Disordered ensembles of random matrices

It is shown that the families of generalized matrix ensembles recently considered which give rise to an orthogonal invariant stable Levy ensemble can be generated by the simple procedure of dividing Gaussian matrices by a random variable. The nonergodicity of this kind of disordered ensembles is investigated. It is shown that the same procedure applied to random graphs gives rise to a family that interpolates between the Erdos-Renyi and the scale free models.

Effects of Infrared-LED Illumination Applied During High-Intensity Treadmill Training in Postmenopausal Women

Background data: Technology and physical exercise can enhance physical performance during aging. Objective: The purpose of this study was to investigate the effects of infrared-light-emitting diode (LED) illumination (850 nm) applied during treadmill training. Materials and methods: Twenty postmenopausal women participated in this study. They were randomly divided into two groups. The LED group performed treadmill training associated with infrared-LED illumination (n = 10) and the control group performed only treadmill training (n = 10). The training was performed during 3 months, twice a week during 30 min at intensities between 85 and 90% of maximal heart rate. The irradiation parameters were 31 mW/cm(2), treatment time 30 min, 14,400 J of total energy and 55.8 J/cm(2) of fluence. Physiological, biomechanical, and body composition parameters were measured at the baseline and after 3 months. Results: Both groups improved the time of tolerance limit (Tlim) (p < 0.05) during submaximal constant-speed testing. The peak torque did not differ between groups. However, the results showed significantly higher values of power [from 56 +/- 10 to 73 +/- 8W (p = 0.002)] and total work [from 1,537 +/- 295 to 1,760 +/- 262 J (p = 0.006)] for the LED group when compared to the control group [power: from 58 +/- 14 to 60 +/- 15W (p >= 0.05) and total work: from 1,504 +/- 404 to 1,622 +/- 418 J (p >= 0.05)]. The fatigue significantly increased for the control group [from 51 +/- 6 to 58 +/- 5 % (p = 0.04)], but not for the LED group [from 60 +/- 10 to 60 +/- 4 % (p >= 0.05)]. No significant differences in body composition were observed for either group. Conclusions: Infrared-LED illumination associated with treadmill training can improve muscle power and delay leg fatigue in postmenopausal women.

Statistics of opinion domains of the majority-vote model on a square lattice

The existence of juxtaposed regions of distinct cultures in spite of the fact that people's beliefs have a tendency to become more similar to each other's as the individuals interact repeatedly is a puzzling phenomenon in the social sciences. Here we study an extreme version of the frequency-dependent bias model of social influence in which an individual adopts the opinion shared by the majority of the members of its extended neighborhood, which includes the individual itself. This is a variant of the majority-vote model in which the individual retains its opinion in case there is a tie among the neighbors' opinions. We assume that the individuals are fixed in the sites of a square lattice of linear size L and that they interact with their nearest neighbors only. Within a mean-field framework, we derive the equations of motion for the density of individuals adopting a particular opinion in the single-site and pair approximations. Although the single-site approximation predicts a single opinion domain that takes over the entire lattice, the pair approximation yields a qualitatively correct picture with the coexistence of different opinion domains and a strong dependence on the initial conditions. Extensive Monte Carlo simulations indicate the existence of a rich distribution of opinion domains or clusters, the number of which grows with L(2) whereas the size of the largest cluster grows with ln L(2). The analysis of the sizes of the opinion domains shows that they obey a power-law distribution for not too large sizes but that they are exponentially distributed in the limit of very large clusters. In addition, similarly to other well-known social influence model-Axelrod's model-we found that these opinion domains are unstable to the effect of a thermal-like noise.

Effective coordination concept applied for phase change (GeTe)(m)(Sb(2)Te(3))(n) compounds

In this work, we employed the effective coordination concept to study the local environments of the Ge, Sb, and Te atoms in the Ge(m)Sb(2n)Te(m+3n) compounds. From our calculations and analysis, we found an average effective coordination number (ECN) reduction of 1.59, 1.42, and 1.37, for the Ge, Sb, Te atoms in the phase transition from crystalline, ECN=5.55 (Ge), 5.73 (Sb), 4.37 (Te), to the amorphous phase, ECN=3.96 (Ge), 4.31 (Sb), 3.09 (Te), for the Ge(2)Sb(2)Te(5) composition. Similar changes are observed for other compositions. Thus, our results indicate that the coordination changes from the crystalline to amorphous phase are not large as previously assumed in the literature, i.e., from sixfold to fourfold for Ge, which can contribute to obtain a better understanding of the crystalline to amorphous phase transition. (C) 2011 American Institute of Physics. [doi:10.1063/1.3533422]

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.

