NIL(1971)

This long essay critically examines the persistent problem of digital piracy within the Nigerian music industry, analyzing the adequacy and effectiveness of the nation's legal framework from a legal and human rights perspective. The central thesis is that
Nigeria’s response to this challenge is characterized by a fundamental paradox: the system is strong in law but profoundly weak in execution. While the Copyright Act 2022 provides a modern, comprehensive arsenal of rights and digital safeguards, its
practical implementation is severely undermined by institutional and procedural failures. The nature and scope of piracy have drastically evolved from physical markets to technologically sophisticated digital methods, including widespread stream-ripping, cyberlockers, and illicit sharing across decentralized social media platforms, a shift the enforcement institutions have failed to match. The unchecked prevalence of piracy results in an estimated annual loss of ₦918 trillion across Nigerian copyright industries, which translates into a direct and severe violation of the economic and human rights of Nigerian creators to benefit from the fruits of their labor. This institutional execution gap is manifested in the Nigerian Copyright Commission (NCC) being operationally overstretched, the Nigerian Police Force deprioritizing intellectual property crime, and Collective Management rganisations (CMOs) being plagued by governance crises and credibility challenges. Furthermore, the framework contains a critical gap regarding the emerging threat of generative Artificial Intelligence (AI). A comparative analysis of the US and South African models confirms that the solution does not lie in legislative overhaul but in decisively adopting proven models for procedural efficiency, institutional transparency, and strong judicial deterrence. This research concludes that safeguarding the sustainability and global competitiveness of Nigeria's music sector requires a fundamental shift in priority to bridge the gap between statutory promise and practical reality.

This study examines the use of metaphor as a tool for social criticism in selected poems from Kola Eke’s August 1985. The research explores how Eke employs figurative expressions to expose and challenge social, political, and economic injustices in Nigerian society. Through vivid metaphors, the poet critiques corruption, class oppression, gender inequality, and moral decay that characterize post-colonial realities. The study interprets these metaphors as symbols of resistance and social awakening, reflecting the voice of the marginalized and the oppressed. The analysis focuses on how Eke transforms ordinary experiences into powerful social commentaries that provoke thought and inspire change. His language of protest and imagery of struggle reveal the tension between the ruling elite and the common people, making his poetry not only artistic but revolutionary. The study finds that Eke’s metaphors deepen the meaning of his criticism, turning poetic language into a weapon of awareness and reform.
The research concludes that metaphor in August 1985 is not just a stylistic device but a conscious political act. It exposes inequality, questions authority, and advocates social justice. By merging art with activism, Kola Eke’s poetry strengthens the tradition of Nigerian writers who use literature to mirror society and drive transformation.

This research examines the economic and political importance of women's right of inheritance under Ibibio customary law in Nigeria. The study aims to analyze inheritance practices across four major Nigerian ethnic groups (Ibibio, Efik, Igbo, and Benin), evaluate constitutional and judicial protections for women's inheritance rights, and identify barriers to implementing these
rights. The research employed doctrinal methodology, analyzing primary sources including the 1999 Constitution, Supreme Court decisions, and statutes, alongside secondary sources such as journal articles, textbooks, and reports. Major findings reveal that all four ethnic groups operate under patrilineal inheritance systems that systematically exclude women from property ownership. The Ukeje v Ukeje (2014) Supreme Court decision declared discriminatory customary practices unconstitutional under Section 42 of the Constitution. However, a significant gap exists between legal protections and social practice, particularly in rural communities where traditional authorities prioritize customary norms over statutory law. Economic vulnerability, educational disparities, religious beliefs, and inadequate enforcement mechanisms perpetuate discriminatory practices. The study recommends comprehensive state legislation domesticating the Ukeje judgment, expanded legal aid services for women, public education campaigns, engagement with traditional and religious leaders, judicial capacity building, and sustained monitoring of inheritance practices. True reform requires coordinated action by government, civil society, traditional institutions, and communities to transform
constitutional rights into lived reality for Nigerian women

