Muhafzan, Narwen Ahmad Iqbal Baqi Zulakmal, A. G. Lestari, M. Oktaviani
. This work presents a fractional SITR mathematical model that investigates the Tuberculosis (TB) spread in a human population. It was shown that disease-free and endemic equilibrium stability depended on the basic reproduction number. These results are in accordance with the epidemic theory. A numerical example is given to demonstrate the validity of the results. The results show that the infected subpopulation increases in the absence of special treatment
{"title":"A fractional SITR model for dynamic of tuberculosis spread","authors":"Muhafzan, Narwen Ahmad Iqbal Baqi Zulakmal, A. G. Lestari, M. Oktaviani","doi":"10.28919/cmbn/7864","DOIUrl":"https://doi.org/10.28919/cmbn/7864","url":null,"abstract":". This work presents a fractional SITR mathematical model that investigates the Tuberculosis (TB) spread in a human population. It was shown that disease-free and endemic equilibrium stability depended on the basic reproduction number. These results are in accordance with the epidemic theory. A numerical example is given to demonstrate the validity of the results. The results show that the infected subpopulation increases in the absence of special treatment","PeriodicalId":44079,"journal":{"name":"Communications in Mathematical Biology and Neuroscience","volume":"1 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69239041","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 current investigation focuses on the dynamics of a discrete-time predator-prey system with additive Allee effect. Discretization is accomplished by the use of a piecewise constant argument approach of differential equations. Firstly, we studied the existence and topological classification of equilibrium points. We then investigated existence and direction of period-doubling and Neimark-Sacker bifurcations in the system. Moreover, to control the chaos caused by bifurcation, we employ a hybrid control technique. Finally, all theoretical results are justified numerically
{"title":"Stability, bifurcation, and chaos control of predator-prey system with additive Allee effect","authors":"R. Ahmed, S. Akhtar, U. Farooq, S. Ali","doi":"10.28919/cmbn/7824","DOIUrl":"https://doi.org/10.28919/cmbn/7824","url":null,"abstract":". The current investigation focuses on the dynamics of a discrete-time predator-prey system with additive Allee effect. Discretization is accomplished by the use of a piecewise constant argument approach of differential equations. Firstly, we studied the existence and topological classification of equilibrium points. We then investigated existence and direction of period-doubling and Neimark-Sacker bifurcations in the system. Moreover, to control the chaos caused by bifurcation, we employ a hybrid control technique. Finally, all theoretical results are justified numerically","PeriodicalId":44079,"journal":{"name":"Communications in Mathematical Biology and Neuroscience","volume":"423 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69239113","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}
U. Tonggumnead, Kittipong Klinjan, Ekapak Tanprayoon, S. Aryuyuen
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{"title":"A four-parameter negative binomial-Lindley regression model to analyze factors influencing the number of cancer deaths using Bayesian inference","authors":"U. Tonggumnead, Kittipong Klinjan, Ekapak Tanprayoon, S. Aryuyuen","doi":"10.28919/cmbn/7933","DOIUrl":"https://doi.org/10.28919/cmbn/7933","url":null,"abstract":",","PeriodicalId":44079,"journal":{"name":"Communications in Mathematical Biology and Neuroscience","volume":"1 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69240276","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}
Anna Islamiyati, M. Zakir, Ummi Sari, Dewi Sartika, Salam
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{"title":"The use of the binary spline logistic regression model on the nutritional status data of children","authors":"Anna Islamiyati, M. Zakir, Ummi Sari, Dewi Sartika, Salam","doi":"10.28919/cmbn/7935","DOIUrl":"https://doi.org/10.28919/cmbn/7935","url":null,"abstract":",","PeriodicalId":44079,"journal":{"name":"Communications in Mathematical Biology and Neuroscience","volume":"1 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69240732","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}
. To understand cancer as a biomathematical process, we establish our model to give an analytical and a numerical examination of the fractional derivative impact on developing breast cancer with endocrine diet therapy and immunotherapy. So, we try, in this paper, to formulate the cancer dynamics involving the normal cells, tumor cells, immune cells, estrogen (endocrine parameter) and immunotherapy. We show the wellposedness of the breast cancer model and we analyze the existence and the stability of the equilibria, then, we discuss the numerical results in order to conclude that the use of fractional derivatives provides more useful information about the stability of the breast cancer dynamics with mixed treatments model.
