This study delves into a continuous-time mathematical framework that delineates the transmission dynamics of the monkeypox virus across distinct regions, involving both human and animal hosts. We introduce an optimal approach that encompasses awareness campaigns, security protocols, and health interventions in areas endemic to the virus, aiming to curtail the transmission among individuals and animals, thereby minimizing infections in humans and eradicating the virus in animals. Leveraging the discrete-time Pontryagin principle of maximum, we ascertain optimal controls, employing an iterative methodology to solve the optimal system. Employing Matlab, we conduct numerical simulations and compute a cost-effectiveness ratio. Through a comprehensive cost-effectiveness analysis, we underscore the efficacy of strategies centered around safeguarding vulnerable individuals, preventing contact with infected counterparts—both human and animal—and fostering the utilization of quarantine facilities as the most potent means to govern the spread of the monkeypox virus.
{"title":"Mathematical modeling and monkeypox's optimal control strategy","authors":"","doi":"10.28919/cmbn/8198","DOIUrl":"https://doi.org/10.28919/cmbn/8198","url":null,"abstract":"This study delves into a continuous-time mathematical framework that delineates the transmission dynamics of the monkeypox virus across distinct regions, involving both human and animal hosts. We introduce an optimal approach that encompasses awareness campaigns, security protocols, and health interventions in areas endemic to the virus, aiming to curtail the transmission among individuals and animals, thereby minimizing infections in humans and eradicating the virus in animals. Leveraging the discrete-time Pontryagin principle of maximum, we ascertain optimal controls, employing an iterative methodology to solve the optimal system. Employing Matlab, we conduct numerical simulations and compute a cost-effectiveness ratio. Through a comprehensive cost-effectiveness analysis, we underscore the efficacy of strategies centered around safeguarding vulnerable individuals, preventing contact with infected counterparts—both human and animal—and fostering the utilization of quarantine facilities as the most potent means to govern the spread of the monkeypox virus.","PeriodicalId":44079,"journal":{"name":"Communications in Mathematical Biology and Neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135106298","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}
In this work, we have constructed a new system of differential equations which mathematically models infectious diseases with several mutations. (such as covid 19 disease and their mutations). Therefore, we are interested in studying the asymptotic stability of our new system.
{"title":"The global stability of fractional epidemiological model with n strain \"all coronavirus mutations\"","authors":"","doi":"10.28919/cmbn/8193","DOIUrl":"https://doi.org/10.28919/cmbn/8193","url":null,"abstract":"In this work, we have constructed a new system of differential equations which mathematically models infectious diseases with several mutations. (such as covid 19 disease and their mutations). Therefore, we are interested in studying the asymptotic stability of our new system.","PeriodicalId":44079,"journal":{"name":"Communications in Mathematical Biology and Neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135106306","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}
Hermantoro, M. A. Kurniawan, J. P. Trinugroho, T. Suparyanto, Mahmud Isnan, D. Sudigyo, B. Pardamean
. The oil palm tree is one of the essential plants with a major contribution to the Indonesian economy but is also vulnerable to pathogen infection, such as Ganoderma . Ganoderma boninense is a group of polyporous fungi which is responsible for Basal Stem Rot disease. The disease is extremely serious and easily spreads, posing a significant threat to the economy, so early detection of the disease becomes vital. However, the current detection techniques for the disease are expensive and time-consuming; hence, they are not ideal for large plantation areas. The development of image processing technology could be utilized to predict Ganoderma infection, using the images that are captured by a drone. This research aims to predict the spread of Ganoderma infection, in the oil palm tree plantation area in North Sumatra, Indonesia, by utilizing image processing and Artificial Neural Network methods. Our model results showed the prediction accuracy (with Green color) was 73,8%. In addition, we also showed the distribution of Ganoderma infection in the area: score 0 was 229 trees, score 1 was 295 trees, score 2 was 112 trees, score 3 was 238 trees, and score 4 was 23 trees. Overall, our research provided a non-destructive method to detect Basal Stem Rot disease in the oil palm plantation sites.
