Dynamic range of hypercubic stochastic excitable media

We study the response properties of d-dimensional hypercubic excitable networks to a stochastic stimulus. Each site, modelled either by a three-state stochastic susceptible-infected-recovered-susceptible system or by the probabilistic Greenberg-Hastings cellular automaton, is continuously and independently stimulated by an external Poisson rate h. The response function (mean density of active sites rho versus h) is obtained via simulations (for d=1, 2, 3, 4) and mean field approximations at the single-site and pair levels (for all d). In any dimension, the dynamic range of the response function is maximized precisely at the nonequilibrium phase transition to self-sustained activity, in agreement with a reasoning recently proposed. Moreover, the maximum dynamic range attained at a given dimension d is a decreasing function of d.Comment: 7 pages, 4 figure

Emergence of Hierarchy on a Network of Complementary Agents

Complementarity is one of the main features underlying the interactions in biological and biochemical systems. Inspired by those systems we propose a model for the dynamical evolution of a system composed by agents that interact due to their complementary attributes rather than their similarities. Each agent is represented by a bit-string and has an activity associated to it; the coupling among complementary peers depends on their activity. The connectivity of the system changes in time respecting the constraint of complementarity. We observe the formation of a network of active agents whose stability depends on the rate at which activity diffuses in the system. The model exhibits a non-equilibrium phase transition between the ordered phase, where a stable network is generated, and a disordered phase characterized by the absence of correlation among the agents. The ordered phase exhibits multi-modal distributions of connectivity and activity, indicating a hierarchy of interaction among different populations characterized by different degrees of activity. This model may be used to study the hierarchy observed in social organizations as well as in business and other networks.Comment: 13 pages, 4 figures, submitte

Response of electrically coupled spiking neurons: a cellular automaton approach

Experimental data suggest that some classes of spiking neurons in the first layers of sensory systems are electrically coupled via gap junctions or ephaptic interactions. When the electrical coupling is removed, the response function (firing rate {\it vs.} stimulus intensity) of the uncoupled neurons typically shows a decrease in dynamic range and sensitivity. In order to assess the effect of electrical coupling in the sensory periphery, we calculate the response to a Poisson stimulus of a chain of excitable neurons modeled by $n$-state Greenberg-Hastings cellular automata in two approximation levels. The single-site mean field approximation is shown to give poor results, failing to predict the absorbing state of the lattice, while the results for the pair approximation are in good agreement with computer simulations in the whole stimulus range. In particular, the dynamic range is substantially enlarged due to the propagation of excitable waves, which suggests a functional role for lateral electrical coupling. For probabilistic spike propagation the Hill exponent of the response function is $\alpha=1$, while for deterministic spike propagation we obtain $\alpha=1/2$, which is close to the experimental values of the psychophysical Stevens exponents for odor and light intensities. Our calculations are in qualitative agreement with experimental response functions of ganglion cells in the mammalian retina.Comment: 11 pages, 8 figures, to appear in the Phys. Rev.

Anticipated Synchronization in a Biologically Plausible Model of Neuronal Motifs

Two identical autonomous dynamical systems coupled in a master-slave configuration can exhibit anticipated synchronization (AS) if the slave also receives a delayed negative self-feedback. Recently, AS was shown to occur in systems of simplified neuron models, requiring the coupling of the neuronal membrane potential with its delayed value. However, this coupling has no obvious biological correlate. Here we propose a canonical neuronal microcircuit with standard chemical synapses, where the delayed inhibition is provided by an interneuron. In this biologically plausible scenario, a smooth transition from delayed synchronization (DS) to AS typically occurs when the inhibitory synaptic conductance is increased. The phenomenon is shown to be robust when model parameters are varied within physiological range. Since the DS-AS transition amounts to an inversion in the timing of the pre- and post-synaptic spikes, our results could have a bearing on spike-timing-dependent-plasticity models

Effects of the mean particle size in the deflagration index estimation for cornstarch dust

The National Fire Protection Association (NFPA) defines the dust explosions as a “credible risk”. Hence, to meet the challenge to prevent and protect from the catastrophic effects of these phenomena, it is fundamental to know what are the characteristics and the burning conditions regarding the combustible dusts that could have an effect on the explosion violence. The KSt, also known as deflagration index, is one of the relevant parameters in dust explosions, together with the maximum explosion overpressure generated in the test chamber, the minimumignition energy and so on. In particular, the deflagration index measures the relative explosion severity and it is used in the design of the dust venting protection equipment. However, one of the criticalities of such a parameter is that is strongly affected by the particle mean diameter. Hence, in the following, it will be preliminary presented the validation of a single particle spherical model able to predict the variation of the deflagration index with the increasing mean particle size knowing just one experimental KSt value

Safe optimization of potentially runaway processes using topology based tools and software

