Entropy-based randomisation of rating networks

In the last years, due to the great diffusion of e-commerce, online rating platforms quickly became a common tool for purchase recommendations. However, instruments for their analysis did not evolve at the same speed. Indeed, interesting information about users' habits and tastes can be recovered just considering the bipartite network of users and products, in which links have different weights due to the score assigned to items. With respect to other weighted bipartite networks, in these systems we observe a maximum possible weight per link, that limits the variability of the outcomes. In the present article we propose an entropy-based randomisation of (bipartite) rating networks by extending the Configuration Model framework: the randomised network satisfies the constraints of the degree per rating, i.e. the number of given ratings received by the specified product or assigned by the single user. We first show that such a null model is able to reproduce several non-trivial features of the real network better than other null models. Then, using it as a benchmark, we project the information contained in the real system on one of the layers, showing, for instance, the division in communities of music albums due to the taste of customers, or, in movies due the audience.Comment: 12 pages, 30 figure

Solar UV-B Radiation Influences Carotenoid Accumulation of Tomato Fruit through Both Ethylene-Dependent and -independent Mechanisms

The effect of UV-B shielding on ethylene production in ripening tomato fruits and the contribution of ethylene and UV-B radiation on carotenoid accumulation and profile during ripening were assessed to get more insight about the interplay between these two regulatory factors. To this aim, rin and nor tomato mutants, unable to produce ripening ethylene, and cv Ailsa Craig were cultivated under control or UV-B depleted conditions until full fruit ripening. The significantly decreased ethylene evolution following UV-B depletion, evident only in Ailsa Craig, suggested the requirement of functional rin and nor genes for UVB-mediated ethylene production. Carotenoid content and profile were found to be controlled by both ethylene and UV-B radiation. This latter influenced carotenoid metabolism either in an ethylene-dependent or -independent way, as indicated by UVB-induced changes also in nor and rin carotenoid content and confirmed by correlation plots between ethylene evolution and carotenoid accumulation performed separately for control and UV-B shielded fruits. In conclusion, natural UV-B radiation influences carotenoid metabolism in a rather complex way, involving ethylene-dependent and -independent mechanisms, which seem to act in an antagonistic way

Modelling Pulsed Deposition of Nanoparticles into films

We propose a numerical tool to mimic the pulsed deposition of nanoparticles, a technique used to fabricate thin films from the deposition of nanoparticles upon a substrate. We employ such tool under different initial conditions, in particular exploring the effect of depositing an heterogeneous/homogenenous sample of nanoparticles in terms of their morphology (size and shape). We monitor how changing the nature of the building block affects the porosity and roughness of the grown nanofilms. We found a strong dependence on the size of the nanoparticles, following, in the low size regime, a growth of the porosity following a power law.Comment: 10 pages; 12 figure

Collaboration and followership: A stochastic model for activities in social networks

In this work we investigate how future actions are influenced by the previous ones, in the specific contexts of scientific collaborations and friendships on social networks. We describe the activity of the agents, providing a model for the formation of the bipartite network of actions and their features. Therefore we only require to know the chronological order in which the actions are performed, and not the order in which the agents are observed. Moreover, the total number of possible features is not specified a priori but is allowed to increase along time, and new actions can independently show some new-entry features or exhibit some of the old ones. The choice of the old features is driven by a degree-fitness method: indeed, the probability that a new action shows one of the old features does not solely depend on the popularity of that feature (i.e. the number of previous actions showing it), but it is also affected by some individual traits of the agents or the features themselves, synthesized in certain quantities, called fitnesses or weights, that can have different forms and different meaning according to the specific setting considered. We show some theoretical properties of the model and provide statistical tools for the parameters' estimation. The model has been tested on three different datasets and the numerical results are provided and discussed