Exact field-driven interface dynamics in the two-dimensional stochastic Ising model with helicoidal boundary conditions

We investigate the interface dynamics of the two-dimensional stochastic Ising model in an external field under helicoidal boundary conditions. At sufficiently low temperatures and fields, the dynamics of the interface is described by an exactly solvable high-spin asymmetric quantum Hamiltonian that is the infinitesimal generator of the zero range process. Generally, the critical dynamics of the interface fluctuations is in the Kardar-Parisi-Zhang universality class of critical behavior. We remark that a whole family of RSOS interface models similar to the Ising interface model investigated here can be described by exactly solvable restricted high-spin quantum XXZ-type Hamiltonians. (C) 2012 Elsevier B.V. All rights reserved.

Three time-based scale formulations for the two-stage lot sizing and scheduling in process industries

In this paper, we propose three novel mathematical models for the two-stage lot-sizing and scheduling problems present in many process industries. The problem shares a continuous or quasi-continuous production feature upstream and a discrete manufacturing feature downstream, which must be synchronized. Different time-based scale representations are discussed. The first formulation encompasses a discrete-time representation. The second one is a hybrid continuous-discrete model. The last formulation is based on a continuous-time model representation. Computational tests with state-of-the-art MIP solver show that the discrete-time representation provides better feasible solutions in short running time. On the other hand, the hybrid model achieves better solutions for longer computational times and was able to prove optimality more often. The continuous-type model is the most flexible of the three for incorporating additional operational requirements, at a cost of having the worst computational performance. Journal of the Operational Research Society (2012) 63, 1613-1630. doi:10.1057/jors.2011.159 published online 7 March 2012

Stripe-tetragonal phase transition in the two-dimensional Ising model with dipole interactions: Partition function zeros approach

We have performed multicanonical simulations to study the critical behavior of the two-dimensional Ising model with dipole interactions. This study concerns the thermodynamic phase transitions in the range of the interaction delta where the phase characterized by striped configurations of width h = 1 is observed. Controversial results obtained from local update algorithms have been reported for this region, including the claimed existence of a second-order phase transition line that becomes first order above a tricritical point located somewhere between delta = 0.85 and 1. Our analysis relies on the complex partition function zeros obtained with high statistics from multicanonical simulations. Finite size scaling relations for the leading partition function zeros yield critical exponents. that are clearly consistent with a single second-order phase transition line, thus excluding such a tricritical point in that region of the phase diagram. This conclusion is further supported by analysis of the specific heat and susceptibility of the orientational order parameter.

A spatial stochastic model for rumor transmission

We consider an interacting particle system representing the spread of a rumor by agents on the d-dimensional integer lattice. Each agent may be in any of the three states belonging to the set {0,1,2}. Here 0 stands for ignorants, 1 for spreaders and 2 for stiflers. A spreader tells the rumor to any of its (nearest) ignorant neighbors at rate lambda. At rate alpha a spreader becomes a stifler due to the action of other (nearest neighbor) spreaders. Finally, spreaders and stiflers forget the rumor at rate one. We study sufficient conditions under which the rumor either becomes extinct or survives with positive probability.

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.

STOCHASTIC MODEL FOR SIMULATING MAIZE YIELD

Maize is one of the most important crops in the world. The products generated from this crop are largely used in the starch industry, the animal and human nutrition sector, and biomass energy production and refineries. For these reasons, there is much interest in figuring the potential grain yield of maize genotypes in relation to the environment in which they will be grown, as the productivity directly affects agribusiness or farm profitability. Questions like these can be investigated with ecophysiological crop models, which can be organized according to different philosophies and structures. The main objective of this work is to conceptualize a stochastic model for predicting maize grain yield and productivity under different conditions of water supply while considering the uncertainties of daily climate data. Therefore, one focus is to explain the model construction in detail, and the other is to present some results in light of the philosophy adopted. A deterministic model was built as the basis for the stochastic model. The former performed well in terms of the curve shape of the above-ground dry matter over time as well as the grain yield under full and moderate water deficit conditions. Through the use of a triangular distribution for the harvest index and a bivariate normal distribution of the averaged daily solar radiation and air temperature, the stochastic model satisfactorily simulated grain productivity, i.e., it was found that 10,604 kg ha(-1) is the most likely grain productivity, very similar to the productivity simulated by the deterministic model and for the real conditions based on a field experiment.

