Lag and generation times for the growth of Salmonella typhimurium on sterile lean beef were modeled as functions of cooling time under various carcass-chilling scenarios. Gompertz growth models were fit to the log10 colony counts over time at each of six temperatures in the range of 15 to 40 degrees C. Lag and generation times were defined as the points at which the second and first derivatives...

Coming out from the growth kinetics, the Gompertz model has been developed and considered as the best one for simulating the biogas production from anaerobic digestion. However, the model has failed to describe the starting point of the process, and no-sense of lag phase constant has been pointed out. Thus, the goal of this study is to develop a new kinetic model of biogas production with meani...

This study examines the mathematical characteristics of logistic, generalized logistic and Gompertz growth function used in human population analysis. When a is mathematically modeled, it starts with differential equations considered as preliminary study. Then, general solution equation derived. method followed by mathematicians who developed these models. To prepare for study, I framework obje...

The present study investigated differences in the growth rate of multicellular tumour spheroids of the MCF-7 line of human breast cancer before and after their irradiation. Growth of the spheroids was analysed according to a model based on a Gompertz function. In this model, normalization to a common initial volume is achieved in a way that enables meaningful comparisons to be made between the ...

In clique tree clustering, inference consists of propagation in a clique tree compiled from a Bayesian network. In this paper, we develop an analytical approach to characterizing clique tree growth as a function of increasing Bayesian network connectedness, speci cally: (i) the expected number of moral edges in their moral graphs or (ii) the ratio of the number of non-root nodes to the number o...

Although Multiscale Cancer Modeling has a realistic view in the process of tumor growth, its numerical algorithm is time consuming. Therefore, it is problematic to run and to find the best treatment plan for chemotherapy, even in case of a small size of tissue. Using an artificial neural network, this paper simulates the multiscale cancer model faster than its numerical algorithm. In order to f...