Pub Date : 2023-10-13DOI: 10.3389/fams.2023.1241538
Paola Stolfi, Davide Vergni, Filippo Castiglione
Introduction Mathematical modeling has emerged as a crucial component in understanding the epidemiology of infectious diseases. In fact, contemporary surveillance efforts for epidemic or endemic infections heavily rely on mathematical and computational methods. This study presents a novel agent-based multi-level model that depicts the transmission dynamics of gonorrhea, a sexually transmitted infection (STI) caused by the bacterium Neisseria gonorrhoeae . This infection poses a significant public health challenge as it is endemic in numerous countries, and each year sees millions of new cases, including a concerning number of drug-resistant cases commonly referred to as gonorrhea superbugs or super gonorrhea. These drug-resistant strains exhibit a high level of resistance to recommended antibiotic treatments. Methods The proposed model incorporates a multi-layer network of agents' interaction representing the dynamics of sexual partnerships. It also encompasses a transmission model, which quantifies the probability of infection during sexual intercourse, and a within-host model, which captures the immune activation following gonorrhea infection in an individual. It is a combination of agent-based modeling, which effectively captures interactions among various risk groups, and probabilistic modeling, which enables a theoretical exploration of sexual network characteristics and contagion dynamics. Results Numerical simulations of the dynamics of gonorrhea infection using the complete agent-based model are carried out. In particular, some examples of possible epidemic evolution are presented together with an application to a real case study. The goal was to construct a virtual population that closely resembles the target population of interest. Discussion The uniqueness of this research lies in its objective to accurately depict the influence of distinct sexual risk groups and their interaction on the prevalence of gonorrhea. The proposed model, having interpretable and measurable parameters from epidemiological data, facilitates a more comprehensive understanding of the disease evolution.
{"title":"An agent-based multi-level model to study the spread of gonorrhea in different and interacting risk groups","authors":"Paola Stolfi, Davide Vergni, Filippo Castiglione","doi":"10.3389/fams.2023.1241538","DOIUrl":"https://doi.org/10.3389/fams.2023.1241538","url":null,"abstract":"Introduction Mathematical modeling has emerged as a crucial component in understanding the epidemiology of infectious diseases. In fact, contemporary surveillance efforts for epidemic or endemic infections heavily rely on mathematical and computational methods. This study presents a novel agent-based multi-level model that depicts the transmission dynamics of gonorrhea, a sexually transmitted infection (STI) caused by the bacterium Neisseria gonorrhoeae . This infection poses a significant public health challenge as it is endemic in numerous countries, and each year sees millions of new cases, including a concerning number of drug-resistant cases commonly referred to as gonorrhea superbugs or super gonorrhea. These drug-resistant strains exhibit a high level of resistance to recommended antibiotic treatments. Methods The proposed model incorporates a multi-layer network of agents' interaction representing the dynamics of sexual partnerships. It also encompasses a transmission model, which quantifies the probability of infection during sexual intercourse, and a within-host model, which captures the immune activation following gonorrhea infection in an individual. It is a combination of agent-based modeling, which effectively captures interactions among various risk groups, and probabilistic modeling, which enables a theoretical exploration of sexual network characteristics and contagion dynamics. Results Numerical simulations of the dynamics of gonorrhea infection using the complete agent-based model are carried out. In particular, some examples of possible epidemic evolution are presented together with an application to a real case study. The goal was to construct a virtual population that closely resembles the target population of interest. Discussion The uniqueness of this research lies in its objective to accurately depict the influence of distinct sexual risk groups and their interaction on the prevalence of gonorrhea. The proposed model, having interpretable and measurable parameters from epidemiological data, facilitates a more comprehensive understanding of the disease evolution.","PeriodicalId":36662,"journal":{"name":"Frontiers in Applied Mathematics and Statistics","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135855212","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 : 2023-10-04DOI: 10.3389/fams.2023.1278146
Rosa Fabbricatore, Lucio Palazzo