{"title":"Fractional mathematical model underlying mixed treatments using endocrine diet therapy and immunotherapy for breast cancer","authors":"M. Elkaf, K. Allali","doi":"10.28919/cmbn/8036","DOIUrl":"https://doi.org/10.28919/cmbn/8036","url":null,"abstract":". To understand cancer as a biomathematical process, we establish our model to give an analytical and a numerical examination of the fractional derivative impact on developing breast cancer with endocrine diet therapy and immunotherapy. So, we try, in this paper, to formulate the cancer dynamics involving the normal cells, tumor cells, immune cells, estrogen (endocrine parameter) and immunotherapy. We show the wellposedness of the breast cancer model and we analyze the existence and the stability of the equilibria, then, we discuss the numerical results in order to conclude that the use of fractional derivatives provides more useful information about the stability of the breast cancer dynamics with mixed treatments model.","PeriodicalId":44079,"journal":{"name":"Communications in Mathematical Biology and Neuroscience","volume":"1 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69245660","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":"Delay in eco-epidemiological prey-predator model with predation fear and hunting cooperation","authors":"K. Q. Al-Jubouri, R. K. Naji, 𝑎, 𝐷, 𝑏","doi":"10.28919/cmbn/8081","DOIUrl":"https://doi.org/10.28919/cmbn/8081","url":null,"abstract":",","PeriodicalId":44079,"journal":{"name":"Communications in Mathematical Biology and Neuroscience","volume":"1 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69246156","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}
Brilyan Nathanael, Rumahorbo, Kenjovan Nanggala, G. N. Elwirehardja, B. Pardamean
. Major Depressive Disorder (MDD) has been known as one of the most prevalent mental disorders whose symptoms can be observed from changes in facial behaviors. Previous studies had attempted to build Machine Learning (ML) models to assess depression severity using such features but few have utilized these models to determine key facial behaviors for MDD. In this study, we used video data to assess the severity of MDD and determine important features based on three approaches (XGBoost, Spearman’s correlation, and t-test). In addition, there is the Facial Action Coding System (FACS) framework that allows visual data such as changes in facial behavior to be modeled as time series data. The results show that the XGBoost model obtained the best results when trained using features selected through the t-test statistical method with 5.387 MAE, 6.266 RMSE, and 0.042 R 2 . The majority of the important features consist of Action Unit (AU) and Features 3D around the regions of the left eye, right cheek, and lip area. However, the majority of the important features discovered from the three approaches, are the first derivatives of the 3D facial landmark coordinates of the cheeks, eyes, and ∗ Corresponding
{"title":"Analyzing important statistical features from facial behavior in human depression using XGBoost","authors":"Brilyan Nathanael, Rumahorbo, Kenjovan Nanggala, G. N. Elwirehardja, B. Pardamean","doi":"10.28919/cmbn/7916","DOIUrl":"https://doi.org/10.28919/cmbn/7916","url":null,"abstract":". Major Depressive Disorder (MDD) has been known as one of the most prevalent mental disorders whose symptoms can be observed from changes in facial behaviors. Previous studies had attempted to build Machine Learning (ML) models to assess depression severity using such features but few have utilized these models to determine key facial behaviors for MDD. In this study, we used video data to assess the severity of MDD and determine important features based on three approaches (XGBoost, Spearman’s correlation, and t-test). In addition, there is the Facial Action Coding System (FACS) framework that allows visual data such as changes in facial behavior to be modeled as time series data. The results show that the XGBoost model obtained the best results when trained using features selected through the t-test statistical method with 5.387 MAE, 6.266 RMSE, and 0.042 R 2 . The majority of the important features consist of Action Unit (AU) and Features 3D around the regions of the left eye, right cheek, and lip area. However, the majority of the important features discovered from the three approaches, are the first derivatives of the 3D facial landmark coordinates of the cheeks, eyes, and ∗ Corresponding","PeriodicalId":44079,"journal":{"name":"Communications in Mathematical Biology and Neuroscience","volume":"1 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69240007","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}
Sifriyani, AR Rum, Mia Sari, Andrea Tri, Rian Dani, S. Jalaluddin