In chemical industries, fast and strongly exothermic reactions are often to be carried out to synthesize a number of intermediates and final desired products. Such processes can exhibit a phenomenon known as \u201cthermal runaway\u201d that consists in a reactor temperature loss of control. During the course of the years, lots of methods, aimed to detect the set of operating parameters (e.g., dosing times, initial reactor temperature, coolant temperature, etc..) at which such a dangerous phenomenon can occur, have been developed. Moreover, in the last few years, the attention has been posed on safe process optimization, that is how to compute the set of operating parameters able to ensure high reactor productivity and, contextually, safe conditions. To achieve this goal, with particular reference to industrial semibatch synthesis carried out using both isothermal and isoperibolic temperature control mode, a dedicated optimization software has been implemented. Such a software identifies the optimum set of operating parameters using a topological criterion able to bind the so-called \u201cQFS region\u201d (where reactants accumulation is low and all the heat released is readily removed by the cooling equipment) and, then, iteratively searching for the constrained system optimum. To manage the software, only a few experimental parameters are needed; essentially: heat(s) of reaction, apparent system kinetics (Arrhenius law), threshold temperature(s) above which unwanted side reactions, decompositions or boiling phenomena are triggered, heat transfer coefficients and reactants heat capacities. Such parameters can be obtained using simple calorimetric techniques (DSC, ARC, RC1, etc..). Over the optimization section, the software posses a simulation section where both normal and upset operating conditions (such as pumps failure and external fire) can be tested

Aeraulic behaviour of a biotrickling filter pilot plant: experiments and simulations

Trickling bed biofilters (or biotrickling filters, BTFs) are biological systems for polluted air treatment. Hydrodynamics of BTFs, and reactors in general, is of paramount importance for obtaining good performances. In fact, a non-uniform distribution of the pollutant into the bed brings to dead zones or bypass which reduce the bed working volume and, therefore, cause low removal efficiencies. The paper presents the preliminary results obtained regarding the aeraulic behavior of a BTF pilot plant with seashells as packing material. Experimental results of bed void fraction and pressure drop at several flow rates were used to obtain Ergun equation coefficients for dry bed. A numerical simulation of the reactor flow field carried out with a commercial CFD (Computational Fluid Dynamics) code, validated by the means of velocity measurements made with a Hot Wire Anemometer (HWA) completed the analysis of the reactor hydrodynamics

An infinite-period phase transition versus nucleation in a stochastic model of collective oscillations

A lattice model of three-state stochastic phase-coupled oscillators has been shown by Wood et al (2006 Phys. Rev. Lett. 96 145701) to exhibit a phase transition at a critical value of the coupling parameter, leading to stable global oscillations. We show that, in the complete graph version of the model, upon further increase in the coupling, the average frequency of collective oscillations decreases until an infinite-period (IP) phase transition occurs, at which point collective oscillations cease. Above this second critical point, a macroscopic fraction of the oscillators spend most of the time in one of the three states, yielding a prototypical nonequilibrium example (without an equilibrium counterpart) in which discrete rotational (C_3) symmetry is spontaneously broken, in the absence of any absorbing state. Simulation results and nucleation arguments strongly suggest that the IP phase transition does not occur on finite-dimensional lattices with short-range interactions.Comment: 15 pages, 8 figure

Behavioral Safety: A way to decrease injuries at work (with science)

Work-related injuries are a well known problem all around European Union (EU): every year, at least 170000 workers die and even more suffer severe and permanent injuries. Even if EU placed the goal of reducing this number by 25% by 2012, in many countries the situation remains unchanged despite the enforcement of increasingly stringent laws that, anyways, elude the most important question: why? Moreover, in spite of a lot of American and European studies demonstrated that at least 76% of work-related accidents are due to workers unsafe behaviors, blaming workers is not a effective solution because it eludes again the question: why a worker should act unsafe? An answer to this last question comes from studies about human behavior: a person acts a certain way because he is subject to a number of external stimuli, before and after his act. So, if a person receives a positive consequence as a reward for his behavior, he continues to output the same behavior. Till 80's, Behavior-Based Safety (B-BS) uses this mechanic to provide positive consequences to safe behaviors, instead of negative ones, increasing safety and reducing injuries. But does B-BS work? Even if a lot of literature case studies of successful B-BS implementation are present, all across the world, there is a lack of scientific experiments to unequivocally state that B-BS increases safe behaviors and reduces injuries. This work provides two different case studies, using not only a before-after analysis but also using an appropriate mathematical test (Young\u2019s C Test), to examine workers\u2019 behavior changes during time. The work puts in competition two different B-BS protocols, which share all the fundamentals but differ for start-up time and cost, applied on two different Italian industrial sites: a glass bottle factory and a paint factory. These protocols obtains the same results, demonstrating not only that B-BS works, but also that behavioral safety can be achieved at low cost even for small European industries