Credit risk affects the work and reputation of banks. Islamic banks' heavy reliance on debt financing has led to increased interest in credit risk and its management. This paper aimed to identify the bank-specific factors affecting credit risk in Islamic banks, expressed as Non-Performing Finance NPF in the Middle East for the period 2011-2022. The study was based on a panel data analysis of 30 Islamic banks. The findings of study show a significant negative impact of Return On Assets ROA, Capital Adequacy Ratio CAR and size Z on the credit risk. The findings show a significant positive impact of Finance Loss Provision FLP on the credit risk. The findings also show no impact of Finance Expansion FEX, Finance to Deposit Ratio FDR and Capital Ratio CPR on the credit risk. The study showed that increasing the provision for financing losses and capital adequacy helps banks to reduce the impact of credit risks. The study recommends applying cautious lending policies and carefully selecting clients.

Human migration is based on pull factors that individuals evaluate when it comes to moving to a different territory. Likewise, employee attrition is a phenomenon that represents the tendency to a reduction in employees within an organization. This research paper aims to develop and evaluate machine learning algorithms, namely Decision Tree, Random Forest, and Binary Logistic Regression, to predict employee attrition using the IBM dataset available on Kaggle. The objective is to provide organizations with a proactive approach to employee retention and human resource management by creating accurate predictive models. Employee attrition has significant implications for an organization's reputation, profitability, and overall structure. By accurately predicting employee attrition, organizations can identify the factors contributing to it and implement data-driven human resources management practices. This study contributes to improving decision-making processes, including hiring and firing decisions, and ultimately enhances an organization's capital. The IBM dataset used in this study consists of anonymized employee records and their employment outcomes. It provides a comprehensive HR data representation for analysis and prediction. Three machine learning algorithms, Decision Tree, Random Forest, and Binary Logistic Regression, were utilized in this research. These algorithms were selected for their potential to improve accuracy in predicting employee attrition. The Logistic Regression model yielded the highest accuracy of 87.44% among the tested algorithms. By leveraging this study's findings, organizations can develop predictive models to identify factors contributing to employee attrition. These insights can inform strategic decisions and optimize human resource management practices.

Methyl α-D-mannopyranoside (MAM) is a naturally occurring carbohydrate derivative that has gained attention in drug discovery due to its potential therapeutic applications, particularly as an antifungal agent. In this study, we employed a computational approach to investigate the interactions between MAM and two Candida albicans antifungal proteins, 1IYL and 1AI9, through molecular docking simulations. Furthermore, we performed a PASS (Prediction of Activity Spectra for Substances) analysis to predict MAM potential biological activities, explored the pharmacokinetic properties and ADMET (absorption, distribution, metabolism, excretion, and toxicity) profiles, and optimized the MAM using the density functional theory (DFT) method. The molecular docking results revealed favorable binding interactions between MAM and the active sites of the 1IYL and 1AI9 proteins, suggesting potential antifungal activity. Additionally, the ADMET profiles indicated low toxicity and suitable drug-like properties, such as moderate metabolic stability and minimal risk of adverse effects. Furthermore, DFT optimization was performed to investigate the molecular geometry and electronic properties of MAM. The optimization results provided valuable information on the stability and reactivity of MAM, enabling a better understanding of its chemical behavior and potential modifications for enhanced activity. Finally, PASS prediction was employed to evaluate MAM's potential biological activities beyond its antifungal properties. The analysis revealed several potential activities, including antibacterial, antiviral, and immunomodulatory effects, expanding the scope for future research and therapeutic applications. In conclusion, this computational study sheds light on the molecular interactions, pharmacokinetic properties, ADMET profiles, DFT optimization, and PASSES predictions of MAM. These findings highlight the potential of MAM as a promising antifungal agent with favorable pharmacological properties.

Expressive suppression is the process of decreasing, increasing, or maintaining emotional intensity over a period of time. It is employed as an immediate response to emotional stimuli and can result in negative psychological outcomes. This emotional regulation process can be harmful in the workplace, especially when one considers time pressures and the standard corporate hierarchical structure in modern America, which potentially also introduces stress into situations due to the “superior/subordinate” relationship. This study analyzed the correlation between self-reported high usage of expressive suppression and perceived stress and found that a correlation does exist between the emotion regulation technique and perceived stress. The study also reviewed other workplace situations and found that being in the presence of a superior also plays a role in this dynamic. The study highlights the stress impact of employing expressive suppression and the need for further research into factors within the workplace that impact an individual’s emotional regulation and impact overall stress.