: This article discusses statistical modeling implemented in the health sector. This study used a bi-response nonparametric regression method with truncated spline estimation that used two response variables. The nonparametric regression method is used when the regression curve is not known for its shape and pattern. This study aims to model the blood sugar levels of people with diabetes mellitus. The data used are blood sugar levels of people with diabetes mellitus before fasting, blood sugar levels of people with diabetes mellitus two hours after fasting, cholesterol levels, and triglyceride levels. Determination of the optimal knot point using Generalized Cross-Validation. The parameter estimation method used is Weighted Least-Squares. The best model was obtained from the study results,
{"title":"Bi-response truncated spline nonparametric regression with optimal knot point selection using generalized cross-validation in diabetes mellitus patient's blood sugar levels","authors":"Sifriyani, AR Rum, Mia Sari, Andrea Tri, Rian Dani, S. Jalaluddin","doi":"10.28919/cmbn/7903","DOIUrl":"https://doi.org/10.28919/cmbn/7903","url":null,"abstract":": This article discusses statistical modeling implemented in the health sector. This study used a bi-response nonparametric regression method with truncated spline estimation that used two response variables. The nonparametric regression method is used when the regression curve is not known for its shape and pattern. This study aims to model the blood sugar levels of people with diabetes mellitus. The data used are blood sugar levels of people with diabetes mellitus before fasting, blood sugar levels of people with diabetes mellitus two hours after fasting, cholesterol levels, and triglyceride levels. Determination of the optimal knot point using Generalized Cross-Validation. The parameter estimation method used is Weighted Least-Squares. The best model was obtained from the study results,","PeriodicalId":44079,"journal":{"name":"Communications in Mathematical Biology and Neuroscience","volume":"1 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69239219","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}
. Medical treatment, vaccination, and quarantine are the most efficacious controls in preventing the spread of contagious epidemics such as COVID-19. In this paper, we demonstrate the global stability of the endemic and disease-free equilibrium by using the Lyapunov function. Moreover, we apply the three measures to minimize the density of infected people and also reduce the cost of controls. Furthermore, we use the Pontryagin Minimum Principle in order to characterize the optimal controls. Finally, we execute some numerical simulations to approve and verify our theoretical results using the fourth order Runge-Kutta approximation through Matlab
{"title":"Optimal control and global stability of the SEIQRS epidemic model","authors":"M. Azoua, A. Azouani, I. Hafidi","doi":"10.28919/cmbn/7880","DOIUrl":"https://doi.org/10.28919/cmbn/7880","url":null,"abstract":". Medical treatment, vaccination, and quarantine are the most efficacious controls in preventing the spread of contagious epidemics such as COVID-19. In this paper, we demonstrate the global stability of the endemic and disease-free equilibrium by using the Lyapunov function. Moreover, we apply the three measures to minimize the density of infected people and also reduce the cost of controls. Furthermore, we use the Pontryagin Minimum Principle in order to characterize the optimal controls. Finally, we execute some numerical simulations to approve and verify our theoretical results using the fourth order Runge-Kutta approximation through Matlab","PeriodicalId":44079,"journal":{"name":"Communications in Mathematical Biology and Neuroscience","volume":"1 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69239509","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}
A. Dani, Meirinda Fauziyah, M. N. Hayati, Sri Wahyuningsih, Surya Prangga
: This article discusses statistical innovations implemented in the health sector. The research is being conducted on the treatment and prevention of Dengue Hemorrhagic Fever (DHF), focusing on the factors contributing to the increase in DHF. Create a nonparametric regression model with a mixed estimator, truncated spline
{"title":"Spline and kernel mixed estimators in multivariable nonparametric regression for dengue hemorrhagic fever model","authors":"A. Dani, Meirinda Fauziyah, M. N. Hayati, Sri Wahyuningsih, Surya Prangga","doi":"10.28919/cmbn/7790","DOIUrl":"https://doi.org/10.28919/cmbn/7790","url":null,"abstract":": This article discusses statistical innovations implemented in the health sector. The research is being conducted on the treatment and prevention of Dengue Hemorrhagic Fever (DHF), focusing on the factors contributing to the increase in DHF. Create a nonparametric regression model with a mixed estimator, truncated spline","PeriodicalId":44079,"journal":{"name":"Communications in Mathematical Biology and Neuroscience","volume":"1 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69238275","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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