A binary engine fuelling HD 87643's complex circumstellar environment Determined using AMBER/VLTI imaging

Context. The star HD 87643, exhibiting the ""B[e] phenomenon"", has one of the most extreme infrared excesses for this object class. It harbours a large amount of both hot and cold dust, and is surrounded by an extended reflection nebula. Aims. One of our major goals was to investigate the presence of a companion in HD87643. In addition, the presence of close dusty material was tested through a combination of multi-wavelength high spatial resolution observations. Methods. We observed HD 87643 with high spatial resolution techniques, using the near-IR AMBER/VLTI interferometer with baselines ranging from 60 m to 130 m and the mid-IR MIDI/VLTI interferometer with baselines ranging from 25 m to 65 m. These observations are complemented by NACO/VLT adaptive-optics-corrected images in the K and L-bands, and ESO-2.2m optical Wide-Field Imager large-scale images in the B, V and R-bands. Results. We report the direct detection of a companion to HD 87643 by means of image synthesis using the AMBER/VLTI instrument. The presence of the companion is confirmed by the MIDI and NACO data, although with a lower confidence. The companion is separated by similar to 34 mas with a roughly north-south orientation. The period must be large (several tens of years) and hence the orbital parameters are not determined yet. Binarity with high eccentricity might be the key to interpreting the extreme characteristics of this system, namely a dusty circumstellar envelope around the primary, a compact dust nebulosity around the binary system and a complex extended nebula suggesting past violent ejections.

Group I introns and associated homing endonuclease genes reveals a clinal structure for Porphyra spiralis var. amplifolia (Bangiales, Rhodophyta) along the Eastern coast of South America

Background: Group I introns are found in the nuclear small subunit ribosomal RNA gene (SSU rDNA) of some species of the genus Porphyra (Bangiales, Rhodophyta). Size polymorphisms in group I introns has been interpreted as the result of the degeneration of homing endonuclease genes (HEG) inserted in peripheral loops of intron paired elements. In this study, intron size polymorphisms were characterized for different Porphyra spiralis var. amplifolia (PSA) populations on the Southern Brazilian coast, and were used to infer genetic relationships and genetic structure of these PSA populations, in addition to cox2-3 and rbcL-S regions. Introns of different sizes were tested qualitatively for in vitro self-splicing. Results: Five intron size polymorphisms within 17 haplotypes were obtained from 80 individuals representing eight localities along the distribution of PSA in the Eastern coast of South America. In order to infer genetic structure and genetic relationships of PSA, these polymorphisms and haplotypes were used as markers for pairwise Fst analyses, Mantel's test and median joining network. The five cox2-3 haplotypes and the unique rbcL-S haplotype were used as markers for summary statistics, neutrality tests Tajima's D and Fu's Fs and for median joining network analyses. An event of demographic expansion from a population with low effective number, followed by a pattern of isolation by distance was obtained for PSA populations with the three analyses. In vitro experiments have shown that introns of different lengths were able to self-splice from pre-RNA transcripts. Conclusion: The findings indicated that degenerated HEGs are reminiscent of the presence of a full-length and functional HEG, once fixed for PSA populations. The cline of HEG degeneration determined the pattern of isolation by distance. Analyses with the other markers indicated an event of demographic expansion from a population with low effective number. The different degrees of degeneration of the HEG do not refrain intron self-splicing. To our knowledge, this was the first study to address intraspecific evolutionary history of a nuclear group I intron; to use nuclear, mitochondrial and chloroplast DNA for population level analyses of Porphyra; and intron size polymorphism as a marker for population genetics.

Characterization of subgraph relationships and distribution in complex networks

A network can be analyzed at different topological scales, ranging from single nodes to motifs, communities, up to the complete structure. We propose a novel approach which extends from single nodes to the whole network level by considering non-overlapping subgraphs (i.e. connected components) and their interrelationships and distribution through the network. Though such subgraphs can be completely general, our methodology focuses on the cases in which the nodes of these subgraphs share some special feature, such as being critical for the proper operation of the network. The methodology of subgraph characterization involves two main aspects: (i) the generation of histograms of subgraph sizes and distances between subgraphs and (ii) a merging algorithm, developed to assess the relevance of nodes outside subgraphs by progressively merging subgraphs until the whole network is covered. The latter procedure complements the histograms by taking into account the nodes lying between subgraphs, as well as the relevance of these nodes to the overall subgraph interconnectivity. Experiments were carried out using four types of network models and five instances of real-world networks, in order to illustrate how subgraph characterization can help complementing complex network-based studies.

