Robustness of the non-Markovian Alzheimer walk under stochastic perturbation

The elephant walk model originally proposed by Schutz and Trimper to investigate non-Markovian processes led to the investigation of a series of other random-walk models. Of these, the best known is the Alzheimer walk model, because it was the first model shown to have amnestically induced persistence-i.e. superdiffusion caused by loss of memory. Here we study the robustness of the Alzheimer walk by adding a memoryless stochastic perturbation. Surprisingly, the solution of the perturbed model can be formally reduced to the solutions of the unperturbed model. Specifically, we give an exact solution of the perturbed model by finding a surjective mapping to the unperturbed model. Copyright (C) EPLA, 2012

PERFORMANCE EVALUATION OF RESOURCE-AWARE BUSINESS PROCESSES USING STOCHASTIC AUTOMATA NETWORKS

In this work, we study the performance evaluation of resource-aware business process models. We define a new framework that allows the generation of analytical models for performance evaluation from business process models annotated with resource management information. This framework is composed of a new notation that allows the specification of resource management constraints and a method to convert a business process specification and its resource constraints into Stochastic Automata Networks (SANs). We show that the analysis of the generated SAN model provides several performance indices, such as average throughput of the system, average waiting time, average queues size, and utilization rate of resources. Using the BP2SAN tool - our implementation of the proposed framework - and a SAN solver (such as the PEPS tool) we show through a simple use-case how a business specialist with no skills in stochastic modeling can easily obtain performance indices that, in turn, can help to identify bottlenecks on the model, to perform workload characterization, to define the provisioning of resources, and to study other performance related aspects of the business process.

Particle Acceleration in Turbulence and Weakly Stochastic Reconnection

In this Letter we analyze the energy distribution evolution of test particles injected in three dimensional (3D) magnetohydrodynamic (MHD) simulations of different magnetic reconnection configurations. When considering a single Sweet-Parker topology, the particles accelerate predominantly through a first-order Fermi process, as predicted in [3] and demonstrated numerically in [8]. When turbulence is included within the current sheet, the acceleration rate is highly enhanced, because reconnection becomes fast and independent of resistivity [4,11] and allows the formation of a thick volume filled with multiple simultaneously reconnecting magnetic fluxes. Charged particles trapped within this volume suffer several head-on scatterings with the contracting magnetic fluctuations, which significantly increase the acceleration rate and results in a first-order Fermi process. For comparison, we also tested acceleration in MHD turbulence, where particles suffer collisions with approaching and receding magnetic irregularities, resulting in a reduced acceleration rate. We argue that the dominant acceleration mechanism approaches a second order Fermi process in this case.

Early and late neurodegeneration and memory disruption after intracerebroventricular streptozotocin

Glucose metabolism and insulin signaling disruptions in the brain have been proposed as a likely etiology of Alzheimer's disease. The aim of the present study was to investigate the time course of cognitive impairments induced by intracerebroventricular injection of streptozotocin (STZ) in rats and correlate them with the ensuing neurodegenerative process. Early and late effects of STZ were evaluated by using the reference and working memory versions of the Morris' water maze task and the evaluation of neurodegenerative markers by immunoblotting and the Fluoro-jade C histochemistry. The results revealed different types of behavioral and neurodegenerative responses, with distinct time courses. We observed an early disruption on the working memory as early as 3 h after STZ injections, which was followed by degenerative processes in the hippocampus at 1 and 15 days after STZ injections. Memory disruption increases over time and culminates with significant changes in amyloid-beta peptide and hyperphosphorylated Tau protein levels in distinct brain structures. These findings add information on the Alzheimer's disease-like STZ animal model and on the mechanisms underlying neurodegenerative processes. (C) 2012 Elsevier Inc. All rights reserved.

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.

