National Universities Commission

There are numerous victims and consequences of corruption and money laundering (ML) in many developing countries (DCs). This article reiterates the conspicuous symbiotic relationship between corruption and ML, making it difficult to isolate them in financial crime. The article uses a doctrinal approach and relies on both primary and secondary documents in the analysis. Some of the documents are inclusive of but not limited to the United Kingdom Bribery Act 2010, the United States Foreign Corrupt Practices Act 1977, the Nigerian Economic and Financial Crimes Commission Act 2011 and Independent Corrupt Practices and other Related Offences Commission Act 2000 and some pronouncements of the World Bank. It is incontestable that corruption and ML have devastating domino implications in DCs, particularly Nigeria, and the time is now ripe to increase efforts towards tackling this problem which has a strong potential to become even more serious. This article seeks to highlight the problem of ML in DCs and bolster efforts to reduce it.

The advent of quantum computing poses a significant threat to the cryptographic foundations that secure critical infrastructure information systems, including energy grids, transportation networks, healthcare systems, and financial services. Conventional public-key cryptographic schemes such as RSA and elliptic curve cryptography are vulnerable to quantum attacks, necessitating a paradigm shift toward post-quantum secure design principles. This review paper examines emerging post-quantum cryptographic frameworks and their role in strengthening detection and mitigation mechanisms within critical infrastructure environments. It systematically analyzes post-quantum algorithms, hybrid cryptographic models, and quantum-resilient authentication schemes, emphasizing their integration into intrusion detection systems, anomaly detection frameworks, and secure communication protocols. Additionally, the paper explores quantum-aware threat models, resilience-oriented system architectures, and adaptive mitigation strategies that enhance system survivability against both classical and quantum-enabled cyber threats. Key challenges including computational overhead, legacy system compatibility, scalability, and regulatory compliance are critically discussed, alongside ongoing standardization efforts and implementation case studies. By synthesizing current research and industry practices, this review provides a comprehensive roadmap for designing, deploying, and managing post-quantum secure detection and mitigation frameworks that ensure the long-term resilience, reliability, and trustworthiness of critical infrastructure information systems in the quantum era.

This paper systematically reviews the role of STEM edupreneurship in addressing Sustainable Development Goals (SDGs), highlighting its contributions and identifying future directions. STEM edupreneurship, which merges STEM education with entrepreneurial ventures, plays a crucial role in fostering innovation, economic growth, and sustainable development. This review examines the impact of STEM edupreneurship on various SDGs, particularly those related to quality education, gender equality, decent work and economic growth, industry innovation and infrastructure, and climate action. Through an extensive analysis of existing literature and case studies from diverse global contexts, the study reveals significant contributions of STEM edupreneurship, such as enhancing educational outcomes through innovative technologies, promoting gender equality by empowering women in STEM fields, creating job opportunities, driving industrial innovation, and developing sustainable technologies. The review also identifies key challenges, including limited access to resources, inadequate policy support, and barriers for underrepresented groups. To address these issues, the study proposes strategic recommendations, such as enhancing policy frameworks, improving resource accessibility, fostering collaboration, promoting diversity, and supporting ongoing research and innovation. This research aims to provide a comprehensive framework for policymakers, educators, and entrepreneurs to leverage STEM edupreneurship as a catalyst for achieving the SDGs, ensuring a sustainable and inclusive future. The findings underscore the critical importance of integrating STEM education with entrepreneurial initiatives to meet global sustainability targets effectively.

The Republic of Guinea, characterized by significant eco-climatic diversity and four major natural regions, has a population heavily reliant on natural resources. Rainfall plays a crucial role, influencing not only agriculture and water availability but also the dynamics of bushfires. These fires are a recurring phenomenon, linked to human activities (slash-and-burn agriculture, hunting, and pasture management) and climatic conditions. However, few studies have thoroughly explored the relationship between rainfall patterns and bushfires, despite these interactions being crucial for the sustainable management of ecosystems and the prevention of environmental risks. The overall objective of this study is to analyze the spatio-temporal impact of rainfall indices on wildfire dynamics in the Republic of Guinea, in order to make a dual scientific and operational contribution: understanding climatic mechanisms and supporting public policy. The data used come from satellite rainfall estimates from the CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data) product, covering the period 2010 - 2018, as well as wildfire data from the AVHRR-LTDR Burned Area Grid v1.1 product, allowing for the assessment of the spatial and temporal dynamics of burned areas and the intensity of wildfires. The methodology is based on the calculation of monthly and annual climatology, the analysis of standardized anomalies, and the correlation between rainfall and burned areas. The results show a clear inverse relationship between rainfall and wildfires. Burned areas peak in January-February and November-December, periods of extreme drought, and almost completely disappear during the rainy season (June-September). Spatially, fires are more intense in the east and southeast during the dry season, while they become almost nonexistent during the wet periods. Standardized anomalies confirm a negative correlation between rainfall and burned areas, although this correlation is not statistically significant over the period 2010–2018. Finally, this study reveals the crucial role of rainfall patterns in the seasonal and spatial regulation of wildfires in Guinea. It highlights the need to integrate rainfall indices into prevention and adaptation strategies in the face of climate change, while also taking into account human activities.