Context tree selection: A unifying view

Context tree models have been introduced by Rissanen in [25] as a parsimonious generalization of Markov models. Since then, they have been widely used in applied probability and statistics. The present paper investigates non-asymptotic properties of two popular procedures of context tree estimation: Rissanen's algorithm Context and penalized maximum likelihood. First showing how they are related, we prove finite horizon bounds for the probability of over- and under-estimation. Concerning overestimation, no boundedness or loss-of-memory conditions are required: the proof relies on new deviation inequalities for empirical probabilities of independent interest. The under-estimation properties rely on classical hypotheses for processes of infinite memory. These results improve on and generalize the bounds obtained in Duarte et al. (2006) [12], Galves et al. (2008) [18], Galves and Leonardi (2008) [17], Leonardi (2010) [22], refining asymptotic results of Buhlmann and Wyner (1999) [4] and Csiszar and Talata (2006) [9]. (C) 2011 Elsevier B.V. All rights reserved.

A PHASE TRANSITION FOR COMPETITION INTERFACES

We study the competition interface between two growing clusters in a growth model associated to last-passage percolation. When the initial unoccupied set is approximately a cone, we show that this interface has an asymptotic direction with probability 1. The behavior of this direction depends on the angle theta of the cone: for theta >= 180 degrees, the direction is deterministic, while for theta < 180 degrees, it is random, and its distribution can be given explicitly in certain cases. We also obtain partial results on the fluctuations of the interface around its asymptotic direction. The evolution of the competition interface in the growth model can be mapped onto the path of a second-class particle in the totally asymmetric simple exclusion process; from the existence of the limiting direction for the interface, we obtain a new and rather natural proof of the strong law of large numbers (with perhaps a random limit) for the position of the second-class particle at large times.

POLLING SYSTEMS WITH PARAMETER REGENERATION, THE GENERAL CASE

We consider a polling model with multiple stations, each with Poisson arrivals and a queue of infinite capacity. The service regime is exhaustive and there is Jacksonian feedback of served customers. What is new here is that when the server comes to a station it chooses the service rate and the feedback parameters at random; these remain valid during the whole stay of the server at that station. We give criteria for recurrence, transience and existence of the sth moment of the return time to the empty state for this model. This paper generalizes the model, when only two stations accept arriving jobs, which was considered in [Ann. Appl. Probab. 17 (2007) 1447-1473]. Our results are stated in terms of Lyapunov exponents for random matrices. From the recurrence criteria it can be seen that the polling model with parameter regeneration can exhibit the unusual phenomenon of null recurrence over a thick region of parameter space.

Screening of Microorganisms Producing Cold-Active Oxidoreductases to Be Applied in Enantioselective Alcohol Oxidation. An Antarctic Survey

Several microorganisms were isolated from soil/sediment samples of Antarctic Peninsula. The enrichment technique using (RS)-.1-(phenyl) ethanol as a carbon source allowed us to isolate 232 psychrophile/psychrotroph microorganisms. We also evaluated the enzyme activity (oxidoreductases) for enantioselective oxidation reactions, by using derivatives of (RS)-.1-(phenyl) ethanol as substrates. Among the studied microorganisms, 15 psychrophile/psychrotroph strains contain oxidoreductases that catalyze the (S)-.enantiomer oxidation from racemic alcohols to their corresponding ketones. Among the identified microorganisms, Flavobacterium sp. and Arthrobacter sp. showed excellent enzymatic activity. These new bacteria strains were selected for optimization study, in which the (RS)-.1-(4-.methyl-.phenyl) ethanol oxidation was evaluated in several reaction conditions. From these studies, it was observed that Flavobacterium sp. has an excellent enzymatic activity at 10 degrees C and Arthrobacter sp. at 15 and 25 degrees C. We have also determined the growth curves of these bacteria, and both strains showed optimum growth at 25 degrees C, indicating that these bacteria are psychrotroph.

