Stochastic delay differential equations driven by fractional Brownian motion with Hurst parameter H 1/2

We consider the Cauchy problem for a stochastic delay differential equation driven by a fractional Brownian motion with Hurst parameter H>¿. We prove an existence and uniqueness result for this problem, when the coefficients are sufficiently regular. Furthermore, if the diffusion coefficient is bounded away from zero and the coefficients are smooth functions with bounded derivatives of all orders, we prove that the law of the solution admits a smooth density with respect to Lebesgue measure on R.

Carbohydrate and nitrogen stores in Festuca paniculata under mowing explain dominance in subalpine grasslands

Cessation of traditional management threatens semi-natural grassland diversity through the colonisation or increase of competitive species adapted to nutrient-poor conditions. Regular mowing is one practice that controls their abundance. This study evaluated the ecophysiological mechanisms limiting short- and long-term recovery after mowing for Festuca paniculata, a competitive grass that takes over subalpine grasslands in the Alps following cessation of mowing. We quantified temporal variations in carbon (C) and nitrogen (N) content, starch, fructan and total soluble sugars in leaves, stem bases and roots of F. paniculata during one growth cycle in mown and unmown fields and related them to the dynamics of soil mineral N concentration and soil moisture. Short-term results suggest that the regrowth of F. paniculata following mowing might be N-limited, first because of N dilution by C increments in the plant tissue, and second, due to low soil mineral N and soil moisture at this time of year. However, despite short-term effects of mowing on plant growth, C and N content and concentration at the beginning of the following growing season were not affected. Nevertheless, total biomass accumulation at peak standing biomass was largely reduced compared to unmown fields. Moreover, lower C storage capacity at the end of the growing season impacted C allocation to vegetative reproduction during winter, thereby dramatically limiting the horizontal growth of F. paniculata tussocks in the long term. We conclude that mowing reduces the growth of F. paniculata tussocks through both C and N limitation. Such results will help understanding how plant responses to defoliation regulate competitive interactions within plant communities.

Stochastic resonance in a dipole

We show that the dipole, a system usually proposed to model relaxation phenomena, exhibits a maximum in the signal-to-noise ratio at a nonzero noise level, thus indicating the appearance of stochastic resonance. The phenomenon occurs in two different situations, i.e., when the minimum of the potential of the dipole remains fixed in time and when it switches periodically between two equilibrium points. We have also found that the signal-to-noise ratio has a maximum for a certain value of the amplitude of the oscillating field.

Entropic stochastic resonance

We present a novel scheme for the appearance of stochastic resonance when the dynamics of a Brownian particle takes place in a confined medium. The presence of uneven boundaries, giving rise to an entropic contribution to the potential, may upon application of a periodic driving force result in an increase of the spectral amplification at an optimum value of the ambient noise level. The entropic stochastic resonance, characteristic of small-scale systems, may constitute a useful mechanism for the manipulation and control of single molecules and nanodevices.

A hybrid algorithm combining metaheuristic with Monte Carlo simulation for solving the Stochastic Flow Shop problem

In this paper, a hybrid simulation-based algorithm is proposed for the StochasticFlow Shop Problem. The main idea of the methodology is to transform the stochastic problem into a deterministic problem and then apply simulation to the latter. In order to achieve this goal, we rely on Monte Carlo Simulation and an adapted version of a deterministic heuristic. This approach aims to provide flexibility and simplicity due to the fact that it is not constrained by any previous assumption and relies in well-tested heuristics.

A hybrid algorithm combining metaheuristic with Monte Carlo simulation for solving the Stochastic Flow Shop problem

In this paper, a hybrid simulation-based algorithm is proposed for the StochasticFlow Shop Problem. The main idea of the methodology is to transform the stochastic problem into a deterministic problem and then apply simulation to the latter. In order to achieve this goal, we rely on Monte Carlo Simulation and an adapted version of a deterministic heuristic. This approach aims to provide flexibility and simplicity due to the fact that it is not constrained by any previous assumption and relies in well-tested heuristics.

Asymmetric stochastic switching driven by intrinsic molecular noise

Low-copy-number molecules are involved in many functions in cells. The intrinsic fluctuations of these numbers can enable stochastic switching between multiple steady states, inducing phenotypic variability. Herein we present a theoretical and computational study based on Master Equations and Fokker-Planck and Langevin descriptions of stochastic switching for a genetic circuit of autoactivation. We show that in this circuit the intrinsic fluctuations arising from low-copy numbers, which are inherently state-dependent, drive asymmetric switching. These theoretical results are consistent with experimental data that have been reported for the bistable system of the gallactose signaling network in yeast. Our study unravels that intrinsic fluctuations, while not required to describe bistability, are fundamental to understand stochastic switching and the dynamical relative stability of multiple states.

