Frontiers in Applied Mathematics and Statistics最新文献

{"title":"EESB-FDO: enhancing the fitness-dependent optimizer through a modified boundary handling mechanism","authors":"Aram Kamal Faraj, Aso M. Aladdin, Azad A. Ameen","doi":"10.3389/fams.2025.1640044","DOIUrl":"https://doi.org/10.3389/fams.2025.1640044","url":null,"abstract":"The fitness-dependent optimizer (FDO) has recently gained attention as an effective metaheuristic for solving different optimization problems. However, it faces limitations in exploitation and convergence speed. To overcome these challenges, this study introduces two enhanced variants: enhancing exploitation through stochastic boundary for FDO (EESB-FDO) and enhancing exploitation through boundary carving for FDO (EEBC-FDO). In addition, the ELFS strategy is proposed to constrain Levy flight steps, ensuring more stable exploration. Experimental results show that these modifications significantly improve the performance of FDO compared to the original version. To evaluate the performance of the EESB-FDO and EEBC-FDO, three primary categories of benchmark test functions were utilized: classical, CEC 2019, and CEC 2022. The assessment was further supported by the application of statistical analysis methods to ensure a comprehensive and rigorous performance evaluation. The performance of the proposed EESB-FDO and EEBC-FDO algorithms was evaluated through comparative analysis with several existing FDO modifications, as well as with other well-established metaheuristic algorithms, including the Arithmetic Optimization Algorithm (AOA), the Learner Performance-Based Behavior Algorithm (LPB), the Whale Optimization Algorithm (WOA), and the Fox-inspired Optimization Algorithm (FOX). The statistical analysis indicated that both EESB-FDO and EEBC-FDO exhibit better performance compared to the aforementioned algorithms. Furthermore, a final evaluation involved applying EESB-FDO and EEBC-FDO to four real-world optimization problems: the gear train design problem, the three-bar truss problem, the pathological igg fraction in the nervous system, and the integrated cyber-physical attack on a manufacturing system. The results demonstrate that both proposed variants significantly outperform both the FDO and the modified fitness-dependent optimizer (MFDO) in solving these complex problems.","PeriodicalId":36662,"journal":{"name":"Frontiers in Applied Mathematics and Statistics","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.frontiersin.org/journals/applied-mathematics-and-statistics/articles/10.3389/fams.2025.1640044/pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147900545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Learning surrogate equations for the analysis of an agent-based cancer model","authors":"Kevin Burrage, Pamela Burrage, Justin N. Kreikemeyer, Adelinde M. Uhrmacher, Hasitha N. Weerasinghe","doi":"10.3389/fams.2025.1578604","DOIUrl":"https://doi.org/10.3389/fams.2025.1578604","url":null,"abstract":"In this paper, we adapt a two-species agent-based cancer model that describes the interaction between cancer cells and healthy cells on a uniform grid to include the interaction with a third species—namely immune cells. We run six different scenarios to explore the competition between cancer and immune cells and the initial concentration of the immune cells on cancer dynamics. We then use coupled equation learning to construct a population-based reaction model for each scenario. We show how they can be unified into a single surrogate population-based reaction model, whose underlying three coupled ordinary differential equations are much easier to analyse than the original agent-based model. As an example, by finding the single steady state of the cancer concentration, we are able to find a linear relationship between this concentration and the initial concentration of the immune cells. This then enables us to estimate suitable values for the competition and initial concentration to reduce the cancer substantially without performing additional complex and expensive simulations from an agent-based stochastic model.","PeriodicalId":36662,"journal":{"name":"Frontiers in Applied Mathematics and Statistics","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.frontiersin.org/journals/applied-mathematics-and-statistics/articles/10.3389/fams.2025.1578604/pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147900022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mathematical Model of Influenza Infection Suggests JAK-STAT Activity Drives Severe Pathologies in Juvenile Mice.","authors":"Lauren L Luciani, Lauren M Nichols, Brydie R Huckestein, John F Alcorn, Jason E Shoemaker","doi":"10.3389/fams.2025.1694710","DOIUrl":"10.3389/fams.2025.1694710","url":null,"abstract":"<p><p>Children are uniquely susceptible to severe influenza infection, with one million children experiencing severe life-threatening disease each year. However, there is little evidence that an underdeveloped immune system or differences in viral loads are responsible, implicating the host inflammatory response as responsible for increased lung injury in juveniles. Here, we used mechanism-based mathematical modeling, age-specific lung immune data from influenza-infected mice, Bayesian statistics, and rigorous Monte Carlo-based methods to identify immune mechanisms that may be differently regulated in juvenile animals. We hypothesized that the immunological mechanisms between juvenile and adult mice are primarily conserved, and that immune response differences arise due to a minimal set of parameter differences. First, we developed and identified parameter bounds for an ordinary differential equation (ODE) model of the innate immune response to influenza infection which capture the dynamic changes of select parameters. Using publicly available juvenile and adult murine data, we then conducted a computational screen of different age-specific model scenarios and evaluated the scenarios using the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) to select the optimal scenario. These results suggest that the rate of production of JAK-STAT pathway activators, like type I IFNs and IL-6, is age-specific. Preconditioned Monte Carlo (PMC) analysis revealed that JAK-STAT activator production is higher in juveniles than adults. Additional simulations suggest antiviral therapeutics may be more effective in juvenile populations. While not significantly suppressing virus replication, age-specific IFN or IL-6 production may be responsible for increased inflammation, lung injury, and mortality observed in juvenile influenza infection.</p>","PeriodicalId":36662,"journal":{"name":"Frontiers in Applied Mathematics and Statistics","volume":"11 ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12928754/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147285540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Value at Risk long memory volatility models with heavy-tailed distributions for cryptocurrencies.","authors":"Stephanie Danielle Subramoney, Knowledge Chinhamu, Retius Chifurira","doi":"10.3389/fams.2025.1567626","DOIUrl":"10.3389/fams.2025.1567626","url":null,"abstract":"<p><p>This paper investigates the volatility dynamics and underlying long memory features of four major cryptocurrencies-Bitcoin, Ethereum, Litecoin, and Ripple-which were selected due to their high liquidity, large trading volumes, and historical significance in the digital asset market. The long-range dependence exhibited in cryptocurrency markets is often overlooked. However, based on the strong evidence of persistent dependence in the return series, we adopt advanced volatility models that are capable of accommodating high volatility and heavy-tails, as well as the long memory properties of cryptocurrencies. Specifically, we employ long-memory extensions of the GAS (Long memory GAS) and GARCH (Fractionally Integrated Asymmetric Power ARCH) models, integrating heavy-tailed innovation distributions: the Generalized Hyperbolic Distribution (GHD) and Generalized Lambda Distribution (GLD). Standard GARCH and GAS models are included as benchmarks. The performance of the models are assessed using Value-at-Risk (VaR) estimation, backtesting (in-sample and out-of-sample) and volatility forecasting metrics. The results indicate that long memory models, particularly the FIAPARCH model, consistently outperforms the standard GAS and GARCH models in capturing tail risk and the volatility persistence. These findings emphasize the critical role of long memory in modeling the risk of cryptocurrencies, indicating that accounting for volatility persistence can significantly enhance the accuracy of risk estimates and strengthen risk management practices.</p>","PeriodicalId":36662,"journal":{"name":"Frontiers in Applied Mathematics and Statistics","volume":"11 ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12945339/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147327350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"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}

{"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}

{"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}

{"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}

{"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}

{"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}