{"title":"Detecting Ganoderma basal stem rot disease on oil palm using artificial neural network method","authors":"Hermantoro, M. A. Kurniawan, J. P. Trinugroho, T. Suparyanto, Mahmud Isnan, D. Sudigyo, B. Pardamean","doi":"10.28919/cmbn/7911","DOIUrl":"https://doi.org/10.28919/cmbn/7911","url":null,"abstract":". The oil palm tree is one of the essential plants with a major contribution to the Indonesian economy but is also vulnerable to pathogen infection, such as Ganoderma . Ganoderma boninense is a group of polyporous fungi which is responsible for Basal Stem Rot disease. The disease is extremely serious and easily spreads, posing a significant threat to the economy, so early detection of the disease becomes vital. However, the current detection techniques for the disease are expensive and time-consuming; hence, they are not ideal for large plantation areas. The development of image processing technology could be utilized to predict Ganoderma infection, using the images that are captured by a drone. This research aims to predict the spread of Ganoderma infection, in the oil palm tree plantation area in North Sumatra, Indonesia, by utilizing image processing and Artificial Neural Network methods. Our model results showed the prediction accuracy (with Green color) was 73,8%. In addition, we also showed the distribution of Ganoderma infection in the area: score 0 was 229 trees, score 1 was 295 trees, score 2 was 112 trees, score 3 was 238 trees, and score 4 was 23 trees. Overall, our research provided a non-destructive method to detect Basal Stem Rot disease in the oil palm plantation sites.","PeriodicalId":44079,"journal":{"name":"Communications in Mathematical Biology and Neuroscience","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69239608","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}
: Mango's internal quality can be determined based on its acidity and sweetness in the form of pH and total soluble solids (TSS) content. Research on fruit internal quality prediction based on near-infrared spectroscopy generally uses parametric regression modeling such as linear and partial least square regression. The study proposed biresponse multipredictor local polynomial nonparametric regression to determine mango's internal quality. The study aims to apply the theory of biresponse multipredictor local polynomial nonparametric regression for predicting the mango's internal quality in the form of pH and TSS value. We created R code for estimating nonparametric
{"title":"Prediction of pH and total soluble solids content of mango using biresponse multipredictor local polynomial nonparametric regression","authors":"M. Ulya, N. Chamidah, T. Saifudin","doi":"10.28919/cmbn/7941","DOIUrl":"https://doi.org/10.28919/cmbn/7941","url":null,"abstract":": Mango's internal quality can be determined based on its acidity and sweetness in the form of pH and total soluble solids (TSS) content. Research on fruit internal quality prediction based on near-infrared spectroscopy generally uses parametric regression modeling such as linear and partial least square regression. The study proposed biresponse multipredictor local polynomial nonparametric regression to determine mango's internal quality. The study aims to apply the theory of biresponse multipredictor local polynomial nonparametric regression for predicting the mango's internal quality in the form of pH and TSS value. We created R code for estimating nonparametric","PeriodicalId":44079,"journal":{"name":"Communications in Mathematical Biology and Neuroscience","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69240961","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}
Albanus Muambi Musyoka, Marilyn Ronoh, P. Wanjau, Dominic Makaa Kitavi
,
,
{"title":"Mathematical modeling of drug abuse, unemployment and mental stress on population dynamics of mental illness","authors":"Albanus Muambi Musyoka, Marilyn Ronoh, P. Wanjau, Dominic Makaa Kitavi","doi":"10.28919/cmbn/8002","DOIUrl":"https://doi.org/10.28919/cmbn/8002","url":null,"abstract":",","PeriodicalId":44079,"journal":{"name":"Communications in Mathematical Biology and Neuroscience","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69244810","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}
This paper analyzes and examines the optimal control in the co-infection of COVID-19 with HIV/AIDS by providing preventive and treatment control measures. The population is divided into eight subpopulations. The preventive control of COVID-19 is denoted by u1. The preventive control of HIV/AIDS is denoted by u2. The treatment control of COVID-19 is denoted by u3, and the treatment control of COVID-19 for the subpopulation co-infected with HIV/AIDS is denoted by u4. Based on the model analysis, non-endemic and endemic equilibrium points are obtained, along with the basic reproduction number of the COVID-19, HIV/AIDS, and COVID-19-HIV/AIDS sub-models. Numerical simulations reveal that using preventive control u1 is more effective in reducing the spread of COVID-19 compared to u3 or u4, both individually and together. Preventive control u2 is more effective in controlling the spread of HIV/AIDS compared to the absence of control. The sensitivity analysis of parameter identifies parameters that significantly affect the reduction or increase in the spread of COVID-19-HIV/AIDS co-infection. We found that in order to reduce the co-infection’s spread, we should pay attention to the reducing the contact rate of HIV/AIDS patients or increasing their treatment rate.