Introduction Modern FinTech tools (e.g., instant payments, blockchain, roboadvisor) represent the new frontier of digital finance. Consequently, the evaluation of the knowledge level of the population about these topics is a crucial concern. In this context, several exogenous factors may influence individual differences in financial literacy. In particular, the territorial characteristics can have an impact on FinTech. In this work, we investigate individual heterogeneity in subjective financial knowledge in Italy, specifically focusing on modern FinTech tools, and exploring the differences at the individual and regional levels. Methods A sample of 598 Italian individuals from 10 different Italian regions was involved. A multilevel IRT model is performed to evaluate the level of FinTech individual knowledge and the differences according to Italian regions to account for the hierarchical structure of the data. Results Results reported a weak regional effect, revealing that heterogeneity in financial knowledge can be mainly attributed to individual characteristics. At the individual level, age, economic condition, knowledge of traditional financial objects and numeracy showed a significant effect. In addition, a scientific field of study and work have an impact on respondents' knowledge level. Discussion What is shown and discussed in this contribution can inspire policymakers' actions to increase financial literacy in the population. In particular, the obtained results imply that policymakers should improve the population's awareness of less popular FinTech tools and foster individuals' literacy about numbers and traditional financial tools, which proved to have a great influence in explaining FinTech knowledge differences.
{"title":"Multilevel IRT models to explore heterogeneity in subjective financial knowledge at individual and regional levels: the Italian case","authors":"Rosa Fabbricatore, Lucio Palazzo","doi":"10.3389/fams.2023.1278146","DOIUrl":"https://doi.org/10.3389/fams.2023.1278146","url":null,"abstract":"Introduction Modern FinTech tools (e.g., instant payments, blockchain, roboadvisor) represent the new frontier of digital finance. Consequently, the evaluation of the knowledge level of the population about these topics is a crucial concern. In this context, several exogenous factors may influence individual differences in financial literacy. In particular, the territorial characteristics can have an impact on FinTech. In this work, we investigate individual heterogeneity in subjective financial knowledge in Italy, specifically focusing on modern FinTech tools, and exploring the differences at the individual and regional levels. Methods A sample of 598 Italian individuals from 10 different Italian regions was involved. A multilevel IRT model is performed to evaluate the level of FinTech individual knowledge and the differences according to Italian regions to account for the hierarchical structure of the data. Results Results reported a weak regional effect, revealing that heterogeneity in financial knowledge can be mainly attributed to individual characteristics. At the individual level, age, economic condition, knowledge of traditional financial objects and numeracy showed a significant effect. In addition, a scientific field of study and work have an impact on respondents' knowledge level. Discussion What is shown and discussed in this contribution can inspire policymakers' actions to increase financial literacy in the population. In particular, the obtained results imply that policymakers should improve the population's awareness of less popular FinTech tools and foster individuals' literacy about numbers and traditional financial tools, which proved to have a great influence in explaining FinTech knowledge differences.","PeriodicalId":36662,"journal":{"name":"Frontiers in Applied Mathematics and Statistics","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135592743","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 : 2023-10-04DOI: 10.3389/fams.2023.1271296
Dong Wang, Xing Dang, Weijing Liu, Yuanquan Wang
Introduction Gradient vector flow (GVF) has been proven as an effective external force for active contours. However, its smoothness constraint does not take the image structure into account, such that the GVF diffusion is isotropic and cannot preserve weak edges well. Methods In this article, an image structure adaptive gradient vector flow (ISAGVF) external force is proposed for active contours. In the proposed ISAGVF model, the smoothness constraint is first reformulated in matrix form, and then the image structure tensor is incorporated. As the structure tensor characterizes the image structure well, the proposed ISAGVF model can be adaptive to image structure, and the ISAGVF snake performs well on weak edge preservation and deep concavity convergence while possessing some other desirable properties of the GVF snake, such as enlarged capture range and insensitivity to initialization. Results Experiments on synthetic and real images manifest these properties of the ISAGVF snake.