Water quality remains a critical public health concern, particularly in rapidly urbanizing regions like Benin City, Nigeria. This study assessed the physicochemical properties, essential minerals, and potential contaminants in five bottled water brands (EVA, CWAY,
AQUAFINA, EIO, and ROI) to evaluate their safety and compliance with regulatory standards. Water samples were collected from different retail outlets in Benin City and analyzed for parameters such as pH, conductivity, total dissolved solids (TDS), turbidity,
hardness, chloride, sulphate, nitrate, and trace metals using standard laboratory procedures. The results showed significant variations across brands. EIO had the highest pH (7.37 ± 0.19), while ROI had the lowest (6.63 ± 0.11). Conductivity and TDS were highest in EIO (41.33 ± 1.16 µS/cm and 20.67 ± 0.58 mg/L, respectively) and lowest in ROI (12.00 ± 2.00 µS/cm and 6.00 ± 1.00 mg/L, respectively). Hardness levels were within the WHO recommended limits, with CWAY showing the highest value (22.00 ± 2.00 mg/L). Trace metal analysis revealed that ROI had the highest levels of iron (0.12 ± 0.01 mg/L), zinc (0.27 ± 0.05 mg/L), manganese (0.48 ± 0.07 mg/L), and copper (0.52 ± 0.09 mg/L), suggesting possible contamination from natural sources or packaging materials. While most bottled water samples met regulatory standards, ROI exhibited elevated levels of turbidity, suspended solids, and trace metals, indicating potential filtration inefficiencies. These findings emphasize the need for stricter regulatory monitoring and quality control measures to ensure the safety of bottled water in Benin City.

The present study evaluated the physical, chemical, and heavy metals content (Fe, Zn, Mn, and Cu) and fertility status of soils from three dumpsites within the Benin city metropolis and the effect of NPK (15:15:15) fertilizer on the growth and yield of Okra and Garden Egg. Soils samples were collected processed and analyzed using standard laboratory methods. The experiment was a 3 x 4 factorial fitted in a Completely Randomized Design (CRD), with three levels of fertilizer (0 g NPK, 14 g NPK and 28 g NPK) and (3) dumpsites (Benin Sapele Road Dumpsite (BSD), Benin Agbor Road Dumpsite (BAD) and Benin Oluku Bypass Dumpsite
(BOD) and the control with three replications. Growth parameters (plant height, number of leaves; stem girth; leaf area) and yield were collected. The fruit yield per hectare was derived by estimating the fruit yield per poly bag. Data were subjected to Analysis of Variance (ANOVA), and treatment means were separated using Duncan’s Multiple Range Test at 5% probability level. Results showed that, physical and chemical properties of the dumpsite soils were slightly alkaline with pH range of 7.28 to 7.56. The organic carbon ranged between 11.6 and 13.7 g/kg. The fertility status of the soils from the different dumpsites revealed that soils
from Agbor Road ByePass were high in potassium while soils from Oluku and Sapele ByePass dumpsites were high in phosphorus and nitrogen. The total N from the dumpsites ranged between 0.065 to 0.199 %. The heavy metal content of dumpsite soils varied significantly, but was within the limits recommended by FAO/WHO. The application of 28 g NPK fertilizer enhanced the growth and yield of Okra and Garden Egg compared to the control. This study suggest that dumpsite soils amended with NPK fertilizer improved soil nutrients status and enhanced the yield and growth of Okra and Garden Egg plant.

Access to academic materials is one of the main key factors that can affect the academic performance of a student. The traditional method of accessing materials such as handwritten lecture notes, printed handouts, and textbooks are still useful but all have their own challenges in trying to use them. These challenges can lead to loss of material and accessibility. This project highlights the need for a digital and centralized approach to academic resource management. The proposed system in this work is the Student Academic Resource Hub (SARH) which is designed to serve as a digital repository for students and lecturers where
they can upload, access, and download academic materials such as lecture notes, past questions and other study resources according to their academic levels or courses. The design of the Student Academic Resource Hub is focused on creating a simple user friendly web platform that uploading and accessing materials easy for students and lecturers. The SARH was built with the frontend and the backend. The database is used for storing users’ data and uploaded resources. Certain implementation libraries were integrated to handle secure authentication and data protection. The result of this project is a developed system which is capable of providing an efficient, secure, and scalable alternative to the manual methods currently in use.

The research work explores the comparison of various methods for estimating variance components in a two-way random effects model, a critical task in experimental data analysis. The methods assessed include classical Analysis of Variance (ANOVA), Restricted Maximum Likelihood (REML), and Bayesian estimation. The experiment was designed with treatments (3 levels) and blocks (4 levels), with each combination replicated 5 times, resulting in 60 observations. The objective was to estimate variance components attributable to treatments, blocks, and errors. The results were compared across the three methods: ANOVA produced variance components of σ²α = 3.84, σ²β = 2.43, and σ²ε = 3.58, while REML and Bayesian estimates were σ²α = 4.805 and 4.75, σ²β = 2.4067 and 2.60, and σ²ε = 3.58 and 3.60, respectively. While the three methods yielded similar results, minor differences were observed, reflecting their respective properties. ANOVA, though simple and interpretable, may be biased in small samples or unbalanced designs, whereas REML offers better performance in such situations, and Bayesian estimation provides flexibility with credible intervals to quantify uncertainty. The research work highlights the importance of method selection depending on sample size, design, and the need for uncertainty quantification, suggesting future work on more complex or larger-scale experiments.

