Disclosing the generic behavior of topological solutions: An orbit-based approach

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

ALGORITHM FOR PROBABILISTIC ANALYSIS of DISTRIBUTION SYSTEMS WITH DISTRIBUTED GENERATION

In this paper an efficient algorithm for probabilistic analysis of unbalanced three-phase weakly-meshed distribution systems is presented. This algorithm uses the technique of Two-Point Estimate Method for calculating the probabilistic behavior of the system random variables. Additionally, the deterministic analysis of the state variables is performed by means of a Compensation-Based Radial Load Flow (CBRLF). Such load flow efficiently exploits the topological characteristics of the network. To deal with distributed generation, a strategy to incorporate a simplified model of a generator in the CBRLF is proposed. Thus, depending on the type of control and generator operation conditions, the node with distributed generation can be modeled either as a PV or PQ node. To validate the efficiency of the proposed algorithm, the IEEE 37 bus test system is used. The probabilistic results are compared with those obtained using the Monte Carlo method.

Noether and topological currents equivalence and soliton/particle correspondence in affine sl(2)((1)) Toda theory coupled to matter

A submodel of the so-called conformal affine Toda model coupled to the matter field (CATM) is defined such that its real Lagrangian has a positive-definite kinetic term for the Toda field and a usual kinetic term for the (Dirac) spinor field. After spontaneously broken the conformal symmetry by means of BRST analysis, we end up with an effective theory, the off-critical affine Toda model coupled to the matter (ATM). It is shown that the ATM model inherits the remarkable properties of the general CATM model such as the soliton solutions, the particle/soliton correspondence and the equivalence between the Noether and topological currents. The classical solitonic spectrum of the ATM model is also discussed. (C) 2001 Elsevier B.V. B.V. All rights reserved.

Direct instantons, topological charge screening, and QCD glueball sum rules

Nonperturbative Wilson coefficients of the operator product expansion (OPE) for the spin-0 glueball correlators are derived and analyzed. A systematic treatment of the direct instanton contributions is given, based on a realistic instanton size distribution and renormalization at the operator scale. In the pseudoscalar channel, topological charge screening is identified as an additional source of (semi-) hard nonperturbative physics. The screening contributions are shown to be vital for consistency with the anomalous axial Ward identity, and previously encountered pathologies (positivity violations and the disappearance of the 0(-+) glueball signal) are traced to their neglect. on the basis of the extended OPE, a comprehensive quantitative analysis of eight Borel-moment sum rules in both spin-0 glueball channels is then performed. The nonperturbative OPE coefficients turn out to be indispensable for consistent sum rules and for their reconciliation with the underlying low-energy theorems. The topological short-distance physics strongly affects the sum rule results and reveals a rather diverse pattern of glueball properties. New predictions for the spin-0 glueball masses and decay constants and an estimate of the scalar glueball width are given, and several implications for glueball structure and experimental glueball searches are discussed.

Probabilistic analysis of the distributed power generation in weakly meshed distribution systems

This paper presents an approach for probabilistic analysis of unbalanced three-phase weakly meshed distribution systems considering uncertainty in load demand. In order to achieve high computational efficiency this approach uses both an efficient method for probabilistic analysis and a radial power flow. The probabilistic approach used is the well-known Two-Point Estimate Method. Meanwhile, the compensation-based radial power flow is used in order to extract benefits from the topological characteristics of the distribution systems. The generation model proposed allows modeling either PQ or PV bus on the connection point between the network and the distributed generator. In addition allows control of the generator operating conditions, such as the field current and the power delivery at terminals. Results on test with IEEE 37 bus system is given to illustrate the operation and effectiveness of the proposed approach. A Monte Carlo Simulations method is used to validate the results. © 2011 IEEE.

