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This paper aims to evaluate the effect of consumption of a high-fat diet (HFD) rich with total saturated fats on adiposity and serum levels of vascular cell adhesion molecule (sVCAM-1), a biomarker of endothelial inflammation/dysfunction. Another aim is to evaluate whether supplementation of a phytosomal formulation of curcumin would reduce adiposity measures and sVCAM-1 levels in HFD rats.

The study was conducted on 17 male rats which were allocated to one of three feeding regimen groups: normal diet (ND); HFD, or HFD with dietary phytosomal curcumin (HFD-C). Anthropometric measures were recorded weekly up to 20 weeks of feeding intervention, at the end of which, sVCAM-1 levels were also compared with one-way ANOVA and Tukey post-hoc analysis.

The HFD group had the greatest values for raw anthropometric data, and there was a group difference in anthropometric measures, however there was no significant difference between HFD and HFD-C for any measure. The gain at 20 weeks from initial values did reveal significant differences in weight and abdominal circumference between HFD and HFD-C groups. There were significant group differences in sVCAM-1 levels, with only HFD-C displaying significant lower levels than HFD group.

This is the first study that shows the capacity of a phytosomal formulation of curcumin in reducing adiposity and sVCAM-1 levels during daily intake of saturated fats above the recommended level. The results are promising in that this formulation can protect against endothelial inflammation/dysfunction, and can be used as complimentary therapy to suppress dyslipidemia/obesity-related cardiovascular complications.

Organizational culture is a determinant for quality improvement. This paper aims to assess organizational culture in a hospital setting, understand its relationship with perceptions about quality of care and identify areas for improvement.

The paper is based on a cross‐sectional survey in a large clinical department that used two validated questionnaires. The first contained 20 items addressing perceptions of cultural typology (64 respondents). The second one assessed staff views on quality improvement implementation (48 faculty) in three domains: leadership, information and analysis and human resource utilization (employee satisfaction).

All four cultural types received scoring, from a mean of 17.5 (group), 13.7 (developmental), 31.2 (rational) to 37.2 (hierarchical). The latter was the dominant cultural type. Group (participatory) and developmental (open) culture types had significant positive correlation with optimistic perceptions about leadership (r=0.48 and 0.55 respectively, p<0.00). Hierarchical (bureaucratic) culture was significantly negatively correlated with domains; leadership (r=−0.61, p<0.00), information and analysis (−0.50, p<0.00) and employee satisfaction (r=−0.55, p<0.00). Responses reveal a need for leadership to better utilize suggestions for improving quality of care, strengthening the process of information analysis and encouraging reward and recognition for employees.

It is likely that, by adopting a participatory and open culture, staff views about organizational leadership will improve and employee satisfaction will be enhanced. This finding has implications for quality care implementation in other hospital settings.

The paper bridges an important gap in the literature by addressing the relationship between culture and quality care perceptions in a Pakistani hospital. As such a new and informative perspective is added.

Corruption and money laundering (ML) are severe concerns for both developing and developed countries. According to international organizations, such as Transparency International, the Basel Institute on Governance and the International Country Risk Guide, corruption and ML exist in every country. This research aims to investigate the impact of corruption and ML on the loan portfolio quality of banks.

From 2013 to 2019, this study used the panel data of 132 countries, including 87 highly corrupt and 45 least corrupt countries: the fixed effect and random effect econometric regression techniques for data analysis. Additionally, this study used the generalized methods of moment technique to check the result’s robustness.

This study shows that corruption and ML have diverse relationships with non-performing loans in highly corrupt and low corrupt countries. It is potentially because of the differences in the regulatory structure of a highly corrupt and least corrupt environment.

To the best of the authors’ knowledge, this study is the first attempt that provides a unique perspective on corruption, ML and its effect on the loan’s portfolio quality of banks. Furthermore, this study suggests that governments in highly corrupt environments develop robust anti-corruption and anti-ML regulations.

This paper aims to offer a wider examination of the research concerning entrepreneurship characteristics in the Middle East and North Africa (MENA) region via a review of recent studies relevant to this topic. Research publications concerning entrepreneurship within the MENA region evidence growing interest in this field of study, with the potential to boost and drive future economic development and growth. This focus within entrepreneurship research is because of the economic development in the region, which is becoming increasingly important for policymakers and businesses.

