Modeling the kinetics of the coalescence of water droplets in crude oil emulsions subject to an electric field, with the cellular automata technique

In this study, the concept of cellular automata is applied in an innovative way to simulate the separation of phases in a water/oil emulsion. The velocity of the water droplets is calculated by the balance of forces acting on a pair of droplets in a group, and cellular automata is used to simulate the whole group of droplets. Thus, it is possible to solve the problem stochastically and to show the sequence of collisions of droplets and coalescence phenomena. This methodology enables the calculation of the amount of water that can be separated from the emulsion under different operating conditions, thus enabling the process to be optimized. Comparisons between the results obtained from the developed model and the operational performance of an actual desalting unit are carried out. The accuracy observed shows that the developed model is a good representation of the actual process. (C) 2010 Published by Elsevier Ltd.

On the basic reproduction number and the topological properties of the contact network: An epidemiological study in mainly locally connected cellular automata

We study the spreading of contagious diseases in a population of constant size using susceptible-infective-recovered (SIR) models described in terms of ordinary differential equations (ODEs) and probabilistic cellular automata (PCA). In the PCA model, each individual (represented by a cell in the lattice) is mainly locally connected to others. We investigate how the topological properties of the random network representing contacts among individuals influence the transient behavior and the permanent regime of the epidemiological system described by ODE and PCA. Our main conclusions are: (1) the basic reproduction number (commonly called R(0)) related to a disease propagation in a population cannot be uniquely determined from some features of transient behavior of the infective group; (2) R(0) cannot be associated to a unique combination of clustering coefficient and average shortest path length characterizing the contact network. We discuss how these results can embarrass the specification of control strategies for combating disease propagations. (C) 2009 Elsevier B.V. All rights reserved.

Small-World Effect in Epidemics Using Cellular Automata

The spread of an infectious disease in a population involves interactions leading to an epidemic outbreak through a network of contacts. Extending on Watts and Strogatz (1998) who showed that short-distance connections create a small-world effect, a model combining short-and long-distance probabilistic and regularly updated contacts helps considering spatial heterogeneity. The method is based on cellular automata. The presence of long-distance connections accelerates the small-world effect, as if the world shrank in proportion of their total number.

Cellular automaton model for molecular traffic jams

We consider the time evolution of an exactly solvable cellular automaton with random initial conditions both in the large-scale hydrodynamic limit and on the microscopic level. This model is a version of the totally asymmetric simple exclusion process with sublattice parallel update and thus may serve as a model for studying traffic jams in systems of self-driven particles. We study the emergence of shocks from the microscopic dynamics of the model. In particular, we introduce shock measures whose time evolution we can compute explicitly, both in the thermodynamic limit and for open boundaries where a boundary-induced phase transition driven by the motion of a shock occurs. The motion of the shock, which results from the collective dynamics of the exclusion particles, is a random walk with an internal degree of freedom that determines the jump direction. This type of hopping dynamics is reminiscent of some transport phenomena in biological systems.

Sensitivity to noise and ergodicity of an assembly line of cellular automata that classifies density

We investigate the sensitivity of the composite cellular automaton of H. Fuks [Phys. Rev. E 55, R2081 (1997)] to noise and assess the density classification performance of the resulting probabilistic cellular automaton (PCA) numerically. We conclude that the composite PCA performs the density classification task reliably only up to very small levels of noise. In particular, it cannot outperform the noisy Gacs-Kurdyumov-Levin automaton, an imperfect classifier, for any level of noise. While the original composite CA is nonergodic, analyses of relaxation times indicate that its noisy version is an ergodic automaton, with the relaxation times decaying algebraically over an extended range of parameters with an exponent very close (possibly equal) to the mean-field value.

Who should wear mask against airborne infections? Altering the contact network for controlling the spread of contagious diseases

There are several ways of controlling the propagation of a contagious disease. For instance, to reduce the spreading of an airborne infection, individuals can be encouraged to remain in their homes and/or to wear face masks outside their domiciles. However, when a limited amount of masks is available, who should use them: the susceptible subjects, the infective persons or both populations? Here we employ susceptible-infective-recovered (SIR) models described in terms of ordinary differential equations and probabilistic cellular automata in order to investigate how the deletion of links in the random complex network representing the social contacts among individuals affects the dynamics of a contagious disease. The inspiration for this study comes from recent discussions about the impact of measures usually recommended by health public organizations for preventing the propagation of the swine influenza A (H1N1) virus. Our answer to this question can be valid for other eco-epidemiological systems. (C) 2010 Elsevier BM. All rights reserved.

