UMYU Scientifica

Dissolution and Characterization of Goldfieldite Ore from Wase (Nigeria) via Hydrometallurgical Leaching in Ammonia Solutions

2026-09-08T08:16:42+00:00

This study investigates the hydrometallurgical extraction of copper from a complex goldfieldite ore sourced from Wase, Plateau State, Nigeria. The raw ore was systematically characterized using X-ray fluorescence (XRF), X-ray diffraction (XRD), and scanning electron microscopy coupled with energy-dispersive spectroscopy (SEM-EDS). Elemental analysis revealed an ore composition dominated by SiO₂ (57.89%), PbO (19.19%), CuO (8.91%), and Al₂O₃ (9.02%), with mineralogical phases identifying goldfieldite (Cu20.60Te5.20Sb1.71), cerussite, and quartz. Dissolution experiments were performed in an aqueous ammonium hydroxide (NH₄OH) medium to assess the impacts of lixiviant concentration (0.05–0.5 M), reaction temperature (25–75°C), and particle size (45–125 µm) as a function of time. The dissolution rate correlated positively with both increasing lixiviant concentration and temperature, while varying inversely with particle size. Under the operating conditions (0.5 M NH₃, 75°C, 45 µm particle size, and 120 min run time), maximum copper dissolution of 87.0%.was achieved. Mineralogical and morphological evaluations of the spent leached residue verified the systematic depletion of copper phases, leaving a residual matrix dominated by quartz and pyrrhotite (Fe36.00S40.00). These results underscore the viability of alkaline ammoniacal leaching for processing complex, low-grade copper-bearing telluride ores.

A Secured Low-Latency Cyber-Physical Attack Detection and Mitigation Scheme

2026-08-16T20:51:12+00:00

The transition to smart grids integrated with information and communication technology (ICTs) for the Special Protection Group (SPG) not only increases operational efficiency but also creates opportunities for advanced Cyber-Physical Attacks (CPAs). These threats are often stealthy, hard to detect with current security measures, and can quickly evade machine learning (ML) approaches. This paper presents a framework designed for real-time detection and mitigation of CPAs in modern grids. The paper uses a hybrid feature-engineering method that combines physical power information from phasor measurement units (PMUs) and Supervisory Control and Data Acquisition (SCADA) with cyber-side network logs. Using statistical and time-series analysis on this fused information, the authors detected subtle evidence of malicious activity. The key to the developed scheme is a stacking-based ensemble learning framework that integrates XGBoost, Support Vector Machine, and Convolutional Neural Network models to ensure high detection accuracy and reliability. The dataset was divided into 80% for training and 20% for testing; experimental evaluation showed a high detection rate of 96% and a low false positive rate of 1.5% for False Data Injection (FDI), Denial of Service (DoS), and Replay attacks. The framework also provides low detection latency and high throughput, supporting real-time operation. Low latency includes Data acquisition, Data cleaning, Normalization, Synchronization, and windowing. The scheme not only detects threats but enable a context-aware response module to provide real-time isolation of components or rerouting of power in response. This keeps the grid stable even during an attack. The paper presents an advanced AI-powered, real-time defense against increasingly sophisticated cyber-physical threats.

Post-Harvest Losses in Fish Supply Chains in Nigeria and Other Developing Countries: A Review of Causes, Quantification, and Emerging Technologies for Loss Reduction

2026-08-17T06:58:26+00:00

Fish post-harvest losses (FPHLs) are a major constraint to food security, livelihoods and sustainable fisheries, particularly in developing countries. This review synthesizes evidence on the magnitude, causes, assessment methods, mitigation strategies and emerging technologies associated with FPHLs, with emphasis on Nigeria and comparable low- and middle-income countries. A structured literature search covering 2005-2026 was conducted in Scopus, Web of Science, ScienceDirect, Google Scholar, Crossref, PubMed and authoritative FAO and World Bank sources. 215 records were identified, 174 screened and 43 met the inclusion criteria. Evidence was extracted on loss magnitude and types, causal factors, assessment methods, preservation technologies, digital innovations, policy and institutional context, and was synthesized thematically. The evidence indicates that losses occur throughout fish value chains through biological deterioration, poor handling, inadequate preservation, weak cold-chain infrastructure, transportation constraints and socioeconomic factors. Nigerian evidence remains geographically fragmented and methodologically heterogeneous, limiting reliable national estimates of physical, quality and economic losses. Traditional smoking and drying remain important, while improved kilns, solar drying, cold-chain systems and digital technologies provide opportunities for reduction. The review distinguish from previous work by explicitly linking Nigerian evidence with an integrated IFLAM, LT and QLAM assessment framework and technology-enabled monitoring, while examining policy, institutional and implementation gaps. Priority actions include standardized national loss assessments, affordable preservation technologies, stronger cold chains, improved data systems and context-specific policy implementation.

Chemical Surface Functionalization of Woven Kenaf and Industrial Hemp Preforms Using Methyl Acrylate

2026-08-18T12:42:36+00:00

The hydrophilic nature of lignocellulosic fibres, a consequence of the abundant hydroxyl groups in cellulose, hemicellulose, and lignin, remains a persistent barrier to their use in structural polymer composites, promoting moisture uptake, fibre swelling, and weak interfacial adhesion with hydrophobic resin matrices. This study investigated free-radical graft copolymerization of methyl acrylate (MA) as a surface modification route for woven kenaf and industrial hemp preforms, aiming to reduce hydroxyl availability while introducing ester-functional, matrix-compatible polymer chains onto the fibre surface. Alkali-pretreated preforms were grafted with MA using a Fenton (H₂O₂/Fe²⁺) redox initiator system at 50 °C and pH 3.5 for 90 minutes under nitrogen, followed by Soxhlet extraction to remove unbound homopolymer. Grafting outcomes differed measurably between the two preform fibres: kenaf achieved a grafting percentage, grafting efficiency, and percentage polymerization of 21.66%, 57.68%, and 78.11%, respectively, while industrial hemp recorded 17.74%, 44.13%, and 82.53%. FTIR spectroscopy confirmed successful functionalization in both preforms, showing a diagnostic carbonyl band shift toward 1721 cm⁻¹ alongside changes in the hydroxyl and C–O fingerprint regions, consistent with an ester-containing grafted group. Thermogravimetric analysis showed that MA grafting pushed both preforms toward greater thermal resistance, the major degradation onset rose from approximately 200 °C to 220 °C in kenaf and from 250 °C to 270 °C in industrial hemp, while the DTG peak temperature increased by roughly 20–25 °C in each case, and char residue nearly doubled, from 9–10% to 17–18%, in both preform fibres. SEM revealed distinct morphological changes, a continuous polymer film on grafted kenaf compared to granular surface deposits on grafted hemp.

