Cosmic topology: a brief overview

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A SUGGESTION ON THE PAIR OF QSO TRIPLETS 1130+106 (B,A,C), (X,Y,Z)

The alignment of a pair of QSO triplets discovered by Arp and Hazard are tentatively explained by a combination of (I) the idea of quasar ejection by galaxies; (II) a construction by Narlikar suggesting a common origin for the six images; and (III) a nontrivial topology of cosmic space.

Highly swollen liquid crystals as new reactors for the synthesis of nanomaterials

Synthesis and self-assembly of nanomaterials can be controlled by the properties of soft matter. on one hand, dedicated nanoreactors such as reverse microemulsions or miniemulsions can be designed. on the other hand, direct shape control can be provided by the topology of liquid crystals that confine the reacting medium within a specific geometry. In the first case, the preparation of micro- or miniemulsions generally requires energetic mechanical stirring. The second approach uses thermodynamically stable systems, but it remains usually limited to binary (water + surfactant) systems. We report the preparation of different families of materials in highly ordered quaternary mediums that exhibit a liquid crystal structure with a high cell parameter. They were prepared with the proper ratios of salted water, nonpolar solvent, surfactant. and cosurfactants that form spontaneously swollen hexagonal phases. These swollen liquid crystals can be prepared from all classes of surfactants (cationic, anionic, and nonionic). They contain a regular network of parallel cylinders, whose diameters can be swollen with a nonpolar solvent, that are regularly spaced in a continuous aqueous salt solution. We demonstrate in the present report that both aqueous and organic phases can be used as nanoreactors for the preparation of materials. This property is illustrated by various examples such as the synthesis of platinum nanorods prepared in the aqueous phase or zirconia needles or the photo- or gamma-ray-induced polymerization of polydiacetylene in the organic phase. In all cases, materials can be easily extracted and their final shapes are directed by the structure-directing effect imposed by the liquid crystal.

Density functional theory study on the structural and electronic properties of low index rutile surfaces for TiO2/SnO2/TiO2 and SnO2/TiO2/SnO2 composite systems

The present study is concerned with the structural and electronic properties of the TiO2/SnO2/TiO2 and SnO2/TiO2/SnO2 composite systems. Periodic quantum mechanical method with density functional theory at the B3LYP level has been carried out. Relaxed surface energies, structural characteristics and electronic properties of the (I 10), (0 10), (10 1) and (00) low-index rutile surfaces for TiO2/SnO2/TiO2 and SnO2/TiO2/SnO2 models are studied. For, comparison purposes, the bare rutile TiO2 and SnO2 structures are also analyzed and compared with previous theoretical and experimental data. The calculated surface energy for both rutile TiO2 and SnO2 surfaces follows the sequence (110) < (010) < (101) < (001) and the energy increases as (010) < (101) < (110) < (001) and (010) approximate to (110) < (101) < (001) for SnO2/TiO2/SnO2 and TiO2/SnO2/TiO2 composite systems, respectively. SnO2/TiO2/SnO2 presents larger values of surface energy than the individual SnO2 and TiO2 metal oxides and the TiO2/SnO2/TiO2 system renders surface energy values of the same order that the TiO2 and lower than the SnO2. An analysis of the electronic structure of the TiO2/SnO2/TiO2 and SnO2/TiO2/SnO2 systems shows that the main characteristics of the upper part of the valence bands for all the studied surfaces are dominated by the external layers, i.e., by the TiO2 and the SnO2, respectively, and the topology of the lower part of the conduction bands looks like the core layers. There is an energy stabilization of both valence band top and conduction band bottom for (110) and (010) surfaces of the SnO2/TiO2/SnO2 composite system in relation to their core TiO2, whereas an opposite trend is found for the same surfaces of the TiO2/SnO2/TiO2 composite system in relation to the bare SnO2. The present theoretical results may explain the growth of TiO2@SnO2 bimorph composite nanotape.

