Análise quantitativa da distribuição de jogadores de futebol em campo durante jogos oficiais

Universidade Estadual de Campinas. Faculdade de Educação Física

Desenvolvimento de ferramentas de análise de desempenho de atletas em 3 diferentes modalidades : Handebol, Provas Combinadas e Salto com Vara

Universidade Estadual de Campinas. Faculdade de Educação Física

Desenvolvimento de uma metodologia para reconstrução tridimensional e analise de superficies do corpo humano

Universidade Estadual de Campinas . Faculdade de Educação Física

Configurações centrais planares do tipo pipa

Neste artigo estudamos configurações centrais planares do tipo pipa para o problema de quatro corpos. Mostramos a existência de tais configurações para as pipas côncavas, quando uma das massas está no interior do triângulo formado pelas outras três massas, e para as pipas convexas, quando uma das massas está no exterior do triângulo formado pelas outras três massas.

Metapyrophorus pharolim a new genus and species of Pyrophorini (Coleoptera, Elateridae, Agrypninae)

Metapyrophorus, a new monotypic genus, is erected based on M. pharolim, new species from Trinidad and Tobago and Venezuela. The genus is characterized mainly by its pair of convex pronotal bioluminescent organs, equidistant between the median line and the lateral margin.

UNIQUENESS AND NONUNIQUENESS RESULTS FOR A CERTAIN CLASS OF ALMOST PERIODIC DISTRIBUTIONS

We consider distributions u is an element of S'(R) of the form u(t) = Sigma(n is an element of N) a(n)e(i lambda nt), where (a(n))(n is an element of N) subset of C and Lambda = (lambda n)(n is an element of N) subset of R have the following properties: (a(n))(n is an element of N) is an element of s', that is, there is a q is an element of N such that (n(-q) a(n))(n is an element of N) is an element of l(1); for the real sequence., there are n(0) is an element of N, C > 0, and alpha > 0 such that n >= n(0) double right arrow vertical bar lambda(n)vertical bar >= Cn(alpha). Let I(epsilon) subset of R be an interval of length epsilon. We prove that for given Lambda, (1) if Lambda = O(n(alpha)) with alpha < 1, then there exists epsilon > 0 such that u vertical bar I(epsilon) = 0 double right arrow u 0; (2) if Lambda = O(n) is uniformly discrete, then there exists epsilon > 0 such that u vertical bar I(epsilon) = 0 double right arrow u 0; (3) if alpha > 1 and. is uniformly discrete, then for all epsilon > 0, u vertical bar I(epsilon) = 0 double right arrow u = 0. Since distributions of the above mentioned form are very common in engineering, as in the case of the modeling of ocean waves, signal processing, and vibrations of beams, plates, and shells, those uniqueness and nonuniqueness results have important consequences for identification problems in the applied sciences. We show an identification method and close this article with a simple example to show that the recovery of geometrical imperfections in a cylindrical shell is possible from a measurement of its dynamics.

Crossover between the extended and localized regimes in stochastic partially self-avoiding walks in one-dimensional disordered systems

Consider N sites randomly and uniformly distributed in a d-dimensional hypercube. A walker explores this disordered medium going to the nearest site, which has not been visited in the last mu (memory) steps. The walker trajectory is composed of a transient part and a periodic part (cycle). For one-dimensional systems, travelers can or cannot explore all available space, giving rise to a crossover between localized and extended regimes at the critical memory mu(1) = log(2) N. The deterministic rule can be softened to consider more realistic situations with the inclusion of a stochastic parameter T (temperature). In this case, the walker movement is driven by a probability density function parameterized by T and a cost function. The cost function increases as the distance between two sites and favors hops to closer sites. As the temperature increases, the walker can escape from cycles that are reminiscent of the deterministic nature and extend the exploration. Here, we report an analytical model and numerical studies of the influence of the temperature and the critical memory in the exploration of one-dimensional disordered systems.

A perivascular epithelioid cell tumor of the stomach: An unsuspected diagnosis

Perivascular epithelioid cell tumor (PEComa) is a rare mesenchymal neoplasia and currently well recognized as a distinct entity with characteristic morphological, immunohistochemical and molecular findings. We report a case of PEComa arising in the antrum of a 71-year-old female with melena. The tumor, located predominantly in the submucosa as a well delimited nodule, measured 3.0 cm in diameter and was completely resected, with no evidence of the disease elsewhere. Histologically, it was composed predominantly of eosinophilic epithelioid cells arranged in small nests commonly related to variably sized vessels, with abundant extracellular material, moderate nuclear variation and discrete mitotic activity. No necrosis, angiolymphatic invasion or perineural infiltration was seen. Tumor cells were uniformly positive for vimentin, smooth muscle actin, desmin and melan A. Although unusual, PEComa should be considered in the differential diagnosis of gastric neoplasia with characteristic epithelioid and oncocytic features and prominent vasculature: (C) 2010 Baishideng. All rights reserved.

