BIMA JOURNAL OF SCIENCE AND TECHNOLOGY GOMBE

Determination of Physicochemical Parameters and Heavy Metals in Some Selected Borehole Water Within Nguru Local Government Area, Yobe State

Sadi Idriss — 2025-07-30

Recently, there has been widespread kidney infection and other waterborne diseases in Yobe, most especially in areas of Nguru, Gashua, and their environs. This research was conducted to ascertain the water quality of some selected boreholes within Nguru Local Government Yobe State. The samples were collected in four different locations in the area. The Atomic Absorption Spectrophotometer (AAS) was used to identify the heavy metals. A comparison was made with the standard given by the World Health Organization (WHO), Standard Organization of Nigeria (SON), and National Agency for Food and Drug Administration Control (NAFDAC) respectively. The chemical parameters as well as the physical parameters such as pH, turbidity, alkalinity, and color in all the samples were determined. The result revealed that almost all the samples have a higher content of cadmium (0.003-0.005 mg/L) than the required threshold (0.003 mg/L). Cadmium is reported to be toxic to the kidneys, as such this requires serious concern. Likewise, the values obtained for arsenic (0.01-0.02 mg/L) and chromium (0.04-0.1 mg/L) have exceeded the required threshold (0.01 mg/L for arsenic and 0.05 mg/L for chromium). This also calls for serious attention as they are known carcinogens. It is concluded that all the water samples are not safe for drinking and as such require treatment before consumption to meet the standard for portable drinking water.

Modeling the Relationship Between Exchange Rate Instability and Economic Performance in African Countries

Lumpye Innocent Simji — 2025-07-30

Exchange rate volatility has created an unstable environment for most factors, such as investment and economic performance. It has, however, severely affected most countries in Africa, which rely on primary export and essential imports. This research investigated exchange rate variability's impact on economic performance in Africa. It sought to apply macroeconomic variables in Standard GARCH and Panel ARDL models; measure exchange rate volatility through the Ggeneralized Autoregressive Heteroskedasticity model; and assess short-run and long-run exchange rate movements: Ex-post facto design research design was adopted, covering the period 1990 to 2023 employing the econometric techniques of GARCH model, panel unit root tests (IPS and LLC), and panel cointegration methods. Pooled Mean Group (PMG) model was used to determined the most appropriate for interpretation using Hausman test results. The output indicated that while the exchange rate value (1.3071) had a positive impact, exchange rate volatility (-0.2784) and inflation (-0.3647) were negatively impacting long-run economic performance. Interest rates also had a positive but statistically insignificant effect (0.2022). In the short run, interest rates positively influenced economic performance (0.0818), while inflation (-0.0707) and exchange rates (-0.6945) had negative effects. Exchange rate volatility (-0.0764) was insignificant. The ECM of (-0.2934) shows that the long-run equilibrium will be restored by a factor of 29% annual correction rate. Recommendations include more stringent inflation-targeting measures that could lessen adverse effects on economic performance. Strengthening(CBN) capacity to maintain price stability is particularly important in interest rate management and open market operations, which would improve economic performance.

Skin Disease Classification Using Iwoa-Resnet Deep Learning Architecture

Faiza Haruna — 2025-07-30

Accurate classification of skin diseases remains a significant challenge due to the wide range of conditions, image variability, and class imbalance. Conventional diagnostic systems often struggle with limited accuracy and computational inefficiency, hindering real-time clinical use. This study presents a hybrid deep learning model that integrates ResNet-50 with an Improved Whale Optimization Algorithm (IWOA) to address these issues. A diverse skin image dataset was collected and preprocessed before being passed through ResNet-50 for feature extraction. IWOA was employed to optimize key parameters, enhancing model training and convergence. Experimental results show that the proposed IWOA-ResNet model achieves 99.09% accuracy, with a 25% reduction in training time, maintaining strong performance across unbalanced and varied data. When compared to traditional CNN and machine learning models, the hybrid approach demonstrates superior accuracy and efficiency. This research highlights the potential of combining deep learning with metaheuristic optimization for automated, real-time skin disease diagnosis, offering a scalable and robust solution for clinical deployment.

Topological Space: A Space in Finite Dimensional Euclidean Plane with Variables in "Z(q)"

Semiu Oladipupo Oladejo — 2025-07-30

This work centres on a finite dimensional Euclidean geometry with variables in called near-linear finite geometry. In it, we investigate points and lines in the geometry. A set of points joined together forms lines in the geometry and a presence of trivial divisors yields a set together with the collection of only two subsets, that is, the whole set itself and integer one as members with subgeometries as induced topology where the only open set is the universal set and an empty set. We prove that the Euclidean plane for prime forms an indiscrete topological space whose open sets are trivial subgeometries, and

Discrete Topological Space as a Space in Finite Geometry with Variables in Integer Modulo m

Semiu Oladipupo Oladejo — 2025-07-30

This paper explores the construction of discrete topological spaces on non-near-linear finite geometries, where points and lines are defined over the ring of integers modulo m. By introducing a partial order among subgeometries, we demonstrate how such structures satisfy the axioms of topology and provide illustrative examples for specific cases such as finite geometry The geometry under discourse together with the collection of its subsets called subgeometry yields a discrete topological space with its subgeometries as topology.

Efficacy of Selected Fungicides Against Thielaviopsis paradoxa, the Causal Agent of Neck Bending Disease in Oil Palm

Ojieabu, A — 2025-07-30

The oil palm (Elaeis guineensis Jacq.) is a vital tropical crop cultivated primarily for palm oil production. In Nigeria, the emerging Thielaviopsis paradoxa-induced neck bending disease poses a significant threat to oil palm yield. This study evaluated the efficacy of four fungicides (Z-force (80%), W-force (3%), Cabrio (3%), and Purudan (40 g/L)) against T. paradoxa in vitro and in vivo. Fungicides were tested in vitro at concentrations of 5, 10, 15, and 20 ppm against two T. paradoxa isolates from diseased oil palm trunks. Z-force (20 ppm) and W-force (20 ppm) exhibited the highest mycelial growth in vitro, while W-force demonstrated notable antifungal activity at 15 ppm. The most effective fungicide (W-force) was further tested in vivo using ring and center spraying methods to assess its impact on oil palm yield. The ring spray method significantly enhanced reproductive output, leading to increased inflorescence and fruit bunch production compared to center spear spraying. However, complete field control of T. paradoxa symptoms was not achieved, highlighting the need for integrated disease management approaches. These findings suggest that strategic fungicide application, particularly W-force (3%) via ring spraying, can improve oil palm productivity and contribute to more effective disease management in commercial plantations.