The author performed a systematic literature review to produce robust information about entrepreneurship in the MENA region, followed by a thematic analysis to identify key research themes within each category.

Despite the growth in entrepreneurship research in the MENA region, research on certain factors is lacking. An analysis of 271 studies published between 2009 and 2019 identifies 9 main research categories, within which 30 themes have attracted significant academic attention. Female entrepreneurship and gender, youth entrepreneurship and entrepreneurship behaviour and orientation are the three key categories influencing perspectives on entrepreneurship in the MENA region. This study highlights research gaps and provides recommendations to guide future research on the sustainable development of entrepreneurship in the MENA region.

This paper highlights trends in entrepreneurship research amongst scholars within the MENA region and suggests paths for future research efforts.

Most conventional financial products currently on offer to Muslims in the Indian market are incompatible with Islamic religious principles; there is a recognized demand for alternatives within this niche community. India has the third largest Muslim population in the world – 155,477,386 in 2011. The purpose of this paper is to present the status of marketing activities of Shari'ah‐based investments and a comprehensive analysis of avenues for Islamic investments in India.

In India, Islamic investment is gathering pace as Muslims in the country are becoming more vocal in their demands for greater self expression. Hence, there is a great potential in India itself. Even if a small percentage of this population can be pressured to invest in the Islamic investments, the amount of money that can be brought into the system could be enormous.

The findings reveal the emergence of Islamic investment opportunities on Shari'ah‐based investments in India. This paper also provides suggestions for enhancement of Islamic investment opportunities in India.

With a sound economic base and with hundreds of companies complying with Shari'ah norms, India offers a huge opportunity for Islamic equity investment. If performance as a parameter is considered, it is observed that Shari'ah‐compliant investments, being low in debt and having sound fundamental principles, tend to perform better, hence large non‐Muslim investors should take the benefit of these socially responsible and above par performing Islamic investments.

India's engagement with Afghanistan readily became multi-dimensional after the defeat of the Taliban and the installation of an Interim Authority in 2001. This was reflected in an immediate upgradation of Indian representation in Afghanistan from Liaison Office to full-fledged Embassy in 2002. India actively participated in the Bonn Conference and was instrumental in the emergence of post-Taliban governing and political authority in Afghanistan. Since then, India's main focus has been to support the Afghan government and the political process in the country as mandated under the Bonn agreement of 2001. It has continued to pursue a policy of high-level engagement with Afghanistan through extensive and wide-ranging humanitarian, financial, and project assistance, and participation in international efforts aimed at political reconciliation and economic rebuilding of Afghanistan.

Intellectual capital (IC) plays a pivotal role in the high-tech and knowledge-based economic sectors. With the emergence of FinTech, which, with respect to the banking sector, is merging high-tech with the k-economy, there is an emerging need to highlight the importance and understand the dynamics of bank IC. With respect to Gulf Cooperation Council (GCC) economies, where FinTech has become de rigueur, banking is bifurcated into Islamic and banking sectors. Through comparative empirical analysis, the purpose of this paper is to examine IC efficiency in Islamic and conventional banks with a view to elucidating the impact of IC, in aggregate and decomposed into its components, on an operational, financial and market performance of Islamic banks juxtaposed with conventional banks.

Using data collected from 59 banks for five years (2012-2016) involving 295 observations, an independent variable derived from the modified value added IC (MVAIC) components are regressed against dependent bank performance indicator variables [Return on Assets (ROA), Return on Equity (ROE) and Tobin’s Q (TQ)]. Two types of control variables complete the regression analysis in this study: bank-specific and macroeconomic.

The findings elicited from the empirical results demonstrate that there is positive relationship between IC efficiency and financial performance (ROE) and market performance (TQ) in Islamic banks. In conventional banks, however, there is a positive relationship between IC and operational performance (ROE) and financial performance (ROE).

The model in this paper presents a valuable analytical framework for exploring IC efficiency as a driver of performance in dual-sector banking economies characterized by co-existence of Islamic and conventional financial institutions. In addition, this paper highlights bank management lacunae manifesting in terms of the weak nexus between: IC and asset efficiency (ROA) in Islamic banks and IC and market value (TQ) in conventional banks.

