Adams Adewale1, Helen Ali1, Sewanu Akapo1

Introduction: Access to safe drinking water remains a critical public health concern, particularly in developing countries where inadequate sanitation, poor water treatment, and faecal contamination contribute to the spread of waterborne diseases. In Lagos State, Nigeria, limited access to potable water forces many communities to rely on alternative sources that may be microbiologically unsafe, posing significant health risks, especially to school children. Aims: This study aimed to assess the physicochemical and bacteriological quality of drinking water in selected public primary schools in Lagos State, Nigeria. Materials and Methods: Water samples were collected from twenty public primary schools using standard sampling procedures. Physicochemical parameters, including temperature, pH, turbidity, total dissolved solids, residual chlorine and Visual inspection, Colour, Taste, Odour, Iron, Total acidity, Total hardness, Calcium hardness, Magnesium hardness, Chloride, Nitrite, Nitrate, Organic matter, and Salinity, were analysed using standard laboratory methods. Bacteriological quality was determined using the pour plate method for total plate count and the Most Probable Number (MPN) technique for coliform detection. Isolates were further identified based on morphological and biochemical characteristics. Results: Most physicochemical parameters were within acceptable limits; however, pH values were generally acidic, and several samples showed elevated total dissolved solids. Residual chlorine was absent in all samples, indicating inadequate disinfection. Bacteriological analysis revealed that the majority of samples exceeded recommended limits, with 85% testing positive for coliforms. Identified organisms included Escherichia coli, Klebsiella, Enterobacter, and Citrobacter species, indicating faecal contamination. Conclusion: Despite acceptable physicochemical properties, the presence of high microbial loads renders the water unsafe for consumption. The findings highlight the need for improved water treatment, regular monitoring, and better sanitation practices in public primary schools to reduce the risk of waterborne diseases.

Cornelius Ogab1, Tijani Shehu1, Babatunde Idowu1, Olorunfemi Fakunle1, Eugene Onori1, Rilwan Mustapha2, Muyiwa Bamgbose1, Shu’aib Muhammad1

Introduction: Nonlinear dynamical systems show complex behaviour sensitive to initial conditions. Controlling and synchronising chaos has applications in engineering, science, secure communications, encryption, biology, chemistry, finance, neural networks, cryptography, and medicine. Aim: This paper aims to analyze the synchronisation, tracking control, and stability of hyperchaotic 5D Lorenz systems. A linear feedback controller is built to ensure asymptotic stability of the two identical hyperchaotic 5D Lorenz systems developing from distinct initial conditions, based on Lyapunov stability theory and active backstepping nonlinear approaches. Methods: The three positive Lyapunov exponents and complex dynamical behaviour of the hyperchaotic 5D system are demonstrated. The control functions for the corresponding control and synchronisation of the hyperchaotic 5D Lorenz system are designed using the active backstepping nonlinear technique. The nonlinear controllers of the intended backstepping can stabilise and direct the hyperchaotic 5D Lorenz system at any place to follow any smooth function of time trajectory. The proposed method integrates the selection of a Lyapunov function with the creation of active control, and it is a systematic design technique. To validate the feasibility and effectiveness of the proposed control technique, numerical simulation results are presented. Conclusion: The use of an active backstepping control approach to control and synchronise the hyperchaotic 5D Lorenz system stabilises chaotic motion, simplifies design without needing eigenvalues, and efficiently controls high-dimensional hyperchaotic systems, outperforming conventional chaos. Thus, numerical simulations confirm effectiveness.

