Search results

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-Fe₃O₄ hybrid 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 adopts a qualitative approach to a critical media analysis of the multifaceted aspects of child marriage in the Yemeni context as an example of the broader Arab context. It seeks to provide a deeper understanding of the current situation, underlying causes and consequences of child marriage, as well as efforts to curb the practice.

This study utilizes a thematic analysis approach, examining various textual and multimodal sources on child marriage. A corpus of Arab media, including news and opinion articles, online discussions and public comments, was compiled and analyzed. Additionally, sentiment analysis techniques were employed to examine a YouTube report about Nujood Ali, a victim of child marriage in Yemen, to gauge the emotional tone and attitudes of viewers towards the media coverage and the practice itself.

This study identifies prevalent themes, narratives and perspectives related to child marriage in Yemen, highlighting the diverse journalism genres addressing the issue. The thematic analysis of the media corpus reveals several themes that align with findings from other studies, particularly those discussing the practice, its causes and its prevalence. The sentiment analysis of a YouTube report on Nujood Ali reveals significant insights into the public’s emotional response and attitude towards child marriage.

This study is limited to the content available in the compiled corpus and the specific methodologies employed, including thematic and sentiment analysis. These limitations might influence the generalizability of the findings.

This study is distinctive in its comprehensive and multidisciplinary approach to examining child marriage in Yemen and the broader Arab context. It employs a selection of digital humanities software to attempt a systematic, critical media analysis on child marriage in Yemen. Thematic analysis has uncovered unique insights, such as the inadvertent consequences of legislation intended to protect children, which have instead exacerbated the problem. In addition, the media has highlighted the negative role played by some religious scholars in Yemeni Parliament. These scholars have used their political power and immunity to obstruct efforts to end the practice, either directly or by mobilizing their supporters. A sentiment analysis of YouTube comments clearly indicates that the practice of child marriage is not widely accepted within the Yemeni community, despite some perceptions to the contrary.

Recycled aggregate self-compacting concrete (RASCC) has the potential for sustainable resource utilization and has been widely applied. Predicting the compressive strength (CS) of RASCC is challenging due to its complex composite nature and nonlinear behavior.

This study comprehensively evaluated commonly used machine learning (ML) techniques, including artificial neural networks (ANN), random trees (RT), bagging and random forests (RF) for predicting the CS of RASCC. The results indicate that RF and ANN models typically have advantages with higher R2 values, lower root mean square error (RMSE), mean square error (MSE) and mean absolute error (MAE) values.

The combination of ML and Shapley additive explanation (SHAP) interpretable algorithms provides physical rationality, allowing engineers to adjust the proportion based on parameter analysis to predict and design RASCC. The sensitivity analysis of the ML model indicates that ANN’s interpretation ability is weaker than tree-based algorithms (RT, BG and RF). ML regression technology has high accuracy, good interpretability and great potential for predicting the CS of RASCC.

ML regression technology has high accuracy, good interpretability and great potential for predicting the CS of RASCC.

In this paper, the heterogeneity of the linkages among financial development, productivity and growth across income groups is emphasized.

An empirical analysis is conducted with an illustrative sample of 130 economies over the period 1991–2019 and classified into four subsamples: Organisation for Economic Co-operation and Development (OECD), developing, least developed and net food importing developing countries. Forecast error variance decompositions and panel vector auto-regressive estimations are computed, with insightful findings.

Higher levels of output stimulate the economic development in the agricultural sector, mainly via the productivity channel and, in the most developed economies, also through access to credit. Differently, in developing and least developed economies, the role of access to credit is marginal. The findings have practical implications for stakeholders involved in the planning of long-run investments. In less developed economies, priorities should be given to investments in technology and innovation, whereas financial markets are more suited to boost the development of the agricultural sector of developed economies.

The authors conclude on the credit–output–productivity nexus and contribute to the literature in (at least) three ways. First, they assess how credit access, agricultural output and agricultural productivity are jointly determined. Second, they use a novel approach, which departs from most of the case studies based on single-country data. Third, they conclude on potential causality links to conclude on policy implications.

The purpose of this paper, a critical reflection, is twofold. First, by comprehensively reviewing scale development procedures in hospitality research, a concerning lack of nomological validity testing is demonstrated. Second, the need for nomological validity testing is discussed and both conceptually and empirically reasoned.

This research systematically reviews scale development studies in three leading hospitality journals, including Cornell Hospitality Quarterly, International Journal of Contemporary Hospitality Management and International Journal of Hospitality Management over ten years (2012–2021) to analyze the completeness of scale development procedures. Specifically, the authors evaluate whether the reviewed studies engage in testing the nomological and predictive validity of the newly developed measures.

The results indicate a concerning gap in the current practices in hospitality research. Specifically, only 33.3% of the examined studies assess nomological validity. These findings collectively underscore the need for improving the comprehensiveness of scale development processes in hospitality research.

The study offers important implications for hospitality researchers. The paper provides an extensive discussion on the importance and benefits of testing for nomological validity in scale development studies, contributing to the completeness and consistency of scale development procedures in the hospitality discipline.

