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This study evaluates machine learning (ML) classifiers for diagnosing Parkinson’s disease (PD) using subcortical brain region data from 3D T1 magnetic resonance imaging (MRI) Parkinson’s Progression Markers Initiative (PPMI database). We aim to identify top-performing algorithms and assess gender-related differences in accuracy.

Multiple ML algorithms will be compared for their ability to classify PD vs healthy controls using MRI scans of the brain structures like the putamen, thalamus, brainstem, accumbens, amygdala, caudate, hippocampus and pallidum. Analysis will include gender-specific performance comparisons.

The study reveals that ML classifier performance in diagnosing PD varies across subcortical brain regions and shows gender differences. The Extra Trees classifier performed best in men (86.36% accuracy in the putamen), while Naive Bayes performed best in women (69.23%, amygdala). Regions like the accumbens, hippocampus and caudate showed moderate accuracy (65–70%) in men and poor performance in women. The results point out a significant gender-based performance gap, highlighting the need for gender-specific models to improve diagnostic precision across complex brain structures.

This study highlights the significant impact of gender on machine learning diagnosis of PD using data from subcortical brain regions. Our novel focus on these regions uncovers their diagnostic potential, improves model accuracy and emphasizes the need for gender-specific approaches in medical AI. This work could ultimately lead to earlier PD detection and more personalized treatment.

COVID-19 has alerted all stakeholders to the serious challenges of biothreats to humanity and its progress. Tourism as a business has been one of the worst sufferers from the COVID-19 impacts and has been held responsible to an extent for the spread of the virus. The ‘containment, isolation, and restrictions’ of biosafety and biosecurity measures exposed the vulnerability of the tourism industry. The densely populated urban areas in India can always be hot spots for the spread of biovectors from similar biothreats in the future, with a more significant threat to employment from mitigation measures. This theoretical paper combines research from medical science, biology, tourism, and other related areas to develop a thesis that social scientists can add value in designing socially acceptable measures for scientific solutions recommended by experts from medical and other related fields. The general environment of health and hygiene in India needs to be made safer for its population and tourists as a first-level strategy to reduce the risks of biothreats. The next level strategy shall be dominated by science to suggest mitigation measures with parallel action by tourism stakeholders for a socially acceptable face of safety measures.

For close to two decades, the West African Monetary Zone (WAMZ) has been preparing to launch a second monetary union within the ECOWAS region. This study aims to determine the impact such a unionised monetary regime will have on financial stability as represented by the nonperforming loan ratios of Ghana in a counterfactual framework.

This study models nonperforming loan ratios as dependent on the monetary policy rate and the business cycle. The study then used historical data to estimate the parameters of the nonperforming loan ratio response function using an Autoregressive Distributed Lag (ARDL) approach. The estimated parameters are further used to estimate the impact of several counterfactual unionised monetary policy rates on the nonperforming loan ratios and its volatility of Ghana. As robustness check, the Least Absolute Shrinkage Selection Operator (LASSO) regression is also used to estimate the nonperforming loan ratios response function and to predict nonperforming loans under the counterfactual unionised monetary policy rates.

The results of the counterfactual study reveals that the apparent cost of monetary unification is much less than supposed with a monetary union likely to dampen volatility in non-performing loans in Ghana. As such, the WAMZ members should increase the pace towards monetary unification.

The paper contributes to the existing literature by explicitly modelling nonperforming loan ratios as dependent on monetary policy and the business cycle. The study also settles the debate on the financial stability cost of a monetary union due to the nonalignment of business cycles and economic structures.

The study aims to appraise the impact of service quality dimensions on user satisfaction in Bangladeshi public university libraries using structural equation modeling (SEM).

This study developed an SEM method based on SERVQUAL, LibQUAL+ and SERVPERF instruments, including 30 items under five service quality dimensions and eight satisfaction items with the 7-point Likert scale to appraise the impact of library service quality dimensions on user satisfaction. For this purpose, a survey was carried out among 437 students, 52 MPhil/PhD researchers and 32 teachers of the nine selected public university libraries of Bangladesh through a structured questionnaire. The SEM approach included path analysis, confirmatory and exploratory factor analysis, as well as construct reliability and validity where user satisfaction was used as the dependent variable, and five service quality dimensions were applied as independent variables.

This model was identified as significant and clarified 58% of the total variation in user satisfaction. The study findings indicated that resources of the libraries, staff competence, demeanor approach and tangible facilities of the public university libraries have a significant impact on user satisfaction.

