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ABSTRACT <br><br> This study examines the role of public debt in financing infrastructure development in Nigeria <br><br> using annual time series data from 1981 to 2023 sourced from CBN Statistical Bulletin and the <br><br> World Bank Development Indicators. The analysis employs the Autoregressive Distributed Lag <br><br> (ARDL) model to estimate both short-run and long-run relationships among key variables, <br><br> including domestic public debt, external public debt, interest rates, and exchange rates. The <br><br> findings reveal that both domestic and external public debt has a positive effect on <br><br> infrastructure development. Specifically, a 1% increase in domestic debt leads to about a <br><br> 0.88% rise in infrastructure development, while a 1% increase in external debt raises <br><br> infrastructure development by approximately 0.34%. In contrast, a 1% rise in interest rate <br><br> reduces infrastructure development by around 0.01%, and a 1% increase in exchange rate <br><br> decreases it by 0.005%. These results underscore the significance of well-managed domestic <br><br> borrowing while highlighting the potential risks associated with macroeconomic volatility. The <br><br> error correction term confirms a stable long-run relationship, with deviations adjusting at a <br><br> rate of 31.32% per period. These findings align with previous empirical studies, reinforcing <br><br> the argument that effective debt management strategies are essential for optimizing <br><br> infrastructure investment and economic growth. The study provides policy recommendations <br><br> emphasizing the need for prudent debt utilization, exchange rate stability, and efficient <br><br> resource allocation to maximize the benefits of public borrowing for infrastructure <br><br> development. <br><br> <br><br> Key Words: Public Debt, Infrastructure Development, ARDL Model, and Exchange Rate <br><br> Jel Codes: H63, H54, E43, F31

The fast transition to remote work has significantly expanded the attack surface for organizations, <br> creating new vulnerabilities to insider threats that are usually difficult to detect and mitigate <br> through traditional security measures. This report covers the development and application of <br> interactive digital twin simulations as a proactive defense strategy for securing remote work <br> environments. By creating dynamic virtual replicas of organizational systems, workflows, and <br> user behaviors, digital twins enable real-time monitoring, scenario testing, and predictive analysis <br> of potential insider threat activities. The interactive nature of these simulations allows security <br> teams to model human–system interactions, identify anomalies in patterns, and assess the impact <br> of both intentional and unintentional insider actions. Furthermore, the approach supports adaptive<br> training, risk assessment, and policy validation in a controlled environment without exposing <br> actual systems to harm. The findings highlight how integrating digital twin technology with <br> advanced analytics and behavioral modeling enhances resilience against insider threats by <br> improving detection accuracy, response readiness, and decision-making in distributed remote <br> work settings. This work covers the potential of interactive digital twins as a transformative tool <br> for organizations seeking to strengthen cybersecurity in the era of hybrid and remote operations.

Maize (Zea mays) is the leading grain in the world with an annual production of more than 1 billion tons in 2013, and it constitutes staple foods for large groups of people in Latin America, Africa, and Asia. Rodents cause significant damage to maize crops resulting in substantial yield loss and economic hardship for farmers.This study was at the Teaching and Research farms of Federal University of Agriculture, Abeokuta (FUNAAB) to determine the effect of some bio pesticides (goat dung and pepper mint oil) on the infestation and damage levels of Rodent pests of maize. The research was a 2*3 factorial experiment conducted using two maize varieties (Oba super 6 and local variety from a market) and three Bio pesticides (Goat dung, peppermint oil, water as control). Data obtained was subjected to Analysis of variance and the treatment means were compared using least significant difference means at 5% probability level revealed no significant difference in rodent infestation and damage among treatment suggesting that neither goat dung or peppermint oil had a significant repellent effect on rodents under the conditions of this study. In conclusion, Rodents infest and cause damage to maize crop and the bio pesticide used in this research were unable to have any effect in controlling the rodent pests. Further research should be carried out on increasing the frequency of application, using a combination of these bio pesticides with other repellents or control methods for more effective results.

This study develops a Copula-Based Dynamic Conditional Correlation (DCC) model to simulate financial risks and analyze dependencies among equities, bonds, and commodities from 2013 to 2023. By integrating Copula functions with DCC models, the framework captures time-varying correlations and tail dependencies, addressing limitations of traditional risk models.Results demonstrate superior performance in estimating Value-at-Risk (VaR) and Conditional Value-at Risk (CVaR), particularly during the 2020 COVID-19 market crash, with fewer backtesting violations compared to multivariate GARCH and static correlation models. The Student’s t-Copula excels in modeling symmetric tail dependencies. The model offers practical benefits for portfolio risk management, stress testing, and regulatory oversight, despite computational complexity.

