Nnamdi Azikiwe University Journals
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ACCOUNTING AND DISRUPTIVE TECHNOLOGIES: EXAMINATION OF THE ETHICAL IMPLICATIONS OF EMERGING TECHNOLOGIES
No full textThe integration of disruptive technologies such as artificial intelligence (AI), blockchain, and big data analytics into accounting practices has revolutionized the field, offering significant benefits in terms of efficiency, transparency, and decision-making. However, these advancements also present substantial ethical challenges that must be addressed to ensure responsible adoption. This study explores the ethical implications of these technologies in accounting, focusing on transparency, accountability, fairness, data privacy, and security. Through a comprehensive synthesis of insights from existing literature and case studies, the research identifies key ethical concerns and proposes guidelines and best practices for their mitigation. The findings highlight the importance of developing transparent AI systems that are explainable to stakeholders, establishing clear accountability mechanisms for AI-driven decisions, and implementing strategies to mitigate biases in AI algorithms. The study also underscores the need for robust data privacy and security measures in the use of blockchain technology, particularly in compliance with data protection regulations such as the General Data Protection Regulation (GDPR). Additionally, the research emphasizes the necessity of ethical training and education for accounting professionals, fostering collaboration and stakeholder engagement, and regularly monitoring and evaluating ethical practices. By addressing these ethical considerations, the accounting profession can navigate the challenges associated with disruptive technologies and harness their benefits responsibly. The recommendations provided in this study aim to guide the ethical adoption and implementation of AI, blockchain, and big data analytics in accounting, ensuring that these technologies contribute positively to the profession and society at large
FINANCIAL LEVERAGE AND INTERNAL GROWTH RATE OF LISTED INDUSTRIAL GOODS FIRMS IN NIGERIA
No full text The study examined the effect of financial leverage on the internal growth rate of listed industrial goods firms in Nigeria. The specific objective was to ascertain the effect of debt asset ratio, debt equity ratio, debt to earnings before interest, taxes, depreciation, and amortisation (EBITDA) ratio and interest coverage ratio on internal growth rate. Ex-post facto research design was adopted. The population comprised thirteen listed industrial goods firms in Nigeria, from which a purposive sample size of nine was selected. Secondary data were sourced from the annual reports of the firms (2013-2023). The hypotheses were tested using panel estimated generalised least square. The findings revealed that: Debt Asset Ratio has a positive and significant effect on internal growth rate of listed industrial goods firms in Nigeria (β = 0.8677, p = 0.0012); Debt Equity Ratio has a negative and significant effect on internal growth rate (β = -1.7390, p = 0.0000); Debt to EBITDA Ratio has a positive and significant effect on internal growth rate (β = 0.2397, p = 0.0000); Interest Coverage Ratio has a positive but insignificant effect on internal growth rate of listed industrial goods firms in Nigeria (β = 0.0004, p = 0.8113). The study concluded that financial leverage exerts both positive and negative influences on the internal growth rate of listed industrial goods firms in Nigeria, emphasizing the need for strategic debt management to balance growth potential with financial stability. It therefore recommends that management teams of Nigerian industrial goods firms are advised to strategically use debt financing to fund expansion and capital investment, ensuring that the firm is making optimal use of its assets by supporting growth initiatives, such as new product development or market expansion, without jeopardizing the firm’s long-term sustainability
PREVALENCE OF FOOT PAIN AND ASSOCIATED RISK FACTORS AMONG FINAL YEAR CLINICAL STUDENTS AT UNIVERSITY OF BENIN, EDO STATE, NIGERIA
No full textBackground: Foot pain is a common musculoskeletal complaint that can interfere with mobility, daily activities, and clinical performance. Clinical students are particularly vulnerable due to prolonged standing, unsuitable footwear, and heavy Understanding clinical its prevalence associated risk factors is essential for developing effective preventive strategies and improving students’ well-being.
Aim: To determine the prevalence of foot pain and identify the associated risk factors among final-year clinical students at the University of Benin.
Methods: A descriptive cross-sectional study among 208 final-year clinical students of Physiotherapy, Nursing, Radiography, and Medical Laboratory Science. Participants were selected using a proportionate stratified sampling technique. Data were collected using a validated Foot Health Status Questionnaire (FHSQ). Descriptive statistics summarized the data, while inferential tests (Kruskal Wallis, Mann–Whitney U, Spearman’s correlation, and binary logistic regression) were used to assess associations at a significance level of p < 0.05.
