Journal of Basics and Applied Sciences Research

Integrated mechanical and chemical control of wild rice (Oryza Longistaminata) and its impact on rice yield in upper east region, Ghana

2026-09-29T10:31:32+00:00

Wild rice (Oryza longistaminata) is a pervasive weed in rice fields in the Upper East Region, significantly reducing rice yields and threatening food security. The study aimed to evaluate the efficacy of integrated mechanical and chemical control methods in Garu and Tempane Districts. The experiment was laid out in a split-plot design with three replications. The districts were assigned to the main plots and the weed control methods to the subplots. Land preparation was done manually, and Glyphosate was applied one week after, at a rate of 100 ml per 15 litres of water. One week later, Jasmine rice was planted. Data were collected on the wild rice population and rice yield parameters. The data were analyzed using GenStat 12 Edition; a two-way ANOVA was used to determine treatment differences. Means were separated using Lsd at a 5% level of significance. Results showed that glyphosate-based treatments effectively suppressed weeds. Plough + Glyphosate achieved the highest grain yields of 3.87 t/ha in Garu and 3.53 t/ha in Tempane. The weed control method was significant (p < 0.001) and reduced wild rice population by 2.7-fold. Uncontrolled wild rice infestation reduced rice yields by approximately 56%. Combined Plough + Glyphosate application is recommended for managing O. longistaminata, with Glyphosate application only where resources are limited. Awareness of the weed's rhizomatous regeneration capacity is essential for farmers to understand the control methods. Further research should examine the cost-benefit analysis of the control methods and socio-economic factors that could influence adoption.

Water scarcity mitigation strategies and implementation challenges among the populace of Batagarawa Local Government Area of Katsina State, Nigeria

2026-09-29T10:42:37+00:00

Scarcity of water poses serious risk to the health and livelihoods of people living in the arid and semi-arid parts of northern Nigeria. This is due to mostly climate change, poor water infrastructure, improper water management and growing populations that keep putting pressure on the limited sources of water in the areas. The objective of this study was to assess the strategies adopted in solving the problem of water scarcity in Batagarawa LGA, Katsina State, as well as to assess challenges associated with the adoption of the strategies. In this study, qualitative research methodology was utilized in the data collection process where Focus Group Discussion (FGD) and direct observation were mainly adopted. The primary data were collected using FGD and direct observation on the field to ensure a more holistic data collection. The secondary data were collected from Katsina State Water Board and from NGOs working among the people of Batagarawa. The data collected was analyzed through the use of thematic analysis technique. According to results from the interviews conducted, it emerged that borehole water is the main source of water supply to the people. Access to water differs based on whether an individual's home possesses a borehole, the proximity of one’s home to a communal borehole, and availability of pipe-borne water which in some cases may be hindered by shortage of power. People adopt personal measures in handling the situation such as water conservation and reusing water; however, financial difficulties and lengthy distances make it hard for such measures to be sustained effectively. The study conclude that households make use of several localized measures aimed at coping with water problems, including water storage, rainwater collection, and reuse of water. It was recommended that the governments should support households with financial or technical help in obtaining their own boreholes and installation of water storage systems.

Production and characterization of biodegradable plastics from water Yam peel starch and rubber seed oil

2026-09-29T10:59:40+00:00

Packaging waste forms a significant part of municipal solid waste and has caused increasing environmental concern. This research investigates the potential of producing bioplastics using the starch from water yam peels and epoxidized rubber seed oil. The starch and epoxidized rubber seed oil with additives were copolymerized to form the bioplastic. Analysis of the starch were: moisture content (10.08±0.42%), ash content (0.175±0.010%). amylase (26.93±0.01%) and amylopectin (73.07±0.10%). Physicochemical analysis of the epoxidized rubber seed oil were pH (6.50±0.01), specific gravity (0.97±0.24), viscosity (12.30±0.20 poise) acid value (22.62±0.01 mgKOH/g) and iodine value (158.51±0.03 mg𝐼₂/g). The bioplastic was subsequently produced by copolymerization of the epoxidized rubber seed oil and water yam peels starch. The tensile strengths of both bioplastic and the control were 20.54N/mm² and 12.28N/mm² respectively. Also, the results showed that the bioplastic had a poor resistance in acidic and water media, good resistance in basic, and alcoholic media. The biodegradability test results showed that weight loss was more evident in loamy soil whereas no change was observed for the control.

