This study examines the estimation of the scale parameter of the Weibull-Power Function Distribution (WPFD) using both maximum likelihood and Bayesian approaches. Bayesian estimation is conducted under one informative Gamma prior with hyperparameters , as well as two non-informative priors: the uniform prior and Jeffreys’ prior. For each prior specification, Bayes estimators are derived under squared error, quadratic, and precautionary loss functions. Closed-form expressions for the posterior distributions and corresponding Bayes estimators are obtained. The finite-sample performance of the competing estimators is evaluated through a Monte Carlo simulation study based on 1000 replications. Estimator performance is assessed using mean squared error (MSE), bias, and coverage probability. The results indicate that all estimators are consistent, with bias and MSE decreasing as sample size increases. Across different prior specifications and parameter settings, the Bayesian estimator under the quadratic loss function consistently attains the lowest MSE, yielding reductions of approximately 10-20% relative to the maximum likelihood estimator in small and moderate samples. These findings suggest that Bayesian estimation under quadratic loss provides improved finite-sample efficiency for estimating the WPFD scale parameter, while maintaining asymptotic comparability with the maximum likelihood approach.

Hospital length of stay (LOS) is a key indicator of healthcare efficiency and resource utilization, particularly for chronic infectious diseases such as hepatitis B virus (HBV) infection. Prolonged hospitalization increases costs and strains limited hospital capacity in low-resource settings. Accurate statistical modelling of LOS is therefore essential for planning bed utilization and improving patient management. This study compares Exponential and Log-Normal accelerated failure time (AFT) survival regression models for predicting LOS among patients living with HBV in Maiduguri, Nigeria. A retrospective cohort of 60 HBV admissions at a tertiary hospital in Maiduguri was analyzed. LOS (days) was defined as the time from admission to discharge, with deaths and transfers treated as non-discharge outcomes in sensitivity analyses. Covariates included age, gender, marital status, diagnostic method, disease stage, comorbidity, antiviral treatment, and admission type. Exponential and Log-Normal AFT models were fitted and compared using log-likelihood, Akaike and Bayesian information criteria (AIC, BIC), likelihood ratio tests, graphical diagnostics (Q–Q and residual plots), and prediction accuracy metrics (mean absolute error (MAE) and root mean squared error (RMSE)). Of the 60 patients, 38 were discharged alive, 6 died, and 16 were transferred. LOS was positively skewed. The Log-Normal AFT model outperformed the Exponential model with higher log-likelihood (−139.56 vs −194.48), lower AIC (161.87 vs 402.97) and BIC (178.62 vs 417.63), and substantially improved prediction accuracy (MAE = 3.66 vs 12.97 days; RMSE = 8.50 vs 28.20 days). In the Log-Normal model, age significantly prolonged LOS (TR ≈ 1.06 per year), implying about a 5–6% increase in expected stay per additional year of age. Antiviral treatment markedly reduced hospitalization time (TR ≈ 0.55), resulting in a roughly 45% shorter LOS. Gender, disease stage, and comorbidity also showed significant associations with LOS. Diagnostic plots indicated better conformity to Log-Normal assumptions than to the Exponential specification. The log-normal AFT model offers better fit, prediction, and interpretability than the exponential model for HBV-related LOS. Effects on time ratios may be translated to indicate that timely use of antiviral therapy may save 4–5 bed-days per patient, whereas older age alone significantly increases demand for bed types. These results justify the application of Log-Normal AFT models to predict LOS and hospital resource planning in resource-constrained environments.

An investigation was conducted to assess the heavy metal contamination, physicochemical quality, and associated non-carcinogenic health risks in well water and borehole water sources across the Kaduna Metropolis. Water samples were analyzed for six physicochemical parameters and five heavy metals (Zn, Cd, Pb, Cu, Cr) in triplicate, achieving high precision with method detection limits (LOD) typically below 0.001 mg/L. Statistical analysis showed a highly significant difference (p<0.01) in Electrical Conductivity (EC), with the well water mean (1.59 mS/cm ) exceeding the WHO limit. The study found widespread contamination with toxic metals in both sources. Key exceedances included Cadmium (Cd), which exceeded the WHO limit by approximately 2.3 × (up to 0.008 mg/L), and Lead (Pb), which exceeded the WHO limit by over 5 × (up to 0.054 mg/L) in well water. The health risk assessment confirmed a Significant Non-Carcinogenic Risk for well water (Hazard Index, HI=2.472) and a Potential Risk for borehole water (HI=1.317), with Chromium (Cr) as the primary driver (Well Cr up to 0.484 mg/L, a 9.7× exceedance). This study provides new spatial evidence of Cr and Cd migration into deep aquifers of Kaduna Metropolis, demonstrating that toxic metal pollution is not confined to shallow water sources and necessitates urgent advanced treatment interventions.