Knowledge, Attitudes, and Practices (KAP) on Tuberculosis (TB) Among Mining Communities in Gombe State, Nigeria

Suraj Abdulkarim — 2025-07-30

Tuberculosis (TB) remains a significant public health challenge, particularly in underserved mining communities where occupational hazards, poor living conditions, and limited healthcare access exacerbate the disease burden. This study assessed the knowledge, attitudes, and practices (KAP) related to TB among mining communities in Gombe State, Nigeria, using a cross-sectional design with 292 participants. Statistical analyses, including frequency table, multivariate logistic regression, Chi-square Automatic Interaction Detection (CHAID), and latent class analysis, were employed to identify key predictors and subgroups. The findings revealed significant gaps in TB knowledge, with education level being the strongest predictor of accurate transmission knowledge (aOR = 5.60 for higher education, p < 0.001). Stigmatizing attitudes were prevalent, particularly among males with no formal education (41.2%) and those who believed TB is incurable (52.6%). Three distinct practice subgroups were identified: proactive practitioners (24%), moderate practitioners (42%), and low practitioners (34%). The study underscores the need for targeted interventions to address knowledge gaps, reduce stigma, and improve prevention practices. Recommendations include community education campaigns, stigma reduction programs, and tailored interventions for low-practice subgroups. These findings contribute to the global effort to combat TB by providing evidence-based insights for improving TB management in mining communities.

Evaluation of Phytonutrient and Proximate Composition Profiles of Cereal-Based Tuwo Commonly Consumed in Matsango-Azare, Katagum Local Government Area of Bauchi State

I. Salihu — 2025-07-30

Cereal-based foods, particularly Tuwo, are among the the most consumed dishes not only in the Hausa/Fulani community of Matsango-Azare Katagum Local Government area of Bauchi State but the whole of sub-saharan Africa where these ethnic groups are the dominance. Anti-nutritional profiles and proximate composition of the tuwo from maize, millet, rice and guinea-corn consumed in this locality have been evaluated. Proximate composition ranged as follows, moisture 58.3940-68.3760%, ash 0.8320-0.3000%, fat 1.7950-3.1100%, protein 6.0170-10.9400%, carbohydrate 20.3600-33.4320%, crude fiber 0.4960-1.0695%. Phytochemical composition of the tuwo collected also ranged as follows, alkaloid 0.6830-2.7270mg/100g, flavonoid 0.8650-3.0620mg/100g, terpenoids 0.4005-1.1170mg/100g, glycosides 0.5160-1.5025mg/100g, steroids 0.9040-2.0670mg/100g, tannins 2.2000-5.2545mg/100g, saponins 1.1575-5.0320mg/100g. The study provided important data on the most consumed of the tuwo types in the locality and their nutrients and anti-nutrient profiles were analyzed as stated. A campaign was set up which geared on improving the nutritional status of the people in this study area. It is recommended that the tuwo from single cereal-based flours require value addition with a legume which will improve the nutrient profiles and methods such as soaking, de-hulling need to be emphasized to these inhabitants as they help to reduce the extent of these phyto-chemicals.

Quantitative Structure Activity Relationship (QSAR) Analysis of Some Pyrazole Derivatives as Hypoglycemic Agents: Computational Approach for Drugs Discovery

K. M. Aujara — 2025-07-30

Diabetes mellitus (DM) represents a significant global health issue marked by persistent high blood sugar levels, driving the need for innovative treatment options. This research centers on the creation and assessment of pyrazole derivatives as potential agents to lower blood sugar, employing a robust machine learning-based QSAR model designed to predict the inhibitory activity of compounds, utilizing RDKit for molecular descriptor calculation. A range of pyrazole derivatives sourced from the ChEMBL database were analyzed, and their inhibitory activities to reduce blood sugar levels were tested. QSAR models were constructed using Multiple linear regression (MLR) and Random Forest regression for model development, integrating molecular descriptors to identify relationships between structural characteristics and biological effectiveness. These models exhibited strong predictive capabilities, pinpointing critical structural features that enhance hypoglycemic activity, achieving an R² of 0.82, cross-validated correlation coefficient Q² of 0.80, and RMSE of 0.25 for Multiple Linear Regression and R² of 0.90, Q² of 0.85 and RMSE of 0.20 for Random Forest model. This study identified several pyrazole derivatives with promising blood sugar-lowering properties, offering a pathway for the development of new diabetes treatments. The results highlight the value of QSAR in guiding drug discovery and lay the groundwork for future preclinical and clinical studies.

Survey and Identification of Fungi Associated with Eucalyptus camaldulensis in Modibbo Adama Universiy, Yola

Audu Sanusi Kiri — 2025-07-30

Eucalyptus species are valuable for timber, pulp, and essential oil production. A laboratory study was conducted which shows the percentage frequency of the fungal isolates in Modibbo Adama University and was calculated based on the total number of isolates obtained from the four different locations. The results showed varying levels of abundance for the four identified fungal species: Rhizopus nigricans was isolated in 2 out of 14 samples, resulting in a percentage frequency of 14.2%. Aspergillus flavus had the second-highest occurrence, being isolated in 5 out of 14 samples, with a percentage frequency of 35%. Penicillium notatum was the least frequent, isolated in just 1 out of 14 samples, giving a percentage frequency of 7.1%. Aspergillus brasiliensis was the most abundant species, isolated in 6 out of 14 samples, accounting for 42.8% of the total isolates. The results of this study highlight the prevalence of fungal pathogens associated with Eucalyptus camaldulensis in the Modibbo Adama University area. Aspergillus brasiliensis and Aspergillus flavus were the most commonly found fungi, indicating that these species may play a significant role in the degradation of Eucalyptus leaves and other tissues. Rhizopus nigicans and Penicillium notatum were less frequent but still present, suggesting their contribution to the overall fungal biodiversity within the study area. This research demonstrates the need for further investigation into the pathogenicity of these fungi, their potential impact on Eucalyptus trees, and the development of management strategies to mitigate fungal infections.