Partial shading mitigation on DC link stability based on deep reinforcement learning grid-forming inverter control

2026-09-29T11:17:28+00:00

Partial shading on photovoltaic (PV) arrays induces nonlinear power–voltage characteristics that cause rapid, multi-peaked fluctuations in DC-link power injection. Conventional grid-forming (GFM) inverter controllers, which rely on fixed-gain PI regulators tuned around a nominal operating point, struggle to track these fast, nonlinear disturbances: their linear control action cannot adapt quickly enough to abrupt irradiance changes, leading to sluggish transient response and, under severe shading, DC-link voltage collapse. This paper proposes a hybrid deep reinforcement learning (DRL) based GFM inverter control strategy that replaces these fixed-gain regulators with adaptive, learning-based controllers to overcome this limitation. A Deep Deterministic Policy Gradient (DDPG) agent governs the DC–DC boost converter for maximum power point tracking (MPPT), while a Twin Delayed Deep Deterministic Policy Gradient (TD3) agent replaces the conventional inner current PI regulators of the droop-controlled GFM inverter, enabling the controller to continuously learn and adjust its response to nonlinear, time-varying shading conditions rather than relying on static gains. Performance is evaluated under four irradiance scenarios, from uniform irradiation to severe partial shading, and compared against a conventional PI–PI GFM controller. Results show that the proposed GFM (PI–TD3) controller achieves faster DC-link voltage stabilization and superior voltage regulation under all shading conditions, maintaining the DC-link at 779.1 V under severe shading compared to a collapse to 290 V with the conventional controller. These findings indicate that TD3-based DRL GFM inverter control offers a robust, adaptive solution for standalone PV systems under variable irradiance conditions.

Predicting academic performance: a comparative study of UTME and Direct entry students using a hybrid Kernel model

2026-09-29T11:27:54+00:00

This Study introduces a novel Hybrid kernel Model (HKM) that integrates weighted and unweighted kernel regression within a unified framework to predict and compared the academic performance of students admitted through two unified pathways-Unified tertiary Matriculation Examination (UTME) and Direct Entry (DE) at Sokoto State University. While prior research has employed single kernel model and machine learning techniques in educational data mining, these studies often overlook admission mode differences and integrated kernel approaches, limiting their predictive accuracy and generalizability. Using a dataset spanning 2018-2025, partitioned into training (2018-2023) and testing (2024-2025) sets, the HKM was evaluated using MSE, RMSE, MAE and . Results consistently show DE student outperforming UTME students across graduation metrics, including higher class: first class and second-class upper percentages, and lower-class rate: second lower and third-class percentage. Performance score on a 4-point scale ranged from 3.09-3.28 for DE versus 2.65-2.90 for UTME. Statistical tests confirmed admission mode as a significant predictor (P < 0,05), with prediction confidence exceeding 84% for both groups. This study fills a critical gap by disaggregating student populations and offering pathway-specific insights, challenging homogeneous treatment in existing literature. Its contributions include a replicable methodological framework and actionable recommendations for differentiated admission orientation, and support systems. The HKM proves analytics in education, supporting equitable policy and institutional quality enhancement.

Metal-coordinated Aldazine Schiff Base: synthesis, spectroscopic characterisation, and evaluation of antimicrobial and antioxidant potentials of CU (II), ZN (II) and AG(I) complexes

2026-09-29T11:48:20+00:00

Antimicrobial resistance poses a growing threat to global health as multidrug-resistant pathogens render many conventional drugs ineffective. This has created an urgent need for alternative therapeutic approaches. In response, an aldazine Schiff base and Cu(II), Zn(II) and Ag(I) complexes were synthesised, spectroscopically characterised and evaluated for antimicrobial and antioxidant potentials. The ligand, 3EHH, was prepared from hydrazine and 3-ethoxy-2-hydroxybenzaldehyde. The Cu(II) (Cu3E), Zn(II) (Zn3E), and Ag(I) (Ag₂3E) complexes were synthesised and characterised by magnetic moments, NMR, IR and UV/Vis spectra. The in vitro antimicrobial and antioxidant properties were investigated using agar well diffusion, DPPH radical scavenging and ferric reducing antioxidant power (FRAP) assays, respectively. Formation of 3EHH was confirmed by the bis-azomethine protons signal at 8.69 δ ppm and the absence of amino and carbonyl protons. Coordination via azine nitrogen and phenolate oxygen was supported by shifts in v(C=N) from 1622 to 1631–1616 cm^–1 and v(C–O) from 1214 to 1210–1193 cm^–1, loss of phenolic protons in Zn3E NMR spectrum, and changes in π→π* transitions, together with new LMCT (423–405 nm) and d→d bands (662 nm) in the UV-Visible spectra. The inhibition zones and MIC were in the ranges of 8–24 mm and 10–0.125 mg/mL, respectively. The DPPH and FRAP antioxidant assays showed IC₅₀ 138.62–486.82 µg/mL and 9.240–22.890 AAE mg/g at 1000 µg/mL, respectively. Chelation of 3EHH with Cu (II), Zn(II), and Ag(I) improved its bioactivity, with the Cu (II) complex showing the greatest potential as a dual antimicrobial and antioxidant agent.