Taofik Ajagbe1, Mba Odim2, John Akintayo21, Funmilayo Olopade3, Benjamin Aribisala1,3

Introduction: Dementia represents a significant global health challenge, affecting over 55 million individuals worldwide and projected to triple by 2050 due to aging populations. Early diagnosis is critical for effective intervention, symptom management, and resource planning. Machine Learning (ML) has been identified as a tool that can be used to diagnose dementia. Aims: This study aimed to develop and compare ML Models for Dementia diagnosis using clinical dataset. Materials and Methods: The study utilized a publicly available dataset from Kaggle comprising 2,149 patient records. Data pre-processing was employed to address missing values, outlier handling, normalization, and class imbalance using SMOTE. Models were trained on 70% of the data and tested on 30%. Performance was assessed using sensitivity, specificity, accuracy, F1-score, and Area under the receiver operating curve (AUC-ROC). Features include demographic information (age, gender, education), lifestyle factors (BMI, smoking, physical activity), medical history (diabetes, hypertension), vital signs (blood pressure, cholesterol), and cognitive assessments (MMSE, functional assessment, ADL). Six machine learning classifiers; Logistic Regression (LR), Support Vector Machine (SVM), Random Forest (RF), K-Nearest Neighbors (KNN), Naive Bayes (NB), and Multi-Layer Perceptron (MLP) were employed to build the model for dementia diagnosis. We evaluated the model using accuracy, precision, recall, F1-score and Area Under Curve. We finally compared the metrics from the six models. Results: RF classifier achieved the highest performance with 88.32% accuracy, 87.41% Sensitivity, 89.12% Specificity, 88.32% F1-Score and 94.12% AUC-ROC, SVM and MLP followed closely, while KNN showed the lowest performance due to sensitivity to noise. Conclusion: This work provides valuable insights that ML models can predict Dementia using clinical dataset especially RF which has the highest metrics. ML tools in dementia diagnostics, potentially enhancing early detection and patient outcomes.

Kehinde Sotonwa1, Tomiloba Olowo1, Hanat Raji- Lawal1, Adedoyin Odumabo2, Folasade Okikiola3, Idris Aremu2, Mariam Aliyu1, Ogunyemi Oluwapelumi1

Introduction: Skin cancer incidence is increasing globally, making early and accurate diagnosis essential. Dermoscopy improves detection but is limited by clinician variability. Automated segmentation using deep learning offers a promising alternative, though challenges such as image variability and artifacts remain. Aims: To develop and evaluate an improved UNet++-based model for accurate skin lesion segmentation and classification in dermoscopic images. Materials and Methods: The study utilised the ISIC 2018 dataset comprising 2,694 dermoscopic images with corresponding expert-annotated segmentation masks. A UNet++ architecture with an ImageNet-pretrained EfficientNet-B5 encoder was implemented. Data augmentation techniques, including geometric and photometric transformations, were applied to improve generalisation. A composite loss function combining Dice loss (50%), binary cross-entropy (30%), and focal loss (20%) was used to address class imbalance and improve boundary delineation. Model performance was evaluated using sensitivity, specificity, accuracy, Dice coefficient (DC), Intersection over Union (IoU), F1-score, and area under the curve (AUC). Results: The model achieved classification sensitivity of 0.8900, specificity of 0.9200, accuracy of 0.9500, F1-score of 0.8870, and AUC of 0.9278. For segmentation, it achieved a Dice coefficient of 0.8870 and an IoU of 0.8200. The model outperformed U-Net and showed consistent improvements over O-Net across key metrics. Conclusion: The proposed UNet++ framework improves segmentation accuracy and classification performance, demonstrating strong potential for clinical application in automated skin cancer diagnosis.