A Two-Stage Aerobic/Anaerobic Denitrifying Horizontal Bioreactor Designed for Treating Ammonium and H2S Simultaneously

A two-stage bioreactor was operated for a period of 140 days in order to develop a post-treatment process based on anaerobic bioxidation of sulfite. This process was designed for simultaneously treating the effluent and biogas of a full-scale UASB reactor, containing significant concentrations of NH4 and H2S, respectively. The system comprised of two horizontal-flow bed-packed reactors operated with different oxygen concentrations. Ammonium present in the effluent was transformed into nitrates in the first aerobic stage. The second anaerobic stage combined the treatment of nitrates in the liquor with the hydrogen sulfide present in the UASB-reactor biogas. Nitrates were consumed with a significant production of sulfate, resulting in a nitrate removal rate of 0.43 kg N m(3) day(-1) and a parts per thousand yen92 % efficiency. Such a removal rate is comparable to those achieved by heterotrophic denitrifying systems. Polymeric forms of sulfur were not detected (elementary sulfur); sulfate was the main product of the sulfide-based denitrifying process. S-sulfate was produced at a rate of about 0.35 kg m(3) day(-1). Sulfur inputs as S-H2S were estimated at about 0.75 kg m(3) day(-1) and Chemical Oxygen Demand (COD) removal rates did not vary significantly during the process. DGGE profiling and 16S rRNA identified Halothiobacillus-like species as the key microorganism supporting this process; such a strain has not yet been previously associated with such bioengineered systems.

Hydrogen and Methane Production, Energy Recovery, and Organic Matter Removal from Effluents in a Two-Stage Fermentative Process

This study evaluates the potential for using different effluents for simultaneous H-2 and CH4 production in a two-stage batch fermentation process with mixed microflora. An appreciable amount of H-2 was produced from parboiled rice wastewater (23.9 mL g(-1) chemical oxygen demand [COD]) and vinasse (20.8 mL g(-1) COD), while other effluents supported CH4 generation. The amount of CH4 produced was minimum for sewage (46.3 mL g(-1) COD), followed by parboiled rice wastewater (115.5 mL g(-1) COD) and glycerol (180.1 mL g(-1) COD). The maximum amount of CH4 was observed for vinasse (255.4 mL g(-1) COD). The total energy recovery from vinasse (10.4 kJ g(-1) COD) corresponded to the maximum COD reduction (74.7 %), followed by glycerol (70.38 %, 7.20 kJ g(-1) COD), parboiled rice wastewater (63.91 %, 4.92 kJ g(-1) COD), and sewage (51.11 %, 1.85 kJ g(-1) COD). The relatively high performance of vinasse in such comparisons could be attributed to the elevated concentrations of macronutrients contained in raw vinasse. The observations are based on kinetic parameters of H-2 and CH4 production and global energy recovery of the process. These observations collectively suggest that organic-rich effluents can be deployed for energy recovery with sequential generation of H-2 and CH4.

Integrodifference model for blowfly invasion

We propose a stage-structured integrodifference model for blowflies' growth and dispersion taking into account the density dependence of fertility and survival rates and the non-overlap of generations. We assume a discrete-time, stage-structured, model. The spatial dynamics is introduced by means of a redistribution kernel. We treat one and two dimensional cases, the latter on the semi-plane, with a reflexive boundary. We analytically show that the upper bound for the invasion front speed is the same as in the one-dimensional case. Using laboratory data for fertility and survival parameters and dispersal data of a single generation from a capture-recapture experiment in South Africa, we obtain an estimate for the velocity of invasion of blowflies of the species Chrysomya albiceps. This model predicts a speed of invasion which was compared to actual observational data for the invasion of the focal species in the Neotropics. Good agreement was found between model and observations.

