Dialogic STEM Journal

The nuclear proliferation problem is an important issue in the field of nuclear strategy, characterized by dynamic in-vestments 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. Specif-ically, we propose a comprehensive differential game model for nuclear strategy problems, focusing on the interaction 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 progressively 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 in-formation, 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 pre-venter 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 im-portant 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.

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, Fussarium and Penicillium species during secondary metabolism and they pose a major threat to humans and animals. Estimation of mycotoxin exposure by measuring contamination of food coupled with dietary intake questionnaires has been improved by the availability of bi-omarkers 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 chromatography (HPLC)-fluorescent detection and Gas chromatography (GC)-electron capture, and HPLC mass spectrometry. 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 developments, 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.

This study demonstrated how Copilot, an artificial intelligence (AI) tool, was used to facilitate the design and materials selection to conceptualise, design and prototype a mechanical spinner intended to facilitate practicing and gamification of domain-based systems thinking. Domain-based systems and systematic thinking proposed 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 software and additive manufacturing. Integrating 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 and low-cost prototype within a short lead time. Overall, the spinner offers opportunities for creating activities to aid collaborative brainstorming, co-creativity, co-analysis and gamification of teaching and learning statistics and probability.

River Kano is prone to water pollution due to its proximity to many pollution sources like domestic wastewater, industrial effluent discharge, solid waste disposal and agricultural runoff. Surface water samples were collected at the upper, middle and lower profile of Kano River during wet and dry season of 2012 with a view of evaluating the spatial variations of the water quality to investigate the sources apportionment of river water quality and to identify the emerging contaminants. 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, pH, TDS, and temperature with 31.6% variability. Multiple linear regression models identified the contribution of each variable with significant values of r = 0.894, R2 = 0.800, (p< 0.05) which strongly suggest that salinity, conductivity, pH, TDS, and temperature are the primary controllers of water quality variation in Kano River Basin.

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 utilized 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, and additional mechanical installations. 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.

Climatic conditions in Africa are worsening with severe impacts on the agricultural sector. This study examines resilient adaptation pathways across seven African countries and highlights agroforestry, early warning systems, altered planting times, migration, alternative livelihoods, and forest fire control as promising strategies.

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 activities. To realise the Mechatronic Spinner with seven Questelligence domains (i.e. Objective, Place, People, Pro cess, Time, Reason and Specific domains) included steps such as ideas generation, hand sketching, detailed engineer ing design, design optimisations, circuit design, coding, prototyping and testing were implemented leveraging Lean and Agile Design and Rapid Prototyping using additive manufacturing. During testing, the prototype mechatronic spinner generated randomness at each spin, which makes it suitable for application for generating randomness of outcomes. The case of how the spinner can be used for teaching and learning probability and statistics based on the numerical feature of the spinner was instantiated. This device offers an opportunity to develop a wide range of models to practice creative and analytical thinking activities such as domain-based brainstorming, ideas generation and problem-solving.