This study explores the unique characteristics of talc ore sourced from the Ingawa Local Government Area in Katsina State, with a focus on its potential for diverse industrial applications. Representative samples were analysed using X-ray Fluorescence (XRF), X-ray Diffraction (XRD), and Fourier Transform Infrared (FTIR) spectroscopy to determine elemental composition, mineralogical phases, and structural bonding. XRD analysis confirmed that the ore is a heterogeneous assemblage dominated by Talc (triclinic), with significant amounts of quartz and kaolinite. XRF analysis quantified the chemical composition, revealing deviations from stoichiometric purity, with high silica (SiO2, 37.23%) and aluminium oxide (Al2O3, 26.41%) content. Magnesium oxide (MgO) concentration was found to be (0.91%), which is lower than the theoretical standard for pure Talc of 31.8%. Iron oxide Fe2O3 was present at 10.99%, correlating with the observed light-to-dark brown coloration of the samples. A comparative assessment against industrial specifications indicates that the Ingawa deposit is low-to-medium grade. While the high quartz and iron content currently restricts its use in pharmaceuticals and cosmetics, the raw ore is technically feasible for use as a structural filler in the rubber and plastics industries. Advanced beneficiation, specifically to reduce abrasive silica and chromophoric iron oxides, is recommended to upgrade the ore for high-value applications.

In this study, 240 juvenile Clarias gariepinus fish fed three locally manufactured fish feeds (F2, F3, and F4) as well as a foreign feed (F1) were examined for growth performance and nutrient consumption. Three treatments and a control were administered in triplicate during the twelve (12) week investigation, which used a completely randomized design. Water samples and morphometric measurements were collected biweekly. The objectives of this study were to determine the growth performance, nutrient consumption, survival rate, and cost-effectiveness of C. gariepinus fed three locally produced fish feeds and a foreign feed. The findings showed that the temperature, dissolved oxygen, and pH of the water were all within the permissible range. From the feeding trials, it was observed that all samples utilized the trial diets effectively. Nonetheless, the fish given F1 gained the most weight (185.73g), followed by F2 (170.24g), F4 (166.46 g), and F3 (149.17 g). There was no discernible difference (p>0.05) in the fish's weight growth after consuming various feeds. The SGR showed no significant difference, where F3-fed fish had the lowest specific growth rate (3.27), whereas F4, F2 and F1-fed fish had 3.39g, 3.44g and 3.53g, respectively. Fish fed F3 had the highest survival rate (93.33%), while fish fed F4 had the lowest (88.33%). However, fish fed F1 had the highest feed conversion ratio (1.42), while fish fed F2 had the lowest (1.29). Significant difference was not observed in FCR and survival rate (p>0.05) across fish that were fed various feeds. Despite fish fed F1 having the highest SGR (3.53), it had the lowest net profit (₦−87.45), whereas F4 yielded the highest net profit (₦80.41, p<0.05) followed by F2 (₦11.6) and F3 (₦4.75). This study revealed that although the foreign feed (F1) had the best growth performance and nutrient utilization, locally manufactured feeds can be more profitable for fish farmers because they are lower in cost than foreign feeds.

Tumour neoantigens, which are products of tumour-specific mutations, are ideal targets for cancer immunotherapy because they are highly specific and have the potential to elicit a robust T-cell response. Nevertheless, clinical translation of neoantigen-based therapy is not uniform, and systematic analysis of the discovery, validation, and implementation plans is required. A systematic literature search was conducted across PubMed, Scopus, Web of Science, Google Scholar, and Embase in July, 2025, to identify articles on neoantigen discovery and clinical use. In accordance with the PRISMA, 20 studies were included. Among the 20 original papers, 65% (13/20) were based on computational prediction, and only 35% (7/20) contained experimental validation, such as mass spectrometry-based immunopeptidomics or cell-based T-cell assays. Some studies used clinical translation, most of which used personalised vaccines and T-cell therapies, and, in some cases, immune checkpoint inhibitors. A high level of technological heterogeneity and inconsistent accuracy in neoantigen prioritisation were identified as critical limitations to clinical reliability. Neoantigen-based immunotherapy (immunotherapy) presents a high potential, but it is limited by the inaccuracy of predictions and low levels of validation. To enhance the chances of a successful translation, we suggest incorporating immunopeptidomics regularly, implementing AI-based models, expanding the global HLA sample, accelerating the manufacturing process, and standardising validation pipelines.

Groundwater is the primary source of domestic water in Kano Metropolis, yet its quality is increasingly threatened by rapid urbanization and anthropogenic activities. This study evaluated the spatiotemporal variation in groundwater quality using systematic sampling and multivariate statistical approaches. Forty-eight water samples (24 boreholes and 24 wells) were purposely collected across eight Local Government Areas during dry and wet seasons (feb-sept 2023). Physicochemical parameters were analyzed in line with WHO standards. Results indicated significant seasonal differences, with higher contamination observed during the dry season. Chloride concentrations peaked at 579.38 mg L⁻¹, turbidity at 8.01 NTU, and total dissolved solids (TDS) at 538 mg L⁻¹, both exceeding WHO permissible limits and posing potential risks of salinity-related health effects. Principal Component Analysis (PCA) identified four key factors explaining 76.1% of the total variance, attributed to salinity and mineralization, carbonate buffering, organic contamination, and sulphate enrichment. Agglomerative Hierarchical Clustering (AHC) distinguished boreholes, which showed relative stability, from wells, which were highly susceptible to surface contamination. Hydrochemical facies plots from Piper diagrams revealed dominance of Ca–Mg–SO₄–Cl and Ca–Mg–Cl–SO₄ water types, reflecting both geogenic and anthropogenic influences. The findings demonstrate that groundwater in Kano is vulnerable to deterioration from industrial effluents, poor sanitation, and unregulated land-use practices. To mitigate contamination risks, the study recommends an integrated groundwater management strategy that includes continuous monitoring, stricter waste disposal regulations, improved well and borehole siting, and community education on water safety. These interventions are critical to ensuring long-term groundwater sustainability and safeguarding public health in the metropolis