The Integration of the Glutamatergic and the White Matter Hypotheses of Schizophrenia's Etiology

Background: schizophrenia's endophenotipic profile is not only generally complex, but often varies from case to case. The perspective of trying to define specific anatomic correlates of the syndrome has led to disappointing results. In that context, neurophysiologic hypotheses (e. g. glutamatergic hypothesis) and connectivity hypotheses became prominent. Nevertheless, despite their commitment to the principle of denying 'localist' views and approaching the syndrome's endophenotype from a whole brain perspective, efforts to integrate both have not flourished at this moment in time. Objectives: This paper aims to introduce a new etiological model that integrates the glutamatergic and the WM (WM) hypotheses of schizophrenia's etiology. This model proposes to serve as a framework in order to relate to patterns of brain abnormalities from the onset of the syndrome to stages of advanced chronification. Highlights: Neurotransmitter abnormalities forego noticeable WM abnormalities. The former, chiefly represented by NMDAR hypo-function and associated molecular cascades, is related to the first signs of cell loss. This process is both directly and indirectly integrated to the underpinning of WM structural abnormalities; not only is the excess of glutamate toxic to the WM, but its disruption is associated to the expression of known genetic risk factors (e. g., NRG-1). A second level of the model develops the idea that abnormal neurotransmission within specific neural populations ('motifs') impair particular cognitive abilities, while subsequent WM structural abnormalities impair the integration of brain functions and multimodality. As a result of this two-stage dynamic, the affected individual progresses from experiencing specific cognitive and psychological deficits, to a condition of cognitive and existential fragmentation, linked to hardly reversible decreases in psychosocial functioning.

Antimicrobial activity of two techniques for arm skin disinfection of blood donors in Brazil

Objective: Evaluation of the antimicrobial effect of skin disinfection techniques is essential to avoid the transmission of infectious agents during blood transfusion. The aim of this study was to examine the effectiveness of two methods of arm skin disinfection used in blood donors at a Hemotherapy Center in Brazil that represents an important centre for distributing haemocomponents to many cities in the country. Methods: Two skin disinfection techniques in 50 blood donors were evaluated. For the first arm, 10% povidone-iodine/two-stage technique was used. On the opposite arm, 0.5% chlorhexidine digluconate alcohol solution/one-stage technique was used. The swabs were seeded on three culture media: blood agar, mannitol salt agar and Mac Conkey agar. Automated bacterial classification based on biochemical tests/specific substrates was performed. Donor characteristics were collected using the computerised system of the Hemotherapy Center. Results: We found that microbial reduction was significantly higher for 10% povidone-iodine technique (98.57-98.87%) when compared with 0.5% chlorhexidine technique (94.38-95.06%). The species Leuconostoc mesenteroides and Staphylococcus hominis showed resistance to both disinfection techniques. We did not find statistically significant relationships between donor characteristics and microbial reduction. Conclusions: Arm skin disinfection with 10% povidone-iodine produced better antimicrobial activity. We must acknowledge that 10% povidone-iodine technique has the limitation of being a two-stage method. However, prevention of adverse events due to bacterial contamination and transfusion reactions should be prioritised. Production of hypoallergenic and stronger antiseptics that allowed a safe one-stage disinfection technique should be encouraged in health systems, not only in Brazil but also around the world.

A new damage model for composite laminates

Aircraft composite structures must have high stiffness and strength with low weight, which can guarantee the increase of the pay-load for airplanes without losing airworthiness. However, the mechanical behavior of composite laminates is very complex due the inherent anisotropy and heterogeneity. Many researchers have developed different failure progressive analyses and damage models in order to predict the complex failure mechanisms. This work presents a damage model and progressive failure analysis that requires simple experimental tests and that achieves good accuracy. Firstly, the paper explains damage initiation and propagation criteria and a procedure to identify the material parameters. In the second stage, the model was implemented as a UMAT (User Material Subroutine), which is linked to finite element software, ABAQUS (TM), in order to predict the composite structures behavior. Afterwards, some case studies, mainly off-axis coupons under tensile or compression loads, with different types of stacking sequence were analyzed using the proposed material model. Finally, the computational results were compared to the experimental results, verifying the capability of the damage model in order to predict the composite structure behavior. (C) 2011 Elsevier Ltd. All rights reserved.

