KMITL

Permanent URI for this communityhttps://dspace.kmitl.ac.th/handle/kmitl/1

Browse

Settings

Access type: UnknownAuthor: search.filters.author.Lenbury, Yongwimon

Search Results

Now showing 1 - 4 of 4
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Mathematical modeling of infectious disease transmission in macroalgae
    (2017-12-01)
    Nokkaew, Artorn
    ;
    Modchang, Charin
    ;
    Amornsamankul, Somkid
    ;
    Lenbury, Yongwimon
    ;
    Pimpunchat, Busayamas
    Understanding the infectious diseases outbreak of algae can provide significant knowledge for disease control intervention and/or prevention. We consider here a disease caused by highly pathogenic organisms that can result in the death of algae. Even though a great deal of understanding about diseases of algae has been reached, studies concerning effects of the outbreak at the population level are still rare. For this reason, we computationally model an outbreak in the algae reservoir or container systems consisting of several patches or clusters of algae being infected with a contagious infectious disease. We computationally investigate the systems as well as make some predictions via the deterministic SEIR epidemic model. We consider the factors that could affect the spread of the disease including the number of patches, the size of initial infected population, the distance between patches or spatial range, and the basic reproduction number (R<inf>0</inf>). The results provide some information that may be beneficial to algae disease control, intervention or prevention.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Approximate solutions and parameter estimations of G-protein coupled receptor signal transduction model
    (2013-02-20)
    Modchang, Charin
    ;
    Pimpunchat, Busayamas
    ;
    Lenbury, Yongwimon
    ;
    Triampo, Wannapong
    We find approximate analytical solutions of a model for the signal transduction mediated by the G-protein coupled receptor proposed earlier by Modchang et al. The time evolution of the approximate solutions will be explored and compared with numerical solutions of the model. Moreover, an alternative procedure for estimating unknown parameters in the model has been proposed. This alternative parameter estimation method directly uses the exact equilibrium solutions for fitting with the experimental data. We found that this new parameter estimation method can estimate unknown parameter values faster than the method used in previous works. © 2013 Pushpa Publishing House.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Modeling and optimization of G-protein coupled receptor signal transduction
    (2011-06-01)
    Modchang, Charin
    ;
    Pimpunchat, Busayamas
    ;
    Triampo, Wannapong
    ;
    Triampo, Darapond
    ;
    Lenbury, Yongwimon
    Signal transduction is the process by which a cell converts one kind of signal or stimulus into another. In this process, G-protein coupled receptors (GPCRs) are considered a major class of membrane protein receptors. GPCRs play a critical role in signal transduction, and they are important pharmacological drug targets. Motivated by some specific experimental data, we construct a mathematical model to investigate a signaling system of interest. The model is composed of mass-action ordinary differential equations that describe ligand-receptor and receptor- G-protein interactions. Because the kinetic reaction rates in the signaling processes previously gathered in reliable in vivo and in vitro experiments are limited to a small number of known values, we apply a genetic algorithm (GA) to estimate the parameter values in our model. In order to carry out the parameter estimation, we use the Augmented Lagrangian Genetic Algorithm (ALGA) with help from the mathematical theorem of infinite norm. This method ensures a faster parameter estimation speed in the modeled system. In addition, mathematical analyses are also performed. Some good agreement between analytic, numerical and experimental data was found. The simulation results of the model are extensively discussed and compared with the experimental data. © 2011 Pushpa Publishing House.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Modelling glucose-insulin feedback signal interchanges involving β-cells with delays
    (2008-01-01)
    Sarika, Warunee
    ;
    Lenbury, Yongwimon
    ;
    Kumnungkit, Kanchana
    ;
    Kunphasuruang, Wannapa
    In this paper, we studied a mathematical model system of delay-differential equations which describe the dynamic behavior of the glucose-insulin feedback system which involved β-cells, incorporating two time delays, one being the glucose triggered insulin production delay τ<inf>g</inf>, and the other being the hepatic glucose delay τ<inf>i</inf>. This secretory mechanism was governed by nonlinear and time-delayed feedforward and feedback signal interchanges. Moreover, delayed responses to the changes in β-cell density were incorporated. The model system was analyzed to investigate the effect of delays on the dynamic behavior of the system and the possibility of periodic solution which simulate sustained oscillations frequently observed in the experiments.