{"title":"Image segmentation using active contours with image structure adaptive gradient vector flow external force","authors":"Dong Wang, Xing Dang, Weijing Liu, Yuanquan Wang","doi":"10.3389/fams.2023.1271296","DOIUrl":"https://doi.org/10.3389/fams.2023.1271296","url":null,"abstract":"Introduction Gradient vector flow (GVF) has been proven as an effective external force for active contours. However, its smoothness constraint does not take the image structure into account, such that the GVF diffusion is isotropic and cannot preserve weak edges well. Methods In this article, an image structure adaptive gradient vector flow (ISAGVF) external force is proposed for active contours. In the proposed ISAGVF model, the smoothness constraint is first reformulated in matrix form, and then the image structure tensor is incorporated. As the structure tensor characterizes the image structure well, the proposed ISAGVF model can be adaptive to image structure, and the ISAGVF snake performs well on weak edge preservation and deep concavity convergence while possessing some other desirable properties of the GVF snake, such as enlarged capture range and insensitivity to initialization. Results Experiments on synthetic and real images manifest these properties of the ISAGVF snake.","PeriodicalId":36662,"journal":{"name":"Frontiers in Applied Mathematics and Statistics","volume":"168 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135590692","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 : 2023-09-26DOI: 10.3389/fams.2023.1267664
Fernando E. Serrano, Jesus M. Munoz-Pacheco, Marco A. Flores
This paper presents the fractional-order projection of a chaotic system, which delivers a collection of self-excited and hidden chaotic attractors as a function of a single system parameter. Based on an integer-order chaotic system and the proposed transformation, the fractional-order chaotic system obtains when the divergence of integer and fractional vector fields flows in the same direction. Phase portraits, bifurcation diagrams, and Lyapunov exponents validate the chaos generation. Apart from these results, two passivity-based fractional control laws are designed effectively for the integer and fractional-order chaotic systems. In both cases, the synchronization schemes depend on suitable storage functions given by the fractional Lyapunov theory. Several numerical experiments confirm the proposed approach and agree well with the mathematical deductions.
{"title":"Fractional-order projection of a chaotic system with hidden attractors and its passivity-based synchronization","authors":"Fernando E. Serrano, Jesus M. Munoz-Pacheco, Marco A. Flores","doi":"10.3389/fams.2023.1267664","DOIUrl":"https://doi.org/10.3389/fams.2023.1267664","url":null,"abstract":"This paper presents the fractional-order projection of a chaotic system, which delivers a collection of self-excited and hidden chaotic attractors as a function of a single system parameter. Based on an integer-order chaotic system and the proposed transformation, the fractional-order chaotic system obtains when the divergence of integer and fractional vector fields flows in the same direction. Phase portraits, bifurcation diagrams, and Lyapunov exponents validate the chaos generation. Apart from these results, two passivity-based fractional control laws are designed effectively for the integer and fractional-order chaotic systems. In both cases, the synchronization schemes depend on suitable storage functions given by the fractional Lyapunov theory. Several numerical experiments confirm the proposed approach and agree well with the mathematical deductions.","PeriodicalId":36662,"journal":{"name":"Frontiers in Applied Mathematics and Statistics","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135719168","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}
Introduction Ensuring fair competition through manual review is a complex undertaking. This paper introduces the utilization of Long Short-Term Memory (LSTM) neural networks and TextCNN to establish a text classifier for classifying and reviewing normative documents. Methods The experimental dataset used consists of policy measure samples provided by the antitrust division of the Guangdong Market Supervision Administration. We conduct a comparative analysis of the performance of LSTM and TextCNN classification models. Results In three classification experiments conducted without an enhanced experimental dataset, the LSTM classifier achieved an accuracy of 95.74%, while the TextCNN classifier achieved an accuracy of 92.7% on the test set. Conversely, in three classification experiments utilizing an enhanced experimental dataset, the LSTM classifier demonstrated an accuracy of 96.36%, and the TextCNN classifier achieved an accuracy of 96.19% on the test set. Discussion The experimental results highlight the effectiveness of LSTM and TextCNN in classifying and reviewing normative documents. The superior accuracy achieved with the enhanced experimental dataset underscores the potential of these models in real-world applications, particularly in tasks involving fair competition review.