Diet and the risk of head and neck cancer: a pooled analysis in the INHANCE consortium

We investigated the association between diet and head and neck cancer (HNC) risk using data from the International Head and Neck Cancer Epidemiology (INHANCE) consortium. The INHANCE pooled data included 22 case-control studies with 14,520 cases and 22,737 controls. Center-specific quartiles among the controls were used for food groups, and frequencies per week were used for single food items. A dietary pattern score combining high fruit and vegetable intake and low red meat intake was created. Odds ratios (OR) and 95% confidence intervals (CI) for the dietary items on the risk of HNC were estimated with a two-stage random-effects logistic regression model. An inverse association was observed for higher-frequency intake of fruit (4th vs. 1st quartile OR = 0.52, 95% CI = 0.43-0.62, p (trend) < 0.01) and vegetables (OR = 0.66, 95% CI = 0.49-0.90, p (trend) = 0.01). Intake of red meat (OR = 1.40, 95% CI = 1.13-1.74, p (trend) = 0.13) and processed meat (OR = 1.37, 95% CI = 1.14-1.65, p (trend) < 0.01) was positively associated with HNC risk. Higher dietary pattern scores, reflecting high fruit/vegetable and low red meat intake, were associated with reduced HNC risk (per score increment OR = 0.90, 95% CI = 0.84-0.97).

A Bayesian destructive weighted Poisson cure rate model and an application to a cutaneous melanoma data

In this article, we propose a new Bayesian flexible cure rate survival model, which generalises the stochastic model of Klebanov et al. [Klebanov LB, Rachev ST and Yakovlev AY. A stochastic-model of radiation carcinogenesis - latent time distributions and their properties. Math Biosci 1993; 113: 51-75], and has much in common with the destructive model formulated by Rodrigues et al. [Rodrigues J, de Castro M, Balakrishnan N and Cancho VG. Destructive weighted Poisson cure rate models. Technical Report, Universidade Federal de Sao Carlos, Sao Carlos-SP. Brazil, 2009 (accepted in Lifetime Data Analysis)]. In our approach, the accumulated number of lesions or altered cells follows a compound weighted Poisson distribution. This model is more flexible than the promotion time cure model in terms of dispersion. Moreover, it possesses an interesting and realistic interpretation of the biological mechanism of the occurrence of the event of interest as it includes a destructive process of tumour cells after an initial treatment or the capacity of an individual exposed to irradiation to repair altered cells that results in cancer induction. In other words, what is recorded is only the damaged portion of the original number of altered cells not eliminated by the treatment or repaired by the repair system of an individual. Markov Chain Monte Carlo (MCMC) methods are then used to develop Bayesian inference for the proposed model. Also, some discussions on the model selection and an illustration with a cutaneous melanoma data set analysed by Rodrigues et al. [Rodrigues J, de Castro M, Balakrishnan N and Cancho VG. Destructive weighted Poisson cure rate models. Technical Report, Universidade Federal de Sao Carlos, Sao Carlos-SP. Brazil, 2009 (accepted in Lifetime Data Analysis)] are presented.

Heat conduction in a chain of harmonic and anharmonic oscillators under the presence of an energy conserving noise

Reproducing Fourier's law of heat conduction from a microscopic stochastic model is a long standing challenge in statistical physics. As was shown by Rieder, Lebowitz and Lieb many years ago, a chain of harmonically coupled oscillators connected to two heat baths at different temperatures does not reproduce the diffusive behaviour of Fourier's law, but instead a ballistic one with an infinite thermal conductivity. Since then, there has been a substantial effort from the scientific community in identifying the key mechanism necessary to reproduce such diffusivity, which usually revolved around anharmonicity and the effect of impurities. Recently, it was shown by Dhar, Venkateshan and Lebowitz that Fourier's law can be recovered by introducing an energy conserving noise, whose role is to simulate the elastic collisions between the atoms and other microscopic degrees of freedom, which one would expect to be present in a real solid. For a one-dimensional chain this is accomplished numerically by randomly flipping - under the framework of a Poisson process with a variable “rate of collisions" - the sign of the velocity of an oscillator. In this poster we present Langevin simulations of a one-dimensional chain of oscillators coupled to two heat baths at different temperatures. We consider both harmonic and anharmonic (quartic) interactions, which are studied with and without the energy conserving noise. With these results we are able to map in detail how the heat conductivity k is influenced by both anharmonicity and the energy conserving noise. We also present a detailed analysis of the behaviour of k as a function of the size of the system and the rate of collisions, which includes a finite-size scaling method that enables us to extract the relevant critical exponents. Finally, we show that for harmonic chains, k is independent of temperature, both with and without the noise. Conversely, for anharmonic chains we find that k increases roughly linearly with the temperature of a given reservoir, while keeping the temperature difference fixed.