On the specific filtration mechanism of a mesoporous silica membrane, prepared with non-connecting parallel pores

We report the singular filtration properties of an ultrafiltration membrane made with mesoporous silica that exhibits cylindrical pores aligned mostly normal to the support. This membrane supported on tubular commercial macroporous alumina supports was prepared by the interfacial growth mechanism between stable silica-surfactant hybrid micelles made of the association of silica oligomers with polyethyleneoxide-based (PEO) surfactants and sodium fluoride, a well-known silica condensation catalyst [Boissière et al., An ultrafiltration membrane made with mesoporous MSU-X silica, Chem. Mater. 15 (2003) 460-463]. It appears that the combined effect of the silica nature of the membrane, whose surface charge can be easily adjusted by changing the pH and the non-connected cylindrical shape of the pores provides a new behavior in the retention properties, as proved by the filtration of polyoxyethylene polymers (PEO) with different molecular weights. Depending on the filtration conditions, a rejection rate of 80% and a steep cut-off at 2000 Da can be obtained or, on the reverse, polymers three times bigger than the pore diameter can diffuse through the membrane. This new filtration mechanism, which opens up new modes of separation modes, is explained in the light of both topology of the porous network and pH-dependent interactions between PEO polymers and silica porous media. © 2004 Elsevier B.V. All rights reserved.

Multiplicity of solutions for a biharmonic equation with subcritical or critical growth

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Analysis of the radial operation of distribution systems considering operation with minimal losses

Electric power distribution systems, and particularly those with overhead circuits, operate radially but as the topology of the systems is meshed, therefore a set of circuits needs to be disconnected. In this context the problem of optimal reconfiguration of a distribution system is formulated with the goal of finding a radial topology for the operation of the system. This paper utilizes experimental tests and preliminary theoretical analysis to show that radial topology is one of the worst topologies to use if the goal is to minimize power losses in a power distribution system. For this reason, it is important to initiate a theoretical and practical discussion on whether it is worthwhile to operate a distribution system in a radial form. This topic is becoming increasingly important within the modern operation of electrical systems, which requires them to operate as efficiently as possible, utilizing all available resources to improve and optimize the operation of electric power systems. Experimental tests demonstrate the importance of this issue. (C) 2014 Elsevier Ltd. All rights reserved.

Differentiation and species status of the Neotropical yellow-eared bats Vampyressa pusilla and V. thyone (Phyllostomidae) with a molecular phylogeny and review of the genus

A systematic re-evaluation of Vampyressa pusilla warrants the elevation of V. p. thyone from subspecies to species rank based on its distinction from the allopatric V. p. pusilla. Morphological, mensural, chromosomal, and mitochondrial differences define each of these two taxa as divergent lineages. Vampyressa pusilla is endemic to the Atlantic Forest of southeastern South America and V. thyone is found allopatrically in northwestern South America, Central America, and southern Mexico. A molecular phylogenetic analysis of the mtDNA ND3-4 gene region using restriction endonuclease cut sites resulted in a monophyletic, although weakly supported Vampyressa ingroup with Chiroderma, and a clade of Mesophylla and Ectophylla as successive basal outgroup lineages. The phylogeny within Vampyressa, with the exception of V. melissa which is most similar to V. thyone based on karyotypes and morphology, had a topology of ((pusilla + thyone) + ((brocki + nymphaea) + bidens))).

