Discrete-time Markov chain approach to contact-based disease spreading in complex networks

Many epidemic processes in networks spread by stochastic contacts among their connected vertices. There are two limiting cases widely analyzed in the physics literature, the so-called contact process (CP) where the contagion is expanded at a certain rate from an infected vertex to one neighbor at a time, and the reactive process (RP) in which an infected individual effectively contacts all its neighbors to expand the epidemics. However, a more realistic scenario is obtained from the interpolation between these two cases, considering a certain number of stochastic contacts per unit time. Here we propose a discrete-time formulation of the problem of contact-based epidemic spreading. We resolve a family of models, parameterized by the number of stochastic contact trials per unit time, that range from the CP to the RP. In contrast to the common heterogeneous mean-field approach, we focus on the probability of infection of individual nodes. Using this formulation, we can construct the whole phase diagram of the different infection models and determine their critical properties.Comment: 6 pages, 4 figures. Europhys Lett (in press 2010

Emergence of influential spreaders in modified rumor models

The burst in the use of online social networks over the last decade has provided evidence that current rumor spreading models miss some fundamental ingredients in order to reproduce how information is disseminated. In particular, recent literature has revealed that these models fail to reproduce the fact that some nodes in a network have an influential role when it comes to spread a piece of information. In this work, we introduce two mechanisms with the aim of filling the gap between theoretical and experimental results. The first model introduces the assumption that spreaders are not always active whereas the second model considers the possibility that an ignorant is not interested in spreading the rumor. In both cases, results from numerical simulations show a higher adhesion to real data than classical rumor spreading models. Our results shed some light on the mechanisms underlying the spreading of information and ideas in large social systems and pave the way for more realistic diffusion models.Comment: 14 Pages, 6 figures, accepted for publication in Journal of Statistical Physic

Optimal map of the modular structure of complex networks

Modular structure is pervasive in many complex networks of interactions observed in natural, social and technological sciences. Its study sheds light on the relation between the structure and function of complex systems. Generally speaking, modules are islands of highly connected nodes separated by a relatively small number of links. Every module can have contributions of links from any node in the network. The challenge is to disentangle these contributions to understand how the modular structure is built. The main problem is that the analysis of a certain partition into modules involves, in principle, as many data as number of modules times number of nodes. To confront this challenge, here we first define the contribution matrix, the mathematical object containing all the information about the partition of interest, and after, we use a Truncated Singular Value Decomposition to extract the best representation of this matrix in a plane. The analysis of this projection allow us to scrutinize the skeleton of the modular structure, revealing the structure of individual modules and their interrelations.Comment: 21 pages, 10 figure

The topology of a discussion: the #occupy case

We analyse a large sample of the Twitter activity developed around the social movement 'Occupy Wall Street' to study the complex interactions between the human communication activity and the semantic content of a discussion. We use a network approach based on the analysis of the bipartite graph @Users-#Hashtags and of its projections: the 'semantic network', whose nodes are hashtags, and the 'users interest network', whose nodes are users In the first instance, we find out that discussion topics (#hashtags) present a high heterogeneity, with the distinct role of the communication hubs where most the 'opinion traffic' passes through. In the second case, the self-organization process of users activity leads to the emergence of two classes of communicators: the 'professionals' and the 'amateurs'. Moreover the network presents a strong community structure, based on the differentiation of the semantic topics, and a high level of structural robustness when a certain set of topics are censored and/or accounts are removed. Analysing the characteristics the @Users-#Hashtags network we can distinguish three phases of the discussion about the movement. Each phase corresponds to specific moment of the movement: from declaration of intent, organisation and development and the final phase of political reactions. Each phase is characterised by the presence of specific #hashtags in the discussion. Keywords: Twitter, Network analysisComment: 13 pages, 9 figure

Levels, sources and seasonality of coarse particles (PM10-PM2.5) in three European capitals e implications for particulate pollution control

