Non-equilibrium phase transition in negotiation dynamics

We introduce a model of negotiation dynamics whose aim is that of mimicking the mechanisms leading to opinion and convention formation in a population of individuals. The negotiation process, as opposed to ``herding-like'' or ``bounded confidence'' driven processes, is based on a microscopic dynamics where memory and feedback play a central role. Our model displays a non-equilibrium phase transition from an absorbing state in which all agents reach a consensus to an active stationary state characterized either by polarization or fragmentation in clusters of agents with different opinions. We show the exystence of at least two different universality classes, one for the case with two possible opinions and one for the case with an unlimited number of opinions. The phase transition is studied analytically and numerically for various topologies of the agents' interaction network. In both cases the universality classes do not seem to depend on the specific interaction topology, the only relevant feature being the total number of different opinions ever present in the system.Comment: 4 pages, 4 figure

Topology-induced coarsening in language games

We investigate how very large populations are able to reach a global consensus, out of local “microscopic” interaction rules, in the framework of a recently introduced class of models of semiotic dynamics, the so-called naming game. We compare in particular the convergence mechanism for interacting agents embedded in a low-dimensional lattice with respect to the mean-field case. We highlight that in low dimensions consensus is reached through a coarsening process that requires less cognitive effort of the agents, with respect to the mean-field case, but takes longer to complete. In one dimension, the dynamics of the boundaries is mapped onto a truncated Markov process from which we analytically computed the diffusion coefficient. More generally we show that the convergence process requires a memory per agent scaling as N and lasts a time N1+2∕d in dimension d⩽4 (the upper critical dimension), while in mean field both memory and time scale as N3∕2, for a population of N agents. We present analytical and numerical evidence supporting this picture

Statistical physics of language dynamics

Language dynamics is a rapidly growing field that focuses on all processes related to the emergence, evolution, change and extinction of languages. Recently, the study of self-organization and evolution of language and meaning has led to the idea that a community of language users can be seen as a complex dynamical system, which collectively solves the problem of developing a shared communication framework through the back-and-forth signaling between individuals. We shall review some of the progress made in the past few years and highlight potential future directions of research in this area. In particular, the emergence of a common lexicon and of a shared set of linguistic categories will be discussed, as examples corresponding to the early stages of a language. The extent to which synthetic modeling is nowadays contributing to the ongoing debate in cognitive science will be pointed out. In addition, the burst of growth of the web is providing new experimental frameworks. It makes available a huge amount of resources, both as novel tools and data to be analyzed, allowing quantitative and large-scale analysis of the processes underlying the emergence of a collective information and language dynamics

Ordering dynamics of the multi-state voter model

The voter model is a paradigm of ordering dynamics. At each time step, a random node is selected and copies the state of one of its neighbors. Traditionally, this state has been considered as a binary variable. Here, we relax this assumption and address the case in which the number of states is a parameter that can assume any value, from 2 to \infty, in the thermodynamic limit. We derive mean-field analytical expressions for the exit probability and the consensus time for the case of an arbitrary number of states. We then perform a numerical study of the model in low dimensional lattices, comparing the case of multiple states with the usual binary voter model. Our work generalizes the well-known results for the voter model, and sheds light on the role of the so far almost neglected parameter accounting for the number of states

Nonequilibrium dynamics of language games on complex networks

The naming game is a model of nonequilibrium dynamics for the self-organized emergence of a linguistic convention or a communication system in a population of agents with pairwise local interactions. We present an extensive study of its dynamics on complex networks, that can be considered as the most natural topological embedding for agents involved in language games and opinion dynamics. Except for some community structured networks on which metastable phases can be observed, agents playing the naming game always manage to reach a global consensus. This convergence is obtained after a time generically scaling with the population’s size N as tconv∼N1.4±0.1, i.e., much faster than for agents embedded on regular lattices. Moreover, the memory capacity required by the system scales only linearly with its size. Particular attention is given to heterogenous networks, in which the dynamical activity pattern of a node depends on its degree. High-degree nodes have a fundamental role, but require larger memory capacity. They govern the dynamics acting as spreaders of (linguistic) conventions. The effects of other properties, such as the average degree and the clustering, are also discussed

Clusters of solutions and replica symmetry breaking in random k-satisfiability

We study the set of solutions of random k-satisfiability formulae through the cavity method. It is known that, for an interval of the clause-to-variables ratio, this decomposes into an exponential number of pure states (clusters). We refine substantially this picture by: (i) determining the precise location of the clustering transition; (ii) uncovering a second `condensation' phase transition in the structure of the solution set for k larger or equal than 4. These results both follow from computing the large deviation rate of the internal entropy of pure states. From a technical point of view our main contributions are a simplified version of the cavity formalism for special values of the Parisi replica symmetry breaking parameter m (in particular for m=1 via a correspondence with the tree reconstruction problem) and new large-k expansions.Comment: 30 pages, 14 figures, typos corrected, discussion of appendix C expanded with a new figur

Monitoring, Delivery and Outcome in Early Onset Fetal Growth Restriction

Early fetal growth restriction (FGR) remains a challenging entity associated with an increased risk of perinatal morbidity and mortality as well as maternal complications. Significant variations in clinical practice have historically characterized the management of early FGR fetuses. Nevertheless, insights into diagnosis and management options have more recently emerged. The aim of this review is to summarize the available evidence on monitoring, delivery and outcome in early-onset FGR

Nonlinear Response Characterization of Post-Tensioned R.C. Bridges through Hilbert–Huang Transform Analysis

A novel methodology for the characterisation of the nonlinear behaviour of post-tensioned r.c. bridges, which exploits the response to heavy traffic travelling during operational conditions, is presented. This type of bridges shows a nonlinear elastic behaviour due to the partial opening of cracks under heavy loads whose entity is related to the intensity of the prestressing force. The properties of this response vary because of material relaxation or damage of the prestressing system. The study exploits the abilities of the Hilbert–Huang transform (HHT) to extract the instantaneous properties of the dynamic response, and a novel procedure to characterise the nonlinear elastic response is presented and investigated through theoretical applications on simplified dynamic systems. A frequency-amplitude correlation chart is proposed as a visual tool to retrieve useful information on the nonlinear response related to the instantaneous variation of the natural frequency with the response amplitude. With the aim of denoising and eliminating spurious contributions introduced by the local nature of the information extracted through the Hilbert spectral analysis, a probabilistic model is proposed for the result interpretation, through which the probability distribution of the instantaneous natural frequencies conditional to different levels of the response amplitude is provided and potential bridge’s response modifications and anomalous behaviours of the prestressing system can be detected. An extensive parametric analysis is performed to assess the influence of the most relevant parameters governing the problem and verify the effectiveness of the proposed strategy

The return of the Blue Crab, Callinectes sapidus Rathbun, 1896, after 70 years from its first appearance in the Gulf of Trieste, northern Adriatic Sea, Italy (Decapoda: Portunidae)

Since August 2015, an increasing number of Blue Crabs, Callinectes sapidus Rathbun, 1896, have been reported in the Marano and Grado Lagoon, Gulf of Trieste, in the northern Adriatic Sea. This species is not a new introduction and in fact the first record of C. sapidus in Italy and the entire Adriatic Sea dates back to 1949 in the Grado Lagoon. Interestingly, no other records of C. sapidus have been reported since the first record. Here, we note the re-appearance of C. sapidus in the Gulf of Trieste