Modeling and forecasting monthly Hepatitis B virus infections in Benue State using prophet time series model

2026-09-29T11:54:27+00:00

Hepatitis B Virus (HBV) infection remains a major public health challenge in Nigeria, particularly in Benue State, where endemic transmission persists despite ongoing prevention programmes. This retrospective time-series study aimed to model historical trends and forecast monthly HBV infections in Benue State using the Prophet forecasting time series model while evaluating the effects of selected public health interventions. Secondary surveillance data comprising 192 monthly laboratory-confirmed HBV records collected between January 2010 and December 2025 were obtained from the Benue State Epidemiological Unit, Makurdi. Rainy season, vaccination weeks, and public health awareness campaigns were incorporated as intervention variables because they represent environmental conditions and routine control measures expected to influence HBV transmission and case detection. Descriptive statistics, the Anderson-Darling normality test, Prophet decomposition, model diagnostics, and forecast evaluation were performed. The series had a mean monthly value of 61,544 confirmed cases, with significant non-normality (A² = 2.994; p < 0.005). The fitted Prophet model identified a significant upward trend (k = 2.8553, p < 0.001), significant seasonal patterns, increased infections during the rainy season (β = 8.5085, p = 0.0001), and significant reductions during vaccination weeks (β = −3.2244, p = 0.0077) and awareness campaigns (β = −1.1253, p = 0.0060). Model performance was satisfactory (R² = 0.8716; RMSE = 3.6625; MAPE = 6.35%), with diagnostic tests confirming model adequacy. Forecasts for January 2026-December 2027 indicated persistent endemic transmission with seasonal peaks during June-August, accompanied by 95% prediction intervals quantifying forecast uncertainty. The findings demonstrate that the Prophet model provides a reliable framework for HBV surveillance, early warning, and evidence-based public health planning in Benue State.

Calibration technique for compensation of non-response in domains of study with probability proportional to size

2026-09-29T12:00:20+00:00

In sample survey, it is expected that the information would be collected from all the selected units in the sample, but practically, it is generally not possible because of non-response. Some of the units may not respond or may not be contacted during the survey period. This work focuses on domain estimation of population mean with sub-sampling the non-respondents using probability proportional to size. In this study, we consider calibration technique as a method of correcting non-response in domains of study by minimizing the chi-square distance function between the weight of the main estimator and the calibrated weight subject to the formulated constraint on the auxiliary variable. The bias and mean square error (MSE) for the proposed estimators are derived. The use an auxiliary variable to estimate the population mean assuming that the non-response is observed only on the study variable is adopted. The proposed estimator and the existing estimators were compared empirically in the domains with small sampling units and two populations were considered in terms of the MSE and Percentage Relative Efficiency (PRE). Also, two cases were considered, where non-responses are uniform in the two strata at approximately (30%) and a case where the nonresponse rates are different with 20% and 40% in strata 1 and 2 respectively. The proposed estimator gained more efficiency than the existing estimators. However, the proposed estimator performed better in case II than in case I in some domains but the aggregate result suggests otherwise in both populations.

A multiset-theoretic framework for inventory optimization in Motor garage systems

2026-09-29T12:07:34+00:00

Inventory system in motor garages involve repeated spare parts such as spark plugs, filters, and bolts, where multiplicity is essential for accurate representation. Classical set-theoretic model fails to capture repeated elements structurally, requiring external quantity variables. This paper develops a multiset-theoretic framework for motor garage inventory modelling, representing inventory as multiplicity functions over a finite universe of items. Algebraic operations, such as addition, difference, union, and intersection are formalized. Structural properties such as closure, commutativity, and stability are established. A dynamic inventory update model and demand-balancing optimization are proposed. Computational analysis demonstrates linear scalability. The framework provides a robust, computationally efficient method for small- and medium- scale inventory management.

