A Catalogue of Galaxies in the HDF-South: Photometry and Structural Parameters

We describe the construction of a catalogue of galaxies in the optical field of the Hubble Deep Field South. The HDF-S observations produced WFPC2 images in U, B, V, and I, the version 1 data have been made public on 23 November 1999. The effective field of view is 4.38 arcmin$^2$, and the 5$\sigma$ limiting magnitudes (in a FWHM aperture) are 28.87, 29.71, 30.19, 29.58 in the U, B, V and I bands, respectively. We created a catalogue for each pass-band (I$_{814}$, V$_{606}$, B$_{450}$, U$_{300}$), using simulations to account for incompleteness and spurious sources contamination. Along with photometry in all bands, we determined on the I$_{814}$-selected catalogue (I$_{814}<26$) structural parameters, such as a metric apparent size, derived from the petrosian radius, an asymmetry index, light concentration indexes and the mean surface brightness within the petrosian radius.Comment: 10 pages, 11 figures. Accepted for publication in A&ASS. The catalog is available in the source and at http://www.merate.mi.astro.it/~saracco/science.htm

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

Molecular junctions for thermal transport between graphene nanoribbons: covalent bonding vs. interdigitated chains

Proper design and manufacturing thermal bridges based on molecular junctions at the contact between graphene platelets or other thermally conductive nanoparticles would provide a fascinating way to produce efficient heat transport networks for the exploitation in heat management applications. In this work, using Non Equilibrium Molecular Dynamics, we calculated thermal conductance of alkyl chains used as molecular junctions between two graphene nanoribbons, both as covalently bound and Van der Waals interdigitated chains. Effect of chain length, grafting density, temperature and chain interdigitation were systematically studied. A clear reduction of conductivity was found with increasing chain length and decreasing grafting density, while lower conductivity was observed for Van der Waals interdigitated chains compared to covalently bound ones. The importance of molecular junctions in enhancing thermal conductance at graphene nanoribbons contacts was further evidenced by calculating the conductance equivalence between a single chain and an overlapping of un-functionalized graphene sheets. As an example, one single pentyl covalently bound chain was found to have a conductance equivalent to the overlapping of an area corresponding to about 152 carbon atoms. These results contribute to the understanding of thermal phenomena occurring within networks of thermally conductive nanoparticles, including graphene nanopapers and graphene-based polymer nanocomposites, which are or high interest for the heat management application in electronics and generally in low-temperature heat exchange and recovery

Layer-by-Layer Assembly of Efficient Flame Retardant Coatings Based On High Aspect Ratio Graphene Oxide and Chitosan Capable of Preventing Ignition of PU Foam

The layer-by-layer (LbL) technique is adopted for the construction of multilayers encompassing chitosan and graphene oxide (GO) platelets capable of improving the flame retardant properties open cell PU foams. The LbL assembly follows a linear growth regime as evaluated by infrared spectroscopy and yields a multilayer structure where GO platelets are embedded within a chitosan continuous matrix. 3 and 6 bi-layers (BL) can efficiently coat the complex 3D structure of the foam and substantially improve its flame retardant properties. 3BL only add 10% to the original mass and can suppress the melt dripping during flammability and reduce both the peak of heat release rate by 54% and the total smoke released by 59% in forced combustion tests. Unprecedented among other LbL assemblies employed for FR purposes, the deposition 6BL is capable of slowing down the release of combustible volatile to the limits of non-ignitability thus preventing ignition in half of the specimens during cone calorimetry tests. This has been ascribed to the formation of a protective coating where the thermally stable char produced by chitosan serves as a continuous matrix embedding GO platelets, which control volatile release while mechanically sustaining the PU foam structure

Development of a Photosynthetic Microbial Electrochemical Cell (PMEC) Reactor Coupled with Dark Fermentation of Organic Wastes: Medium Term Perspectives

