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Research Article
Maximum Discharge of Lateral Pipes in Sewage Flow
Reuben Wambugu Mwangi,
Mathew Ngugi Kinyanjui,
Phineas Roy Kiogora*
Issue:
Volume 14, Issue 1, February 2025
Pages:
1-11
Received:
20 November 2024
Accepted:
3 December 2024
Published:
2 January 2025
DOI:
10.11648/j.acm.20251401.11
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Abstract: Rapid growth and population increase in urban centers has led to unplanned and rushed construction of buildings and amenities. This has led to poor development of sewer intakes from the buildings to the main sewer line. Therefore sewer blockage and low velocity of the sludge have been witnessed. The aim of this study is to investigate on how to achieve a maximum discharge of the lateral pipes into the main sewer line both from buildings and service (streets) sewer lines. This is achieved when sewerage system discharge is determined by the size of the sewer pipe used, effective inflow into the main sewer (linkages), slope (excavation depth) and distance between manhole. The governing equations for the flow are equation of continuity, momentum equations, energy equation and concentration equation. The nonlinear partial differential equations are transformed to ordinary differential equations , then solved numerically using the Collocation Method using an inbuilt MATLAB library known as Bvp4c. Velocity profiles, temperature profiles and the concentration profiles obtained are analyzed and discussed on how they affect the maximum discharge of sewer flow. Flow parameters are varied and their effect on the flow variables are determined and discussed. This study has remarkable applications in designing of the water, sanitation and sewer systems. This will reduce outbreak of diseases such as cholera, typhoid and enhance clean water and environment.
Abstract: Rapid growth and population increase in urban centers has led to unplanned and rushed construction of buildings and amenities. This has led to poor development of sewer intakes from the buildings to the main sewer line. Therefore sewer blockage and low velocity of the sludge have been witnessed. The aim of this study is to investigate on how to ach...
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Research Article
A State Estimation H∞ Issue for Continuous-Time Impulsive Genetic Regulatory Networks with Random Delays Via Sampled-Data Approach
Pandiselvi Selvakumar,
Meenakshi Ramachandran*
Issue:
Volume 14, Issue 1, February 2025
Pages:
12-22
Received:
20 October 2024
Accepted:
20 November 2024
Published:
3 January 2025
DOI:
10.11648/j.acm.20251401.12
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Views:
Abstract: This paper addresses the state-estimation H∞ problem for continuous-time impulsive genetic regulatory networks (GRNs) with random delays, using a sampled-data approach. Genetic regulatory networks are fundamental in controlling gene expression and protein synthesis, governed by regulatory interactions between transcription factors and mRNA (Messenger Ribonucleic Acid) binding sites. To estimate mRNA and protein concentrations, sampled measurements replace continuous measurements in this framework. We propose a new model that leverages impulsive control strategies to regulate mRNA and protein dynamics under conditions with random delays. The primary contribution of this study is the derivation of sufficient conditions that guaranteeing that impulsive genetic regulatory networks is globally asymptotically stable is derived. By introducing a discontinuous Lyapunov- Krasovskii functional, sufficient stability analysis has been rooted in terms of LMIs: Linear Matrix Inequalities. By applying Wirtinger inequality technique, conservation of the impulsive GRNs system is globally asymptotically stable in the mean- square sense have been diminished greatly. Eventually, a numerical example is given to the feasibility and advantages of the developed results.
Abstract: This paper addresses the state-estimation H∞ problem for continuous-time impulsive genetic regulatory networks (GRNs) with random delays, using a sampled-data approach. Genetic regulatory networks are fundamental in controlling gene expression and protein synthesis, governed by regulatory interactions between transcription factors and mRNA (Messeng...
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Research Article
Advancing Measurement Error Correction: A Systematic Review and Meta-Analysis of Hierarchical Bayesian Semi-Parametric Models
Issue:
Volume 14, Issue 1, February 2025
Pages:
23-36
Received:
18 July 2024
Accepted:
13 August 2024
Published:
14 January 2025
DOI:
10.11648/j.acm.20251401.13
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Abstract: Data-driven research in various scientific fields has greatly enhanced understanding of complicated phenomena. However, the genuineness and dependability of such an insight depends significantly on the quality of the data collected. Measurement error is a ubiquitous challenge present in all sciences, which makes the measured values differ from real ones. Such discrepancies might distort results strongly; therefore inferences may be false leading to wrong policy or optimal fertilizer recommendations levels. Consequently, researchers have been caught up in finding out workable solutions to these errors that may have far-reaching effects. Out of many approaches that have been suggested by different practitioners, Hierarchical Bayesian semi-parametric (HBSP) models assume a unique position as an effective tool for this purpose. These models are solidly grounded on Bayesian statistical paradigms and combine both parametric and non-parametric techniques which endows them with flexibility to adapt to any type of data structures and patterns of errors. This adaptability is particularly important given that measurement errors can emanate from diverse sources including instrument inaccuracies, observer biases, and environmental fluctuations since they are multi-faceted. However, even though their effectiveness has been proven, HBSP models are not widely used and only applied in certain specialized contexts. This gap between potential and actual use deserves careful examination. This Systematic review is a survey of studies and meta –analysis on the use of HBSP models in measurement error correction. It examines scholarly works that have tested this theory, indicate where it may be useful outside specific contexts and compare its competence with other ways of correcting errors. Therefore, this study seeks to broaden the application of HBSP models to improve scientific findings through reducing persistent errors in measurements.
Abstract: Data-driven research in various scientific fields has greatly enhanced understanding of complicated phenomena. However, the genuineness and dependability of such an insight depends significantly on the quality of the data collected. Measurement error is a ubiquitous challenge present in all sciences, which makes the measured values differ from real...
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Research Article
An Age-stratified Mathematical Model for Human Immunodeficiency Virus and Tuberculosis Co-infection with Optimal Control
Issue:
Volume 14, Issue 1, February 2025
Pages:
37-63
Received:
17 December 2024
Accepted:
2 January 2025
Published:
14 January 2025
DOI:
10.11648/j.acm.20251401.14
Downloads:
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Abstract: One significant risk factor that is considered to contribute to Kenya’s TB burden is HIV. TB is one of the most common opportunistic infections associated with HIV, and HIV infection increases the risk of developing active TB disease in individuals with latent TB infection. Due to their compromised immune systems, increased susceptibility to TB infection and latent TB reactivation, people with HIV have a higher probability of attaining TB. This study develops an age-stratified mathematical model with optimal control for co-infection of HIV and TB. The model’s reproduction number, as well as the equilibrium of endemic and disease-free states have been computed. Least Squares technique of minimization has be used to determine the model parameters. HIV antiretroviral therapy treatment adherence and tuberculosis treatment have been considered for optimization. Runge-Kutta 𝒪(h4) has been used to solve the system differential equations for its high accuracy and flexibility. Results from the numerical simulations show that ART adherence is the best intervention to control the co-infection in its earlier stages (HIV and latent TB). TB treatment is the best intervention for those affected with the coinfection on the later stage (HIV and active TB). Considering viral load suppression and TB prevention, viral load suppression is most effective for children and TB prevention is most effective for adults. The results of this research can be used by the Ministry of Health (MOH) for emphasis on most effective interventions as well as a basis study tool that can be recreated for other co-infections.
Abstract: One significant risk factor that is considered to contribute to Kenya’s TB burden is HIV. TB is one of the most common opportunistic infections associated with HIV, and HIV infection increases the risk of developing active TB disease in individuals with latent TB infection. Due to their compromised immune systems, increased susceptibility to TB inf...
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,
Samuel Musili Mwalili