Assessment of bacterial contamination of wells and boreholes in selected students’ hostels in Nnamdi Azikiwe University, Awka Anambra State, Nigeria

2026-09-29T12:16:36+00:00

Access to safe drinking water is crucial for public health, yet many students rely on potentially contaminated wells and boreholes. which can lead to serious health issues. Understanding bacterial contamination levels is essential for effective interventions, ensuring students well-being. This study assesses the bacterial contamination of water in wells and boreholes at selected students hostels in Nnamdi Azikiwe University Awka, focusing on total microbial load, total coliform counts, and the prevalence of specific bacterial species. A total of sixteen water samples were analyzed, revealing microbial load counts ranging from 1.7x10² CFU/ml to 2.78x10³ CFU/ml in well water and 2.0x10² CFU/ml to 1.87x10³CFU/ml in borehole water. Mean microbial loads were notable higher in well water (890±317.478 CFU/ml) than in borehole water (525±197.935 CFU/ml), but no significant difference existed between the two sources (F=0.9518, P=0.3458). Both sources remained below the WHO safe limit for recreational water (2300 CFU/ml). Total coliform counts were within safety limit for borehole water (1.25±1.25 CFU/ml) but exceeded WHO safe limits of 126 CFU/ml for well water, with means of 318.75±223.178 CFU/ml. Biochemical identification revealed five bacterial species: Escherichia coli, Enterobacter aerogenes, Klebsiella pneumoniae, Citrobacter freundii, and Proteus mirabilis. Klebsiella pneumoniae was the most prevalent, found in 25% of samples, while Enterobacter aerogenes was least, detected in only 6.25% of samples. This study highlights the significant public health risks associated with bacterial contamination in university water sources, and underscores the need for regular monitoring and management efforts to ensure water quality and public health safety for hostel residents.

Comparative analysis of some physicochemical and biological parameters of well and borehole water samples obtained in Dustin-Ma Town, Katsina State, Nigeria

2026-09-29T12:22:14+00:00

ABSTRACT

Water quality continues to pose a major challenge in many urban areas particularly in the developing countries, in which Dutsin-Ma town of Katsina State is not an exception. The aim of this study was to compare the physicochemical and biological characteristics of water obtained from three wells and three boreholes located in six different areas of Dutsin-Ma Local Government Area, Katsina State, Nigeria. The analysis was carried out using standard procedure recommended by the American Public Health Association (APHA). The physicochemical parameters analysed include the pH, electrical conductivity (EC), turbidity, total dissolved solids (TDS), Total suspended solids (TSS), total solids (TS), dissolved oxygen (DO), and temperature. Bacteriological examination of the water samples was assessed using the membrane filtration technique. Findings revealed that borehole water generally had better quality than well water, with most physicochemical parameters such as pH (6.90–7.40) and electrical conductivity (300–550 µS/cm) found to be within the permissible limits set by the WHO. In contrast, well water recorded higher turbidity levels (5.2–6.8 NTU) and significant microbial contamination, with E. coli counts reaching up to 18 CFU/100 mL, exceeding recommended standards. The Water Quality Index rated borehole water from “good” to “poor,” whereas well water ranged from “poor” to “unsuitable” for consumption. Overall, borehole water was found to be relatively safer for domestic use, although treatment is still necessary for both water sources before consumption.

Implementing a community-based health education and mobile screening intervention to improve accessibility and uptake of breast and cervical cancer screening programs in Ebonyi State, Nigeria

2026-09-29T12:35:19+00:00

Breast and cervical cancers continue to be major causes of cancer morbidity and mortality among women in developing nations such as Nigeria. Inadequate knowledge about screening, lack of access to screening programs, sociocultural impediments, and poor health system performance are some factors that lead to low participation rates especially in remote areas. This study evaluated community-based education and mobile screening interventions to improve breast and cervical cancer screening access among Ebonyi women. A quasi-experimental design of community-based studies with pre-test and post-test measurements was employed among women aged 21-65 years within selected communities in Ebonyi State. The health education and mobile screening services involved culturally sensitive educational talks, and clinical breast examination and visual inspection with acetic acid (VIA) test for cervical cancer screening, respectively. Statistical analysis was done using descriptive and inferential statistics with a significant level of p < 0.05. Awareness and utilization of breast and cervical cancer screening services were low at baseline. Awareness about breast and cervical cancer screening, as well as the perceived benefits of screening, was significantly enhanced post-intervention. Utilization of screening services increased greatly among those screened for breast cancer (from 18.0% to 61.0%) and those who underwent screening for cervical cancer (from 14.5% to 55.5%) (p < 0.001). Most respondents indicated that screening services became more accessible to them after the intervention. A community health education campaign coupled with mobile screening services has proven highly effective in improving access to, and utilization of, breast and cervical cancer screening services in Ebonyi State.