Dihadron azimuthal correlations in Au+Au collisions at root s(NN)=200 GeV

Azimuthal angle (Delta phi) correlations are presented for a broad range of transverse momentum (0.4 < p(T) < 10 GeV/c) and centrality (0-92%) selections for charged hadrons from dijets in Au+Au collisions at root s(NN) = 200 GeV. With increasing p(T), the away-side Delta phi distribution evolves from a broad and relatively flat shape to a concave shape, then to a convex shape. Comparisons with p + p data suggest that the away-side distribution can be divided into a partially suppressed ""head"" region centered at Delta phi similar to pi, and an enhanced ""shoulder"" region centered at Delta phi similar to pi +/- 1.1. The p(T) spectrum for the associated hadrons in the head region softens toward central collisions. The spectral slope for the shoulder region is independent of centrality and trigger p(T). The properties of the near-side distributions are also modified relative to those in p + p collisions, reflected by the broadening of the jet shape in Delta phi and Delta eta, and an enhancement of the per-trigger yield. However, these modifications seem to be limited to p(T)less than or similar to 4 GeV/c, above which both the hadron pair shape and per-trigger yield become similar to p + p collisions. These observations suggest that both the away- and near-side distributions contain a jet fragmentation component which dominates for p(T) greater than or similar to 5 GeV/c and a medium-induced component which is important for p(T) less than or similar to 4 GeV/c. We also quantify the role of jets at intermediate and low p(T) through the yield of jet-induced pairs in comparison with binary scaled p + p pair yield. The yield of jet-induced pairs is suppressed at high pair proxy energy (sum of the p(T) magnitudes of the two hadrons) and is enhanced at low pair proxy energy. The former is consistent with jet quenching; the latter is consistent with the enhancement of soft hadron pairs due to transport of lost energy to lower p(T).

Transverse momentum and centrality dependence of dihadron correlations in Au plus Au collisions at root s(NN)=200 GeV: Jet quenching and the response of partonic matter

Azimuthal angle (Delta phi) correlations are presented for charged hadrons from dijets for 0.4 < p(T)< 10 GeV/c in Au+Au collisions at root s(NN)=200 GeV. With increasing p(T), the away-side distribution evolves from a broad and relatively flat shape to a concave shape, then to a convex shape. Comparisons to p+p data suggest that the away-side can be divided into a partially suppressed ""head"" region centered at Delta phi similar to pi and an enhanced ""shoulder"" region centered at Delta phi similar to pi +/- 1.1. The p(T) spectrum for the head region softens toward central collisions, consistent with the onset of jet quenching. The spectral slope for the shoulder region is independent of centrality and trigger p(T), which offers constraints on energy transport mechanisms and suggests that it contains the medium response to energetic jets.

Systematic investigation of a family of gradient-dependent functionals for solids

Eleven density functionals are compared with regard to their performance for the lattice constants of solids. We consider standard functionals, such as the local-density approximation and the Perdew-Burke-Ernzerhof (PBE) generalized-gradient approximation (GGA), as well as variations of PBE GGA, such as PBEsol and similar functionals, PBE-type functionals employing a tighter Lieb-Oxford bound, and combinations thereof. On a test set of 60 solids, we perform a system-by-system analysis for selected functionals and a full statistical analysis for all of them. The impact of restoring the gradient expansion and of tightening the Lieb-Oxford bound is discussed, and confronted with previous results obtained from other codes, functionals or test sets. No functional is uniformly good for all investigated systems, but surprisingly, and pleasingly, the simplest possible modifications to PBE turn out to have the most beneficial effect on its performance. The atomization energy of molecules was also considered and on a testing set of six molecules, we found that the PBE functional is clearly the best, the others leading to strong overbinding.

Gene Expression Complex Networks: Synthesis, Identification, and Analysis

Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdos-Renyi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabasi-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree k variation, decreasing its network recovery rate with the increase of k. The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.

INFERENCE FOR EIGENVALUES AND EIGENVECTORS OF GAUSSIAN SYMMETRIC MATRICES

This article presents maximum likelihood estimators (MLEs) and log-likelihood ratio (LLR) tests for the eigenvalues and eigenvectors of Gaussian random symmetric matrices of arbitrary dimension, where the observations are independent repeated samples from one or two populations. These inference problems are relevant in the analysis of diffusion tensor imaging data and polarized cosmic background radiation data, where the observations are, respectively, 3 x 3 and 2 x 2 symmetric positive definite matrices. The parameter sets involved in the inference problems for eigenvalues and eigenvectors are subsets of Euclidean space that are either affine subspaces, embedded submanifolds that are invariant under orthogonal transformations or polyhedral convex cones. We show that for a class of sets that includes the ones considered in this paper, the MLEs of the mean parameter do not depend on the covariance parameters if and only if the covariance structure is orthogonally invariant. Closed-form expressions for the MLEs and the associated LLRs are derived for this covariance structure.

Multiclass Hammersley-Aldous-Diaconis process and multiclass-customer queues

In the Hammersley-Aldous-Diaconis process, infinitely many particles sit in R and at most one particle is allowed at each position. A particle at x, whose nearest neighbor to the right is at y, jumps at rate y - x to a position uniformly distributed in the interval (x, y). The basic coupling between trajectories with different initial configuration induces a process with different classes of particles. We show that the invariant measures for the two-class process can be obtained as follows. First, a stationary M/M/1 queue is constructed as a function of two homogeneous Poisson processes, the arrivals with rate, and the (attempted) services with rate rho > lambda Then put first class particles at the instants of departures (effective services) and second class particles at the instants of unused services. The procedure is generalized for the n-class case by using n - 1 queues in tandem with n - 1 priority types of customers. A multi-line process is introduced; it consists of a coupling (different from Liggett's basic coupling), having as invariant measure the product of Poisson processes. The definition of the multi-line process involves the dual points of the space-time Poisson process used in the graphical construction of the reversed process. The coupled process is a transformation of the multi-line process and its invariant measure is the transformation described above of the product measure.

Random perturbations of stochastic processes with unbounded variable length memory

We consider binary infinite order stochastic chains perturbed by a random noise. This means that at each time step, the value assumed by the chain can be randomly and independently flipped with a small fixed probability. We show that the transition probabilities of the perturbed chain are uniformly close to the corresponding transition probabilities of the original chain. As a consequence, in the case of stochastic chains with unbounded but otherwise finite variable length memory, we show that it is possible to recover the context tree of the original chain, using a suitable version of the algorithm Context, provided that the noise is small enough.