An initiative has been taken for the first time to ascertain the impact of library service quality on user satisfaction applying the SEM approach in Bangladesh. Moreover, it creates an avenue to prompt future studies on the structural relationship between user satisfaction and service quality dimensions in academic libraries globally.

Recognising the significance of international trade in economic growth, this research explores the drivers of exports in South Asian Association for Regional Cooperation countries from 2008 to 2021. The study employs the export demand model and the augmented exports supply model and utilises pooled time-series data. This study questions whether export supply decisions are based on traditional trade model factors, emerging trading realities or macroeconomic variables. The model based on fixed effects evaluates the connection between exports and their possible drivers. Traditional export supply models suggest determinants like production capacity, variable cost and relative pricing influencing South Asian export supply performance substantially. Changes in trade, for example, have a substantial impact on export supply, demonstrating that the trade liberalisation procedure promotes growth in exports, compression in imports and technological advancement. The worsening state of the energy industry and growing levels of corruption have proved to be significant deterrents to export supply decisions. The results verify foreign direct investment's positive and medium influence on the expansion of exports. Other variables, however, such as GDP and its growth, Official Development Assistance (ODA), development expenditure, indirect taxation, labour supply and the exchange rate of currencies, have a positive impact on the flow of exports. Furthermore, the data corroborate the notion that increased savings have a significant beneficial influence on the flow of exports. The study proposes that concerned governments examine their export policies and adopt new policies adapted in accordance with changing circumstances with the goal of increasing and enhancing the performance of exports.

The study explored various dimensions of overconfidence bias (OB) among retail investors in Indian financial markets. Further, these dimensions were validated through formative assessments for OB.

The study applied exploratory factor analysis (EFA) to 764 respondents to explore dimensions of OB. These were validated with formative assessments on 489 respondents by the partial least square path modeling (PLS-PM) approach in SmartPLS 4.0 software.

The major findings of EFA explored four dimensions for OB, i.e. accuracy, perceived control, positive illusions and past investment success. The formative assessments revealed that positive illusions followed by past investment success among retail investors played an instrumental role in orchestrating the OBs that affect investment decisions in financial markets.

The formative index of OB has several practical implications for registered financial and investment advisors, bank advisors, business media companies and portfolio managers, besides individual investors in the domain of behavioral finance.

This research provides a novel approach to provide a formative index of OB with four dimensions. This formative index can acts as an overview for upcoming researchers to investigate the OB of retail individual investors.

1. Overconfidence bias is an important predictor of retail investors' behavior

2. Formative dimensions of the overconfidence bias index.

3. Accuracy, perceived control, positive illusions and past investment success are important dimensions of overconfidence bias.

4. Modern portfolio theory and illusion of control theory support this study.

Overconfidence bias is an important predictor of retail investors' behavior

Formative dimensions of the overconfidence bias index.

Accuracy, perceived control, positive illusions and past investment success are important dimensions of overconfidence bias.

Modern portfolio theory and illusion of control theory support this study.

Contemporary literature reveals that, to date, the poultry livestock sector has not received sufficient research attention. This particular industry suffers from unstructured supply chain practices, lack of awareness of the implications of the sustainability concept and failure to recycle poultry wastes. The current research thus attempts to develop an integrated supply chain model in the context of poultry industry in Bangladesh. The study considers both sustainability and supply chain issues in order to incorporate them in the poultry supply chain. By placing the forward and reverse supply chains in a single framework, existing problems can be resolved to gain economic, social and environmental benefits, which will be more sustainable than the present practices.

The theoretical underpinning of this research is ‘sustainability’ and the ‘supply chain processes’ in order to examine possible improvements in the poultry production process along with waste management. The research adopts the positivist paradigm and ‘design science’ methods with the support of system dynamics (SD) and the case study methods. Initially, a mental model is developed followed by the causal loop diagram based on in-depth interviews, focus group discussions and observation techniques. The causal model helps to understand the linkages between the associated variables for each issue. Finally, the causal loop diagram is transformed into a stock and flow (quantitative) model, which is a prerequisite for SD-based simulation modelling. A decision support system (DSS) is then developed to analyse the complex decision-making process along the supply chains.

The findings reveal that integration of the supply chain can bring economic, social and environmental sustainability along with a structured production process. It is also observed that the poultry industry can apply the model outcomes in the real-life practices with minor adjustments. This present research has both theoretical and practical implications. The proposed model’s unique characteristics in mitigating the existing problems are supported by the sustainability and supply chain theories. As for practical implications, the poultry industry in Bangladesh can follow the proposed supply chain structure (as par the research model) and test various policies via simulation prior to its application. Positive outcomes of the simulation study may provide enough confidence to implement the desired changes within the industry and their supply chain networks.

