Knowledge acquisition by networks of interacting agents in the presence of observation errors

In this work we investigate knowledge acquisition as performed by multiple agents interacting as they infer, under the presence of observation errors, respective models of a complex system. We focus the specific case in which, at each time step, each agent takes into account its current observation as well as the average of the models of its neighbors. The agents are connected by a network of interaction of Erdos-Renyi or Barabasi-Albert type. First, we investigate situations in which one of the agents has a different probability of observation error (higher or lower). It is shown that the influence of this special agent over the quality of the models inferred by the rest of the network can be substantial, varying linearly with the respective degree of the agent with different estimation error. In case the degree of this agent is taken as a respective fitness parameter, the effect of the different estimation error is even more pronounced, becoming superlinear. To complement our analysis, we provide the analytical solution of the overall performance of the system. We also investigate the knowledge acquisition dynamic when the agents are grouped into communities. We verify that the inclusion of edges between agents (within a community) having higher probability of observation error promotes the loss of quality in the estimation of the agents in the other communities.

SZNAJD MODEL AND PROPORTIONAL ELECTIONS: THE ROLE OF THE TOPOLOGY OF THE NETWORK

The Sznajd model (SM) has been employed with success in the last years to describe opinion propagation in a community. In particular, it has been claimed that its transient is able to reproduce some scale properties observed in data of proportional elections, in different countries, if the community structure (the network) is scale-free. In this work, we investigate the properties of the transient of a particular version of the SM, introduced by Bernardes and co-authors in 2002. We studied the behavior of the model in networks of different topologies through the time evolution of an order parameter known as interface density, and concluded that regular lattices with high dimensionality also leads to a power-law distribution of the number of candidates with v votes. Also, we show that the particular absorbing state achieved in the stationary state (or else, the winner candidate), is related to a particular feature of the model, that may not be realistic in all situations.

MODELING THE EVOLUTION OF COMPLEX NETWORKS THROUGH THE PATH-STAR TRANSFORMATION AND OPTIMAL MULTIVARIATE METHODS

The topology of real-world complex networks, such as in transportation and communication, is always changing with time. Such changes can arise not only as a natural consequence of their growth, but also due to major modi. cations in their intrinsic organization. For instance, the network of transportation routes between cities and towns ( hence locations) of a given country undergo a major change with the progressive implementation of commercial air transportation. While the locations could be originally interconnected through highways ( paths, giving rise to geographical networks), transportation between those sites progressively shifted or was complemented by air transportation, with scale free characteristics. In the present work we introduce the path-star transformation ( in its uniform and preferential versions) as a means to model such network transformations where paths give rise to stars of connectivity. It is also shown, through optimal multivariate statistical methods (i.e. canonical projections and maximum likelihood classification) that while the US highways network adheres closely to a geographical network model, its path-star transformation yields a network whose topological properties closely resembles those of the respective airport transportation network.

Shape classification using complex network and Multi-scale Fractal Dimension

Shape provides one of the most relevant information about an object. This makes shape one of the most important visual attributes used to characterize objects. This paper introduces a novel approach for shape characterization, which combines modeling shape into a complex network and the analysis of its complexity in a dynamic evolution context. Descriptors computed through this approach show to be efficient in shape characterization, incorporating many characteristics, such as scale and rotation invariant. Experiments using two different shape databases (an artificial shapes database and a leaf shape database) are presented in order to evaluate the method. and its results are compared to traditional shape analysis methods found in literature. (C) 2009 Published by Elsevier B.V.

A complex network-based approach for boundary shape analysis

This paper introduces a novel methodology to shape boundary characterization, where a shape is modeled into a small-world complex network. It uses degree and joint degree measurements in a dynamic evolution network to compose a set of shape descriptors. The proposed shape characterization method has all efficient power of shape characterization, it is robust, noise tolerant, scale invariant and rotation invariant. A leaf plant classification experiment is presented on three image databases in order to evaluate the method and compare it with other descriptors in the literature (Fourier descriptors, Curvature, Zernike moments and multiscale fractal dimension). (C) 2008 Elsevier Ltd. All rights reserved.

Fossil groups in the Millennium Simulation Evolution of the brightest galaxies

Aims. We create a catalogue of simulated fossil groups and study their properties, in particular the merging histories of their first-ranked galaxies. We compare the simulated fossil group properties with those of both simulated non-fossil and observed fossil groups. Methods. Using simulations and a mock galaxy catalogue, we searched for massive (>5 x 10(13) h(-1) M-circle dot) fossil groups in the Millennium Simulation Galaxy Catalogue. In addition, we attempted to identify observed fossil groups in the Sloan Digital Sky Survey Data Release 6 using identical selection criteria. Results. Our predictions on the basis of the simulation data are: (a) fossil groups comprise about 5.5% of the total population of groups/clusters with masses larger than 5 x 10(13) h(-1) M-circle dot. This fraction is consistent with the fraction of fossil groups identified in the SDSS, after all observational biases have been taken into account; (b) about 88% of the dominant central objects in fossil groups are elliptical galaxies that have a median R-band absolute magnitude of similar to-23.5-5 log h, which is typical of the observed fossil groups known in the literature; (c) first-ranked galaxies of systems with M > 5 x 10(13) h(-1) M-circle dot, regardless of whether they are either fossil or non-fossil, are mainly formed by gas-poor mergers; (d) although fossil groups, in general, assembled most of their virial masses at higher redshifts in comparison with non-fossil groups, first-ranked galaxies in fossil groups merged later, i.e. at lower redshifts, compared with their non-fossil-group counterparts. Conclusions. We therefore expect to observe a number of luminous galaxies in the centres of fossil groups that show signs of a recent major merger.