Predicting epidemic outbreak from individual features of the spreaders

Knowing which individuals can be more efficient in spreading a pathogen throughout a determinate environment is a fundamental question in disease control. Indeed, over recent years the spread of epidemic diseases and its relationship with the topology of the involved system have been a recurrent topic in complex network theory, taking into account both network models and real-world data. In this paper we explore possible correlations between the heterogeneous spread of an epidemic disease governed by the susceptible-infected-recovered (SIR) model, and several attributes of the originating vertices, considering Erdos-Renyi (ER), Barabasi-Albert (BA) and random geometric graphs (RGG), as well as a real case study, the US air transportation network, which comprises the 500 busiest airports in the US along with inter-connections. Initially, the heterogeneity of the spreading is achieved by considering the RGG networks, in which we analytically derive an expression for the distribution of the spreading rates among the established contacts, by assuming that such rates decay exponentially with the distance that separates the individuals. Such a distribution is also considered for the ER and BA models, where we observe topological effects on the correlations. In the case of the airport network, the spreading rates are empirically defined, assumed to be directly proportional to the seat availability. Among both the theoretical and real networks considered, we observe a high correlation between the total epidemic prevalence and the degree, as well as the strength and the accessibility of the epidemic sources. For attributes such as the betweenness centrality and the k-shell index, however, the correlation depends on the topology considered.

Quantum spherical model with competing interactions

We analyse the phase diagram of a quantum mean spherical model in terms of the temperature T, a quantum parameter g, and the ratio p = -J(2)/J(1) where J(1) > 0 refers to ferromagnetic interactions between first-neighbour sites along the d directions of a hypercubic lattice, and J(2) < 0 is associated with competing anti ferromagnetic interactions between second neighbours along m <= d directions. We regain a number of known results for the classical version of this model, including the topology of the critical line in the g = 0 space, with a Lifshitz point at p = 1/4, for d > 2, and closed-form expressions for the decay of the pair correlations in one dimension. In the T = 0 phase diagram, there is a critical border, g(c) = g(c) (p) for d >= 2, with a singularity at the Lifshitz point if d < (m + 4)/2. We also establish upper and lower critical dimensions, and analyse the quantum critical behavior in the neighborhood of p = 1/4. 2012 (C) Elsevier B.V. All rights reserved.

EFFECT OF HEAD GROUP AND CURVATURE ON BINDING OF THE ANTIMICROBIAL PEPTIDE TRITRPTICIN TO LIPID MEMBRANES

In this work we examine the interaction between the 13-residue cationic antimicrobial peptide (AMP) tritrpticin (VRRFPWWWPFLRR, TRP3) and model membranes of variable lipid composition. The effect on peptide conformational properties was investigated by means of CD (circular dichroism) and fluorescence spectroscopies. Based on the hypothesis that the antibiotic acts through a mechanism involving toroidal pore formation, and taking into account that models of toroidal pores imply the formation of positive curvature, we used large unilamellar vesicles (LUV) to mimic the initial step of peptide-lipid interaction, when the peptide binds to the bilayer membrane, and micelles to mimic the topology of the pore itself, since these aggregates display positive curvature. In order to more faithfully assess the role of curvature, micelles were prepared with lysophospholipids containing (qualitatively and quantitatively) head groups identical to those of bilayer phospholipids. CD and fluorescence spectra showed that, while TRP3 binds to bilayers only when they carry negatively charged phospholipids. binding to micelles occurs irrespective of surface charge, indicating that electrostatic interactions play a less predominant role in the latter case. Moreover, the conformations acquired by the peptide were independent of lipid composition in both bilayers and micelles. However, the conformations were different in bilayers and in micelles, suggesting that curvature has an influence on the secondary structure acquired by the peptide. Fluorescence data pointed to an interfacial location of TRP3 in both types of aggregates. Nevertheless, experiments with a water soluble fluorescence quencher suggested that the tryptophan residues are more accessible to the quencher in micelles than in bilayers. Thus, we propose that bilayers and micelles can be used as models for the two steps of toroidal pore formation. (C) 2011 Elsevier Ireland Ltd. All rights reserved.

