International Journal of Science for Global Sustainability

Epidemiology and Risk Factors of Urinary Schistosomiasis Among Residents Within Dallaje Reservoir, Bindawa Local Government, Katsina State, Nigeria

Ahmed Ibrahim Suleiman — 2025-10-25

Schistosomiasis remains a major neglected tropical disease and a leading cause of morbidity in sub-Saharan Africa. Schistosoma haematobium, transmitted via freshwater snails, is responsible for urinary schistosomiasis, with school-aged children being the most vulnerable. This study assessed the prevalence and predictors of urinary schistosomiasis among residents near the Dallaje Reservoir, Katsina State, Nigeria. A cross-sectional survey was conducted among 392 schoolchildren aged 7–15 years. Socio-demographic data were collected using pre-tested questionnaires. Urine samples were examined for S. haematobium eggs by sedimentation, and statistical analysis was performed using chi-square tests with significance set at p ≤ 0.05. The overall prevalence of urinary schistosomiasis was 28.6%. Infection was detected exclusively in males (46.7%), while no cases were recorded among females (0%), reflecting significant gender disparity (p < 0.0001). Age-specific prevalence was highest among children aged 13–15 years (37.6%). Children of working-class parents were significantly more affected (p < 0.0001), likely due to reduced supervision. No association was found between parental education and infection (p = 0.5867). Engagement in water-related activities such as swimming, fishing, and irrigation was strongly linked with infection risk (p < 0.0001). Urinary schistosomiasis remains highly prevalent around the Dallaje Reservoir, with transmission strongly influenced by gender, age, parental occupation, and water-contact behaviors. The absence of infection in females highlights cultural practices that limit exposure. Control strategies should prioritize gender-sensitive interventions, improved water and sanitation access, and targeted health education for at-risk populations.Schistosoma haematobium

Application of Two-Stage Stochastic Programming for Multi-Product Inventory Optimization in a Nigerian Pharmaceutical Firm

Afolabi Oludele Raphael — 2025-10-25

Inventory management remains a key challenge in pharmaceutical supply chains, especially in emerging markets like Nigeria. Unpredictable demand, poor infrastructure, and limited budgets often cause stock imbalances. Traditional inventory models work well in stable environments but struggle to manage demand and lead time uncertainties. This study uses a two-stage stochastic programming model to improve multi-product inventory management for Miracle Kudura Pharmacy, a Nigerian retail and wholesale distributor. Based on 37 months of sales, holding, and ordering cost data for over 100 products, the model incorporates uncertainty through probability distributions grounded in real figures. In the first stage, it sets preliminary order quantities without knowing actual demand. In the second, it updates these quantities as actual demand becomes clear. The initial stage reduced inventory costs to ₦1,224,000, demonstrating cost-effective efficiency. The second stage, however, reported a total cost of ₦1,435,000, showing a trade-off between cost savings and flexibility. Sensitivity analysis revealed that demand for products such as Clarten and Postinor varied widely, while items like Tribotan were more stable. These findings highlight the importance of stochastic models in managing costs, service levels, and risks which are crucial factors in pharmaceuticals where shortages impact public health. Overall, the study highlights how stochastic optimization offers practical, adaptable solutions for managing pharmaceutical inventory in resource-constrained environments.

Flood Risk Mapping in the River-Rima Basin, Kebbi State, Nigeria: A Geographic Information System-Based Approach

M. Aliyu — 2025-10-25

Floods are a growing menace to human life, as well as to infrastructure and agricultural yields in emerging river floodplain regions. The River Rima floodplain is well known in Birnin Kebbi for its agricultural production, especially rice production, which is essential to local livelihood and food security. This study employs an integrated GIS and Analytic Hierarchy Process (AHP) approach to evaluate flood risk zones within the River Rima basin, Nigeria. Six geomorphological and hydrological factors (elevation, slope, drainage density, rainfall, soil type, and land use) were weighted through pairwise comparisons to generate hazard and vulnerability indices. The Flood Hazard Index was accomplished. Settlement distribution was taken as a susceptibility criterion to create the Flood Vulnerability Index. By linking these maps with indices, a flood risk map was generated, which shows that the study area is divided into high (25.29%), moderate (29.64%), and low (45.07%) flood risk classes, indicating that more than half of the floodplain is at risk of floods. The research identifies six main flood hazard predictors: elevation (38.1%), drainage density (19.6%), slope (17.8%), mean annual rainfall (12.2%), soil type (6.4%), and land use (6.0%). This means that elevation and drainage density, which are geomorphological factors, play a major role in causing floods in the area. Urban expansion poses a great threat to settlements like Ambursa, Birnin Kebbi, and Dagere, whereas settlements like Makerah, Anguwar Kayi, and Maurida are located in the floodplain and are therefore very prone to the effects. Farmland and built-up land are the most at-risk elements, with 64.7% of farmland and 70.2% of built-up areas classified as highly or moderately vulnerable. Based on these findings, the study recommends incorporating land-use zoning, community-based flood preparedness, and relocating critical infrastructure. The implementation of long-term planning strategies demands both climate change projections and machine learning technologies for future flood modelling.