Stochastic lattice model describing a vector-borne disease

We employ the approach of stochastic dynamics to describe the dissemination of vector-borne diseases such as dengue, and we focus our attention on the characterization of the threshold of the epidemic. The coexistence space comprises two representative spatial structures for both human and mosquito populations. The human population has its evolution described by a process that is similar to the Susceptible-Infected-Recovered (SIR) dynamics. The population of mosquitoes follows a dynamic of the type of the Susceptible Infected-Susceptible (SIS) model. The coexistence space is a bipartite lattice constituted by two structures representing the human and mosquito populations. We develop a truncation scheme to solve the evolution equations for the densities and the two-site correlations from which we get the threshold of the disease and the reproductive ratio. We present a precise deØnition of the reproductive ratio which reveals the importance of the correlations developed in the early stage of the disease. According to our deØnition, the reproductive rate is directed related to the conditional probability of the occurrence of a susceptible human (mosquito) given the presence in the neighborhood of an infected mosquito (human). The threshold of the epidemic as well as the phase transition between the epidemic and the non-epidemic states are also obtained by performing Monte Carlo simulations. References: [1] David R. de Souza, T^ania Tom∂e, , Suani R. T. Pinho, Florisneide R. Barreto and M∂ario J. de Oliveira, Phys. Rev. E 87, 012709 (2013). [2] D. R. de Souza, T. Tom∂e and R. M. ZiÆ, J. Stat. Mech. P03006 (2011).

A stochastic spatially structured epidemic model with diffusive processes

We developed a stochastic lattice model to describe the vector-borne disease (like yellow fever or dengue). The model is spatially structured and its dynamical rules take into account the diffusion of vectors. We consider a bipartite lattice, forming a sub-lattice of human and another occupied by mosquitoes. At each site of lattice we associate a stochastic variable that describes the occupation and the health state of a single individual (mosquito or human). The process of disease transmission in the human population follows a similar dynamic of the Susceptible-Infected-Recovered model (SIR), while the disease transmission in the mosquito population has an analogous dynamic of the Susceptible-Infected-Susceptible model (SIS) with mosquitos diffusion. The occurrence of an epidemic is directly related to the conditional probability of occurrence of infected mosquitoes (human) in the presence of susceptible human (mosquitoes) on neighborhood. The probability of diffusion of mosquitoes can facilitate the formation of pairs Susceptible-Infected enabling an increase in the size of the epidemic. Using an asynchronous dynamic update, we study the disease transmission in a population initially formed by susceptible individuals due to the introduction of a single mosquito (human) infected. We find that this model exhibits a continuous phase transition related to the existence or non-existence of an epidemic. By means of mean field approximations and Monte Carlo simulations we investigate the epidemic threshold and the phase diagram in terms of the diffusion probability and the infection probability.

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.

Stochastic quantization of the spherical model and supersymmetry.

In this work, we reported some results about the stochastic quantization of the spherical model. We started by reviewing some basic aspects of this method with emphasis in the connection between the Langevin equation and the supersymmetric quantum mechanics, aiming at the application of the corresponding connection to the spherical model. An intuitive idea is that when applied to the spherical model this gives rise to a supersymmetric version that is identified with one studied in Phys. Rev. E 85, 061109, (2012). Before investigating in detail this aspect, we studied the stochastic quantization of the mean spherical model that is simpler to implement than the one with the strict constraint. We also highlight some points concerning more traditional methods discussed in the literature like canonical and path integral quantization. To produce a supersymmetric version, grounded in the Nicolai map, we investigated the stochastic quantization of the strict spherical model. We showed in fact that the result of this process is an off-shell supersymmetric extension of the quantum spherical model (with the precise supersymmetric constraint structure). That analysis establishes a connection between the classical model and its supersymmetric quantum counterpart. The supersymmetric version in this way constructed is a more natural one and gives further support and motivations to investigate similar connections in other models of the literature.

IFN-γ-induced priming maintains long-term strain-transcending immunity against blood-stage Plasmodium chabaudi malaria

