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This study aims to investigate entropy generation through natural convection and examine heat transfer properties within a partially heated and cooled enclosure influenced by an angled magnetic field. The enclosure, subjected to consistent heat production or absorption, contains a porous medium saturated with a hybrid nanofluid blend of Cu-Fe₃O₄ and MoS₂-Fe₃O₄.

The temperature and velocity equations are converted to a dimensionless form using suitable non-dimensional quantities, adhering to the imposed constraints. To solve these transformed dimensionless equations, the finite-difference method, based on the MAC (Marker and Cell) technique, is used. Comprehensive numerical simulations address various control parameters, including nanoparticle volume fraction, Rayleigh number, heat source or sink, Darcy number, Hartmann number and slit position. The results are illustrated through streamlines, isotherms, average Nusselt numbers and entropy generation plots, offering a clear visualization of the impact of these parameters across different scenarios.

Results obtained show that the Cu-Fe₃O₄hybrid nanofluid exhibits higher entropy generation than the MoS₂-Fe₃O₄ hybrid nanofluid when comparing them at a Rayleigh number of 10⁶ and a Darcy number of 10^–1. The MoS₂ hybrid nanofluid demonstrates a low permeability, as evidenced by an average Darcy number of 10^–3, in comparison to the Cu hybrid nanofluid. The isothermal contours for a Rayleigh number of 10⁴are positioned parallel to the vertical walls. Additionally, the quantity of each isotherm contour adjacent to the hot wall is being monitored. The Cu and MoS₂ nanoparticles exhibit the highest average entropy generation at a Rayleigh number of 10⁵ and a Darcy number of 10^–1, respectively. When a uniform heat sink is present, the temperature gradient in the central part of the cavity decreases. In contrast, the absence of a heat source or sink leads to a more intense temperature distribution within the cavity. This differs significantly from the scenario where a uniform heat sink regulates the temperature.

The originality of this study is to examine the generation of entropy in natural convection within a partially heated and cooled enclosure that contains hybrid nanofluids. Partially heated corners are essential for optimizing heat transfer in a wide range of industrial applications. This enhancement is achieved by increasing the surface area, which improves convective heat transfer. These diverse applications encompass fields such as chemical engineering, mechanical engineering, surface research, energy production and heat recovery processes. Researchers have been working on improving the precision of heated and cold corners using various methods, such as numerical, experimental and analytical approaches. These efforts aim to enhance the broad utility of these corners further.

This study aims to optimize the design of falling film heat exchangers by providing a deeper understanding of wave characteristics and capillary flow in laminar inclined falling films at low Reynolds numbers. The focus is on the effects of different Kapitza numbers, influenced by fluid properties and inclination, on the interfacial wave behavior.

A numerical investigation was conducted using the volume of fluid method within OpenFOAM’s interFoam solver. This study examined the effects of Kapitza number, inclination angle and inlet disturbances on wave formation and flow dynamics, analyzing how these factors influence interfacial wave amplitude, wavelength and flow in the capillary region.

The results revealed that higher Kapitza numbers lead to the formation of stronger capillary waves. Flow separation was observed in the capillary wave region for materials with high Kapitza numbers. An improved Nosoko correlation model was developed, incorporating the inclination angle to more accurately predict the relationship between wave peaks and wavelengths in inclined cases.

This research investigates the impact of low Kapitza number on inclined falling film flow, and a correlation model was derived that provides a broader range for evaluating wave behavior in inclined conditions, offering extended references for the design of falling film heat exchangers.

This article aims to propose a model to support the assessment and prioritization of risk in manufacturing processes.

The model integrates the failure modes and effects analysis (FMEA) criteria with the evaluation procedures of a new hesitant fuzzy linguistic-technique for Order of Preference by Similarity to Ideal Solution (HFL-TOPSIS) variation. A case study evaluating failure risk in a wiring harness assembly process demonstrated the model's applicability. A sensitivity analysis was performed to verify the effect of the variation in the weights assigned to the decision-makers (DMs).