Enhancing Biogas Quality and Energy Content through Calcium Hydroxide Treatment: A Study on the Effectiveness of 20% Ca(OH)2 Solution in Improving Methane Content and Reducing Impurities

B. A. Umar — 2025-10-25

This study investigates the effectiveness of treating biogas with 20% calcium hydroxide solution to improve its quality and energy content. The treatment process significantly increased methane content from 64.0% to 98.1% and reduced impurities like CO₂, H₂S, CO, and water vapor. Treated biogas demonstrated a 35% faster heating time compared to raw biogas and outperformed kerosene, showcasing its potential as a more efficient and cleaner-burning fuel source. The results highlight the benefits of biogas treatment, making it a viable alternative energy source for cooking, heating, and other applications. This research contributes to the development of sustainable energy solutions, emphasizing the importance of biogas treatment for improved energy efficiency and reduced environmental impact.

Residue Theorem and Contour Integration: A Python-Based Approach to Real Integrals

Nura Buwai — 2025-10-25

Contour integration and the Residue Theorem provide powerful techniques for evaluating real integrals that are otherwise difficult to compute by elementary methods. These tools, rooted in complex analysis, have long been applied to problems in physics, engineering, and applied mathematics. This paper presents a Python-assisted approach to contour integration, blending classical analytical methods with symbolic computation and numerical verification. Specifically, we employ the SymPy library for residue evaluation and symbolic manipulation, and the mpmath library for high-precision numerical integration. Representative examples include the Lorentzian integral the Dirichlet integral , and the rational integral . In addition to reproducing these classical results, we also visualize canonical contours such as semicircular paths in the complex plane and demonstrate parameterized numerical contour integrals to illustrate the role of residues and Jordan’s lemma. Results confirm the accuracy of classical theory and highlight the value of computational tools in reducing algebraic errors, enhancing reproducibility, and providing visual intuition. This synergy between theory and computation enriches the teaching of complex analysis and opens avenues for extending contour integration methods to more advanced applications.

Dynamical Behaviour of Wall Concentration and Superhydrophobicity Effects on a Combined Reactive Flow in a Slit Microchannel

Emmanuel Omokhuale — 2025-10-25

This work shows how Arrhenius-controlled heat and mass transfer flow influenced by uniform wall concentration over a superhydrophobic microchannel is affected by mixed convection with a constant pressure gradient. While the other parallel plate has a no-slip surface (NSS), one of the plates is purposefully altered to have a superhydrophobic surface (SHS). A semi-analytical approach is used for the nonlinear ordinary differential equations. A graphic illustration of the behaviors of the main parameters governing the flow behavior in terms of mass diffusion, temperature, and velocity trends is provided. It was observed that the presence of mixed convection parameter boosts the fluid velocity. Additionally, the symmetric wall concentration effect significantly affects the development of flow reversal. Finally, these findings will find applications in manufacturing processes like hot rolling, drawing of wire, continuous casting, production of glass fiber, and fabrication of paper, cracking in petrochemical engineering, chemical synthesis, anti-wetting micro-technology, etc.

Development of K-Neareast Neighbor Based Model for Network Intrusion Detection Using Random Forest for Feature Selection

Ogah Muhammad Usman — 2025-10-25

Networked monitoring has emerged as one of the primary security technological advances, and network security challenges have gained increasing attention due to the extensive usage of the web. As a result, conventional signature-based and anomaly-centered intrusion detection systems are not effective enough. The efficacy and preciseness of network security measures are significantly impacted by the beginning information source's substantial dimension and volume of content. An inventive method for choosing the key attributes and reducing the overall length of information was the random forest-based feature selection, which simultaneously increased the Ture Positive Rate and decreased the False Positive Rate. Consequently, the classifier and selection of features both contribute significantly to improving network monitoring performance. On the simulated dataset, the suggested K-nearest neighbor and Random Forest perform admirably and successfully ensure the kNN classifier's progress. Simulations and experiments were conducted using the R programming language, and the results indicate that the model we developed reaches 99% accuracy. The experimental findings demonstrate the effectiveness