Earned value management (EVM)–based models for estimating project actual duration (AD) and cost at completion using various methods are continuously developed to improve the accuracy and actualization of predicted values. This study primarily aimed to examine natural gradient boosting (NGBoost-2020) with the classification and regression trees (CART) base model (base learner). To the best of the authors' knowledge, this concept has never been applied to EVM AD forecasting problem. Consequently, the authors compared this method to the single K-nearest neighbor (KNN) method, the ensemble method of extreme gradient boosting (XGBoost-2016) with the CART base model and the optimal equation of EVM, the earned schedule (ES) equation with the performance factor equal to 1 (ES1). The paper also sought to determine the extent to which the World Bank's two legal factors affect countries and how the two legal causes of delay (related to institutional flaws) influence AD prediction models.

In this paper, data from 30 construction projects of various building types in Iran, Pakistan, India, Turkey, Malaysia and Nigeria (due to the high number of delayed projects and the detrimental effects of these delays in these countries) were used to develop three models. The target variable of the models was a dimensionless output, the ratio of estimated duration to completion (ETC(t)) to planned duration (PD). Furthermore, 426 tracking periods were used to build the three models, with 353 samples and 23 projects in the training set, 73 patterns (17% of the total) and six projects (21% of the total) in the testing set. Furthermore, 17 dimensionless input variables were used, including ten variables based on the main variables and performance indices of EVM and several other variables detailed in the study. The three models were subsequently created using Python and several GitHub-hosted codes.

For the testing set of the optimal model (NGBoost), the better percentage mean (better%) of the prediction error (based on projects with a lower error percentage) of the NGBoost compared to two KNN and ES1 single models, as well as the total mean absolute percentage error (MAPE) and mean lags (MeLa) (indicating model stability) were 100, 83.33, 5.62 and 3.17%, respectively. Notably, the total MAPE and MeLa for the NGBoost model testing set, which had ten EVM-based input variables, were 6.74 and 5.20%, respectively. The ensemble artificial intelligence (AI) models exhibited a much lower MAPE than ES1. Additionally, ES1 was less stable in prediction than NGBoost. The possibility of excessive and unusual MAPE and MeLa values occurred only in the two single models. However, on some data sets, ES1 outperformed AI models. NGBoost also outperformed other models, especially single models for most developing countries, and was more accurate than previously presented optimized models. In addition, sensitivity analysis was conducted on the NGBoost predicted outputs of 30 projects using the SHapley Additive exPlanations (SHAP) method. All variables demonstrated an effect on ETC(t)/PD. The results revealed that the most influential input variables in order of importance were actual time (AT) to PD, regulatory quality (RQ), earned duration (ED) to PD, schedule cost index (SCI), planned complete percentage, rule of law (RL), actual complete percentage (ACP) and ETC(t) of the ES optimal equation to PD. The probabilistic hybrid model was selected based on the outputs predicted by the NGBoost and XGBoost models and the MAPE values from three AI models. The 95% prediction interval of the NGBoost–XGBoost model revealed that 96.10 and 98.60% of the actual output values of the testing and training sets are within this interval, respectively.

Due to the use of projects performed in different countries, it was not possible to distribute the questionnaire to the managers and stakeholders of 30 projects in six developing countries. Due to the low number of EVM-based projects in various references, it was unfeasible to utilize other types of projects. Future prospects include evaluating the accuracy and stability of NGBoost for timely and non-fluctuating projects (mostly in developed countries), considering a greater number of legal/institutional variables as input, using legal/institutional/internal/inflation inputs for complex projects with extremely high uncertainty (such as bridge and road construction) and integrating these inputs and NGBoost with new technologies (such as blockchain, radio frequency identification (RFID) systems, building information modeling (BIM) and Internet of things (IoT)).

