The Effect of Expectancy of a Threatening Event on Time Perception in Human Adults

Two experiments were conducted to investigate the effect of a threatening stimulus in human adults in a temporal bisection task. In Experiment I. for two anchor duration conditions (400/800 vs. 800/1600 ms), the participants completed trials in which the probe duration was followed by an aversive stimulus or a nonaversive stimulus. The results showed that the duration was judged longer when the participants expected an aversive rather than a nonaversive stimulus. In Experiment 2, the effect of the temporal localization of the aversive stimulus was also tested, with the aversive stimulus being presented at the beginning or at the end of the probe duration. The results revealed a temporal overestimation in each condition compared to the trials in which no aversive stimulus was presented. Furthermore, the temporal overestimation was greater when the expectation for the forthcoming threatening stimulus was longer. This temporal overestimation is explained in terms of a speeding-up of the neural timing system in response to the increase in the arousal level produced by the expectation of a threatening stimulus.

Standard Values for Real-Time Transthoracic Three-Dimensional Echocardiographic Dyssynchrony Indexes in a Normal Population

Background: There is a paucity of information describing the real-time 3-dimensional echocardiography (RT3DE) and dyssynchrony indexes (DIs) of a normal population. We evaluate the RT3DE DIs in a population with normal electrocardiograms and 2- and 3-dimensional echocardiographic analyses. This information is relevant for cardiac resynchronization therapy. Methods: We evaluated 131 healthy volunteers (73 were male, aged 46 +/- 14 years) who were referred for routine echocardiography; who presented normal cardiac structure on electrocardiography, 2-dimensional echocardiography, and RT3DE; and who had no history of cardiac diseases. We analyzed 3-dimensional left ventricular ejection fraction, left ventricle end-diastolic volume, left ventricle end-systolic volume, and left ventricular systolic DI% (6-, 12-, and 16-segment models). RT3DE data were analyzed by quantifying the statistical distribution (mean, median, standard deviation [SD], relative SD, coefficient of skewness, coefficient of kurtosis, Kolmogorov-Smirnov test, D`Agostino-Pearson test, percentiles, and 95% confidence interval). Results: Left ventricular ejection fraction ranged from 50% to 80% (66.1% +/- 7.1%); left ventricle end-diastolic volume ranged from 39.8 to 145 mL (79.1 +/- 24.9 mL); left ventricle end-systolic volume ranged from 12.9 to 66 mL (27 +/- 12.1 mL); 6-segment DI% ranged from 0.20% to 3.80% (1.21% +/- 0.66%), median: 1.06, relative SD: 0.5482, coefficient of skewness: 1.2620 (P < .0001), coefficient of Kurtosis: 1.9956 (P = .0039); percentile 2.5%: 0.2900, percentile 97.5%: 2.8300; 12-segment DI% ranged from 0.22% to 4.01% (1.29% +/- 0.71%), median: 1.14, relative SD: 0.95, coefficient of skewness: 1.1089 (P < .0001), coefficient of Kurtosis: 1.6372 (P = .0100), percentile 2.5%: 0.2850, percentile 97.5%: 3.0700; and 16-segment DI% ranged from 0.29% to 4.88% (1.59 +/- 0.99), median: 1.39, relative SD: 0.56, coefficient of skewness: 1.0792 (P < .0001), coefficient of Kurtosis: 0.9248 (P = .07), percentile 2.5%: 0.3750, percentile 97.5%: 3.750. Conclusion: This study allows for the quantification of RT3DE DIs in normal subjects, providing a comparison for patients with heart failure who may be candidates for cardiac resynchronization therapy. (J Am Soc Echocardiogr 2008; 21: 1229-1235)

Anti-aversive effects of the atypical antipsychotic, aripiprazole, in animal models of anxiety

Aripiprazole is a unique antipsychotic that seems to act as a partial agonist at dopamine D2-receptors, contrasting with other drugs in this class, which are silent antagonists. Aripiprazole may also bind to serotonin receptors. Both neurotransmitters may play major roles in aversion-, anxiety-and panic-related behaviours. Thus, the present work tested the hypothesis that this antipsychotic could also have anti-aversive properties. Male Wistar rats received injections of aripiprazole (0.1-10 mg/kg) and were tested in the open field, in the elevated plus and T mazes (EPM and ETM, respectively) and in a contextual fear conditioning paradigm. Aripiprazole (1mg/kg) increased the percentage of entries onto the open arms of the EPM and attenuated escape responses in the ETM. In the latter model, the dose of 0.1 mg/kg also decreased the latency to leave the enclosed arm, suggesting anxiolytic- and panicolytic-like properties. This dose also decreased the time spent in freezing in a contextual fear conditioning. No significant motor effects were observed at these doses. The present data support the hypothesis that aripiprazole could inhibit anxiety-related responses. Acting as a partial agonist at dopamine receptors, this drug could effectively treat schizophrenia and, in contrast with most antipsychotic drugs, alleviate aversive states.