Synthesis, characterization and antimicrobial studies of Schiff base derived from 2-Hydroxy Acetophenone and P-Anisidine and its metal (II) complexes

2026-09-29T12:40:07+00:00

Microbial infections remain a major global health challenge due to the rapid emergence and spread of antimicrobial-resistant pathogens. The misuse and overuse of conventional antimicrobial agents have accelerated multidrug resistance, highlighting the need for new therapeutic candidates with improved biological activity. In this study, Mn(II), Co(II), and Ni(II) complexes of a Schiff base derived from p-anisidine and 2-hydroxyacetophenone were synthesized, characterized, and evaluated for antimicrobial activity. The ligand and its complexes were obtained in good yields and characterized using physicochemical and spectroscopic techniques. The ligand exhibited a melting point of 197°C, while the complexes decomposed at 242–263°C, indicating enhanced thermal stability upon complexation. Molar conductivity values (6.23 – 31.40 Ω^-1cm²mol^-1) confirmed their non-electrolytic nature. Magnetic susceptibility measurements and effective magnetic moments of 5.5, 4.3, and 3.2 BM for the Mn(II), Co(II), and Ni(II) complexes, respectively, suggested tetrahedral geometry and paramagnetic behavior. Electronic spectra showed characteristic π→π* (230 – 265 nm) and n→π* (305 – 335 nm) transitions, while FTIR spectra revealed a shift of the azomethine C=N band from 1607 cm^-1 to 1585 – 1592 cm^-1 and disappearance of the phenolic O–H band at 3387 cm^-1, confirming coordination through azomethine nitrogen and phenolic oxygen atoms. Job’s method established a 1:2 metal-to-ligand ratio. The ligand and complexes exhibited concentration-dependent antimicrobial activity against Staphylococcus aureus, Escherichia coli, Salmonella typhi, Candida albicans, Tinea capitis, and Aspergillus flavus. The complexes showed enhanced activity relative to the free ligand but remained less active than the standard drugs amoxicillin and griseofulvin.

Invitro anticancer effect of D. Mespiliformis stem back chloroform extract against breast cancer cell lines MCF-7

2026-09-29T12:45:15+00:00

Breast cancer is among the most prevalent cancers in Nigeria constituting aipproximately 27% of all new cases and representing a significant and growing public health concern. The impact of cancers continues to grow due to several factors, leading to an estimated mortality of up to 10 million annually. Medicinal plants have been utilized widely for treatment of diseases including cancer. This study evaluated the phytochemical analysis and cytotoxic effects of D. mespiliformis stem bark extract against human breast adenocarcinoma cells (MCF7). The extract was prepared using D. mespiliformis stem bark and chloroform as a solvent. The phytochemical constituents were identified using qualitative method. The anticancer effect was determined using cell titre Glo pro mega assay while total intracellular glutathione (GSH) was measured to assess whether redox imbalance contributed to the observed cytotoxic response. The phytochemical screening of the extract reveals the presence of important compounds. At 48 hours, the extract exhibited a strong cytotoxic effect (IC₅₀ of 21.75 µg/mL) against MCF-7 cells while sparing MCF-10. Mechanistic assessment showed that the extract reduced intracellular GSH levels in MCF-7 cells, indicating that glutathione depletion and oxidative stress may be involved in the cytotoxic effect. The cytotoxicity of the extract might be attributed to the presence of important secondary metabolites. The findings from the present study highlights the chemopreventive potential of D. mespiliformis stem chloroform extract against MCF-7 breast Cancer cell. Further studies are required to isolate the active constituents, confirm the molecular mechanism and evaluate safety in broader experimental models.

