The three-dimensional Ising model: A paradigm of liquid-vapor coexistence in nuclear multifragmentation

Clusters in the three-dimensional Ising model rigorously obey reducibility and thermal scaling up to the critical temperature. The barriers extracted from Arrhenius plots depend on the cluster size as $B \propto A^{\sigma}$ where $\sigma$ is a critical exponent relating the cluster size to the cluster surface. All the Arrhenius plots collapse into a single Fisher-like scaling function indicating liquid-vapor-like phase coexistence and the univariant equilibrium between percolating clusters and finite clusters. The compelling similarity with nuclear multifragmentation is discussed.Comment: (4 pages, 4 figures

Disrupting resilient criminal networks through data analysis: The case of sicilian mafia

Compared to other types of social networks, criminal networks present particularly hard challenges, due to their strong resilience to disruption, which poses severe hurdles to LawEnforcement Agencies (LEAs). Herein, we borrow methods and tools from Social Network Analysis (SNA) to (i) unveil the structure and organization of Sicilian Mafia gangs, based on two real-world datasets, and (ii) gain insights as to how to efficiently reduce the Largest Connected Component (LCC) of two networks derived from them. Mafia networks have peculiar features in terms of the links distribution and strength, which makes them very different from other social networks, and extremely robust to exogenous perturbations. Analysts also face difficulties in collecting reliable datasets that accurately describe the gangs' internal structure and their relationships with the external world, which is why earlier studies are largely qualitative, elusive and incomplete. An added value of our work is the generation of two realworld datasets, based on raw data extracted from juridical acts, relating to a Mafia organization that operated in Sicily during the first decade of 2000s. We created two different networks, capturing phone calls and physical meetings, respectively. Our analysis simulated different intervention procedures: (i) arresting one criminal at a time (sequential node removal); and (ii) police raids (node block removal). In both the sequential, and the node block removal intervention procedures, the Betweenness centrality was the most effective strategy in prioritizing the nodes to be removed. For instance, when targeting the top 5% nodes with the largest Betweenness centrality, our simulations suggest a reduction of up to 70% in the size of the LCC. We also identified that, due the peculiar type of interactions in criminal networks (namely, the distribution of the interactions' frequency), no significant differences exist between weighted and unweighted network analysis. Our work has significant practical applications for perturbing the operations of criminal and terrorist networks

Semantic disambiguation and contextualisation of social tags

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-28509-7_18This manuscript is an extended version of the paper ‘cTag: Semantic Contextualisation of Social Tags’, presented at the 6th International Workshop on Semantic Adaptive Social Web (SASWeb 2011).We present an algorithmic framework to accurately and efficiently identify the semantic meanings and contexts of social tags within a particular folksonomy. The framework is used for building contextualised tag-based user and item profiles. We also present its implementation in a system called cTag, with which we preliminary analyse semantic meanings and contexts of tags belonging to Delicious and MovieLens folksonomies. The analysis includes a comparison between semantic similarities obtained for pairs of tags in Delicious folksonomy, and their semantic distances in the whole Web, according to co-occurrence based metrics computed with results of a Web search engine.This work was supported by the Spanish Ministry of Science and Innovation (TIN2008-06566-C04-02), and Universidad Autónoma de Madrid (CCG10-UAM/TIC-5877

An advanced sheep (Ovis aries, 2n = 54) cytogenetic map and assignment of 88 new autosomal loci by fluorescence in situ hybridization and R-banding

Presented herein is an updated sheep cytogenetic map that contains 452 loci (291 type I and 161 type II) assigned to specific chromosome bands or regions on standard R-banded ideograms. This map, which significantly extends our knowledge of the physical organization of the ovine genome, includes new assignments for 88 autosomal loci, including 74 type I loci (known genes) and 14 type II loci (SSRs/microsatellite marker/STSs), by FISH-mapping and R-banding. Comparison of the ovine map to the cattle and goat cytogenetic maps showed that common loci were located within homologous chromosomes and chromosome bands, confirming the high level of conservation of autosomes among ruminant species. Eleven loci that were FISH-mapped in sheep (B3GAT2, ASCC3, RARSL, BRD2, POLR1C, PPP2R5D, TNRC5, BAT2, BAT4, CDC5L and OLA-DRA) are unassigned in cattle and goat. Eleven other loci (D3S32, D1S86, BMS2621, SFXN5, D5S3, D5S68, CSKB1, D7S49, D9S15, D9S55 and D29S35) were assigned to specific ovine chromosome (OAR) bands but have only been assigned to chromosomes in cattle and goat

On generalized cluster algorithms for frustrated spin models

Standard Monte Carlo cluster algorithms have proven to be very effective for many different spin models, however they fail for frustrated spin systems. Recently a generalized cluster algorithm was introduced that works extremely well for the fully frustrated Ising model on a square lattice, by placing bonds between sites based on information from plaquettes rather than links of the lattice. Here we study some properties of this algorithm and some variants of it. We introduce a practical methodology for constructing a generalized cluster algorithm for a given spin model, and investigate apply this method to some other frustrated Ising models. We find that such algorithms work well for simple fully frustrated Ising models in two dimensions, but appear to work poorly or not at all for more complex models such as spin glasses.Comment: 34 pages in RevTeX. No figures included. A compressed postscript file for the paper with figures can be obtained via anonymous ftp to minerva.npac.syr.edu in users/paulc/papers/SCCS-527.ps.Z. Syracuse University NPAC technical report SCCS-52

Effect of Yerba Mate Extract as Feed Additive on Ruminal Fermentation and Methane Emissions in Beef Cattle

The inclusion of plant extracts that contain secondary compounds with the potential to modulate rumen fermentation and improve animal performance has gained attention in recent years. The aim of this study was to evaluate the effect of the inclusion of yerba mate extract (Ilex paraguariensis ST. Hilaire) (YME) on the ruminal parameters. Eight castrated cattle were divided into four groups, a control without YME (0%) and three treatment groups with 0.5, 1 and 2% inclusion of YME in the dry matter. The inclusion of YME did not show differences in ruminal methane emissions (CH4), and total apparent digestibility (p = 0.54). Likewise, YME did not modify ruminal pH, but positively affected NH3-N, which decreased linearly as the extract level in the diet increased (p = 0.01). No short chain fatty acids (SCFA) were influenced by YME, except isovaleric acid (p = 0.01), which showed a lower concentration in the inclusion of 2% YME. Our results show that up to 2% YME does not affect digestibility, ruminal fermentation parameters, or the concentration of short-chain fatty acids in the rumen