The mechanism by which protective immunity to Plasmodium is lost in the absence of continued exposure to this parasite has yet to be fully elucidated. It has been recently shown that IFN-γ produced during human and murine acute malaria primes the immune response to TLR agonists. In this study, we investigated whether IFN-γ-induced priming is important to maintain long-term protective immunity against Plasmodium chabaudi AS malaria. On day 60 postinfection, C57BL/6 mice still had chronic parasitemia and efficiently controlled homologous and heterologous (AJ strain) challenge. The spleens of chronic mice showed augmented numbers of effector/effector memory (TEM) CD4(+) cells, which is associated with increased levels of IFN-γ-induced priming (i.e., high expression of IFN-inducible genes and TLR hyperresponsiveness). After parasite elimination, IFN-γ-induced priming was no longer detected and protective immunity to heterologous challenge was mostly lost with >70% mortality. Spontaneously cured mice had high serum levels of parasite-specific IgG, but effector T/TEM cell numbers, parasite-driven CD4(+) T cell proliferation, and IFN-γ production were similar to noninfected controls. Remarkably, the priming of cured mice with low doses of IFN-γ rescued TLR hyperresponsiveness and the capacity to control heterologous challenge, increasing the TEM cell population and restoring the CD4(+) T cell responses to parasites. Contribution of TLR signaling to the CD4(+) T cell responses in chronic mice was supported by data obtained in mice lacking the MyD88 adaptor. These results indicate that IFN-γ-induced priming is required to maintain protective immunity against P. chabaudi and aid in establishing the molecular basis of strain-transcending immunity in human malaria.

Nonlocal asymmetric exclusion process on a ring and conformal invariance

We present a one-dimensional nonlocal hopping model with exclusion on a ring. The model is related to the Raise and Peel growth model. A nonnegative parameter u controls the ratio of the local backwards and nonlocal forwards hopping rates. The phase diagram, and consequently the values of the current, depend on u and the density of particles. In the special case of half-lling and u = 1 the system is conformal invariant and an exact value of the current for any size L of the system is conjectured and checked for large lattice sizes in Monte Carlo simulations. For u > 1 the current has a non-analytic dependence on the density when the latter approaches the half-lling value.

Active fibre-reinforced composites with embedded shape memory alloys

This dissertation concerns active fibre-reinforced composites with embedded shape memory alloy wires. The structural application of active materials allows to develop adaptive structures which actively respond to changes in the environment, such as morphing structures, self-healing structures and power harvesting devices. In particular, shape memory alloy actuators integrated within a composite actively control the structural shape or stiffness, thus influencing the composite static and dynamic properties. Envisaged applications include, among others, the prevention of thermal buckling of the outer skin of air vehicles, shape changes in panels for improved aerodynamic characteristics and the deployment of large space structures. The study and design of active composites is a complex and multidisciplinary topic, requiring in-depth understanding of both the coupled behaviour of active materials and the interaction between the different composite constituents. Both fibre-reinforced composites and shape memory alloys are extremely active research topics, whose modelling and experimental characterisation still present a number of open problems. Thus, while this dissertation focuses on active composites, some of the research results presented here can be usefully applied to traditional fibre-reinforced composites or other shape memory alloy applications. The dissertation is composed of four chapters. In the first chapter, active fibre-reinforced composites are introduced by giving an overview of the most common choices available for the reinforcement, matrix and production process, together with a brief introduction and classification of active materials. The second chapter presents a number of original contributions regarding the modelling of fibre-reinforced composites. Different two-dimensional laminate theories are derived from a parent three-dimensional theory, introducing a procedure for the a posteriori reconstruction of transverse stresses along the laminate thickness. Accurate through the thickness stresses are crucial for the composite modelling as they are responsible for some common failure mechanisms. A new finite element based on the First-order Shear Deformation Theory and a hybrid stress approach is proposed for the numerical solution of the two-dimensional laminate problem. The element is simple and computationally efficient. The transverse stresses through the laminate thickness are reconstructed starting from a general finite element solution. A two stages procedure is devised, based on Recovery by Compatibility in Patches and three-dimensional equilibrium. Finally, the determination of the elastic parameters of laminated structures via numerical-experimental Bayesian techniques is investigated. Two different estimators are analysed and compared, leading to the definition of an alternative procedure to improve convergence of the estimation process. The third chapter focuses on shape memory alloys, describing their properties and applications. A number of constitutive models proposed in the literature, both one-dimensional and three-dimensional, are critically discussed and compared, underlining their potential and limitations, which are mainly related to the definition of the phase diagram and the choice of internal variables. Some new experimental results on shape memory alloy material characterisation are also presented. These experimental observations display some features of the shape memory alloy behaviour which are generally not included in the current models, thus some ideas are proposed for the development of a new constitutive model. The fourth chapter, finally, focuses on active composite plates with embedded shape memory alloy wires. A number of di®erent approaches can be used to predict the behaviour of such structures, each model presenting different advantages and drawbacks related to complexity and versatility. A simple model able to describe both shape and stiffness control configurations within the same context is proposed and implemented. The model is then validated considering the shape control configuration, which is the most sensitive to model parameters. The experimental work is divided in two parts. In the first part, an active composite is built by gluing prestrained shape memory alloy wires on a carbon fibre laminate strip. This structure is relatively simple to build, however it is useful in order to experimentally demonstrate the feasibility of the concept proposed in the first part of the chapter. In the second part, the making of a fibre-reinforced composite with embedded shape memory alloy wires is investigated, considering different possible choices of materials and manufacturing processes. Although a number of technological issues still need to be faced, the experimental results allow to demonstrate the mechanism of shape control via embedded shape memory alloy wires, while showing a good agreement with the proposed model predictions.

