Yaba College of Technology

Measuring gross domestic product has been a challenge to econometricians over the years as different macroeconomic variables have been employed by several investigators with varied results but the subject still remains a topical issue. This study examined empirical dynamic relationship between some selected macroeconomic variables on the growth of Nigeria economy. Secondary data was obtained from the World Bank online database which covered a period of thirty-six years (1985–2021). The variables employed were the Gross Domestic Product (GDP) in billions of Naira, Population Growth Rate (PGR) in (%), Exchange Rate (ER) of Dollar to Naira, Interest Rate (INR) in (%) and Inflation Rate (IR) in (%) and Statistical Package for Social Sciences (SPSS) IBM Version 23.0 was employed in analyzing the data. The fitted regression equation for this model was: GDP = -1.629E+12 + 6.843E+11*population growth + 1088791164*exchange rate + 641376491*inflation rate + 1076243147*interest rate. Therefore, the study found that population growth and exchange are statistically significant in inferring gross domestic product. It is recommended that the apex banking body in Nigeria should put in place a stringent foreign exchange control mechanism to ensure that value of Naira against other currency is appropriately determined and steps should be taken to reduce inflation in the country by implementing different tools to control the circulation of money in the economy.

This article investigates the potential implications of the United Nations Convention on the International Effects of Judicial Sales of Ships ('the Beijing Convention') and its recognition for Nigerian jurisprudence. The Convention, which was finalised by the United Nations Commission on International Trade Law and other international organisations, was signed on September 5, 2023, in Beijing, China. This convention aims to establish a comprehensive framework for recognising and enforcing foreign judicial sales of ships. This article explores the alignment of Nigeria's existing legal framework for judicial sales with the Beijing Convention and assesses the necessity of domesticating the Beijing Convention within the Nigerian legal system. Through an analysis of relevant Nigerian legislation and scholarly discourse, this study evaluates the potential benefits, challenges, and opportunities arising from the Beijing Convention on Nigerian jurisprudence. The findings aim to contribute to the ongoing discussions on harmonising international maritime law as well as provide valuable insights for policymakers and scholars interested in the intersection of maritime law and cross-border judicial sales.

The rising penetration of social media into students’ lives heightens the necessity of investigating its effect on academic engagements of students for the purpose of fostering effective learning. This study investigated how the frequency of social media use during lectures, preference for multiple platforms, and after school-hour use of social media influenced attendance and participation, drawing from a sample of 335 students from one university from each of the six states in the region. Statistics used in Analysing data were descriptive, correlation, and regression analyses. Research indicates that the high frequencies of use of social media during lectures (coefficient = -0.348, p < 0.001), multitasking on different platforms (coefficient = -0.233, p < 0.001), and time spent on various activities with social media beyond lectures (coefficient = -0.298, p < 0.001) all have significant negative effects on attention, participation, and attendance among students. The regression model accounted for more than 91% of the variances covered under attendance and participation, indicating the strong influence of social media activities. In conclusion, ubiquitous and multidimensional social media use decreases students' academic engagement in lectures, thus requiring urgent interventions by higher learning institutions to mitigate its negative effects. Such interventions should involve creating awareness, formulating relevant policies, and training students in efforts to have students effectively manage their social media use to help improve their academic performance.

Artificial intelligence (AI) is increasingly shaping modern healthcare by enabling data-driven decision-making, improving diagnostic accuracy, and optimizing resource use. In transfusion medicine, AI offers substantial opportunities to enhance donor management, automate blood typing and compatibility testing, strengthen inventory forecasting, and support early detection of transfusion-related complications. This review summarizes current applications of AI technologies—including machine learning, deep learning, natural language processing, computer vision, and predictive analytics—and evaluates their impact across laboratory, clinical, and operational domains. Emerging innovations such as precision transfusion, patient digital twins, multi-omics integration, and federated learning highlight AI’s potential to advance personalized and interconnected transfusion practices. However, successful implementation requires addressing challenges related to data heterogeneity, algorithmic bias, privacy and ethical considerations, and evolving regulatory requirements. Establishing rigorous validation standards and promoting interdisciplinary collaboration will be essential to ensure that AI improves the safety, efficiency, and sustainability of transfusion medicine.

