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This paper aims to examine the three-dimensional (3D) flow of carbon nanotubes (CNTs) due to bidirectional nonlinearly stretching surface by considering porous medium. Characteristics of both single-walled CNTs and multi-walled CNTs are discussed by considering Xue model. Darcy–Forchheimer model is used for flow saturating porous medium.

Optimal homotopy analysis method is used for the development of series solutions.

The authors deal with 3D Darcy–Forchheimer flow of CNTs over a nonlinearly stretching surface. Heat transport mechanism is discussed in the presence of Xue model. The homogeneous and heterogeneous effects are also accounted. The mathematical modeling is computed using boundary-layer approximations.

No such work has been done yet in the literature.

This paper aims to elaborate the characteristics of magneto-Maxwell nanoliquid toward moving radiated surface. Flow analysis subject to Darcy–Forchheimer concept is studied. Newtonian heat/mass conditions and heat source aspects are taken into account for modeling. Apposite transformations are introduced for non-dimensionalization process.

Optimal homotopy analysis method is implemented to compute convergent solutions of nonlinear ordinary differential equations.

Temperature field increments when thermophoresis, heat generation and Brownian movement parameters are increased, whereas reverse situation is noticed for larger Prandtl number. The results also witness that concentration distribution has opposite characteristics for larger thermophoresis and Brownian movement parameters. Furthermore, the presented analysis reduces to traditional Darcy relation in the absence of local inertia coefficient.

As per the authors’ knowledge, no such analysis has been yet reported.

This study aims to focus on second grade fluid flow over a rotating disk in the presence of chemical reaction. Uniform magnetic field is also taken into account. Because of the smaller magnetic Reynolds number, induced magnetic field is negligible. Heat equation is constructed by considering heat source/sink.

Suitable variables are used to transform nonlinear partial differential equations to ordinary ones. Convergent series solutions are attained by applying homotopy analysis method.

Trends of different parameters on concentration, velocity and temperature are shown graphically. Skin friction coefficient and local Nusselt number are calculated and investigated under the effect of elaborated parameters. An elevation in the value of magnetic field parameter causes collapse in the velocity distributions. Velocity distribution in increasing function of viscoelastic parameter. Temperature and concentration profiles are decreasing functions of viscoelastic parameter. Concentration distribution reduces by increasing the chemical reaction parameter. There is more surface drag force for larger M, while opposite behavior is noted for β.

To the best of the authors’ knowledge, such consideration is yet to be published in the literature.

Over the past few decades, the flow around circular cylinders has been one of the highly researched topics in the field of offshore engineering and fluid-structure interaction (FSI). In the current study, numerical simulations for flow around a fixed circular cylinder are performed at Reynolds number (Re) = 3900 with the LES method using the ICEM-CFD and ANSYS Fluent tool for meshing and analysis, respectively. Previously, similar studies have been conducted at the same Reynolds number, but there have been discrepancies in the results, particularly in calculating the recirculation length and angle of separation. In addition, the purpose of this study is to address the impact of time interval averaging to obtain the fully converged solution.

This study presents the LES method, using the ICEM-CFD and ANSYS fluent tool for meshing and analysis.

In the current study, turbulence statistics are sampled for 25, 50, 75 and 100 vortex-shedding cycles with the CFL value O (1). The recirculation length, angle of separation, hydrodynamic coefficients and the wake behind the cylinder are investigated up to ten diameters. The drag coefficient and Strouhal number are observed to be less sensitive, whereas the recirculation length appeared to be highly dependent on the average time statistics and the non-dimensional time step. Similarly, the mean streamwise and cross-flow velocity are observed to be sensitive to the average time statistics and non-dimensional time step in the wake region near the cylinder.

In the current investigation, turbulence statistics are sampled for 25, 50, 75 and 100 vortex-shedding cycles with the CFL value O (1), using large eddy simulation method at Re = 3900 around a circular cylinder. The impact of time interval averaging to obtain the fully converged mean flow field is addressed. No such consideration is yet published in the literature.

The purpose of this study is to investigate the impact of COVID-19 on conventional and Islamic stocks by using the data spanning from February 25, 2020, to February 3, 2021, and employing a panel regression approach.

In this study a panel regression approach has been used.

The study finds a negative association between COVID-19 and stock (both Islamic and conventional). After splitting the data into 1st and 2nd waves, the relationship between COVID-19 and stock (both Islamic and conventional) remains the same (negative) in the case of the 1st wave. In contrast, in the case of the 2nd wave, the relationship turned out to be positive. During both waves of the pandemic, the magnitude of the effect is found to be higher for conventional stocks. Additionally, the study also analyzes the aggregate influence of COVID-19 on different sectors and finds that commercial banks, oil and gas exploration and marketing companies are the most influenced sectors. At the same time, automobiles and pharma are the least affected sectors.

The study suggests that markets start gaining momentum to reach their prepandemic level after absorbing the initial shock (emergence of a pandemic). The study also provides thorough insights for market regulators and policymakers by implying the dynamic relations between markets (conventional and Islamic) and financial crisis, which would allow them more effective control of crisis in future endeavors.

This is one of the first studies to investigate the impact of COVID-19 on both conventional and Islamic stocks, especially in the context of Pakistan.

This study aims to investigate the effect of monetary policy on housing prices for US economy. It specifically examines whether nominal or real interest rates are the key drivers behind fluctuations in housing prices in US.