Influence of Methyl Acrylate Grafting on the Physical and Mechanical Performance of Woven Kenaf and Industrial Hemp Infusion Vinyl Ester Resin Composites

2026-08-18T14:05:50+00:00

Natural fibre reinforced polymer composites offer a promising route toward lightweight and more sustainable engineering materials; however, their wider application is often constrained by the hydrophilic nature of lignocellulosic reinforcements and the resulting fibre-matrix incompatibility. In this study, woven kenaf and industrial hemp preforms were surface-modified through methyl acrylate (MA) graft copolymerization and subsequently used as reinforcements in infusion vinyl ester resin composites fabricated by vacuum-assisted resin transfer moulding (VARTM). The influence of MA grafting on the physical, interfacial, mechanical, thermal and morphological characteristics of the resulting composites was evaluated using ungrafted composites as controls. The grafting process produced polymer deposition on both preforms, with grafting percentage, grafting efficiency and percentage polymer pick-up of 37.55%, 57.68% and 78.11% for kenaf, respectively, and 36.31%, 48.88% and 72.63% for industrial hemp. MA modification increased composite density from 1.18 to 1.28 g/cm³ for kenaf and from 1.175 to 1.23 g/cm³ for industrial hemp. Surface wettability was also altered, with contact angles increasing from 87° to approximately 96° for kenaf and from 62° to approximately 103° for industrial hemp, indicating reduced surface wettability following modification. The mechanical response also improved after modification. Tensile strength increased by 32.11% for kenaf and 43.03% for industrial hemp, while tensile modulus increased by 25.00% and 31.84%, respectively. Flexural strength increased by 40.4% and 61.1%, accompanied by increases in flexural modulus of 7.4% and 34.5% for kenaf and industrial hemp, respectively. Impact strength increased by 61.7% for kenaf and 80.4% for industrial hemp, while abrasion mass loss decreased by approximately 41% for both composite systems. Hardness also increased following MA modification. Thermal analysis indicated an upward shift in degradation temperatures, particularly for industrial hemp, while SEM observations revealed improved matrix coverage and a more integrated fracture morphology after grafting. Overall, the findings demonstrate that MA grafting can improve the interfacial and multifunctional performance of woven kenaf and industrial hemp-reinforced infusion vinyl ester composites. Industrial hemp exhibited greater relative improvement in several mechanical and interfacial properties despite its comparatively lower grafting parameters, highlighting the contribution of preform architecture and resin impregnation to the effectiveness of surface modification.

Design and Synthesis of Organic Dyes Incorporating Thiadiazole Moieties for Enhanced Antifungal Applications

2026-08-23T16:12:16+00:00

The growing incidence of drug-resistant fungal infections has intensified the search for novel antifungal agents built on bioactive heterocyclic scaffolds. In this study, we designed two hybridized thiadiazole-based azo dyes, HD1 and HD2, synthesized via diazotization and coupling reactions, and evaluated their antifungal potential. The dyes were obtained in good yields, HD1: 75% and HD2: 80%, displayed sharp melting points, 232–236 °C and 225–230 °C, respectively, and exhibited distinct colorations, purple for HD1 and brown for HD2, consistent with pure, well-conjugated chromophoric systems. FT-IR spectroscopy confirmed the successful incorporation of key functional groups, including carbonyl, 1681.8–1748.8 cm⁻¹, hydroxyl, 3424.7–3514.9 cm⁻¹, and azo, –N=N–, 1581.7–1599.9 cm⁻¹ stretching bands, while UV–Visible analysis revealed absorption maxima at 520 nm for HD1 and 540 nm for HD2, indicative of effective donor–acceptor conjugation across the thiadiazole–azo framework. Antifungal activity was assessed against Candida albicans, Candida tropicalis, and Aspergillus niger using the agar well diffusion method, with fluconazole as the reference drug, followed by determination of the minimum inhibitory concentration, MIC, and minimum fungicidal concentration, MFC. Both dyes displayed dose-dependent inhibition; HD2 consistently produced larger inhibition zones, up to 31 mm against A. niger at 100 mg/mL, than HD1, up to 28 mm, approaching the activity of fluconazole, 34 mm. MIC determination confirmed the superior potency of HD2, which inhibited all test organisms at 12.5 mg/mL, whereas HD1 required 25 mg/mL against C. albicans. MFC values established fungicidal action at 12.5 mg/mL for A. niger and C. tropicalis with HD2, with higher concentrations required against C. albicans. These results show that hybridizing the thiadiazole nucleus with azo chromophores yields dual-function compounds that combine useful colorant properties with promising antifungal activity, and that subtle substituent modifications significantly modulate potency.

Floristic Inventory of Herbaceous Angiosperms and Conservation Needs in the University of Maiduguri Campus, Nigeria

2026-08-23T17:21:16+00:00

Herbaceous angiosperms provide ecosystem services such as the provision of food, local herbal medicines, and maintaining ecosystem properties and functions. The study was conducted at the University of Maiduguri Campus in Borno State, Nigeria, to document and compile an inventory of herbaceous angiosperms within the university campus. From the study, we found that many fields around the campus are disturbed by agricultural activities and infrastructural developments. From our findings, no active undisturbed fields or reserved area specially for botanical garden collections or reserve sites specifically meant for conservation of wild plant biodiversity. Some herbs we documented around the campus are weeds on farms, while some herbs live naturally in drainages and marshes. 8 sampling sites with 14 sampling units were selected for the study. The quadrat sampling method was used, measuring 10x10m for herb documentation since fields around the University of Maiduguri Campus are disturbed by agricultural activities and infrastructural developments. A total of 65 herbaceous angiosperms belonging to 22 families were documented. The family Poaceae has the highest richness of species recorded, with 13. The study contributes to a checklist and in-situ photographs of herbaceous angiosperms. Allocation of permanent undisturbed conservation sites within the University of Maiduguri Campus or University Botanical Garden will play a crucial role in the conservation of native wild flora.

Implementation of a High-Order Diagonally Implicit Block Backward Differentiation Method Incorporating Off-Step Points for Solving Stiff ODEs

2026-09-07T18:29:49+00:00

This work focuses on the derivation and implementation of a 2-point diagonally implicit block backward differentiation formula that integrates off-step points to solve first-order stiff initial value problems (IVPs). The primary architecture of the proposed block method involves the simultaneous computation of two approximate solution values, and , alongside two strategically positioned off-step points, and , at each iteration stage. A rigorous evaluation of the scheme's structural properties confirms that it achieves a true seventh-order algebraic convergence. Furthermore, stability analysis demonstrates that the method is both zero-stable and absolute-stable, making it exceptionally well-suited for the demanding demands of stiff dynamical systems. To evaluate its practical performance, the scheme was deployed against several classic first-order stiff IVPs, and the outcomes were benchmarked against existing state-of-the-art numerical solvers. The empirical results demonstrate that the proposed method consistently outperforms competing schemes, offering a distinct advantage in minimizing scale error while significantly reducing computational execution time. Consequently, this new framework stands as a highly accurate and computationally efficient alternative for integrating first-order stiff ordinary differential equations.

