Bayesian Analysis for Errors in Variables with Changepoint Models

Changepoint regression models have originally been developed in connection with applications in quality control, where a change from the in-control to the out-of-control state has to be detected based on the avaliable random observations. Up to now various changepoint models have been suggested for differents applications like reliability, econometrics or medicine. In many practical situations the covariate cannot be measured precisely and an alternative model are the errors in variable regression models. In this paper we study the regression model with errors in variables with changepoint from a Bayesian approach. From the simulation study we found that the proposed procedure produces estimates suitable for the changepoint and all other model parameters.

Lipopolysaccharide-Induced Sickness Behaviour Evaluated in Different Models of Anxiety and Innate Fear in Rats

The fact that there is a complex and bidirectional communication between the immune and nervous systems has been well demonstrated. Lipopolysaccharide (LPS), a component of gram-negative bacteria, is widely used to systematically stimulate the immune system and generate profound physiological and behavioural changes, also known as sickness behaviour (e.g. anhedonia, lethargy, loss of appetite, anxiety, sleepiness). Different ethological tools have been used to analyse the behavioural modifications induced by LPS; however, many researchers analysed only individual tests, a single LPS dose or a unique ethological parameter, thus leading to disagreements regarding the data. In the present study, we investigated the effects of different doses of LPS (10, 50, 200 and 500 mu g/kg, i.p.) in young male Wistar rats (weighing 180200 g; 89 weeks old) on the ethological and spatiotemporal parameters of the elevated plus maze, light-dark box, elevated T maze, open-field tests and emission of ultrasound vocalizations. There was a dose-dependent increase in anxiety-like behaviours caused by LPS, forming an inverted U curve peaked at LPS 200 mu g/kg dose. However, these anxiety-like behaviours were detected only by complementary ethological analysis (stretching, grooming, immobility responses and alarm calls), and these reactions seem to be a very sensitive tool in assessing the first signs of sickness behaviour. In summary, the present work clearly showed that there are resting and alertness reactions induced by opposite neuroimmune mechanisms (neuroimmune bias) that could lead to anxiety behaviours, suggesting that misunderstanding data could occur when only few ethological variables or single doses of LPS are analysed. Finally, it is hypothesized that this bias is an evolutionary tool that increases animals security while the body recovers from a systemic infection.

Stochastic simulation of time-series models combined with geostatistics to predict water-table scenarios in a Guarani Aquifer System outcrop area, Brazil

Stochastic methods based on time-series modeling combined with geostatistics can be useful tools to describe the variability of water-table levels in time and space and to account for uncertainty. Monitoring water-level networks can give information about the dynamic of the aquifer domain in both dimensions. Time-series modeling is an elegant way to treat monitoring data without the complexity of physical mechanistic models. Time-series model predictions can be interpolated spatially, with the spatial differences in water-table dynamics determined by the spatial variation in the system properties and the temporal variation driven by the dynamics of the inputs into the system. An integration of stochastic methods is presented, based on time-series modeling and geostatistics as a framework to predict water levels for decision making in groundwater management and land-use planning. The methodology is applied in a case study in a Guarani Aquifer System (GAS) outcrop area located in the southeastern part of Brazil. Communication of results in a clear and understandable form, via simulated scenarios, is discussed as an alternative, when translating scientific knowledge into applications of stochastic hydrogeology in large aquifers with limited monitoring network coverage like the GAS.

Holographic field theory models of dark energy in interaction with dark matter

We discuss two Lagrangian interacting dark energy models in the context of the holographic principle. The potentials of the interacting fields are constructed. The models are compared with CMB distance information, baryonic acoustic oscillations, lookback time and the Constitution supernovae sample. For both models, the results are consistent with a nonvanishing interaction in the dark sector of the Universe and the sign of coupling is consistent with dark energy decaying into dark matter, alleviating the coincidence problem-with more than 3 standard deviations of confidence for one of them. However, this is because the noninteracting holographic dark energy model is a bad fit to the combination of data sets used in this work as compared to the cosmological constant with cold dark matter model, so that one needs to introduce the interaction in order to improve this model.

