Air transport infrastructure plays a vital role in economic growth, international trade, tourism, and regional integration, with airports functioning as complex service systems where passenger interactions with terminal facilities shape overall travel experience. This study evaluates the adequacy of facilities at Murtala Muhammed International Airport Terminals I and II and examines their relationship with passenger satisfaction. Data were collected through structured field observations and questionnaires administered to 400 passengers. Descriptive statistics and cross tabulation were used to assess facility provision and satisfaction levels, while chi square test of association and correlation analysis were applied to examine relationships between variables. Results show that Terminal II provides a more developed and passenger oriented environment, with 86.7% of listed facilities available compared to 60% in Terminal I. Correspondingly, 66.7% of passengers in Terminal II reported being satisfied or highly satisfied, compared to 37.0% in Terminal I. The chi square result (χ² = 35.607, p < 0.05) indicates a significant association between terminal type and passenger satisfaction, while correlation analysis shows that key service dimensions such as tangibles (r = 0.62) and reliability (r = 0.57) are strong predictors of satisfaction. Key deficiencies identified include inconsistent power and water supply, inadequate drivers’ lounges, and limited seating and recreation facilities. The findings provide empirical evidence to support targeted improvements in airport planning and management to enhance passenger experience.

Savanna ecosystems are shaped by complex interactions among disturbances, climate extremes, and management, yet quantitative assessments of their structural and floristic characteristics in Nigeria remain limited. This study, therefore, examined the present status of protected areas (PAs) within the savanna ecological zone of Northern Nigeria, focusing on tree species diversity, abundance, stand structure, density, and distribution patterns with the view of providing information for management and conservation purposes. Data were collected from five randomly selected PAs: Yankari Game Reserve and Sumu Wildlife Park (Bauchi State), Kainji Lake National Park and Borgu Game Reserve (Niger State), and Marhai Forest Reserve (Nasarawa State). A systematic line-transect sampling technique was used, with four 50 m × 50 m plots established at 250 m intervals in alternate directions within each site. All trees with DBH ≥10 cm were measured and identified. A total of 1,051 trees, 71 species and 22 families were recorded. Tree density ranged from 68 to 275 trees ha⁻¹. Combretaceae and Fabaceae were the most dominant families, while Combretum micranthum, Anogeissus leiocarpa, and Vitellaria paradoxa were the most frequent species. Despite low population density, Adansonia digitata contributed substantially to basal area and volume. Kainji recorded the highest Shannon index (3.21), evenness (0.95) and Margalef's index of species richness (6.87). Tree density and height varied significantly (p<0.05), but basal area and DBH did not differ. Strong correlations between structural variables and diversity indices highlight the need to conserve and protect large-tree growth in the Nigerian savanna.

The plasticization efficiency evaluation of deep eutectic solvent (DES), based on choline chloride (CC) and ethylene glycol has been performed on the extracted starch from cassava peels as compared to the conventional plasticizer glycerol in the production of thermoplastic starch (TPS) (bioplastic films). In this work, Deep eutectic solvents (Ethaline) was evaluated as plasticizer and it’s plasticization effect was compared with glycerol at varying concentrations (0, 5, 10, 15, 20, 25 and 30 wt%). The mechanical testing portrayed that Ethaline plasticized thermoplastic starch (TPS) exhibited higher tensile strength of 3.9 MPa at low concentrations (15 wt%) compared to glycerol 3.1 MPa, while maintaining acceptable elongation. At higher concentration (>20 wt%), Ethaline enhanced flexibility but reduced tensile strength similar to glycerol. Water absorption studies revealed that Ethaline plasticized-TPSs absorbed less moisture than glycerol counterpart, suggesting improved barrier properties. Overall, Ethaline has a good potential of plasticization and inhibits the migration of plasticizer from the polymer matrix, compare to conventional ones like glycerol, as it improves the performance of bioplastic films (TPSs) in both mechanical and barrier properties.

