Pub Date : 2024-01-08DOI: 10.3389/fams.2023.1260651
I. T. Daba, Wondwosen Gebeyaw Melesse, Guta Demisu Kebede
This study deals with a fitted third-degree B-spline collocation method for two parametric singularly perturbed parabolic problems with a time lag. The proposed method comprises the Cranck-Nicolson method for time discretization and the third-degree B-spline method spatial variable discretization. Rigorous numerical experimentations were carried out on some test examples. The obtained numerical results depict that the proposed scheme is more accurate than some methods existing in the literature. Parameter convergence analysis of the scheme is carried out and shows the present scheme is (ε−μ)−uniform convergent with the order of convergence ((Δt)2 + ℓ2).
本研究针对两个具有时滞的参数奇异扰动抛物问题，提出了一种拟合的三度 B 样条配位法。提出的方法包括时间离散的 Cranck-Nicolson 法和空间变量离散的三度 B 样条法。对一些测试实例进行了严格的数值实验。所获得的数值结果表明，所提出的方案比文献中已有的一些方法更加精确。对方案进行了参数收敛分析，结果表明本方案是 (ε-μ) 均匀收敛的，收敛阶数为 ((Δt)2 + ℓ2) 。
{"title":"Third-degree B-spline collocation method for singularly perturbed time delay parabolic problem with two parameters","authors":"I. T. Daba, Wondwosen Gebeyaw Melesse, Guta Demisu Kebede","doi":"10.3389/fams.2023.1260651","DOIUrl":"https://doi.org/10.3389/fams.2023.1260651","url":null,"abstract":"This study deals with a fitted third-degree B-spline collocation method for two parametric singularly perturbed parabolic problems with a time lag. The proposed method comprises the Cranck-Nicolson method for time discretization and the third-degree B-spline method spatial variable discretization. Rigorous numerical experimentations were carried out on some test examples. The obtained numerical results depict that the proposed scheme is more accurate than some methods existing in the literature. Parameter convergence analysis of the scheme is carried out and shows the present scheme is (ε−μ)−uniform convergent with the order of convergence ((Δt)2 + ℓ2).","PeriodicalId":36662,"journal":{"name":"Frontiers in Applied Mathematics and Statistics","volume":"34 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139447844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-05DOI: 10.3389/fams.2023.1328537
Ronald Wesonga, M. M. Islam, Iman Al Hasani, Afra Al Manei
The study sought to compare two-item response theory (IRT) models, the Rasch and 2PL models, and to uncover insights on COVID-19 knowledge and attitude item difficulty and discrimination among university students. We premise this study on ITM to argue that logical flow, degree of difficulty, and discrimination of items for the constructs among respondents contribute to the validity and quality of statistical inferences. The developed Rasch and 2PL models are compared to determine the difficulty and discrimination of knowledge and attitude items, with an application to COVID-19. Our results show that although the Rasch and 2PL models provide rich diagnostic tools to understand multiple traits, the 2PL model provides more robust results for the assessment of knowledge and attitude of students about the COVID-19 epidemic. Moreover, of the two constructs, the items for the attitude construct recieved more reliable responses than the knowledge construct items. Accordingly, under any pandemic, the lack of proper and evolving knowledge could have dire consequences; hence, strict efforts should be made while designing knowledge items.