A Comparison of Algorithmic Techniques for the Identification of Fake News in Machine Learning for Twitter Misinformation Detection

C. O Ugwunna — 2025-07-30

Misinformation on Twitter is a common issue, and its ill effect is endangering individuals, communities, and society. Its detection through efficient means will minimize its damage. Hence, we conducted a comparative analysis using different machine learning models and neural networks for Twitter misinformation detection with the development environment established in Google Colab and Python as the underlying programming language. We used a set of 44,898 labeled tweets drawn from Kaggle and labeled as fake or true news, and with four significant features. We tested and trained four models: Support Vector Machine (SVM), Recurrent Neural Network (RNN), Naive Bayes, and Random Forest (RF). We tested model performance through several metrics. The accuracy was 0.99 for SVM (precision: 0.99, recall: 0.99, F1-score: 0.99) and Random Forest (accuracy: 0.99, precision: 0.93, recall: 0.95, F1-score: 0.94), which was the highest among all other models. Naive Bayes (accuracy: 0.94, precision: 0.93, recall: 0.95, F1-score: 0.94) and RNN (accuracy: 0.79, precision: 0.94, recall: 0.64, F1-score: 0.76) performed relatively low. This study has contributed to the creation of strong misinformation detection systems, maintaining the integrity of online information and preventing the dissemination of false information on Twitter. Our comparative analysis sheds light on the most effective machine-learning methods for detecting misinformation, opening the door to future research and applications.

Predictive Modeling of Thermo-Mechanical Performance of Bio-reinforced Intumescent Epoxy Coatings for Industrial Sustainability

Sunday Iweriolor — 2025-07-30

This study addresses the critical challenge of enhancing the thermo-mechanical performance of epoxy coatings for industrial applications by integrating agro-waste-derived bio-fillers. Employing Box Behnken Design and multi-objective optimization, bio-reinforced composites were fabricated using a 2:1 epoxy-hardener ratio Prepared samples were subjected to mechanical and thermogravimetric analysis. The composites exhibited an average mechanical properties of tensile strength TS (78.76MPa), Shore D hardness HS (60.29), and flexural strength FS (70.58MPa). Thermogravimetric analysis revealed a thermal stability threshold of 200°C, with minimal moisture absorption (~1.1% mass loss below 100°C) and 30% residual char at 500°C, indicating potential intumescent properties. Validated models yielded adjusted R² values of 0.88(TS), 0.83(HS) and 0.83(FS). Composites under optimum conditions achieved a tensile strength of 91.9 MPa, Shore D hardness of 72.4, and flexural strength of 88.4 MPa. A desirability score of 92% validated the robustness of the optimization model. Bio-reinforced coatings demonstrated comparable durability to petroleum-based alternatives while reducing synthetic additives. The findings provide a scalable framework for developing high-performance, thermally stable coatings, and advancing sustainability objectives without compromising mechanical integrity.

Comparative Assessment of the Classical Half-Slope Ratio and the Normalized Difference Ratio as a Robust Linearity Diagnostic Tools

Babangida Ibrahim Babura — 2025-07-30

Robust quantitative diagnostics are crucial for assessing linearity in Exploratory Data Analysis (EDA), especially when data contain outliers. This work defines and compares two such diagnostics derived from median-based half-slopes calculated across partitioned bivariate data. We examine the established Classical Half-Slope Ratio (CHR), calculated as the ratio of the right to the left half-slope, which indicates linearity near unity but is unbounded. We contrast this with a proposed Normalized Difference Ratio (NDR), formulated as the normalized difference between the half-slopes. The NDR is inherently bounded within [-1, 1], precisely indicates linearity at zero, and directly signals the direction of data curvature through its sign (+/-). Illustrative examples confirm that NDR’s magnitude quantifies the degree of non-linearity, while its sign offers clear guidance for data transformations. While both CHR and NDR are valuable outlier-resistant tools complementing visual analysis, the NDR’s bounded, centered scale pro- vides distinct advantages for comparative analysis, standardization, and potential algorithmic use.

Digital Tools Utilization Among Extension Agents in Edo State, Nigeria

Omoregie Osagie — 2025-07-30

The use of digital tools has been hailed as a critical step in advancing agricultural extension work in this decade. This study examined the level of utilization of digital tools in extension service delivery amongst extension agents in Edo State. A structured questionnaire was used to obtain relevant information from fifty (50) out of eighty-eight (88) extension agents in the State, that were selected using two stage sampling procedure. Data were analysed using descriptive (frequency, percentage and mean) and inferential statistic (logit regression). Results showed that there were more males (72%) respondents among the extension agents and majority were single (64%), educated (94%) and in their productive age. Results also show that the extension agents (100%) were aware of most digital tools and were able to use them (mobile phone (mean=3.00), television (mean=2.86), emails (mean=2.86), WhatsApp (M=2.86), Facebook (Mean =2.86). However, the frequency of usage of TikTok, (mean =1.82), YouTube (mean =1.28),E- journals (mean = 1.14) and some others were low. The logit regression result showed a non-significant relationship between the socio-economic characteristics (age =0.025), marital status (2.195, Educational level (1.483) of agricultural extension agents and their usage of digital tools. The study recommended that relevant agencies as well as government and non-governmental agencies should assist in the provision of digital tools to extension agents and encourage them to use modern digital tools that are not frequently used. Also, there should be a comprehensive training programs to enhance the digital literacy skills of extension workers.

