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Parcellation-based connectome assessment by using structural and functional connectivity
No full textConnectome analysis of the human brain structural and functional architecture provides a unique opportunity to understand the organization of brain networks. In this work, we investigate a novel large scale parcellation-based connectome, merging together information coming from resting state fMRI (rs-fMRI) data and diffusion tensor imaging (DTI) measurements
A poly(ether-ester) copolymer for the preparation of nanocarriers with improved degradation and drug delivery kinetics
No full textAbstract This paper reports the synthesis and the physicochemical, functional and biological characterisations of nanocarriers made of a novel di-block biodegradable poly(ether-ester) copolymer. This material presents tunable, fast biodegradation rates, but its products are less acidic than those of other biosorbable polymers like PLGA, thus presenting a better biocompatibility profile and the possibility to carry pH-sensitive payloads. A method for the production of monodisperse and spherical nanoparticles is proposed; drug delivery kinetics and blood protein adsorption were measured to evaluate the functional properties of these nanoparticles as drug carriers. The copolymer was labelled with a fluorescent dye for internalisation tests, and rhodamine B was used as a model cargo to study transport and release inside cultured cells. Biological tests demonstrated good cytocompatibility, significant cell internalisation and the possibility to vehiculate non-cell penetrating moieties into endothelial cells. Taken together, these results support the potential use of this nanoparticulate system for systemic administration of drugs
Quantitative Abstractions for Collective Adaptive Systems
No full textCollective adaptive systems (CAS) consist of a large number of possibly heterogeneous entities evolving according to local interactions that may operate across multiple scales in time and space. The adaptation to changes in the environment, as well as the highly dispersed decision-making process, often leads to emergent behaviour that cannot be understood by simply analysing the objectives, properties, and dynamics of the individual entities in isolation.
As with most complex systems, modelling is a phase of crucial importance for the design of new CAS or the understanding of existing ones. Elsewhere in this volume the typical workflow of formal modelling, analysis, and evaluation of a CAS has been illustrated in detail. In this chapter we treat the problem of efficiently analysing large-scale CAS for quantitative properties. We review algorithms to automatically reduce the dimensionality of a CAS model preserving modeller-defined state variables, with focus on descriptions based on systems of ordinary differential equations. We illustrate the theory in a tutorial fashion, with running examples and a number of more substantial case studies ranging from crowd dynamics, epidemiology and biological systems
Synchronization of Reinforced Stochastic Processes with a Network-based Interaction
No full textRandomly evolving systems composed by elements which interact among each other have always been of great interest in several scientific fields. This work deals with the synchronization phenomenon, that could be roughly defined as the tendency of different components to adopt a common behavior. We continue the study of a model of interacting stochastic processes with reinforcement, that recently has been introduced in Crimaldi et al. (2016, arXiv:1602.06217). Generally speaking, by reinforcement we mean any mechanism for which the probability that a given event occurs has an increasing dependence on the number of times that events of the same type occurred in the past. The particularity of systems of such stochastic processes is that synchronization is induced along time by the reinforcement mechanism itself and does not require a large-scale limit. We focus on the relationship between the topology of the network of the interactions and the long-time synchronization phenomenon. After proving the almost sure synchronization, we provide some CLTs in the sense of stable convergence that establish the convergence rates and the asymptotic distributions for both convergence to the common limit and synchronization. The obtained results lead to the construction of asymptotic confidence intervals for the limit random variable and of statistical tests to make inference on the topology of the network given the observation of the reinforced stochastic processes positioned at the vertices
Revisiting the problem of a crack impinging on an interface: a modeling framework for the interaction between the phase field approach for brittle fracture and the interface cohesive zone model
No full textThe problem of a crack impinging on an interface has been thoroughly investigated in the last three decades due to its important role in the mechanics and physics of solids. In this investigation, this problem is revisited in view of the recent progresses on the phase field approach to brittle fracture. In this concern, a novel formulation combining the phase field approach for modeling brittle fracture in the bulk and a cohesive zone model for pre-existing adhesive interfaces is herein proposed to investigate the competition between crack penetration and deflection at an interface. The model, implemented within the finite element method framework using a monolithic fully implicit solution strategy, is applied to provide a further insight into the understanding of the role of model parameters on the above competition. In particular, in this study, the role of the fracture toughness ratio between the interface and the adjoining bulks and the characteristic fracture-length scales of the dissipative models are analyzed. In the case of a brittle interface, the asymptotic predictions based on linear elastic fracture mechanics criteria for crack penetration, single deflection or double deflection are fully captured by the present method. Moreover, by increasing the size of the process zone along the interface, or by varying the internal length scale of the phase field model, new complex phenomena are emerging, such as simultaneous crack penetration and deflection and the transition from single crack penetration to deflection and penetration with subsequent branching into the bulk
Fluid Analysis of Spatio-Temporal Properties of Agents in a Population Model
No full textWe consider large stochastic population models in which heterogeneous agents are interacting locally and moving in space. These models are very common, e.g. in the context of mobile wireless networks, crowd dynamics, traffic management, but they are typically very hard to analyze, even when space is discretized in a grid. Here we consider individual agents and look at their properties, e.g. quality of service metrics in mobile networks. Leveraging recent results on the combination of stochastic approximation with formal verification, and of fluid approximation of spatio-temporal population processes, we devise a novel mean-field based approach to check such behaviors, which requires the solution of a low-dimensional set of Partial Differential Equation, which is shown to be much faster than simulation. We prove the correctness of the method and validate it on a mobile peer-to-peer network example
Static VS Dynamic Reversibility in CCS
No full textThe notion of reversible computing is attracting interest because of its applications in diverse fields, in particular the study of programming abstractions for fault tolerant systems. Reversible CCS (RCCS), proposed by Danos and Krivine, enacts reversibility by means of memory stacks. Ulidowski and Phillips proposed a general method to reverse a process calculus given in a particular SOS format, by exploiting the idea of making all the operators of a calculus static. CCSK is then derived from CCS with this method. In this paper we show that RCCS is at least as expressive as CCSK