Mathematical modeling of tumor therapy with oncolytic viruses: Effects of parametric heterogeneity on cell dynamics

One of the mechanisms that ensure cancer robustness is tumor heterogeneity, and its effects on tumor cells dynamics have to be taken into account when studying cancer progression. There is no unifying theoretical framework in mathematical modeling of carcinogenesis that would account for parametric heterogeneity. Here we formulate a modeling approach that naturally takes stock of inherent cancer cell heterogeneity and illustrate it with a model of interaction between a tumor and an oncolytic virus. We show that several phenomena that are absent in homogeneous models, such as cancer recurrence, tumor dormancy, an others, appear in heterogeneous setting. We also demonstrate that, within the applied modeling framework, to overcome the adverse effect of tumor cell heterogeneity on cancer progression, a heterogeneous population of an oncolytic virus must be used. Heterogeneity in parameters of the model, such as tumor cell susceptibility to virus infection and virus replication rate, can lead to complex, time-dependent behaviors of the tumor. Thus, irregular, quasi-chaotic behavior of the tumor-virus system can be caused not only by random perturbations but also by the heterogeneity of the tumor and the virus. The modeling approach described here reveals the importance of tumor cell and virus heterogeneity for the outcome of cancer therapy. It should be straightforward to apply these techniques to mathematical modeling of other types of anticancer therapy.Comment: 45 pages, 6 figures; submitted to Biology Direc

Lie series for celestial mechanics, accelerators, satellite stabilization and optimization

Lie series applications to celestial mechanics, accelerators, satellite orbits, and optimizatio

Finite volume solution of the compressible boundary-layer equations

A box-type finite volume discretization is applied to the integral form of the compressible boundary layer equations. Boundary layer scaling is introduced through the grid construction: streamwise grid lines follow eta = y/h = const., where y is the normal coordinate and h(x) is a scale factor proportional to the boundary layer thickness. With this grid, similarity can be applied explicity to calculate initial conditions. The finite volume method preserves the physical transparency of the integral equations in the discrete approximation. The resulting scheme is accurate, efficient, and conceptually simple. Computations for similar and non-similar flows show excellent agreement with tabulated results, solutions computed with Keller's Box scheme, and experimental data

Computer algebra techniques in object-oriented mathematical modelling.

This thesis proposes a rigorous object-oriented methodology, supported by computer algebra software, to generate and relate features in a mathematical model. Evidence shows that there is little heuristic or theoretical research into this problem from any of the three principal modelling methodologies: 'case study’, ‘scenario’ and ‘generic’. This thesis comprises two other major strands: applications of computer algebra software and the efficacy of symbolic computation in teaching and learning. Developing the principal algorithms in computer algebra has sometimes been done at the expense of ease of use. Developers have also not concentrated on integrating an algebra engine into other software. A thorough review of quantitative studies in teaching and learning mathematics highlights a serious difficulty in measuring the effect of using computer algebra. This arises because of the disparate nature of learning with and without a computer. This research tackles relationship formulation by casting the problem domain into object-oriented terms and building an appropriate class hierarchy. This capitalises on the fact that specific problems are instances of generic problems involving prototype physical objects. The computer algebra facilitates calculus operations and algebraic manipulation. In conjunction, I develop an object-oriented design methodology applicable to small-scale mathematical modelling. An object model modifies the generic modelling cycle. This allows relationships between features in the mathematical model to be generated automatically. The software is validated by quantifying the benefits of using the object-oriented techniques, and the results are statistically significant. The principal problem domain considered is Newtonian particle mechanics. Although the Newtonian axioms form a firm basis for a mathematical description of interactions between physical objects, applying them within a particular modelling context can cause problems. The goal is to produce an equation of motion. Applications to other contexts are also demonstrated. This research is significant because it formalises feature and equation-generation in a novel way. A new modelling methodology ensures that this crucial stage in the modelling cycle is given priority and automated

Investigation of Transient MHD Couette flow and Heat Transfer of Dusty Fluid with Temperature-Dependent Oroperties

In the present study, transient MHD Couette flow and heat transfer of dusty fluid between two parallel plates and the effect of the temperature dependent properties has been investigated. The thermal conductivity and viscosity of the fluid are assumed as linear and exponential functions of temperature, respectively. A constant pressure gradient and an external uniform magnetic field are considered in the main flow direction and perpendicular to the plates, respectively. A hybrid treatment based on finite difference method (FDM) and differential transform method (DTM) is used to solve the coupled flow and heat transfer equations. The effects of the variable properties, Hartman number, Hall current, Reynolds number and suction velocity on the Nusselt number and skin friction factor have been discussed. It is found that when Hartman number increases, skin friction of the upper and lower plates increases

Modeling of systems

The handbook contains the fundamentals of modeling of complex systems. The classification of mathematical models is represented and the methods of their construction are given. The analytical modeling of the basic types of processes in the complex systems is considered. The principles of simulation, statistical and business processes modeling are described. The handbook is oriented on students of higher education establishments that obtain a degree in directions of “Software engineering” and “Computer science” as well as on lecturers and specialists in the domain of computer modeling

Elastodynamic modeling of fluid-loaded cylindrical shells with multiple layers and internal attachments

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Ocean Engineering, 1994.Includes bibliographical references (175-181).by David C. Ricks.Ph.D

Scalability of preconditioners as a strategy for parallel computation of compressible fluid flow

Parallel implementations of a Newton-Krylov-Schwarz algorithm are used to solve a model problem representing low Mach number compressible fluid flow over a backward-facing step. The Mach number is specifically selected to result in a numerically {open_quote}stiff{close_quotes} matrix problem, based on an implicit finite volume discretization of the compressible 2D Navier-Stokes/energy equations using primitive variables. Newton`s method is used to linearize the discrete system, and a preconditioned Krylov projection technique is used to solve the resulting linear system. Domain decomposition enables the development of a global preconditioner via the parallel construction of contributions derived from subdomains. Formation of the global preconditioner is based upon additive and multiplicative Schwarz algorithms, with and without subdomain overlap. The degree of parallelism of this technique is further enhanced with the use of a matrix-free approximation for the Jacobian used in the Krylov technique (in this case, GMRES(k)). Of paramount interest to this study is the implementation and optimization of these techniques on parallel shared-memory hardware, namely the Cray C90 and SGI Challenge architectures. These architectures were chosen as representative and commonly available to researchers interested in the solution of problems of this type. The Newton-Krylov-Schwarz solution technique is increasingly being investigated for computational fluid dynamics (CFD) applications due to the advantages of full coupling of all variables and equations, rapid non-linear convergence, and moderate memory requirements. A parallel version of this method that scales effectively on the above architectures would be extremely attractive to practitioners, resulting in efficient, cost-effective, parallel solutions exhibiting the benefits of the solution technique