Leucine Is Essential for Attenuating Fetal Growth Restriction Caused by a Protein-Restricted Diet in Rats

Certain amino acids, such as leucine (Leu) are not only substrates for protein synthesis but also are important regulators of protein metabolism. Moreover, it is known that alterations in intrauterine growth favor the development of chronic diseases in adulthood. Therefore, we investigated the role of Leu in combination with other BCAA on effects that are induced by maternal protein restriction on fetal growth. Wistar rats were divided into 4 groups according to the diet provided during pregnancy: control (C; 20% casein); V+I [5% casein + 2% L-valine (Val) + 2% L-isoleucine (Ile)1; KYT 15% casein + 1.8% L-lysine (Lys) + 1.2% L-tyrosine (Tyr) + 1% L-threonine (Thr)1; and BCAA (5% casein + 1.8% L-Leu + 1.2% L-Val + 1% L-Ile). Maternal protein restriction reduced the growth and organ weight of the offspring of dams receiving the V+I and KYT diets compared with the C group. Supplementation with BCAA reversed this growth deficit, minimizing the difference or restoring the mass of organs and carcass fat, the liver and muscle protein, and the RNA concentrations compared with newborns in the C group (P < 0.05). These effects could be explained by the activation of the mTOR signaling pathway, because phosphorylation of 4E-BP1 in the liver of offspring of the BCAA group was greater than that in the C, V+I, and KYT groups. The present results identify a critical role for Leu in association with other BCAA in the activation of the mTOR signaling pathway for the control of altered intrauterine growth induced by a maternal low-protein diet. J. Nutr. 142: 924-930, 2012.

Stand-level patterns of carbon fluxes and partitioning in a Eucalyptus grandis plantation across a gradient of productivity, in Sao Paulo State, Brazil

Wood production represents a large but variable fraction of gross primary production (GPP) in highly productive Eucalyptus plantations. Assessing patterns of carbon (C) partitioning (C flux as a fraction of GPP) between above- and belowground components is essential to understand mechanisms driving the C budget of these plantations. Better knowledge of fluxes and partitioning to woody and non-woody tissues in response to site characteristics and resource availability could provide opportunities to increase forest productivity. Our study aimed at investigating how C allocation varied within one apparently homogeneous 90 ha stand of Eucalyptus grandis (W. Hill ex Maiden) in Southeastern Brazil. We assessed annual above-ground net primary production (ANPP: stem, leaf, and branch production) and total belowground C flux (TBCF: the sum of root production and respiration and mycorrhizal production and respiration), GPP (computed as the sum of ANPP, TBCF and estimated aboveground respiration) on 12 plots representing the gradient of productivity found within the stand. The spatial heterogeneity of topography and associated soil attributes across the stand likely explained this fertility gradient. Component fluxes of GPP and C partitioning were found to vary among plots. Stem NPP ranged from 554 g C m(-2) year(-1) on the plot with lowest GPP to 923 g C m(-2) year(-1) on the plot with highest GPP. Total belowground carbon flux ranged from 497 to 1235 g C m(-2) year(-1) and showed no relationship with ANPP or GPP. Carbon partitioning to stem NPP increased from 0.19 to 0.23, showing a positive trend of increase with GPP (R-2 = 0.29, P = 0.07). Variations in stem wood production across the gradient of productivity observed at our experimental site were a result of the variability in C partitioning to different forest system components.

Is the LHC observing the pseudoscalar state of a two-Higgs-doublet model?

The ATLAS and CMS collaborations have recently shown data suggesting the presence of a Higgs boson in the vicinity of 125 GeV. We show that a two-Higgs-doublet model spectrum, with the pseudoscalar state being the lightest, could be responsible for the diphoton signal events. In this model, the other scalars are considerably heavier and are not excluded by the current LHC data. If this assumption is correct, future LHC data should show a strengthening of the gamma gamma signal, while the signals in the ZZ(()*()) -> 4l and WW(*()) -> 2l2 nu channels should diminish and eventually disappear, due to the absence of diboson tree-level couplings of the CP-odd state. The heavier CP-even neutral scalars can now decay into channels involving the CP-odd light scalar which, together with their larger masses, allow them to avoid the existing bounds on Higgs searches. We suggest additional signals to confirm this scenario at the LHC, in the decay channels of the heavier scalars into AA and AZ. Finally, this inverted two-Higgs-doublet spectrum is characteristic in models where fermion condensation leads to electroweak symmetry breaking. We show that in these theories it is possible to obtain the observed diphoton signal at or somewhat above the prediction for the standard model Higgs for the typical values of the parameters predicted.

