Dialogic STEM Journal

Climatic condition in Africa is worsening with severe impacts on the agricultural sector. Promoting resilience through adaptive pathways is essential for sustainable agricultural security. This study employed multiple approaches to gather data from stakeholders across seven African countries, including surveys, key informant interviews, document reviews, and policy analyses. Data was analysed using Excel and R, with a two-pronged approach focusing on aggre gated and country-specific insights. Responses to extreme events like droughts are often autonomous, driven by indig enous knowledge and capacities. Effective adaptation practices identified include agroforestry, early warning systems, altered planting times, migration, alternative livelihoods, and forest fire control, with many showing over 80% impact effectiveness. The success of these practices depends on local relevance, affordability, simplicity, and the ability to meet community needs. Agroforestry and early warning systems emerged as particularly viable strategies. The study recom mends scaling up and promoting the most promising adaptation practices to strengthen climate resilience across Africa’s agricultural landscapes.

The nuclear proliferation problem is an important issue in the field of nuclear strategy, characterized by dy namic investments by states and possibilities of preventive actions. The conventional static game models cannot capture dynamic processes, uncertainties, and irreversibility inherent in nuclear strategy problems. This work aims to develop a unified differential game model for nuclear strategy problems, addressing the gaps identified by conventional models. Specifically, we propose a comprehensive differential game model for nuclear strategy problems, focusing on the inter action between a proliferating state, e.g., Iran, and a preventive state, e.g., Israel/US, within the context of nuclear weapons development. Our differential game model combines four distinct yet integrated models, each of which pro gressively incorporates all critical elements of nuclear strategy problems. Model 1: This model establishes a one-state differential game foundation, where the proliferator invests resources in nuclear capability, and the preventer invests resources in prevention, including a costly, capability-reducing preventive strike. Model 2: This model incorporates asymmetric information, where the speed of nuclear breakout by the proliferator is considered a private information, and the preventer learns from an imperfect observation of the state through Bayesian updating. Model 3: This model employs a multi-stage, continuous time Markov chain method, capturing dynamic nuclear R&D, enrichment, and weaponization, as well as the stage-dependent effectiveness of prevention. Model 4: This model develops a two-state differential game model, where the proliferator has the option of investing resources in deterrence capabilities, making a preventive strike by the preventer more costly. For each model, we derive the corresponding Hamilton-Jacobi-Bellman (HJB) equations, and then analyse the optimal feedback strategies, as well as the equilibrium conditions, for each model. Our results reveal important strategic phenomena, including signalling incentives, pre-emption traps, and deterrence stability, providing a rigorous mathematical foundation for nuclear strategy problems, with testable implications for policy, e.g., optimal sanctions, intelligence, and military intervention.

This paper presented the design, development and rapid prototyping of a novel heptagonal mechatronic spinner for practicing and gamification of “Domain–Based Systems and Systematic thinking”. The spinner is intended to facilitate teaching, learning, brainstorming, storytelling, systematic thinking, co-creative, co-analysis, leisure and game 9 activities. To realise the Mechatronic Spinner including seven domains (i.e. Objective, Place, People, Process, Time, Reason and Specific domains) steps including ideas generation, hand sketching, detailed engineering design, design optimisations, circuit design, coding, prototyping and testing were implemented leveraging Lean and Agile Design and Rapid Prototyping with additive manufacturing. The mechatronic system realised, expectedly, generated randomness at each spin, which makes it suitable for application for cognitive activities. A case of how the spinner can be used for teaching and learning probability and statistics based on the numerical feature was instantiated. This device offers a wide range of opportunities to practice creative and analytical thinking activities such as domain-based brainstorming, ideas generation and problem-solving.

To be effective, chromatography methodology requires specific tailoring to match the properties of the mixture being separated. In this study, an alkane standard mixture of hydrocarbons (nC8 – nC40) was used to develop the method to identify the hydrocarbons present in an oil contaminated environment. To do this, the boiling point of the mixture, the column temperature, the inlet temperature and the flow rate of the chromatography equipment were varied until separations between the components were observed. To validate this method, pure compounds of hexadecane, nC16 (0.765 mg) and undecane, nC11 (0.733 mg) were used. Interestingly, the elution time of nC16 was in accordance with that obtained for nC16 from the standard mixture of alkane. It was observed that the elution time of nC11 was between the elusion times for nC10 and nC12. The significance of these findings is that the proposed method can be used to identify a wide range of hydrocarbons in a mixture, which can be applied in environmental remediation of contaminated soils as hydrocarbons can be clearly and distinctively separated and identified.