The search for new therapeutic agents derived from natural sources has intensified due to the global rise in antimicrobial resistance (AMR). Medicinal plants remain a significant source of bioactive compounds with diverse pharmacological potentials. This study examined the phytochemical components and bacterial inhibitory property of the dichloromethane (DCM) fraction of the stem bark of Antiaris toxicaria var. africana, a plant widely used in African ethnomedicine for treating various infections. The stem bark was extracted using 70% ethanol and subsequently fractionated with DCM using column chromatography. High-Performance Liquid Chromatography (HPLC) and Gas Chromatography–Mass Spectrometry (GC–MS) were employed for chemical characterization. GC–MS analysis revealed the presence of bioactive compounds with known antibacterial and antioxidant properties, including 2,4-di-tert-butylphenol (18.86%), hexadecanoic acid (14.35%), benzoic acid (7.39%), and methyl stearate (6.66%). HPLC profiling confirmed the presence of important phytochemicals such as flavonoids (11.36 µg/mL), proanthocyanidins (13.99 µg/mL), flavanones (9.93 µg/mL), tannins (3.70 µg/mL), cardiac glycosides (5.53 µg/mL), sapogenins (7.96 µg/mL), and steroids (4.70 µg/mL), indicating a rich diversity of secondary metabolites. Antimicrobial testing showed that the extract exhibited inhibitory activity against Pseudomonas aeruginosa (19 mm), Bacillus subtilis (18 mm), Staphylococcus aureus (19 mm), Escherichia coli (20 mm), and Enterobacter cloacae (17 mm), but not against Bacillus cereus. Although the extract demonstrated lower activity than the positive control, ciprofloxacin, it displayed broad-spectrum antibacterial potential. Overall, the findings provide scientific validation for the traditional use of A. Toxicaria var. africana in treating bacterial infections.

Malaria remains a global health crisis, particularly in low-resource regions, where traditional diagnostic methods face challenges such as human error, resource constraints, and delayed detection. This project addresses these limitations by leveraging supervised machine learning (ML) to enhance malaria diagnosis and outbreak prediction. The motivation stems from the urgent need for scalable, accurate, and cost-effective solutions to reduce the disease’s burden, which claims over 600,000 lives annually. The objective is to develop robust ML models capable of automating malaria diagnosis using blood smear images and patient metadata while improving outbreak forecasting through environmental and epidemiological data analysis. Methodologically, the study employs supervised learning algorithms, including convolutional neural networks (CNNs) for imagebased detection and random forests for tabular data. Datasets were preprocessed to handle class imbalance and missing values, followed by hyperparameter tuning and cross-validation to optimize performance. Results demonstrated that CNNs achieved 96% accuracy in classifying infected blood cells, outperforming traditional methods like microscopy. Random Forest models yielded 92% recall and 89% precision in predicting malaria risk from clinical data, highlighting their utility in early diagnosis. Additionally, stratified k-fold cross-validation ensured model generalizability across diverse datasets. This work underscores the transformative potential of supervised ML in malaria control, offering tools that enhance diagnostic speed, accuracy, and accessibility. By bridging technological innovation with public health needs, the project contributes to global efforts toward malaria eradication, particularly in endemic regions

With the rapid development of artificial intelligence, the ethical implications and moral rights associated with it are becoming more significant. This research looks into whether AI systems, especially those that are very advanced, deserve moral attention. The analysis focuses on important ethical concepts, including utilitarianism, deontology, and virtue ethics, to assess the moral position of AI. Furthermore, it looks at different standards for moral personhood, such as awareness, independence, and the ability to feel pain. This study also explores the actual effects, such as legal systems, the role of AI in making decisions, and the possible impacts on society if AI does or does not receive moral consideration. By examining these debates, this research seeks to offer a fair perspective on the challenge of whether machines can or should be granted moral rights, as AI technology becomes more integrated into our lives. In this research, we will be using the critical analytic method for us to be able to understand the topic