Low-discrepancy point sets obtained by digital constructions over finite fields
Lower Bounds for the Discrepancy of Triples of Inversive Congruential Pseudorandom Numbers with Power of Two Modulus.
Machine fault diagnosis and condition prognosis using classification and regression trees and neuro-fuzzy inference system
Marginalization in models generated by compositional expressions
In the framework of models generated by compositional expressions, we solve two topical marginalization problems (namely, the single-marginal problem and the marginal-representation problem) that were solved only for the special class of the so-called “canonical expressions”. We also show that the two problems can be solved “from scratch” with preliminary symbolic computation.
Marginalization in multidimensional compositional models
Efficient computational algorithms are what made graphical Markov models so popular and successful. Similar algorithms can also be developed for computation with compositional models, which form an alternative to graphical Markov models. In this paper we present a theoretical basis as well as a scheme of an algorithm enabling computation of marginals for multidimensional distributions represented in the form of compositional models.
Markov chain small-world model with asymmetric transition probabilities.
Marsaglia's Lattice Test and Non-Linear Congruential Pseudo Random Number Generators.
Mathematical and Computational Models in Tumor Immunology
The immune system is able to protect the host from tumor onset, and immune deficiencies are accompanied by an increased risk of cancer. Immunology is one of the fields in biology where the role of computational and mathematical modeling and analysis were recognized the earliest, beginning from 60s of the last century. We introduce the two most common methods in simulating the competition among the immune system, cancers and tumor immunology strategies:...
Mathematical and numerical modeling of early atherosclerotic lesions***
This article is devoted to the construction of a mathematical model describing the early formation of atherosclerotic lesions. The early stage of atherosclerosis is an inflammatory process that starts with the penetration of low density lipoproteins in the intima and with their oxidation. This phenomenon is closely linked to the local blood flow dynamics. Extending a previous work [5] that was mainly restricted to a one-dimensional setting, we couple...
Mathematical Modeling of Leukemogenesis and Cancer Stem Cell Dynamics
The cancer stem cell hypothesis has evolved to one of the most important paradigms in biomedical research. During recent years evidence has been accumulating for the existence of stem cell-like populations in different cancers, especially in leukemias. In the current work we propose a mathematical model of cancer stem cell dynamics in leukemias. We apply the model to compare cellular properties of leukemic stem cells to those of their benign counterparts....
Mathematical modelling of angiogenesis in wound healing: Comparison of theory and experiment.
Mathematical modelling of tumour angiogenesis and the action of angiostatin as a protease inhibitor.
Mathematical modelling of tumour invasion and metastasis.
Mathematical models and numerical simulations for the P53-Mdm2 network.
Maximal association for the sum of squares of a contingency table
Mean field limit for the one dimensional Vlasov-Poisson equation
We consider systems of particles in dimension one, driven by pair Coulombian or gravitational interactions. When the number of particles goes to infinity in the so called mean field scaling, we formally expect convergence towards the Vlasov-Poisson equation. Actually a rigorous proof of that convergence was given by Trocheris in [Tro86]. Here we shall give a simpler proof of this result, and explain why it implies the so-called “Propagation of molecular chaos”. More precisely, both results will...
Mean-Square Discrepancies of the Hammersley and Zaremba Sequences for Arbitrary Radix.
Measures of pseudorandomness of finite binary lattices, I. The measures , normality
Measuring the Irreversibility of Numerical Schemes for Reversible Stochastic Differential Equations
For a stationary Markov process the detailed balance condition is equivalent to the time-reversibility of the process. For stochastic differential equations (SDE’s), the time discretization of numerical schemes usually destroys the time-reversibility property. Despite an extensive literature on the numerical analysis for SDE’s, their stability properties, strong and/or weak error estimates, large deviations and infinite-time estimates, no quantitative results are known on the lack of reversibility...
Medidas de incertidumbre asociadas a J-divergencias.
En este trabajo se presenta la familia de medidas de incertidumbre asociadas a J-divergencias, que resultan de la distancia entre una distribución y la distribución en la que todos los procesos son equiprobables. Se estudian propiedades teóricas de la familia atendiendo a la pérdida de incertidumbre, a la concavidad y a la condición de medida decisiva. Finalmente se compara a nivel muestral la medida de incertidumbre definida por la función φ(t) = -t log t con las medidas de entropía comúnmente...