The aromatic grass Cymbopogon citratus, commonly known as lemongrass, has traditionally been used for its medicinal properties and is now receiving heightened scientific and commercial attention for its applications in therapeutics, food flavoring, cosmetics, and agro-industrial products. This review synthesizes data from over 30 studies that focused on four critical aspects: (i) the pharmacological properties of C. citratus, (ii) the bioavailability and pharmacokinetics of its active constituents, (iii) formulation strategies to address stability, delivery, and utility challenges, and (iv) commercialization obstacles such as production, regulation, and market acceptance. The report indicates that C. citratus exhibited potent antimicrobial activity with MIC values ranging from 12.5 µg/mL to 100 mg/mL, antioxidant activity with IC50 values from 15.13 µg/mL to 4.05 mg/mL, and anti-inflammatory activity with IC50 values ranging from 50 µg/ to 750 mg/Kg. These pharmacological properties are attributed to the major bioactive compounds, including citral, caryophyllene, and myrcene. Pharmacokinetic studies indicate that citral and myrcene undergo rapid absorption, significant metabolism, and are eliminated through urine and other bodily fluids. Research in formulation has focused on enhancing the bioavailability of C. citratus essential oils (EOs) through the application of microencapsulation, solid lipid nanoparticles, and nanoemulsions to improve stability. While the plant has shown promising efficacy, the path to commercialisation faces several challenges, including variable raw material quality, regulatory scrutiny, and competition from synthetic alternatives. This review concludes with an examination of the potential of C. citratus in both therapeutic and commercial sectors. Despite promising pre-clinical data, a significant lack of clinical trials and mechanistic studies remains the primary barrier to therapeutic application.

The digital divide and the potential of digital technologies in facilitating adaptive learning and inclusive education for individuals with disabilities have been widely studied, noting unequal access to education by this vulnerable group. However, little research has explored the consequences of digital exclusion and over-dependence on digital technologies for inclusive education of students with disabilities in developing countries with limited technology infrastructure, such as Nigeria. It is on this premise that this study reviews existing work on the state of digital exclusion faced by students with disabilities and whether it bridges these gaps. To achieve this, a literature review was conducted to identify relevant sources for the study through searches in databases such as Google, Google Scholar, Scopus, Web of Science, and Wiley Online Library. A total of 182 literature sources were identified and retrieved from these databases. After screening, 24 literature sources that strictly focused on digital inclusion, the state of digital technology inclusion for individuals with disabilities, assistive learning technologies, and Challenges of inclusive education in Nigeria, met the criteria for inclusion and were included in the study. Accordingly, Universal Design Learning (UDL) and Relative Deprivation Theory (RDT) were employed to guide this study. The review analysis exposed inadequacies in assistive technology tools, limited access to other emerging technologies, insufficient digital skills, and a lack of political will to implement education policies for people with disabilities in Nigerian education practices. A practice that further exacerbates existing exclusion gaps in equitable access to quality education by students with disabilities.

Leptospirosis is a zoonotic disease with a worldwide occurrence cause by the bacterial spirochete Leptospira. Many wild and domestic animals, including dogs, shed Leptospira in their urine and serve as sources of human infection, either directly or indirectly. The study aimed to investigate anti-Leptospira IgG antibodies among dog handlers. Blood samples were collected (in September to November, 2018) from 143 participants into plain EDTA bottles, sera were separated by centrifugation and harvested into cryovials using a sterile pipette. Demographic data for the research subjects were collected using a structured questionnaire. The detection of anti-Leptospira IgG antibodies was achieved using Diagnostic Automation Inc. (DAI) ELISA Kit USA, with 100/100 reported sensitivity/specificity. The study found prevalences of 47.8% (95% CI: 37.5–58.1) in Jos South and 54.7% (95% CI: 41.4–68.0) in Kanke LGAs. None of the sociodemographic factors were significantly associated with Leptospira IgG seropositivity on univariate analysis; however, after adjusting for confounders, occupation showed a significant association with Leptospira antibodies in the multivariable logistic regression model (p = 0.021 overall). Seropositivity to Leptospira antibodies appeared higher among veterinary practitioners (72.7%) at 95% CI (53.0–92.0) than other dog handlers, but not statistically significant (p=0.070). Additional methods, such as the microscopic agglutination test (MAT), IgM ELISA (for paired sera samples), and PCR, are needed to establish active Leptospira infection. Further studies that consider both dogs and their handlers are recommended to definitively establish the role of dogs in such a high prevalence.