Results: The prevalence of foot pain was 47.6% among participants, indicating a moderate to high occurrence. The Kruskal–Wallis test revealed significant differences in foot pain across departments (p=0.019), with nursing students reporting highest scores. Spearman’s correlation showed significant relationships between prolonged standing (r = −0.143, p = 0.039), shoe height (r = −0.166, p = 0.017), and shoe fit (r = 0.157, p = 0.024) with foot pain. The Mann–Whitney U test found no significant gender difference (p = 0.555), while the presence of foot defects significantly influenced foot pain (p = 0.045). Logistic regression showed that the overall model was significant (χ² = 27.74, p = 0.015), though no single predictor independently explained the outcome.
Conclusion: Nearly half of the clinical students experienced foot pain, largely associated with prolonged standing, poorly fitted footwear, and pre-existing foot defects
Soft computing optimization of vegetable oil extraction
No full textThe introduction of machine learning in prediction of yield for bioprocessing is stimulating the wide usage of the first-generation biomass (vegetable oil) especially in production of biodiesel and biolubricant. This study focused on soft computing optimization of gmelina seed oil extraction using ANN and ANFIS. The results showed that ANN is better tool for prediction of oil yield with highest coefficient of determination of 0.998 and minimum error of 0.241. The optimal GSO yield of 50.4% was obtained when these factors were adjusted to 1.5mL/mg, 45minutes, 50oC, 0.55mm, and 200rpm. This provides a crucial step towards developing a sustainable and renewable energy source, which has the potential to positively impact both the environment and local communities
Investigating the Effects of Thermal and Radiation on CFRP-Reinforced Concrete Shell Roof Structures
No full textReinforced concrete shell roofs are critical components in nuclear structures, requiring high durability, thermal resistance, and radiation stability. This study investigates the viability of Carbon Fiber Reinforced Polymer (CFRP) as an alternative to traditional steel reinforcement in nuclear environments. The research focuses on thermal stress effects, radiation-induced degradation, shape formulation optimization, and structural performance under multi-axial loading conditions. Finite element simulations were conducted to analyze the thermal resistance of CFRP-reinforced concrete shell roofs. Results indicate that CFRP exhibits 65% higher thermal stability than steel, reducing the risk of heat-induced structural failure. Additionally, radiation exposure tests reveal that CFRP suffers 40% less degradation compared to steel, enhancing its long-term durability in high-radiation zones. A comparative structural performance analysis demonstrates that CFRP-reinforced shells maintain 50% greater mechanical strength under extreme environmental conditions than their steel counterparts. Shape formulation studies show that a 19-degree shell angle provides superior load distribution and stress reduction, improving structural efficiency by 25%. Moreover, reliability-based design optimization accounts for geometric imperfections and material uncertainties, resulting in a significant increase in overall structural resilience. The findings confirm CFRP’s potential as a sustainable, high-performance reinforcement material for nuclear structures, offering a 55% longer service life and significant life-cycle cost reductions. The study concludes with design recommendations, advocating for the integration of CFRP in nuclear containment structures to enhance safety, reliability, and longevity
Hydro-geological surveys and evaluation in parts of Anambra state, Nigeria
No full textHydro geological surveys and evaluation were carried out in parts of Anambra State, Nigeria, A multi-objective, multi-technique; multidisciplinary and integrated approach was adopted in the area. The hydro-geological parameters (Water quality parameters tested fall within the WHO standard, desirable, permissible and acceptable limits, except for the high iron, nitrate contents of most surface waters and Nnewi ground-water for which appropriate treatments have been advised under discussion. The ground water, resources potentials are quite promising with high yield, high transmissivity, good specific capacity and minimal drawdown. Hydro geological environment depends on the aquifer of interest, and varies from formation to formation. The empirical hydro geological model shows that when the apparent resistivity for a 150m current electrode spread and below, comes to the average of 175, the ground water resources potential is promising. Imo shale formation, Nanka Sands formation, and Ogwashi-Asaba formation reveal the total depth of boreholes are at average of 62m to 550m, 150m and 550m, and 120.5m to 178.0m respectively. The Imo Formation has poor permeability but good storage. The Nanka Sands formation shows that the study area with a thickness of 120m to 440m in several places used for the study. The hydro geochemical study in Imo shale shows the average ph of the aquifier ground water is between 4.8 to 6.5 pH scales, with maximum permissible pH scale of 8.5, Nanka sand areas show the average ph of the aquifier ground water is between 5.0 to 6.6 pH scales, with maximum permissible pH scale of 8.5, while Ogwashi-Asaba formation also shows the average ph of the aquifier ground water is between 4.9 to 6.5 pH scales, with maximum permissible pH scale of 6.5. The Ogwashi-Asaba hydro geological data indicate good yield aquifers and its formation has equally good yields aquifer. The hydro geochemical study acquired along with derived and computed analyses of results of pumping tests of boreholes appraised in this study in parts of the study area, indicate the study area is hydro-geologically promising