Youth unemployment continues to pose a major challenge in Nigeria despite sustained government initiatives promoting entrepreneurship and empowerment. The National Youth Service Corps (NYSC) established the Skill Acquisition and Entrepreneurship Development (SAED) programme to provide graduates with practical skills that can stimulate job creation. Earlier studies have often examined entrepreneurial intentions rather than actual job creation after participation in SAED or the joint influence of demographic attributes and graduate attitudes on such outcomes. This study examined how age, gender, marital status, educational qualification, and graduate attitude relate to job creation among Nigerian corps members. A survey research design was used to gather data from more than nineteen thousand NYSC members who served between 2012 and 2021. Data were obtained electronically through social media platforms and analysed with descriptive statistics and logistic regression, while a machine learning model was used to assess the strength of predictive accuracy. The results showed that graduate attitude, educational qualification, and marital status were significant predictors of job creation, whereas age and gender were not. The model performed effectively, confirming the reliability of the findings. This study contributes to current understanding of graduate employment outcomes in Nigeria and provides useful evidence for improving entrepreneurship education and policy measures aimed at addressing youth unemployment.

Accurate reconstruction of Respiratory Virus Transmission Networks (RVTNs) depends heavily on the reliability of RT-PCR results, which are directly influenced by upstream RNA extraction processes. This study evaluates three commonly used extraction methods silica column, magnetic bead–based, and rapid lysis to determine their impact on RT-PCR sensitivity, Ct variability, viral load estimation, and downstream RVTN model stability. Experimental analyses showed that magnetic bead extraction consistently produced the highest RNA yield, lowest Ct variability, and most stable amplification performance, resulting in minimal propagation error within transmission modeling. Silica column extraction demonstrated moderate reliability, while rapid lysis produced substantial Ct variability and high diagnostic uncertainty, significantly weakening network coherence and transmission link detection. By quantifying how extraction-induced errors propagate into epidemiological modeling outputs, the study demonstrates that optimized RNA extraction is critical not only for diagnostic accuracy but also for producing reliable and interpretable transmission networks. These findings underscore the need for standardized extraction practices and improved quality control frameworks to strengthen outbreak response systems and enhance public health decision-making.

إذا كانت الموارد البشرية والطبيعية التي يتمتع بها بلد ما هي مقياس عظمته وتطوره، فلا جدال في أن نيجيريا مقدر لها أن تكون عظيمة. ومع ذلك، ففي النظام الاقتصادي العالمي اليوم، تقع نيجيريا بشكل واضح في محيط الهامش على الرغم من مواردها الوفيرة. ويُعزى ذلك إلى عوامل غير أخلاقية مختلفة مثل سوء إدارة الموارد والاختلاس واسع النطاق الذي أعاق تنميتها وساهم في تخلفها الاقتصادي. تستكشف الورقة هذه العوامل السابقة، وتعتمد على مصادر بيانات أولية وثانوية. ومن منظور إسلامي، تجادل الورقة بأن الممارسات غير الأخلاقية التي يحرمها الإسلام بشدة قد أصبحت طبيعية في البيئة الاقتصادية والاجتماعية والسياسية في نيجيريا، مما يؤدي إلى تفاقم المشاكل الاقتصادية للبلاد مع ضعف احتمالات الخلاص. كما أن من الملاحظ أنه لم يتم إيلاء اهتمام جاد لكيفية تقويض هذه العوامل للتنمية. بالاستناد إلى بعض الآيات القرآنية والأحاديث النبوية، تُحلل هذه الورقة كيفية توليد الإيرادات واستخدامها وتوجيهها نحو التنمية الاقتصادية. وتخلص إلى أن الممارسات الاقتصادية في نيجيريا، في معظم الحالات، تُخالف المبادئ الأخلاقية الإسلامية للاقتصاد، على الرغم من أن المسلمين يُشكلون الأغلبية الديموغرافية. هذه الأخلاقيات، إذا ما طُبّقت، لا تعود بالنفع على المسلمين فحسب، بل على البلاد أيضًا. ولتحرير البلاد من براثن التخلف، تُوصي هذه الورقة بضرورة دمج الأخلاق الإسلامية في الأنشطة الحكومية، لا سيما في سنّ القوانين، ووضع الميزانيات، وصياغة السياسات، وتنفيذها، مما سيُسهم هذا بشكل كبير في إصلاح الاقتصاد وتعزيز التنمية.