Use of Medicinal Plants by Hausa Ethnic Settlers in Lagos, Nigeria, for Treatment of Common Health Problems

2026-09-07T20:41:25+00:00

An ethnobotanical investigation was conducted to document the use of medicinal plants among Hausa settlers in Lagos. A total of 125 informants (91 men and 34 women) were interviewed using semi-structured questionnaires between 2018 and 2022. The study identified 138 plant species from 101 genera belonging to 57 families used to treat 19 health conditions. The most represented families were Fabaceae (29 species), Euphorbiaceae (8 species), and Moraceae (8 species). Woody tree species (44%), followed by shrubs (29%) and herbs (21%), constituted the primary sources of herbal medicines, with leaves and stem bark being the most frequently utilized plant parts. Decoction was the predominant preparation method (47%), while oral administration was the most common route (83%). Relative frequency of citation (RFC) values ranged from 0.01 to 0.06, and fidelity level (FL) values ranged from 44% to 100%. Boswellia dalzielii and Vangueria agrestis exhibited the highest use value (UV 0.143), followed by Erythrina senegalensis (UV 0.143). Informant consensus was highest for the use of medicinal plants in treating gastrointestinal system disorders (ICF: 0.69) and jaundice (ICF: 0.53). It is recommended that species with high UV and RFC values undergo further phytochemical analysis. The documentation of these findings contributes to the preservation of Hausa cultural heritage and provides a basis for future pharmacological research and the sustainable use of medicinal plants in Lagos.

Computational Investigation of the Electronic Structure of Molybdenum-Doped Lead Tungstate (PbW1−xMoxO4) Scintillators

2026-08-14T20:35:04+00:00

Lead tungstate (PbWO₄) is a prominent scintillator used in high-energy physics experiments owing to its rapid decay time (5 ns) and excellent radiation hardness. However, its low light yield (≈ 200 ph/MeV) limits its utility in medical imaging applications, such as positron emission tomography (PET), which requires higher scintillation efficiency. This study investigates the effects of molybdenum (Mo) doping on the electronic properties of PbW_1−xMo_xO₄ (x = 0.25, 0.5, 0.75) using density functional theory (DFT). Calculations were performed within the GGA+U framework as implemented in the VASP software, utilizing the projector-augmented-wave (PAW) method. Our results reveal a bandgap transition dependent on the doping concentration: x = 0.25 exhibits a direct bandgap of 3.82 eV, while x = 0.5 and x = 0.75 demonstrate indirect bandgaps of 3.62 eV and 3.58 eV, respectively. We observe a systematic decrease in the bandgap as the Mo concentration increases, suggesting a tunable electronic structure. These findings provide a theoretical foundation for the optimization of PbWO₄-based scintillators.

Forecasting Home Win Outcomes in English Premier League Football Matches Using Logistic Regression with Advanced Passing Metrics

2026-09-09T09:30:56+00:00

Football match result prediction is such a huge phenomenon. Prediction can be used by managers and club directors to decide what is needed to win matches. This work sought to develop and evaluate a predictive model for English Premier League (EPL) football match home success using historical EPL summary statistics and logistics regression. The data used was collected from the summary stats section of English Premier League match data collection on fbref.com for the period of 8 years (2018 - 2025). The dataset comprises one dependent variable (HomeWin) and 12 independent variables with a sample size of four hundred and ninety-eight (498) matches. The model built attained 81.05% accuracy after experiments were conducted by altering the seasons of training data used. During the analysis, it was found that Assist Home, Shot on Target Home, ProgressiveP Passes Home, Assist Away, Shot on Target Away, Progressive passes Away, and Successive Take-Ons Away were the only significant variables, while other variables are not significant controlling for them has no significant relationship with whether HomeWin will be 0(no) or 1 (yes). We recommend that both home and away games should not be ignored, as they may have the highest significance in the outcome of football matches. Also, this work can be extended by developing a recommender system from the prediction results to assist club managers to form tactic or strategies both in home and away games, and also enable players to strengthen their significant variables in football matches.

Statistical Evaluation of Geological Influence on Groundwater Radon Concentrations in Gusau Metropolis, Nigeria

2026-09-09T09:51:35+00:00

Groundwater serves as a primary source of domestic water in many urban areas across developing regions, yet naturally occurring radionuclides like Radon-222 can dissolve into aquifer systems and present health risks depending on subsurface geological conditions. This study aimed to statistically evaluate the concentration, spatial distribution, and lithological dependencies of Rn in groundwater across the distinct basement complex formations of Gusau metropolis. A total of 60 groundwater samples (boreholes and hand-dug wells) were collected across seven geological units using a stratified random sampling strategy. Radioactivity levels were analyzed using a Tri-Carb-LSA1000 Liquid Scintillation Counter (LSC) equipped for high-precision analysis after achieving radioactive equilibrium. Data were evaluated using descriptive statistics, frequency distribution modeling, one-way Analysis of Variance (ANOVA), and post-hoc Tukey HSD tests. The overall arithmetic mean concentration of Rn was found to be 26.37 ± 1.14 Bq/L (range: 11.03 - 59.99 Bq/L), with 55% of all samples clustering within the 20 - 30 Bq/L modal range. All measured values complied with the World Health Organization (WHO) reference guideline of 100 Bq/L, though 98.3% exceeded the USEPA maximum contaminant level of 11 Bq/L. Statistically, the data exhibited a positive skewness (1.398) and leptokurtic kurtosis (3.289), indicating localized high-concentration outliers. One-way ANOVA confirmed significant lithological influence on radon concentration (F = 3.066, p = 0.0119 < 0.05). Post-hoc analysis revealed that this statistical variation was primarily driven by a significant difference between the Migmatite (GS4) and Mica Schist (GS7) formations (p = 0.0466). These findings demonstrate that groundwater radon concentrations in Gusau metropolis are inherently controlled by local subsurface lithology. The highly sheared, foliated matrix of the Mica Schist optimizes alpha recoil and elevates radon emanation, whereas dense, recrystallized Migmatite segregations restrict fluid-rock interactions. The results provide essential baseline data for environmental monitoring and suggest that future public health water management strategies in the region should account for localized geological "hotspots" rather than assuming uniform regional risk.

Occurrence of Extended Spectrum β-Lactamase (ESBL)-producing Enterobacterales and blaTEM/blaSHV genes in selected well and river water sources in Adamawa-North, Nigeria

2026-09-09T17:02:29+00:00

Enterobacterales are organisms of public health significance that cause opportunistic and severe infections associated with substantial morbidity and increased mortality. This study examined the occurrence of ESBL-producing organisms in water sources in the Adamawa-North Senatorial Zone, Nigeria. Water samples were screened for bacterial growth, and isolates were identified using standard procedures. Enterobacterales isolates were investigated by phenotypic and molecular methods to assess the prevalence of antibiotic resistance genes associated with Extended Spectrum Beta-Lactamase (ESBL) enzymes. Presumptive ESBL producers were identified by disc diffusion testing and confirmed by the double-disc synergy test. Specific Polymerase Chain Reaction (PCR) assays were used to detect the ESBL genes bla_SHV and bla_TEM. A total of 341 bacterial isolates belonging to the order Enterobacterales were recovered from the water samples. Of these, 153 (44.9%) were resistant to ceftriaxone, ceftazidime, or both. Among the 75 phenotypically confirmed ESBL producers, 62 (82.7%) carried at least one of the two tested genes, whereas 13 (17.3%) had neither bla_TEM nor bla_SHV detected. The bla_TEM gene was detected in 43 (57.3%) isolates and bla_SHV in 47 (62.7%), while 28 (37.3%) carried both genes. Co-detection was most frequent in K. variicola (100%), followed by E. cloacae (80.0%), K. oxytoca (50.0%), C. freundii (50.0%), and M. morgani (50.0%). The odds of detecting bla_TEM relative to bla_SHV were 1.33 times higher among isolates from river water than among those from hand-dug wells, although the association was not statistically significant. These findings indicate the widespread occurrence of ESBLs in Enterobacterales from non-clinical sources. Water sources may therefore serve as reservoirs for the dissemination of antibiotic resistance genes, posing a potential risk to the health and safety of the affected communities.