{"title":"Sensitivity analysis and optimal countermeasures control of model of the spread of COVID-19 co-infection with HIV/AIDS","authors":"","doi":"10.28919/cmbn/8161","DOIUrl":"https://doi.org/10.28919/cmbn/8161","url":null,"abstract":"This paper analyzes and examines the optimal control in the co-infection of COVID-19 with HIV/AIDS by providing preventive and treatment control measures. The population is divided into eight subpopulations. The preventive control of COVID-19 is denoted by u1. The preventive control of HIV/AIDS is denoted by u2. The treatment control of COVID-19 is denoted by u3, and the treatment control of COVID-19 for the subpopulation co-infected with HIV/AIDS is denoted by u4. Based on the model analysis, non-endemic and endemic equilibrium points are obtained, along with the basic reproduction number of the COVID-19, HIV/AIDS, and COVID-19-HIV/AIDS sub-models. Numerical simulations reveal that using preventive control u1 is more effective in reducing the spread of COVID-19 compared to u3 or u4, both individually and together. Preventive control u2 is more effective in controlling the spread of HIV/AIDS compared to the absence of control. The sensitivity analysis of parameter identifies parameters that significantly affect the reduction or increase in the spread of COVID-19-HIV/AIDS co-infection. We found that in order to reduce the co-infection’s spread, we should pay attention to the reducing the contact rate of HIV/AIDS patients or increasing their treatment rate.","PeriodicalId":44079,"journal":{"name":"Communications in Mathematical Biology and Neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135401837","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}
This study aims to identify the best model for the stunting rate by applying and comparing several methods based on the Tobit quantile regression method's modification. The stunting rate dataset is left censored and violated with linear model assumptions; thus, Tobit quantile approaches are used. The Tobit quantile regression is adjusted by combining it with the Bayesian approach since the Bayesian method can produce the best model in small-size samples. Three kinds of modified Tobit quantile regression methods considered here are the Bayesian Tobit quantile regression, the Bayesian Adaptive Lasso Tobit quantile regression, and the Bayesian Lasso Tobit quantile regression. This article implements the skewed Laplace distribution as the likelihood function in Bayesian analysis. This study used the data of 3534 stunting children obtained from the Health Departments of several districts and municipals in West Sumatra, Indonesia. The result of this study indicated that Bayesian Lasso quantile regression performed well compared to the other two methods. Criteria of better method are based on a smaller absolute bias and a shorter Bayesian credible interval which are obtained from the simulation study and empirical study. This study also found that exclusive breastfeeding give impact to stunting rate only at middle quantiles, while comorbidity tend to affect all distribution of stunting rate.
{"title":"Bayesian regularized tobit quantile to construct stunting rate model","authors":"","doi":"10.28919/cmbn/7976","DOIUrl":"https://doi.org/10.28919/cmbn/7976","url":null,"abstract":"This study aims to identify the best model for the stunting rate by applying and comparing several methods based on the Tobit quantile regression method's modification. The stunting rate dataset is left censored and violated with linear model assumptions; thus, Tobit quantile approaches are used. The Tobit quantile regression is adjusted by combining it with the Bayesian approach since the Bayesian method can produce the best model in small-size samples. Three kinds of modified Tobit quantile regression methods considered here are the Bayesian Tobit quantile regression, the Bayesian Adaptive Lasso Tobit quantile regression, and the Bayesian Lasso Tobit quantile regression. This article implements the skewed Laplace distribution as the likelihood function in Bayesian analysis. This study used the data of 3534 stunting children obtained from the Health Departments of several districts and municipals in West Sumatra, Indonesia. The result of this study indicated that Bayesian Lasso quantile regression performed well compared to the other two methods. Criteria of better method are based on a smaller absolute bias and a shorter Bayesian credible interval which are obtained from the simulation study and empirical study. This study also found that exclusive breastfeeding give impact to stunting rate only at middle quantiles, while comorbidity tend to affect all distribution of stunting rate.","PeriodicalId":44079,"journal":{"name":"Communications in Mathematical Biology and Neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136202752","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}
In this paper, we propose and analyze the dynamical behavior of a delayed COVID-19 transmission model with immigration, vaccination and general incidence function. The time delay into the proposed model represents the incubation period. Firstly, the well-posedness of the model is investigated. Moreover, we construct appropriate Lyapunov function to prove the global stability of equilibria. To support the theoretical results, numerical simulations are presented at the end of the study.