This study introduces an innovative ensemble learning approach for stock direction classification and prediction. The methodology enhances accuracy through strategic base learner selection, hyperparameter optimisation using GridSearchCV, and hybrid ensemble techniques. Leveraging a diverse set of machine learning models—including Logistic Regression (LR), Random Forest (RF), Decision Trees (DT), Support Vector Machines (SVM), K-Nearest Neighbors (KNN), AdaBoost, and Lasso-LSTM—this research compares single classifiers, hybrid ensembles, and a Voting-based classification model. Using S P 500 index data spanning from June 8, 2016, to September 6, 2023, the study evaluates classification performance across multiple metrics: accuracy, precision, recall, F1 score, AUC, and sensitivity. Statistical analysis, including Kruskal–Wallis tests and Dunn’s post hoc comparisons, reveals significant performance variations among models. The results indicate that the SVC + LR + RF + VOTING ensemble achieves the highest accuracy (95.8%) and AUC (0.97), followed closely by AdaBoost (ADAB) with an accuracy of 94.2% and AUC of 0.96. These findings underscore the superiority of ensemble classification methods over individual classifiers in stock market prediction. This research provides practical insights for financial decision-makers by addressing key gaps in the existing literature and emphasising the importance of diverse evaluation metrics in model assessment. The study establishes a solid foundation for classification-based predictive modelling in stock market analysis and encourages further research into diverse datasets and advanced classification algorithms to enhance model generalisation.

Corporate environmental practices are facing more and more scrutiny from stakeholders as a result of growing ecological concerns that affect not just local communities but the planet as a whole. To this end, this paper examines the moderating role of audit committees on the relationship between diversity-in-board and environmental reporting of Listed Manufacturing Companies in Nigeria (LMCN). The paper employed an ex-post facto research design and data collected from annual reports of thirty-six LMCN were analyzed using descriptive statistics and linear multiple regression techniques. Findings suggest that while diversity-in-board positively influenced environmental reporting, this effect became statistically significant when moderated by the audit committee. This underscores the importance of audit committee crucial role as a moderator in influences that impact of diversity-in-board and ensures adequate disclosure of environmental information in the annual reports of listed manufacturing companies in Nigeria. The study recommends among others that Financial Reporting Council (FRC) of Nigeria should no longer allow environmental disclosure in Nigeria to be voluntary, but make it compulsory using ISO 14031 reporting guideline as a common standard among listed manufacturing firms in Nigeria for the purpose of attaining detailed environmental disclosures and easy comparison of such disclosures among firms. Also, encourage regulators to regularly review corporate governance codes to strengthen diversity provisions for more credible stakeholder reporting. Additionally, manufacturing firms should focus on boosting the effectiveness of their audit committees to enhance environmental stewardship, which will in turn improve corporate brand image and reputation.

There are numerous victims and consequences of corruption and money laundering (ML) in many developing countries (DCs). This article reiterates the conspicuous symbiotic relationship between corruption and ML, making it difficult to isolate them in financial crime. The article uses a doctrinal approach and relies on both primary and secondary documents in the analysis. Some of the documents are inclusive of but not limited to the United Kingdom Bribery Act 2010, the United States Foreign Corrupt Practices Act 1977, the Nigerian Economic and Financial Crimes Commission Act 2011 and Independent Corrupt Practices and other Related Offences Commission Act 2000 and some pronouncements of the World Bank. It is incontestable that corruption and ML have devastating domino implications in DCs, particularly Nigeria, and the time is now ripe to increase efforts towards tackling this problem which has a strong potential to become even more serious. This article seeks to highlight the problem of ML in DCs and bolster efforts to reduce it.