Fungal Contamination and FTIR-Based Metabolic Profiling of Mycotoxigenic Fungi in Tea Sold in Katsina Metropolis, Nigeria

2026-09-14T13:23:51+00:00

Tea is a widely consumed plant-derived beverage that can serve as a vehicle for fungal and mycotoxin contamination during production, storage, and retail. This study assessed fungal contamination in tea products retailed in Katsina Metropolis, Nigeria, and characterised the associated mycotoxigenic isolates using conventional, molecular and spectroscopic methods. Nine tea brands (coded A–I) were purchased from Katsina Central Market and subjected to serial dilution and plating on Potato Dextrose Agar to enumerate yeasts and moulds. The mean colony counts ranged from 35.0 ± 1.0 to 170.5 ± 10.5 at the 10⁻⁵ dilution and from 10.0 ± 1.0 to 99.5 ± 11.5 at the 10⁻⁶ dilution. Morphological examination and ITS rDNA sequencing identified the recovered isolates as Aspergillus niger, Aspergillus brasiliensis and Aspergillus flavus, with BLASTN sequence identities of 98.84%, 96.81% and 99.61% to reference GenBank accessions, respectively. Fourier-transform infrared spectroscopy of the three isolates produced distinct absorption bands corresponding to O–H, C–H, C=O and C–O functional groups, consistent with proteins, lipids and polysaccharides in the fungal biomass, with isolate-specific differences in peak position and intensity that distinguished the three species. These findings confirm that tea sold in Katsina Metropolis harbours potentially mycotoxigenic Aspergillus species and demonstrate that combining conventional microbiology, molecular identification and FTIR fingerprinting can support rapid, complementary screening of tea for fungal food-safety hazards. However, direct mycotoxin quantification remains necessary to confirm actual toxin exposure risk.

Dough Leavening Ability of Saccharomyces species Isolated from Fruits for Bread Production

2026-09-14T16:14:19+00:00

This study aimed to isolate, identify, and characterize yeast strains from pineapple, orange, and watermelon juices for their potential use as leavening agents in bread production. The yeast isolates were obtained using Potato Dextrose Agar (PDA), followed by morphological and biochemical screening to identify viable Saccharomyces strains. The isolates were then subjected to a series of characterization tests, including temperature and ethanol tolerance and sugar fermentation assays. The fermentation capacity of the most promising isolates was evaluated by producing bread, which was subsequently analyzed for its sensory attributes and volatile organic compounds (VOCs) via Gas Chromatography-Mass Spectrometry (GC-MS). Results showed successful isolation of thermotolerant and ethanol-tolerant yeast strains, with the pineapple isolate exhibiting the highest growth at 40°C. Fermentation tests confirmed the isolates’ ability to utilize a wide range of sugars, including glucose, lactose, and maltose, and their non-pathogenic nature was verified by negative germ tube and urease tests. A one-way ANOVA on sensory evaluation data revealed a statistically significant difference between the fruit-leavened breads and the negative control (p < 0.05). Crucially, there was no statistically significant difference in sensory ratings between the fruit-leavened breads and the positive control (p = 0.84), indicating that the isolated yeasts produced bread with equally desirable attributes. GC-MS analysis provided the chemical basis for these findings, identifying key VOCs such as oleic acid, which contributed to the favorable flavor and aroma profiles. These findings indicate that the yeast strains isolated from fruit juices are suitable for baking and can serve as a viable alternative to commercial baker’s yeast.

Ethnobotanical Use of Nutraceutical Plants and Nutritional Status of Pregnant Women in Katsina State, Nigeria

2026-09-15T07:13:19+00:00

Maternal malnutrition and anemia remain important public health concerns, particularly in low- and middle-income countries where indigenous food plants are widely incorporated into maternal diets. This study assessed nutraceutical plant utilization and maternal nutritional status among pregnant women in Katsina State, Nigeria. A hospital-based cross-sectional study was conducted among 226 pregnant women attending antenatal clinics at four selected hospitals. Socio-demographic, obstetric, and ethnobotanical data were collected using a validated interviewer-administered questionnaire. Nutritional status was assessed using body mass index (BMI) and packed cell volume (PCV), while plant-use patterns were evaluated using frequency of citation and relative frequency of citation (RFC). Multivariable logistic regression was used to assess the association between nutraceutical plant-use intensity and PCV-defined anemia after adjustment for selected maternal characteristics. Twelve nutraceutical plant species were documented. Abelmoschus esculentus (RFC = 0.903), Brassica oleracea (0.881), Spinacia oleracea (0.867), Hibiscus sabdariffa (0.854), and Moringa oleifera (0.827) were the most frequently cited. Overall, 4.0% of respondents were underweight, whereas 29.2% and 28.3% were overweight and obese, respectively. Anemia prevalence was 69.0%. Plant-use intensity was not independently associated with anemia after adjustment for age, residence, education, and parity (adjusted OR = 0.89; 95% CI: 0.71–1.11; p = 0.288). The findings demonstrate widespread nutraceutical plant utilization alongside a substantial burden of maternal anemia. Strengthened antenatal nutrition interventions and further evaluation of the nutritional composition and safety of commonly consumed indigenous plants are warranted.

Physics-Informed Predictive Analytics for Subsurface Fluid–Contaminant Migration Using Hybrid Geophysical Inversion and Machine Learning

2026-09-21T06:25:33+00:00

Geological heterogeneity poses a major challenge to predicting subsurface fluid–contaminant migration and assessing groundwater vulnerability. This study develops a physics-informed predictive framework that integrates geophysical inversion with machine learning (ML) to improve the prediction and interpretation of contaminant migration in heterogeneous subsurface environments. A synthetic dataset comprising 10,000 subsurface realizations was generated within physically representative ranges of electrical resistivity (10–1200 Ωm), seismic velocity (2.5–5.8 km/s), induced polarization chargeability (5–35 mV/V), porosity (12–32%), permeability (80–520 mD), and fracture connectivity (0.2–0.9). The dataset was partitioned into 7,000 training, 1,500 validation, and 1,500 independent test samples, with a fixed random seed used to ensure reproducibility. Geophysical and hydrogeological variables were integrated through constrained modelling and used as inputs to Random Forest (RF) and Gradient Boosting (GB) classifiers for contaminant-migration risk prediction. Model performance was evaluated using accuracy, precision, recall, and F1-score, while feature-importance analysis was used to identify the dominant controls on predicted contaminant migration. The class-specific evaluation produced accuracies ranging from 76.9% to 84.6% and F1-scores from 0.75 to 0.84 across the three contaminant-risk classes. In the ablation analysis, the complete physics-informed configuration achieved independent-test accuracies of 91.07% for Random Forest and 91.47% for Gradient Boosting, with corresponding macro-F1 scores of 0.900 and 0.904, respectively. Relative to the conventional machine-learning baseline, the Gradient Boosting macro-F1 increased from 0.771 to 0.904, representing a 17.3% relative improvement under identical test conditions. Resistivity, permeability, and fracture connectivity emerged as important predictors of contaminant-migration behaviour, reflecting the influence of fluid saturation, hydraulic properties, and preferential flow pathways. The results demonstrate the potential of integrating geophysical information with machine learning to provide physically interpretable predictions of contaminant-migration risk in heterogeneous subsurface environments. The framework provides a reproducible simulation-based foundation for subsequent validation using independent field or benchmark datasets.