Nitric oxide-mediated anxiolytic-like and antidepressant-like effects in animal models of anxiety and depression

The effects of microinjection of the nitric oxide (NO) precursor L-arginine (L-Arg), the NO synthase (NOS) inhibitors N-methyl-L-arginine (L-NAME) and 7-nitroindazole (7-NI), and the cyclic guanosine 3`,5`-monophosphate (cGMP) analog 8-Br-cGMP into the dorsal raphe nucleus (DRN) were assessed in rats using the elevated plus maze (EPM) and the forced swim test (FST). L-Arg (100 and 200 nmol) produced an anxiolytic-like effect in the EPM. 8-Br-cGMP (25 and 50 nmol) dose-dependently increased locomotor activity. In the FST, antidepressant-like effects were produced by L-Arg (50 and 100 nmol) and 8-Br-cGMP (12.5 and 25 nmol). Dual effects were observed with NOS inhibitors L-NAME and 7-NI in both the EPM and FST. While low doses of L-NAME (25 nmol) or 7-NI (1 nmol) induced a selective increase in EPM open arm exploration and a decrease in immobility time in the FST, high doses (L-NAME 400 nmol, 7-NI 10 nmol) decreased locomotor activity. These results show that interference with NO-mediated neurotransmission in the DRN induced significant and complex motor and emotional effects. Further studies are needed to elucidate the mechanisms involved in these effects. (C) 2007 Elsevier Inc. All rights reserved.

Genetic associations between carcass traits measured by real-time ultrasound and scrotal circumference and growth traits in Nelore cattle

The aim of the present study was to evaluate the genetic correlations among real-time ultrasound carcass, BW, and scrotal circumference (SC) traits in Nelore cattle. Carcass traits, measured by real-time ultrasound of the live animal, were recorded from 2002 to 2004 on 10 farms across 6 Brazilian states on 2,590 males and females ranging in age from 450 to 599 d. Ultrasound records of LM area (LMA) and backfat thickness (BF) were obtained from cross-sectional images between the 12th and 13th ribs, and rump fat thickness (RF) was measured between the hook and pin bones over the junction between gluteus medius and biceps femoris muscles. Also, BW (n = 22,778) and SC ( n = 5,695) were recorded on animals born between 1998 and 2003. The BW traits were 120, 210, 365, 450, and 550-d standardized BW (W120, W210, W365, W450, and W550), plus BW (WS) and hip height (HH) on the ultrasound scanning date. The SC traits were 365-, 450-, and 550-d standardized SC (SC365, SC450, and SC550). For the BW and SC traits, the database used was from the Nelore Breeding Program-Nelore Brazil. The genetic parameters were estimated with multivariate animal models and REML. Estimated genetic correlations between LMA and other traits were 0.06 (BF), -0.04 ( RF), 0.05 (HH), 0.58 (WS), 0.53 (W120), 0.62 (W210), 0.67 (W365), 0.64 ( W450 and W550), 0.28 (SC365), 0.24 (SC450), and 0.00 ( SC550). Estimated genetic correlations between BF and with other traits were 0.74 ( RF), -0.32 (HH), 0.19 (WS), -0.03 (W120), -0.10 (W210), 0.04 (W365), 0.01 (W450), 0.06 ( W550), 0.17 (SC365 and SC450), and -0.19 (SC550). Estimated genetic correlations between RF and other traits were -0.41 (HH), -0.09 (WS), -0.13 ( W120), -0.09 ( W210), -0.01 ( W365), 0.02 (W450), 0.03 (W550), 0.05 ( SC365), 0.11 ( SC450), and -0.18 (SC550). These estimates indicate that selection for carcass traits measured by real-time ultrasound should not cause antagonism in the genetic improvement of SC and BW traits. Also, selection to increase HH might decrease subcutaneous fat as correlated response. Therefore, to obtain animals suited to specific tropical production systems, carcass, BW, and SC traits should be considered in selection programs.

