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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 investigates the behavior of viscous hybrid ferromagnetic fluids flowing through plain elastic sheets with the magnetic polarization effect. It examines flow in a porous medium using Stefan blowing and utilizes a versatile hybrid ferrofluid containing MnZnFe₂O₄ and Fe₃O₄ nanoparticles in the C2H2F4 base fluid, offering potential real-world applications. The study focuses on steady, laminar and viscous incompressible flow, analyzing heat and mass transfer aspects, including thermal radiation, Brownian motion, thermophoresis and viscous dissipation with convective boundary condition.

The governing expression of the flow model is addressed with pertinent non-dimensional transformations, and the finite element method solves the obtained system of ordinary differential equations.

The variations in fluid velocity, temperature and concentration profiles against all the physical parameters are analyzed through their graphical view. The association of these parameters with local surface friction coefficient, Nusselt number and Sherwood number is examined with the numerical data in a table.

This work extends previous research on ferrofluid flow, investigating unexplored parameters and offering valuable insights with potential engineering, industrial and medical implications. It introduces a novel approach that uses mathematical simplification techniques and the finite element method for the solution.

The purpose of this study is to investigate the effects of entropy generation of some embedded thermophysical properties on heat and mass transfer of pulsatile flow of non-Newtonian nanofluid flows between two porous parallel plates in the presence of Lorentz force are taken into account in this research.

The governing partial differential equations (PDEs) were nondimensionalized using suitable nondimensional quantities to transform the PDEs into a system of coupled nonlinear PDEs. The resulting equations are solved using the spectral relaxation method due to the effectiveness and accuracy of the method. The obtained velocity and temperature profiles are used to compute the entropy generation rate and Bejan number. The influence of various flow parameters on the velocity, temperature, entropy generation rate and Bejan number are discussed graphically.

The results indicate that the energy losses can be minimized in the system by choosing appropriate values for pertinent parameters; when thermal conductivity is increasing, this leads to the depreciation of entropy generation, and while this increment in thermal conductivity appreciates the Bejan number, the Eckert number on entropy generation and Bejan number, the graph shows that each time of increase in Eckert will lead to rising of entropy generation while this increase shows a reduction in Bejan number. To shed more light, these results were further demonstrated graphically. The current research was very well supported by prior literature works.

All results are presented graphically, and the results in this article are anticipated to be helpful in the area of engineering.

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.

Traditional library book recommendation methods are mainly based on association rules and user profiles. They may help to learn about students' interest in different types of books, e.g., students majoring in science and engineering tend to pay more attention to computer books. Nevertheless, most of them still need to identify users' interests accurately. To solve the problem, the authors propose a novel embedding-driven model called InFo, which refers to users' intrinsic interests and academic preferences to provide personalized library book recommendations.

The authors analyze the characteristics and challenges in real library book recommendations and then propose a method considering feature interactions. Specifically, the authors leverage the attention unit to extract students' preferences for different categories of books from their borrowing history, after which we feed the unit into the Factorization Machine with other context-aware features to learn students' hybrid interests. The authors employ a convolution neural network to extract high-order correlations among feature maps which are obtained by the outer product between feature embeddings.

The authors evaluate the model by conducting experiments on a real-world dataset in one university. The results show that the model outperforms other state-of-the-art methods in terms of two metrics called Recall and NDCG.

It requires a specific data size to prevent overfitting during model training, and the proposed method may face the user/item cold-start challenge.

The embedding-driven book recommendation model could be applied in real libraries to provide valuable recommendations based on readers' preferences.

The proposed method is a practical embedding-driven model that accurately captures diverse user preferences.

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.

This paper aims to explain the occurrence of sustainable entrepreneurship in the underresearched sub-Saharan Africa context and to improve the understanding of how effectuation manifests in this context.

This study uses a qualitative research approach based on multiple case studies. Responses were sourced from owners, employees, suppliers, the community and customers of sustainable entrepreneurial firms. Data collection methods included in-depth interviews, document reviews and observations. The Gioia analytical approach was used.

Overall, the authors find the concept of effectuation to be well-suited to capturing the processes through which individuals with limited means seek to engage in sustainable entrepreneurship. The authors also identify three pervasive practices that are key to understanding effectuation in the developing country context: complementation of indigenous knowledge with modern science, compassion and pluriactivity.

This study underscores the importance of co-creation, diversification of revenue sources and the role of emotional awareness and interpersonal skills in entrepreneurial endeavors.

This study, therefore, contributes new knowledge about the mechanisms through which entrepreneurs faced with resource constraints use control as opposed to prediction strategies to exploit sustainable entrepreneurship opportunities. In so doing, this study contributes to entrepreneurship theory by proposing the integration of cognitive and affective dimensions in realizing sustainable entrepreneurship goals.

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.

Present study aimed to nanosilver-treat some commercially dyed denim fabric using an eco-friendly cross-linker of citric acid for possible application in the fabrication of sustainable antibacterial and nontoxic surgical gowns.

The conventional untreated surgical gowns are prone to bacterial attack making them unprotective and infection carriers. Thereby, nanosilver finishing of the surgical-grade dyed denim fabric was achieved via citrate cross-linking under the pad-dry-cure method. The hence treated denim fabrics were characterized for surface chemical, crystalline, textile, color and antibacterial attributes using both conventional and advanced analytical approaches.

The results expressed that the prepared denim specimens contained surface roughness at the nanoscale besides some alterations in their textile and color parameters. Both textile and comfort properties of the finished fabric remained in the acceptable range with effective antibacterial activity.

The silver nano-finished dyed denim expressed broad-spectrum antibacterial activity and qualified as a potential substrate in the fabrication of surgical gowns. Such sustainable application of nanosilver finishing could be perused for industrial implications.

This study presents citric acid as a crosslinking agent to impregnate the commercially dyed denim fabric for potential application in the fabrication of surgical gowns. The application of nanosilver on prior citrated dyed-grown fabrics could be a novel approach. This study used approximately all the reagents and auxiliaries as bio-based to ensure the nontoxicity and sustainability of the resultant fabric.