Computational study of CuAlO2/ZnO, and NiO/ZnO Perovskite Solar Cells by Numerical Simulation

A. T. Mohammad — 2025-07-30

This study presents a comparative analysis of the performance of CuAlO₂/ZnO and NiO/ZnO perovskite solar cells employs numerical simulation with an emphasis on temperature flactuations, layer thicknesses and electrical propeties using the SCAPS-1D modlling tool, the photovoltaic parameters such as open circuit voltage (V_OC), short circuit current density (J_SC), fill factor (FF), and power convrsion efficiency (PCE) were invstigated under standard test conditions and varying operational senarios. The effects of the hole transport layer (HTL) materials (CuAlO₂ and NiO) on device performace were assessed with particular attention to their band alighment, carrier mobility, and defect density. Results indicate that CuAlO₂ structure achieves higher efficiency due to better band alghment and charge transport properties compared to NiO/ZnO. However, the NiO-based device demostrated superior thermal stability over a wide temperature range. Optimization of HTL thickness and defect density further enhaned device performance with CuAlO₂ exhibiting optimal peformance at lower defects densities. This comparative study provides an insights into material selection an design parameters for efficient and stable perovskite solar cells

Effect of Sodium Carbonate Pretreatment and Pretreatment Duration on Total Solids of Maize Stalk: Response Surface Methodology Approach

Reuben. K Tum — 2025-07-30

Maize stalks (MS) are among the most abundant lignocellulosic crop residues in Kenya, offering considerable but under-utilized energy potential. Although cellulose in such biomass releases about 15 kJ g⁻¹ when burned, converting it to methane can raise the energy yield to roughly 50 kJ g⁻¹. The chief obstacle to microbial access is lignin, which shields the cellulose and hemicellulose fractions in municipal solid waste. To generate biogas efficiently from lignocellulosic feedstocks, co‑digestion is often preceded by enzymatic hydrolysis, and the success of that step hinges on an effective pretreatment that opens the biomass structure. This study evaluated sodium carbonate (Na₂CO₃) as a pretreatment agent for MS, focusing on its effect on total solids (TS) and on identifying an optimum pretreatment time. A central composite design (CCD) guided the experimental matrix, combining several Na₂CO₃ concentrations with different exposure periods: 7 % for 8 days, 3 % for 4 days, 7 % for 4 days, 5 % for 6 days, 5 % for 3 days, 2 % for 6 days, 5 % for 6 days, 5 % for 6 days, 7.8 % for 6 days, 5 % for 8.8 days, 3 % for 8 days and 5 % for 6 days. Changes in TS were used as a proxy for improved digestibility. The optimal pretreatment—7 % Na₂CO₃ applied for 4 days—achieved the highest TS value, 15.15 %, corresponding to a 7.26 % increase relative to untreated MS. Statistical analysis confirmed the fitted TS response model was significant at P < 0.05.

Analysis of the Impact of Climatic Element Variability on Surface Water Degradation in Komadugu Yobe Basin, Nigeria

Babagana Boso — 2025-07-30

This study intended to analyses the impact of climatic variability on surface water degradation in Komadugu Yobe Basin, Nigeria. Its aim to examine the water resources degradation of the basin and its aerial extent. Satellite images were officially sourced and downloaded from the United State Geological Survey website. The images were Landsat generated. Image processing and analysis was done under the supervision of GIS laboratory technician. Image interpretation, classification and overlay was done by GIS expert. Images with digital data was constructed with relevant design and presented in form of maps and tables which reflected land cover changes. Surface water which occupies about 3790.545km²representing 18% of the total area of the Komadugu Yobe Basin in 1972 was reduced to 584.002km²representing a paltry of 3.2% of the total area in 2017. Findings from Key Informant Interview indicated that about 66.5% of the basin communities are farmers engaged in different crop production. Though farming is the dominant economic activity, Fishing and Livestock rearing are the second and third major economic activities in the basin. Climatic variability, particularly, irregular rainfall, declining surface water mainly due to upstream dam construction and climate change are key factors responsible for the surface water degradation. The findings from the study also revealed that decline in surface water and rainfall have resulted in declining food production due to low crop yield, herders and fishermen migration due to none availability of pasture and low fish catch, hence food insecurity at the community level with over 75% of the household became food insecure. The study further reveals that surface water degradation has negative impact on food security of the basin communities. It is recommended that dam re-optimization, awareness creation on water conservation techniques and sustainable agricultural practice, river training (desilting and typha grass clearance in the river bed to improve flow of water for livelihood activities) of the basin would go a long way in addressing water resources degradation of the basin.

Allelopathic Effect of Ivory Coast Almond (Terminalia ivorensis A. Chev.) Leaf Aqueous Extract on Germination and Early Seedling Growth of Maize (Zea mays L.) Cultivars

A. S. Lawal — 2025-07-30

Wider distribution of Ivory Coast Almond (Terminalia ivorensis) into farmland areas, is getting worrisome in northern part of Nigeria. This study therefore aimed to evaluate the allelopathic effect of T. ivorensis aqueous leaf extract on germination percentage and seedling growth of some cultivated maize cultivars (EWH-79, EEWH-123 & TZE-YDT-STR). Petri dish experiment was conducted in the laboratory of Federal University Gusau. Different concentrations of 0% (Distilled water), 5%, 25%, 50% and 100% were prepared from 10g/L crude extract. Germination percentage, length of radicle and plumule were determined. The findings of this study showed Allelopathic interaction of T. ivorensis aqueous leaf extract on germination percentage of the three maize cultivars has no significant effect compared with the Control (P > 0.05). Inhibitory effect of T. ivorensis aqueous leaf extract on plumule length of all the maize cultivars was observed to be significant (P< 0.05). EWH-79 and EEWH-123 showed no variation with the control at 5% of the extract concentration. Furthermore, no pronounced allelopathic effect between the aqueous leaf extract and the control in the radicle length of all the maize cultivars. This study delineated allelochemicals of T. ivorensis inhibits plumule development of the cultivars which in turn affects the plant physiology. The inhibition in increasing order of EWH-79 > EEWH > TZE-YDT-STR.