{"title":"Item response theory to discriminate COVID-19 knowledge and attitudes among university students","authors":"Ronald Wesonga, M. M. Islam, Iman Al Hasani, Afra Al Manei","doi":"10.3389/fams.2023.1328537","DOIUrl":"https://doi.org/10.3389/fams.2023.1328537","url":null,"abstract":"The study sought to compare two-item response theory (IRT) models, the Rasch and 2PL models, and to uncover insights on COVID-19 knowledge and attitude item difficulty and discrimination among university students. We premise this study on ITM to argue that logical flow, degree of difficulty, and discrimination of items for the constructs among respondents contribute to the validity and quality of statistical inferences. The developed Rasch and 2PL models are compared to determine the difficulty and discrimination of knowledge and attitude items, with an application to COVID-19. Our results show that although the Rasch and 2PL models provide rich diagnostic tools to understand multiple traits, the 2PL model provides more robust results for the assessment of knowledge and attitude of students about the COVID-19 epidemic. Moreover, of the two constructs, the items for the attitude construct recieved more reliable responses than the knowledge construct items. Accordingly, under any pandemic, the lack of proper and evolving knowledge could have dire consequences; hence, strict efforts should be made while designing knowledge items.","PeriodicalId":36662,"journal":{"name":"Frontiers in Applied Mathematics and Statistics","volume":"79 21","pages":""},"PeriodicalIF":1.4,"publicationDate":"2024-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139381577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-04DOI: 10.3389/fams.2023.1346541
Bapan Ghosh, S. Djilali, A. Supriatna
{"title":"Editorial: Justified modeling frameworks and novel interpretations of ecological and epidemiological systems","authors":"Bapan Ghosh, S. Djilali, A. Supriatna","doi":"10.3389/fams.2023.1346541","DOIUrl":"https://doi.org/10.3389/fams.2023.1346541","url":null,"abstract":"","PeriodicalId":36662,"journal":{"name":"Frontiers in Applied Mathematics and Statistics","volume":"11 2","pages":""},"PeriodicalIF":1.4,"publicationDate":"2024-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139386723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-04DOI: 10.3389/fams.2023.1286914
Beza Zeleke Aga, T. Keno, Debela Etefa Terfasa, Hailay Weldegiorgis Berhe
In this study, we present a nonlinear deterministic mathematical model for co-infection of pneumonia and COVID-19 transmission dynamics. To understand the dynamics of the co-infection of COVID-19 and pneumonia sickness, we developed and examined a compartmental based ordinary differential equation type mathematical model. Firstly, we showed the limited region and non-negativity of the solution, which demonstrate that the model is biologically relevant and mathematically well-posed. Secondly, the Jacobian matrix and the Lyapunov function are used to illustrate the local and global stability of the equilibrium locations. If the related reproduction numbers R0c, R0p, and R0 are smaller than unity, then pneumonia, COVID-19, and their co-infection have disease-free equilibrium points that are both locally and globally asymptotically stable otherwise the endemic equilibrium points are stable. Sensitivity analysis is used to determine how each parameter affects the spread or control of the illnesses. Moreover, we applied the optimal control theory to describe the optimal control model that incorporates four controls, namely, prevention of pneumonia, prevention of COVID-19, treatment of infected pneumonia and treatment of infected COVID-19. Then the Pontryagin's maximum principle is introduced to obtain the necessary condition for the optimal control problem. Finally, the numerical simulation of optimality system reveals that the combination of treatment and prevention is the most optimal to minimize the diseases.
{"title":"Pneumonia and COVID-19 co-infection modeling with optimal control analysis","authors":"Beza Zeleke Aga, T. Keno, Debela Etefa Terfasa, Hailay Weldegiorgis Berhe","doi":"10.3389/fams.2023.1286914","DOIUrl":"https://doi.org/10.3389/fams.2023.1286914","url":null,"abstract":"In this study, we present a nonlinear deterministic mathematical model for co-infection of pneumonia and COVID-19 transmission dynamics. To understand the dynamics of the co-infection of COVID-19 and pneumonia sickness, we developed and examined a compartmental based ordinary differential equation type mathematical model. Firstly, we showed the limited region and non-negativity of the solution, which demonstrate that the model is biologically relevant and mathematically well-posed. Secondly, the Jacobian matrix and the Lyapunov function are used to illustrate the local and global stability of the equilibrium locations. If the related reproduction numbers R0c, R0p, and R0 are smaller than unity, then pneumonia, COVID-19, and their co-infection have disease-free equilibrium points that are both locally and globally asymptotically stable otherwise the endemic equilibrium points are stable. Sensitivity analysis is used to determine how each parameter affects the spread or control of the illnesses. Moreover, we applied the optimal control theory to describe the optimal control model that incorporates four controls, namely, prevention of pneumonia, prevention of COVID-19, treatment of infected pneumonia and treatment of infected COVID-19. Then the Pontryagin's maximum principle is introduced to obtain the necessary condition for the optimal control problem. Finally, the numerical simulation of optimality system reveals that the combination of treatment and prevention is the most optimal to minimize the diseases.","PeriodicalId":36662,"journal":{"name":"Frontiers in Applied Mathematics and Statistics","volume":"15 9","pages":""},"PeriodicalIF":1.4,"publicationDate":"2024-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139387203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-03DOI: 10.3389/fams.2023.1250227