Particle competition for complex network community detection

In many real situations, randomness is considered to be uncertainty or even confusion which impedes human beings from making a correct decision. Here we study the combined role of randomness and determinism in particle dynamics for complex network community detection. In the proposed model, particles walk in the network and compete with each other in such a way that each of them tries to possess as many nodes as possible. Moreover, we introduce a rule to adjust the level of randomness of particle walking in the network, and we have found that a portion of randomness can largely improve the community detection rate. Computer simulations show that the model has good community detection performance and at the same time presents low computational complexity. (C) 2008 American Institute of Physics.

Generalized connectivity between any two nodes in a complex network

This article focuses on the identification of the number of paths with different lengths between pairs of nodes in complex networks and how these paths can be used for characterization of topological properties of theoretical and real-world complex networks. This analysis revealed that the number of paths can provide a better discrimination of network models than traditional network measurements. In addition, the analysis of real-world networks suggests that the long-range connectivity tends to be limited in these networks and may be strongly related to network growth and organization.

Chain motifs: The tails and handles of complex networks

A great part of the interest in complex networks has been motivated by the presence of structured, frequently nonuniform, connectivity. Because diverse connectivity patterns tend to result in distinct network dynamics, and also because they provide the means to identify and classify several types of complex network, it becomes important to obtain meaningful measurements of the local network topology. In addition to traditional features such as the node degree, clustering coefficient, and shortest path, motifs have been introduced in the literature in order to provide complementary descriptions of the network connectivity. The current work proposes a different type of motif, namely, chains of nodes, that is, sequences of connected nodes with degree 2. These chains have been subdivided into cords, tails, rings, and handles, depending on the type of their extremities (e.g., open or connected). A theoretical analysis of the density of such motifs in random and scale-free networks is described, and an algorithm for identifying these motifs in general networks is presented. The potential of considering chains for network characterization has been illustrated with respect to five categories of real-world networks including 16 cases. Several interesting findings were obtained, including the fact that several chains were observed in real-world networks, especially the world wide web, books, and the power grid. The possibility of chains resulting from incompletely sampled networks is also investigated.

Electron collisions with the CH(2)O-H(2)O complex

We report cross sections for elastic collisions of low-energy electrons with the CH(2)O-H(2)O complex. We employed the Schwinger multichannel method with pseudopotentials in the static-exchange and in the static-exchange-polarization approximations for energies from 0.1 to 20 eV. We considered four different hydrogen-bonded structures for the complex that were generated by classical Monte Carlo simulations. Our aim is to investigate the effect of the water molecule on the pi* shape resonance of formaldehyde. Previous studies reported a pi* shape resonance for CH(2)O at around 1 eV. The resonance positions of the complexes appear at lower energies in all cases due to the mutual polarization between the two molecules. This indicates that the presence of water may favor dissociation by electron impact and may lead to an important effect on strand breaking in wet DNA by electron impact.

Dynamical estimates of chaotic systems from Poincare recurrences

We show a function that fits well the probability density of return times between two consecutive visits of a chaotic trajectory to finite size regions in phase space. It deviates from the exponential statistics by a small power-law term, a term that represents the deterministic manifestation of the dynamics. We also show how one can quickly and easily estimate the Kolmogorov-Sinai entropy and the short-term correlation function by realizing observations of high probable returns. Our analyses are performed numerically in the Henon map and experimentally in a Chua's circuit. Finally, we discuss how our approach can be used to treat the data coming from experimental complex systems and for technological applications. (C) 2009 American Institute of Physics. [doi: 10.1063/1.3263943]

Experimental observation of a complex periodic window

The existence of a special periodic window in the two-dimensional parameter space of an experimental Chua's circuit is reported. One of the main reasons that makes such a window special is that the observation of one implies that other similar periodic windows must exist for other parameter values. However, such a window has never been experimentally observed, since its size in parameter space decreases exponentially with the period of the periodic attractor. This property imposes clear limitations for its experimental detection.

Jensen inequalities for tunneling probabilities in complex systems

The Jensen theorem is used to derive inequalities for semiclassical tunneling probabilities for systems involving several degrees of freedom. These Jensen inequalities are used to discuss several aspects of sub-barrier heavy-ion fusion reactions. The inequality hinges on general convexity properties of the tunneling coefficient calculated with the classical action in the classically forbidden region.