{"title":"Stability analysis of a delayed COVID-19 transmission model involving immigration and vaccination","authors":"","doi":"10.28919/cmbn/8151","DOIUrl":"https://doi.org/10.28919/cmbn/8151","url":null,"abstract":"In this paper, we propose and analyze the dynamical behavior of a delayed COVID-19 transmission model with immigration, vaccination and general incidence function. The time delay into the proposed model represents the incubation period. Firstly, the well-posedness of the model is investigated. Moreover, we construct appropriate Lyapunov function to prove the global stability of equilibria. To support the theoretical results, numerical simulations are presented at the end of the study.","PeriodicalId":44079,"journal":{"name":"Communications in Mathematical Biology and Neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135909856","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}
The fishery sector has a vital role in driving Indonesia's economy. However, the supply of fish has recently begun to dwindle because of the high cost of fish and unpredictable weather changes. Because of that, this increases the demand for freshwater fish and raises the potential for freshwater aquaculture. Besides, finding suitable water, sources and farming land for fish is extremely difficult because of the limitations of the primary source. This study aims to develop an Internet of Things (IoT) that can monitor water quality parameters, including acid content, dissolved oxygen, the temperature of the water, as well as ammonia, and is integrated with Internet-based mobile applications. The results of the system design have been successfully implemented. The system structure has successfully incorporated a sensor that collects data from the system and sends it to the blynk cloud server, which can be accessed directly via the Internet. Furthermore, this research showed that water quality and circulation are well preserved. The sensor's accuracy of potential hydrogen (pH) acid water is an average error of 1.52%, temperature sensor error of 0.238%, dissolved oxygen sensor error of 0.23%, and ammonia sensor error of 1.723%, and the monitoring system is functioning normally.
{"title":"Water quality monitoring system for aquaponic technology using the internet of things (IoT)","authors":"","doi":"10.28919/cmbn/8221","DOIUrl":"https://doi.org/10.28919/cmbn/8221","url":null,"abstract":"The fishery sector has a vital role in driving Indonesia's economy. However, the supply of fish has recently begun to dwindle because of the high cost of fish and unpredictable weather changes. Because of that, this increases the demand for freshwater fish and raises the potential for freshwater aquaculture. Besides, finding suitable water, sources and farming land for fish is extremely difficult because of the limitations of the primary source. This study aims to develop an Internet of Things (IoT) that can monitor water quality parameters, including acid content, dissolved oxygen, the temperature of the water, as well as ammonia, and is integrated with Internet-based mobile applications. The results of the system design have been successfully implemented. The system structure has successfully incorporated a sensor that collects data from the system and sends it to the blynk cloud server, which can be accessed directly via the Internet. Furthermore, this research showed that water quality and circulation are well preserved. The sensor's accuracy of potential hydrogen (pH) acid water is an average error of 1.52%, temperature sensor error of 0.238%, dissolved oxygen sensor error of 0.23%, and ammonia sensor error of 1.723%, and the monitoring system is functioning normally.","PeriodicalId":44079,"journal":{"name":"Communications in Mathematical Biology and Neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135448481","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":"Phytoplankton diffusive model with pulse and viral infection","authors":"","doi":"10.28919/cmbn/3807","DOIUrl":"https://doi.org/10.28919/cmbn/3807","url":null,"abstract":"","PeriodicalId":44079,"journal":{"name":"Communications in Mathematical Biology and Neuroscience","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69226905","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：