Heavy Metal Contamination and Human Health Risk Assessment of Borehole Water at an Academic Campus in Ila-Orangun, Southwestern Nigeria

2026-08-13T08:32:24+00:00

This study assessed the hydrogeochemistry and health risks associated with groundwater from five existing boreholes sampled once in July, 2024, at Osun State College of Education, Ila-Orangun (OSCEILA), to determine their suitability for drinking and dermal use. Physicochemical parameters and heavy metal concentrations were analyzed, alongside Water Quality Index (WQI) evaluations and human health risk assessments through ingestion and dermal exposure pathways. Most water samples exhibited acceptable pH (7.05–7.89), turbidity (0.76–0.82 NTU), and salinity (0.48–0.97 mg/L), with four boreholes classified as “Excellent” by reflecting the quality of the physicochemical parameters incorporated into the WQI indices. However, Borehole 2 (BH 2) showed elevated electrical conductivity, total dissolved solids, and heavy metal levels, likely influenced by atmospheric deposition and anthropogenic sources such as waste disposal and runoff. Health risk analysis revealed non-carcinogenic and carcinogenic concerns, especially for children. While most samples had hazard quotient (HQ) values below the safe threshold (HQ < 1), BH 2exceeded this limit for children (HQ = 1.45), suggesting potential adverse effects. Carcinogenic risk values for both adults and children far exceeded the acceptable threshold (10⁻⁴), with children at BH 2 facing the highest risk (3.123189). Although dermal exposure posed comparatively lower risks, values still exceeded safe levels. Regular monitoring is recommended to mitigate long-term health effects.

Extension of the Fuzzy Laplace Transform Method for Solving Higher-Order Nonlinear Fuzzy Ordinary Differential Equations under Generalized Hukuhara Differentiability

2026-08-13T13:20:01+00:00

Higher-order nonlinear fuzzy ordinary differential equations (FODEs) arise in many real-world systems where uncertainty and imprecision are inherent, such as engineering processes, biological models, and economic dynamics. Traditional analytical and numerical techniques often encounter difficulties when dealing with such equations, particularly under generalized differentiability conditions. This study presents an extension of the Fuzzy Laplace Transform Method (FLTM) for solving higher-order nonlinear FODEs under generalized Hukuhara differentiability. The proposed approach combines the Laplace transform technique with fuzzy calculus to transform complex fuzzy differential equations into more manageable algebraic forms in the Laplace domain. The method accommodates different cases of generalized Hukuhara differentiability and provides systematic procedures for handling nonlinear terms in higher-order fuzzy systems. By applying the inverse fuzzy Laplace transform, explicit fuzzy solutions can be obtained in parametric form. The effectiveness and reliability of the extended method are demonstrated through illustrative examples of higher-order nonlinear FODEs, where the obtained solutions show strong agreement with known analytical results and highlight the method’s capability in dealing with uncertainty in dynamic systems. The results indicate that the extended FLTM offers a powerful, efficient, and flexible framework for solving a wide class of higher-order nonlinear fuzzy differential equations under generalized Hukuhara differentiability, thereby contributing to the advancement of analytical techniques in fuzzy differential analysis. The study concludes with recommendations for future research, focusing on establishing solutions for both odd- and even-order FODEs.

Synergistic Effects of Hybrid Zinc Oxide/Graphene Oxide Nanocatalyst on Photocatalytic Degradation of Acetamiprid Insecticide

2026-08-13T13:15:50+00:00

The persistence of pesticide residues in aquatic environments necessitates the development of efficient and sustainable remediation technologies. This study investigated the synergistic effects of a ZnO/GO nanohybrid on the photocatalytic degradation of acetamiprid in aqueous medium. The photocatalyst was synthesized via a co-precipitation method and characterized using XRD, SEM/EDX, FTIR, and BET analyses. XRD confirmed the formation of crystalline hexagonal wurtzite ZnO with an average crystallite size of 10.7 nm, while the characteristic diffraction peak of GO at 2θ = 11.1⁰ verified successful oxidation of graphite. SEM revealed layered GO sheets decorated with well-dispersed ZnO nanoparticles, whereas EDX analysis confirmed the elemental composition of the nanohybrid through the presence of Zn and O. FTIR spectra showed characteristic oxygen-containing functional groups and Zn-O vibrations. BET analysis revealed mesoporous structures with surface areas of 216.3 and 197.7 m²/g for GO and ZnO/GO, respectively, indicating suitability for adsorption and photocatalytic applications. Photocatalytic investigations at pH 9, a catalyst dose of 70 mg, and an irradiation period of 120 minutes resulted in maximum degradation efficiencies of 68%, 74%, and 96%. Kinetic analysis showed that acetamiprid degradation followed a pseudo-first-order model with a rate constant of 0.0246 min^-1 and a half-life of 28.17 min. Thermodynamic studies indicated a photon-driven process with low energy of activation and positive Gibbs free energy values. Photolysis resulted in only 9.6% degradation, while recyclability studies demonstrated good catalyst stability over five successive cycles. The enhanced photocatalytic performance was due to the interaction between ZnO and GO, demonstrating its potential for pesticide-contaminated wastewater treatment.

Habitat Fragmentation and Seasonal Variation Shape Butterfly Community Structure in a Tropical University Landscape, Nigeria

2026-08-13T13:04:56+00:00

Habitat fragmentation and seasonal variation are key ecological factors influencing butterfly community structure in tropical ecosystems. This study investigated their effects at Federal University Wukari, Taraba State, Nigeria. Surveys were conducted along a 1500 m transect within each of two habitat types (fragmented and non-fragmented), sampled weekly for four weeks per season, using sweep-netting and the Pollard walk method. Data were analyzed in R for species richness, abundance, diversity (Shannon–Wiener, Simpson), evenness, dominance, and Jaccard similarity, with paired comparisons across replicate weekly samples testing habitat and seasonal effects. A total of 438 individuals representing 45 species and five families were recorded; Nymphalidae was dominant (164 individuals, 37.4%), followed by Pieridae (124, 28.3%) and Lycaenidae (105, 24.0%). The non-fragmented habitat had significantly greater abundance (303; t = 4.01, p = 0.005) and richness (41 species; t = 5.48, p < 0.001) than the fragmented habitat (135; 26 species), persisting after rarefaction to equal sample size. Diversity indices were higher in the non-fragmented habitat (Shannon = 3.121; Simpson = 0.935) than the fragmented habitat (Shannon = 2.493; Simpson = 0.861). The dry season had significantly higher abundance than the wet season (251 vs 187; t = 2.39, p = 0.048), though richness did not differ significantly (p = 0.157); wet-season diversity and evenness were slightly higher. Species composition showed moderate similarity between habitats (Jaccard = 0.489) and seasons (0.556), indicating turnover. These findings show habitat fragmentation exerts a stronger, statistically supported influence on community structure than seasonal variation, underscoring the value of intact vegetation for tropical university landscapes.