Effectiveness of Varying Concentrations of Salt and Vinegar against the Bacterial Contaminants of Fruits and Vegetables

U. H. Yuguda — 2025-07-30

Fruits and vegetables, which are of human diets, are regularly tainted by various microbes. Microbial contamination can arise from various causes such as environment, animals, human activity, through transportation or preparation of produce from the farm to the table. The purpose of this study was to evaluate the effects of different vinegar and salt concentrations on the bacterial loads of several fruits and vegetables that are sold in the city of Gombe. For the evaluation, a total of thirty fruits and vegetables from various suppliers were used. A portion of each sample was subjected to a ten-fold serial dilution prior to treatment with either of the two agents. Aliquots of the 10^-1, 10^-2, and 10^-3 dilutions were then inoculated using the pour-plate technique on nutrient agar and MacConkey agar plates. The plates were incubated at 37°C for 24 hours during which the counts of aerobic mesophilic and faecal coliform were observed. Results of the bacterial loads observed prior to washing ranged from 3.7x10⁴ to 2.7x10⁵ and 2.9x10⁴to 8.7x10⁴ for total mesophilic and faecal coliform count, respectively; however, a significant decrease of the bacterial loads of up to 0.77-1.91 and 0.50-1.23 log was observed following treatment with vinegar and salt solutions, respectively. It was concluded that vinegar was significantly more effective than salt in reducing the bacterial loads of the fruits and vegetables (P<0.05). In summary, the fruits and vegetables were found to be contaminated with high bacterial loads that decreased with increased concentrations as well as the exposure time of the vinegar and salt solutions.

Appraising Habitability of Affordable Housing Projects in Nairobi, Kenya

Valerio Musiitwa — 2025-07-30

The objective of this study is to empirically evaluate the habitability of three exemplary affordable housing projects in Nairobi, Kenya, based on criteria related to physical house qualities and architectural excellence. A 24-item questionnaire derived from a synthetic habitability measure was delivered to 92 participants, with data analysis conducted utilising the Severity measure (SI). The findings indicated that respondents primarily derived functional meaning from specific habitability variables such as circulation and access efficiency, locational factors, acoustic quality, and the suitability of height and density, whereas social meaning was predominantly derived from the capacity to foster interaction and the adequacy of privacy. Residents found diminished significance in housing resilience and the implementation of sustainable and renewable systems. Anova tests indicated substantial correlations between inhabitants' essential socio-demographic attributes and specific variables. The analysis of national and global housing standards was conducted using three checklists, while interviews with professionals in architecture, planning, and health were employed to evaluate the impact of the planning system on habitability. Findings can aid policymakers in identifying and prioritising the most significant aspects when formulating future housing plans in Kenya.

An Integrated Diagnostic Model for Identifying and Diagnosing Groundnut Leaf Diseases

Sanusi Dahiru Yerima — 2025-07-30

Groundnut (Arachis hypogaea L.), also known as peanut, serves as a significant source of edible oil and protein, making it essential for the agricultural economy and food security. However, groundnut plants are susceptible to various diseases, notably leaf diseases. Early and accurate identification of these diseases is crucial for implementing timely management strategies to mitigate losses. In recent years, advancements in deep learning especially convolutional neural networks (CNNs), have revolutionized image recognition tasks, including plant disease identification. This study employed the use of ResNet50 and VGG16 Convolutional Neural Networks (CNNs) with Bayesian Optimization (BO). The dataset comprises both infected and uninfected groundnut leaf images, categorized into six folders based on their status. Performance evaluation demonstrates that ResNet50 and VGG16 model’s ability to accurately identify groundnut leaves diseases. Results indicate that the hybrid models ResNet50 and VGG16 effectively captures and distinguishes between infected and uninfected groundnut leaves disease with a high degree of accuracy of 98.72% and 98.22% respectively.

Convolutional Neural Network (CNN) Based Skin Cancer Classification: A Deep Learning Approach

Fatima Umar Daware — 2025-07-30

Skin cancer ranks among the most commonly diagnosed forms of cancer worldwide, with millions of new cases identified annually. Over 2 million cases of non-melanoma skin cancer and approximately 132,000 melanoma cases are reported each year . The study aims is to develop an efficient deep learning model using CNN’s architectures to accurately classify skin lesions as malignant or benign based on dermoscopic images. This study explored the use of Convolutional Neural Network (CNN) models using AlexNet and ResNet architectures for skin cancer classification. The performance of both models were evaluated based on key metrics such as accuracy, precision, recall, and F1-score. AlexNet was trained on 1,200 skin lesion images and validated on 600 images,training spanned 10 epochs. ResNet was similarly trained and validated after 10 epochs. Both architectures were compared under identical conditions (same dataset, pre-processing, optimizer, and hyperparameters). ResNet outperformed AlexNet in all performance metrics of accuracy as 91.00% and 59.00% respectively. This research explored the performance of CNN(ResNet50) and CNN(AlexNet). This validates that deeper architectures with residual connections, batch normalization, and optimized feature extraction are more effective for binary skin cancer classification.