Mohammad Salem Oudat, Basel J. A. Ali, Sameh Abdelhay, H. M. Hazaimeh, Mohamed Saif Rashid Altalay, Attiea Marie, Magdi El-Bannany
Risk management has emerged as a critical element across several economic sectors, with particular significance in the banking industry. The governing bodies of these industries encounter a multitude of threats stemming from the escalation of an unpredictable economic environment, the intricacy of transactions and big data, and several other concealed factors. The primary aim of the present research is to investigate the impact of certain financial risks, including capital risk, liquidity risk, and operational risk, on the financial performance of both commercial and Islamic banks operating within the banking sector of the United Arab Emirates. The study will focus on the time frame spanning from 2015 to 2022. The data used in this study was sourced from the annual reports of banks, which were acquired from the official websites of the Abu Dhabi Securities Exchange and the Dubai stock market. The most prevalent indicators used to assess a bank's financial performance are Return on Assets (ROA) and Return on Equity (ROE). In contrast, the financial risk metrics included three distinct categories of risk: capital risk, liquidity risk, and operational risk. The findings indicate that there is a statistically significant positive relationship between capital risk and both return on assets (ROA) and return on equity (ROE). However, it was observed that neither liquidity risk nor operational risk had a statistically significant impact on either of the financial performance metrics. Moreover, the size of a bank has a notable and favorable impact on both return on assets (ROA) and return on equity (ROE). The ramifications of the study's conclusions have significant importance for regulators, bank management, and investors. IPolicymakers need to prioritize the enhancement of the regulatory framework pertaining to caboutements in order to the financial stability of banks. Bank managers should give priority to the management of capital risk and the size of the bank in order to their financial performance. In order to optimize profits, it is important for investors to carefully evaluate and take into account the many risk considerations associated with their investment selections.G20, G21
{"title":"The effect of financial risks on the performance of Islamic and commercial banks in UAE","authors":"Mohammad Salem Oudat, Basel J. A. Ali, Sameh Abdelhay, H. M. Hazaimeh, Mohamed Saif Rashid Altalay, Attiea Marie, Magdi El-Bannany","doi":"10.3389/fams.2023.1250227","DOIUrl":"https://doi.org/10.3389/fams.2023.1250227","url":null,"abstract":"Risk management has emerged as a critical element across several economic sectors, with particular significance in the banking industry. The governing bodies of these industries encounter a multitude of threats stemming from the escalation of an unpredictable economic environment, the intricacy of transactions and big data, and several other concealed factors. The primary aim of the present research is to investigate the impact of certain financial risks, including capital risk, liquidity risk, and operational risk, on the financial performance of both commercial and Islamic banks operating within the banking sector of the United Arab Emirates. The study will focus on the time frame spanning from 2015 to 2022. The data used in this study was sourced from the annual reports of banks, which were acquired from the official websites of the Abu Dhabi Securities Exchange and the Dubai stock market. The most prevalent indicators used to assess a bank's financial performance are Return on Assets (ROA) and Return on Equity (ROE). In contrast, the financial risk metrics included three distinct categories of risk: capital risk, liquidity risk, and operational risk. The findings indicate that there is a statistically significant positive relationship between capital risk and both return on assets (ROA) and return on equity (ROE). However, it was observed that neither liquidity risk nor operational risk had a statistically significant impact on either of the financial performance metrics. Moreover, the size of a bank has a notable and favorable impact on both return on assets (ROA) and return on equity (ROE). The ramifications of the study's conclusions have significant importance for regulators, bank management, and investors. IPolicymakers need to prioritize the enhancement of the regulatory framework pertaining to caboutements in order to the financial stability of banks. Bank managers should give priority to the management of capital risk and the size of the bank in order to their financial performance. In order to optimize profits, it is important for investors to carefully evaluate and take into account the many risk considerations associated with their investment selections.G20, G21","PeriodicalId":36662,"journal":{"name":"Frontiers in Applied Mathematics and Statistics","volume":"3 5","pages":""},"PeriodicalIF":1.4,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139451469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-03DOI: 10.3389/fams.2023.1282975
J. M. Chen, Nika Šimurina, Martina Solenički
This article analyzes the impact of tax policy on income inequality in the European Union (EU). Each EU member-state has adopted a distinct set of fiscal policies. Although most member-states have coordinated their tax systems to promote economic growth, EU countries hold politically divergent views about income inequality and the power of taxation to redress inequality. This research applies linear regression methods incorporating regularization as well as fixed and random effects. Stacking generalization produces a composite model that dramatically improves predictive accuracy while aggregating causal inferences from simpler models. Social contributions, income taxes, and consumption taxes ameliorate inequality. Government spending, however, exacerbates inequality.