The failure mode (FM) ranking was FM4 > FM9 > FM17 > FM2>FM8>FM12 > FM16 > FM19 > FM11 > FM3>FM18 > FM15 > FM13 > FM10 > FM14 > FM7 > FM1 > FM5 > FM6. These outcomes suggest that “stripping length less than specified” was the top priority among the 19 FMs evaluated. Sensitivity tests demonstrated the effect of the DMs’ weights on the ranking of FMs. A comparison with FMEA and HFL-TOPSIS demonstrates the model's greater capacity to discriminate levels of risk priority, as it identifies a total of 19 risk levels compared with 9 levels in the other approaches.

The adoption of the proposed model can drive substantial improvements in risk management practices across industries, provided that the organization has a decision-making team experienced with FMEA. Therefore, this approach promotes the continuous improvement of operations and ensures that mitigation actions effectively address critical FMs.

This is the first study to propose a risk evaluation model that accounts for DMs' hesitation in defining criteria weights through linguistic expressions. Additionally, it addresses uncertainty when assessing weights for the DMs’ opinions and considers multiple factors that affect these weights in decision-making for risk prioritization.

Neglected communities, such as transgender individuals in developing nations like Pakistan, face substantial barriers to economic participation due to diverse economic and social conditions. This study aims to explore the role of inclusive entrepreneurial ecosystems in enhancing entrepreneurial intentions among these communities, emphasizing the mediating role of psychological capital and the moderating effect of entrepreneurial education.

Using social cognitive theory and the theory of planned behavior, the research adopts a questionnaire survey methodology with a sample size of 308 to gather data from transgender individuals engaged in or interested in entrepreneurship. The analysis was conducted using AMOS and SPSS software.

The results show that inclusive entrepreneurial ecosystems directly enhance psychological capital but do not significantly affect entrepreneurial intentions unless psychological capital acts as a mediator. Entrepreneurial education does not illustrate a significant moderating effect on the connection between inclusive entrepreneurial ecosystems and entrepreneurial intentions.

These findings highlight the significance of psychological resources in transforming environmental supports into entrepreneurial action, proposing significant insights for policymakers and educators to foster more inclusive entrepreneurial ecosystems aligned with sustainable development goals. This study contributes to the discussion on entrepreneurship among underserved populations and demonstrates the vital role of personalized educational and environmental supports in developing economic participation.

Exploring the Lean and Green relationship goes back to the beginnings of Lean manufacturing. Most cases established that companies implementing Lean have Green results. However, there are Lean practices with a higher impact on Green, but others with less impact. Therefore, this paper presents research that explores the relationship between Lean and Green in manufacturing companies and aims to determine whether Lean practices have a higher association with Green aspects.

A survey was conducted amongst manufacturing firms to determine their Lean Index (LI). The internally related elements of the Lean construct determined each firm’s LI, whilst Cronbach alpha determined internal LI consistency. The survey also identified firms developing six Green aspects: International Organisation for Standardisation (ISO) 14001, ISO 50001, general Green aspects and the specific aspects of materials, energy and water. An individual sample t-test shows different LI levels of association for each Green aspect. Binomial logistic regression shows the LI element association for each Green aspect.

LI is higher at firms reporting the inclusion of Green aspects. More than half of LI components have a statistically relevant association with the six Green aspects. In general, Ishikawa diagrams had the highest association with Green aspects whilst the lowest was seen in workers as improvement initiators. By grouping the LI elements into their categories, the Lean practices related to controlling processes have a higher association, whilst the involvement of employees has the lowest.

Further research found in this paper identifies the possibilities for investigating the specificities of each Lean tool to develop Green aspects in companies.

Practitioners learn that Lean and Green are not separate issues in business. This article provides evidence that Lean practices in place at companies are already associated with Green aspects, so integration may already be happening.

This paper provides specifics on the relationship between each Lean practice and developing Green aspects. Thus, this paper specifies the Lean practices that contribute most to Green efficiency to support the joint development of both themes.