The legal/intuitive recommendations made to governments are strict control of prices, adequate supervision, removal of additional rules, removal of unfair regulations, clarification of the future trend of a law change, strict monitoring of property rights, simplification of the processes for obtaining permits and elimination of unnecessary changes particularly in developing countries and at the onset of irregular projects with limited information and numerous uncertainties. Furthermore, the managers and stakeholders of this group of projects were informed of the significance of seven construction variables (institutional/legal external risks, internal factors and inflation) at an early stage, using time series (dynamic) models to predict AD, accurate calculation of progress percentage variables, the effectiveness of building type in non-residential projects, regular updating inflation during implementation, effectiveness of employer type in the early stage of public projects in addition to the late stage of private projects, and allocating reserve duration (buffer) in order to respond to institutional/legal risks.

Ensemble methods were optimized in 70% of references. To the authors' knowledge, NGBoost from the set of ensemble methods was not used to estimate construction project duration and delays. NGBoost is an effective method for considering uncertainties in irregular projects and is often implemented in developing countries. Furthermore, AD estimation models do fail to incorporate RQ and RL from the World Bank's worldwide governance indicators (WGI) as risk-based inputs. In addition, the various WGI, EVM and inflation variables are not combined with substantial degrees of delay institutional risks as inputs. Consequently, due to the existence of critical and complex risks in different countries, it is vital to consider legal and institutional factors. This is especially recommended if an in-depth, accurate and reality-based method like SHAP is used for analysis.

In the present study, the thermal performance of engine radiator using conventional coolant and nanofluid is determined experimentally for the different flow rates. Further, the study implemented the Integrated Taguchi-GRA-PCA for optimising the heat transfer performance.

Nanofluids were prepared by taking ethylene glycol and water (25:75 by volume) with volume fraction of 0.01, 0.03 and 0.05% of TiO₂ nanopowder. Experimental Data were collected based on the design of experiments (DOE) L9 orthogonal array using Taguchi method. Statistical analysis via Grey relation analysis (GRA) and principal component analysis (PCA) were done to determine the role of experimental parameters on heat transfer coefficient and rate of heat transfer. Impact of three control factors, vol. % of TiO₂ concentration (φ), flow rate (LPH), and sonication time (min) on the performance characteristics on heat transfer coefficient and ratio of heat transfer rate is analysed to get the best combination of the parameters involved.

Analysis revealed the importance of parameters on heat transfer coefficient and can be sorted in terms of contributions from higher to lower degree. Finally, ANOVA test has been conducted to validate the effect of process parameters. The major controllable parameter is φ (concentration), contributing about 32.74%, then flow rate contributing 32.5% and finally sonication time showing small contribution of 18.57%.

A grey relational analysis integrated with principal component analyses (PCA) are implemented to get the optimum heat transfer coefficient and ratio of heat transfer rate. The novelty of the work is to adopt and implement the Integrated Taguchi-GRA-PCA first time for the purpose of thermal performance analysis of engine nano-coolant for radiator.

The purpose of this study is to introduce new tools to develop a more precise and focused bibliometric analysis on the field of digitalization in healthcare management. Furthermore, this study aims to provide an overview of the existing resources in healthcare management and education and other developing interdisciplinary fields.

This work uses bibliometric analysis to conduct a comprehensive review to map the use of the unified theory of acceptance and use of technology (UTAUT) and the unified theory of acceptance and use of technology 2 (UTAUT2) research models in healthcare academic studies. Bibliometric studies are considered an important tool to evaluate research studies and to gain a comprehensive view of the state of the art.

Although UTAUT dates to 2003, our bibliometric analysis reveals that only since 2016 has the model, together with UTAUT2 (2012), had relevant application in the literature. Nonetheless, studies have shown that UTAUT and UTAUT2 are particularly suitable for understanding the reasons that underlie the adoption and non-adoption choices of eHealth services. Further, this study highlights the lack of a multidisciplinary approach in the implementation of eHealth services. Equally significant is the fact that many studies have focused on the acceptance and the adoption of eHealth services by end users, whereas very few have focused on the level of acceptance of healthcare professionals.

To the best of the authors’ knowledge, this is the first study to conduct a bibliometric analysis of technology acceptance and adoption by using advanced tools that were conceived specifically for this purpose. In addition, the examination was not limited to a certain era and aimed to give a worldwide overview of eHealth service acceptance and adoption.