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Abstract Slug liquid holdup (SLH) is a critical requirement for accurate pressure drop prediction during multiphase pipe flows and by extension optimal gas lift design and production optimization in wellbores. Existing empirical correlations provide inaccurate predictions because they were developed with regression analysis and data measured for limited ranges of flow conditions. Existing SLH machine learning models provide accurate predictions but are published without any equations making their use by other researchers difficult. The only existing ML model published with actual equations cannot be considered optimum because it was selected by considering artificial neural network (ANN) structures with only one hidden layer. In this study, an ANN-based model for SLH prediction with actual equations is presented. A total of 2699 data points randomly divided into 70%, 15%, and 15% for training, validation, and testing was used in constructing 71 different network structures with 1, 2, and 3 hidden layers respectively. Sensitivity analysis revealed that the optimum network structure has 3 hidden layers with 20, 5, and 15 neurons in the first, second, and third hidden layers, respectively. The optimum network structure was translated into actual equations with the aid of the weights, biases, and activation functions. Trend analysis revealed that this study’s model reproduced the expected effects of inputs on SLH. Test against measured data revealed that this study’s model is in agreement with measured data with coefficient of determinations of 0.9791, 0.9727, 0.9756, and 0.9776 for training, testing, validation, and entire datasets, respectively. Comparative study revealed that this study’s model outperformed existing models with a relative performance factor of 0.002. The present model is presented with visible mathematical equations making its implementation by any user easy and without the need for any ML framework. Unlike existing ANN-based models developed with one hidden layered ANN structures, the present model was developed by considering ANN structures with one, two, and three hidden layers, respectively.

Sustainability of domestic water access in communities is essential for good health, society’s dignity and progress. This study investigated the sources and functionality of rural water supply in nine communities of three local government area (LGA) in three senatorial zones of Imo State, Nigeria using structured questionnaires. The questionnaires were administered on 100 women in each community. Data obtained were analysed using multivariate analysis of variance (MANOVA) to reveal the frequency of using the various sources of rural water supply, and Wilcoxon’s test for matched pairs to reveal the functionality status of the most frequently used water source. The findings indicate the importance of borehole water facilities in these rural communities and the necessity for intervention programs to strengthen their functionality in tandem with the State’s aspirations in achieving sustainable development goals.

Wastewater volume is a necessary prerequisite for planning transformation to valuable resource and averting environmental degradation. This study investigated the dynamics of POME volume generation in palm oil mills in relation to types of fresh fruit bunches (FFBs), seasons, milling scales and volume of crude palm oil (CPO) produced in ADAPALMS and catchment communities, Ohaji/Egbema LGA, Imo State. The eight catchment communities of ADAPALMS were categorised into three strata in relation to the number of small-scale mills in each community (1-5mills, 6-10mills, and 11-15mills). In each stratum, a community was randomly sampled. A total of nine small-scale mills were sampled from the three sampled communities (Ohoba, Amafor and Etekwuru) in proportion to the average number of mills in each stratum. The lone medium and large scale mill (ADAPLAMS) in the study area represented the other scales of milling. For small and medium scale mills, the volume of POME generated was measured from the dimensions of the vessels where POME was stored, while that of large scale mill was obtained from industrial records. Data was analysed using multiple linear regression of SPSS. The volume of POME generated is significantly related to milling scales and volume of CPO produced (p< 0.01); R2=0.788. Within small scale mills, the volume of POME is significantly related to types of FFBs (p< 0.01), different small milling scales (p< 0.05), and volume of CPO produced (p< 0.01); R2=0.762. Thus, these independent variables are the principal determinants of POME volume generation in the area. The result has implication on the necessity of predictive models in managing the dynamics of POME volumes for efficient recovery and transformation of the wastewater to bioenergy.

Background: Africa has the highest prevalence of hypertension at 46%. Schoolteachers are vulnerable to hypertension due to work-related and general risk factors. Identifying these factors is key to providing interventions., Aim: This study aimed to determine the prevalence of hypertension and associated factors among schoolteachers in Calabar, Nigeria., Methods: This was a cross-sectional study of 427 randomly selected schoolteachers who were recruited through a multistage sampling technique. Questionnaires were self-administered, and blood pressure measurements were done. Data analysis was done using Statistical Package for the Social Sciences (SPSS) version 20. A binary logistic regression analysis was used to determine factors associated with hypertension at a 5% significance level., Results: The mean age of the participants was 38 ± 9 years, and 65% of them were females. The prevalence of hypertension was 32%. The adjusted model showed that age and body mass index (BMI) were significantly associated with hypertension. The teachers in the 30-39 (adjusted odds ratio [aOR] = 2.63, 95% confidence interval [CI]: 0.93-7.43, P = 0.07), 40-49 (aOR = 6.27, 95% CI: 2.08-18.91, P < 0.01), and ≥50 (aOR = 7.95, 95% CI: 2.24-28.20, P < 0.01) year age categories had increased odds of being hypertensive than those in the 20-29-year-old age group. Those who were overweight (aOR = 2.63, 95% CI: 1.52-4.57, P < 0.01) or obese (aOR = 2.15, 95% CI: 1.21-3.85, P = 0.01) had two-fold increased odds of having hypertension compared with those who had normal weight., Conclusions: Increasing age and BMI are risk factors for hypertension in this study. Health interventions should focus on weight control, especially among older teachers., (Copyright © 2024 Copyright: © 2024 Nigerian Journal of Clinical Practice.)