In recent times, the growing popularity of virtual learning in higher institutions has been observed, however, there is a limited research on the effect of distance learning institutions, especially Chemistry, on students’ academic performance. Chemistry is viewed as an abstract and a difficult course by many students; hence, this study examined the effects of virtual learning on the academic performance of Chemistry students in Distance Learning Institute (DLI), University of Lagos. Virtual Learning and Academic Performance Questionnaire was distributed via stratified random sampling technique. Descriptive statistics was used in analyzing the data related to the research questions while inferential statistics used in testing the hypotheses was Chi-square. The findings showed that the physical facilities in terms of structures and computers were adequate for Chemistry students, revealing a significant effect of virtual learning on academic performances of learners of Chemistry Education of the Distance Learning Institute. The study indicated that there is better access and use of virtual tools with better academic performance in DLI, at 0.05 significant level, leading to a positive relationship between engagement in virtual activities and Chemistry performance. The internet quality, timely academic support, and interactive virtual sessions significantly affect students’ virtual learning experience. Based on these findings, it is recommended that government and school management should improve the internet infrastructure, provide adequate learning materials, adopt multiple learning platforms, provide better e-learning environment for facilitators, provide better student support services and ultimately integrate interactive and gamified tools in higher Institutions.

The adoption of autonomous vehicle (AVs) has sparked considerable interest across diverse industries, including public transportation, underground mining, and agriculture sectors. The autonomous vehicle is about to hit the mass-market. The question is not about when it will happen but in which conditions, under which form or who will be the first autonomous vehicle manufacturer to release an efficient and reliable final product in Nigeria. By now, the equation has not been solved, due to the high price of the technologies needed, the lack of solutions to provide a reliable network, and the necessity to change conventions established before now in terms of responsibility of drivers. Nevertheless, the autonomous vehicle is not only an evolution of a previous product, which is able to evaluate and to progressively transform into a self-driven vehicle. This innovation is one step further and is challenging everything that had been established until now in terms of objective criteria expected from a vehicle. This is why it was called a disruptive innovation, or even a revolution, in the sense that it has the power to totally change the way we interact with our everyday transportation system. To enter into the market, this technology, will have to overcome some challenges, on the technological side but also on the psychological side of his future clients. Therefore, an heterogeneous method approach was employed, hybridizing quantitative data from surveys of approximately 2000 randomly selected individuals and qualitative insights from in-depth interviews with policymakers, traffic engineers, and industry representatives.

The increasing prevalence of antibiotic-resistant bacterial strains such as Salmonella typhi and Staphylococcus aureus has necessitated the search for alternative antimicrobial agents, particularly from plant sources. This study investigates the phytochemical composition and in vitro antibacterial activity of leaf extracts from Acacia senegal medicinal plant traditionally used in the treatment of infectious diseases. Crude extract was obtained via ethanol maceration and subsequently fractionated using solvents of increasing polarity. Phytochemical screening revealed the presence of tannins, terpenoids, phenolics, steroids, and saponins in A. Senegal. Antibacterial activity was assessed using the agar diffusion method against clinical isolates of S. typhi and S. aureus. The results demonstrated that chloroform and hexane extracts of A. senegal exhibited strong inhibitory effects against S. typhi (zones up to 24.5 mm). (43 mm at 100 mg/ml) Minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) assays confirmed the potency of the extracts, particularly methanol and ethanol fractions. Bioactive compounds were isolated and characterized using thin-layer chromatography (TLC), column chromatography, Fourier-transform infrared spectroscopy (FT-IR), and nuclear magnetic resonance (¹H & ¹³C NMR). The major compound isolated from A. senegal was identified as lupeol, a pentacyclic triterpenoid, based on characteristic NMR signals (δC 151.01, 109.33, 79.03 ppm; δH 5.30–5.35, 4.95–5.05, ~3.35–3.60 ppm). These findings validate the ethnomedicinal use of the plant and suggest its potential as sources of novel antibacterial agents

Many Researchers have used the notion of interpolative Kannan contraction due to its wider range in applications and its flexibility, rather than the normal Banach contraction. This paper studies the existence, uniqueness, and convergence of fixed points for coupled interpolative Kannan-type contractions in metric spaces. Using Picard and Mann iterative schemes, sufficient conditions ensuring convergence to a unique fixed point are established. The results extend and generalize several existing findings in fixed-point theory.

