Defining and identifying communities in networks

The investigation of community structures in networks is an important issue in many domains and disciplines. This problem is relevant for social tasks (objective analysis of relationships on the web), biological inquiries (functional studies in metabolic, cellular or protein networks) or technological problems (optimization of large infrastructures). Several types of algorithm exist for revealing the community structure in networks, but a general and quantitative definition of community is still lacking, leading to an intrinsic difficulty in the interpretation of the results of the algorithms without any additional non-topological information. In this paper we face this problem by introducing two quantitative definitions of community and by showing how they are implemented in practice in the existing algorithms. In this way the algorithms for the identification of the community structure become fully self-contained. Furthermore, we propose a new local algorithm to detect communities which outperforms the existing algorithms with respect to the computational cost, keeping the same level of reliability. The new algorithm is tested on artificial and real-world graphs. In particular we show the application of the new algorithm to a network of scientific collaborations, which, for its size, can not be attacked with the usual methods. This new class of local algorithms could open the way to applications to large-scale technological and biological applications.Comment: Revtex, final form, 14 pages, 6 figure

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

A Yule-Simon process with memory

The Yule-Simon model has been used as a tool to describe the growth of diverse systems, acquiring a paradigmatic character in many fields of research. Here we study a modified Yule-Simon model that takes into account the full history of the system by means of an hyperbolic memory kernel. We show how the memory kernel changes the properties of preferential attachment and provide an approximate analytical solution for the frequency distribution density as well as for the frequency-rank distribution.Comment: 7 pages, 5 figures; accepted for publication in Europhysics Letter

Clinical, laboratory and immunohistochemical characterization of in situ pulmonary arterial thrombosis in fatal COVID-19

Background: COVID-19 patients carry an increased rate of thrombosis. It is controversial to which extent thrombi in the pulmonary arterial tree really contribute to disease severity with hypoxemia secondary to microvascular/lung parenchymal damage with viral alveolitis considered to play the main role in critical disease. Objectives: The primary objective was to compare post-mortem lung disease from fatal COVID-19 pneumonia in patients with macroscopically evident pulmonary arterial tree thrombosis and patients without, by characterizing the immunohistochemical nature of thrombi, and by comparing clinical and laboratory features of these patients with other COVID-19 patients who died but without evidence of pulmonary arterial thrombosis (controls). Patients and methods: 13 COVID-19 pneumonia cases (mean age ± standard deviation: 74 ± 6.5 years) with macroscopically visible pulmonary arterial thrombosis were compared to 14 controls. Hematoxylin and Eosin stained slides were reviewed choosing those with visible pulmonary thrombi which were further characterized by immunohistochemistry, in particular for the inflammatory infiltrates. Ante mortem serum markers relevant to pulmonary embolism were evaluated in both groups. Results: Twenty arterial thrombi (5 cases with multiple thrombi) were selected for study and were composed by white blood cells (WBC) [median, IQR range: 10 % (5–12.25)], mainly neutrophils [58 % (35.2–64.5)]. Cases with thrombosis showed significantly higher levels of platelet count [median, IQR range: 195000/mmc (157750–274,500) vs 143,500 (113000–175,250), p = 0.011], LDH [854 U/L (731–1315) vs 539 (391.5–660), p = 0.003] at admission, and D-dimer at ICU transfer [25,072 FEU (6951–50,531) vs 1024 (620–5501), p = 0.003]. Conclusions: Immunothrombotically driven arterial thrombi in COVID-19 patients are associated with D-Dimer and LDH elevations, thus linking inflammation, coagulopathy and organ damage in fatal COVID-19

Ising model with memory: coarsening and persistence properties

We consider the coarsening properties of a kinetic Ising model with a memory field. The probability of a spin-flip depends on the persistence time of the spin in a state. The more a spin has been in a given state, the less the spin-flip probability is. We numerically studied the growth and persistence properties of such a system on a two dimensional square lattice. The memory introduces energy barriers which freeze the system at zero temperature. At finite temperature we can observe an apparent arrest of coarsening for low temperature and long memory length. However, since the energy barriers introduced by memory are due to local effects, there exists a timescale on which coarsening takes place as for the Ising model. Moreover the two point correlation functions of the Ising model with and without memory are the same, indicating that they belong to the same universality class.Comment: 10 pages, 7 figures; some figures and some comments adde