Prominent Effect of Soil Network Heterogeneity on Microbial Invasion

Using a network representation for real soil samples and mathematical models for microbial spread, we show that the structural heterogeneity of the soil habitat may have a very significant influence on the size of microbial invasions of the soil pore space. In particular, neglecting the soil structural heterogeneity may lead to a substantial underestimation of microbial invasion. Such effects are explained in terms of a crucial interplay between heterogeneity in microbial spread and heterogeneity in the topology of soil networks. The main influence of network topology on invasion is linked to the existence of long channels in soil networks that may act as bridges for transmission of microorganisms between distant parts of soil.

A system for classification of time-series data from industrial non-destructive device

This work proposes a system for classification of industrial steel pieces by means of magnetic nondestructive device. The proposed classification system presents two main stages, online system stage and off-line system stage. In online stage, the system classifies inputs and saves misclassification information in order to perform posterior analyses. In the off-line optimization stage, the topology of a Probabilistic Neural Network is optimized by a Feature Selection algorithm combined with the Probabilistic Neural Network to increase the classification rate. The proposed Feature Selection algorithm searches for the signal spectrogram by combining three basic elements: a Sequential Forward Selection algorithm, a Feature Cluster Grow algorithm with classification rate gradient analysis and a Sequential Backward Selection. Also, a trash-data recycling algorithm is proposed to obtain the optimal feedback samples selected from the misclassified ones.

Probing the statistical properties of unknown texts: application to the Voynich manuscript

While the use of statistical physics methods to analyze large corpora has been useful to unveil many patterns in texts, no comprehensive investigation has been performed on the interdependence between syntactic and semantic factors. In this study we propose a framework for determining whether a text (e.g., written in an unknown alphabet) is compatible with a natural language and to which language it could belong. The approach is based on three types of statistical measurements, i.e. obtained from first-order statistics of word properties in a text, from the topology of complex networks representing texts, and from intermittency concepts where text is treated as a time series. Comparative experiments were performed with the New Testament in 15 different languages and with distinct books in English and Portuguese in order to quantify the dependency of the different measurements on the language and on the story being told in the book. The metrics found to be informative in distinguishing real texts from their shuffled versions include assortativity, degree and selectivity of words. As an illustration, we analyze an undeciphered medieval manuscript known as the Voynich Manuscript. We show that it is mostly compatible with natural languages and incompatible with random texts. We also obtain candidates for keywords of the Voynich Manuscript which could be helpful in the effort of deciphering it. Because we were able to identify statistical measurements that are more dependent on the syntax than on the semantics, the framework may also serve for text analysis in language-dependent applications.

Machine-learning methods for structure prediction of β-barrel membrane proteins

Different types of proteins exist with diverse functions that are essential for living organisms. An important class of proteins is represented by transmembrane proteins which are specifically designed to be inserted into biological membranes and devised to perform very important functions in the cell such as cell communication and active transport across the membrane. Transmembrane β-barrels (TMBBs) are a sub-class of membrane proteins largely under-represented in structure databases because of the extreme difficulty in experimental structure determination. For this reason, computational tools that are able to predict the structure of TMBBs are needed. In this thesis, two computational problems related to TMBBs were addressed: the detection of TMBBs in large datasets of proteins and the prediction of the topology of TMBB proteins. Firstly, a method for TMBB detection was presented based on a novel neural network framework for variable-length sequence classification. The proposed approach was validated on a non-redundant dataset of proteins. Furthermore, we carried-out genome-wide detection using the entire Escherichia coli proteome. In both experiments, the method significantly outperformed other existing state-of-the-art approaches, reaching very high PPV (92%) and MCC (0.82). Secondly, a method was also introduced for TMBB topology prediction. The proposed approach is based on grammatical modelling and probabilistic discriminative models for sequence data labeling. The method was evaluated using a newly generated dataset of 38 TMBB proteins obtained from high-resolution data in the PDB. Results have shown that the model is able to correctly predict topologies of 25 out of 38 protein chains in the dataset. When tested on previously released datasets, the performances of the proposed approach were measured as comparable or superior to the current state-of-the-art of TMBB topology prediction.