Effect of Step Quenching Ageing on the Wear and Corrosion Properties of Al-Cu-Mg/ 3% Rice Husk Ash Composite

O. B. Umaru — 2025-07-30

This study investigates the impact of Step Quenching Ageing on the Wear and Corrosion resistance behaviour and microstructure of Al-Cu-Mg/ 3% Rice Husk Ash Content that was fabricated via stir casting technique. The temper conditions of the sample involve pre aging at 90°C for 1 hour and further heat treating to 180°C for 1-5 hours respectively. This was compared with the control sample that was aged at 180°C for 5 hours. The corrosion resistance of the Al-Cu-Mg/3%RHA composite was determined using linear polarization resistance technique, while the wear rate was determined using a pin-on disc tribometer. The findings showed improved corrosion and wear rate behaviour of pre-aged samples having a corrosion rate of 9.727E02 mm/yr when put side by side with the control sample, particularly for the 3 hours trials. It was observed that more precipitates (possibly Al, Cu, Al,CuMg, Mg₂Cu or MgCu₂) were established and seen to be more uniformly dispersed in the pre-aged specimens than control sample. It can be affirmed that the step quenching treatment has enhanced the corrosion and wear characteristic of the composite being invested.

Developing a Career Guidance Expert System for Selection of University Programme by Secondary School Students

Awi Godwin Ijupti — 2025-07-30

Selecting an appropriate university programme is a critical decision in the life of a secondary school student. However, many students make this decision without adequate professional guidance, leading to poor career alignment and underutilization of their potential. The lack of structured and accessible career counseling services in many schools further exacerbates this issue. This study presents the design and implementation of an Intelligent Career Guidance Expert System using Decision Tree Algorithm, Rule-Based Inference Engine, and Fuzzy Logic to assist students in making informed university programme choices. The system leverages artificial intelligence techniques to provide personalized recommendations based on students’ academic performance, vocational interests, personality traits, and career aspirations. A diverse dataset was compiled, including academic records, interest inventories, and personality indicators. The architecture of the expert system integrates a decision tree algorithm optimized via hyperparameter tuning (e.g., adjusting max_depth) alongside rule-based inference and fuzzy logic components to simulate expert reasoning. The system was trained and validated using real-world data from secondary schools and historical university admission records. Results showed that the decision tree model achieved high accuracy in mapping student profiles to appropriate programmes. The integration of rule-based reasoning and fuzzy logic further enhanced the system’s ability to handle uncertainty and expert-level nuances in decision-making. This expert system demonstrated the potential to offer reliable, cost-effective, and time-saving guidance, outperforming traditional counseling approaches. It provided students with data-driven, objective recommendations aligned with their long-term academic and career goals. The study underscores the value of integrating expert systems into school counseling services. Future improvements may include incorporating psychometric assessments, expanding datasets across various regions, and implementing feedback mechanisms involving human counselors to refine system performance continuously.

Biodegradation Efficacy of Bacillus cereus and Pseudomonas aeruginosa on Polythene Bags

Sabiya F. A. — 2025-07-30

Plastic pollution arises as the second obvious threat to the world environment after global warming. This is a descriptive cross-sectional research design aim to evaluate the efficiency of bacteria as biodegradable organisms on polythene bags. The selected bacterial isolate was identified by morphological characterization like shape, size, structure, texture, appearance, elevation and colors. Phenotypic characteristics such as microscopic characterization of gram reaction, motility were performed the standard protocols. Bacillus cereus degrades 1.000g of polythene bag in 30 days to 0. 975g. Pseudomonas aeruginosa degrades 1.000g of polythene bag in 30 days to 0. 955g. The percentage of polythene bags loss at day 30 was 3.10% weight loss when treated with Bacillus cereus, when treated with Pseudomonas aeruginosa at day 30, the percentage lost was 4.50%. The overall investigation can be concluded that P. aeruginosa and other species exhibited significant polythene degradation ability and in the near future, Pseudomonas sp. can be used to reduce the quantity of plastic waste, which is rapidly accumulating in the natural environment. Among the two isolates tested.

In-vitro Anti-Plasmodial Activity of Mangifera indica Leaves Against Plasmodium falciparum

Muhammad R. H. — 2025-07-30

Malaria remains a critical global health concern, particularly in sub-Saharan Africa, where Plasmodium falciparum accounts for the majority of infections and fatalities. With increasing resistance to the current antimalarial treatments, including artemisinin-based combination therapies (ACTs), there is growing interest in exploring natural remedies, especially plant-derived alternatives. The current study investigated the in-vitro antiplasmodial activity of aqueous leaf extracts of Mangifera indica (mango). Phytochemical evaluation of the leaf extract revealed the presence of flavonoids, tannins, saponins, and terpenoids, compounds with known pharmacological relevance. The extract showed a reduction in parasitemia in the culture based on different concentrations, achieving a maximum inhibition rate of 93% at 10 mg/ml, comparable to that of the artemether control (96%). The study's findings revealed that M. indica leaf extract holds promise as an affordable and effective candidate for the development of antimalarial drugs. Further investigations should focus on isolating specific active compounds, elucidating their mechanisms of action, and conducting in vivo validation studies, which are highly recommended.

Comparative Phytochemical Screening and Antimicrobial Activities of Acacia nilotica (L.) Delile and Morinda citrifolia (L.) Extracts against selected Bacterial strains