{"title":"Le rouge, le noir, et l'inégalité: tax policy and inequality in the European Union","authors":"J. M. Chen, Nika Šimurina, Martina Solenički","doi":"10.3389/fams.2023.1282975","DOIUrl":"https://doi.org/10.3389/fams.2023.1282975","url":null,"abstract":"This article analyzes the impact of tax policy on income inequality in the European Union (EU). Each EU member-state has adopted a distinct set of fiscal policies. Although most member-states have coordinated their tax systems to promote economic growth, EU countries hold politically divergent views about income inequality and the power of taxation to redress inequality. This research applies linear regression methods incorporating regularization as well as fixed and random effects. Stacking generalization produces a composite model that dramatically improves predictive accuracy while aggregating causal inferences from simpler models. Social contributions, income taxes, and consumption taxes ameliorate inequality. Government spending, however, exacerbates inequality.","PeriodicalId":36662,"journal":{"name":"Frontiers in Applied Mathematics and Statistics","volume":"35 3","pages":""},"PeriodicalIF":1.4,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139389149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-03DOI: 10.3389/fams.2023.1146776
Álvaro Saiz-Sepúlveda, Carmen Orden-Cruz, Álvaro Hernández-Tamurejo
A retrospective view of the “subprime mortgage” crisis enables us to assess the actions of banks, both those prompting the genesis of the crisis and those resulting from subsequent actions aimed at resolving it and rebooting the economy. However, given the fact that the crisis is framed by the sudden appearance of another outside the established parameters of the post-recession boom, we are able to analyze whether the actions adopted by regulators were as effective as initially thought. Solvency and profitability are two of the most important factors that reveals the quality of banking management. From the numerous parameters described in the literature reviewed, fourth banking ratios were selected to evaluate the relationship between solvency and profitability from 2011 to 2021, a period between the two economic-financial crises of the 21st century. Using a representative sample of Spanish banking and applying a descriptive and explicative methodology, the results show a complementarity between solvency and profitability. This evidence provides to bank managers more knowledge about the behavior of banking during crisis periods.
{"title":"Solvency and profitability: the duality of the large Spanish banks between the two economic-financial crises of the 21st century","authors":"Álvaro Saiz-Sepúlveda, Carmen Orden-Cruz, Álvaro Hernández-Tamurejo","doi":"10.3389/fams.2023.1146776","DOIUrl":"https://doi.org/10.3389/fams.2023.1146776","url":null,"abstract":"A retrospective view of the “subprime mortgage” crisis enables us to assess the actions of banks, both those prompting the genesis of the crisis and those resulting from subsequent actions aimed at resolving it and rebooting the economy. However, given the fact that the crisis is framed by the sudden appearance of another outside the established parameters of the post-recession boom, we are able to analyze whether the actions adopted by regulators were as effective as initially thought. Solvency and profitability are two of the most important factors that reveals the quality of banking management. From the numerous parameters described in the literature reviewed, fourth banking ratios were selected to evaluate the relationship between solvency and profitability from 2011 to 2021, a period between the two economic-financial crises of the 21st century. Using a representative sample of Spanish banking and applying a descriptive and explicative methodology, the results show a complementarity between solvency and profitability. This evidence provides to bank managers more knowledge about the behavior of banking during crisis periods.","PeriodicalId":36662,"journal":{"name":"Frontiers in Applied Mathematics and Statistics","volume":"4 3","pages":""},"PeriodicalIF":1.4,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139451411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-03DOI: 10.3389/fams.2023.1320177
Mohannad Alkanan, Yonis Gulzar
In the era of advancing artificial intelligence (AI), its application in agriculture has become increasingly pivotal. This study explores the integration of AI for the discriminative classification of corn diseases, addressing the need for efficient agricultural practices. Leveraging a comprehensive dataset, the study encompasses 21,662 images categorized into four classes: Broken, Discolored, Silk cut, and Pure. The proposed model, an enhanced iteration of MobileNetV2, strategically incorporates additional layers—Average Pooling, Flatten, Dense, Dropout, and softmax—augmenting its feature extraction capabilities. Model tuning techniques, including data augmentation, adaptive learning rate, model checkpointing, dropout, and transfer learning, fortify the