CHEMICAL EVOLUTION OF THE GALACTIC BULGE: SINGLE AND DOUBLE INFALL MODELS

Recent work, has produced a wealth of data concerning the chemical evolution of the Galactic bulge, both for stars and nebulae. Present theoretical models generally adopt it limited range of such constraints, frequenfly using it single chemical element (usually iron), which is not enough to describe it unambiguously. In this work, we take into account contraints involving,9 Many chemical elements as possible, basically obtained from bulge nebulae and stars. Our main goal is to show that different scenarios can describe, at least partially the abundance distribution and several dishuice-independent correlations for these objects . Three classes of models were developed. The first is it one-zone, single-infall model, the. Second is it one-zone, double-infall model and the third is a multizone, double-infall model. We show that a one-zone model with it single infall episode is able to reproduce some of the observational data, but the best results tire achieved using it multizone, double-infall model.

Revisiting 2D numerical models for the 19th century outbursts of eta Carinae

We present here new results of two-dimensional hydrodynamical simulations of the eruptive events of the 1840s (the great) and the 1890s (the minor) eruptions suffered by the massive star eta Carinae (Car). The two bipolar nebulae commonly known as the Homunculus and the little Homunculus (LH) were formed from the interaction of these eruptive events with the underlying stellar wind. We assume here an interacting, non-spherical multiple-phase wind scenario to explain the shape and the kinematics of both Homunculi, but adopt a more realistic parametrization of the phases of the wind. During the 1890s eruptive event, the outflow speed decreased for a short period of time. This fact suggests that the LH is formed when the eruption ends, from the impact of the post-outburst eta Car wind (that follows the 1890s event) with the eruptive flow (rather than by the collision of the eruptive flow with the pre-outburst wind, as claimed in previous models; Gonzalez et al.). Our simulations reproduce quite well the shape and the observed expansion speed of the large Homunculus. The LH (which is embedded within the large Homunculus) becomes Rayleigh-Taylor unstable and develop filamentary structures that resemble the spatial features observed in the polar caps. In addition, we find that the interior cavity between the two Homunculi is partially filled by material that is expelled during the decades following the great eruption. This result may be connected with the observed double-shell structure in the polar lobes of the eta Car nebula. Finally, as in previous work, we find the formation of tenuous, equatorial, high-speed features that seem to be related to the observed equatorial skirt of eta Car.

Consciousness minus retrospective mental time travel

In this paper we apply the concept of mental time travel to introduce the basic features of full-blown conscious experiences (encapsulation in mental models and recollection). We discuss the perspective that Lamme`s `Level 3` experiences can be considered as part of the scope of phenomenological consciousness, in relation to which we emphasize the necessity to consider the different degrees of consciousness and how a particular situation compares to the conscious experiences present in resting states of wakefulness.

Using non-homogeneous Poisson models with multiple change-points to estimate the number of ozone exceedances in Mexico City

In this paper, we consider some non-homogeneous Poisson models to estimate the probability that an air quality standard is exceeded a given number of times in a time interval of interest. We assume that the number of exceedances occurs according to a non-homogeneous Poisson process (NHPP). This Poisson process has rate function lambda(t), t >= 0, which depends on some parameters that must be estimated. We take into account two cases of rate functions: the Weibull and the Goel-Okumoto. We consider models with and without change-points. When the presence of change-points is assumed, we may have the presence of either one, two or three change-points, depending of the data set. The parameters of the rate functions are estimated using a Gibbs sampling algorithm. Results are applied to ozone data provided by the Mexico City monitoring network. In a first instance, we assume that there are no change-points present. Depending on the adjustment of the model, we assume the presence of either one, two or three change-points. Copyright (C) 2009 John Wiley & Sons, Ltd.

Exact Search Directions for Optimization of Linear and Nonlinear Models Based on Generalized Orthonormal Functions

A novel technique for selecting the poles of orthonormal basis functions (OBF) in Volterra models of any order is presented. It is well-known that the usual large number of parameters required to describe the Volterra kernels can be significantly reduced by representing each kernel using an appropriate basis of orthonormal functions. Such a representation results in the so-called OBF Volterra model, which has a Wiener structure consisting of a linear dynamic generated by the orthonormal basis followed by a nonlinear static mapping given by the Volterra polynomial series. Aiming at optimizing the poles that fully parameterize the orthonormal bases, the exact gradients of the outputs of the orthonormal filters with respect to their poles are computed analytically by using a back-propagation-through-time technique. The expressions relative to the Kautz basis and to generalized orthonormal bases of functions (GOBF) are addressed; the ones related to the Laguerre basis follow straightforwardly as a particular case. The main innovation here is that the dynamic nature of the OBF filters is fully considered in the gradient computations. These gradients provide exact search directions for optimizing the poles of a given orthonormal basis. Such search directions can, in turn, be used as part of an optimization procedure to locate the minimum of a cost-function that takes into account the error of estimation of the system output. The Levenberg-Marquardt algorithm is adopted here as the optimization procedure. Unlike previous related work, the proposed approach relies solely on input-output data measured from the system to be modeled, i.e., no information about the Volterra kernels is required. Examples are presented to illustrate the application of this approach to the modeling of dynamic systems, including a real magnetic levitation system with nonlinear oscillatory behavior.

