Approach to Equilibrium for a Class of Random Quantum Models of Infinite Range

We consider random generalizations of a quantum model of infinite range introduced by Emch and Radin. The generalizations allow a neat extension from the class l (1) of absolutely summable lattice potentials to the optimal class l (2) of square summable potentials first considered by Khanin and Sinai and generalised by van Enter and van Hemmen. The approach to equilibrium in the case of a Gaussian distribution is proved to be faster than for a Bernoulli distribution for both short-range and long-range lattice potentials. While exponential decay to equilibrium is excluded in the nonrandom l (1) case, it is proved to occur for both short and long range potentials for Gaussian distributions, and for potentials of class l (2) in the Bernoulli case. Open problems are discussed.

Comparison of some theoretical models for fittings of the temperature dependence of the fundamental energy gap in GaAs

In this work we report on a comparison of some theoretical models usually used to fit the dependence on temperature of the fundamental energy gap of semiconductor materials. We used in our investigations the theoretical models of Viña, Pässler-p and Pässler-ρ to fit several sets of experimental data, available in the literature for the energy gap of GaAs in the temperature range from 12 to 974 K. Performing several fittings for different values of the upper limit of the analyzed temperature range (Tmax), we were able to follow in a systematic way the evolution of the fitting parameters up to the limit of high temperatures and make a comparison between the zero-point values obtained from the different models by extrapolating the linear dependence of the gaps at high T to T = 0 K and that determined by the dependence of the gap on isotope mass. Using experimental data measured by absorption spectroscopy, we observed the non-linear behavior of Eg(T) of GaAs for T > ΘD.

Non-additive genetic effects on weights and performance of a Brazilian Bos taurus x Bos indicus beef composite

The aim of the present study was to evaluate the heterosis effects on weaning weight at 205 days (WW, N = 146,464), yearling weight at 390 days (YW, N = 69,315) and weight gain from weaning to yearling (WG, N = 59,307) in composite beef cattle. The fixed models were: RM, which included contemporary groups, class of age of dam, outcrossing percentages for direct and maternal effects, and additive direct and maternal ( AM) breed effects; R, RM model, minus AM breed effects, and H, RM model, minus additive breed effects. The estimates for W205 were in general positive (P < 0.01). The R and H models resulted in similar estimates, but they were very different from the ones estimated by the RM model. For W390, the R and H models resulted in general positive estimates (P < 0.05). For WG, the RM model resulted in general significant heterosis effects (P < 0.05). It can be concluded that the RM model seems to supply estimates of better quality (P < 0.01).

Active Dendrites Enhance Neuronal Dynamic Range

Since the first experimental evidences of active conductances in dendrites, most neurons have been shown to exhibit dendritic excitability through the expression of a variety of voltage-gated ion channels. However, despite experimental and theoretical efforts undertaken in the past decades, the role of this excitability for some kind of dendritic computation has remained elusive. Here we show that, owing to very general properties of excitable media, the average output of a model of an active dendritic tree is a highly non-linear function of its afferent rate, attaining extremely large dynamic ranges (above 50 dB). Moreover, the model yields double-sigmoid response functions as experimentally observed in retinal ganglion cells. We claim that enhancement of dynamic range is the primary functional role of active dendritic conductances. We predict that neurons with larger dendritic trees should have larger dynamic range and that blocking of active conductances should lead to a decrease in dynamic range.

Differential expression of microRNAs in mouse pain models

Background: MicroRNAs (miRNAs) are short non-coding RNAs that inhibit translation of target genes by binding to their mRNAs. The expression of numerous brain-specific miRNAs with a high degree of temporal and spatial specificity suggests that miRNAs play an important role in gene regulation in health and disease. Here we investigate the time course gene expression profile of miR-1, -16, and -206 in mouse dorsal root ganglion (DRG), and spinal cord dorsal horn under inflammatory and neuropathic pain conditions as well as following acute noxious stimulation. Results: Quantitative real-time polymerase chain reaction analyses showed that the mature form of miR-1, -16 and -206, is expressed in DRG and the dorsal horn of the spinal cord. Moreover, CFA-induced inflammation significantly reduced miRs-1 and -16 expression in DRG whereas miR-206 was downregulated in a time dependent manner. Conversely, in the spinal dorsal horn all three miRNAs monitored were upregulated. After sciatic nerve partial ligation, miR-1 and -206 were downregulated in DRG with no change in the spinal dorsal horn. On the other hand, axotomy increases the relative expression of miR-1, -16, and 206 in a time-dependent fashion while in the dorsal horn there was a significant downregulation of miR-1. Acute noxious stimulation with capsaicin also increased the expression of miR-1 and -16 in DRG cells but, on the other hand, in the spinal dorsal horn only a high dose of capsaicin was able to downregulate miR-206 expression. Conclusions: Our results indicate that miRNAs may participate in the regulatory mechanisms of genes associated with the pathophysiology of chronic pain as well as the nociceptive processing following acute noxious stimulation. We found substantial evidence that miRNAs are differentially regulated in DRG and the dorsal horn of the spinal cord under different pain states. Therefore, miRNA expression in the nociceptive system shows not only temporal and spatial specificity but is also stimulus-dependent.

