{"title":"Vertical Transmission of HIV-HBV Co-infection with Liquor Habit and Vaccination","authors":"N. H. Shah, Z. A. Patel, B. M. Yeolekar","doi":"10.47836/mjms.16.1.10","DOIUrl":"https://doi.org/10.47836/mjms.16.1.10","url":null,"abstract":"In this paper, the transmission of HIV-HBV co-infection is carried out. The individuals who are infected with both diseases HIV and HBV simultaneously, are said to be HIV-HBV co-infected. These infected individuals have high risk of liver failure. It is the main cause for serious liver complications like cirrhosis and liver cancer at younger age. A deterministic model is considered with liquor habit in men and vaccination to new-borns and carrier mother. Carrier class results in the vertical transmission. In this paper, the transmission dynamics of the model is analyzed. The total population is divided in to twenty eight class viz. Susceptible, HBV Vaccinated, HBV-infected female, HBV-carrier female, HBV infected alcoholic male, HBV carrier alcoholic male, HBV infected non-alcoholic male, HBV carrier non-alcoholic male, HBV recovered class, pre-AIDS female, AIDS female, pre-AIDS-HBV co-infected female, AIDS-HBV co-infected female, pre-AIDS-HBV carrier female, AIDS-HBV carrier female, pre-AIDS alcoholic male, AIDS alcoholic male, pre-AIDS non-alcoholic male, AIDS non-alcoholic male, pre-AIDS-HBV co-infected alcoholic male, pre-AIDS-HBV co-infected non-alcoholic male, pre-AIDS-HBV carrier alcoholic male, pre-AIDS-HBV carrier non-alcoholic male, AIDS-HBV co-infected alcoholic male, AIDS-HBV co-infected non-alcoholic male, AIDS-HBV carrier non-alcoholic male, HIV infected -HBV recovered classes. The basic reproduction numbers for HIV, for HBV and for HIV-HBV are found using next generation matrix. Local and global stability of HIV-HBV disease free equilibrium is worked out. Model is validated with the numerical simulation.","PeriodicalId":43645,"journal":{"name":"Malaysian Journal of Mathematical Sciences","volume":" ","pages":""},"PeriodicalIF":0.5,"publicationDate":"2022-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41867671","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":"Hermite-Hadamard Fejér Inequalities for Fractional Integrals for Functions Whose Second-Order Mixed Derivatives are Coordinated Preinvex","authors":"S. Mehmood, F. Zafar, H. Humza, A. Rasheed","doi":"10.47836/mjms.16.1.12","DOIUrl":"https://doi.org/10.47836/mjms.16.1.12","url":null,"abstract":"The main aim of this article is to establish some new refinements of Hermite Hadmard type inequalities via coordinate preinvex functions for fractional integrals. Here we give special cases to our results.","PeriodicalId":43645,"journal":{"name":"Malaysian Journal of Mathematical Sciences","volume":" ","pages":""},"PeriodicalIF":0.5,"publicationDate":"2022-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42167088","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}
Kho L. C., Kasihmuddin M. S. M., Mansor M. A., Sathasivam S.
{"title":"Propositional Satisfiability Logic via Ant Colony Optimization in Hopfield\u0000Neural Network","authors":"Kho L. C., Kasihmuddin M. S. M., Mansor M. A., Sathasivam S.","doi":"10.47836/mjms.16.1.04","DOIUrl":"https://doi.org/10.47836/mjms.16.1.04","url":null,"abstract":"Minimizing the cost function that corresponds to propositional logic is vital to ensure the learning phase of HNN can occur optimally. In that regard, optimal and non-biased algorithm is required to ensure HNN will always converge to global solution. Ant Colony Optimization (ACO) is a population-based and nature-inspired algorithm to solve various combinatorial optimization problems. ACO simulates the behaviour of the real ants that forage for food and communication of ants through pheromone density. In this work, ACO will be used to minimize the cost function that corresponds to the logical rule in Hopfield Neural Network. ACO will utilize pheromone density to find the optimal path that leads to zero cost function without consuming more learning iteration. Performance for all learning models will be evaluated based on various performance metrics. Results collected from computer simulation implies that ACO outperformed conventional learning model in minimizing the logical cost function.","PeriodicalId":43645,"journal":{"name":"Malaysian Journal of Mathematical Sciences","volume":" ","pages":""},"PeriodicalIF":0.5,"publicationDate":"2022-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46266594","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}