A Deep Learning Approach to Smishing Detection in Mobile Apps Using Convolutional Neural Network and Long ShortTerm Memory

Ogah Muhammad Usman — 2025-10-25

Smishing, or SMS phishing, poses a significant cybersecurity threat to smartphone users. These attacks exploit the brevity and symbolic nature of SMS messages, making detection challenging. Existing methods, such as DSmishSMS, employ traditional machine learning techniques but require further enhancement. To address this rising and concerning issue, this thesis offers a model for an improved detection. The experiment demonstrate that the developed CNN model outperformed traditional algorithms, achieving an accuracy of 98.97% which is better than the 97.93% from the benchmark paper. By integrating deep learning techniques, this contributes to safeguarding users from fraudulent smishing attack.

Assessment and Comparison of Cardiometabolic Diseases Risk Factors in Urban and Rural Communities of Kebbi State

Muhammad Jelani — 2025-10-25

Cardiometabolic diseases, including cardiovascular disease, obesity, and type 2 diabetes, are major public health problems related to significant morbidity and mortality worldwide. Despite the growing burden of these diseases, there is a lack of comprehensive data on cardiometabolic risk factors in both rural and urban areas of Kebbi State. This study aims to assess and compare the prevalence of cardiometabolic risk factors, including hypertension, obesity, and diabetes, in rural and urban communities of Kebbi State. The study is a cross-sectional study that involved field data collection from selected rural and urban communities, including the administration of structured questionnaires, clinical measurements, and biochemical testing to evaluate key cardiometabolic markers. Blood pressure was measured using a digital sphygmomanometer, and body mass index (BMI) was calculated from weight and height measurements. Fasting blood samples were collected for the analysis of glucose levels. The study found that urban residents had a higher prevalence of cardiometabolic risk factors compared to rural communities (p<0.0001). Hypertension and diabetes were found to be more prevalent in urban areas compared to rural communities (p = 0.010 and p < 0.0001, respectively). Although urban residents had higher mean weight and height, BMI did not differ significantly (p>0.05). Urban residents are more aware (68.5%) and are more likely to believe that lifestyle changes can reduce risks, suggesting the need for better health education in urban areas. There are significant urban-rural disparities in cardiometabolic health, with urban residents experiencing a higher prevalence of hypertension and diabetes, even though urban residents have more knowledge about these risk factors. There is a need for improved health education, especially in rural communities.

Serum Inflammatory Markers [(Interleukin (Il)-6, Il-8, And Il-10)] Relative to Group B Streptococcus Colonisation in Women At Delivery

J Muhammad — 2025-10-25

Newborns with Group B Streptococcus (GBS) infections have a significant rate of morbidity and mortality. One of the main risk factors for newborn GBS illness is maternal GBS colonisation during pregnancy. Previous investigations reported that inflammatory indicators produced by immune cells as a result of bacterial infection could also aid in identifying bacterial infections, in addition to other conventional methods. Thus, the study examined the potential utility of maternal serum interleukin (IL)-6, -8, and -10 as markers for predicting GBS colonisation at birth. The study included 136 HIV negative pregnant women who were not taking any antibiotics and had no other medical conditions. At the time of delivery, venous blood and vaginal swabs were taken. Using the culture approach, GBS was isolated from swabs. If a mother's culture was positive, she was considered GBS colonised. Maternal serum was used to analyse inflammatory markers (cytokines) using the R&D pre-mixed magnetic Luminex assay. A logarithmic transformation was used to normalise the cytokine values. Forty-seven (47) of the 136 participants had GBS colonisation. The logged concentrations of IL-6 (P=0.8), IL-8 (P=0.5) or IL-10 (P=0.9) did not differ significantly upon delivery according to colonisation status. According to our findings, maternal serum levels of IL-6, IL-8, and IL-10 are not accurate indicators of GBS colonisation at delivery.