Ground and excited state charmonium production in p plus p collisions at root s=200 GeV

We report on charmonium measurements [J/psi (1S), psi' (2S), and chi(c) (1P)] in p + p collisions at root s = 200 GeV. We find that the fraction of J/psi coming from the feed-down decay of psi' and chi(c) in the midrapidity region (vertical bar y vertical bar < 0: 35) is 9.6 +/- 2.4% and 32 +/- 9%, respectively. We also present the p(T) and rapidity dependencies of the J/psi yield measured via dielectron decay at midrapidity (vertical bar y vertical bar < 0.35) and via dimuon decay at forward rapidity (1.2 < vertical bar y vertical bar < 2.2). The statistical precision greatly exceeds that reported in our previous publication [Phys. Rev. Lett. 98, 232002 (2007)]. The new results are compared with other experiments and discussed in the context of current charmonium production models.

Evaluation of the Concentration of Nonessential and Essential Elements in Chicken, Pork, and Beef Samples Produced in Brazil

Food safety is a global concern. Meat represents the most important protein source for humans. Thus, contamination of meat products by nonessential elements is a ready source of human exposure. In addition, knowledge of the concentration of essential elements is also relevant with respect to human nutrition. The aim of the present study was to determine the concentration of 17 elements in pork, beef, and chicken produced in Brazil. Meat samples were analyzed by inductively coupled plasma mass spectrometry. The estimated daily intake for nonessential elements including arsenic (As), cadmium (Cd), lead (Pb), mercury (Hg), and antimony (Sb) through meat consumption is below the toxicological reference values. However, high levels were detected for the nonessential element cesium (Cs), mainly in beef samples, an observation that deserves future studies to identify the source of contamination and potential adverse consequences.

Secondary production of sandy beach macrofauna: An evaluation of predictive models

During the last three decades, several predictive models have been developed to estimate the somatic production of macroinvertebrates. Although the models have been evaluated for their ability to assess the production of macrobenthos in different marine ecosystems, these approaches have not been applied specifically to sandy beach macrofauna and may not be directly applicable to this transitional environment. Hence, in this study, a broad literature review of sandy beach macrofauna production was conducted and estimates obtained with cohort-based and size-based methods were collected. The performance of nine models in estimating the production of individual populations from the sandy beach environment, evaluated for all taxonomic groups combined and for individual groups separately, was assessed, comparing the production predicted by the models to the estimates obtained from the literature (observed production). Most of the models overestimated population production compared to observed production estimates, whether for all populations combined or more specific taxonomic groups. However, estimates by two models developed by Cusson and Bourget provided best fits to measured production, and thus represent the best alternatives to the cohort-based and size-based methods in this habitat. The consistent performance of one of these Cusson and Bourget models, which was developed for the macrobenthos of sandy substrate habitats (C&B-SS), shows that the performance of a model does not depend on whether it was developed for a specific taxonomic group. Moreover, since some widely used models (e.g., the Robertson model) show very different responses when applied to the macrofauna of different marine environments (e.g., sandy beaches and estuaries), prior evaluation of these models is essential.

Influence diagnostics in Gaussian spatial linear models

Spatial linear models have been applied in numerous fields such as agriculture, geoscience and environmental sciences, among many others. Spatial dependence structure modelling, using a geostatistical approach, is an indispensable tool to estimate the parameters that define this structure. However, this estimation may be greatly affected by the presence of atypical observations in the sampled data. The purpose of this paper is to use diagnostic techniques to assess the sensitivity of the maximum-likelihood estimators, covariance functions and linear predictor to small perturbations in the data and/or the spatial linear model assumptions. The methodology is illustrated with two real data sets. The results allowed us to conclude that the presence of atypical values in the sample data have a strong influence on thematic maps, changing the spatial dependence structure.