model's efficiency. Results showcase the proposed model's exceptional performance, achieving an accuracy of ~96% across the four classes. Precision, recall, and F1-score metrics underscore the model's proficiency, with precision values ranging from 0.949 to 0.975 and recall values from 0.957 to 0.963. In a comparative analysis with state-of-the-art (SOTA) models, the proposed model outshines counterparts in terms of precision, recall, F1-score, and accuracy. Notably, MobileNetV2, the base model for the proposed architecture, achieves the highest values, affirming its superiority in accurately classifying instances within the corn disease dataset. This study not only contributes to the growing body of AI applications in agriculture but also presents a novel and effective model for corn disease classification. The proposed model's robust performance, combined with its competitive edge against SOTA models, positions it as a promising solution for advancing precision agriculture and crop management.
{"title":"Enhanced corn seed disease classification: leveraging MobileNetV2 with feature augmentation and transfer learning","authors":"Mohannad Alkanan, Yonis Gulzar","doi":"10.3389/fams.2023.1320177","DOIUrl":"https://doi.org/10.3389/fams.2023.1320177","url":null,"abstract":"In the era of advancing artificial intelligence (AI), its application in agriculture has become increasingly pivotal. This study explores the integration of AI for the discriminative classification of corn diseases, addressing the need for efficient agricultural practices. Leveraging a comprehensive dataset, the study encompasses 21,662 images categorized into four classes: Broken, Discolored, Silk cut, and Pure. The proposed model, an enhanced iteration of MobileNetV2, strategically incorporates additional layers—Average Pooling, Flatten, Dense, Dropout, and softmax—augmenting its feature extraction capabilities. Model tuning techniques, including data augmentation, adaptive learning rate, model checkpointing, dropout, and transfer learning, fortify the model's efficiency. Results showcase the proposed model's exceptional performance, achieving an accuracy of ~96% across the four classes. Precision, recall, and F1-score metrics underscore the model's proficiency, with precision values ranging from 0.949 to 0.975 and recall values from 0.957 to 0.963. In a comparative analysis with state-of-the-art (SOTA) models, the proposed model outshines counterparts in terms of precision, recall, F1-score, and accuracy. Notably, MobileNetV2, the base model for the proposed architecture, achieves the highest values, affirming its superiority in accurately classifying instances within the corn disease dataset. This study not only contributes to the growing body of AI applications in agriculture but also presents a novel and effective model for corn disease classification. The proposed model's robust performance, combined with its competitive edge against SOTA models, positions it as a promising solution for advancing precision agriculture and crop management.","PeriodicalId":36662,"journal":{"name":"Frontiers in Applied Mathematics and Statistics","volume":"106 16","pages":""},"PeriodicalIF":1.4,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139387918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-19DOI: 10.3389/fams.2023.1282544
Jemal Muhammed Ahmed, Getachew Teshome Tilahun, Shambel Tadesse Degefa
Malaria is an infectious disease caused by intracellular parasites of the genus Plasmodium. It is a major health problem around the world. In this study, a cell-level mathematical model of malaria parasites with antimalarial drug treatments is formulated and analyzed. The model consists of seven compartments for cell populations. We analyzed the qualitative behavior of the model using various techniques. The stability analysis of the parasite-free equilibrium is obtained, whereas it is locally and globally stable if the basic reproduction number R0<1. The parasite persistence equilibrium point exists, and it is locally asymptotically stable if R0>1. The sensitivity analysis of the basic reproduction number is computed, and the results show that the infection rate of the erythrocyte by merozoites, the average number of merozoites per ruptured infected erythrocyte cells, the natural death rate of merozoites, and the requirement rate of the uninfected erythrocyte are the most influential parameters within-host dynamics of malaria infection. Different numerical simulations are performed to supplement our analytical findings. The effect of primary tissue schizontocides, blood schizontocides, and gametocytocides on infected hepatocytes, infected erythrocytes, and gametocytes have been investigated, respectively. Finally, some counterplots are presented in order to investigate the impact of parameters on the basic reproduction number. The in-host basic reproduction number decreases as the antimalarial treatment administration increases. Therefore, increasing antimalarial treatment administration is the best way to mitigate the in-host malaria infection.