Strategy for Improving the Effectiveness of Appointment System in Yariman Bakura Specialist Hospital Gusau, Zamfara State

Iliyasu Liman — 2025-10-25

Appointment system is a method use for effective clinic preparation in such a way that, every patient is giving a specific date and time in order to see their attending physicians. Appointment system encounter with a number of challenges such as queuing system causing a long waiting time as an inefficiency of healthcare delivery system. The study therefore investigated the Effectiveness of Appointment System (EAS) in Yariman Bakura Specialist Hospital Gusau, Zamfara State. Survey research design was adopted for the study. The population of this study was Health Information Management Personnel. A total enumeration was use for the study. A structured and validated checklist was used for data collection. Data were analyzed using descriptive and inferential statistics at 5% level of significance. Findings showed that effectiveness of the appointment system in Yariman Bakura Specialist are rated positive, but equipment used are to be considered for future improvement of appointment system at the hospital. The study concluded that human efforts and procedural efficiencies are rated positively, but equipment use, remain significantly weak and negative. The study recommends that, there is need for management and government to provide the hospital with adequate materials use for effective appointment system.

Investigation on the Consequences of Missing Case Folder in General Hospital Gusau, Zamfara State

Iliyasu Liman — 2025-10-25

Missing case folders refers to as a loss, misplacement, or unavailability of physical or digital files containing patient medical information which consist of patients’ medical history, clinical investigation and final diagnosis for continuity of patient care. Missing patient case folder resulted to improper patient management, therefore patient case folder is the case indicator measuring the level of service provided to the patient. Survey research design was used for this study. The target population of this study was Health Information Managers. The instrument for data collection in this study area is check list tool. The result shows that Human Factor scale returned the highest reliability value among the individual determinants, with a Cronbach’s Alpha of 0.81, denoting excellent internal consistency. The items within this section skill level, staff commitment, patient-staff relationships, and service delivery are closely related, indicating that respondents' perceptions of human contributions to the problem are measured consistently and reliably. The Natural Disaster Factors scale had a slightly lower reliability coefficient of 0.69, which is still within the acceptable range. This set of items assessed backup systems, space, shelves, and security measures in the context of natural events, and although less consistent than other determinants, it remains statistically acceptable for inclusion in the analysis. In conclusion missing patient case folder reduce healthcare quality and safety to the patient. Work experience plays a critical role in shaping staff awareness and concern regarding operational inefficiencies and infrastructural gaps that may lead to missing patient case folders. The study recommends that, there is need for management, government to providing necessary training to enhance service delivery mechanisms of Health Information Management Personnel. Good filling method should be provided to minimise missing patient case folders. Filling space should be provided to enhance the services.

Phytochemical, Antibacterial and Characterization of 9-methoxy-12-phenyl-dodec-10-enoic acid-3,4,5-trihydroxy-6-methyl-tetrahydropyran-2-ylester Isolated from Acacia macrostachya leaves

Garba Umar — 2025-10-25

Acacia macrostachya is plant usually a tree belong to family Mimosaceae (Fabaceae), it is popularly known as “Gardaye” in Hausa Language (Sokoto). A. macrostachya is one of such useful plants in African traditional medicine. It is used to treat numerous diseases such as malaria with convulsion, diarrhea, inflammatory diseases, snake bite, anti-diabetic, and cancer among others. The aim of this research is conduct phytochemical screening; antibacterial studies of Acacia macrostachya leaves and characterizes the isolated compound from A macrostachya leaves. The plant were collected from “Lungu” bush in Shagari local government area 12°38′N 5°0′E and authenticated at herbarium Department of Pharmacognosy and Ethnopharmacy Faculty of Pharmaceutical Sciences, Usmanu Danfodiyo University, Sokoto, Nigeria with Voucher number PCG/UDUS/Faba/0016. One kilogram of the powdered plant materials was methanol which gave the extract yields of 131.72g (13.17%). The phytochemical screening reveals the presence of alkaloids, steroids, flavonoids, cardiac glycosides, tannins, saponins, carbohydrate and phenolics. Antibacterial effects on the extracts at various concentration (200 mg/cm³, 100 mg/cm³, 50 mg/cm³ and 25 mg/cm³, against S. Typhi, S. dysenterae, E. coli, P. aeruginosa were studied. The extract was then subjected to column chromatography which leads to the isolation of compound UGP₂. The isolated compound was characterized using FTIR, and Nmr. The study showed that A. macrostachya leaves have medicinal potential which could help in the treatment of bacterial infections that affect human and animal respectively.