Morphological and functional study of cerebral aging in rat

Aging is a physiological process characterized by a progressive decline of the “cellular homeostatic reserve”, refereed as the capability to respond suitably to exogenous and endogenous stressful stimuli. Due to their high energetic requests and post-mitotic nature, neurons are peculiarly susceptible to this phenomenon. However, the aged brain maintains a certain level of adaptive capacities and if properly stimulated may warrant a considerable functional recovery. Aim of the present research was to verify the plastic potentialities of the aging brain of rats subjected to two kind of exogenous stimuli: A) the replacement of the standard diet with a ketogenic regimen (the change forces the brain to use ketone bodies (KB) in alternative to glucose to satisfy the energetic needs) and B) a behavioural task able to induce the formation of inhibitory avoidance memory. A) Fifteen male Wistar rats of 19 months of age were divided into three groups (average body weight pair-matched), and fed for 8 weeks with different dietary regimens: i) diet containing 10% medium chain triglycerides (MCT); ii) diet containing 20% MCT; iii) standard commercial chow. Five young (5 months of age) and five old (26-27 months of age) animals fed with the standard diet were used as further controls. The following morphological parameters reflecting synaptic plasticity were evaluated in the stratum moleculare of the hippocampal CA1 region (SM CA1), in the outer molecular layer of the hippocampal dentate gyrus (OML DG), and in the granule cell layer of the cerebellar cortex (GCL-CCx): average area (S), numeric density (Nvs), and surface density (Sv) of synapses, and average volume (V), numeric density (Nvm), and volume density (Vv) of synaptic mitochondria. Moreover, succinic dehydrogenase (SDH) activity was cytochemically determined in Purkinje cells (PC) and V, Nvm, Vv, and cytochemical precipitate area/mitochondrial area (R) of SDH-positive mitochondria were evaluated. In SM CA1, MCT-KDs induced the early appearance of the morphological patterns typical of old animals: higher S and V, and lower Nvs and Nvm. On the contrary, in OML DG, Sv and Vv of MCT-KDs-fed rats were higher (as a result of higher Nvs and Nvm) vs. controls; these modifications are known to improve synaptic function and metabolic supply. The opposite effects of MCT-KDs might reflect the different susceptibility of these brain regions to the aging processes: OML DG is less vulnerable than SM CA1, and the reactivation of ketone bodies uptake and catabolism might occur more efficiently in this region, allowing the exploitation of their peculiar metabolic properties. In GCL-CCx, the results described a new scenario in comparison to that found in the hippocampal formation: 10%MCT-KD induced the early appearance of senescent patterns (decreased Nvs and Nvm; increased V), whereas 20%MCT-KD caused no changes. Since GCL-CCx is more vulnerable to age than DG, and less than CA1, these data further support the hypothesis that MCT-KDs effects in the aging brain critically depend on neuronal vulnerability to age, besides MCT percentage. Regarding PC, it was decided to evaluate only the metabolic effect of the dietetic regimen (20%MCT-KD) characterized by less side effects. KD counteracted age-related decrease in numeric density of SDH-positive mitochondria, and enhanced their energetic efficiency (R was significantly higher in MCT-KD-fed rats vs. all the controls). Since it is well known that Purkinje and dentate gyrus cells are less vulnerable to aging than CA1 neurons, these results corroborate our previous hypothesis. In conclusion, the A) experimental line provides the first evidence that morphological and functional parameters reflecting synaptic plasticity and mitochondrial metabolic competence may be modulated by MCT-KDs in the pre-senescent central nervous system, and that the effects may be heterogeneous in different brain regions. MCT-KDs seem to supply high energy metabolic intermediates and to be beneficial (“anti-aging”) for those neurons that maintain the capability to exploit them. This implies risks but also promising potentialities for the therapeutic use of these diets during aging B) Morphological parameters of synapses and synaptic mitochondria in SM CA1 were investigated in old (26-27 month-old) female Wistar rats following a single trial inhibitory avoidance task. In this memory protocol animals learn to avoid a dark compartment in which they received a mild, inescapable foot-shock. Rats were tested 3 and 6 or 9 hours after the training, divided into good and bad responders according to their performance (retention times above or below 100 s, respectively) and immediately sacrificed. Nvs, S, Sv, Nvm, V, and Vv were evaluated. In the good responder group, the numeric density of synapses and mitochondria was significantly higher and the average mitochondrial volume was significantly smaller 9 hours vs. 6 hours after the training. No significant differences were observed among bad responders. Thus, better performances in passive avoidance memory task are correlated with more efficient plastic remodeling of synaptic contacts and mitochondria in hippocampal CA1. These findings indicate that maintenance of synaptic plastic reactivity during aging is a critical requirement for preserving long-term memory consolidation.