{"title":"Text classification in fair competition law violations using deep learning","authors":"Yinying Kong, Niangqiu Huang, Haodong Deng, Junwen Feng, Xingyi Liang, Weisi Lv, Jingyi Liu","doi":"10.3389/fams.2023.1177081","DOIUrl":"https://doi.org/10.3389/fams.2023.1177081","url":null,"abstract":"Introduction Ensuring fair competition through manual review is a complex undertaking. This paper introduces the utilization of Long Short-Term Memory (LSTM) neural networks and TextCNN to establish a text classifier for classifying and reviewing normative documents. Methods The experimental dataset used consists of policy measure samples provided by the antitrust division of the Guangdong Market Supervision Administration. We conduct a comparative analysis of the performance of LSTM and TextCNN classification models. Results In three classification experiments conducted without an enhanced experimental dataset, the LSTM classifier achieved an accuracy of 95.74%, while the TextCNN classifier achieved an accuracy of 92.7% on the test set. Conversely, in three classification experiments utilizing an enhanced experimental dataset, the LSTM classifier demonstrated an accuracy of 96.36%, and the TextCNN classifier achieved an accuracy of 96.19% on the test set. Discussion The experimental results highlight the effectiveness of LSTM and TextCNN in classifying and reviewing normative documents. The superior accuracy achieved with the enhanced experimental dataset underscores the potential of these models in real-world applications, particularly in tasks involving fair competition review.","PeriodicalId":36662,"journal":{"name":"Frontiers in Applied Mathematics and Statistics","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136059635","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 : 2023-09-15DOI: 10.3389/fams.2023.1268340
Nasrullah Khan, Muhammad Aslam, Mohammed Albassam
This study investigates the efficiency of a modified exponentially weighted moving average (EWMA) control method using conditional expected delay to improve its efficiency in detecting changes in a process over time. While the modified EWMA control method is commonly used for this purpose, it can sometimes experience delays in detecting changes. The proposed method aims to address this limitation by incorporating conditional expected delay. The study utilizes simulations to conduct a performance comparison between the modified EWMA control method and the conventional EWMA control, employing the metric of conditional expected delay. Simulation results demonstrate the modified EWMA control method with conditional expected delay in terms of accurately and rapidly detecting changes. Overall, this study concludes that the integration of conditional expected delay into the modified EWMA control method can increase its effectiveness in detecting changes in a process. This has significant practical implications for a variety of industries that require timely and accurate detection of changes to maintain product quality and optimize processes.
