The 19th century proved to be one of the most complicated periods in Spanish history for the Spanish Crown, as it faced both internal conflicts—the French War of Independence—and external conflict—the independence of what were its territories in most of America. France did not remain indifferent to this and always had a clear idea of where to draw the boundaries of what “belonged” to it. Thus, amid the wave of independence movements in the Spanish colonies, the French continued to produce rich cartography to establish these boundaries and settle their power over the new nations that were arising after the period of revolutions. The cartography of Rigobert Bonne, the last cartographer of the French king and the Revolution Era, and one of its disciples, Eustache Hérisson, represent the perfect witness to the changes over the borders of the Spanish colonies during the change of the century. This study aims to analyze such cartography, examine the rich toponyms it offers, and examine the changes in the boundaries created over time between both empires. The main cartography we will rely on will be that of Bonne, one of the most important cartographers of the 18th century, and his disciple Hérisson, a geographer engineer, who lived through the onset of the conflicts and always prioritized the French perspective and the interests of their nation.

The introduction of artificial intelligence (AI) marks the beginning of a revolutionary period for the global economic environments, particularly in the developing economies of Africa. This concept paper explores the various ways in which AI can stimulate economic growth and innovation in developing markets, despite the challenges they face. By examining examples like VetAfrica, we investigate how AI-powered applications are transforming conventional business models and improving access to financial resources. This highlights the potential of AI in overcoming obstacles such as inefficient procedures and restricted availability of capital. Although AI shows potential, its implementation in these areas faces obstacles such as insufficient digital infrastructure, limited data availability, and a lack of necessary skills. There is a strong focus on the need for a balanced integration of AI, which involves aligning technological progress with ethical considerations and economic inclusivity. This paper focuses on clarifying the capabilities of AI in addressing economic disparities, improving productivity, and promoting sustainable development. It also aims to address the challenges associated with digital infrastructure, regulatory frameworks, and workforce transformation. The methodology involves a comprehensive review of relevant theories, literature, and policy documents, complemented by comparative analysis across South Africa, Nigeria, and Mauritius to illustrate transformative strategies in AI adoption. We propose strategic recommendations to effectively and ethically utilize the potential of AI, by advocating for substantial investments in digital infrastructure, education, and legal frameworks. This will enable Africa to fully benefit from the transformative impact of AI on its economic landscape. This discourse seeks to offer valuable insights for policymakers, entrepreneurs, and investors, emphasizing innovative AI applications for business growth and financing, thereby promoting economic empowerment in developing economies.

Zero-valent iron is a moderately reducing reagent that is both non-toxic and affordable. In the present work, iron nanoparticles were synthesized using bitter guard leaf extract (Momordica charantia L.) (BGL-Fe NP). Using leaf samples from bitter protectant extract, iron nanoparticles were synthesized with secondary metabolites such as flavonoids and polyphenols acting as capping and reducing agents. Polyphenols reduce Fe²⁺/Fe³⁺ to nanovalent iron or iron nanoparticles. Iron nanoparticles were synthesized by reducing iron chloride as a precursor with bitter protective leaf extract in an alkaline environment. The obtained BGL-Fe NPs were calcined for 4 h at various temperatures of 400 °C, 500 °C, and 600 °C. The obtained samples were coded as BGL-Fe NPs-4, BGL-Fe NPs-5, and BGL-Fe NPs-6, respectively. The synthesized BGL-Fe NPs were systematically characterized by XRD, SEM, FTIR, UV-Vis and TG-DTA analysis. The obtained BGL-Fe NPs were then used as an adsorbent to remove the aqueous solution of basic methylene blue (MB) dye. MB concentration was monitored using UV-Vis spectroscopy.

Europium (Eu) doped Calcium borophosphate (CBP) phosphors were synthesized via the solid-state diffusion method. The prepared Europium (Eu) doped Calcium borophosphate (CBP) powder was heated up to 600 ℃ for 6 h for a complete diffusion of ions in the powder system. XRD results showed that the prepared phosphors exhibit a well-crystallized hexagonal phase. The complete diffusion inside the CBP/Eu powder system has been confirmed by the presence of elements such as P, O, Bi, Ca, C, Eu, and B. Apart from that, the synthesized powder system has shown a down-conversion property where the Eu³⁺-activated ion was excited at 251 nm. Under the excitation of 251 nm, CBP/Eu phosphor showed intense emissions peaking at 591,617, and 693 nm due to the ⁵D₀ → ⁷F₁, ⁵D₀ → ⁷F₂, and ⁵D₀ → ⁷F₄ transition of Eu³⁺ ions. The obtained results suggest that the CBP/Eu phosphors have the potential for spectral response coating materials to improve photovoltaic (PV) panel efficiency.

National governments and academic higher education institutions continue to realign human resource development (HRD) strategies to address the gaps in HRD mandate. This study will investigate new and recalibrated skills that higher institutions (HEIs) professionals and the labor force produce to reconfigure curriculum development in tertiary education. The study extracts narrative from 6 curriculum developers, 3 HRD heads and h3 manpower organizations on the labor landscapes from different local and multinational industries from entry-level to mid-career ranges through case scenario-based interviews and focus group discussions to determine the skills around motivation, innovativeness, and adaptability and subsequently integrate strategic initiatives to reconfigure the compatibility of these skills from higher education institutions to post-pandemic industries. The findings reveal skills that can be managed at the individual level, e.g., self-motivation and adaptability as well as the need to emerge from the technological pressures by adapting to organizational and clientele demands. These human resource traits become the mantra of surviving and progressing in a landscape shaped by the pre- and post-pandemic setting and become the basis of HEI programs to match the needs of the labor force and the industries.

This study aims to predict whether university students will make efficient use of Artificial Intelligence (AI) in the coming years, using a statistical analysis that predicts the outcome of a binary dependent variable (in this case, the efficient use of AI). Several independent variables, such as digital skills management or the use of Chat GPT, are considered.The results obtained allow us to know that inefficient use is linked to the lack of digital skills or age, among other factors, whereas Social Sciences students have the least probability of using Chat GPT efficiently, and the youngest students are the ones who make the worst use of AI.