Manufacturing firms operating in today’s competitive global markets must continuously find the appropriate manufacturing scheme and strategies to effectively meet customer needs for various types of quality of merchandise under the constraints of short order lead-time and limited in-house capacity. Inspired by the offering of a decision-making model to aid smooth manufacturers’ operations, this study builds an analytical model to expose the influence of the outsourcing of common parts, postponement policies, overtime options, and random scrapped items on the optimal replenishment decision and various crucial system performance indices of the multiproduct problem. A two-stage fabrication scheme is presented to handle the products’ commonality and the uptime-reduced strategies to satisfy the short amount of time before the due dates of customers’ orders. A screening process helps identify and remove faulty items to ensure the finished lot’s anticipated quality. Mathematical derivation assists us in finding the manufacturing relevant total cost function. The differential calculus helps optimize the cost function and determine the optimal stock-replenishing rotation cycle policy. Lastly, a simulated numerical illustration helps validate our research result’s applicability and demonstrate the model’s capability to disclose the crucial managerial insights and facilitate manufacturing-relevant decision making.

This research aims to investigate the upcoming challenges of green innovation and sustainability in the hospitality and tourism sectors of Saudi Arabia and the mediating role of National Vision 2030 in fostering industry growth. A quantitative design was used, and a close-ended questionnaire was used to collect data from 499 respondents in the hospitality and tourism sectors of Saudi Arabia. The analysis was performed using SmartPLS and structural equation modeling (SEM). The findings indicate several upcoming challenges, such as renewable energy consumption, energy efficiency, and the changing preferences of consumers. However, these challenges can be dealt with adequate government policies and the mediating role of the Saudi Arabia 2030 vision to achieve sustainability in the hospitality and tourism sectors. These findings have theoretical and practical implications, which are discussed in the end. The scope of the findings is constrained to the geographic context of Saudi Arabia, inviting future investigations in a broader international context.

Public sector development projects are found to have poor repute in terms of completion within assigned cost and time. Almost every 2nd project is impacted by financial burdens and time delays. The aim of this literature review is to highlight the potential factors that impact the completion time and estimated cost with respect to public sector infrastructure development projects in Pakistan. 39 sub-factors have been identified from 32 existing research which are then classified into 8 main factors. The main factors include administrative issues, improper financial plans, market risks, input cost estimates, poor corporate governance, legal issues, technical matters errors, and environmental issues. The results of this systematic literature review will provide policymakers with oversight on how to formulate effective strategies regarding cost cutting and timely execution of the infrastructure development projects in Pakistan.

Nowadays, tardiness has become a significant risk in the logistics industry. To address this problem, we introduce the tardiness risk index to quantify both the magnitude of the tardiness risk and the maximum probability of tardiness occurring. In this paper, we investigate the contract design problem with the tardiness risk index to mitigate the tardiness risk when a fourth-party logistics company (4PL) delegates the delivery task of a client to a third-party logistics company (3PL). Specifically, the contracts are designed in a decentralized system with information symmetry and information asymmetry when 3PL is risk neutral and risk averse. Furthermore, the incentive problems demonstrated that the 3PL is encouraged to make the optimal effort for delivery and the 4PL determines the optimal fixed payment and penalty coefficient. Through analyzing the experimental simulation results, we can find that the contract can effectively mitigate the tardiness risk and the maximum probability of risk occurrence.

The nitrovinyl moiety is surely one of the most reactive fragments in organic chemistry, continuously employed to explore original pathways and reach new targets. One of the most important classes of chemicals containing this fragment are nitro-functionalised analogues of 1,3-butadiene. In this paper a comprehensive review study of these compounds is performed. The manuscript includes an analysis of physicochemical properties, spectral characteristic, synthesis, biological activity, and possible transformations of nitro substituted analogues of 1,3-butadiene. The analysis was divided into several parts, depending on the number of nitro groups included in the structure of a 1,3-butadiene analogue. In addition, the work includes information about hazards and safety principles when working with nitro compounds. Based on the analysis of the literature, it can be concluded that nitro-functionalised analogues of 1,3-butadiene exhibit diversified profile of properties, and an outstanding potential as valuable reagents in organic synthesis useful to obtain heterocycles that can be applied in medicine.

This study explores the influence of two key factors, namely communication and disposition, on policy implementation in the educational environment. The main objective of the research is to investigate the impact of communication and disposition on policy implementation, with a specific emphasis on the moderating role of disposition in the relationship between communication and policy implementation. The method used in this research is partial least squares structural equation modelling (PLS-SEM), analysing data from 232 research samples obtained from nine schools in Indonesia. The research results indicate that communication has a significant and positive influence on policy implementation, while disposition also has a significant and positive impact on policy implementation. A more interesting finding is that disposition, in the context of this research, proves to play a crucial role as a moderating variable, enhancing the positive influence between communication and policy implementation. This finding contributes significantly to our understanding of the complexity of factors influencing policy implementation in the educational environment, particularly from the interaction perspective between communication and disposition. The implications of this research can form the basis for the formulation of more effective and contextual policy strategies in the future.