{"title":"Efficiency enhancement of the modified EWMA control method with conditional expected delay for change detection in processes","authors":"Nasrullah Khan, Muhammad Aslam, Mohammed Albassam","doi":"10.3389/fams.2023.1268340","DOIUrl":"https://doi.org/10.3389/fams.2023.1268340","url":null,"abstract":"This study investigates the efficiency of a modified exponentially weighted moving average (EWMA) control method using conditional expected delay to improve its efficiency in detecting changes in a process over time. While the modified EWMA control method is commonly used for this purpose, it can sometimes experience delays in detecting changes. The proposed method aims to address this limitation by incorporating conditional expected delay. The study utilizes simulations to conduct a performance comparison between the modified EWMA control method and the conventional EWMA control, employing the metric of conditional expected delay. Simulation results demonstrate the modified EWMA control method with conditional expected delay in terms of accurately and rapidly detecting changes. Overall, this study concludes that the integration of conditional expected delay into the modified EWMA control method can increase its effectiveness in detecting changes in a process. This has significant practical implications for a variety of industries that require timely and accurate detection of changes to maintain product quality and optimize processes.","PeriodicalId":36662,"journal":{"name":"Frontiers in Applied Mathematics and Statistics","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135437813","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 : 2023-09-14DOI: 10.3389/fams.2023.1164491
Philipp Flotho, Cosmas Heiss, Gabriele Steidl, Daniel J. Strauss
Microexpressions are fast and spatially small facial expressions that are difficult to detect. Therefore, motion magnification techniques, which aim at amplifying and hence revealing subtle motion in videos, appear useful for handling such expressions. There are basically two main approaches, namely, via Eulerian or Lagrangian techniques. While the first one magnifies motion implicitly by operating directly on image pixels, the Lagrangian approach uses optical flow (OF) techniques to extract and magnify pixel trajectories. In this study, we propose a novel approach for local Lagrangian motion magnification of facial micro-motions. Our contribution is 3-fold: first, we fine tune the recurrent all-pairs field transforms (RAFT) for OFs deep learning approach for faces by adding ground truth obtained from the variational dense inverse search (DIS) for the OF algorithm applied to the CASME II video set of facial micro expressions. This enables us to produce OFs of facial videos in an efficient and sufficiently accurate way. Second, since facial micro-motions are both local in space and time, we propose to approximate the OF field by sparse components both in space and time leading to a double sparse decomposition. Third, we use this decomposition to magnify micro-motions in specific areas of the face, where we introduce a new forward warping strategy using a triangular splitting of the image grid and barycentric interpolation of the RGB vectors at the corners of the transformed triangles. We demonstrate the feasibility of our approach by various examples.
{"title":"Lagrangian motion magnification with double sparse optical flow decomposition","authors":"Philipp Flotho, Cosmas Heiss, Gabriele Steidl, Daniel J. Strauss","doi":"10.3389/fams.2023.1164491","DOIUrl":"https://doi.org/10.3389/fams.2023.1164491","url":null,"abstract":"Microexpressions are fast and spatially small facial expressions that are difficult to detect. Therefore, motion magnification techniques, which aim at amplifying and hence revealing subtle motion in videos, appear useful for handling such expressions. There are basically two main approaches, namely, via Eulerian or Lagrangian techniques. While the first one magnifies motion implicitly by operating directly on image pixels, the Lagrangian approach uses optical flow (OF) techniques to extract and magnify pixel trajectories. In this study, we propose a novel approach for local Lagrangian motion magnification of facial micro-motions. Our contribution is 3-fold: first, we fine tune the recurrent all-pairs field transforms (RAFT) for OFs deep learning approach for faces by adding ground truth obtained from the variational dense inverse search (DIS) for the OF algorithm applied to the CASME II video set of facial micro expressions. This enables us to produce OFs of facial videos in an efficient and sufficiently accurate way. Second, since facial micro-motions are both local in space and time, we propose to approximate the OF field by sparse components both in space and time leading to a double sparse decomposition. Third, we use this decomposition to magnify micro-motions in specific areas of the face, where we introduce a new forward warping strategy using a triangular splitting of the image grid and barycentric interpolation of the RGB vectors at the corners of the transformed triangles. We demonstrate the feasibility of our approach by various examples.","PeriodicalId":36662,"journal":{"name":"Frontiers in Applied Mathematics and Statistics","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134911555","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 : 2023-09-07DOI: 10.3389/fams.2023.1208774
Nabeela Anwar, Iftikhar Ahmad, A. Kiani, M. Shoaib, M. Raja
The most important factor for increasing crop production is pest and pathogen resistance, which has a major impact on global food security. Pest management also emphasizes the need for farming awareness. A high crop yield is ultimately achieved by protecting crops from pests and raising public awareness of the devastation caused by pests. In this research, we aim to investigate the intricate impacts of nonlinear delayed systems for managing crop pest management (CPM) supervised by Ordinary Differential Equations (ODEs). Our focus will be on highlighting the intricate and often unpredictable relationships that occur over time among crops, pests, strategies for rehabilitation, and environmental factors. The nonlinear delayed CPM model incorporated the four compartments: crop biomass density [B(t)], susceptible pest density [S(t)], infected pest density [I(t)], and population awareness level [A(t)]. The approximate solutions for the four compartments B(t), S(t), I(t), and A(t) are determined by the implementation of sundry scenarios generated with the variation in crop biomass growth rate, rate of pest attacks, pest natural death rate, disease associated death rate and memory loss of aware people, by means of exploiting the strength of the Adams (ADS) and explicit Runge-Kutta (ERK) numerical solvers. Comparative analysis of the designed approach is carried out for the dynamic impacts of the nonlinear delayed CPM model in terms of numerical outcomes and simulations based on sundry scenarios.
