwelling in disaster-prone areas. Therefore, this study intends to explore the status of household vulnerability and resilience practices of hazard-prone communities in Pakistan from existing literature. This study has identified the 17 most relevant documents. It argues that household vulnerability is increasing consistently with the increasing rate of disaster intensity. Frequent flooding, landslide, erosion, and crop loss are the leading causes of household vulnerability. This study reveals five types of household vulnerability components which look into several livelihood vulnerability indicators of Pakistani households. Moreover, the study unfolds that the main causes of disaster vulnerability are widespread crop loss, a lack of water, loss of soil fertility, and low socioeconomic situations. The major vulnerability components of dwellers are exposure (increasing summer duration, the rapid increase of population house build-up in the riparian areas, and increasing occurrence of hailstorms), sensitivity, low access to education facilities, human loss, diseases infestation, food insecurity, and social conflict), and less adaptive capacity (social networks, migration, poor emergency services, multiple income sources, and less access to the health facility). To address the household vulnerability, this study has also identified four key aspects of resilience, like social resilience, economic resilience, institutional resilience, and physical resilience. The findings will effectively help to understand the dynamics of household vulnerability and resilience and its measurement and management strategy from developed indicators.

This study investigates the flow and heat transfer in a magnetohydrodynamic (MHD) ternary hybrid nanofluid (HNF), considering the effects of viscous dissipation and radiation.

The transport equations are transformed into nondimensional partial differential equations. The local nonsimilarity (LNS) technique is implemented to truncate nonsimilar dimensionless system. The LNS truncated equation can be treated as ordinary differential equations. The numerical results of the equation are accomplished through the implementation of the bvp4c solver, which leverages the fourth-order three-stage Lobatto IIIa formula as a finite difference scheme.

The findings of a comparative investigation carried out under diverse physical limitations demonstrate that ternary HNFs exhibit remarkably elevated thermal efficiency in contrast to conventional nanofluids.

The LNS approach (Mahesh et al., 2023; Khan et al., 20223; Farooq et al., 2023) that we have proposed is not currently being used to clarify the dynamical issue of HNF via porous media. The LNS method, in conjunction with the bvp4c up to its second truncation level, yields numerical solutions to nonlinear-coupled PDEs. Relevant results of the topic at hand, obtained by adjusting the appropriate parameters, are explained and shown visually via tables and diagrams.

Economic costs and benefits are at the core while taking decision to adopt digitalization in the supply chain. The present chapter provides an in-depth exploration of the economic dimensions of digital supply chain management (DSCM) adoption in a firm. Drawing from a diverse source of literature, this chapter discusses the effect of economic outlook on DSCM adoption, the economic benefits of DSCM adoption and costs associated with it, and economic analysis and evaluation methodologies. The chapter also shares the case studies illustrating the real-world implications of economic considerations within DSCM initiatives. The chapter highlights how changing international socioeconomic and political dynamics can influence businesses across the globe. By analyzing the impacts of evolving market trends, changing consumer preferences, and geopolitical tensions, organizations can considerably forecast the possible impacts of these macroeconomic forces adeptly. The chapter also undertakes discussion on the economic cost and benefits associated with DSCM adoption. The economic analysis helps understand that the expected benefits outweigh economic costs, substantiating the economic viability of DSCM projects. The chapter concludes by discussing the examples of some real-world companies, highlighting how organizations have successfully applied economic analyses to their DSCM initiatives. This also highlights as to how showcasing how detailed economic assessments can justify substantial investments, deliver operational efficiencies, and reshape industries.

The primary focus of this study is to tackle a critical industry issue concerning energy inefficiency. This is achieved through an investigation into enhancing heat transfer in solar radiation phenomena on a curved surface. The problem formulation of governing equations includes the combined effects of thermal relaxation, Newtonian heating, radiation mechanism, and Darcy-Forchheimer to enhance the uniqueness of the model. This research employs the Cattaneo–Christov heat theory model to investigate the thermal flux via utilizing the above-mentioned phenomenon with a purpose of advancing thermal technology. A mixture of silicon dioxide (SiO_2)\ and Molybdenum disulfide (MoS_2) is considered for the nanoparticle’s thermal propagation in base solvent propylene glycol. The simulation of the modeled equations is solved using the Shifted Legendre collocation scheme (SLCS). The findings show that, the solar radiation effects boosted the heating performance of the hybrid nanofluid. Furthermore, the heat transmission progress increases against the curvature and thermal relaxation parameter.

Shifted Legendre collocation scheme (SLCS) is utilized to solve the simulation of the modeled equations.

The findings show that, the solar radiation effects boosted the heating performance of the hybrid nanofluid. The heat transmission progress increase against the curvature and thermal relaxation parameter.

This research employs the Cattaneo–Christov heat theory model to investigate the thermal flux via utilizing the above-mentioned phenomenon with a purpose of advancing thermal technology.