Abstract: This paper presents a complete dynamic modeling
of a membrane distillation process. The model contains two
consistent dynamic models. A 2D advection-diffusion equation
for modeling the whole process and a modified heat equation
for modeling the membrane itself. The complete model describes
the temperature diffusion phenomenon across the feed, membrane,
permeate containers and boundary layers of the membrane. It gives
an online and complete temperature profile for each point in the
domain. It explains heat conduction and convection mechanisms that
take place inside the process in terms of mathematical parameters, and
justify process behavior during transient and steady state phases. The
process is monitored for any sudden change in the performance at any
instance of time. In addition, it assists maintaining production rates
as desired, and gives recommendations during membrane fabrication
stages. System performance and parameters can be optimized
and controlled using this complete dynamic model. Evolution of
membrane boundary temperature with time, vapor mass transfer along
the process, and temperature difference between membrane boundary
layers are depicted and included. Simulations were performed over
the complete model with real membrane specifications. The plots
show consistency between 2D advection-diffusion model and the
expected behavior of the systems as well as literature. Evolution
of heat inside the membrane starting from transient response till
reaching steady state response for fixed and varying times is
illustrated.
Abstract: Many digital signal processing, techniques have been used to automatically distinguish protein coding regions (exons) from non-coding regions (introns) in DNA sequences. In this work, we have characterized these sequences according to their nonlinear dynamical features such as moment invariants, correlation dimension, and largest Lyapunov exponent estimates. We have applied our model to a number of real sequences encoded into a time series using EIIP sequence indicators. In order to discriminate between coding and non coding DNA regions, the phase space trajectory was first reconstructed for coding and non-coding regions. Nonlinear dynamical features are extracted from those regions and used to investigate a difference between them. Our results indicate that the nonlinear dynamical characteristics have yielded significant differences between coding (CR) and non-coding regions (NCR) in DNA sequences. Finally, the classifier is tested on real genes where coding and non-coding regions are well known.
Abstract: Leptospirosis occurs worldwide (except the
poles of the earth), urban and rural areas, developed and
developing countries, especially in Thailand. It can be
transmitted to the human by rats through direct and indirect
ways. Human can be infected by either touching the infected rats
or contacting with water, soil containing urine from the infected
rats through skin, eyes and nose. The data of the people who
are infected with this disease indicates that most of the
patients are adults. The transmission of this disease is studied
through mathematical model. The population is separated into human
and rat. The human is divided into two classes, namely juvenile
and adult. The model equation is constructed for each class. The
standard dynamical modeling method is then used for
analyzing the behaviours of solutions. In addition, the
conditions of the parameters for the disease free and endemic
states are obtained. Numerical solutions are shown to support the
theoretical predictions. The results of this study guide the way to
decrease the disease outbreak.