{"title":"Numerical treatment for mathematical model of farming awareness in crop pest management","authors":"Nabeela Anwar, Iftikhar Ahmad, A. Kiani, M. Shoaib, M. Raja","doi":"10.3389/fams.2023.1208774","DOIUrl":"https://doi.org/10.3389/fams.2023.1208774","url":null,"abstract":"The most important factor for increasing crop production is pest and pathogen resistance, which has a major impact on global food security. Pest management also emphasizes the need for farming awareness. A high crop yield is ultimately achieved by protecting crops from pests and raising public awareness of the devastation caused by pests. In this research, we aim to investigate the intricate impacts of nonlinear delayed systems for managing crop pest management (CPM) supervised by Ordinary Differential Equations (ODEs). Our focus will be on highlighting the intricate and often unpredictable relationships that occur over time among crops, pests, strategies for rehabilitation, and environmental factors. The nonlinear delayed CPM model incorporated the four compartments: crop biomass density [B(t)], susceptible pest density [S(t)], infected pest density [I(t)], and population awareness level [A(t)]. The approximate solutions for the four compartments B(t), S(t), I(t), and A(t) are determined by the implementation of sundry scenarios generated with the variation in crop biomass growth rate, rate of pest attacks, pest natural death rate, disease associated death rate and memory loss of aware people, by means of exploiting the strength of the Adams (ADS) and explicit Runge-Kutta (ERK) numerical solvers. Comparative analysis of the designed approach is carried out for the dynamic impacts of the nonlinear delayed CPM model in terms of numerical outcomes and simulations based on sundry scenarios.","PeriodicalId":36662,"journal":{"name":"Frontiers in Applied Mathematics and Statistics","volume":" ","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44145575","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 : 2023-09-07DOI: 10.3389/fams.2023.1107441
Joshua C. Kynaston, Christian A. Yates, Anna V. F. Hekkink, Chris Guiver
There exist several methods for simulating biological and physical systems as represented by chemical reaction networks. Systems with low numbers of particles are frequently modeled as discrete-state Markov jump processes and are typically simulated via a stochastic simulation algorithm (SSA). An SSA, while accurate, is often unsuitable for systems with large numbers of individuals, and can become prohibitively expensive with increasing reaction frequency. Large systems are often modeled deterministically using ordinary differential equations, sacrificing accuracy and stochasticity for computational efficiency and analytical tractability. In this paper, we present a novel hybrid technique for the accurate and efficient simulation of large chemical reaction networks. This technique, which we name the regime-conversion method, couples a discrete-state Markov jump process to a system of ordinary differential equations by simulating a reaction network using both techniques simultaneously. Individual molecules in the network are represented by exactly one regime at any given time, and may switch their governing regime depending on particle density. In this manner, we model high copy-number species using the cheaper continuum method and low copy-number species using the more expensive, discrete-state stochastic method to preserve the impact of stochastic fluctuations at low copy number. The motivation, as with similar methods, is to retain the advantages while mitigating the shortfalls of each method. We demonstrate the performance and accuracy of our method for several test problems that exhibit varying degrees of inter-connectivity and complexity by comparing averaged trajectories obtained from both our method and from exact stochastic simulation.