A Dynamic Analysis of Tuberculosis Dissemination to Improve Control and Surveillance

Background: Detailed analysis of the dynamic interactions among biological, environmental, social, and economic factors that favour the spread of certain diseases is extremely useful for designing effective control strategies. Diseases like tuberculosis that kills somebody every 15 seconds in the world, require methods that take into account the disease dynamics to design truly efficient control and surveillance strategies. The usual and well established statistical approaches provide insights into the cause-effect relationships that favour disease transmission but they only estimate risk areas, spatial or temporal trends. Here we introduce a novel approach that allows figuring out the dynamical behaviour of the disease spreading. This information can subsequently be used to validate mathematical models of the dissemination process from which the underlying mechanisms that are responsible for this spreading could be inferred. Methodology/Principal Findings: The method presented here is based on the analysis of the spread of tuberculosis in a Brazilian endemic city during five consecutive years. The detailed analysis of the spatio-temporal correlation of the yearly geo-referenced data, using different characteristic times of the disease evolution, allowed us to trace the temporal path of the aetiological agent, to locate the sources of infection, and to characterize the dynamics of disease spreading. Consequently, the method also allowed for the identification of socio-economic factors that influence the process. Conclusions/Significance: The information obtained can contribute to more effective budget allocation, drug distribution and recruitment of human skilled resources, as well as guiding the design of vaccination programs. We propose that this novel strategy can also be applied to the evaluation of other diseases as well as other social processes.

Comparison of different models to estimate genetic parameters for carcass traits in a commercial broiler line

The effect of genetic and non-genetic factors for carcass, breast meat and leg weights, and yields of a commercial broiler line were investigated using the restricted maximum likelihood method, considering four different animal models, including or excluding maternal genetic effect with covariance between direct and maternal genetic effects, and maternal permanent environmental effect. The likelihood ratio test was used to determine the most adequate model for each trait. For carcass, breast, and leg weight, and for carcass and breast yield, maternal genetic and permanent environmental effects as well as the covariance between direct and maternal genetic effects were significant. The estimates of direct and maternal heritability were 0.17 and 0.04 for carcass weight, 0.26 and 0.06 for breast weight, 0.22 and 0.02 for leg weight, 0.32 and 0.02 for carcass yield, and 0.52 and 0.04 for breast yield, respectively. For leg yield, maternal permanent environmental effect was important, in addition to direct genetic effects. For that trait, direct heritability and maternal permanent environmental variance as a proportion of the phenotypic variance were 0.43 and 0.02, respectively. The results indicate that ignoring maternal effects in the models, even though they were of small magnitude (0.02 to 0.06), tended to overestimate direct genetic variance and heritability for all traits.

Deformed Gaussian-orthogonal-ensemble description of small-world networks

The study of spectral behavior of networks has gained enthusiasm over the last few years. In particular, random matrix theory (RMT) concepts have proven to be useful. In discussing transition from regular behavior to fully chaotic behavior it has been found that an extrapolation formula of the Brody type can be used. In the present paper we analyze the regular to chaotic behavior of small world (SW) networks using an extension of the Gaussian orthogonal ensemble. This RMT ensemble, coined the deformed Gaussian orthogonal ensemble (DGOE), supplies a natural foundation of the Brody formula. SW networks follow GOE statistics until a certain range of eigenvalue correlations depending upon the strength of random connections. We show that for these regimes of SW networks where spectral correlations do not follow GOE beyond a certain range, DGOE statistics models the correlations very well. The analysis performed in this paper proves the utility of the DGOE in network physics, as much as it has been useful in other physical systems.