Sustainable tourism will be an appropriate strategy to be promoted during the post COVID-19 pandemic, as this is a turning point for the tourism industry to grab the unique chance to have a true reset by focussing on achieving long-term sustainability and a shift from a ‘me to we’ economy. To support sustainable tourism and foster future success in the tourism industry, the process of integrating green knowledge and knowledge management can begin with entrepreneurial education in higher education institutions (HEIs). However, empirical research on university students' green entrepreneurial intention in sustainable tourism has not been exhaustively studied. Additionally, there is a need to further explore knowledge management process and entrepreneurial learning in HEIs. Hence, the aim of this study is to analyze knowledge management as a technique to explore the green entrepreneurial intention of students in HEIs in sustaining Malaysia's tourism post COVID-19 pandemic. Exploratory research with quantitative analysis was conducted through partial least squares structural equation modelling (PLS-SEM). The findings reveal that there is a positive and significant relationship between green entrepreneurial knowledge and green entrepreneurial intention in sustainable tourism among university business students. Additionally, knowledge revision and conceptual change positively and significantly influence green entrepreneurial knowledge and green entrepreneurial intention in sustainable tourism. However, knowledge application has no impact on green entrepreneurial knowledge and green entrepreneurial intention. The results of this study also reveal that green entrepreneurial knowledge does not have a mediation effect on green entrepreneurial intention. The present work contributes by going beyond the study of entrepreneurial intention, as the research focusses on interconnection among these three major areas: knowledge management, sustainable tourism, and entrepreneurship education post COVID-19 pandemic. Hence, the combination of these diverse aspects in this study provides insights to educators and policy makers to investigate the importance of green entrepreneurial knowledge and benefits of knowledge management that can be integrated into entrepreneurship education for current and future sustainable tourism development.

A theoretical methodology premised on the epistemology of divine unity as the world view of all Islamic socio‐scientific inquiry, is introduced. This general theory based on the knowledge‐centred interactive, integrative and evolutionary process of social becoming is next formulated for the specific case of capital markets. The methodology premised on unity and unification of knowledge is shown to be a universal application interconnecting science and society through a process‐oriented knowledge‐centred model. Finally, the generalized theoretical methodology and its specification to the case of Islamic capital market is used to critically evaluate Malaysia’s Islamization program, specially during the heady days of her stock market and currency turmoils. Alternative policy recommendations are provided for a newer outlook on Malaysian development and capital market Islamization programs. A general inference is thus derived and conveyed to the field of capital market stability arising from a direct linkage between real sectoral activities and endogenous money as store of value of real transactions. The approach of this paper being epistemological in nature, it undertakes a fundamental look at Qur’an and Sunnah for developing shari’ah‐rules (Islamic law), i.e. ahkam as‐shari’ah (rules derived from shari’ah), in the area of socio‐scientific inquiry in general and Islamic capital market in particular.

In the dynamic landscape of the modern business world, the pursuit of employee well-being and satisfaction with life (SWL) has gained prominence. Yet, few studies exist on SWL among Indian working professionals. This study aims to investigate the impact of inclusive leadership (IL) on the employees’ SWL. Moreover, employing a mediation approach, the study also reveals the mediating role of workplace inclusion (WI) and career satisfaction (CS) in the relationship between IL and SWL.

The study involves a cross-sectional quantitative approach, drawing upon a sample of 279 professionals belonging to the Indian IT sector by administering standardized questionnaires. Data were analyzed using PLS through SmartPLS4.0 software.

The findings reveal a fully complementary mediating role of WI and CS in the IL–SWL relationship, supporting the hypothesized mediation model.

This finding implies that leaders, with their inclusive behavior, can significantly influence employees’ SWL when accompanied by a sense of inclusiveness and CS among employees. The study offers valuable insights for organizations and leaders seeking to enhance employee satisfaction in the IT sector, emphasizing the significance of career-focused and inclusive practices in the workplace through leadership to promote a fulfilling workplace.

This study represents a pioneering effort to integrate the relationship between IL and SWL within the Indian context, going beyond the existing literature on WI and SWL. Additionally, the research model explores the influence of WI and CS in the IL–SWL relationship, a novel approach that has not been previously investigated.