{"title":"The regime-conversion method: a hybrid technique for simulating well-mixed chemical reaction networks","authors":"Joshua C. Kynaston, Christian A. Yates, Anna V. F. Hekkink, Chris Guiver","doi":"10.3389/fams.2023.1107441","DOIUrl":"https://doi.org/10.3389/fams.2023.1107441","url":null,"abstract":"There exist several methods for simulating biological and physical systems as represented by chemical reaction networks. Systems with low numbers of particles are frequently modeled as discrete-state Markov jump processes and are typically simulated via a stochastic simulation algorithm (SSA). An SSA, while accurate, is often unsuitable for systems with large numbers of individuals, and can become prohibitively expensive with increasing reaction frequency. Large systems are often modeled deterministically using ordinary differential equations, sacrificing accuracy and stochasticity for computational efficiency and analytical tractability. In this paper, we present a novel hybrid technique for the accurate and efficient simulation of large chemical reaction networks. This technique, which we name the regime-conversion method, couples a discrete-state Markov jump process to a system of ordinary differential equations by simulating a reaction network using both techniques simultaneously. Individual molecules in the network are represented by exactly one regime at any given time, and may switch their governing regime depending on particle density. In this manner, we model high copy-number species using the cheaper continuum method and low copy-number species using the more expensive, discrete-state stochastic method to preserve the impact of stochastic fluctuations at low copy number. The motivation, as with similar methods, is to retain the advantages while mitigating the shortfalls of each method. We demonstrate the performance and accuracy of our method for several test problems that exhibit varying degrees of inter-connectivity and complexity by comparing averaged trajectories obtained from both our method and from exact stochastic simulation.","PeriodicalId":36662,"journal":{"name":"Frontiers in Applied Mathematics and Statistics","volume":"1 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41786833","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 : 2023-09-07DOI: 10.3389/fams.2023.1255672
Zerihun Ibrahim Hassen, G. Duressa
This paper presents a parameter-uniform numerical method to solve the time dependent singularly perturbed delay parabolic convection-diffusion problems. The solution to these problems displays a parabolic boundary layer if the perturbation parameter approaches zero. The retarded argument of the delay term made to coincide with a mesh point and the resulting singularly perturbed delay parabolic convection-diffusion problem is approximated using the implicit Euler method in temporal direction and extended cubic B-spline collocation in spatial orientation by introducing artificial viscosity both on uniform mesh. The proposed method is shown to be parameter uniform convergent, unconditionally stable, and linear order of accuracy. Furthermore, the obtained numerical results agreed with the theoretical results.
{"title":"Parameter-uniformly convergent numerical scheme for singularly perturbed delay parabolic differential equation via extended B-spline collocation","authors":"Zerihun Ibrahim Hassen, G. Duressa","doi":"10.3389/fams.2023.1255672","DOIUrl":"https://doi.org/10.3389/fams.2023.1255672","url":null,"abstract":"This paper presents a parameter-uniform numerical method to solve the time dependent singularly perturbed delay parabolic convection-diffusion problems. The solution to these problems displays a parabolic boundary layer if the perturbation parameter approaches zero. The retarded argument of the delay term made to coincide with a mesh point and the resulting singularly perturbed delay parabolic convection-diffusion problem is approximated using the implicit Euler method in temporal direction and extended cubic B-spline collocation in spatial orientation by introducing artificial viscosity both on uniform mesh. The proposed method is shown to be parameter uniform convergent, unconditionally stable, and linear order of accuracy. Furthermore, the obtained numerical results agreed with the theoretical results.","PeriodicalId":36662,"journal":{"name":"Frontiers in Applied Mathematics and Statistics","volume":" ","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47914346","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}
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