Percolation of randomly distributed growing clusters: Finite Size Scaling and Critical Exponents

We study the percolation properties of the growing clusters model. In this model, a number of seeds placed on random locations on a lattice are allowed to grow with a constant velocity to form clusters. When two or more clusters eventually touch each other they immediately stop their growth. The model exhibits a discontinuous transition for very low values of the seed concentration $p$ and a second, non-trivial continuous phase transition for intermediate $p$ values. Here we study in detail this continuous transition that separates a phase of finite clusters from a phase characterized by the presence of a giant component. Using finite size scaling and large scale Monte Carlo simulations we determine the value of the percolation threshold where the giant component first appears, and the critical exponents that characterize the transition. We find that the transition belongs to a different universality class from the standard percolation transition.Comment: 5 two-column pages, 6 figure

Some discussions of D. Fearnhead and D. Prangle's Read Paper "Constructing summary statistics for approximate Bayesian computation: semi-automatic approximate Bayesian computation"

This report is a collection of comments on the Read Paper of Fearnhead and Prangle (2011), to appear in the Journal of the Royal Statistical Society Series B, along with a reply from the authors

Laser-matter interactions, phase changes and diffusion phenomena during laser annealing of plasmonic AlN:Ag templates and their applications in optical encoding

Nanocomposite thin films incorporating silver nanoparticles are emerging as photosensitive templates for optical encoding applications. However, a deep understanding of the fundamental physicochemical mechanisms occurring during laser-matter interactions is still lacking. In this work, the photosensitivity of AlN:Ag plasmonic nanocomposites is thoroughly examined and a series of UV laser annealing parameters, such as wavelength, fluence and the number of pulses are investigated. We report and study effects such as the selective crystallization of the AlN matrix, the enlargement of the Ag nanoparticle inclusions by diffusion of laser-heated Ag and the outdiffusion of Ag to the film's surface. Detailed optical calculations contribute to the identification and understanding of the aforementioned physical mechanisms and of their dependency on the laser processing parameters. We are then able to predetermine the plasmonic response of processed AlN:Ag nanocomposites and demonstrate its potential by means of optically encoding an overt or covert cryptographic pattern

Structural properties of spatially embedded networks

We study the effects of spatial constraints on the structural properties of networks embedded in one or two dimensional space. When nodes are embedded in space, they have a well defined Euclidean distance $r$ between any pair. We assume that nodes at distance $r$ have a link with probability $p(r) \sim r^{- \delta}$. We study the mean topological distance $l$ and the clustering coefficient $C$ of these networks and find that they both exhibit phase transitions for some critical value of the control parameter $\delta$ depending on the dimensionality $d$ of the embedding space. We have identified three regimes. When $\delta <d$, the networks are not affected at all by the spatial constraints. They are ``small-worlds'' $l\sim \log N$ with zero clustering at the thermodynamic limit. In the intermediate regime $d<\delta<2d$, the networks are affected by the space and the distance increases and becomes a power of $\log N$, and have non-zero clustering. When $\delta>2d$ the networks are ``large'' worlds $l \sim N^{1/d}$ with high clustering. Our results indicate that spatial constrains have a significant impact on the network properties, a fact that should be taken into account when modeling complex networks.Comment: 5 pages, To appear in Europhysics Letter

Positive words carry less information than negative words

We show that the frequency of word use is not only determined by the word length \cite{Zipf1935} and the average information content \cite{Piantadosi2011}, but also by its emotional content. We have analyzed three established lexica of affective word usage in English, German, and Spanish, to verify that these lexica have a neutral, unbiased, emotional content. Taking into account the frequency of word usage, we find that words with a positive emotional content are more frequently used. This lends support to Pollyanna hypothesis \cite{Boucher1969} that there should be a positive bias in human expression. We also find that negative words contain more information than positive words, as the informativeness of a word increases uniformly with its valence decrease. Our findings support earlier conjectures about (i) the relation between word frequency and information content, and (ii) the impact of positive emotions on communication and social links.Comment: 16 pages, 3 figures, 3 table

A Random Matrix Approach to Language Acquisition

Since language is tied to cognition, we expect the linguistic structures to reflect patterns we encounter in nature and analyzed by physics. Within this realm we investigate the process of protolanguage acquisition, using analytical and tractable methods developed within physics. A protolanguage is a mapping between sounds and objects (or concepts) of the perceived world. This mapping is represented by a matrix and the linguistic interaction among individuals is described by a random matrix model. There are two essential parameters in our approach. The strength of the linguistic interaction $\beta$, which following Chomsky's tradition, we consider as a genetically determined ability, and the number $N$ of employed sounds (the lexicon size). Our model of linguistic interaction is analytically studied using methods of statistical physics and simulated by Monte Carlo techniques. The analysis reveals an intricate relationship between the innate propensity for language acquisition $\beta$ and the lexicon size $N$, $N \sim \exp(\beta)$. Thus a small increase of the genetically determined $\beta$ may lead to an incredible lexical explosion. Our approximate scheme offers an explanation for the biological affinity of different species and their simultaneous linguistic disparity.Comment: 16 pages, 4 figures. Submitted to JSTA

Fatal outcome of a hypersensitivity reaction to paclitaxel: a critical review of premedication regimens

Hypersensitivity reactions (HSRs) to paclitaxel are frequently encountered in patients receiving this antitumour drug. Administration of histamine H1- and H2-receptor antagonists and corticosteroids has been shown to reduce significantly the risk of developing an HSR in patients receiving taxanes. In this case report, we describe the fatal outcome of an HSR in a patient receiving paclitaxel despite short-course premedication. The level of evidence supporting the short-course i.v. premedication schedule is challenged, as it is not compatible with the pharmacokinetic properties of dexamethasone