This study identified credit risk factors in the Nigerian banking sector and developed a hybrid deep learning model to improve credit facility engagements. Both secondary and primary datasets were employed. Secondary data were sourced from selected commercial banks and peer-reviewed publications, while primary data were gathered through Key Informant Interviews (KII) with experienced commercial bankers. Categorical features underwent data transformation, and feature importance was assessed using mutual information, which informed the generation of a reformed dataset. A Hybrid Deep Learning classification model was formulated and simulated using varying proportions of the hold-one-out method via Google Colaboratory. Model performance was evaluated based on accuracy, true positive rate, false positive rate, and precision. Six key features were identified as most relevant to credit risk classification: monthly income, annual income, amount invested monthly, outstanding debt, equated monthly installments, and type of loan. The DNN-based model trained on these features achieved a prediction accuracy of 99.9%, significantly reducing redundancy across the original 23 features and cutting processing time. Furthermore, the Hybrid model (combining an AutoEncoder with a Deep Neural Network) outperformed a standalone DNN-based model by 46.8%. The study concluded that selecting relevant features for predictive modelling tasks reduces model complexity, simulation time, and memory usage, collectively contributing to improved performance. These findings offer a practical framework for enhancing credit risk assessment in the Nigerian banking sector through intelligent, efficiency-driven machine learning approaches.

Water is a ubiquitous chemical substance essential for all forms of life, and access to safe drinking water is critical for public health and well-being. Globally, about 80 % of illnesses are linked to contaminated water and poor sanitation, contributing significantly to mortality rates, particularly in Nigeria and other developing countries. This study assessed the physicochemical properties and heavy metal content of shallow hand-dug well water consumed in Makurdi, Benue State. A total of twenty-five (25) wells were randomly sampled, with five wells selected from each of five locations (Adeke, Gaadi, Kanshio, Wurukum and North Bank). The samples underwent physicochemical and heavy metal analyses to determine compliance with World Health Organization (WHO) and National Agency for Food and Drug Administration and Control (NAFDAC) standards for potable water. Results showed that most physicochemical parameters conformed to WHO (2017) and NAFDAC (2019) standards. However, turbidity exceeded the recommended limit of 5 NTU in Kanshio (6.65±0.45 NTU) and Wurukum (6.24±0.08 NTU). Lead and zinc concentrations were within acceptable limits, while cadmium levels were slightly elevated in Gaadi (0.107±0.005 mg/L), Kanshio (0.086±0.001 mg/L), and Adeke (0.12±0.001 mg/L). Nickel concentrations were also marginally above the permissible limit of 0.02 mg/L across all sampled locations. Overall, most parameters complied with WHO and NAFDAC guidelines, suggesting the water is generally safe for domestic use. However, proactive measures are necessary to control cadmium and nickel levels, as prolonged exposure may pose cumulative health risks.

This study utilizes panel data from 2000–2022 to examine the nexus between climate change and economic growth in West Africa, employing a Panel Autoregressive Distributed Lag (ARDL) model and the Pooled Mean Group (PMG) estimator. After confirming the model's validity through cross-sectional dependence and unit root tests, the empirical results indicate that carbon emissions and energy imports act as significant drivers of economic performance in the short run, reflecting a temporary reliance on emission-intensive activities. However, these factors, along with population growth, become statistically insignificant in the long run, suggesting that current growth models are unsustainable. With a highly significant error correction term indicating a swift return to equilibrium after shocks, the findings highlight a critical need for West African policymakers to shift toward renewable energy, enhance climate adaptation, and invest in productivity-led development to ensure durable, long-term economic stability.