Tamarindus indica L. (Tamarind) of family Fabaceae is an edible fruit native to Africa’s tropical regions. This study analysed the proximate content of tamarind fruit pulp as well as compared the phytochemical and antioxidant properties using three different solvents: lime juice, honey solution, and aqueous solution. Proximate content was assayed through protocols of AOAC while phytochemical and antioxidant analyses were carried out using standard methods. The percentage of proximate content varied with ash value (4.61±0.01), crude fibre (7.27±0.03), crude fat/lipid (3.83±0.02), crude protein (8.49±0.01) while the highest content was from crude carbohydrate at 78.21±0.02 %. In the qualitative phytochemical analysis, saponins, reducing sugar, terpenoids, cardiac glycosides, flavonoids steroids, and phenolic compounds were detected in all three samples while alkaloids, anthraquinones, tannins and triterpenoids were not detected. The highest concentration of reducing sugar at 255.89±0.13 mg/g was detected in honey extract while phenolic compounds were detected more in the aqueous extract. In the antioxidant assay, aqueous and lime juice extracts of the tamarind fruit pulp exhibited greater scavenging potential on DPPH at dose-dependent rates. This comparative study provides insights into solvent selection for extracting bioactive compounds from tamarind pulp, emphasizing lime juice and honey as promising options. Such findings are valuable for industries involved in tamarind processing for consumption and could contribute to developing more efficient and sustainable extraction methods.

Purpose The purpose of this study is to evaluate the role of internship in shaping lifelong learning trajectories of technical vocational education and training undergraduates. Design/methodology/approach The study adopted a descriptive survey design. Structural equation modelling was used with the extended theory of planned behaviour (TPB) to evaluate the role of internship in shaping lifelong learning among Technical Vocational Education and Training (TVET) undergraduates. The study group comprised 365 third- and fourth-year TVET undergraduates from higher institutions in Lagos State, Nigeria, selected through a multistage sampling technique. Data were analysed using partial least squares structural equation modeling (PLS-SEM) through SmartPLS 3.0. to analyse data collected for the study. Findings The result of the study shows that internship have a significant relationship with attitude, self-efficacy, subjective norms and behavioural intentions, but subjective norms only have significantly relationship with lifelong learning. Originality/value Students’ participation in internship gives them real work experience which will be beneficial to employers and complement technical vocational education programmes, as they are exposed to real-life situations.

Diabetes mellitus (DM) is a complex disease recognised as one of the leading causes of death and disability worldwide. Diet modification and enhanced food behaviour is necessary for the disease management and the patients’ wellbeing. Disease progression in diabetes is greatly influenced by foods consumption pattern which makes it worrisome for sufferers to snack between meals due to fear of possible rise in blood glucose levels. The study therefore produced crackers (snack) made from fonio and conophor nuts. The ingredients were combined using three (3) ratios of 95: 5%, 90:10%, 85:15%. The proximate composition was analysed as described by association of official analytical chemist (AOAC, 2015) and sensory evaluation was carried out using the 9-point hedonic scale. The population of the study was twenty students. A 9-point hedonic scale was the instrument used for data collection. Mean, standard deviation and Analysis of variance (ANOVA) were used for data analysis. The nutrient composition of analysis showed that the different samples of crackers had appreciable values of protein, fats, and carbohydrate. The sensory evaluation result indicated a significant difference in the mean responses of the students on the sensory evaluation of the cracker samples. However, the control sample followed by Sample B had the highest value for colour, taste, crunchiness, texture and general acceptability. The study concluded that the sample B with 90:10 Fonio and Conophor nut flour is nutritionally and organoleptically acceptable and the consumption should be encouraged among diabetes patients. Keywords: Food behaviour, type-2 diabetes, crack we s, Fonio

Digital device usage now transcends age and demographic boundaries, having become commonplace among children from all racial and ethnic groups. The rapid proliferation of touch screen use among infants (6–24 months) has outpaced evidence-based design standards, creating an urgent need for developmentally-grounded interfaces. In this paper, BabySens-an ethical Infant-Centered HCI Design (ICHD) framework that integrates stage-aligned interactions adapting to sensorimotor abilities, real-time scaffolding via on-device ML, built-in guardrails, and hybrid physical-digital play is developed using Bluetooth-connected toys. Through an approved and controlled lab study with infants (N = 12), our object permanence teaching prototype demonstrated significantly higher touch accuracy of 83–90% CI [78%, 88%] vs. 52% [45%, 59%] in controls; *p* < 0.001, Cohen’s *d* = 1.87) and no sustained distress events compared to commercial apps, with positive transfer effects to real-world tasks (ρ = 0.41). Machine learning analysis revealed that the adaptive system reduced error distances by 68% for infants less than 12 months. These pilot study results challenge current "baby-proofing" approaches, showing that developmental alignment enhances efficacy while reducing risks. This paper emphasizes the need for larger-scale validation and advocate for industry standards based on Piagetian developmental milestones and parental mediation tools, offering BabySens as a concrete template for responsible infant-tech design that prioritizes learning over engagement.