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I. Fazekas

Publications and source records attributed to I. Fazekas.

3 recordsLinked to original sources

Convergence of sequences of ordered selections

In this paper, we introduce a convergence notion for ordered selections. Our convergence notion is based on subpermutation densities and convergences of the marginal distributions. A particular case of this convergence is the well-known convergence of permutation sequences. We also introduce a family of probability measures called generalized permutons. We show that in the family of generalized permutons several convergence notions are equivalent. We embed the set of ordered selections to the set of generalized permutons. We prove that any convergent sequence of ordered selections has a limit which is a generalized permuton. Moreover, any generalized permuton is the limit of a sequence of ordered selections. Our results are generalizations of well-known theorems on convergence of permutation sequences to permutons.

math.PR

A population evolution model and its applications to random networks

A general population evolution model is considered. Any individual of the population is characterized by its score. Certain general conditions are assumed concerning the number of the individuals and their scores. Asymptotic theorems are obtained for the number of individuals having some fixed score. It is proved that the score distribution is scale free. The result is applied to obtain the weight distributions of the cliques in a random graph evolution model.

math.PR

Locomotion and proliferation of glioblastoma cells in vitro: statistical evaluation of videomicroscopic observations

Long-term videomicroscopy and computer-aided statistical analysis were used to determine some characteristic parameters of in vitro cell motility and proliferation in three established cell lines derived from human glioblastoma tumors. Migration and proliferation activities were compared among the three cell lines since these are two features of tumor cells that strongly influence the progression of cancer. The results on these dynamical parameters of cell locomotion were compared to pathological data obtained by traditional methods. The data indicate that the analysis of cell motility provides more specific information and is potentially useful in diagnosis.

physics.bio-ph