Carbohydrate and nitrogen stores in Festuca paniculata under mowing explain dominance in subalpine grasslands

Cessation of traditional management threatens semi-natural grassland diversity through the colonisation or increase of competitive species adapted to nutrient-poor conditions. Regular mowing is one practice that controls their abundance. This study evaluated the ecophysiological mechanisms limiting short- and long-term recovery after mowing for Festuca paniculata, a competitive grass that takes over subalpine grasslands in the Alps following cessation of mowing. We quantified temporal variations in carbon (C) and nitrogen (N) content, starch, fructan and total soluble sugars in leaves, stem bases and roots of F. paniculata during one growth cycle in mown and unmown fields and related them to the dynamics of soil mineral N concentration and soil moisture. Short-term results suggest that the regrowth of F. paniculata following mowing might be N-limited, first because of N dilution by C increments in the plant tissue, and second, due to low soil mineral N and soil moisture at this time of year. However, despite short-term effects of mowing on plant growth, C and N content and concentration at the beginning of the following growing season were not affected. Nevertheless, total biomass accumulation at peak standing biomass was largely reduced compared to unmown fields. Moreover, lower C storage capacity at the end of the growing season impacted C allocation to vegetative reproduction during winter, thereby dramatically limiting the horizontal growth of F. paniculata tussocks in the long term. We conclude that mowing reduces the growth of F. paniculata tussocks through both C and N limitation. Such results will help understanding how plant responses to defoliation regulate competitive interactions within plant communities.

Anticipating linear stochastic differential equations driven by a Lévy process

In this paper we study the existence of a unique solution for linear stochastic differential equations driven by a Lévy process, where the initial condition and the coefficients are random and not necessarily adapted to the underlying filtration. Towards this end, we extend the method based on Girsanov transformations on Wiener space and developped by Buckdahn [7] to the canonical Lévy space, which is introduced in [25].

Asymmetric stochastic switching driven by intrinsic molecular noise

Low-copy-number molecules are involved in many functions in cells. The intrinsic fluctuations of these numbers can enable stochastic switching between multiple steady states, inducing phenotypic variability. Herein we present a theoretical and computational study based on Master Equations and Fokker-Planck and Langevin descriptions of stochastic switching for a genetic circuit of autoactivation. We show that in this circuit the intrinsic fluctuations arising from low-copy numbers, which are inherently state-dependent, drive asymmetric switching. These theoretical results are consistent with experimental data that have been reported for the bistable system of the gallactose signaling network in yeast. Our study unravels that intrinsic fluctuations, while not required to describe bistability, are fundamental to understand stochastic switching and the dynamical relative stability of multiple states.

Monotonic continuous-time random walks with drift and stochastic reset events

In this paper we consider a stochastic process that may experience random reset events which suddenly bring the system to the starting value and analyze the relevant statistical magnitudes. We focus our attention on monotonic continuous-time random walks with a constant drift: The process increases between the reset events, either by the effect of the random jumps, or by the action of the deterministic drift. As a result of all these combined factors interesting properties emerge, like the existence (for any drift strength) of a stationary transition probability density function, or the faculty of the model to reproduce power-law-like behavior. General formulas for two extreme statistics, the survival probability, and the mean exit time, are also derived. To corroborate in an independent way the results of the paper, Monte Carlo methods were used. These numerical estimations are in full agreement with the analytical predictions.

Panel Data Stochastic Convergence Analysis of the Mexican Regions

The stochastic convergence amongst Mexican Federal entities is analyzed in panel data framework. The joint consideration of cross-section dependence and multiple structural breaks is required to ensure that the statistical inference is based on statistics with good statistical properties. Once these features are accounted for, evidence in favour of stochastic convergence is found. Since stochastic convergence is a necessary, yet insufficient condition for convergence as predicted by economic growth models, the paper also investigates whether-convergence process has taken place. We found that the Mexican states have followed either heterogeneous convergence patterns or divergence process throughout the analyzed period.

Asymptotic analysis of stock price densities and implied volatilities in mixed stochastic models

In this paper, we obtain sharp asymptotic formulas with error estimates for the Mellin con- volution of functions de ned on (0;1), and use these formulas to characterize the asymptotic behavior of marginal distribution densities of stock price processes in mixed stochastic models. Special examples of mixed models are jump-di usion models and stochastic volatility models with jumps. We apply our general results to the Heston model with double exponential jumps, and make a detailed analysis of the asymptotic behavior of the stock price density, the call option pricing function, and the implied volatility in this model. We also obtain similar results for the Heston model with jumps distributed according to the NIG law.

Numerical Dominance of the Argentine Ant vs Native Ants and Consequences on Soil Resource Searching in Mediterranean Cork-Oak Forests (Hymenoptera: Formicidae)

This study is focused on the dominance exerted by the invasive Argentine ant over native ants in a coastal Mediterranean area. Theimpact of this invasive ant on native ant assemblages and its consequences on total ant biomass and on the intensity of habitat explorationwere evaluated. Foraging ants were observed and their trajectories recorded during 5-minute periods in two study zones, one invaded andthe other non-invaded. Ant species detected, ant worker abundance, ant biomass and the intensity of soil surface searching done by antswere compared between the two zones. The Argentine ant invasion provoked a drastic reduction of the ant species richness. Apparentlyonly one native ant species is able to coexist with the Argentine ant, the cryptic Plagiolepis pygmaea. Ant worker abundance was also modified after the invasion: the number of Argentine ant workers detected, which represented 92% of the invaded zone, was two times higher than the number of native ant workers detected in the non-invaded zone. The total ant biomass was inversely affected, becoming four times lower in the invaded zone highly dominated by Linepithema humile. The higher number of Argentine ant workers and their fast tempo of activity implied an alteration of the intensity of soil surface searching: scanning by the Argentine ants in the invaded zone was higher than that done by the native ants in the non-invaded zone, and the estimated time for a complete soil surface scan was 64 minutes in the invaded zone and 108 minutes in the non-invaded zone. Consequently, resources will be discovered faster by ants in the invaded zone than in the non-invaded zone. The increase of the mean temperature and the decrease of the relative humidity from May to August reduced the ant activity in the two study zones but this reduction was greater in the invaded zone