Adams Adewale1, , Sewanu Akapo1, Olabimpe Egberongbe2, Akeeb Oyefolu1

Introduction: Access to safe drinking water is essential for human health, yet water quality remains a major public health concern, particularly in developing countries experiencing rapid urbanisation and environmental stress. In healthcare settings, contaminated water poses an even greater risk due to the vulnerability of patients to waterborne infections. However, there is limited information on the quality of hospital drinking water in Lagos State, Nigeria. This study therefore assessed the physicochemical and bacteriological quality of drinking water in selected hospitals in Lagos State. Aims: To determine the physicochemical properties, total plate count, coliform count, and identify isolated coliform bacteria from water samples in hospitals in Lagos State. Materials and Methods: Water samples were collected from 20 hospitals in Lagos State using sterile and labelled bottles and transported under cold conditions (4°C) prior to analysis. Physicochemical parameters including Temperature, Visual inspection, Colour, Taste, Odour, pH, Conductivity, Turbidity, Total dissolved solids, Residual chlorine, Iron, Total acidity, Total hardness, Calcium hardness, Magnesium hardness, Chloride, Nitrite, Nitrate, Organic matter, and Salinity were determined using standard laboratory methods. Bacteriological analysis was carried out using the pour plate technique for total plate count and the most probable number (MPN) method for coliform count. Isolates were further identified based on morphological and biochemical characteristics. Results: All samples had pH values ranging from 5.4 to 6.2, below recommended standards, indicating acidity. Most physicochemical parameters were within acceptable limits, except total dissolved solids, where 5 samples exceeded the standard. Microbiological analysis showed that 12 (60%) samples exceeded the WHO limit for total plate count, with 8 samples recorded as too numerous to count. Additionally, 15 samples contained coliforms above acceptable limits, including Escherichia coli, Klebsiella species, Proteus vulgaris, Enterobacter species, and Citrobacter species, indicating faecal contamination. Conclusion: The study reveals that most hospital drinking water samples were microbiologically unsafe and acidic, posing potential health risks. Regular monitoring, improved treatment, and strict water safety practices are recommended to ensure a safe water supply in healthcare facilities.

Ladan, Haruna Aminu1

Introduction: The energy sector poses one of the greatest challenges in most nations as it influences economic growth. Decades of neglect of renewable energy sources has resulted in over dependence on hazardous fossil-fuel. Aims: In this study, we reported the development of high-performance lead-free methyl ammonium germanium halide (CH3NH3GeI3) based Perovskite Photovoltaic cells using computational method. Materials and Methods: The optical property of two dimensional (2D) graphene and mxenes nanocomposites as hole and electron transporters were incorporated to optimize the device performance using SCAP 1D software. The effect of several parameters on the solar cell performance were investigated such as thicknesses of perovskite, hole-transporting materials (HTMs), defect density, hole mobility, and metal electrode work function on the charge collection. Results: Ge-based PSCs with graphene and mxenes (Ti3C2) and TMDCs (NiS2/NiTe2) as alternating HTMs exhibited a remarkable power conversion efficiency (PCE) reaching 21% and a 62.01V; 0.60 mAcm-2; 80.10% as open-circuit voltage, current density and fill factor respectively. Conclusion: Our results advocate for a simple and safe design of HTMs for highly efficient and stable solar cells at low cost.

Kayode Idowu Ogungbemi1, Muteeu Abayomi Olopade1, , Ayo Zaccheaus Ibitoye2, Jadesola Fatimah Iyowu1, Oluwamayowa Joseph Adeoye1, Samuel Abisoye Shittu1

Introduction: Standalone diagnostics centres are be established in compliance with the radiation protection and safety measures. Aim: The study aims to evaluate the radiation safety level in standalone X-ray diagnostic radiological centres. Methods: Five Standalone radiological diagnostic centres have been studied in terms of the mAs, kVp and the annual effective dose obtained during radiological procedures. The annual effective dose is estimated from the instantaneous doses’ measurement using a radiation survey meter (survey meter was held at about 1.2 meters high), Geiger counter version BR- 9C with threshold setting based on the World Health Organisation (WHO). The measurement ranges between 0 µSv/h and 99.99 µSv/h, with real-time measurement and real-time error ≤ 10%. The mAs and kVp measurements were obtained directly from the X-ray machines used. Results: The highest kVp obtained is 80kV, and the lowest is 45kV; while the highest mAs is 129.7 mAs, and the lowest is 2.83 mAs. The highest annual effective dose from these radiological diagnostic centres is 21.23 mSv/y, and the lowest is 2.31 mSv/y. Discussion: The annual effective dose obtained from this study is within the recommended dose (whole body) by ICRP for radiation workers. However, for the patients, it is high for individuals, but the standalone radiological diagnostic centres are safe. Conclusion: The variation in X-ray tube currents and the kVp values are factors that contributed to radiation doses in these studied centres, and the annual effective doses due to the scatter radiation shows significant effect on the annual cumulated doses on both the patients and radiation workers in most of the centres. The lowest value of annual effective dose from all the centres is 2.31 mSv/y, high for an individual part of the body for non-radiological workers. Unprotected patients or workers during the diagnostic procedures are at high risk of the highest radiation doses obtainable from the X-ray machine at any given time.