Comparative Antimicrobial Evaluation of Acacia macrostachya Fractions against Selected Pathogens

Hadiza Adamu Kwazo — 2025-10-25

The rising resistance of microorganisms to current antibiotics has intensified the need for new antimicrobial agents, predominantly from natural sources. Acacia macrostachya, a medicinal plant widely used in African traditional medicine, has been used to treat various ailments such as diarrhea, malaria with convulsions, snake bites, dysentery, inflammatory conditions, stomach cramps, uterine fibroids, and parasitic infections. This study aimed to comparatively evaluate the antimicrobial activity of Acacia macrostachya fractions against selected pathogens with the objective of identifying the most potent fraction and validating the plant's traditional use. The N-hexane, ethyl acetate, and methanol extracts from the leaves of Acacia macrostachya were subjected to antimicrobial screening against Salmonella typhi, Shigella dysenteriae, Escherichia coli, Pseudomonas aeruginosa, Candida albicans, Aspergillus niger, Aspergillus fumigatus, and Trichophyton rubrum using agar well diffusion and broth dilution methods. Susceptibility test results showed that most fractions demonstrated notable antimicrobial activity, except for the N-hexane and ethyl acetate fractions at the lowest concentration (25 mg/mL) against Shigella dysenteriae, Escherichia coli, and Pseudomonas aeruginosa. The Minimum Inhibitory Concentration (MIC) for the ethyl acetate and methanol fractions ranged from 11–20 mg/mL and 17–27 mg/mL, respectively, against bacterial pathogens, and from 6–19 mg/mL against fungal pathogens. The Minimum Bactericidal/Fungicidal Concentration (MBC/MFC) of the N-hexane, ethyl acetate, and methanol fractions was found to be 0.2 mg/mL, and 0.1 mg/mL, respectively. These results suggest that the methanol fraction possessed the most significant antimicrobial activity among the fractions tested against the pathogens.

Evaluation Of Pesticides Practices and In Silico Toxicity Profilling Of Pesticides Used In Tsafe Zamfara State, Nigeria

Idris Sherifat Banke — 2025-10-25

some of the major difficulties such as time and cost in evaluating pesticides through traditional techniques (in vitro and In vivo). This study aims to identify the type of pesticides being used and to access attitudes towards pesticide use and safe handling and analyze using computational methods the toxicity and pharmacokinetic properties of commonly used pesticides in Tsafe. Data was gathered through interview of 206 respondents. Chemical library of chemicals from Tsafe was created and then screened using for ADMET, drug likeness and toxicity prediction was done using insilico methods (SwissADME). Using PyRx and PyMol, molecular docking was performed on the predicted target proteins acetylcholinesterase and MAP kinase for two of the pesticides in Tsafe. The results indicated that the pesticides used in Tsafe were chlorpyrifos, cypermethrin, deltamethrin, dichlorvos, paraquat, and glyphosate. According to the prediction analysis's results, all selected pesticides exhibited good human intestinal absorption. Dichlorvos and paraquat were able to cross the blood-brain barrier, and all of the pesticides were found to be highly toxic. The docking studies indicate that chlorpyrifos has a lower binding energy to acetylcholinesterase compared to donepezil, a strong cholinesterase inhibitor drug. Cypermethrin exhibits a higher binding energy for MAP kinase compared to methotrexate, a well-established anticancer agent. Six highly toxic pesticides were identified, with some capable of crossing the blood-brain barrier. Docking analysis showed strong protein interactions, indicating potential health risks.

Two–State Stochastic Model with Application to the Nigeria’s Labour Market

Lubem Matthew Kwaghkor — 2025-10-25

This research seeks to address the critical issue of unemployment in Nigeria by developing a two-state stochastic model to analyse transitions between employment and unemployment states in the labour market. Traditional models, such as ARIMA, rely heavily on historical data and are limited to short-term predictions. To overcome these limitations, a Modified Exponential Distribution (MED) is introduced in this work that can model long-term transition probabilities, contrasting it with the conventional exponential distribution (ED). The model is applied to Nigeria's labour market, segmented into public and private sectors, with the private sector further divided into formal and informal sectors. Key findings reveal that the MED is more suitable for long-term analysis, showing gradual transitions, while the ED predicts rapid changes, ideal for short-term forecasts. Regional analysis highlights disparities across Nigeria's geopolitical zones, with the South-East and South-South exhibiting the highest unemployment and employment probabilities, indicating dynamic but unstable labour markets. The private sector dominates employment absorption, offering an 82% probability by year 10, compared to 18% in the public sector. Similarly, the informal sector provides immediate employment but plateaus early, while the formal sector shows steady growth, suggesting long-term stability. The study underscores the need for targeted policies to address regional imbalances and promote formal sector growth. It recommends prioritizing private sector opportunities for job seekers while advocating for structural reforms to enhance formal employment. By providing a robust framework for long-term labour market analysis, this research contributes to informed policy-making and economic planning in Nigeria.