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.

Using company size as a moderator, this article examines the MENA region’s gender balance on boards and how it influences capital structure. The study uses the Generalized Method of Moments (GMM) estimate technique to analyze data from a sample of 556 non-financial organizations across 10 MENA countries from 2010 to 2023. The results show that a lower debt ratio is connected with a higher percentage of female board members. Further steps towards debt reduction include increasing the number of independent female board members and decreasing the board’s overall size. The opposite is true for larger enterprises, more profitability, more expansion opportunities, and macroeconomic variables like inflation and GDP growth, which tend to raise the debt ratio. Capital structure decisions in the MENA area are influenced by gender diversity on boards and business characteristics. Therefore, Companies in the MENA area would do well to support initiatives that increase the representation of women on corporate boards. One way to achieve this goal is to establish gender diversity targets or launch programs to increase the number of women serving on boards of directors, particularly in positions of power.

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.

In Nigeria, deforestation has led to an unimaginable loss of genetic variation within tree populations. Regrettably, little is known about the genetic variation of many important indigenous timber species in Nigeria. More so, the specific tools to evaluate the genetic diversity of these timber species are scarce. Therefore, this study developed species-specific markers for Pterygota macrocarpa using state-of-the-art equipment. Leaf samples were collected from Akure Forest Reserve, Ondo State, Nigeria. DNA isolation, quantification, PCR amplification, gel electrophoresis, post-PCR purification, and sequencing were done following a standardized protocol. The melting temperatures (TM) of the DNA fragments range from 57.5 ℃to 60.1 ℃ for primers developed from the MatK gene and 58.7 ℃ to 60.5 ℃ for primers developed from the RuBisCo gene. The characteristics of the ten primers developed are within the range appropriate for genetic diversity assessment. These species-specific primers are therefore recommended for population evaluation of Pterygota macrocarpa in Nigeria.

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.