K. K. Abubakar — 2025-07-30

Plants have long been recognized as reservoir of bioactive compounds with therapeutic potentials, many of which possess antimicrobial properties. Among these, Acacia nilotica and Morinda citrifolia have attracted scientific interest due to their ethnomedicinal application and rich phytochemical profiles. This study investigated the phytochemical constituents and antibacterial efficacy of Acacia nilotica (L.) Delile and Morinda citrifolia L. extracts against five clinical bacterial strains: Escherichia coli, Staphylococcus aureus, Proteus mirabilis, Salmonella typhi, and Klebsiella pneumoniae. Ethanol extracts of stem bark and leaves of A. nilotica, as well as leaves and fruit of M. citrifolia, were evaluated using standard phytochemical screening, agar well diffusion assay, and MIC/MBC determinations. Phytochemical analysis revealed a rich presence of bioactive compounds. A. nilotica stem bark and leaves contained high levels of tannins (+), flavonoids (+), and saponins (+), while M. citrifolia fruit and leaves showed strong positivity for steroids (+), alkaloids (+), and flavonoids (+), though they lacked terpenoids and tannins. Antimicrobial results showed that all extracts exhibited concentration-dependent inhibition. At 100 mg/mL, A. nilotica leaf extract recorded the highest zone of inhibition (28.00 ± 0.70 mm) against P. mirabilis, followed closely by A. nilotica stem bark (27.65 ± 0.58 mm) and M. citrifolia fruit (23.93 ± 0.94 mm) against S. aureus. Streptomycin (100 µg/mL) served as control, producing inhibition zones ranging from 26.43 mm (S. aureus) to 27.82 mm (P. mirabilis). Minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) tests confirmed the potency of A. nilotica extracts. The lowest MICs were recorded by A. nilotica stem bark against S. aureus (6.81 mg/mL) and P. mirabilis (6.97 mg/mL), while M. citrifolia leaf and fruit showed higher MICs ranging from 12.01–15.46 mg/mL, with the highest MIC observed against E. coli (15.46 mg/mL). Corresponding MBCs followed a similar trend, with A. nilotica generally achieving bactericidal effects at half the concentration required by M. citrifolia. Overall, A. nilotica extracts demonstrated superior antibacterial activity compared to M. citrifolia, likely due to higher concentrations of polyphenolic compounds and tannins. These results support the traditional use of both plants in ethnomedicine and highlight the therapeutic potential of A. nilotica in combating bacterial infections, particularly those involving P. mirabilis and S. aureus.

An Autonomous Framework for Crop Monitoring and Management Using Machine Learning Techniques

Mingyi Charity Lazaru — 2025-07-30

Agriculture remains a cornerstone of global food security and economic development, particularly in developing countries. However, modern agriculture faces significant challenges such as crop diseases, irregular weather patterns, inefficient resource utilization, and lack of timely intervention, all of which can impact crop yield and sustainability. To address these issues, this study proposes the development of an autonomous framework for crop monitoring and management using machine learning (ML) techniques. The objective is to create a smart, data-driven system capable of predicting crop health, optimizing input use (such as fertilizer and water), and supporting farmers in decision-making through real-time insights. To achieve this, a diverse crop data-set was collected from open-source repositories and local farm sensors, including features such as soil nutrient levels (Nitrogen, Phosphorus, Potassium), environmental factors (temperature, humidity, rainfall), and crop performance records. Several machine learning algorithms including Random Forest, Gradient Boosting, and Convolution Neural Networks were evaluated for their suitability in predicting crop conditions, recommending best-fit crops, detecting early signs of disease, and suggesting irrigation and fertilizer practices. This study addresses the persistent challenges in agriculture such as crop diseases, resource inefficiencies, and unpredictable weather by developing an autonomous crop management and monitoring framework powered by machine learning (ML). The system utilizes a combination of open-source and locally collected farm data, including soil nutrients and environmental conditions, to predict crop health, recommend optimal inputs, and detect diseases. Among the ML models tested, Random Forest demonstrated the highest accuracy (91.2%) in crop recommendation and disease prediction. The framework integrates Io T sensors, drone imagery, and a mobile interface to deliver real-time insights to farmers. Overall, the system aims to improve decision-making, reduce resource waste, and enhance agricultural sustainability, with future plans to scale and adapt it for broader agro-ecological applications.

Impact of Human Activities on Biodiversity in Yola North Local Government Area, Adamawa State, Nigeria

AHMED F. M — 2025-07-30

Primary reasons for biodiversity loss are environmental pollution, destruction of natural habitats, overuse of biological resources, and population explosion. This study aimed to ascertain the impact of human activities on biodiversity in Yola North LGA. Descriptive survey research design was employed for the distribution of well-structured questionnaire. The sample for the study comprises 384 residents that was randomly selected from Doubeli, Jambutu, Karewa, Luggere, and Nasarawo Wards of Yola North LGA, Adamawa State. The data was analysed using Statistical Package for Social Sciences (SPSS) version 23.0. The analysis of the impact of population growth on biodiversity showed that majority of the respondents agreed that population affects; air, water and fishing activities, the impact of pollution on biodiversity is shown in the contamination of water bodies, reduced agricultural yield and tree growth. The responses of the respondents showed that majority agreed that habitat loss restrict animals from moving freely and can causes extinction in insect species. The study found that pollution significantly impacts biodiversity, aligning with global studies. Land use change was also found to significantly impact biodiversity, which is consistent with global research. Habitat loss was found to significantly impact biodiversity, which aligns with global studies.

Suitability of Fobur Biotite – Granite as an Aggregate Construction Material, Jos, North Central Nigeria

Abalaka Isaac Edimeh — 2025-07-30

The physical properties of the Fobur Granites in Plateau State were examined with the aim of determining their suitability as aggregates for construction. Some rock samples were collected from different points within the study area. Ten (10) samples were collected and their specific gravity values were determined using the pyncometre. Their specific gravity values range from 2.597 to 2.654. Its low percentage measured from the percentage pass indicates that more energy is needed to dislodge or disassemble the rock particle. The energy required to do this is called the comminution energy as compared to the specific gravities of different types of soil / rock aggregates. The average specific gravity of the granites in Fobur falls within the range of the standard specific gravity of rocks. As a result, the granites in Fobur community can be for use as construction aggregates. From literature, granites are composed of quartz, orthoclase, hornblende and biotite. The mineral composition of granites in Fobur gives them a specific gravity that is more than 2.50. The research objective is to determine the suitability of Fobur Biotite Granite as an aggregate construction material in Jos, North Central Nigeria.

