NIL

Highway accidents are a significant concern worldwide, leading to substantial loss of life, property, and economic productivity. This study aims to conduct a comprehensive analysis of highway accidents by investigating their frequency, underlying causes, and exploring effective preventive measures. Through an extensive review of historical accident data, this research will assess key factors contributing to highway accidents, including human behavior, vehicle conditions, environmental influences, and road infrastructure. Special attention will be given to identifying accident-prone areas (blackspots) and determining the most common types of accidents, as well as the timeframes in which they frequently occur. To better understand the root causes of these accidents, the study will employ statistical analysis and machine learning techniques on data sourced from government databases and highway safety reports. The study will focus on critical factors such as driver error, vehicle malfunctions, poor road design, adverse weather conditions, and inadequate traffic management systems. It will also analyze the effectiveness of existing safety measures like traffic signals, road signage, and speed limits, while proposing new, data-driven interventions for improving highway safety. The expected results of this research include a clearer identification of high-risk areas and times for highway accidents, as well as the discovery of key accident causative factors. Based on these findings, the study will propose targeted solutions, such as enhancing road infrastructure, increasing public awareness campaigns on safe driving, implementing stricter vehicle inspection protocols, and adopting advanced traffic monitoring systems. Ultimately, the results are expected to provide actionable insights for policymakers and highway authorities to reduce accident rates and improve overall road safety.

In this project, I explored the spectral properties of the Kondo lattice model using MATLAB’s symbolic computation tools. By constructing and diagonalising a 9x9 Hamiltonian matrix, I analysed the interaction between conduction electrons and a magnetic impurity, a hallmark of the Kondo effect. The eigenvalue analysis revealed a non-degenerate ground state at (λ = 0) , representing a fully screened impurity spin, while higher energy levels indicated magnetic excitations within the system. Through this work, I developed a deeper understanding of how symbolic and numerical methods can be used to study strongly correlated electron systems. This project not only strengthened my grasp of quantum many-body theory but also enhanced my computational and analytical skills for future research in condensed matter physics.

This study investigates the use of guava leaf extract (Psidium guajava) as an organic corrosion inhibitor for low-carbon steel in a carbonic medium. Corrosion of steel remains a critical global issue, with its annual cost estimated to exceed $2.5 trillion, representing approximately 3.4% of the world’s GDP. This necessitates an environmentally friendly alternative to traditional toxic synthetic inhibitors. The research method involved preparing the extract and conducting corrosion tests on mild steel coupons (with a carbon content of less than 0.25%). Experiments were carried out in a 1M HCl acidic medium using techniques such as weight loss measurements, potential dynamic polarization, and EIS, across a temperature range of 25–60°C and a pH range of 2–6. The study focused on short-term exposure (up to 24 hours) to assess the initial inhibition efficiency. The guava leaf extract proved to be a highly effective inhibitor. Statistical validation via ANOVA established the model's significance with an extremely high Model F-value of 921.10 and a p-value of < 0.0001 for Inhibition Efficiency. The predictive power was robust, as indicated by a Predicted R² of 0.9945 being in reasonable agreement with the Adjusted R² of 0.9978 , and an Adequate Precision ratio of 79.032. Time and Temperature were confirmed as the only statistically significant model terms, suggesting the corrosion process is under kinetic control. The numerical optimization demonstrated that a near-maximum predicted efficiency could be achieved at the lowest inhibitor dosage, supporting the extract's high potency and cost-effectiveness. In conclusion, the guava leaf extract successfully performed as an environmentally sustainable corrosion inhibitor. The inhibition mechanism was determined to be chemisorption, driven by the active phenolic groups and aromatic rings in the extract, which form a compact protective barrier on the steel surface.

This study critically evaluates Immanuel Kant’s concept of space and time as presented in his Critique of Pure Reason, examining its implications in the context of human existence. Kant revolutionized metaphysics by proposing that space and time are not empirical realities existing independently of human experience, but rather a priori forms of intuition through which the human mind structures all sensory data. This transcendental idealism asserts that space and time are subjective conditions that make experience possible, rather than external entities. The study explores how Kant’s notion redefines human existence by situating individuals as active participants in the construction of reality, emphasizing the centrality of human cognition in shaping the phenomenal world. Through this evaluation, the research highlights the profound philosophical implications of Kant’s theory for understanding human perception, knowledge, and existence. It argues that Kant’s framework bridges the gap between empiricism and rationalism, providing a foundation for existential reflection on human limitations and possibilities within the bounds of perception. Ultimately, the study affirms that Kant’s concept of space and time remains crucial in understanding the human condition as one that is both finite and meaningfully engaged with the world of appearances.

This study explores David Humes skepticism and its implication for human knowledge. Emphasizing the challenges posed by his empirical approach of philosophy, Hume argues that all human understanding is rooted in sensory experience, yet he questions the validity of inferences made beyond immediate observation. His skepticism (extent) to concepts of causation induction, and the self-suggesting that our beliefs about the world are often unfounded. The study examines Humes critique of rationalism particularly his assertion that reason is subordinate to passion in guiding human 9 behavior. It also discusses the implications of human’s skepticism for epistemology, particularly the limitations of certainty in knowledge acquisition. By analyzing Humes contributions, the study highlights the enduring relevance of his philosophical inquiries in contemporary discussions about the nature and limits of human’s knowledge.