Socioeconomic Impact on Maternal Health Outcomes in Nigeria

2026-08-13T13:01:16+00:00

This study examines the socioeconomic pathways influencing maternal health utilization and outcomes in Nigeria using data from the 2018 Nigeria Demographic and Health Survey (NDHS). While prior studies have established associations between socioeconomic factors and maternal health, limited attention has been paid to distinguishing maternal health utilisation from outcomes and to decomposing the direct and indirect effects of socioeconomic status within a unified modelling framework. Structural Equation Modeling (SEM) was employed to estimate both measurement and structural relationships among latent constructs. Confirmatory Factor Analysis (CFA) and reliability diagnostics confirmed adequate construct validity and internal consistency. Model fit indices indicated good overall model performance. The results show that socioeconomic status has a significant positive effect on maternal health utilization (β = 0.41, p < 0.01) and maternal health outcomes (β = 0.32, p < 0.01), with utilization partially mediating the relationship between socioeconomic status and health outcomes. The findings highlight the central role of income, education, and employment in shaping access to maternal health services and improving health outcomes. This study provides updated national evidence and policy-relevant insights to support targeted socioeconomic and health system interventions aimed at achieving maternal health improvement goals in Nigeria.

Assessment of Geothermal Potential in Sokoto and Environs, North-Western Nigeria, using Airborne Magnetic Data

2026-08-13T12:52:33+00:00

The search for alternative and sustainable energy resources has increased interest in geothermal energy exploration across Nigeria. This study assessed the geothermal potential of Sokoto and its environs, north-western Nigeria, using high-resolution aeromagnetic data. The study area lies between longitudes 4.5°E and 6.0°E and latitudes 12.5°N and 13.5°N within the Sokoto Basin and adjoining basement terrains. The aeromagnetic data were processed and interpreted using spectral depth analysis based on the modified centroid method to estimate the depth to magnetic sources, Curie point depth (CPD), geothermal gradient, and heat-flow distribution. Results show that the depth to the top of magnetic sources ranges from 0.23 to 0.52 km, while centroid depths vary from approximately 3 to 10 km. Curie point depths range from 6 to 19 km, indicating significant variations in the thermal structure of the crust. The derived geothermal gradients vary between 30 and 90 °C/km, whereas heat-flow values range from 75 to 225 mWm⁻². Shallow Curie depths, high geothermal gradients, and elevated heat-flow values are concentrated mainly in the eastern part of the study area, suggesting relatively high subsurface temperatures and favourable geothermal conditions. Comparison with the geological map indicates that these thermal anomalies are largely associated with sedimentary formations comprising shale, claystone, siltstone, and sandstone units. The results reveal considerable geothermal resource potential within the study area, particularly in the eastern sector, and provide a useful basis for future geothermal exploration and development in north-western Nigeria.

A Multi-Depot Shipper Lane Selection Problem with Time Windows in Transportation Service Market

2026-08-13T12:47:22+00:00

In the transportation service market, Shippers take the role of auctioneers, facing a problem known as the Shipper Lane Selection Problem (SLSP). The problem involves carefully evaluating which lanes should be serviced by their vehicle fleets and which should be outsourced to external carriers through auctions. However, the SLSP has not been applied when a logistics distribution company has multiple depots. In this study, the multi-depot nature of the problem is incorporated into SLSPTW to become Multi-Depot Shipper Lane Selection Problem with Time Windows (MDSLSPTW). The mixed integer linear program model developed was aimed at minimizing the total cost of shippers' transportation services expenditure. The model was implemented using AMPL and solved with CPLEX 22.1.2 to obtain the optimal solution. The validity of the model has been tested by using a modified instance of Solomon’s data. From the scenario analysis, it was found that the percentage of lanes auctioned off increases with the cost of self-servicing but decreases with the cost of outsourcing as the fixed setup cost for conducting an auction becomes lower. The findings of this study provide valuable insights for logistics distribution companies operating multiple depots, offering opportunities to enhance the strategic decision-making processes for the procurement of transportation services.

In Vitro Evaluation of Ocimum gratissimum Leaf (Scent Leaf) Extracts Against Selected Clinical Multidrug-Resistant Bacterial Isolates

2026-08-13T12:44:08+00:00

The rise in multidrug-resistant (MDR) pathogens has made the search for alternative sources of antimicrobial agents a global priority. This study investigated the phytochemical constituents, antioxidant capacity, and antibacterial activities of aqueous and ethanol leaf extracts of O. gratissimum against selected MDR clinical bacterial isolates (Staphylococcus aureus, Bacillus cereus, Escherichia coli, and Klebsiella pneumoniae). Phytochemical constituents and total antioxidant capacity of O. gratissimum were determined using standard laboratory procedures. Antibacterial activity was assessed by the agar well diffusion method at concentrations ranging from 12.5 to 200 mg/mL, while minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) were determined using broth dilution techniques. Data were expressed as mean ± standard deviation (SD), and statistical analysis was performed using one-way analysis of variance (ANOVA) at p < 0.05. The ethanol extract produced a higher extraction yield (17.88%) than the aqueous extract (13.66%) and contained significantly greater amounts of phytochemicals (p < 0.05) and exhibited higher antioxidant capacity (240.53 ± 3.12 µg/mL) than the aqueous extract (228.19 ± 2.84 µg/mL) (p = 0.018). Both extracts showed concentration-dependent antibacterial activity, although the ethanolic extract produced significantly larger inhibition zones ( p < 0.001). Both extracts had an MIC of 25 mg/mL, while the ethanolic extract exhibited MBC values between 50-100 mg/mL. These findings support the traditional therapeutic use of the plant and suggest its potential as a natural source of antimicrobial agents. Further studies involving advanced phytochemical characterization, toxicity evaluation, and in vivo validation are recommended to support future pharmaceutical applications.

Microbiological Spectrum and Antibiotic Resistance Patterns of Diabetic Foot Infections Among Adults in some Tertiary Health Care Facilities in Adamawa State, Nigeria