Folksonomies and clustering in the collaborative system CiteULike

We analyze CiteULike, an online collaborative tagging system where users bookmark and annotate scientific papers. Such a system can be naturally represented as a tripartite graph whose nodes represent papers, users and tags connected by individual tag assignments. The semantics of tags is studied here, in order to uncover the hidden relationships between tags. We find that the clustering coefficient reflects the semantical patterns among tags, providing useful ideas for the designing of more efficient methods of data classification and spam detection.Comment: 9 pages, 5 figures, iop style; corrected typo

Mitochondrial apurinic/apyrimidinic endonuclease 1 enhances mtDNA repair contributing to cell proliferation and mitochondrial integrity in early stages of hepatocellular carcinoma

Background: Hepatocellular carcinoma (HCC) is the leading cause of primary liver cancers. Surveillance of individuals at specific risk of developing HCC, early diagnostic markers, and new therapeutic approaches are essential to obtain a reduction in disease-related mortality. Apurinic/apyrimidinic endonuclease 1 (APE1) expression levels and its cytoplasmic localization have been reported to correlate with a lower degree of differentiation and shorter survival rate. The aim of this study is to fully investigate, for the first time, the role of the mitochondrial form of APE1 in HCC. Methods: As a study model, we analyzed samples from a cohort of patients diagnosed with HCC who underwent surgical resection. Mitochondrial APE1 content, expression levels of the mitochondrial import protein Mia40, and mtDNA damage of tumor tissue and distal non-tumor liver of each patient were analyzed. In parallel, we generated a stable HeLa clone for inducible silencing of endogenous APE1 and re-expression of the recombinant shRNA resistant mitochondrially targeted APE1 form (MTS-APE1). We evaluated mtDNA damage, cell growth, and mitochondrial respiration. Results: APE1's cytoplasmic positivity in Grades 1 and 2 HCC patients showed a significantly higher expression of mitochondrial APE1, which accounted for lower levels of mtDNA damage observed in the tumor tissue with respect to the distal area. In the contrast, the cytoplasmic positivity in Grade 3 was not associated with APE1's mitochondrial accumulation even when accounting for the higher number of mtDNA lesions measured. Loss of APE1 expression negatively affected mitochondrial respiration, cell viability, and proliferation as well as levels of mtDNA damage. Remarkably, the phenotype was efficiently rescued in MTS-APE1 clone, where APE1 is present only within the mitochondrial matrix. Conclusions: Our study confirms the prominent role of the mitochondrial form of APE1 in the early stages of HCC development and the relevance of the non-nuclear fraction of APE1 in the disease progression. We have also confirmed overexpression of Mia40 and the role of the MIA pathway in the APE1 import process. Based on our data, inhibition of the APE1 transport by blocking the MIA pathway could represent a new therapeutic approach for reducing mitochondrial metabolism by preventing the efficient repair of mtDNA

Outflow Dynamics in Modeling Oligopoly Markets: The Case of the Mobile Telecommunications Market in Poland

In this paper we introduce two models of opinion dynamics in oligopoly markets and apply them to a situation, where a new entrant challenges two incumbents of the same size. The models differ in the way the two forces influencing consumer choice -- (local) social interactions and (global) advertising -- interact. We study the general behavior of the models using the Mean Field Approach and Monte Carlo simulations and calibrate the models to data from the Polish telecommunications market. For one of the models criticality is observed -- below a certain critical level of advertising the market approaches a lock-in situation, where one market leader dominates the market and all other brands disappear. Interestingly, for both models the best fits to real data are obtained for conformity level $p \in (0.3,0.4)$. This agrees very well with the conformity level found by Solomon Asch in his famous social experiment

Memory in aged granular media

Stimulated by recent experimental results, we simulate ``temperature''-cycling experiments in a model for the compaction of granular media. We report on the existence of two types of memory effects: short-term dependence on the history of the sample, and long-term memory for highly compact (aged) systems. A natural interpretation of these results is provided by the analysis of the density heterogeneities.Comment: 5 eps figures, uses euromacr.tex and europhys.sty (included