Effect of Copper-Based Fungicide on Chemical Composition of Cocoa Seeds
No full textProduction of cocoa seeds, one of Nigeria’s major non-oil foreign exchange earners as well as a major raw material for the beverage industry, is greatly hindered by diseases caused by various species of the genus Phytophthora. To avert this, copper-based fungicides are sprayed on the leaves of cocoa trees to control or prevent the survival of this organism by the farmers without paying attention to the effects of this chemical on the proximate composition of cocoa seeds. This study therefore investigated the effects of a copper-based fungicide (Ridomil Gold Copper) on the quality of the cocoa seeds by spraying cocoa trees, including the pods, with 50.00 g/L of copper-based fungicide. The results obtained showed that cocoa seeds from the control trees showed significantly higher contents of fiber (4.51%), protein (15.1%), and fat (36.1%) when compared to the respective values of 3.45, 3.95, and 7.59% obtained for the cocoa seeds harvested from the fungicide-treated cocoa trees. All other proximate compositions did not show any statistical difference, except for carbohydrate and calorific values, which were significantly higher in cocoa seeds from fungicide-treated cocoa trees. Seeds from fungicide-treated trees showed significantly higher potassium, phosphorus, and magnesium contents but lower zinc and copper contents. However, phytochemicals such as phenols, alkaloids, flavonoids, and tannins were significantly lower in content in the seeds of fungicide-treated cocoa trees. The contents of glycosides and antioxidants in the cocoa seeds were statistically similar for both the control and treatment, except for ascorbic acid, which showed a significantly lower value (4.8 mg/100 ml) in cocoa seeds from fungicide-treated cocoa trees, compared with the value recorded for the control in this study (13.33%). The foregoing results showed that the use of copper-based fungicides for the control of black pod disease in cocoa adversely affected the quality of cocoa seeds from the treated trees
Linearised Model of Surface-Mounted Permanent Magnet Synchronous Motor for Stability and Speed Enhancement
No full textThis paper presents a linearised model of the Surface-Mounted Permanent Magnet Synchronous Motor (SPMSM) to enhance stability studies and facilitate control system design. The SPMSM is widely used in various industrial applications due to its high efficiency and performance. However, its non-linear behaviour poses challenges for analysis and control. A state-space model of the SPMSM is derived and linearised at a chosen operating point, with key motor parameters such as Ld = Lq = 0.0171 H, R = 5.29 Ω, and λm = 0.321 Wb. Simulation results demonstrate that the linearised model accurately captures the behaviour of the non-linear system across various input conditions. The step response showed stable, well-damped behaviour with all state variables (current, speed, and position) settling within a few milliseconds. The impulse response analysis confirmed the system’s rapid return to equilibrium, with overshoot levels kept below 5%, indicating good damping. The Bode plot revealed a smooth frequency response, with gain margins and phase margins indicating a stable system. The pole-zero map confirmed that all poles lie in the left-half plane, ensuring system stability. These results validate the linearised model as a reliable tool for stability analysis and control design in SPMSM applications
Factorial model prediction for performance of sawdust ash-metakolin blended oil well cement
No full textFactorial methods provide an efficient statistical approach to model and optimize oil well cementing material -based on OPC blended with Metakaolin and Sawdust-Ash by systematically investigating the effects of key parameters of cementing slurry and its hardened cake including thickening time, free fluid, fluid loss, slurry density, rheology and compressive strength. The mix design of using Sawdust Ash (SDA) and Metakaolin (MK) as a blend to ordinary Portland cement (OPC) was carried out using a mathematical arrangement of a factorial DOE model allowing percentages blend of the OPC with Metakaolin for 10%,12.5% and, 15% and Sawdust ash at 0%, 5% 10% respectively. Materials for the study were characterized based on physical, chemical, and pozzolanic test parameters. the Design of the Experiment (DOE) was used for two domains three interactive factors (2x3) following the specifications of the America Institute of Petroleum (API) SPEC 10A and 10B). The results obtained showed that Metakaolin blend with OPC alone at 15% were detrimental to rheology but incorporating Sawdust-Ash up to 10% with Metakaolin at both 10% and 15% improved the both the rheology performance, free water within (0.032-1.435%), decreased fluid loss to the recommended API RP-10B range of 50 to 250ml, increased of thickening time, and modulate the control sample (OPC). The interaction effect from the yield output of the model were used to obtain several predictive mathematical models readily needed for Oil well cementing