Characterisation of Soils in Angwan Michika, Using Their Compaction Behaviours, Jos, North Central, Nigeria

Abalaka Isaac Edimeh — 2025-07-30

The study area is around Angwan Michika metropolis. Ten (10) soil samples were investigated using compaction test analysis. The study area is located on Latitudes N 9⁰ 84^’ 72^” to 8⁰ 89^’ 36^” and Longitudes E 9⁰ 86^’ 78^” to 8⁰ 90^’ 44^”. The compaction tests and their interpretation revealed that, soil samples collected at locations 1, 6, 7, 9 and 10 were inferred to be competent soils since there are (1,6,7,9 and 10) made up of sand and gravel materials. Soil samples collected at locations 2, 3, 4, 5 and 8 were inferred to be incompetent, they are basically clayish in nature. In terms of optimum moisture contents, the incompetent soil materials had a range of 17.20 to 23.70 % while the competent soil samples had a range of 10.40 to 12.80 %. In terms of maximum dry densities, soils in the incompetent areas had a range of 1.67 to 1.84 % while the soils in the competent areas had a range of 1.84 to 1.91 %. According to the specifications for roads and bridges in 2017, soil samples from the incompetent areas have high optimum moisture content and low maximum dry density. As a result, civil engineering structures like roads cannot be constructed in areas that the soil samples are incompetent. The sand and gravels that characterise the competent areas do not pose any threat to civil engineering structures rather they help in concretising and solidifying them. The clay material that characterise the incompetent areas makes them to be susceptible to frequent shrinkage and swelling during variations in climatic conditions. This constant alteration leads to cracks, potholes and complete damage of the road. The soil is there by mechanically unfit for road constructions.

Prevalence and Risk Factors of SARS-CoV-2 Among Patients with Suspected Respiratory Infections at Specialist Hospital, Gombe State, Nigeria

Adamu Bello Yakubu — 2025-07-30

The novel corona virus (SARS-CoV-2) has quickly spread from person to person and claimed millions of lives worldwide. However, there is a lack of epidemiological data on this infectious agent in Gombe State. This study aimed to determine the prevalence of SARS-CoV-2 and its associated risk factors among patients with suspected respiratory infections attending the General Hospital in Gombe State, Nigeria. Approximately 200 nasopharyngeal and/or oropharyngeal samples were collected from participants across Gombe State and screened for COVID-19 using Rapid Diagnostic Kits (RDT). In addition, Semi-structured questionnaires were used to collect additional demographic data. The data were analyzed statistically using SPSS version 22. The results indicated an overall prevalence rate of 26.5%. Chi-square analysis showed that demographic factors such as gender, age, location, and educational background were significantly associated with COVID-19 infection, while tribe and occupation were found to be statistically insignificant. Additionally, binary and multiple logistic regression analyses identified male sex, adult age, urban residence, and lower education levels as significant risk factors for COVID-19 infection. Therefore, this study recommends the implementation of a vaccination program to help contain the spread of SARS-CoV-2 infection.

Isolation of Catechin and Catechin Glycoside from Indigofera welwitschii (Fabaceae)

A. Muntaka — 2025-07-30

Proper phytochemical investigations of medicinal plants derived constituent has become of paramount importance owing to their versatile application as lead molecules in conventional medicine and as herbal medicine traditional practices. Indigofera welwitschii is not an exception. It belongs to genus Indigofera belongs and family fabaceae (Leguminaceae) that are well known for their ethnomedicinal claims and establish pharmacological activities. The aim of the study is to isolate and characterize phenolic compounds from the ethylacetate fraction of the methanol extract of Indigofera welwitschii. The preliminary phytochemical screenings of aerial parts (whole plant, leaves, flowers, seed and seedling) alone revealed the presence of different classes of compounds of which phenolic compounds are the most abundant. The method employed the use of silica gel chromatographic separation of the ethylacetate fraction using gradient elusion followed by repeated gel filtration using sephadex LH-20 to purify and obtain pure isolate; while the structure of the compound as was confirmed on the basis of chemical test, 1D- & 2D-NMR spectroscopy and comparison with an existing reported literature. catechin (a flavan-3-ol) and catechin glycoside were isolated. On the bases of literature search, this experimentation appears to be first report of isolation of epicatechin from the ethylacetate fraction of aqueous methanolic extract of the aerial parts of Indigofera welwitschii.

A Review of Dimension Reduction and Feature Selection: A New Perspective

Simon Ashiru — 2025-07-30

With the rapid growth of high-dimensional data, dimensionality reduction has become essential for improving computational efficiency and model performance. This paper presents a comprehensive review of two primary approaches to dimensionality reduction: feature selection (FS) and feature extraction (FE), with particular emphasis on the Chi-Square-based feature selection technique. While Chi-Square has been widely adopted due to its simplicity and effectiveness, its dependence on document frequency introduces notable limitations. This review highlights key developments in feature selection strategies, identifies gaps in existing Chi-Square-based methods, and explores recent improvements proposed in the literature. Finally, the paper offers a new perspective on enhancing Chi-Square by incorporating contextual relevance and hybrid scoring mechanisms, setting the stage for future research.

Community Satisfaction for People with Physical Disabilities in Mubi: The Impact of Home Modification

K. C. Okoye — 2025-07-30

This study examined the relationship between home modification and community satisfaction for people with physical disability that effect mobility in Mubi, North Eastern Nigeria. A total of 50 people with physical disabilities that effect mobility, comprising of 25 adults in Mubi North and 25 adults in Mubi South local government areas of Adamawa state were randomly selected. Home modifications relating to; entrance to the buildings, access to goods and services, usability of rest rooms, were implemented for people in Mubi North, while people in Mubi South waited for their turn. Vreugdenhil & Rigby General Community Satisfaction Scale (GCSS) was used as the measurement tool and administered one on one to the respondents before the execution of home modifications and after three months of the modifications. Responses to each item in the GCSS are provided on a 5 point Likert scale ranging from “strongly disagree” to “strongly agree”. Findings from the study indicates that community satisfaction was significantly enhanced for the participants in Mubi North after home modification with mean score 4.111 (p=0.001), as compared to the waiting participants in Mubi south with score1.780 (P=0.126). Overall Satisfaction with modification outcomes has a significant positive correlations at p<0.01 level with the variables of home modification. The study recommends that home modification should be recognized as a key element for residential satisfaction that enhances safety, accessibility, and comfort, allowing individuals, especially those with disabilities, to live independently and satisfied within their own homes and communities.