ABSTRACT<br><br><br><br><br> The study examined the effect of credit management on the profitability of eight <br><br><br><br><br> manufacturing firms in Nigeria. In order to achieve the objectives of the study expost<br><br><br><br><br> facto was adopted. Secondary data were used for the study. The study adopted <br><br><br><br><br> judgmental sampling technique to select eight consumers’ goods manufacturing <br><br><br><br><br> companies. These companies were chose based on availability of data for the <br><br><br><br><br> number of five years (2018-2022) under review. A multiple regression analysis was <br><br><br><br><br> adopted using Econometrics views. Findings revealed that receivables collection <br><br><br><br><br> period was negatively significant on the return on assets of eight quoted <br><br><br><br><br> manufacturing firms in Nigeria and payables payment period was positively <br><br><br><br><br> significant on the return on assets of eight manufacturing firms in Nigeria. It was <br><br><br><br><br> concluded that companies that extending credit to customers can boost sales and <br><br><br><br><br> revenue, but it also carries the risk of bad debts and delayed payments. It was <br><br><br><br><br> recommended that firms take caution on account receivable period so that it does <br><br><br><br><br> not harm their volume of credit sales which can adversely affect their profitability <br><br><br><br><br> and firms should increase their average payable period so that they can have internal <br><br><br><br><br> financing to help them save cost associated with external financing.

This study assesses the use of internet services among students of Ambrose Alli University, Ekpoma, Edo State. The increasing importance of the Internet in academic settings prompted this research, which investigates the nature, relevance, challenges, and frequency of internet usage among university students for academic purposes. Through a survey, data was collected from students to evaluate how the Internet influences their academic activities, including research, communication, and information access. The findings indicate that internet services are crucial in enhancing students’ learning experiences and academic performance, although challenges such as slow connectivity, limited access, and lack of digital literacy still persist. This research contributes to understanding how the Internet is utilized in higher education and offers recommendations for improving internet access and usage for academic success.<br> <br> Key Words: Internet Usage, Academic Performance, Students, Challenges, Digital Literacy

ABSTRACT<br> This research focus on the “Effects of social development on learning activities of Primary Schools pupils, a case study of Giwa Local Government Area of Kaduna State”. The objectives of this research include: To find out the effects of social development on learning activities of Primary School pupils, the role of teacher`s qualification on the social development of primary school pupils, the role of parents and community in social development of primary school pupils in Giwa Local Government Area of Kaduna State. The beneficiaries of this research include; pupils, teachers, parents and community as its affect their behaviour and ability to interact with one another in a presentable manner.<br><br> Social development in primary school is crucial for shaping a child's interactions, relationships, and understanding of the world around them. <br><br> The population of this research include 71 teachers in which 35 of them were taken as a sample to represent the entire population. However, descriptive survey method was employed for this research in which 35 questionnaires were distributed to the 4 selected primary schools in Giwa LGA, Kaduna State. The research revealed that majority of the respondents disagreed that engaging pupils in social activities, forming and maintaining healthy relationship, training teachers on classroom management techniques and understanding the diverse needs of pupils, collaboration between teachers and school and ability of community to provide important resources for social development can help pupils to develop social skills. Therefore, it is recommended that pupils should be engaged in social activities and healthy relationship. Teachers should be trained on classroom management techniques. They should also encourage pupils to interact and collaborate with one another. Parents should collaborate with teachers, teach pupils basic social etiquette such as greeting others, making eye contact, sharing, taking turns and expressing gratitude because that can help them to learn effective social skill. Community should demonstrate positive behaviors, values, attitudes and provide important resources for social development, such as libraries, community centers, sports facilities, and parks help pupils to learn social skill.

Tomato (Solanum lycopersicum L.) is an important vegetable crop whose productivity and <br> seed quality are strongly influenced by physiological maturity at harvest. This study <br> investigated the determinants of seed physiological quality in two tomato varieties (Roma <br> and Cobra) grown under open field conditions. Fruits were sampled at 10, 15, 20, 25, 30, <br> 35, 40, and 45 days after anthesis (DAA) to evaluate fruit fresh and dry weight, seed mass, <br> and germination percentage. Data were analysed using analysis of variance (ANOVA) and <br> means separated by least significant difference (LSD) at 5% probability level. <br> Results showed progressive increases in both fresh and dry fruit weights across all <br> developmental stages, with Roma significantly outperforming Cobra in biomass <br> accumulation, particularly at 25 and 45 DAA. Seed mass increased steadily and stabilized <br> around 40–45 DAA, with Cobra producing slightly heavier seeds. Germination <br> percentage remained negligible before 20 DAA but increased markedly thereafter, <br> peaking at over 90% by 45 DAA. Notably, Roma exhibited higher germination rates <br> earlier (35–40 DAA) than Cobra, indicating faster attainment of physiological maturity. <br> The findings highlight that optimal harvesting for maximum seed quality occurs between <br> 35 and 45 DAA, with 40 DAA identified as the ideal harvest window for Roma while <br> Cobra benefits from slightly later harvests to maximize seed mass. These results provide<br> practical guidance for tomato seed producers to optimize harvesting schedules for <br> enhanced seed vigour, viability, and overall quality