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Displaying 1041 –
1060 of
1854
We present two simple models describing relations between heterotrophic and autotrophic organisms in the land and water environments. The models are based on the Dawidowicz & Zalasiński models but we assume the boundedness of the oxygen resources. We perform a basic mathematical analysis of the models. The results of the analysis are complemented by numerical illustrations.
Bacillus subtilis swarms rapidly over the surface of a synthetic medium
creating remarkable hyperbranched dendritic communities. Models to reproduce such effects
have been proposed under the form of parabolic Partial Differential Equations representing
the dynamics of the active cells (both motile and multiplying), the passive cells
(non-motile and non-growing) and nutrient concentration. We test the numerical behavior of
such models and compare...
Molecular motors are nano- or colloidal machines that keep the living cell in a highly ordered, stationary state far from equilibrium. This self-organized order is sustained by the energy transduction of the motors, which couple exergonic or 'downhill' processes to endergonic or 'uphill' processes. A particularly interesting case is provided by the chemomechanical coupling of cytoskeletal motors which use the chemical energy released during ATP hydrolysis in order to generate mechanical forces and...
Mathematics Subject Classification: 65C05, 60G50, 39A10, 92C37In this paper the multi-dimensional Monte-Carlo random walk simulation
models governed by distributed fractional order differential equations
(DODEs) and multi-term fractional order differential equations are constructed.
The construction is based on the discretization leading to a generalized
difference scheme (containing a finite number of terms in the time
step and infinite number of terms in the space step) of the Cauchy problem
for...
Low dimensional ODE approximations that capture the main characteristics of SIS-type epidemic propagation along a cycle graph are derived. Three different methods are shown that can accurately predict the expected number of infected nodes in the graph. The first method is based on the derivation of a master equation for the number of infected nodes. This uses the average number of SI edges for a given number of the infected nodes. The second approach is based on the observation that the epidemic...
Artists have long recognized that trees are self-similar across enormous differences in magnitudes; i.e., they share a common fractal structure - a trunk subdivides into branches which subdivide into more branches which eventually terminate in leaves, flowers, fruits, etc. Artistid Lindenmayer (1971, 1975, 1989, 1990) invented a mathematics based on graph grammar rewriting systems to describe such iteratively branching structures; these were named in honor of him and are referred to as L-systems....
In this paper, we introduce several system theoretic problems brought forward by recent studies on neural models of motor control. We focus our attention on three topics: (i) the cerebellum and adaptive control, (ii) reinforcement learning and the basal ganglia, and (iii) modular control with multiple models. We discuss these subjects from both neuroscience and systems theory viewpoints with the aim of promoting interplay between the two research communities.
This study presents a numerical investigation of basic interactions between respiratory
mucus motion, air circulation and epithelium ciliated cells vibration. One focuses on
identification of meaningful rheological parameters, physiological and numerical
simulation dimensioning. These preliminary results are crucial before the study of more
general configurations of respiratory mucus motion. The numerical study presented in this
work aims at providing...
Blur is a common problem that limits the effective resolution of many imaging systems. In this article, we give a general overview of methods that can be used to reduce the blur. This includes the classical multi-channel deconvolution problems as well as challenging extensions to spatially varying blur. The proposed methods are formulated as energy minimization problems with specific regularization terms on images and blurs. Experiments on real data illustrate very good and stable performance of...
Multi-scale modeling plays an important role in understanding the structure and biological functionalities of large biomolecular complexes. In this paper, we present an efficient computational framework to construct multi-scale models from atomic resolution data in the Protein Data Bank (PDB), which is accelerated by multi-core CPU and programmable Graphics Processing Units (GPU). A multi-level summation of Gaussian kernel functions is employed to generate implicit models for biomolecules. The coefficients...
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