Co-metabolic models of Streptococcus thermophilus in co-culture with Lactobacillus bulgaricus or Lactobacillus acidophilus

To shed light on the interactions occurring in fermented milks when using co-cultures of Streptococcus thermophilus with Lactobacillus bulgaricus (StLb) or Lactobacillus acidophilus (StLa), a new co-metabolic model was proposed and checked either in the presence of Inulin as a prebiotic or not. For this purpose, the experimental data of concentrations of substrates and fermented products were utilized in balances of carbon, reduction degree and ATP. S. thermophilus exhibited always quicker growth compared to the other two microorganisms, while the percentage of lactose fermented to lactic acid, that of galactose metabolized, and the levels of diacetyl and acetoin formed strongly depended on the type of co-culture and the presence of inulin. The StLb co-culture led to higher acetoin and lower diacetyl levels compared to StLa, probably because of more reducing conditions or limited acetoin dehydrogenation. Inulin addition to StLa suppressed acetoin accumulation and hindered that of diacetyl, suggesting catabolite repression of alpha-acetolactate synthase expression in S. thermophilus. Both co-cultures showed the highest ATP requirements for biomass growth and maintenance at the beginning of fermentation, consistently with the high energy demand of enzyme induction during lag phase. Inulin reduced these requirements making biomass synthesis and maintenance less energy-consuming. Only a fraction of galactose was released from lactose, consistently with the galactose-positive phenotype of most dairy strains. The galactose fraction metabolized without inulin was about twice that in its presence, which suggests inhibition of the galactose transport system of S. thermophilus by fructose released from partial inulin hydrolysis. (C) 2012 Elsevier B.V. All rights reserved.

Fractionation of lemon essential oil by solvent extraction: Phase equilibrium for model systems at T=298.2 K

The fractioning of lemon essential oil can be performed by liquid-liquid extraction using hydrous ethanol as a solvent. A quaternary mixture composed of limonene, gamma-terpinene, beta-pinene, and citral was used to simulate lemon essential oil. In this paper, we present (liquid + liquid) equilibrium data that were experimentally determined for systems containing essential oil compounds, ethanol, and water at T = 298.2 K. The experimental data were correlated using the NRTL and UNIQUAC models, and the mean deviations between calculated and experimental data were less than 0.0053 in all systems, indicating the accuracy of these molecular models in describing our systems. The results show that as the water content in the solvent phase increased, the values of the distribution coefficients decreased, regardless of the type of compound studied. However, the oxygenated compound always showed the highest distribution coefficient among the components of the essential oil, thus making deterpenation of the lemon essential oil a feasible process. (C) 2012 Elsevier Ltd. All rights reserved.

A regional multirnodulus algorithm for blind equalization of QAM signals: Introduction and steady-state analysis

It is well known that constant-modulus-based algorithms present a large mean-square error for high-order quadrature amplitude modulation (QAM) signals, which may damage the switching to decision-directed-based algorithms. In this paper, we introduce a regional multimodulus algorithm for blind equalization of QAM signals that performs similar to the supervised normalized least-mean-squares (NLMS) algorithm, independently of the QAM order. We find a theoretical relation between the coefficient vector of the proposed algorithm and the Wiener solution and also provide theoretical models for the steady-state excess mean-square error in a nonstationary environment. The proposed algorithm in conjunction with strategies to speed up its convergence and to avoid divergence can bypass the switching mechanism between the blind mode and the decision-directed mode. (c) 2012 Elsevier B.V. All rights reserved.

Models of passive and active dendrite motoneuron pools and their differences in muscle force control

Motoneuron (MN) dendrites may be changed from a passive to an active state by increasing the levels of spinal cord neuromodulators, which activate persistent inward currents (PICs). These exert a powerful influence on MN behavior and modify the motor control both in normal and pathological conditions. Motoneuronal PICs are believed to induce nonlinear phenomena such as the genesis of extra torque and torque hysteresis in response to percutaneous electrical stimulation or tendon vibration in humans. An existing large-scale neuromuscular simulator was expanded to include MN models that have a capability to change their dynamic behaviors depending on the neuromodulation level. The simulation results indicated that the variability (standard deviation) of a maintained force depended on the level of neuromodulatory activity. A force with lower variability was obtained when the motoneuronal network was under a strong influence of PICs, suggesting a functional role in postural and precision tasks. In an additional set of simulations when PICs were active in the dendrites of the MN models, the results successfully reproduced experimental results reported from humans. Extra torque was evoked by the self-sustained discharge of spinal MNs, whereas differences in recruitment and de-recruitment levels of the MNs were the main reason behind torque and electromyogram (EMG) hysteresis. Finally, simulations were also used to study the influence of inhibitory inputs on a MN pool that was under the effect of PICs. The results showed that inhibition was of great importance in the production of a phasic force, requiring a reduced co-contraction of agonist and antagonist muscles. These results show the richness of functionally relevant behaviors that can arise from a MN pool under the action of PICs.