Mycotoxins are secondary toxic compounds produced by fungi of the Aspergillus, Fusarium and Penicil lium species during secondary metabolism and they pose a major threat to humans and animals. Estimation of myco toxin exposure by measuring contamination of food coupled with dietary intake questionnaires has been improved by the availability of biomarkers of exposure, which allow more accurate and objective exposure measurements. Biomarker assessment in biological fluids has greatly contributed to elucidating the mechanism of health impairments attributable to these toxic compounds and to studying their pharmacokinetics. The analytical methods for the determination of single mycotoxin exposure biomarkers include enzyme linked immunosorbent assay (ELISA), high performance liquid chro matography (HPLC)-fluorescent detection and Gas chromatography (GC)-electron capture, and HPLC mass spectrom etry. Recent advances in liquid chromatography tandem mass spectrometry (LC-MS/MS) have revolutionised mycotoxin biomarker assessment through the analysis of multiple mycotoxins in one sample injection. Despite these current de velopments, efforts still need to be made towards further improvements in sampling procedures, inter-laboratory quality assurance and development of internal standards to ensure appropriate detection of biomarkers.

Heuristic reasoning is used to deduce Fuzzy Decision Variables that could give rise to unforeseen risk in a proposed construction project for a selected client. The case study of some selected projects was undertaken to determine the sources of unforeseen risks in the domain and deduce the impact of the unforeseen risks that could occur in the domain of projects. Fuzzy set analysis was utilised to calculate the likely impact of the risk of unknown unknown. The work items which were unforeseen in the projects included additional foundations, burglar-proofing to windows, omission of work items, additional fixtures, builder’s work, additional external works, additional electrical installations, additional mechanical installations, etc. The likely consequence of the occurrence of the risk of unknown unknown in a domain could be estimated as a fuzzy number. The magnitude of the likely consequence could be obtained by converting the fuzzy value into a crisp value. The concept of Fuzzy Decision variables could be utilized in the identification of events that could lead to unforeseen risk; and fuzzy set analysis could be used to estimate the impact of the risk due to unforeseen events.

During wet and dry season of 2012 with a view of evaluating the spatial variations of the water quality. Water quality samples were transported to the laboratory in samples bottle pre-washed with HNO3. All samples were stored in ice bottle, preserved at 4º C and subsequently analyzed using laboratory standard methods. Discriminant analysis revealed data reduction and pattern recognition by revealing only five parameters with (p <0.05) affording 91.67% and 93.06% correct assignation for stepwise forward and backward modes of discriminant analysis respectively. Factor analysis revealed that most of the variations of surface water at Kano River profile are explained by salinity, conductivity, 15 pH, TDS, and temperature with 31.6% variability. Multiple linear regression models identified the contribution of each 16 variable with significant values of r = 0.894, R2 = 0.800, (p < 0.05).

This study demonstrated how artificial intelligence (AI) tool (Copilot) was used to facilitate the design and materials selection in order to conceptualise, design and prototype a mechanical Spinner System intended to facilitate practicing and gamification of domain-based systems thinking. Domain-based systems and systematic thinking pro posed by Dr Chukwuma Ogbonnaya, which can be applied for individual or group thinking activities, includes seven domains (Object, Process, Time, Place, People, Reason, and Specific domains). The Spinner prototype was created using AI-facilitated design process, computer aided design optimisation using NX and additive manufacturing. Integrat ing Copilot into the product development process reduced the cognitive costs as the large language model provided an opportunity for co-creativity and co-production of a quality prototype, realised within a short lead time and at a low cost. Overall, the Spinner offers opportunities for creating activities to aid collaborative brainstorming, co-creativity, co-anal- ysis and gamification of teaching and learning statistics and probability.