Deformed Gaussian-orthogonal-ensemble description of small-world networks

The study of spectral behavior of networks has gained enthusiasm over the last few years. In particular, random matrix theory (RMT) concepts have proven to be useful. In discussing transition from regular behavior to fully chaotic behavior it has been found that an extrapolation formula of the Brody type can be used. In the present paper we analyze the regular to chaotic behavior of small world (SW) networks using an extension of the Gaussian orthogonal ensemble. This RMT ensemble, coined the deformed Gaussian orthogonal ensemble (DGOE), supplies a natural foundation of the Brody formula. SW networks follow GOE statistics until a certain range of eigenvalue correlations depending upon the strength of random connections. We show that for these regimes of SW networks where spectral correlations do not follow GOE beyond a certain range, DGOE statistics models the correlations very well. The analysis performed in this paper proves the utility of the DGOE in network physics, as much as it has been useful in other physical systems.

Border detection in complex networks

One important issue implied by the finite nature of real-world networks regards the identification of their more external (border) and internal nodes. The present work proposes a formal and objective definition of these properties, founded on the recently introduced concept of node diversity. It is shown that this feature does not exhibit any relevant correlation with several well-established complex networks measurements. A methodology for the identification of the borders of complex networks is described and illustrated with respect to theoretical (geographical and knitted networks) as well as real-world networks (urban and word association networks), yielding interesting results and insights in both cases.

Iridium(III)-surfactant complex immobilized in mesoporous silica via templated synthesis: a new route to optical materials

In this work we report the preparation of a new blue-emitting material based on the templated synthesis of mesoporous silica (MCM-41) using micellar solutions of the newly synthesized monocationic metallosurfactant complex bis[1-benzyl-4-(2,4-difluorophenyl)-1H-1,2,3-triazole](4,4'-diheptadecyl-2,2'- bipyridine)-iridium(III) chloride in hexadecyl-trimethyl-ammonium bromide (CTAB). Under ambient conditions, significant increases in excited state lifetime and quantum yield values (up to 45%), were obtained for the solid materials in comparison to the corresponding micellar solutions. Solid state (1)H and (19)F NMR spectroscopies were successfully employed for quantifying the luminophore content in terms of Ir-surfactant to CTAB and Ir-surfactant to silica ratios.

Purine nucleoside phosphorylase from Schistosoma mansoni in complex with ribose-1-phosphate

Schistosomes are blood flukes which cause schistosomiasis, a disease affecting approximately 200 million people worldwide. Along with several other important human parasites including trypanosomes and Plasmodium, schistosomes lack the de novo pathway for purine synthesis and depend exclusively on the salvage pathway for their purine requirements, making the latter an attractive target for drug development. Part of the pathway involves the conversion of inosine (or guanosine) into hypoxanthine (or guanine) together with ribose-1-phosphate (R1P) or vice versa. This inter-conversion is undertaken by the enzyme purine nucleoside phosphorylase (PNP) which has been used as the basis for the development of novel anti-malarials, conceptually validating this approach. It has been suggested that, during the reverse reaction, R1P binding to the enzyme would occur only as a consequence of conformational changes induced by hypoxanthine, thus making a binary PNP-R1P complex unlikely. Contradictory to this statement, a crystal structure of just such a binary complex involving the Schistosoma mansoni enzyme has been successfully obtained. The ligand shows an intricate hydrogen-bonding network in the phosphate and ribose binding sites and adds a further chapter to our knowledge which could be of value in the future development of selective inhibitors.

Statistics of opinion domains of the majority-vote model on a square lattice

The existence of juxtaposed regions of distinct cultures in spite of the fact that people's beliefs have a tendency to become more similar to each other's as the individuals interact repeatedly is a puzzling phenomenon in the social sciences. Here we study an extreme version of the frequency-dependent bias model of social influence in which an individual adopts the opinion shared by the majority of the members of its extended neighborhood, which includes the individual itself. This is a variant of the majority-vote model in which the individual retains its opinion in case there is a tie among the neighbors' opinions. We assume that the individuals are fixed in the sites of a square lattice of linear size L and that they interact with their nearest neighbors only. Within a mean-field framework, we derive the equations of motion for the density of individuals adopting a particular opinion in the single-site and pair approximations. Although the single-site approximation predicts a single opinion domain that takes over the entire lattice, the pair approximation yields a qualitatively correct picture with the coexistence of different opinion domains and a strong dependence on the initial conditions. Extensive Monte Carlo simulations indicate the existence of a rich distribution of opinion domains or clusters, the number of which grows with L(2) whereas the size of the largest cluster grows with ln L(2). The analysis of the sizes of the opinion domains shows that they obey a power-law distribution for not too large sizes but that they are exponentially distributed in the limit of very large clusters. In addition, similarly to other well-known social influence model-Axelrod's model-we found that these opinion domains are unstable to the effect of a thermal-like noise.