This research critically assesses prevalent, and widely accepted, scale development procedures in hospitality research. This research empirically demonstrates the neglect of nomological validity issues in scale development practices in hospitality research. Scale development is an essential scientific practice used to create a research instrument in a field of study, improving our understanding of a specific phenomenon and contributing to knowledge creation. Considering the significance of scale development in advancing the field of hospitality research, the validation procedures involved in the scale development processes are of utmost importance and should be thoroughly applied.

The aim of this study is to conduct an in-depth exploration of the research landscape concerning the impact of social determinants of health (SDH) on the health outcomes of international migrants.

Leveraging the extensive Scopus database, this study retrieved a total of 2,255 articles spanning the years 1993–2023. The framework for analysis used the SDH categories outlined by the World Health Organization.

The research landscape exhibited an apparent increase in the number of publications, but not a net increase in the research productivity. The USA emerged as the leading contributor to research output, with the Journal of Immigrant and Minority Health emerging as the most prolific publication venue, and the University of Toronto ranking as the most prolific institution. The SDH category that received the highest number of publications was the “community and social context”. Migrants from different regions in Asia (East, Central and South Asia) and those from Latin America and the Caribbean region appeared to be the most commonly researched. Highly cited articles predominantly delved into mental health outcomes arising from discrimination and migration policies.

The findings proffer valuable insights for shaping future research endeavors, accentuating the imperative for diversified studies encompassing underrepresented domains, broader health outcomes and the inclusion of migrant populations from different world regions in investigative pursuits.

This study delivers a comprehensive analysis of the research landscape, unveiling critical trends in the realm of SDH and migrant health outcomes.

The impact of government expenditure on economic performance has been a topic of discussion at both the sectoral and aggregate national levels. Despite its theoretical importance, evidence from literature indicates that this relationship has not been universally accepted across different countries and sectors. Given the significance of agriculture in African economies, particularly in Ghana, and the role of government in this sector, this study examines the impact of government expenditure on agricultural productivity in Ghana from 2000Q1 to 2022Q4.

Specification of the model was done based on the Autoregressive Distributed Lag (ARDL) cointegration bound test approach.

The results revealed that the studied variables cointegrated in the long run. Government expenditure was found to induce agriculture production both for the long run and short run within the period of the study, implying that government expenditure matters in inducing agriculture productivity in Ghana.

The study employed the ARDL methodology to investigate government expenditure and agriculture production contagion in Ghana, which has been specifically overlooked by previous studies. It is suggested that the Government of Ghana as well as others in similar environment should increase investment into the agriculture to boost the productivity of the sector.

The purpose of this study was to explore the perceptions of internally displaced persons regarding their experiences with various human rights prescripts. This study also sought to contribute to the literature on the living conditions of internally displaced persons and narrow the gap in internal displacement studies, particularly in sub-Saharan Africa.

A case study approach and quantitative research paradigm were adopted in the study. A questionnaire was used to collect data from 584 participants in Niger State, Edo State and Kaduna State in Nigeria.

The findings reveal that most of the internally displaced persons were youth, unemployed and had a strong motivation to meet their physiological needs. The empirical evidence in this study leads to the conclusion that the daily struggle of the participants to meet their survival needs overshadows every other human rights consideration among them.

Various practical and theoretical implications are inferred from this study including the imperative to urgently address the causes of internal displacement and provide urgent assistance to internally displaced persons.

Besides the novel conceptual insights and empirical data, this study makes unique contributions to literature on internally displaced persons and human rights theory.

The emergence of distributed ledger technology (DLT) has transformed the way construction industries approach data management, ushering in an era of increased transparency, security and efficiency. The purpose of this study is to investigate the strategies to promote the adoption of DLT in the Nigerian construction sector. This was done to address the challenges that hinder the widespread adoption of DLT within the Nigerian construction sector.

A comprehensive literature review informed the design of a structured questionnaire for data collection. The questionnaire was distributed among diverse construction professionals to explore their perceptions of potential strategies. The collected data were analyzed using the Shapiro–Wilk test for data distribution, while mean values and standard deviations were used to facilitate the ranking of strategies. The Kruskal–Wallis H-test was used to assess opinion differences, and exploratory factor analysis was applied to uncover underlying dimensions.

The findings revealed the top five strategies for DLT adoption as conducting workshops and seminars to educate professionals, collaborating with universities for DLT courses, encouraging joint projects for shared insights, forming consortia for DLT standards and allocating funding for DLT research in construction. Through factor analysis, the strategies identified were categorized into four principal clusters: awareness and education advancements, government support and incentives, industry collaboration and standards and pilot projects and demonstrations.

While prior studies have identified barriers to DLT adoption and offering recommendations, this research advances the field by empirically investigating and assessing several of these strategies proposed in various studies. This approach provides valuable insights that go beyond existing research, offering a deeper understanding of the practical and contextual dynamics influencing DLT adoption in the construction sector.