Using stochastic volatility models to analyse weekly ozone averages in Mexico City

In this paper we make use of some stochastic volatility models to analyse the behaviour of a weekly ozone average measurements series. The models considered here have been used previously in problems related to financial time series. Two models are considered and their parameters are estimated using a Bayesian approach based on Markov chain Monte Carlo (MCMC) methods. Both models are applied to the data provided by the monitoring network of the Metropolitan Area of Mexico City. The selection of the best model for that specific data set is performed using the Deviance Information Criterion and the Conditional Predictive Ordinate method.

Destructive weighted Poisson cure rate models

In this paper, we develop a flexible cure rate survival model by assuming the number of competing causes of the event of interest to follow a compound weighted Poisson distribution. This model is more flexible in terms of dispersion than the promotion time cure model. Moreover, it gives an interesting and realistic interpretation of the biological mechanism of the occurrence of event of interest as it includes a destructive process of the initial risk factors in a competitive scenario. In other words, what is recorded is only from the undamaged portion of the original number of risk factors.

Black-box decomposition approach for computational hemodynamics: One-dimensional models

Increasing efforts exist in integrating different levels of detail in models of the cardiovascular system. For instance, one-dimensional representations are employed to model the systemic circulation. In this context, effective and black-box-type decomposition strategies for one-dimensional networks are needed, so as to: (i) employ domain decomposition strategies for large systemic models (1D-1D coupling) and (ii) provide the conceptual basis for dimensionally-heterogeneous representations (1D-3D coupling, among various possibilities). The strategy proposed in this article works for both of these two scenarios, though the several applications shown to illustrate its performance focus on the 1D-1D coupling case. A one-dimensional network is decomposed in such a way that each coupling point connects two (and not more) of the sub-networks. At each of the M connection points two unknowns are defined: the flow rate and pressure. These 2M unknowns are determined by 2M equations, since each sub-network provides one (non-linear) equation per coupling point. It is shown how to build the 2M x 2M non-linear system with arbitrary and independent choice of boundary conditions for each of the sub-networks. The idea is then to solve this non-linear system until convergence, which guarantees strong coupling of the complete network. In other words, if the non-linear solver converges at each time step, the solution coincides with what would be obtained by monolithically modeling the whole network. The decomposition thus imposes no stability restriction on the choice of the time step size. Effective iterative strategies for the non-linear system that preserve the black-box character of the decomposition are then explored. Several variants of matrix-free Broyden`s and Newton-GMRES algorithms are assessed as numerical solvers by comparing their performance on sub-critical wave propagation problems which range from academic test cases to realistic cardiovascular applications. A specific variant of Broyden`s algorithm is identified and recommended on the basis of its computer cost and reliability. (C) 2010 Elsevier B.V. All rights reserved.

Transformed generalized linear models

The estimation of data transformation is very useful to yield response variables satisfying closely a normal linear model, Generalized linear models enable the fitting of models to a wide range of data types. These models are based on exponential dispersion models. We propose a new class of transformed generalized linear models to extend the Box and Cox models and the generalized linear models. We use the generalized linear model framework to fit these models and discuss maximum likelihood estimation and inference. We give a simple formula to estimate the parameter that index the transformation of the response variable for a subclass of models. We also give a simple formula to estimate the rth moment of the original dependent variable. We explore the possibility of using these models to time series data to extend the generalized autoregressive moving average models discussed by Benjamin er al. [Generalized autoregressive moving average models. J. Amer. Statist. Assoc. 98, 214-223]. The usefulness of these models is illustrated in a Simulation study and in applications to three real data sets. (C) 2009 Elsevier B.V. All rights reserved.

Transformed symmetric models

For the first time, we introduce a class of transformed symmetric models to extend the Box and Cox models to more general symmetric models. The new class of models includes all symmetric continuous distributions with a possible non-linear structure for the mean and enables the fitting of a wide range of models to several data types. The proposed methods offer more flexible alternatives to Box-Cox or other existing procedures. We derive a very simple iterative process for fitting these models by maximum likelihood, whereas a direct unconditional maximization would be more difficult. We give simple formulae to estimate the parameter that indexes the transformation of the response variable and the moments of the original dependent variable which generalize previous published results. We discuss inference on the model parameters. The usefulness of the new class of models is illustrated in one application to a real dataset.