Complete Genome Viral Phylogenies Suggests the Concerted Evolution of Regulatory Cores and Accessory Satellites

We consider the concerted evolution of viral genomes in four families of DNA viruses. Given the high rate of horizontal gene transfer among viruses and their hosts, it is an open question as to how representative particular genes are of the evolutionary history of the complete genome. To address the concerted evolution of viral genes, we compared genomic evolution across four distinct, extant viral families. For all four viral families we constructed DNA-dependent DNA polymerase-based (DdDp) phylogenies and in addition, whole genome sequence, as quantitative descriptions of inter-genome relationships. We found that the history of the polymerase gene was highly predictive of the history of the genome as a whole, which we explain in terms of repeated, co-divergence events of the core DdDp gene accompanied by a number of satellite, accessory genetic loci. We also found that the rate of gene gain in baculovirus and poxviruses proceeds significantly more quickly than the rate of gene loss and that there is convergent acquisition of satellite functions promoting contextual adaptation when distinct viral families infect related hosts. The congruence of the genome and polymerase trees suggests that a large set of viral genes, including polymerase, derive from a phylogenetically conserved core of genes of host origin, secondarily reinforced by gene acquisition from common hosts or co-infecting viruses within the host. A single viral genome can be thought of as a mutualistic network, with the core genes acting as an effective host and the satellite genes as effective symbionts. Larger virus genomes show a greater departure from linkage equilibrium between core and satellites functions.

Haplotype distribution of five nuclear genes based on network genealogies and Bayesian inference indicates that Trypanosoma cruzi hybrid strains are polyphyletic

Chagas disease is still a major public health problem in Latin America. Its causative agent, Trypanosoma cruzi, can be typed into three major groups, T. cruzi I, T. cruzi II and hybrids. These groups each have specific genetic characteristics and epidemiological distributions. Several highly virulent strains are found in the hybrid group; their origin is still a matter of debate. The null hypothesis is that the hybrids are of polyphyletic origin, evolving independently from various hybridization events. The alternative hypothesis is that all extant hybrid strains originated from a single hybridization event. We sequenced both alleles of genes encoding EF-1 alpha, actin and SSU rDNA of 26 T. cruzi strains and DHFR-TS and TR of 12 strains. This information was used for network genealogy analysis and Bayesian phylogenies. We found T. cruzi I and T. cruzi II to be monophyletic and that all hybrids had different combinations of T. cruzi I and T. cruzi II haplotypes plus hybrid-specific haplotypes. Bootstrap values (networks) and posterior probabilities (Bayesian phylogenies) of clades supporting the monophyly of hybrids were far below the 95% confidence interval, indicating that the hybrid group is polyphyletic. We hypothesize that T. cruzi I and T. cruzi II are two different species and that the hybrids are extant representatives of independent events of genome hybridization, which sporadically have sufficient fitness to impact on the epidemiology of Chagas disease.

Performance analysis of an optical network employing waveband and traffic grooming

This paper analyses an optical network architecture composed by an arrangement of nodes equipped with multi-granular optical cross-connects (MG-OXCs) in addition to the usual optical cross-connects (OXCs). Then, selected network nodes can perform both waveband as well as traffic grooming operations and our goal is to assess the improvement on network performance brought by these additional capabilities. Specifically, the influence of the MG-OXC multi-granularity on the blocking probability is evaluated for 16 classes of service over a network based on the NSFNet topology. A mechanism of fairness in bandwidth capacity is also added to the connection admission control to manage the blocking probabilities of all kind of bandwidth requirements. Comprehensive computational simulation are carried out to compare eight distinct node architectures, showing that an adequate combination of waveband and single-wavelength ports of the MG-OXCs and OXCs allow a more efficient operation of a WDM optical network carrying multi-rate traffic.

Synaptic compensation on Hopfield network: implications for memory rehabilitation

The discrete-time neural network proposed by Hopfield can be used for storing and recognizing binary patterns. Here, we investigate how the performance of this network on pattern recognition task is altered when neurons are removed and the weights of the synapses corresponding to these deleted neurons are divided among the remaining synapses. Five distinct ways of distributing such weights are evaluated. We speculate how this numerical work about synaptic compensation may help to guide experimental studies on memory rehabilitation interventions.

