Anomalous diffusion originated by two Markovian hopping-trap mechanisms

We show through intensive simulations that the paradigmatic features of anomalous diffusion are indeed the features of a (continuous-time) random walk driven by two different Markovian hopping-trap mechanisms. If $p \in (0,1/2)$ and $1-p$ are the probabilities of occurrence of each Markovian mechanism, then the anomalousness parameter $\beta \in (0,1)$ results to be $\beta \simeq 1 - 1/\{1 + \log[(1-p)/p]\}$. Ensemble and single-particle observables of this model have been studied and they match the main characteristics of anomalous diffusion as they are typically measured in living systems. In particular, the celebrated transition of the walker's distribution from exponential to stretched-exponential and finally to Gaussian distribution is displayed by including also the Brownian yet non-Gaussian interval.BERC 2018–2021 BERC 2022–2025 MOSAIC project DIT.AD004.14

Fractional Diffusion and Medium Heterogeneity: The Case of the Continuos Time Random Walk

In this contribution we show that fractional diffusion emerges from a simple Markovian Gaussian random walk when the medium displays a power-law heterogeneity. Within the framework of the continuous time random walk, the heterogeneity of the medium is represented by the selection, at any jump, of a different time-scale for an exponential survival probability. The resulting process is a non-Markovian non-Gaussian random walk. In particular, for a power-law distribution of the time-scales, the resulting random walk corresponds to a time-fractional diffusion process. We relates the power-law of the medium heterogeneity to the fractional order of the diffusion. This relation provides an interpretation and an estimation of the fractional order of derivation in terms of environment heterogeneity. The results are supported by simulations

Gaussian processes in complex media: new vistas on anomalous diffusion

Normal or Brownian diffusion is historically identified by the linear growth in time of the variance and by a Gaussian shape of the displacement distribution. Processes departing from the at least one of the above conditions defines anomalous diffusion, thus a nonlinear growth in time of the variance and/or a non-Gaussian displacement distribution. Motivated by the idea that anomalous diffusion emerges from standard diffusion when it occurs in a complex medium, we discuss a number of anomalous diffusion models for strongly heterogeneous systems. These models are based on Gaussian processes and characterized by a population of scales, population that takes into account the medium heterogeneity. In particular, we discuss diffusion processes whose probability density function solves space- and time-fractional diffusion equations through a proper population of time-scales or a proper population of length-scales. The considered modeling approaches are: the continuous time random walk, the generalized gray Brownian motion, and the time-subordinated process. The results show that the same fractional diffusion follows from different populations when different Gaussian processes are considered. The different populations have the common feature of a large spreading in the scale values, related to power-law decay in the distribution of population itself. This suggests the key role of medium properties, embodied in the population of scales, in the determination of the proper stochastic process underlying the given heterogeneous medium.This research was supported by the Basque Government through the BERC 2014–2017 and BERC 2018–2021 programs, and by the Spanish Ministry of Economy and Competitiveness MINECO through BCAM Severo Ochoa excellence accreditations SEV- 2013-0323 and SEV-2017-0718 and through project MTM2016- 76016-R MI

Langevin equation in complex media and anomalous diffusion

The problem of biological motion is a very intriguing and topical issue. Many efforts are being focused on the development of novel modelling approaches for the description of anomalous diffusion in biological systems, such as the very complex and heterogeneous cell environment. Nevertheless, many questions are still open, such as the joint manifestation of statistical features in agreement with different models that can also be somewhat alternative to each other, e.g. continuous time random walk and fractional Brownian motion. To overcome these limitations, we propose a stochastic diffusion model with additive noise and linear friction force (linear Langevin equation), thus involving the explicit modelling of velocity dynamics. The complexity of the medium is parametrized via a population of intensity parameters (relaxation time and diffusivity of velocity), thus introducing an additional randomness, in addition to white noise, in the particle’s dynamics. We prove that, for proper distributions of these parameters, we can get both Gaussian anomalous diffusion, fractional diffusion and its generalizations.V.S. acknowledges BCAM Internship Program, Bilbao, for the financial support to her internship research period during which she developed her master’s thesis research useful for her master’s degree in Physics at University of Bologna. S.V. acknowledges the University of Bologna for the financial support through the ‘Marco Polo Programme’ for her PhD research period abroad spent at BCAM, Bilbao, useful for her PhD degree in Physics at University of Bologna. P.P. acknowledges financial support from Bizkaia Talent and European Commission through COFUND scheme, 2015 Financial Aid Program for Researchers, project number AYD–000–252 hosted at BCAM, Bilbao

Centre-of-mass like superposition of Ornstein-Uhlenbeck processes: A pathway to non-autonomous stochastic differential equations and to fractional diffusion

We consider an ensemble of Ornstein–Uhlenbeck processes featuring a population of relaxation times and a population of noise amplitudes that characterize the heterogeneity of the ensemble. We show that the centre-of-mass like variable corresponding to this ensemble is statistically equivalent to a process driven by a non-autonomous stochastic differential equation with time-dependent drift and a white noise. In particular, the time scaling and the density function of such variable are driven by the population of timescales and of noise amplitudes, respectively. Moreover, we show that this variable is equivalent in distribution to a randomly-scaled Gaussian process, i.e., a process built by the product of a Gaussian process times a non-negative independent random variable. This last result establishes a connection with the so-called generalized grey Brownian motion and suggests application to model fractional anomalous diffusion in biological systems.”Marco Polo Programme” (University of Bologna

Occurrence and Antimicrobial Susceptibility Profiles of Streptococcus equi subsp. zooepidemicus Strains Isolated from Mares with Fertility Problems

Streptococcus equi subsp. zooepidemicus (S. zooepidemicus), is a β-hemolytic Streptococcus belonging to the Lancefield group C; it is a rare human pathogen, but in horses, it is frequently associated with endometritis. This study aimed to isolate S. zooepidemicus strains, associated with bacterial endometritis in mares, and to define their antimicrobial resistance profile. Twenty-three isolates were recovered from one hundred ninety-six equine uterine swabs (11.7%). Bacterial identification was carried out by Api 20 Strep and confirmed by matrix assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF-MS), while antimicrobial susceptibility testing was performed by disk diffusion method on Muller Hinton agar plates. The antibiotic resistance profiles of the isolates revealed a high percentage of resistance to amikacin (95.6%), ampicillin (73.9%) and tetracycline (69.6%), while ceftiofur and ceftriaxone were highly effective with 82.6% and 78.3% of the isolates inhibited, respectively. An intriguing value of resistance to penicillin (34.8%), which represents the first-choice antibiotic in equine S. zooepidemicus infections, was observed. Furthermore, a high prevalence of multidrug-resistant strains (82.6%) was recorded. Continuous surveillance of this potential zoonotic pathogen and an appropriate antimicrobial stewardship program with the promotion of correct use of antimicrobials, after a proper diagnosis, are needed to allow an effective therapy

Cardiovascular and thrombophilic risk factors for idiopathic sudden sensorineural hearing loss

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