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Fixed points in conjunctive networks and maximal independent sets in graph contractions
(2017)
Given a graph G, viewed as a loop-less symmetric digraph, we study the maximum number of fixed points in a conjunctive boolean network with G as interaction graph. We prove that if G has no induced C-4, then this quantity ...
Counting independent sets in amenable groups
(2023)
Given a locally finite graph Γ, an amenable subgroup G of graph automorphisms acting freely and almost transitively on its vertices, and a G-invariant activity function λ, consider the free energy fG(Γ,λ) of the hardcore ...
On Riesz transforms and maximal functions in the context of Gaussian harmonic analysis
(American Mathematical Society, 2007-12)
The purpose of this paper is twofold. We introduce a general maximal function on the Gaussian setting which dominates the Ornstein-Uhlenbeck maximal operator and prove its weak type by using a covering lemma which is ...
Model sets with Euclidean internal space
(2023)
We give a characterization of inter-model sets with Euclidean internal space. This characterization is similar to previous results for general inter-model sets obtained independently by Baake, Lenz and Moody, and Aujogue. ...
Un algoritmo paralelo para el problema del conjunto independiente
(Universidad de Costa Rica, Centro de Investigación en Matemática Pura y Aplicada (CIMPA), 2000)
Physiological responses at maximal aerobic swimming pacing in different distance-trials
(Univ Alicante, 2019-01-01)
The aim of this study was to analyse the physiological responses of swimmers while performing different swimming distances at the maximal aerobic velocity (MAV) in order to understand the swimmers physiological impact along ...
Colouring Clique-Hypergraphs of Circulant Graphs
(Springer Japan KkTokyoJapão, 2013)
Objective and subjective prior distributions for the gompertz distribution
(2018-07-01)
This paper takes into account the estimation for the unknown parameters of the Gompertz distribution from the frequentist and Bayesian view points by using both objective and subjective prior distributions. We first derive ...