Monthly data from January 1991 to July 2023 and various appropriate analytical tools such as unit root tests, Johansen’s cointegration test, vector error correction model (VECM), impulse response function and Granger causality test were applied for the data analysis.

The Johansen cointegration findings reveal the presence of a long-term relationship among the variables. VECM results indicate a negative correlation between nominal and real interest rates and housing prices in both the short and long terms, suggesting that a strict monetary policy can help in controlling the housing price increase in the USA. However, housing prices are more responsive to changes in nominal interest rates than to real interest rates. Additionally, the study reveals that the COVID-19 pandemic contributed to the upsurge in housing prices in the USA.

This study contributes by examining the role that nominal or real interest rates play in shaping housing prices in the USA. Moreover, given the recent significant upsurge in housing prices, this study presents a unique opportunity to investigate whether these price increases are influenced by the Federal Reserve's monetary policy decisions regarding nominal or real interest rates. Additionally, using monthly data, this study provides a deeper understanding of the fluctuations in housing prices and their connection to monetary policy tools.

This study aims to explore empirically the impact of various factors/determinants on housing prices at the country level as well as in Lahore, the most populous metropolitan city of the most populous province Punjab, Pakistan.

This study uses monthly data ranging from 2013M1 to 2020M1 on variables used in the study. Based on the stationarity results, the method of robust least square is used as an estimation technique. The validity of initial results is also authenticated by canonical cointegration regression.

The empirical result reveals that all included variables significantly affect housing prices both at country level as well as in Lahore. This study found negative impact of regressor age, real exchange rate and urbanization on housing prices, whereas the positive impact of gross domestic product (GDP) per capita, foreign remittances, broad money and real interest rate on housing prices in the case of Pakistan was found. On the other hand, results unveiled the negative impact of regressor age (proportion of population aged between 15 and 64), real exchange rate and urbanization on housing prices, whereas the positive impact of GDP per capita, foreign remittances, broad money and real interest rate on housing prices in Lahore metropolitan city was unveiled.

Based on the extant literature survey, this is a more holistic study of its kind that uncovers the macroeconomic determinants by considering the demand side, supply side and demographic factors of escalated housing prices in Pakistan, so that proper policies can be adopted to keep the housing sector stable. Empirical findings are helpful to acquire an enhanced understanding of how the housing price is determined and form a base for government to tackle the housing affordability problem.

This study aims to investigate the effect of the wall thickness, deposition orientation and two different post-processing methods on the local mechanical properties and microstructure of additively manufactured parts made of maraging steel. In order to examine the local properties of the build, miniaturized testing specimens were employed. Before application of small-sized specimens, their performance was verified.

The investigation was composed of two stages. As first, the part thickness, specimen size and orientation were studied on a laser-powder bed fusion (L-PBF) platform with deposited walls of various thicknesses made of maraging steel. Subsequently, the influence of different heat-treatment methods was investigated on the final product, i.e. impellers. The miniaturized and standard tensile tests were performed to investigate the local mechanical properties. The porosity, microstructures and fracture surfaces were analysed by X-ray-computed tomography, X-ray diffraction and scanning electron microscopy with electron backscatter diffraction.

The results revealed good agreement between the values provided by miniaturized and standard specimens. The thinnest parts produced had the largest pores and the highest scatter of elongation values. In these cases, also the sub-contour porosity was observed. Part thickness affected pores’ size and results repeatability but not total porosity. The two-step heat-treatment (solutionizing and age-hardening) exhibited the highest yield and ultimate tensile strength.

The microstructure and local mechanical properties were studied on L-PBF platform with deposited walls of various thicknesses. Subsequently, a detailed analysis was conducted on real components (impellers) made of maraging steel, commonly used in tooling, automotive and aerospace industries.

The broadly understood quality of manufactured parts is crucial for their reliable and long-lasting operation. The findings presented in the manuscript allow the readers better understanding of the connection between deposition parameters, post-processing, microstructure and mechanical performance of additive manufacturing-processed parts.

In this work, we estimated the different entropies like Shannon entropy, Rényi divergences, Csiszár divergence by using Jensen’s type functionals. The Zipf’s–Mandelbrot law and hybrid Zipf’s–Mandelbrot law are used to estimate the Shannon entropy. The Abel–Gontscharoff Green functions and Fink’s Identity are used to construct new inequalities and generalized them for m-convex function.

Using three theoretical lenses − organismic integration theory (OIT), theory of values-belief-norm (VBN) and gender schema theory (GST) − this study aims to examine the effect of environmental factors (environmental attitude, environmental concerns, perceived environmental responsibility and peer influence) on consumers' intentions to purchase eco-friendly athletic wear.

A sample of n = 380 Pakistani consumers was used to test hypothesized relationships. Data were analyzed through the partial least square structural equation modeling (PLS-SEM) technique using SmartPLS version 3.3.3.

Findings suggest that environmental attitude, environmental concerns, perceived environmental responsibility and peer influence are positively associated with green purchase behavior. The moderating effects of individual green values were found statistically significant between peer influence and green purchase behavior. The data further revealed that the effect of environmental attitude, environmental concerns, peer influence and perceived environmental responsibility on green purchase behavior varies across the gender.

This research is one of the first attempts to explore the effect of environmental motivational factors on consumers' intentions to purchase eco-friendly athletic wear using theories of OIT, VBN and GST. This study employs advanced analytical methods to perform multi-group analysis and establish the predictive relevance of the model, using PLS-SEM in sports management and marketing context.