In this article the concept, the materials and the exploitation potential of a photosynthetic microbial electrochemical cell for the production of hydrogen driven by solar power are investigated. In a photosynthetic microbial electrochemical cell, which is based on photosynthetic microorganisms confined to an anode and heterotrophic bacteria confined to a cathode, water is split by bacteria hosted in the anode bioactive film. The generated electrons are conveyed through external "bio-appendages" developed by the bacteria to transparent nano-pillars made of indium tin oxide (ITO), Fluorine-doped tin oxide (FTO) or other conducting materials, and then transferred to the cathode. On the other hand, the generated protons diffuse to the cathode via a polymer electrolyte membrane, where they are reduced by the electrons by heterotrophic bacteria growing attached to a similar pillared structure as that envisaged for the anode and supplemented with a specific low cost substrate (e.g., organic waste, anaerobic digestion outlet). The generated oxygen is released to the atmosphere or stored, while the produced pure hydrogen leaves the electrode through the porous layers. In addition, the integration of the photosynthetic microbial electrochemical cell system with dark fermentation as acidogenic step of anaerobic digester, which is able to produce additional H2, and the use of microbial fuel cell, feed with the residues of dark fermentation (mainly volatile fatty acids), to produce the necessary extra-bias for the photosynthetic microbial electrochemical cell is here analyzed to reveal the potential benefits to this novel integrated technology

The role of bot squads in the political propaganda on Twitter

Social Media are nowadays the privileged channel for information spreading and news checking. Unexpectedly for most of the users, automated accounts, also known as social bots, contribute more and more to this process of news spreading. Using Twitter as a benchmark, we consider the traffic exchanged, over one month of observation, on a specific topic, namely the migration flux from Northern Africa to Italy. We measure the significant traffic of tweets only, by implementing an entropy-based null model that discounts the activity of users and the virality of tweets. Results show that social bots play a central role in the exchange of significant content. Indeed, not only the strongest hubs have a number of bots among their followers higher than expected, but furthermore a group of them, that can be assigned to the same political tendency, share a common set of bots as followers. The retwitting activity of such automated accounts amplifies the presence on the platform of the hubs' messages.Comment: Under Submissio

Inferring monopartite projections of bipartite networks: an entropy-based approach

Bipartite networks are currently regarded as providing a major insight into the organization of many real-world systems, unveiling the mechanisms driving the interactions occurring between distinct groups of nodes. One of the most important issues encountered when modeling bipartite networks is devising a way to obtain a (monopartite) projection on the layer of interest, which preserves as much as possible the information encoded into the original bipartite structure. In the present paper we propose an algorithm to obtain statistically-validated projections of bipartite networks, according to which any two nodes sharing a statistically-significant number of neighbors are linked. Since assessing the statistical significance of nodes similarity requires a proper statistical benchmark, here we consider a set of four null models, defined within the exponential random graph framework. Our algorithm outputs a matrix of link-specific p-values, from which a validated projection is straightforwardly obtainable, upon running a multiple hypothesis testing procedure. Finally, we test our method on an economic network (i.e. the countries-products World Trade Web representation) and a social network (i.e. MovieLens, collecting the users' ratings of a list of movies). In both cases non-trivial communities are detected: while projecting the World Trade Web on the countries layer reveals modules of similarly-industrialized nations, projecting it on the products layer allows communities characterized by an increasing level of complexity to be detected; in the second case, projecting MovieLens on the films layer allows clusters of movies whose affinity cannot be fully accounted for by genre similarity to be individuated.Comment: 16 pages, 9 figure

Extracting significant signal of news consumption from social networks: the case of Twitter in Italian political elections

According to the Eurobarometer report about EU media use of May 2018, the number of European citizens who consult on-line social networks for accessing information is considerably increasing. In this work we analyze approximately $10^6$ tweets exchanged during the last Italian elections. By using an entropy-based null model discounting the activity of the users, we first identify potential political alliances within the group of verified accounts: if two verified users are retweeted more than expected by the non-verified ones, they are likely to be related. Then, we derive the users' affiliation to a coalition measuring the polarization of unverified accounts. Finally, we study the bipartite directed representation of the tweets and retweets network, in which tweets and users are collected on the two layers. Users with the highest out-degree identify the most popular ones, whereas highest out-degree posts are the most "viral". We identify significant content spreaders by statistically validating the connections that cannot be explained by users' tweeting activity and posts' virality by using an entropy-based null model as benchmark. The analysis of the directed network of validated retweets reveals signals of the alliances formed after the elections, highlighting commonalities of interests before the event of the national elections