Directed Abelian algebras and their application to stochastic models

With each directed acyclic graph (this includes some D-dimensional lattices) one can associate some Abelian algebras that we call directed Abelian algebras (DAAs). On each site of the graph one attaches a generator of the algebra. These algebras depend on several parameters and are semisimple. Using any DAA, one can define a family of Hamiltonians which give the continuous time evolution of a stochastic process. The calculation of the spectra and ground-state wave functions (stationary state probability distributions) is an easy algebraic exercise. If one considers D-dimensional lattices and chooses Hamiltonians linear in the generators, in finite-size scaling the Hamiltonian spectrum is gapless with a critical dynamic exponent z=D. One possible application of the DAA is to sandpile models. In the paper we present this application, considering one- and two-dimensional lattices. In the one-dimensional case, when the DAA conserves the number of particles, the avalanches belong to the random walker universality class (critical exponent sigma(tau)=3/2). We study the local density of particles inside large avalanches, showing a depletion of particles at the source of the avalanche and an enrichment at its end. In two dimensions we did extensive Monte-Carlo simulations and found sigma(tau)=1.780 +/- 0.005.

Structural models for yttrium aluminium borate laser glasses: NMR and EPR studies of the system (Y(2)O(3))(0.2)-(Al(2)O(3))(x)-(B(2)O(3))(0.8-x)

The structure of laser glasses in the system (Y(2)O(3))(0.2){(Al(2)O(3))(x))(B(2)O(3))(0.8-x)} (0.15 <= x <= 0.40) has been investigated by means of (11)B, (27)Al, and (89)Y solid state NMR as well as electron spin echo envelope modulation (ESEEM) of Yb-doped samples. The latter technique has been applied for the first time to an aluminoborate glass system. (11)B magic-angle spinning (MAS)-NMR spectra reveal that, while the majority of the boron atoms are three-coordinated over the entire composition region, the fraction of three-coordinated boron atoms increases significantly with increasing x. Charge balance considerations as well as (11)B NMR lineshape analyses suggest that the dominant borate species are predominantly singly charged metaborate (BO(2/2)O(-)), doubly charged pyroborate (BO(1/2)(O(-))(2)), and (at x = 0.40) triply charged orthoborate groups. As x increases along this series, the average anionic charge per trigonal borate group increases from 1.38 to 2.91. (27)Al MAS-NMR spectra show that the alumina species are present in the coordination states four, five and six, and the fraction of four-coordinated Al increases markedly with increasing x. All of the Al coordination states are in intimate contact with both the three-and the four-coordinate boron species and vice versa, as indicated by (11)B/(27)Al rotational echo double resonance (REDOR) data. These results are consistent with the formation of a homogeneous, non-segregated glass structure. (89)Y solid state NMR spectra show a significant chemical shift trend, reflecting that the second coordination sphere becomes increasingly ""aluminate-like'' with increasing x. This conclusion is supported by electron spin echo envelope modulation (ESEEM) data of Yb-doped glasses, which indicate that both borate and aluminate species participate in the medium range structure of the rare-earth ions, consistent with a random spatial distribution of the glass components.

Synergistic interaction between gold nanoparticles and nickel phthalocyanine in layer-by-layer (LbL) films: evidence of constitutional dynamic chemistry (CDC)

The concept of constitutional dynamic chemistry (CDC) based on the control of non-covalent interactions in supramolecular structures is promising for having a large impact on nanoscience and nanotechnology if adequate nanoscale manipulation methods are used. In this study, we demonstrate that the layer-by-layer (LbL) technique may be used to produce electroactive electrodes with ITO coated by tetrasulfonated nickel phthalocyanine (NiTsPc) alternated with poly(allylamine hydrochloride) (PAH) incorporating gold nanoparticles (AuNP), in which synergy has been achieved in the interaction between the nanoparticles and NiTsPc. The catalytic activity toward hydrogen peroxide (H(2)O(2)) in multilayer films was investigated using cyclic voltammetry, where oxidation of H(2)O(2) led to increased currents in the PAH-AuNP/NiTsPc films for the electrochemical processes associated with the phthalocyanine ring and nickel at 0.52 and 0.81 V vs. SCE, respectively, while for PAH/NiTsPc films (without AuNP) only the first redox process was affected. In control experiments we found out that the catalytic activity was not solely due to the presence of AuNP, but rather to the nanoparticles inducing NiTsPc supramolecular structures that favored access to their redox sites, thus yielding strong charge transfer. The combined effects of NiTsPc and AuNP, which could only be observed in nanostructured LbL films, point to another avenue to pursue within the CDC paradigm.

Bayesian updating rules in continuous opinion dynamics models

Here, I investigate the use of Bayesian updating rules applied to modeling how social agents change their minds in the case of continuous opinion models. Given another agent statement about the continuous value of a variable, we will see that interesting dynamics emerge when an agent assigns a likelihood to that value that is a mixture of a Gaussian and a uniform distribution. This represents the idea that the other agent might have no idea about what is being talked about. The effect of updating only the first moments of the distribution will be studied, and we will see that this generates results similar to those of the bounded confidence models. On also updating the second moment, several different opinions always survive in the long run, as agents become more stubborn with time. However, depending on the probability of error and initial uncertainty, those opinions might be clustered around a central value.

