Dialogic STEM Journal
- EISSN 3141-2122
- Open access
- 9 articles
- Registered 14 April 2026
Dialogic STEM Journal welcomes scientifically valid, reproducible and practically relevant work across the full breadth of STEM. It is especially suited to work that crosses disciplinary boundaries and turns specialist knowledge into broader systems insight.
Aims and scope
What the journal publishes
Dialogic STEM Journal welcomes scientifically valid, reproducible and practically relevant work across the full breadth of STEM. It is especially suited to work that crosses disciplinary boundaries and turns specialist knowledge into broader systems insight.
Beyond conventional disciplinary submissions, the journal invites models, simulations, case studies, experimental research, methodological advances and interdisciplinary applications that transfer across fields.
- Publishing model
- Fully open access, in line with UNESCO recommendations on open science and visibility.
- Navigation
- AI-assisted classification helps readers move across sections, subsections and interdisciplinary connections.
Focus areas
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Science
Peer-reviewed research, methods and practical applications within science and its intersections.
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Technology
Peer-reviewed research, methods and practical applications within technology and its intersections.
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Engineering
Peer-reviewed research, methods and practical applications within engineering and its intersections.
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Mathematics
Peer-reviewed research, methods and practical applications within mathematics and its intersections.
What we publish
- Original research articles
- Review articles
- Short communications and letters
- Methodologies and technical notes
- Case studies and applied reports
- Editorials and commentaries
Published articles
Read the latest research
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Volume 1, issue 1 · 2026
Integrated Evaluation of Protective Effects of Cucurbita ficifolia Seed Extract on Systemic Biochemicals in a Dihydrotestosterone Estradiol Valerate Induced Benign Prostatic Hyperplasia in Rats
Achi Ngozi Kalu, Uhuo Emmanuel Nnaemeka, Onyeabo Chimaraoke, Alaebo Prince Ogochukwu, Silas Andrew Chibueze, Chris-Eze Chidinma Esther, Obinna-Obasi Kenechi Lilian, Martins Favour, Marcus Janet Ekemini, Olisa Stephanie Onyinyechi, Ono Blessing Kalu, Ogbaegbe O. and Ohaeri Obioma Christopher
Benign prostatic hyperplasia (BPH) is an age-associated, non-malignant enlargement of the prostate characterized by complex interactions as a result of hormonal imbalance, oxidative stress, inflammation, and metabolic dysfunction. Beyond localized prostatic changes, BPH is increasingly associated with systemic biochemical alterations, including disturbances in electrolyte homeostasis. This study investigated the protective effects of methanol extract of Cucurbita ficifolia seeds on antioxidant, serum electrolyte balance and associated biochemical parameters in a dihydrotestosterone estradiol valerate (DHT–EV) induced BPH model in male Wistar rats. BPH was induced via combined administration of DHT and estradiol valerate, followed by oral treatment with graded doses of C. ficifolia seed extract or finasteride for 28 days. Serum electrolytes prostate-specific antigen (PSA), hormonal and hematological indices, Liver function parameters, lipid profile, antioxidant status, renal function markers, and relative organ weights were evaluated. Hormonal induction resulted in significant prostate enlargement, increase in relative weight of kidney and prostate, elevated PSA levels, and marked disturbances in electrolyte balance, oxidative status, WBC and Platelet (PLT) counts compared with normal controls. Treatment with C. ficifolia extract significantly attenuated prostate enlargement, reduced PSA levels, restored electrolyte homeostasis, prostate and kidney weight, and improved antioxidant, lipid, Hematological and renal function parameters in a dose-dependent manner. The result also showed no significant differences (p>0.05) in liver, testis, total protein, HDL, RBC, PCV, and Hb levels in all the groups with slightly moderate changes in albumin and globulin. However, significant changes were observed in WBC and Platelet (PLT) counts in diseased control groups which was restored after the administration of the extract of Cucurbita ficifolia seed. These findings demonstrate that Cucurbita ficifolia seed extract confers multitarget protective effects against BPH induced systemic and prostatic alterations, highlighting its potential as a promising phytotherapeutic agent for the management of benign prostatic hyperplasia. -
Volume 1, issue 1 · 2026
Measuring Human Mycotoxins Exposure Using Biomarkers - A Review
Ukpai Eze
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. -
Volume 1, issue 1 · 2026
Climate Change Resilience and Adaptation Pathways for Africa’s Agricultural Sector
Francis Bisong, Asuquo Okon, Ekaba Bisong and Jackson Akor
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 aggregated and country-specific insights. Responses to extreme events like droughts are often autonomous, driven by indigenous 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 effec-tiveness. 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 rec-ommends scaling up and promoting the most promising adaptation practices to strengthen climate resilience across Africa’s agricultural landscapes. -
Volume 1, issue 1 · 2026
Design, Prototyping and Testing of Mechatronic Spinner for Domain-Based Systems Thinking
Chukwuma Ogbonnaya and Chagary Ranjan
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. -
Volume 1, issue 1 · 2026
Dynamic Differential Games of Nuclear Proliferation and Preemption under Uncertainty
Innocent Adinebo Katule and Akindele Michael Okedoye
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. -
Volume 1, issue 1 · 2026
Gas Chromatography Method Development and Validation for Separating Non-polar Volatile Hydrocarbons
Perpetual Eze-Idehen
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. -
Volume 1, issue 1 · 2026
Using Artificial Intelligence Tool to Facilitate Design and Materials Selection Processes
Chukwuma Ogbonnaya, Callum Cockcroft and Orji Rex Ogbonnaya
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. -
Volume 1, issue 1 · 2026
Statistical Characterization of River Water Physico-Chemical Parameters in a Highly Heterogeneous Land Use Area Along River Kano
Adamu Mustapha, Hamza Isiyaka Ahmad, Suleiman Mukhtar and Nura Isyaku Bello
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. -
Volume 1, issue 1 · 2026
The Application of Heuristic Reasoning in the Risk Analysis of Unforeseen Risk Events in Construction Projects in Nigeria
Ibrahim Yakubu
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.