Khadijat Oreshile1, Olajide Keshinro1, Taobat Keshinro2, Habibat Ishola1

Introduction: Mushrooms have been broadly used in folk medicine for the treatment of various diseases for years. Polypores are cosmopolitan mushrooms that are widely investigated for their useful properties in battling multidrug-resistant pathogens. Aims: This study investigated the phytochemical, antioxidant and antibacterial properties of wild Bondarzewia berkeleyi and Ganoderma lucidum. The fruiting bodies of G. lucidum and B. berkeleyi were collected at Lagos State University, Ojo Campus. Materials and Methods: Extraction was done using methanol and acetone. Standard tests were carried out to detect different phytochemical compounds present in the mushroom extracts. These phytochemical compounds were further estimated and quantified using standard methods. The antioxidant activity of the extracts was evaluated using a DPPH (2,2-Diphenyl-1-picrylhydrazyl) radical scavenging assay, while antimicrobial activity on Pseudomonas aeruginosa and Salmonella typhi was carried out using the paper disc diffusion assay. Results: Results showed that reducing sugar, terpenoids, steroids, phenolics, flavonoids and triterpenoids were present in both mushrooms while tannins, alkaloids and anthraquinones were absent. Saponins appeared to be present only in the methanolic extracts, while cardiac glycosides were detected only in the acetone extract of both mushrooms. The highest antioxidant activity was recorded in the acetone extract of G. lucidum (90.435±0.112) and the least was recorded in the acetone extract of B. berkeleyi (26.632±0.129), while both mushroom extracts showed antibacterial effects against both tested organisms. The highest inhibition zone was exhibited by the methanolic extract of G. lucidum against P. aeruginosa ranging from 10 mm to 14 mm while the least inhibition zone ranging from 0 mm to 11 mm was exhibited by S. typhi for the extracts. Nevertheless, P. aeruginosa appeared to be more sensitive to G. lucidum extract than S. typhi, which exhibited the smallest zones of inhibition. Conclusion: Based on this research result, these mushroom extracts are a good source of phytochemicals that show potential for antibacterial and antioxidant activity; therefore, they can be exploited as therapeutic products.

Mautin Hunkanrin1, Abdulazeez Giwa1, Sobola Sokefun1, Oluwatosin Adebola1, Abiodun Adams1, Peter Ojo2

Introduction: Fish have recently proved their ability to quickly adapt to newly invaded habitats. The Chrysichthys nigrodigitatus, Silver Catfish is a highly valued commercial fish in Nigeria and other West African countries due to its high nutritional content and market demand. Intra specific variations in the silver catfish are critical for understanding the population dynamics. The study was designed to evaluate phenotypic differences and growth patterns in the Silver Catfish, across Southwestern Nigeria. Aims: To correlate meristic and morphometric measurement, determine homogeneity and heterogeneity of the specie, and evaluate phenotypic differences amongst the groups. Materials and Methods: One hundred and forty-five samples of C. nigrodigitatus were collected from artisanal fishermen at four locations namely the Epe and Ojo Lagoon, Badagry Creek, and the Abeokuta River. Morphological attributes were evaluated using sixteen morphometric measurements, and statistical analyses such as descriptive statistics, one-way ANOVA, and correlation analysis were performed Results: Morphometric variations were observed in body length, head width and other variables with mean value of parameters ranging from 0.67±0.26 in Head Depth at Epe to 23.164±3.57 in Total Length at Abeokuta. Samples from Abeokuta, Ojo, and Epe exhibited negative allometric growth (b <3), while Badagry showed positive allometric growth(b>3). Conclusion: This study highlights the importance of understanding intraspecific variations in C. nigrodigitatus and their ability to adapt to different environments. Highlighting the benefits of phenotypic study in order to assess species population and conserve genetic trait. Variations between populations observed could be as a result of exposure to environmental constraints.