Fertilizers applied to certified organic tomato culture

The tomato culture demands large quantities of mineral nutrients, which are supplied by synthetic fertilizers in the conventional cultivation system. In the organic cultivation system only alternative fertilizers are allowed by the certifiers and accepted as safe for humans and environment. The chemical composition of rice bran, oyster flour, cattle manure and ground charcoal, as well as soils and tomato fruits were evaluated by instrumental neutron activation analysis (INAA). The potential contribution of organic fertilizers to the enrichment of chemical elements in soil and their transfer to fruits was investigated using concentration ratios for fertilizer and soil samples, and also for soil and tomato. Results evidenced that these alternative fertilizers could be taken as important sources of Br, Ca, Ce, K, Na and Zn for the organic tomato culture.

Chemical characterization of agricultural supplies applied to organic tomato cultivation

The agricultural supplies used in the organic system to control pests and diseases as well as to fertilize soil are claimed to be beneficial to plants and innocuous to human health and to the environment. The chemical composition of six agricultural supplies commonly used in the organic tomato culture, was evaluated by instrumental neutron activation analysis (INAA). Results were compared to the maximum limits established by the Environment Control Agency of the Sao Paulo State (CETESB) and the Guidelines for Organic Quality Standard of Instituto Biodinamico (IBD). Concentrations above reference values were found for Co, Cr and Zn in compost, Cr and Zn in cattle manure and Zn in rice bran.

Support vector machines for detecting age-related changes in running kinematics

Age-related changes in running kinematics have been reported in the literature using classical inferential statistics. However, this approach has been hampered by the increased number of biomechanical gait variables reported and subsequently the lack of differences presented in these studies. Data mining techniques have been applied in recent biomedical studies to solve this problem using a more general approach. In the present work, we re-analyzed lower extremity running kinematic data of 17 young and 17 elderly male runners using the Support Vector Machine (SVM) classification approach. In total, 31 kinematic variables were extracted to train the classification algorithm and test the generalized performance. The results revealed different accuracy rates across three different kernel methods adopted in the classifier, with the linear kernel performing the best. A subsequent forward feature selection algorithm demonstrated that with only six features, the linear kernel SVM achieved 100% classification performance rate, showing that these features provided powerful combined information to distinguish age groups. The results of the present work demonstrate potential in applying this approach to improve knowledge about the age-related differences in running gait biomechanics and encourages the use of the SVM in other clinical contexts. (C) 2010 Elsevier Ltd. All rights reserved.

Academic papers about fight, martial arts and combat sports

The present study had as objective to verify the production of fight, martial arts and combat sports in articles published in the main Physical Education academic journals available in Brazil after the establishment of the CONFEF, as well as analyze the subjects studied in these articles. The subject classification followed Tani (1996)`s proposition concerning an academic structure to Kinesiology, Physical Education and Sport. When considering the 2561 articles published on these journals only 75 (2.93%) were related to Fight/Martial Arts/Combat Sports. It was verified a predominance of studies conducted in the Biodynamic area (40%), followed by Human Movement Socio-cultural Studies (32%) and Motor Behavior (8%). The applied studies were divided as: Human Movement Pedagogy (10.7%), Sports Training (8%), Sports Administration (1.3%) and Adapted Human Movement (none study published). These data indicate: (1) a reduced number of publications concerning these activities, especially those of applied nature; (2) a need to promote inter and multidisciplinary research about this subject.

Optimization of Heat Treatment Profiles Applied to Nanometric-Scale Nb(3)Sn Wires With Cu-Sn Artificial Pinning Centers

Nb(3)Sn is one of the most used superconducting materials for applications in high magnetic fields. The improvement of the critical current densities (J(c)) is important, and must be analyzed together with the optimization of the flux pinning acting in the material. For Nb(3)Sn, it is known that the grain boundaries are the most effective pinning centers. However, the introduction of artificial pinning centers (APCs) with different superconducting properties has been proved to be beneficial for J(c). As these APCs are normally in the nanometric-scale, the conventional heat treatment profiles used for Nb(3)Sn wires cannot be directly applied, leading to excessive grain growth and/or increase of the APCs cross sections. In this work, the heat treatment profiles for Nb(3)Sn superconductor wires with Cu(Sn) artificial pinning centers in nanometric-scale were analyzed in an attempt to improve J(c) . It is described a methodology to optimize the heat treatment profiles in respect to diffusion, reaction and formation of the superconducting phases. Microstructural, transport and magnetic characterization were performed in an attempt to find the pinning mechanisms acting in the samples. It was concluded that the maximum current densities were found when normal phases (due to the introduction of the APCs) are acting as main pinning centers in the global behavior of the Nb(3)Sn superconducting wire.