An enhanced convolutional neural network model for brain tumor classification using transfer learning and data augmentation

2026-09-29T13:09:15+00:00

Brain tumors constitute a significant global health challenge, and accurate, timely diagnosis is critical for effective treatment planning. Manual interpretation of magnetic resonance imaging (MRI) remains time-consuming, error-prone and subject to inter-observer variability. The objective of this study was to develop and evaluate a fine-tuned VGG16 convolutional neural network (CNN), combined with a dual online and offline data augmentation pipeline, for the three-class classification of brain tumors from T1 contrast-enhanced MRI under resource-constrained computing conditions. The study used 3,064 T1 contrast-enhanced MRI slices spanning three tumor classes, namely glioma (1,426 slices), meningioma (708 slices) and pituitary tumor (930 slices), drawn from the publicly available Masoud Nickparvar Brain Tumor MRI Dataset on Kaggle. Images were normalised using min-max scaling, denoised using a Gaussian filter and resized to 224 x 224 pixels. The cohort was partitioned by stratified sampling into 2,145 training (70%), 273 validation (9%) and 646 test (21%) images. Six architectures were benchmarked, comprising a custom CNN, VGG16, VGG19, Xception, ResNet50 and DenseNet121. The best-performing backbone was then enhanced through layer freezing and fine-tuning, and finally through augmentation using random horizontal flipping applied online and histogram equalisation applied offline. The novelty of the study lies not in a new network topology but in the empirical demonstration that a selectively fine-tuned VGG16 backbone, coupled with a reproducible dual augmentation protocol, attains competitive diagnostic performance on central processing unit hardware alone. On the held-out test set, the fine-tuned VGG16 with augmentation achieved an accuracy of 98.45%, a macro-averaged sensitivity of 98.26%, a macro-averaged specificity of 99.19% and a macro-averaged precision of 98.37%. Class-wise areas under the receiver operating characteristic curve were 0.998, 0.996 and 0.999 for glioma, meningioma and pituitary tumor respectively. The custom CNN attained 95.40% accuracy and DenseNet121 attained 93.18%. These findings indicate that transfer learning based CNN models with strategic augmentation can reach diagnostically useful performance without specialised graphics hardware, offering a practical decision-support aid for radiological workflows in low-resource settings. External validation on independent clinical cohorts is required before deployment.

On common fixed point for finite family on maps in a relational metric space

2026-09-29T13:36:08+00:00

This research establishes new coincidence and common fixed-point theorems for finite families of self-mappings in complete metric spaces endowed with binary relation. Extending the relational framework initiated by Samet and Turinici and later developed by Shatanawi and Sintunavarat, we introduced g-comparative mappings and prove existence and uniqueness theorems for coincidence and common fixed points of families and single map g. The main results are obtained under a generalized contractive inequality where is comparison function and is auxiliary metric expression. By assuming relational regularity, weak compatibility, and the existence of an admissible initial point, we construct a modular-iterative sequence and prove its convergence to unique common fixed point. A numerical example is given to describe how the scheme works.

Crude oil biodegradation potential by mixed consortia of Pseudomonas Lurida and Bacillus Endophyticus

2026-09-29T13:43:24+00:00

Crude oil contamination poses significant environmental challenges due to the persistence and toxicity of its hydrocarbon components. This study evaluated the biodegradation potential of a mixed bacterial consortium comprising Pseudomonas lurida (DSM 15835) and Bacillus endophyticus (DSM 13796) using gas chromatography–mass spectrometry (GC–MS). Sterile sediment microcosms amended with 10% Bonny light crude oil were inoculated with approximately 5 × 10⁷ CFU of the consortium and monitored over five weeks. GC–MS analysis revealed substantial degradation of hydrocarbons ranging from C7 to C44, with marked reductions in peak abundance and the emergence of intermediate metabolites such as octane derivatives and alcohols. The consortium demonstrated enhanced biodegradation efficiency compared to single strains, indicating synergistic interactions. Growth curve analysis showed rapid exponential growth followed by an early stationary phase, suggesting efficient utilization of readily degradable hydrocarbons. The findings highlight the effectiveness of mixed microbial consortia in the bioremediation of petroleum-contaminated environments.