The increasing demand for flexible, affordable, and collaborative learning has created opportunities for digital platforms that support peer-to-peer skill exchange. This study focuses on the development of an online skill barter-based system for personalized competency matching using machine learning. The system enables users to offer and learn skills through direct exchange rather than monetary transactions. A K-Nearest Neighbor (KNN) algorithm was integrated with TF-IDF and Natural Language Processing (NLP) techniques to intelligently match users based on skill similarity, learning preferences, and availability. The platform was developed using Next.js and TailwindCSS for the frontend, with Supabase as the backend for authentication and data management. The system promotes inclusive and accessible learning by removing financial barriers while fostering collaboration and community growth. This research demonstrates that integrating machine learning into skill exchange platforms significantly enhances user experience, match accuracy, and trust in non-monetary, peer-driven learning environments.

This study assessed the knowledge of women of childbearing age regarding the causes, signs, barriers, and factors contributing to malnutrition among children under five years. Four research questions guided the study, focusing on maternal awareness of malnutrition causes, recognition of its signs, obstacles to applying nutritional knowledge, and factors that enhance understanding. The study adopted a descriptive survey design, as data were collected from a sample population with specific characteristics. The target population comprised women of childbearing age in the study area, and a total of 300 respondents were selected using a combination of random and purposive sampling techniques. A structured questionnaire consisting of relevant items was personally administered by the researcher, with instructions provided to ensure accurate responses. The findings revealed that women demonstrated a moderate level of knowledge regarding the causes of malnutrition (grand mean = 2.51) and its signs (grand mean = 2.53). While most respondents recognised inadequate feeding practices, lack of exclusive breastfeeding, stunted growth, and poor weight gain as indicators of malnutrition, gaps existed in awareness of poverty, repeated childhood illnesses, and maternal nutrition during pregnancy. Key barriers to applying nutritional knowledge included financial constraints, cultural beliefs, household responsibilities, limited access to health professionals, and inadequate health education programmes. Factors contributing to improved maternal knowledge included access to health professionals, participation in health education programmes, formal education, community-based campaigns, and media sources. The study concluded that although women of childbearing age have moderate awareness of malnutrition, cultural, economic, and educational limitations restrict the effective application of their knowledge. It is recommended that government and non- governmental organisations implement intensive maternal education programmes, community awareness campaigns, women’s empowerment initiatives, and media-based nutrition education to enhance maternal understanding and improve child nutrition outcomes.

This study examines the role of women in the French Revolution, focusing on Olympe de Gouges and her fight for women’s rights between 1789 and 1793. While the French Revolution championed the ideals of liberty, equality, and fraternity, these democratic promises largely excluded women, relegating them to the private sphere. Utilizing a historical and analytical research design, this project investigates how female activists resisted this marginalization. The study specifically analyzes Olympe de Gouges’ seminal 1791 document, The Declaration of the Rights of Woman and of the Female Citizen, which challenged the male-centric biases of the revolution’s founding texts. The findings reveal that despite facing political suppression and ultimate execution during the Reign of Terror, Gouges and her contemporaries successfully laid the foundational framework for modern feminism, political inclusivity, and gender equality. The study concludes that women were not mere passive observers but active political agents who shaped the radical discourse of the revolution. It recommends a continuous revision of historical narratives to fully integrate and acknowledge the contributions of women in global political struggles.

Cotton (Gossypium spp.) seeds, a primary by-product of the global cotton industry, are often underutilized but represent a potential source of valuable bioactive compounds. This study was designed to quantify the total phenolic content (TPC) and total flavonoid content (TFC) of dried cotton seeds to evaluate their potential for value-added applications. An aqueous extract was prepared from dried, powdered seeds, and the presence of phenols and flavonoids was confirmed using standard qualitative phytochemical screening. Total phenolic content was determined spectrophotometrically using the Folin-Ciocalteu method with tannic acid as the standard, while total flavonoid content was measured via the aluminum chloride colorimetric assay using quercetin as the standard. The quantitative analysis revealed a substantial total phenolic content of 82.35 ± 0.40 g of tannic acid equivalents per kilogram (g TAE/kg) of the dried sample. The total flavonoid content was also significant, measured at 9.15 ± 1.24 g of quercetin equivalents per kilogram (g QE/kg). These findings demonstrate that dried cotton seed is a rich source of natural phenolic antioxidants, highlighting its potential for valorization as a value-added ingredient in functional food, nutraceutical, and animal feed industries and promoting a more sustainable circular economy in cotton production.

This study examines the influence of sustainable procurement practices on organisational performance at the Benin Electricity Distribution Company (BEDC). The study emphases on three key components which are circular economy practices, waste management and pollution prevention; labour rights compliance and ethical sourcing practices; and supply chain resilience, risk management, innovation and supplier development. A descriptive survey design was adopted, and data were obtained from 300 respondents using structured questionnaires and interviews, complemented by secondary data from organisational reports and regulatory documents. Analysis was conducted using descriptive statistics, correlation analysis, t-tests and multiple regression. Findings show that circular economy practices, waste management and pollution prevention significantly enhance operational efficiency and cost reduction. Labour rights compliance and ethical sourcing also contribute to improved stakeholder trust, fairness and transparency. Furthermore, supply chain resilience, risk management, innovation and supplier development demonstrated the strongest positive effect on organisational performance, particularly in service delivery, productivity and supplier growth. The study recommends that BEDC strengthen its circular economy initiatives, institutionalise ethical sourcing policies, enhance supplier monitoring mechanisms and invest in supply chain resilience and innovation to improve overall performance.