Purpose—In the business sector, reliable and timely data are crucial for business management to formulate a company’s strategy and enhance supply chain efficiency. The main goal of this study is to examine how strong brand strength affects shareholder value with a new Supplier Relationship Management System (SRMS) and to find the specific system qualities that are linked to SRMS adoption. This leads to higher brand strength and stronger shareholder value. Design/Methodology/Approach—This study employed a cross-sectional design with an explanatory survey as a deductive technique to form hypotheses. The primary method of data collection used a drop-off questionnaire that was self-administered to the UAE-based healthcare suppliers. Of the 787 questionnaires sent to the healthcare suppliers, 602 were usable, yielding a response rate of 76.5%. To analyze the data gathered, the study used Partial Least Squares Structural Equation modelling (PLS-SEM) and artificial neural network (ANN) techniques. Findings—The study’s data proved that SRMS adoption and brand strength positively affected and improved healthcare suppliers’ shareholder value. Additionally, it demonstrates that user satisfaction is the most significant predictor of SRMS adoption, while the results show that the mediating role of brand strength is the most significant predictor of shareholder value. The results demonstrated that internally derived constructs were better explained by the ANN technique than by the PLS-SEM approach. Originality/Value—This study demonstrates its practical value by offering decision-makers in the healthcare supplier industry a reference on what to avoid and what elements to take into account when creating plans and implementing strategies and policies.

This study investigates the link between debt and political alignment in international relations between the People’s Republic of China (PRC) and African nations. Using recorded roll-call votes on United Nations General Assembly (UNGA) resolutions, we explore whether PRC investment in sovereign debt influences the voting behaviour of loan recipient countries. We compile voting data for African countries from 2000 to 2020 to calculate an annual voting affinity score as a proxy for political alignment. Concurrently, data on Chinese public and publicly guaranteed (PPG) loans to African governments are collected. A Two-Stage Least-Squares analysis is employed, using the ratio of Chinese PPG debt to GDP as an instrument to address endogeneity. Results reveal a negative impact of Chinese lending on African political support, while trade, foreign direct investment (FDI), and Chinese GDP positively influence political alignment. In high debt-risk African countries, interest rates have a negative impact, whereas loan maturity shows a positive effect. These findings suggest that Chinese loans, particularly under commercial terms, may have strained bilateral relations due to debt sustainability concerns. Nevertheless, the positive impacts of trade and FDI may enhance international relations, highlighting the limitations of China’s loan diplomacy in fostering long-term strategic alignment in Africa.

The creation of points where law, politics and education policies take intersection is a very complex and dynamic environment determined by philosophical shifts, economic problems, and social dynamics. This study dissects various complicated challenges facing the process of the framing of educational policies and their implementation which have become rampant due to the rapid political transformations. The researched evaluation is applied via both qualitative and quantitative methods, including juridical research, case and best practices studies and surveys, with the descriptive nature of the research as the main tool. The heart of the essay is three main themes - the contention between the rigidity of the academic standards and the holistic growth of students, its possible effects when students are too identified with a test-centric approach as their knowledge is sacrificed for their test scores, and the inclusion of rights and protections for underrepresented populations even when faced with a government’s resistance. Similarly, the research examines the perils of creating legislation too quickly, especially, because of unexpected side effects and interpretation conflicts. Findings show profound demographic differentials over districts which implies the designing and implementation of policies need to be modified accordingly. Unless a certain policy brings the best outcomes in the learning process, then nobody should choose it even if it means disrupting student well-being and decreasing their involvement. It is also emblematic of how cross-party cooperation and stakeholders’ understanding are important aspects of fairly dealing with complicated policy environments.

Silymarin, a bioactive compound derived primarily from the seeds and fruit of the milk thistle (Silybum marianum) plant, has garnered increasing attention in recent years due to its potential applications in agriculture. This comprehensive review explores the multifaceted role of silymarin in agricultural practices, shedding light on its chemistry, biological activities, and diverse applications. The chemical structure and properties of silymarin are elucidated, emphasizing its unique solubility, stability, and bioavailability, which render it suitable for agricultural use. A significant portion of the review is dedicated to examining the biological activities of silymarin, which encompasses its antioxidant properties. The underlying mechanisms responsible for these activities are explored, highlighting their potential as a natural solution for mitigating environmental stressors that adversely affect crop health and productivity. Illustrative examples from research studies and practical applications underscore its effectiveness in safeguarding agricultural yields and ensuring food security. Furthermore, the review delves into the potential of silymarin to enhance crop growth, yield, and quality. Mechanisms through which silymarin influences plant physiology and metabolism are examined, providing valuable insights into its role as a growth-promoting agent in agriculture. The review concludes with a forward-looking examination of the prospects of silymarin in agriculture, highlighting emerging trends and areas of innovation that hold promise for sustainable and resilient farming systems. In summary, this review consolidates the current body of knowledge surrounding silymarin’s potential in agriculture. It underscores the versatility of silymarin as a natural tool for crop protection, growth enhancement, and environmental sustainability, offering valuable insights for researchers, practitioners, and policymakers seeking innovative approaches to address the challenges of modern agriculture.

Monitoring marine biodiversity is a challenge in some vulnerable and difficult-to-access habitats, such as underwater caves. Underwater caves are a great focus of biodiversity, concentrating a large number of species in their environment. However, most of the sessile species that live on the rocky walls are very vulnerable, and they are often threatened by different pressures. The use of these spaces as a destination for recreational divers can cause different impacts on the benthic habitat. In this work, we propose a methodology based on video recordings of cave walls and image analysis with deep learning algorithms to estimate the spatial density of structuring species in a study area. We propose a combination of automatic frame overlap detection, estimation of the actual extent of surface cover, and semantic segmentation of the main 10 species of corals and sponges to obtain species density maps. These maps can be the data source for monitoring biodiversity over time. In this paper, we analyzed the performance of three different semantic segmentation algorithms and backbones for this task and found that the Mask R-CNN model with the Xception101 backbone achieves the best accuracy, with an average segmentation accuracy of 82%.