Kinetic and thermodynamic study of saponification of Neem oil (Azadirachta indica) with Sodium Hydroxide using Goat milk as a bioactive additive

2026-09-29T13:50:34+00:00

The growing demand for natural therapeutic personal care products has intensified interest in plant-based oils and dairy additives in soap manufacturing. This study investigates the kinetics and thermodynamics of soap production using neem oil (Azadirachta indica) and sodium hydroxide with goat milk as a functional additive at elevated temperatures (303 K, 313 K, and 323 K). The saponification reaction was monitored by measuring the residual oil concentration at time intervals (10-60 seconds). Kinetic analysis revealed that the reaction follows first-order kinetics across all temperatures, with correlation coefficients (R²) of 0.995, 0.997, and 0.956 at 303 K, 313 K, and 323 K, respectively. Rate constants (k) ranged from 0.012 s⁻¹ to 0.014 s⁻¹. The activation energy (Eₐ) was determined to be 6.41 kJ·mol⁻¹ using the Arrhenius equation. Thermodynamic parameters showed positive enthalpy of activation ( ) ranging from 3.89 to 3.72 kJ·mol⁻¹, indicating an endothermic process. The negative entropy of activation ( =-261 J·mol⁻¹·K⁻¹) suggests a more ordered transition state. Gibbs free energy of activation () increased with temperature from 82.94 to 88.16 kJ·mol⁻¹, indicating reduced reaction spontaneity at higher temperatures. These findings demonstrate that goat milk serves as an effective reaction facilitator by lowering the activation energy barrier compared to conventional saponification processes, while the temperature-dependent kinetic behavior provides valuable insights for optimizing industrial soap production.

Academic Performance Prediction

2026-09-29T15:32:52+00:00

Academic Performance Prediction

Incidence of Clostridium perfringens in retail meat samples from Ikorodu, Lagos, Nigeria

2026-09-29T15:39:37+00:00

Meat is a widely consumed source of protein that is typically cooked or processed to enhance shelf life and ensure safety. However, contamination with Clostridium perfringens is a major cause of foodborne illness due to the ingestion of large numbers of viable vegetative cells following meat consumption. This study investigated the incidence of Clostridium perfringens in retail meat samples from selected markets from Ikorodu, Lagos, Nigeria. A total of 75 samples, comprising 30 beef and 45 chevon, were purchased. Detection and isolation of C. perfringens were carried out on reinforced clostridial agar supplemented with blood under anaerobic conditions after initial pre-enrichment, and the identification was based on morphological and biochemical characteristics using standard microbiological procedures. The overall incidence of C. perfringens in the meat samples was 29.3% (22/75), with an occurrence rate of 31.1% (14/45) in chevon and 26.7% (8/30) in beef. No statistically significant difference (χ² = 0.17, p = 0.68) in occurrence rates between the meat types. These findings highlight the presence of C. perfringens in retail meat sold in markets from Ikorodu and underscore the need for stringent hygiene practices across all stages of meat handling, from slaughter to sale, to reduce the risk of C. perfringens foodborne illness.

Hypoglycemic and α-amylase inhibitory effects of polyherbal aqueous extract in Streptozotocin-induced diabetic Rats

2026-09-29T15:49:06+00:00

Diabetes mellitus is a long-term metabolic disease in which blood sugar is elevated, due to a deficiency of either insulin production or insulin function, or both. Conventional antidiabetic drugs have been found to be limiting, thus making medicinal plants an interest of study as alternative drugs. In this study, antihyperglycemic, α-amylase inhibitory and histopathological effects of polyherbal aqueous extract of Annona muricata, Zingiber officinale and Andrographis paniculata were assessed in streptozotocin induced diabetic rats. Thirty-nine male rats of Sprague-Dawley strain were grouped as diabetic rats treated with 50, 100 & 200 mg/kg of polyherbal extract, diabetic rats not treated, glibenclamide treated rats (10 mg/kg) and normal control rats. Streptozotocin (50 mg/kg) was used to induce diabetes. Seven-day oral treatments were given. The blood glucose level, α-amylase activity, and the histopathology of the pancreas and testicle were determined. The polyherbal extract significantly lowered the blood glucose level in a dose-dependent fashion, with an increase in the level of activity when there was an increase in the dose; significant inhibition of α-amylase activity was also recorded. Histological examination showed that the architecture of the pancreatic islets, presence of β-cell regeneration and structure of the seminiferous tubules were restored in the treated groups as compared to the untreated diabetic rats. Polyherbal aqueous extract showed potent antihyperglycemic and α amylase inhibitory effects and had the beneficial effect on diabetes-induced pancreatic and testicular damage. The results indicated that it could be considered as a therapeutic agent in the management of diabetes mellitus and its associated complications.