Evaluation of GFP Tag as a Screening Reporter in Directed Evolution of a Hyperthermophilic beta-Glucosidase

By applying a directed evolution methodology specific enzymatic characteristics can be enhanced, but to select mutants of interest from a large mutant bank, this approach requires high throughput screening and facile selection. To facilitate such primary screening of enhanced clones, an expression system was tested that uses a green fluorescent protein (GFP) tag from Aequorea victoria linked to the enzyme of interest. As GFP`s fluorescence is readily measured, and as there is a 1:1 molar correlation between the target protein and GFP, the concept proposed was to determine whether GFP could facilitate primary screening of error-prone PCR (EPP) clones. For this purpose a thermostable beta-glucosidase (BglA) from Fervidobacterium sp. was used as a model enzyme. A vector expressing the chimeric protein BglA-GFP-6XHis was constructed and the fusion protein purified and characterized. When compared to the native proteins, the components of the fusion displayed modified characteristics, such as enhanced GFP thermostability and a higher BglA optimum temperature. Clones carrying mutant BglA proteins obtained by EPP, were screened based on the BglA/GFP activity ratio. Purified tagged enzymes from selected clones resulted in modified substrate specificity.

A Practical Teaching Course in Directed Protein Evolution Using the Green Fluorescent Protein as a Model

Protein engineering is a powerful tool, which correlates protein structure with specific functions, both in applied biotechnology and in basic research. Here, we present a practical teaching course for engineering the green fluorescent protein (GFP) from Aequorea victoria by a random mutagenesis strategy using error-prone polymerase chain reaction. Screening of bacterial colonies transformed with random mutant libraries identified GFP variants with increased fluorescence yields. Mapping the three-dimensional structure of these mutants demonstrated how alterations in structural features such as the environment around the fluorophore and properties of the protein surface can influence functional properties such as the intensity of fluorescence and protein solubility.

Experimental tuberculosis: Designing a better model to test vaccines against tuberculosis

Experimental models of infection are good tools for establishing immunological parameters that have an effect on the host-pathogen relationship and also for designing new vaccines and immune therapies. In this work, we evaluated the evolution of experimental tuberculosis in mice infected with increasing bacterial doses or via distinct routes. We showed that mice infected with low bacterial doses by the intratracheal route were able to develop a progressive infection that was proportional to the inoculum size. In the initial phase of disease, mice developed a specific Th1-driven immune response independent of inoculum concentration. However, in the late phase, mice infected with higher concentrations exhibited a mixed Th1/Th2 response, while mice infected with lower concentrations sustained the Th1 pattern. Significant IL-10 concentrations and a more preeminent T regulatory cell recruitment were also detected at 70 days post-infection with high bacterial doses. These results suggest that mice infected with higher concentrations of bacilli developed an immune response similar to the pattern described for human tuberculosis wherein patients with progressive tuberculosis exhibit a down modulation of IFN-gamma production accompanied by increased levels of IL-4. Thus, these data indicate that the experimental model is important in evaluating the protective efficacy of new vaccines and therapies against tuberculosis. (C) 2010 Elsevier Ltd. All rights reserved.

The Genome Sequence of Taurine Cattle: A Window to Ruminant Biology and Evolution

To understand the biology and evolution of ruminants, the cattle genome was sequenced to about sevenfold coverage. The cattle genome contains a minimum of 22,000 genes, with a core set of 14,345 orthologs shared among seven mammalian species of which 1217 are absent or undetected in noneutherian (marsupial or monotreme) genomes. Cattle-specific evolutionary breakpoint regions in chromosomes have a higher density of segmental duplications, enrichment of repetitive elements, and species-specific variations in genes associated with lactation and immune responsiveness. Genes involved in metabolism are generally highly conserved, although five metabolic genes are deleted or extensively diverged from their human orthologs. The cattle genome sequence thus provides a resource for understanding mammalian evolution and accelerating livestock genetic improvement for milk and meat production.

Temporal evolution of epithelial, vascular and interstitial lung injury in an experimental model of idiopathic pulmonary fibrosis induced by butyl-hydroxytoluene

This study was undertaken to test whether the structural remodelling of pulmonary parenchyma can be sequentially altered in a model and method that demonstrate the progression of the disease and result in remodelling within the lungs that is typical of idiopathic pulmonary fibrosis. Three groups of mice were studied: (i) animals that received 3-5-di-tert-butyl-4-hydroxytoluene (BHT) and were killed after 2 weeks (early BHT = 9); (ii) animals that received BHT and were killed after 4 weeks (late BHT = 11); (iii) animals that received corn oil solution (control = 10). The mice were placed in a ventilated Plexiglas chamber with a mixture of pure humidified oxygen and compressed air. Lung histological sections underwent haematoxylin-eosin, immunohistochemistry (epithelial, endothelial and immune cells) and specific staining (collagen/elastic fibres) methods for morphometric analysis. When compared with the control group, early BHT and late BHT groups showed significant decrease of type II pneumocytes, lower vascular density in both and higher endothelial activity. CD4 was increased in late BHT compared with early and control groups, while CD8, macrophage and neutrophil cells were more prominent only in early BHT. The collagenous fibre density were significantly higher only in late BHT, whereas elastic fibre content in late BHT was lower than that in control group. We conclude that the BHT experimental model is pathologically very similar to human usual interstitial pneumonia. This feature is important in the identification of animal models of idiopathic pulmonary fibrosis that can accurately reflect the pathogenesis and progression of the human disease.