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This study aims to investigate the effects of layering sequence, aspect ratios, fiber orientation angles, loading types and boundary conditions on the buckling behavior of glass/carbon/hybrid fiber-reinforced epoxy laminated composites using the differential quadrature (DQ) approach.

In total, different hybrid combinations are considered separately for angle-ply, cross-ply and antisymmetric layup schemes. For this purpose, a DQ code is developed using MATLAB.

The results obtained from the study reveal that the lamination arrangements and varying loading conditions of the hybrid laminated structures have a significant effect on the buckling performance of these materials.

This is the first study to investigate how the critical buckling loads of glass fiber/epoxy and carbon fiber/epoxy laminated hybrid composite plates are influenced by fiber orientation angles, aspect ratios, stacking sequences, loading conditions and boundary conditions using the DQ method. This study contributes to the literature in this regard.

This paper aims to explore the numerical simulation of MHD flow of Williamson hybrid nanofluid over a porous stretched sheet. Cattaneo–Christov thermal and specie fluxes were used in the model. Partial differential equations are exploit to model the underlying physics of the situation (PDEs).

Using an acceptable similarity functions, these equations were changed into total differential equations (ODEs). The spectral relaxation method (SRM) was used to solve the linked and nonlinear altered ODEs. The Gauss–Seidel procedure is used to figure out how to use Chebyshev pseudospectral techniques in SRM. This is an iterative process.

Increasing the heat relaxation flow increases temperature distributions; increasing the mass relaxation flux increases concentration distributions. A higher value of thermal radiation heat generation and Eckert number was noticed to improve temperature and velocity distributions. Due to the imposed electromagnetic force, a higher magnetic field is detected to cause an elevation in the velocity distribution. Also, a higher thermal radiation is observed to upsurge the velocity in company with temperature distributions.

This research benefits from biomedical engineering, biological sciences, astrophysics and geophysics. The rheological applications of Williamson fluid finds usefulness in biological sciences. The nanoparticles as considered in this study finds applications in the field of biomedical engineering. Also, the application of the imposed electromagnetic field and magnetic field strength is very useful in the area of astrophysics. A good agreement may be found in the literature on this study’s findings.

This paper introduces a closed-form solution for analyzing the buckling behavior of orthotropic plates using a refined plate theory with four variable parameters, leveraging a new hyperbolic shear displacement model.

The proposed theory incorporates a quadratic variation of transverse shear strains across the plate’s thickness and satisfies zero traction boundary conditions on both the upper and lower surfaces without employing shear correction factors. The governing equations are derived from the principle of minimum total potential energy. Closed-form solutions for rectangular plates, with two opposite edges simply supported and the remaining two edges subjected to arbitrary boundary conditions, are obtained using the state space approach to the Levy-type solution. Comparative studies are conducted to validate the accuracy of the obtained results.

The paper successfully examines and discusses in detail the effects of boundary conditions, loading conditions, variations in modulus ratio and thickness ratio on the critical buckling load of orthotropic plates.

This study presents a novel and precise method for evaluating the buckling behavior of orthotropic plates. The refined plate theory, without the need for shear correction factors, offers significant insights and improvements in understanding the critical buckling load under various conditions, contributing valuable knowledge to the field of structural analysis.

Workflow optimisation is crucial for establishing a viable acute stroke (AS) intervention programme in a large tertiary care centre. This study aims to utilise Lean Six Sigma (LSS) principles to enhance the hospital's workflow.

The Action Research methodology was used to implement the project and develop the case study. The study took place in a large tertiary care academic hospital in India. The Define-Measure-Analyse-Improve-Control approach optimised the workflow within 6 months. Lean tools such as value stream mapping (VSM), waste audits and Gemba were utilised to identify issues involving various stakeholders in the workflow. Sigma-level calculations were used to compare baseline, improvement and sustainment status. Additionally, statistical techniques were effectively employed to draw meaningful inferences.

LSS tools and techniques can be effectively utilised in large tertiary care hospitals to optimise workflow through a structured approach. Sigma ratings of the processes showed substantial improvement, resulting in a five-fold increase in clinical outcomes. Specifically, there was a 43% improvement in outcome for patients who underwent acute stroke revascularisation. However, certain sigma ratings deteriorated during the control and extended control (sustainment) phases. This indicates that ensuring the sustainability of quality control interventions in healthcare is challenging and requires continuous auditing.

The article presents a single case study deployed in a hospital in India. Thus, the generalisation of outcomes has a significant limitation. Also, the study encounters the challenge of not having a parallel control group, which is a common limitation in quality improvement studies in healthcare. Many studies in healthcare quality improvement, including this one, are limited by minimal data on long-term follow-up and the sustainability of achieved results.

This study pioneers the integration of LSS methodologies in a large Indian tertiary care hospital, specifically targeting AS intervention. It represents the first LSS case study applied in the stroke department of any hospital in India. Whilst most case studies discuss only the positive aspects, this article fills a critical gap by unearthing the challenges of applying LSS in a complex healthcare setting, offering insights into sustainable quality improvement and operational efficiency. This case study contributes to the theoretical understanding of LSS in healthcare. It showcases its real-world impact on patient outcomes and process optimisation.