Structure and efficiency of onion marketing in Katsina State, Nigeria

2026-09-29T15:54:07+00:00

This research investigated the market structure and efficiency of onion marketing within Katsina State, Nigeria. A multi-stage sampling approach was utilized to gather primary data through structured questionnaires from 335 participants, including 112 producers, 91 wholesalers, and 132 retailers from six key markets: Ajiwa, Dan Nakola, Danja, Katsina, Daura, and Funtua. The analysis employed descriptive statistics, the Gini Coefficient, and Acharya's Marketing Efficiency model. Findings indicated that the onion marketing sector is predominantly male (88.0%), with participants mostly in the economically active 21-40 age range (70.4%), averaging 37.7 years old. Most respondents (89.0%) were married, possessed low formal education levels (71.3% with only informal or primary education), and had an average household size of nine. Gini Coefficient analysis revealed a moderate to high market concentration, with producers experiencing the highest concentration (Gini = 0.539), followed by retailers (Gini = 0.500), while wholesalers operated in a highly competitive environment (Gini = 0.276). The average Marketing Efficiency (MME) was 1.24, with Yar Kutungu (Katsina) identified as the most efficient market (MME = 1.32) and Dan Nakola as the least efficient (MME = 1.17). The study concludes that while onion marketing offers structural profitability for producers, considerable structural disparities remain. It recommends bolstering producer cooperatives, upgrading market infrastructure, and improving retailer capacity through specialized training.

Genetic-lifestyle risk prediction model for hypertension and diabetes using logistic regression

2026-09-29T16:01:54+00:00

This study focused on genetic-lifestyle risk prediction modelling of hypertension and diabetes using the logistic regression method. The sample sizes, n =1000 patients selected from a projected population, N= 567,694 in Lafia, Nasarawa State. A cross-sectional analytical design was employed, utilizing secondary data obtained from the District Health Information System (DHIS2) database. Classical logistic regression and LASSO logistic regression models were fitted to identify significant predictors of hypertension and diabetes. The results show (38.2%) had hypertension, and (29.5%) had diabetes. Many factors are indicated as diabetes risk: older age (OR = 1.053, p = .002), higher BMI (OR = 1.099, p = .001), family history (OR = 2.410, p = .001), and smoking (OR = 1.419, p = .041). Staying physically active, show protective indicator (OR = 0.657, p = .018). Hypertension indicate that age (OR = 1.046, p = .001), BMI (OR = 1.085, p = .001), family history (OR = 2.055, p < .001), and smoking (OR = 1.507, p = .021) increase risk, while physical activity gives protection (OR = 0.694, p = .030). The models show good testing, with AUC values of 0.78 for diabetes and 0.82 for hypertension which is suitable for detecting individual at higher risk. The findings show both diseases share a common genetic and lifestyle factor, which means a single predictive model could realistically screen for both at once which helps health workers in the study area a statistical tool for detecting individuals at risk early and prevention intervention.

Plastic contamination in the Nigerian ecosystem: microplastic research, characterization techniques and regulatory gaps

2026-09-29T16:08:33+00:00

Microplastics (MPs) are pollutants within Nigerian ecosystems. They originate from both industrial manufacturing processes and weathering of plastic waste. This review evaluates the state of microplastic research in Nigeria, localized environmental concentrations, extraction and detection methodologies and existing regulatory frameworks. The main techniques used for MP extraction is wet peroxide oxidation, density separation followed by vacuum filtration, then Nile Red staining for visualisation; whilst detection and quantification are performed with Fourier Transform Infrared (FTIR) Spectroscopy, scanning electron microscopy (SEM) and gas chromatography with flame ionization detection (GC-FID). Other techniques which are available but not currently available in Nigeria include Raman Spectroscopy (RS) and pyrolysis gas chromatography-mass spectrometry (pyr-GC-MS). FTIR, SEM and RS are non-destructive, while pyr-GC-MS is a destructive technique. Densely populated cities like Lagos, Kano, and Ibadan experience high abundance of waste from domestic activities. Information from urban areas like the Kaduna Metropolis reveals heavy contamination across vital sites such as river networks, commercial sachet water, bottled water and dietary staples. It was observed that researchers face limitations, namely a lack of standardized protocols and access to advanced instrumentation such as Raman spectroscopy. An integrated framework connecting advanced analytical instruments with standard optimized sampling and processing protocols with enforceable waste management policies can mitigate the ecological and public health threats posed by plastic pollution in Nigeria.