Coarse particles of aerodynamic diameter between 2.5 and 10 mm (PMc) are produced by a range of natural (windblown dust and sea sprays) and anthropogenic processes (non-exhaust vehicle emissions, industrial, agriculture, construction and quarrying activities). Although current ambient air quality regulations focus on PM2.5 and PM10, coarse particles are of interest from a public health point of view as they have been associated with certain mortality and morbidity outcomes. In this paper, an analysis of coarse particle levels in three European capitals (London, Madrid and Athens) is presented and discussed. For all three cities we analysed data from both traffic and urban background monitoring sites. The results showed that the levels of coarse particles present significant seasonal, weekly and daily variability. Their wind driven and non-wind driven resuspension as well as their roadside increment due to traffic were estimated. Both the local meteorological conditions and the air mass history indicating long-range atmospheric transport of particles of natural origin are significant parameters that influence the levels of coarse particles in the three cities especially during episodic events

Locating privileged spreaders on an Online Social Network

Social media have provided plentiful evidence of their capacity for information diffusion. Fads and rumors, but also social unrest and riots travel fast and affect large fractions of the population participating in online social networks (OSNs). This has spurred much research regarding the mechanisms that underlie social contagion, and also who (if any) can unleash system-wide information dissemination. Access to real data, both regarding topology --the network of friendships-- and dynamics --the actual way in which OSNs users interact--, is crucial to decipher how the former facilitates the latter's success, understood as efficiency in information spreading. With the quantitative analysis that stems from complex network theory, we discuss who (and why) has privileged spreading capabilities when it comes to information diffusion. This is done considering the evolution of an episode of political protest which took place in Spain, spanning one month in 2011.Comment: 7 pages, 4 figure

FORMULATION AND EVALUATION OF GLICLAZIDE NANOSPONGES

Objective: The objective of the present study was to develop and characterize an optimal stable nanosponges of Gliclazide (GLZ) by using the emulsion solvent diffusion method and aimed to increase its bioavailability and release the drug in sustained and controlled manner. Methods: The GLZ nanosponge was prepared by emulsion solvent diffusion method using different drug-polymer ratios (1:1 to 1:5) Eudragit S100 is used as a polymer. Differential scanning calorimetry (DSC) and Fourier transform infrared spectroscopy (FTIR) estimated the compatibility of GLZ with polymer. All formulations evaluated for production yield, entrapment efficiency, in vitro drug release, scanning electron microscopy (SEM) and stability studies. Results: The DSC and FTIR Studies revealed that no interaction between drug and polymer. The Production yield of all batches in the range of 73.8±0.30 to 85.6±0.32. Batch F3 showed the highest production yield, the entrapment efficiency of batch F3 70.6±0.77. The average particle size ranges from 303±2.36 to 680±2.50 nm. By the end of 10th hour F3 formulation shown highest drug release was found to be 94.40±1.12%. The release kinetics of the optimized formulation shows zero-order drug release. The stability study indicates no significant change in the in vitro dissolution profile of optimized formulation. Conclusion: The results of various evaluation parameters, revealed that GLZ nanosponges would be possible alternative delivery systems to conventional formulation to improve its bioavailability, the emulsion solvent diffusion method is best method for preparation of nanosponges and release the drug in sustained and controlled manner

Indication of Anisotropy in Electromagnetic Propagation over Cosmological Distances

We report a systematic rotation of the plane of polarization of electromagnetic radiation propagating over cosmological distances. The effect is extracted independently from Faraday rotation, and found to be correlated with the angular positions and distances to the sources. Monte Carlo analysis yields probabilistic P-values of order 10^(-3) for this to occur as a fluctuation. A fit yields a birefringence scale of order 10^(25) meters. Dependence on redshift z rules out a local effect. Barring hidden systematic bias in the data, the correlation indicates a new cosmological effect.Comment: 5 pages, 1 figure, ReVTeX. For more information, see http://www.cc.rochester.edu/college/rtc/Borge/aniso.htm