This paper aims to optimize bioconvective heat transfer for magnetohydrodynamics Eyring–Powell nanofluids containing motile microorganisms with variable viscosity and porous media in ciliated microchannels.

The flow problem is first modeled in the two-dimensional frame and then simplified under low Reynolds number and long wavelength approximations. The numerical method is used to examine the impact of thermal radiation, temperature-dependent viscosity, mixed convection, magnetic fields, Ohmic heating and porous media for velocity, temperature, concentration and motile microorganisms. Graphical results are presented to observe the impact of physical parameters on pressure rise, pressure gradient and streamlines.

It is observed that the temperature of nanofluid decreases with higher values of the viscosity parameter. It is absolutely in accordance with the physical expectation as the radiation parameter increases, the heat transfer rate at the boundary decreases. Nanoparticle concentration increases by increasing the values of bioconvection Rayleigh number. The density of motile microorganisms decreases when bioconvection Peclet number is increased. The velocity of the nanofluid decreases with higher value of Darcy number. With increase in the value of bioconvection parameter, the flow of nanofluid is increased.

The bioconvective peristaltic movement of magnetohydrodynamic nanofluid in ciliated media is proposed. The non-Newtonian behavior of the fluid is described by using an Eyring–Powell fluid model.

This article presents a numerical study of the heat transfer properties of a nanofluid created using engine oil as the common fluid and Fe3O4 nanoparticles within a square cavity embedded with porous media using the LTNE model in the presence of a Cattaneo–Christov heat flux. To obtain the governing boundary layer equations, the Boussinesq approximation and Darcy model are employed.

By applying the Finite Element method, the modeling equations for dimensionless vorticity, stream function and temperature contours with conforming boundary and initial conditions are scrutinized.

One important finding is that streamlines create a core vortex that is oriented centrally and has longer thermal relaxation times. In contrast, solid state isotherms are hardly affected by growth in thermal relaxation parameter values when compared to fluid state isotherms.

The research work carried out in this work is original and no part is copied from others.

This study aims to examine the effects of perceived product–brand fit and brand type on consumer evaluations of wearable smart masks’ technological, aesthetic and social attributes and how these affect consumers’ attitudes and intentions to use.

Through an experimental approach, a total of 240 US consumers’ evaluations of smart masks are compared according to perceived product–brand fit (high vs low) and brand type (electronics vs fashion).

The results showed that high perceived product–brand fit increases consumers’ evaluations, while brand type did not significantly affect consumers’ evaluations. Among various attributes, social acceptability had the greatest influence on consumers’ attitude and intention to use. Perceived ease of use, however, positively influenced attitude but negatively influenced intention to use.

As consumers’ interest in smart health-care wearables increases and air pollution is a serious issue across countries, research on wearable smart masks is being facilitated. Smart masks refer to the digitalized, reusable wearable masks that provide protection and health-care functions. However, their market penetration is still limited. To close this gap between smart mask technology and the market, this study examines how perceived fit and brand type can be used to enhance consumer evaluations.

This study aims to investigate the impact of brand engagement on consumer responses to brand extensions, particularly in terms of value perception, attitude and purchase intention in a masstige context. The study examines low-fit/high-functionality and high-fit/low-functionality products. It also explores the crucial role of self-congruence in enhancing brand engagement, which leads to positive consumer responses towards brand extensions.

After establishing the theoretical foundations, pre-tests identified the product types and their fit level. In this quantitative study, 464 questionnaires were administered. Confirmatory factor analysis and structural equation modelling validated the model and tested the hypotheses for low-fit/high-functionality and high-fit/low-functionality products of a masstige brand.

Data analysis shows that brand engagement positively affects value perception, attitude and purchase intention. However, consumers’ responses to brand extension differed for low-fit versus high-fit products. Moreover, social self-congruence and actual and ideal self-congruence positively impact consumers’ active engagement with masstige brands.

This research shows that low-fit extensions of masstige brands can succeed with high functionality, while high-fit extensions mitigate the negative effects of low functionality, a key attribute of masstige brands. The study adds to the limited literature on self-congruence and engagement by identifying actual and ideal self-congruence as determinants of brand engagement. It is also among the first to demonstrate that social self-congruence drives brand engagement for masstige brands.

This paper aims to present a summary of the green consumer behaviour (GCB) research conducted during the 2001–2021 period using the bibliometric analysis and to carry out a thematic and content analysis on the three clusters which comprise 57 articles resulting from the co-citation analysis and identify the significant green purchasing factors.

The three-pronged methodology applied to this research analysis includes performance analysis of the literature using biblioshiny and R Studio; network mapping analysis using VOSviewer and Gephi; thematic analysis using word clouds generated with R Software and content analysis of each paper with the aid of within and between-study analyses.

Cluster one acted as a base for the theoretical foundations of GCB which aids in understanding the basic concepts of green marketing, its evolution and the methodologies, whereas cluster two determined the predictors of everyday green behaviour, which helps in gaining knowledge about the everyday sustainable activities the consumers indulge and the factors motivating to do so. Cluster three mainly focused on the psycho-socio demographic determinants of GCB, which assists in segmentation and predicting the purchase behaviour of the various consumer segments.

The significant variables and major gaps in each of the clusters were identified and authors have drawn the implications for future researchers and marketing managers.