2026-08-13T12:35:38+00:00

Diabetic foot infections are major complications of diabetes mellitus and are associated with prolonged morbidity, antimicrobial use, hospitalization, and risk of lower-limb amputation. Local data on causative organisms and resistance patterns are essential for effective empirical therapy. This study determined the microbiological spectrum and antibiogram of diabetic foot ulcers among adult patients attending the Surgical Outpatient Department of Modibbo Adama University Teaching Hospital, Yola, Adamawa State, Nigeria. An observational cross-sectional study was conducted from January to December 2025 among consecutively recruited consenting adult patients with diabetic foot ulcers. Demographic and clinical data were collected using a semi-structured questionnaire and medical proforma. A total of 81 diabetic foot wound samples were obtained. Ulcers were graded using Wagner’s classification. Bacterial and fungal isolates were identified using conventional microbiological and biochemical methods. Antibiotic susceptibility testing was performed using the Kirby–Bauer disc diffusion method. Extended-spectrum beta-lactamase production was detected using the double-disc diffusion synergy test, while methicillin-resistant Staphylococcus aureus was identified using the cefoxitin susceptibility test. A total of 118 microbial isolates were recovered from 81 diabetic foot ulcer specimens. Most patients were male, 57/81 (70%), with a mean age of 60.67 ± 11.76 years. Monomicrobial infections accounted for 45/81 (56%) cases, while 36/81 (44%) were polymicrobial. Type 2 diabetes mellitus was predominant, 68/81 (84%), and 45/81 (56%) had lived with diabetes for more than 10 years. Wagner grade 3 ulcers were the most frequent, 26/81 (32%). Gram-negative bacilli predominated, 89/118 (75.4%), followed by Gram-positive bacteria, 26/118 (22%), and Candida albicans, 3/118 (2.6%). The leading isolate was Klebsiella pneumoniae, 28/118 (24%). Gram-negative isolates showed high resistance to Ampicillin and commonly used beta-lactams, while carbapenems retained comparatively better activity. Among Gram-positive isolates, S. aureus showed 100% susceptibility to linezolid and vancomycin, but 75% were methicillin-resistant. No vancomycin resistance was detected. Overall, multidrug resistance was observed in 79/118 (67%) isolates, while 29/118 (24.5%) were extensively drug-resistant. Among Gram-negative isolates, ESBL production, carbapenem resistance, and colistin resistance were detected in 40/89 (45%), 20/89 (22.5%), and 4/66 (6%) isolates, respectively. Diabetic foot infections in this setting were predominantly monomicrobial and mainly caused by Gram-negative bacilli, with a high burden of multidrug resistance, ESBL production, carbapenem resistance, and MRSA. Routine culture, susceptibility testing, and periodic local antibiogram surveillance are recommended to guide empirical therapy and reduce diabetes-related foot complications in Adamawa State.

Oxidative Desulphurization of Thiophene in Model Diesel over Copper-Promoted Nickel Oxide Supported on Silica

2026-08-13T12:30:29+00:00

Stringent environmental regulations and the demand for ultra-low-sulfur fuels have increased interest in oxidative desulfurization (ODS), which operates under mild conditions and efficiently oxidizes refractory sulfur compounds. This study aimed to synthesize and optimize silica-supported nickel oxide and copper-promoted nickel oxide catalysts for the ODS of model diesel fuel. Nominal 2.1 wt% Ni/SiO₂ and 0.23 wt% Cu-promoted Ni/SiO₂ catalysts (Cu/Ni-SiO₂) were prepared by incipient wetness impregnation, dried at 80 °C, and calcined at 600 °C for 5 h. The catalysts were characterized by FTIR, XRD, and EDX spectroscopy. Model diesel (containing 100 ppm thiophene) was oxidized with H₂O₂ and extracted using Dimethylformamide solvent. The conversion of thiophene into extractable sulfone form was determined by UV/Visible Spectrometer at 380 λ max using an external calibration curve (R² = 0.9497). The process optimization employed a 17-run Box–Behnken design. Experiments were performed in triplicate. Preliminary experiments showed that the Cu-promoted catalyst calcined at 600 °C achieved 75% sulfur removal, outperforming the monometallic catalyst (Ni-SiO₂). Analysis of variance indicated that the quadratic response surface model was statistically significant (F = 105.35, p < 0.05) with a non-significant lack of fit (p = 0.28), confirming its adequacy for process optimization. The optimized conditions were 52.5 °C, 60 min, and an oxidant-to-sulfur molar ratio of 1.0, under which a maximum sulfur removal of 92.0% was achieved. Cu-promoted Ni/SiO₂ is a promising catalyst for the oxidative desulfurization of model diesel under mild conditions.

Facile Synthesis of MIL-53(Fe) and its Modification with Green-Synthesized TiO₂ for Enhanced Photocatalytic Degradation of Methylene Blue

2026-08-13T12:27:23+00:00

The continuous release of dye-laden wastewater from industrial processes has become a major environmental and public health concern, highlighting the need for effective and environmentally friendly treatment technologies. In this work, MIL-53(Fe) was synthesized using a solvothermal approach, whereas TiO₂ nanoparticles were produced through a green synthesis method employing Jatropha curcas leaf extract as both a reducing and stabilizing agent. TiO₂–MIL-53(Fe) nanocomposites, denoted as TM-10 and TM-30, were subsequently prepared and investigated for the visible-light-assisted photocatalytic degradation of methylene blue (MB). The structural, morphological, and optical properties of the synthesized materials were examined using FTIR, XRD, SEM, and UV–Vis spectroscopy. The characterization results verified the successful integration of TiO₂ into the MIL-53(Fe) framework, leading to enhanced crystallinity, improved surface morphology, and superior optical performance. The effect of operation parameters on the degradation was also studied. Results showed that the removal rate of methylene blue increased with the increased dosage of catalyst and decreased initial concentration of methylene blue and the acidic condition is favorable for degradation. In particular, TM-30 exhibited a narrowed band gap of 1.8 eV, indicating greater responsiveness to visible-light irradiation. Photocatalytic experiments showed that methylene blue degradation increased progressively with irradiation time for all catalysts, with the activity following the sequence TM-30> TM-10 > TiO₂ > MIL-53(Fe). Under visible-light irradiation for 180 min, TM-30 achieved a degradation efficiency of 90%, markedly exceeding that of the individual components. The superior photocatalytic performance was attributed to enhanced charge-carrier separation, reduced electron–hole recombination, and the synergistic interaction between TiO₂ and MIL-53(Fe). These results highlight the promise of the green-synthesized TM-30 composite as a highly efficient and sustainable photocatalyst for dye-contaminated wastewater treatment.

Design and Prototype Implementation of an ESP32-Based Web Smart Home Automation System for Remote Appliance Control

2026-08-13T12:23:41+00:00

The rapid advancement of the Internet of Things (IoT) has significantly transformed modern home environments by enabling intelligent monitoring and remote control of household appliances. However, many existing smart home automation systems remain expensive, difficult to deploy, or unsuitable for resource-constrained environments. This study presents the design and implementation of a secure web-based smart home automation system using the ESP32 microcontroller for real-time device control. The proposed system integrates a three-layer client-server architecture consisting of a Progressive Web Application (PWA) frontend, a backend API server, and an ESP32-based embedded hardware layer. Communication between the backend and the ESP32 is achieved through Wi-Fi using a polling mechanism, while secure device authentication is implemented using Board ID and Secret Key validation. The system supports role-based access control for administrators, standard users, and restricted users, thereby improving operational security and usability. Hardware integration was achieved using relay modules, LEDs, and a DC motor to simulate household appliances. The developed prototype was evaluated using functional and usability testing approaches to assess system responsiveness, reliability, synchronization accuracy, and ease of use. Experimental results demonstrate that the system provides stable communication, efficient remote device control, reliable real-time synchronization, and secure interaction between software and hardware components. The study establishes that low-cost and readily available embedded technologies can be effectively integrated to develop scalable and user-friendly smart home automation solutions suitable for developing environments.

