Static atomic charges affect key ground-state parameters of quasi-planar boron clusters B_n, n ≤ 20, which serve as building blocks of borophenes and other two-dimensional boron-based materials promising for various advanced applications. Assuming that the outer valence shells partial electron density of the constituent B atoms are shared between them proportionally to their coordination numbers, the static atomic charges in small planar boron clusters in the electrically neutral and positively and negatively singly charged states are estimated to be in the ranges of –0.750e (B₇⁰) to +0.535e (B₂₀⁰), –0.500e (B₇⁺, B₈⁺, and B₉⁺) to +0.556e (B₁₇⁺), and –1.000e (B₇^–) to +0.512e (B₂₀^–), respectively.

The food supply chain in South Africa faces significant challenges related to transparency, traceability, and consumer trust. As concerns about food safety, quality, and sustainability grow, there is an increasing need for innovative solutions to address these issues. Blockchain technology has emerged as a promising tool to enhance transparency and accountability across various industries, including the food sector. This study sought to explore the potential of blockchain technology in revolutionizing through promoting transparency that enable the achievement of sustainable food supply chain infrastructure in South Africa. The study found that blockchain technology used in food supply chain creates an immutable and decentralized ledger of transactions that has the capacity to provide real-time, end-to-end visibility of food products from farm to table. This increased transparency can help mitigate risks associated with food fraud, contamination, and inefficiencies in the supply chain. The study found that blockchain technology can be leveraged to enhance supply chain efficiency and trust among stakeholders. This technology used and/or applied in South Africa can reshape the agricultural sector by improving production and distribution processes. Its integration in the food supply chain infrastructure can equally improve data management and increase transparency between farmers and food suppliers.There is need for policy-makers and scholars in the fields of service delivery and food security to conduct more research in blockchain technology and its roles in creating a more transparent, efficient, and trustworthy food supply chain infractructure that address food supply problems in South Africa. The paper adopted a qualitative methodology to collect data, and document and content analysis techniques were used to interpret collected data. 

The aim was to examine the relationships between selected demographic and psychographic factors and consumers' willingness to accept content generated by advanced technological innovations (AIGC) in social infrastructure. The sample consisted of 1,308 respondents. Spearman's correlation coefficient was used to examine the relationships between ordinal variables. To assess the differences between groups of respondents, a one-way analysis of variance was used, during which multiple linear regression analysis was used to confirm the predictive power of awareness and experience in relation to AI-generated content in relation to the tendency to accept such content. The study confirmed a statistically significant but weak negative relationship between the age of respondents and their willingness to accept AIGC, with younger age groups showing a slightly higher rate of acceptance. Respondents' attitudes toward the use of personal data through AI and their overall awareness of technological trends had a more significant impact on acceptance. The findings show that respondents who are open to data collection through AI technologies show a significantly higher level of acceptance of automatically generated content. Similarly, respondents who positively evaluate the current quality of AIGC have higher expectations for the future transformation of marketing strategies and media practices. The decisive factors in the social infrastructure for the acceptance of AIGC are not so much the age of the respondents, but rather their awareness, technological literacy, and level of trust in the technology itself. The study therefore recommends increasing transparency and public awareness about the use of AI in marketing and media practices in order to strengthen consumer confidence in automated content.

This research examines data from 1989 to 2022 across 48 Sub-Saharan African (SSA) countries using a novel panel data regression approach to uncover how conflict undermines economic stability. The study identifies the destruction of infrastructure, disruption of human capital development, and deterrence of investment as primary channels through which conflict negatively impacts economies. These findings support the hypothesis that armed conflict severely hampers economic performance in SSA, highlighting the urgency for effective conflict resolution strategies and robust institutional frameworks. The negative impacts extend beyond immediate losses, altering income growth trajectories and perpetuating poverty long after hostilities cease. Regional spillover effects emphasize the interconnectedness of SSA economies, where conflict in one country affects its neighbors. The research provides innovative insights by disaggregating impact pathways and employing a robust methodology, revealing the complexity of conflict's economic consequences. It underscores the need for comprehensive policy interventions to foster resilience and sustainable development in conflict-prone regions. While there is evidence of potential post-conflict growth, the overall net effect of armed conflict remains profoundly negative, diminishing economic prospects. Future research should focus on strengthening long-term resilience mechanisms and policy measures to enhance the peace dividend. Addressing the root causes of conflict and investing in peace-building efforts are essential for transforming SSA's economic landscape and ensuring sustainable growth and development.

This work investigated the photocatalytic properties of polymorphic nanostructures based on silica (SiO₂) and magnetite (Fe₃O₄) for the photodegradation of tartrazine yellow dye. In this sense, a fast, easy, and cheap synthesis route was proposed that used sugarcane bagasse biomass as a precursor material for silica. The Fourier transform infrared (FTIR) spectroscopy results showed a decrease in organic content due to the chemical treatment with NaOH solution. This was confirmed through the changes promoted in the bonds of chromophores belonging to lignin, cellulose, and hemicellulose. This treated biomass was calcined at 800 ℃, and FTIR and X-ray diffraction (XRD) also confirmed the biomass ash profile. The FTIR spectrum showed the formation of silica through stretching of the chemical bonds of the silicate group (Si-O-Si), which was confirmed by DXR with the predominance of peaks associated with the quartz phase. Scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDS) confirmed the morphological and chemical changes due to the chemical and thermal treatments applied to this biomass. Using the coprecipitation method, we synthesized Fe₃O₄ nanoparticles (Np) in the presence of SiO₂, generating the material Fe₃O₄/SiO₂-Np. The result was the formation of nanostructures with cubic, spherical, and octahedral geometries with a size of 200 nm. The SEM images showed that the few heterojunctions formed in the mixed material increased the photocatalytic efficiency of the photodegradation of tartrazine yellow dye by more than two times. The degradation percentage reached 45% in 120 min of reaction time. This mixed material can effectively decontaminate effluents composed of organic pollutants containing azo groups.