The aim of this study was to elucidate the expected moderating effect exerted by institutional owners on the intricate correlation between the characteristics of boards of directors and the issue of earnings management, as gauged by the loan loss provisions.The sample encompassed all the banks listed on the Amman Stock Exchange (ASE) over the period between 2010 and 2022, representing a total of 151 observations. The results derived from the examination clearly demonstrate that the institutional owners have a key impact on augmenting the monitoring tasks and responsibilities of the boards of directors across the study sample. The results revealed the fundamental role of such owners in strengthening the supervisory tasks carried out by boards of directors in Jordan. A panel data model has been used in the analysis. The results of this study show that the presence of the owner of an institution has a discernible moderating role in the banks' monitoring landscape. Indeed, their presence strengthens the monitoring tasks of the banks’ boards by underscoring the quest to restrict the EM decisions. Interestingly, the results support the monitoring proposition outlined by agency theory, which introduced CG recommendations as a deterrent tool to reduce the expectation gap between banks' owners and their representatives.

Exposure to high-frequency (HF) electromagnetic fields (EMF) has various effects on living tissues involved in biodiversity. Interactions between fields and exposed tissues are correlated with the characteristics of the exposure, tissue behavior, and field intensity and frequency. These interactions can produce mainly adverse thermal and possibly non-thermal effects. In fact, the most expected type of outcome is a thermal biological effect (BE), where tissues are materially heated by the dissipated electromagnetic energy due to HF-EMF exposure. In case of exposure at a disproportionate intensity and duration, HF-EMF can induce a potentially harmful non-thermal BE on living tissues contained within biodiversity. This paper aims to analyze the thermal BE on biodiversity living tissues and the associated EMF and bio-heat (BH) governing equations.

This paper uses existing studies to explore how Artificial Intelligence (AI) advancements enhance recruitment, retention, and the effective management of a diverse workforce in South Africa. The extensive literature review revealed key themes used to contextualize the study. This study uses a meta-narrative approach to literature to review, critique and express what the literature says about the role of AI in talent recruitment, retention and diversity mapping within South Africa. An unobtrusive research technique, documentary analysis, is used to analyze literature. The findings reveal that South Africa’s Human Resource Management (HRM) landscape, marked by a combination of approaches, provides an opportunity to cultivate alternative methods attuned to contextual conditions in the global South. Consequently, adopting AI in recruiting, retaining, and managing a diverse workforce demands a critical examination of the colonial/apartheid past, integrating contemporary realities to explore the potential infusion of contextually relevant AI innovations in managing South Africa’s workforce.

The reduction of biodiversity and the decline in wildlife populations are urgent environmental issues with devasting consequences for ecosystems and human health. As a result, the protection of wildlife and biodiversity has emerged as one of humanity's greatest goals, not only for protecting and maintaining human health but also for environmental, economic, and social well-being. In recent years, people have become increasingly aware of the importance and effectiveness of wildlife conservation efforts alongside environmental protection measures, sustainable agricultural practices and non-harmful production procedures and services. This study describes the development and implementation of a labeling scheme for wildlife and biodiversity protection for products or services. The label is designed to encourage the adoption of sustainable and environmentally friendly production methods and services that will contribute to biodiversity conservation and the harmonic coexistence of human-wildlife. Moreover, using a case study approach, the research presents an innovative information system designed to streamline the label-awarding process, ensuring transparency and efficiency. The established system evaluates the sustainability practices and measures implemented by businesses, with a focus on honey production in this case. Additionally, the study explores the broader social implications of the label, particularly its potential to engage consumers and promote awareness of biodiversity conservation.

This paper explores the integration of Large Language Models (LLMs) and Software-Defined Resources (SDR) as innovative tools for enhancing cloud computing education in university curricula. The study emphasizes the importance of practical knowledge in cloud technologies such as Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), DevOps, and cloud-native environments. It introduces Lean principles to optimize the teaching framework, promoting efficiency and effectiveness in learning. By examining a comprehensive educational reform project, the research demonstrates that incorporating SDR and LLMs can significantly enhance student engagement and learning outcomes, while also providing essential hands-on skills required in today’s dynamic cloud computing landscape. A key innovation of this study is the development and application of the Entropy-Based Diversity Efficiency Analysis (EDEA) framework, a novel method to measure and optimize the diversity and efficiency of educational content. The EDEA analysis yielded surprising results, showing that applying SDR (i.e., using cloud technologies) and LLMs can each improve a course’s Diversity Efficiency Index (DEI) by approximately one-fifth. The integrated approach presented in this paper provides a structured tool for continuous improvement in education and demonstrates the potential for modernizing educational strategies to better align with the evolving needs of the cloud computing industry.

This study investigated the changing land use patterns and their impacts on ecosystem in the Teesta River Basin of northwestern Bangladesh. Although anthropocentric land use patterns, including agricultural land use, settlements, built areas, and waterbody loss, have been increasing in the Nilphamari district, by negatively affecting local ecosystems, they have not been identified by prior research. Limitations of contemporary literature motivated me to work on this crucial ground in the Teesta River Basin in Northwestern Bangladesh. This study applied a mixed research approach to identify the study objectives. Firstly, the land use and land cover (LULC) changes which occurred between 2000 and 2020 were detected using satellite imagery and supervised classification method. In addition to the detection of LULC changes, the study explored the people’s perceptions and experiences about the ecosystem changes resulted from the LULC changes over the last 20 years, conducting stakeholders’ consultations and household surveys utilizing a semi-structured questionnaire. The findings indicated that waterbodies in Nilphamari district have significantly decreased from 378 km² in 2000 to 181 km² in 2020. In the same way, the vegetation coverage has reduced 187 km² between the years 2000 and 2020. On the contrary, agricultural lands (croplands) have increased from 595 km² to 905 km² and settlements have increased from 81 km² to 206 km² between the years 2000 and 2020. From the chi-square test, it was found a significant association between ecosystem change and biodiversity loss. It was further identified that waterbody decreases have significant impacts on aquatic ecosystems. The results of this study also indicated that due to the introduction of foreign tree species, local and native species have been significantly decreasing over the time. This study emphasizes the non-anthropocentric and inclusive land use policy implications for protecting life on land and preserving the aquatic ecosystem in Bangladesh.