{"title":"A cell-level dynamical model for malaria parasite infection with antimalarial drug treatment","authors":"Jemal Muhammed Ahmed, Getachew Teshome Tilahun, Shambel Tadesse Degefa","doi":"10.3389/fams.2023.1282544","DOIUrl":"https://doi.org/10.3389/fams.2023.1282544","url":null,"abstract":"Malaria is an infectious disease caused by intracellular parasites of the genus Plasmodium. It is a major health problem around the world. In this study, a cell-level mathematical model of malaria parasites with antimalarial drug treatments is formulated and analyzed. The model consists of seven compartments for cell populations. We analyzed the qualitative behavior of the model using various techniques. The stability analysis of the parasite-free equilibrium is obtained, whereas it is locally and globally stable if the basic reproduction number R0<1. The parasite persistence equilibrium point exists, and it is locally asymptotically stable if R0>1. The sensitivity analysis of the basic reproduction number is computed, and the results show that the infection rate of the erythrocyte by merozoites, the average number of merozoites per ruptured infected erythrocyte cells, the natural death rate of merozoites, and the requirement rate of the uninfected erythrocyte are the most influential parameters within-host dynamics of malaria infection. Different numerical simulations are performed to supplement our analytical findings. The effect of primary tissue schizontocides, blood schizontocides, and gametocytocides on infected hepatocytes, infected erythrocytes, and gametocytes have been investigated, respectively. Finally, some counterplots are presented in order to investigate the impact of parameters on the basic reproduction number. The in-host basic reproduction number decreases as the antimalarial treatment administration increases. Therefore, increasing antimalarial treatment administration is the best way to mitigate the in-host malaria infection.","PeriodicalId":36662,"journal":{"name":"Frontiers in Applied Mathematics and Statistics","volume":" 34","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138962081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-19DOI: 10.3389/fams.2023.1294540
H. Poorhemati, Svetlana V. Komarova
Formation of hydroxyapatite in bone, dentin, and enamel occurs at restricted molecular sites of specific extracellular matrix proteins and is controlled by multiple mineralization inhibitors. However, the role of physicochemical factors, such as the availability of required ions and the saturation status of the aqueous environment in biological mineralization, is not fully understood. The goal of this study was to use mathematical modeling to describe the complex physicochemical environment permissive to the precipitation of biological hydroxyapatite.We simulated the processes occurring in the bone interstitial fluid (ISF) defined as an aqueous environment containing seven chemical components (calcium, phosphate, carbonate, sodium, potassium, magnesium, and chloride) that form 30 chemical species. We simulated reversible equilibrium reactions among these chemical species, and calculated supersaturation for hydroxyapatite and its precipitation rate using kinetic theory.The simulated ISF was of correct ionic strength and predicted the equilibrium component concentrations that were consistent with the experimental findings. Supersaturation of physiological ISF was ~15, which is consistent with prior findings that mineralization inhibitors are required to prevent spontaneous mineral precipitation. Only total calcium, total phosphate and to a lesser degree total carbonate affected ion availability, solution supersaturation and hydroxyapatite precipitation rate. Both calcium and phosphate levels directly affected hydroxyapatite precipitation, and phosphate was affected by pH, which additionally influenced hydroxyapatite precipitation. Integrating mathematical models capturing the physiochemical and biological factors regulating bone mineralization will allow in silico studies of complex clinical scenarios associated with alterations in ISF ion composition, such as rickets, hypophosphatemia, and chronic kidney disease.
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