ATG based combination therapy - a novel clinically relevant approach to promote regulation and induce long-term allograft survival

Regulatory T cells (Treg) actively regulate alloimmune responses and promote transplantation tolerance. Polyclonal anti-thymocyte globulin (ATG), a widely used induction therapy in clinical organ transplantation, depletes peripheral T cells. However, resistance to tolerance induction is seen with certain T cell depleting strategies and is attributed to alterations in the balance of naïve, memory and regulatory T cells. Here we report a novel reagent, murine ATG (mATG), depletes T cells but preferentially spares CD25+ natural Tregs which limit skewing of T cell repertoire toward T-effector-memory (Tem) phenotype among the recovering T cells. T-cell depletion with mATG combined with CTLA4Ig and Sirolimus synergize to prolong graft survival by tipping the Treg/Tem balance further in favor of Tregs by preserving Tregs, facilitating generation of new Tregs by a conversion mechanism and limiting Tem expansion in response to alloantigen and homeostatic proliferation. These results provide the rationale for translating such novel combination therapies to promote tolerance in primate and human organ transplantation.

Analysis of eruptive and seismic sequences to improve the short-and long-term eruption forecasting

Forecasting the time, location, nature, and scale of volcanic eruptions is one of the most urgent aspects of modern applied volcanology. The reliability of probabilistic forecasting procedures is strongly related to the reliability of the input information provided, implying objective criteria for interpreting the historical and monitoring data. For this reason both, detailed analysis of past data and more basic research into the processes of volcanism, are fundamental tasks of a continuous information-gain process; in this way the precursor events of eruptions can be better interpreted in terms of their physical meanings with correlated uncertainties. This should lead to better predictions of the nature of eruptive events. In this work we have studied different problems associated with the long- and short-term eruption forecasting assessment. First, we discuss different approaches for the analysis of the eruptive history of a volcano, most of them generally applied for long-term eruption forecasting purposes; furthermore, we present a model based on the characteristics of a Brownian passage-time process to describe recurrent eruptive activity, and apply it for long-term, time-dependent, eruption forecasting (Chapter 1). Conversely, in an effort to define further monitoring parameters as input data for short-term eruption forecasting in probabilistic models (as for example, the Bayesian Event Tree for eruption forecasting -BET_EF-), we analyze some characteristics of typical seismic activity recorded in active volcanoes; in particular, we use some methodologies that may be applied to analyze long-period (LP) events (Chapter 2) and volcano-tectonic (VT) seismic swarms (Chapter 3); our analysis in general are oriented toward the tracking of phenomena that can provide information about magmatic processes. Finally, we discuss some possible ways to integrate the results presented in Chapters 1 (for long-term EF), 2 and 3 (for short-term EF) in the BET_EF model (Chapter 4).