Atenolol blunts blood pressure increase during dynamic resistance exercise in hypertensives

center dot Dynamic resistance exercise promotes a sizeable increase in blood pressure during its execution in non medicated hypertensives. WHAT THIS STUDY ADDS center dot Atenolol not only decreases blood pressure level but also mitigates the increase of blood pressure during dynamic resistance exercise in hypertensive patients. An increase in blood pressure during resistance exercise might be at least in part attributed to an increase in cardiac output. AIMS This study was conducted to determine whether atenolol was able to decrease BP level and mitigate BP increase during dynamic resistance exercise performed at three different intensities in hypertensives. METHODS Ten essential hypertensives (systolic/diastolic BP between 140/90 and 160/105 mmHg) were blindly studied after 6 weeks of placebo and atenolol. In each phase, volunteers executed, in a random order, three protocols of knee-extension exercises to fatigue: (i) one set at 100% of 1 RM; (ii) three sets at 80% of 1 RM; and (iii) three sets at 40% of 1 RM. Intra-arterial radial blood pressure was measured throughout the protocols. RESULTS Atenolol decreased systolic BP maximum values achieved during the three exercise protocols (100% = 186 +/- 4 vs. 215 +/- 7, 80% = 224 +/- 7 vs. 247 +/- 9 and 40% = 223 +/- 7 vs. 252 +/- 16 mmHg, P < 0.05). Atenolol also mitigated an increase in systolic BP in the first set of exercises (100% = +38 +/- 5 vs. +54 +/- 9; 80% = +68 +/- 11 vs. +84 +/- 13 and 40% = +69 +/- 7 vs. +84 +/- 14, mmHg, P < 0.05). Atenolol decreased diastolic BP values and mitigated its increase during exercise performed at 100% of 1 RM (126 +/- 6 vs. 145 +/- 6 and +41 +/- 6 vs. +52 +/- 6, mmHg, P < 0.05), but not at the other exercise intensities. CONCLUSIONS Atenolol was effective in both reducing systolic BP maximum values and mitigating BP increase during resistance exercise performed at different intensities in hypertensive subjects.

Endurance in judogi grip strength tests: comparison between elite and non-elite judo players

Background and Study Aim: The ability to develop a strong grip and maintain it during a judo match has become an important element for judo athletes. Therefore, the purpose of this investigation was to examine differences between measurements of maximal isometric time on judogi pull-up, and number of repetitions during dynamic judogi pull-up. Material/Methods: The sample was composed by two groups: 16 high-level judo athletes from the male Brazilian National Team and 12 male state-level judo athletes, with at least one athlete per weight category. The tests were compared through analysis of co-variance (body mass as co-variable), followed by a post-hoc test (Scheffe). Significance level was set at 5%. Results: No difference was found in the isometric test: Brazilian Team: 35 +/- 18s; Regional: 39 +/- 14s. However, the Brazilian Team performed a high number of repetitions (12 +/- 5 rep) compared to regional group (9 +/- 4 rep) during the dynamic grip strength endurance test. Conclusions: Thus, dynamic grip strength endurance seems to be a discriminating variable between judo athletes, probably because judo combat involves many elbow extensions and flexions in order to avoid the opponent`s grip and to subdue them.

Contribution to dynamic characteristics of the cutting temperature in the drilling process considering one dimension heat flow

The machining of hardened steels has always been a great challenge in metal cutting, particularly for drilling operations. Generally, drilling is the machining process that is most difficult to cool due to the tool`s geometry. The aim of this work is to determine the heat flux and the coefficient of convection in drilling using the inverse heat conduction method. Temperature was assessed during the drilling of hardened AISI H13 steel using the embedded thermocouple technique. Dry machining and two cooling/lubrication systems were used, and thermocouples were fixed at distances very close to the hole`s wall. Tests were replicated for each condition, and were carried out with new and worn drills. An analytical heat conduction model was used to calculate the temperature at tool-workpiece interface and to define the heat flux and the coefficient of convection. In all tests using new and worn out drills, the lowest temperatures and decrease of heat flux were observed using the flooded system, followed by the MQL, considering the dry condition as reference. The decrease of temperature was directly proportional to the amount of lubricant applied and was significant in the MQL system when compared to dry cutting. (C) 2011 Elsevier Ltd. All rights reserved.