An extinction-survival-type phase transition in the probabilistic cellular automaton p182-q200

We investigate the critical behaviour of a probabilistic mixture of cellular automata (CA) rules 182 and 200 (in Wolfram`s enumeration scheme) by mean-field analysis and Monte Carlo simulations. We found that as we switch off one CA and switch on the other by the variation of the single parameter of the model, the probabilistic CA (PCA) goes through an extinction-survival-type phase transition, and the numerical data indicate that it belongs to the directed percolation universality class of critical behaviour. The PCA displays a characteristic stationary density profile and a slow, diffusive dynamics close to the pure CA 200 point that we discuss briefly. Remarks on an interesting related stochastic lattice gas are addressed in the conclusions.

The Effect of Spatial Scale on Predicting Time Series: A Study on Epidemiological System Identification

A susceptible-infective-recovered (SIR) epidemiological model based on probabilistic cellular automaton (PCA) is employed for simulating the temporal evolution of the registered cases of chickenpox in Arizona, USA, between 1994 and 2004. At each time step, every individual is in one of the states S, I, or R. The parameters of this model are the probabilities of each individual (each cell forming the PCA lattice ) passing from a state to another state. Here, the values of these probabilities are identified by using a genetic algorithm. If nonrealistic values are allowed to the parameters, the predictions present better agreement with the historical series than if they are forced to present realistic values. A discussion about how the size of the PCA lattice affects the quality of the model predictions is presented. Copyright (C) 2009 L. H. A. Monteiro et al.

System Identification and Prediction of Dengue Fever Incidence in Rio de Janeiro

Identification, prediction, and control of a system are engineering subjects, regardless of the nature of the system. Here, the temporal evolution of the number of individuals with dengue fever weekly recorded in the city of Rio de Janeiro, Brazil, during 2007, is used to identify SIS (susceptible-infective-susceptible) and SIR (susceptible-infective-removed) models formulated in terms of cellular automaton (CA). In the identification process, a genetic algorithm (GA) is utilized to find the probabilities of the state transition S -> I able of reproducing in the CA lattice the historical series of 2007. These probabilities depend on the number of infective neighbors. Time-varying and non-time-varying probabilities, three different sizes of lattices, and two kinds of coupling topology among the cells are taken into consideration. Then, these epidemiological models built by combining CA and GA are employed for predicting the cases of sick persons in 2008. Such models can be useful for forecasting and controlling the spreading of this infectious disease.

A vaccination game based on public health actions and personal decisions

Susceptible-infective-removed (SIR) models are commonly used for representing the spread of contagious diseases. A SIR model can be described in terms of a probabilistic cellular automaton (PCA), where each individual (corresponding to a cell of the PCA lattice) is connected to others by a random network favoring local contacts. Here, this framework is employed for investigating the consequences of applying vaccine against the propagation of a contagious infection, by considering vaccination as a game, in the sense of game theory. In this game, the players are the government and the susceptible newborns. In order to maximize their own payoffs, the government attempts to reduce the costs for combating the epidemic, and the newborns may be vaccinated only when infective individuals are found in their neighborhoods and/or the government promotes an immunization program. As a consequence of these strategies supported by cost-benefit analysis and perceived risk, numerical simulations show that the disease is not fully eliminated and the government implements quasi-periodic vaccination campaigns. (C) 2011 Elsevier B.V. All rights reserved.

Critical behavior of a contact process with aperiodic transition rates

We performed Monte Carlo simulations to investigate the steady-state critical behavior of a one-dimensional contact process with an aperiodic distribution of rates of transition. As in the presence of randomness, spatial fluctuations can lead to changes of critical behavior. For sufficiently weak fluctuations, we give numerical evidence to show that there is no departure from the universal critical behavior of the underlying uniform model. For strong spatial fluctuations, the analysis of the data indicates a change of critical universality class.

Interaction of Mycoplasma genitalium with host cells: evidence for nuclear localization

Mycoplasma genitalium (Mg) is a mollicute that causes a range of human urogenital infections. A hallmark of these bacteria is their ability to establish chronic infections that can persist despite completion of appropriate antibiotic therapies and intact and functional immune systems. Intimate adherence and surface colonization of mycoplasmas to host cells are important pathogenic features. However, their facultative intracellular nature is poorly understood, partly due to difficulties in developing and standardizing cellular interaction model systems. Here, we characterize growth and invasion properties of two Mg strains (G37 and 1019V). Mg G37 is a high-passage laboratory strain, while Mg 1019V is a low-passage isolate recovered from the cervix. The two strains diverge partially in gene sequences for adherence-related proteins and exhibit subtle variations in their axenic growth. However, with both strains and consistent with our previous studies, a subset of adherent Mg organisms invade host cells and exhibit perinuclear targeting. Remarkably, intranuclear localization of Mg proteins is observed, which occurred as early as 30 min after infection. Mg strains deficient in adherence were markedly reduced in their ability to invade and associate with perinuclear and nuclear sites.