Effects of Gamma Irradiation on Sprout Suppression, Shelf-Life Extension, and Quality Preservation of Yellow Yam (Dioscorea cayenensis) During Ambient Storage

2026-08-13T12:18:54+00:00

In West Africa, Dioscorea cayenensis (yellow yam), one of the major staple food crops, is vulnerable to ambient storage losses due to sprouting, rotting, moisture loss, and quality deterioration. The effects of low-dose gamma irradiation on the suppression of sprouts and proximate composition of yellow yam during ambient storage, storage quality, weight loss, and rotting incidence were evaluated in this study. The 60 healthy tubers were randomly divided among the six treatments (10 tubers/treatment): unirradiated (0 Gy) and irradiation at a cobalt-60 gamma source of 50, 70, 80, 90, and 100 Gy doses. After irradiation, tubers were placed under ambient conditions and were examined periodically for sprouting, rotting, and loss in weight, and the proximate composition was determined by standard AOAC methods after storage for five months. Gamma irradiation was found to give dose-dependent improvements in storage performance. The sprouting dropped to 20% at 50 Gy and 10% at 70 Gy, and was completely suppressed at 80-100 Gy. Rotting was only observed in the control group (10%), while no rotting was observed in the tubers subjected to irradiation. Mean weight loss declined from 64.79 ± 13.45% in the control to 17.27 ± 5.45% at 100 Gy. Ash, crude fibre, protein and carbohydrate contents were higher, and moisture and crude fat were lower in the irradiated tubers as compared to the control. The results of statistical analysis revealed statistically significant differences among the treatments for the sprouting, loss of weight and proximate composition (p<0.05) of the sprouts. It was concluded that low-dose gamma irradiation, especially 80–100 Gy, was a potential technology to stop the sprouting and enhance the storage quality of yellow yam over five months of ambient storage without compromising its nutritional attributes. There is a need to conduct more extensive tests with commercial storage before widespread use.

Performance Evaluation of Empirical Path Loss Models for Some GSM Networks in a Tropical Urban Environment: A Case Study of Zaria City

2026-08-13T12:15:00+00:00

An accurate path loss prediction is essential for efficient wireless network planning, particularly in tropical urban environments where terrain and atmospheric conditions significantly influence signal propagation. This study investigates the performance of four widely used empirical path loss models (Ericsson, COST-231, Plane Earth, and ECC-33) in Zaria City, Nigeria, representing a typical tropical urban environment. The problem addressed in this research is the inaccuracy of conventional path loss models when applied to tropical urban environments without required local validation, leading to inefficient network planning and poor quality of service. Field measurements of Received Signal Strength (RSS) were collected through GPS-aided drive tests using a spectrum analyzer and a digital weather station to simultaneously capture environmental parameters such as temperature, humidity and pressure. The collected data were used to compare measured and predicted path loss values using statistical tools such as Root Mean Square Error (RMSE) and correlation analysis. The results revealed that the COST-231 model achieved the lowest RMSE values (3.36 dB for MTN and 3.83 dB for 9 - Mobile), indicating the highest prediction accuracy in dense urban conditions. The Ericsson model showed moderate performance, while ECC-33 and Plane Earth models exhibited significant deviations and poor suitability. The findings are limited to measurements collected during the late dry season and should therefore be interpreted within that climatic context. The study also provides practical guidance to mobile network operators, researchers, and planners interested in improving the performance of GSM networks in tropical cities.

Spatial Variation of Natural Gamma Radiation and Radiological Dose around a University Hostel Environment in Zaria, Nigeria

2026-08-13T11:38:21+00:00

Natural radioactivity from terrestrial radionuclides significantly raises ambient radiation exposure in densely populated regions and must be routinely monitored. This study assessed the geographical distribution and radiological consequences of natural gamma radiation in the soils surrounding the ICSA/RAHMAT Hostel at Ahmadu Bello University (ABU), Zaria, Nigeria. Measurements were taken at twenty sample locations using a handheld GPS and a portable gamma-ray spectrometer. Potassium-40 (⁴⁰K), thorium-232 (²³²Th), and uranium-238 (²³⁸U) count rates (CPS) and absorbed dose rates in air (nGy/h) were noted. Annual outdoor effective dose (AOED) values were estimated using established UNSCEAR conversion methods and compared to international safety guidelines. Count rates ranged from 0.48-1.40 CPS (Th-232), 1.21-1.78 CPS (U-238), and 3.46-6.92 CPS (K-40). The greatest and most reliable predictor of dosage rate was potassium (R² = 0.774). The absorbed dose rates peaked at SP3, where all three radionuclides were co-elevated, and varied from 107.5 to 196.4 nGy/h. Every sampling station above the UNSCEAR worldwide outdoor average (~59 nGy/h), which was around 2.6 times lower than the survey mean (156.1 nGy/h). Despite this, all AOED levels (mean: 0.1915 mSv/y) remained well below the ICRP public exposure limit of 1 mSv/y (~19% of the threshold). Geospatial interpolation revealed significant spatial diversity, with higher zones between SP3 and SP19 being caused by lithological heterogeneity. Even though the area has a naturally higher radiometric background and does not provide a significant radioactive risk under current occupancy estimates, continuous monitoring is recommended due to the hostel's high population density.

Integrated Organic Geochemical, Biomarker and Carbon Isotope Evaluation of Source-Rock Affinities in the Anambra Basin, Nigeria

2026-08-13T09:37:48+00:00

The Campanian-Maastrichtian succession of the Anambra Basin contains organic-rich lithologies with uncertain contributions to the petroleum system. This study integrates Rock-Eval pyrolysis, TOC, vitrinite reflectance, biomarker geochemistry, and compound-specific carbon isotope analyses of saturated and aromatic hydrocarbon fractions to assess the hydrocarbon generation potential and source-rock affinities of the Nkporo Shale and Mamu Formation. Twenty-eight rock samples (eleven Nkporo shales, nine Mamu shales, eight Mamu coals) were analyzed, with a representative subset (six Nkporo shales, six Mamu shales, four Mamu coals, and six crude oils) subjected to detailed biomarker and isotope analyses. The Nkporo Shale is a fair to good source rock (average TOC = 1.66 wt%) with Type III to mixed Type II/III kerogen, while the Mamu Formation is heterogeneous with organic-rich shales (TOC up to 7.93 wt%). Thermal maturity parameters (Tmax = 417–443°C, Ro = 0.22–1.51%) indicate immature to peak oil-window conditions. Biomarker distributions distinguish the two units: the Nkporo Shale exhibits C₂₀–C₂₃ n-alkanes, moderate Pr/Ph ratios (1.78–2.61), and elevated C₂₈ steranes, indicating mixed marine-terrestrial organic matter deposited under mildly oxic conditions. In contrast, the Mamu Formation shows C₂₇–C₃₉ n-alkanes and elevated Pr/Ph, CPI, and TAR values, reflecting higher-plant input in continental swamp to coastal plain environments. Principal Component Analysis and Hierarchical Cluster Analysis (PC1 = 37.5%, PC2 = 14.8%; cophenetic correlation = 0.772) corroborate two distinct organic facies and place the ANAR crude oil within the mixed marine-terrestrial cluster containing both Nkporo and Mamu shales. While biomarker, isotopic, and multivariate evidence points to closer affinity between the ANAR oil and the Mamu Formation, a subordinate Nkporo contribution cannot be excluded. The Mamu Formation is identified as a significant liquid hydrocarbon source, though quantitative mixing models are needed to precisely partition relative source contributions.