36 research outputs found
Finite-size scaling considerations on the ground state microcanonical temperature in entropic sampling simulations
In this work we discuss the behavior of the microcanonical temperature
obtained by means of numerical entropic
sampling studies. It is observed that in almost all cases the slope of the
logarithm of the density of states is not infinite in the ground state,
since as expected it should be directly related to the inverse temperature
. Here we show that these finite slopes are in fact due to
finite-size effects and we propose an analytic expression for the
behavior of when . To
test this idea we use three distinct two-dimensional square lattice models
presenting second-order phase transitions. We calculated by exact means the
parameters and for the two-states Ising model and for the and
states Potts model and compared with the results obtained by entropic sampling
simulations. We found an excellent agreement between exact and numerical
values. We argue that this new set of parameters and represents an
interesting novel issue of investigation in entropic sampling studies for
different models
Analysing and controlling the tax evasion dynamics via majority-vote model
Within the context of agent-based Monte-Carlo simulations, we study the
well-known majority-vote model (MVM) with noise applied to tax evasion on
simple square lattices, Voronoi-Delaunay random lattices, Barabasi-Albert
networks, and Erd\"os-R\'enyi random graphs. In the order to analyse and to
control the fluctuations for tax evasion in the economics model proposed by
Zaklan, MVM is applied in the neighborhod of the noise critical . The
Zaklan model had been studied recently using the equilibrium Ising model. Here
we show that the Zaklan model is robust and can be reproduced also through the
nonequilibrium MVM on various topologies.Comment: 18 pages, 7 figures, LAWNP'09, 200
Saúde Bucal na Ação Programática da Criança: indicadores e metas de um Serviço de Atenção Primária à Saúde
Astrobiological Complexity with Probabilistic Cellular Automata
Search for extraterrestrial life and intelligence constitutes one of the
major endeavors in science, but has yet been quantitatively modeled only rarely
and in a cursory and superficial fashion. We argue that probabilistic cellular
automata (PCA) represent the best quantitative framework for modeling
astrobiological history of the Milky Way and its Galactic Habitable Zone. The
relevant astrobiological parameters are to be modeled as the elements of the
input probability matrix for the PCA kernel. With the underlying simplicity of
the cellular automata constructs, this approach enables a quick analysis of
large and ambiguous input parameters' space. We perform a simple clustering
analysis of typical astrobiological histories and discuss the relevant boundary
conditions of practical importance for planning and guiding actual empirical
astrobiological and SETI projects. In addition to showing how the present
framework is adaptable to more complex situations and updated observational
databases from current and near-future space missions, we demonstrate how
numerical results could offer a cautious rationale for continuation of
practical SETI searches.Comment: 37 pages, 11 figures, 2 tables; added journal reference belo
Organizational strategy for the development of nurses' competences: possibilities of Continuing Education in Health
Dosimetria de pacientes submetidos a exames de PET/CT cerebral para diagnóstico de comprometimento cognitivo leve
Fine-structured multi-scaling long-range correlations in completely sequenced genomes—features, origin, and classification
The sequential organization of genomes, i.e. the relations between distant base pairs and regions within sequences, and its connection to the three-dimensional organization of genomes is still a largely unresolved problem. Long-range power-law correlations were found using correlation analysis on almost the entire observable scale of 132 completely sequenced chromosomes of 0.5 × 106 to 3.0 × 107 bp from Archaea, Bacteria, Arabidopsis thaliana, Saccharomyces cerevisiae, Schizosaccharomyces pombe, Drosophila melanogaster, and Homo sapiens. The local correlation coefficients show a species-specific multi-scaling behaviour: close to random correlations on the scale of a few base pairs, a first maximum from 40 to 3,400 bp (for Arabidopsis thaliana and Drosophila melanogaster divided in two submaxima), and often a region of one or more second maxima from 105 to 3 × 105 bp. Within this multi-scaling behaviour, an additional fine-structure is present and attributable to codon usage in all except the human sequences, where it is related to nucleosomal binding. Computer-generated random sequences assuming a block organization of genomes, the codon usage, and nucleosomal binding explain these results. Mutation by sequence reshuffling destroyed all correlations. Thus, the stability of correlations seems to be evolutionarily tightly controlled and connected to the spatial genome organization, especially on large scales. In summary, genomes show a complex sequential organization related closely to their three-dimensional organization