FAST, PARALLEL AND SECURE CRYPTOGRAPHY ALGORITHM USING LORENZ`S ATTRACTOR

A novel cryptography method based on the Lorenz`s attractor chaotic system is presented. The proposed algorithm is secure and fast, making it practical for general use. We introduce the chaotic operation mode, which provides an interaction among the password, message and a chaotic system. It ensures that the algorithm yields a secure codification, even if the nature of the chaotic system is known. The algorithm has been implemented in two versions: one sequential and slow and the other, parallel and fast. Our algorithm assures the integrity of the ciphertext (we know if it has been altered, which is not assured by traditional algorithms) and consequently its authenticity. Numerical experiments are presented, discussed and show the behavior of the method in terms of security and performance. The fast version of the algorithm has a performance comparable to AES, a popular cryptography program used commercially nowadays, but it is more secure, which makes it immediately suitable for general purpose cryptography applications. An internet page has been set up, which enables the readers to test the algorithm and also to try to break into the cipher.

Amphetamine modulates cellular recruitment and airway reactivity in a rat model of allergic lung inflammation

Asthma is characterized by pulmonary cellular infiltration, vascular exudation and airway hyperresponsiveness. Several drugs that modify central nervous system (CNS) activity can modulate the course of asthma. Amphetamine (AMPH) is a highly abused drug that presents potent stimulating effects on the CNS and has been shown to induce behavioral, biochemical and immunological effects. The purpose of this study was to investigate the effects of AMPH on pulmonary cellular influx, vascular permeability and airway reactivity. AMPH effects on adhesion molecule expression, IL-10 and IL-4 release and mast cell degranulation were also studied. Male Wistar rats were sensitized with ovalbumin (OVA) plus alum via subcutaneous injection. One week later, the rats received another injection of OVA-alum (booster). Two weeks after this booster, the rats were subjected to AMPH treatment 12 h prior to the OVA airway challenge. In rats treated with AMPH, the OVA challenge reduced cell recruitment into the lung, the vascular permeability and the cellular expression of ICAM-1 and Mac-1. Additionally, elevated levels of IL-10 and IL-4 were found in samples of lung explants from allergic rats. AMPH treatment, in comparison, increased IL-10 levels but reduced those of IL-4 in the lung explants. Moreover, the tracheal responsiveness to methacholine (MCh), as well as to an in vitro OVA challenge, was reduced by AMPH treatment, and levels of PCA titers were not modified by the drug. Our findings suggest that single AMPH treatment down-regulates several parameters of lung inflammation, such as cellular migration, vascular permeability and tracheal responsiveness. These results also indicate that AMPH actions on allergic lung inflammation include endothelium-leukocyte interaction mechanisms, cytokine release and mast cell degranulation. (C) 2010 Elsevier Ireland Ltd. All rights reserved.

Histopathology, humoral and cellular immune response in the murine model of Leishmania (Viannia) shawi

Leishmania (Viannia) shawl was recently characterized and few studies concerning modifications in cellular and humoral immune responses in experimental leishmaniasis have been conducted. In this work, immunopathological changes induced by L. shawl in chronically infected BALB/c mice were investigated. Infected BALB/c mice developed increased lesion size associated with strong inflammatory infiltrate diffusely distributed in the dermis, with highly infected macrophages. The humoral immune response was predominantly directed toward the IgG1 isotype. The functional activity of CD4(+) and CD8(+) T cells showed significantly increased TNF-alpha mRNA levels associated with reduced IFN-gamma expression by CD4(+) T cells and the double negative (dn) CD4CD8 cell subset. High IL-4 levels expressed by CD8(+) T cells and dnCD4CD8 and TGF-beta by CD4(+) and CD8(+) T cells were detected, while IL-10 was highly expressed by all three cell subpopulations. Taken together, these results show an evident imbalance between TNF-alpha and IFN-gamma that is unfavorable to amastigote replication control. Furthermore, L. shawi seems to regulate different cell populations to express deactivating cytokines to avoid its own destruction. This study indicates BALB/c mice as a potentially good experimental model for further studies on American cutaneous leishmaniosis caused by L. shawi. (C) 2010 Elsevier Ireland Ltd. All rights reserved.