Complex networks analysis of language complexity

Methods from statistical physics, such as those involving complex networks, have been increasingly used in the quantitative analysis of linguistic phenomena. In this paper, we represented pieces of text with different levels of simplification in co-occurrence networks and found that topological regularity correlated negatively with textual complexity. Furthermore, in less complex texts the distance between concepts, represented as nodes, tended to decrease. The complex networks metrics were treated with multivariate pattern recognition techniques, which allowed us to distinguish between original texts and their simplified versions. For each original text, two simplified versions were generated manually with increasing number of simplification operations. As expected, distinction was easier for the strongly simplified versions, where the most relevant metrics were node strength, shortest paths and diversity. Also, the discrimination of complex texts was improved with higher hierarchical network metrics, thus pointing to the usefulness of considering wider contexts around the concepts. Though the accuracy rate in the distinction was not as high as in methods using deep linguistic knowledge, the complex network approach is still useful for a rapid screening of texts whenever assessing complexity is essential to guarantee accessibility to readers with limited reading ability. Copyright (c) EPLA, 2012

Reproducing kernel Hilbert spaces associated with kernels on topological spaces

We analyze reproducing kernel Hilbert spaces of positive definite kernels on a topological space X being either first countable or locally compact. The results include versions of Mercer's theorem and theorems on the embedding of these spaces into spaces of continuous and square integrable functions.

Reconstruction and analysis of the NF-kB pathway interactome: a systems biology approach

Background. One of the phenomena observed in human aging is the progressive increase of a systemic inflammatory state, a condition referred to as “inflammaging”, negatively correlated with longevity. A prominent mediator of inflammation is the transcription factor NF-kB, that acts as key transcriptional regulator of many genes coding for pro-inflammatory cytokines. Many different signaling pathways activated by very diverse stimuli converge on NF-kB, resulting in a regulatory network characterized by high complexity. NF-kB signaling has been proposed to be responsible of inflammaging. Scope of this analysis is to provide a wider, systemic picture of such intricate signaling and interaction network: the NF-kB pathway interactome. Methods. The study has been carried out following a workflow for gathering information from literature as well as from several pathway and protein interactions databases, and for integrating and analyzing existing data and the relative reconstructed representations by using the available computational tools. Strong manual intervention has been necessarily used to integrate data from multiple sources into mathematically analyzable networks. The reconstruction of the NF-kB interactome pursued with this approach provides a starting point for a general view of the architecture and for a deeper analysis and understanding of this complex regulatory system. Results. A “core” and a “wider” NF-kB pathway interactome, consisting of 140 and 3146 proteins respectively, were reconstructed and analyzed through a mathematical, graph-theoretical approach. Among other interesting features, the topological characterization of the interactomes shows that a relevant number of interacting proteins are in turn products of genes that are controlled and regulated in their expression exactly by NF-kB transcription factors. These “feedback loops”, not always well-known, deserve deeper investigation since they may have a role in tuning the response and the output consequent to NF-kB pathway initiation, in regulating the intensity of the response, or its homeostasis and balance in order to make the functioning of such critical system more robust and reliable. This integrated view allows to shed light on the functional structure and on some of the crucial nodes of thet NF-kB transcription factors interactome. Conclusion. Framing structure and dynamics of the NF-kB interactome into a wider, systemic picture would be a significant step toward a better understanding of how NF-kB globally regulates diverse gene programs and phenotypes. This study represents a step towards a more complete and integrated view of the NF-kB signaling system.

Topological changes in 2D simplicial meshes for the simulation of fractures

A method for the introduction of strong discontinuities into a mesh will be developed. This method, applicable to a number of eXtended Finite Element Methods (XFEM) with intra-element strong discontinuities will be demonstrated with one specific method: the Generalized Cohesive Element (GCE) method. The algorithm utilizes a subgraph mesh representation which may insert the GCE either adaptively during the course of the analysis or a priori. Using this subgraphing algorithm, the insertion time is O(n) to the number of insertions. Numerical examples are presented demonstrating the advantages of the subgraph insertion method.

Quantitative analysis of imprint shape and its relation to mechanical properties measured by microindentation in bone

Microindentation in bone is a micromechanical testing technique routinely used to extract material properties related to bone quality. As the analysis of microindentation data is based on assumptions about the contact between sample and surface, the aim of this study was to quantify the topological variability of indentations in bone and examine its relationship with mechanical properties. Indentations were performed in dry human and ovine bone in axial and transverse directions and their topology was measured by atomic force microscopy. Statistical shape modeling of the residual imprint allowed to define a mean shape and to describe the variability in terms of 21 principal components related to imprint depth, surface curvature and roughness. The indentation profile of bone was found to be highly consistent and free of any pile up while differing mostly by depth between species and direction. A few of the topological parameters, in particular depth, showed significant but rather weak and inconsistent correlations to variations in mechanical properties. The mechanical response of bone as well as the residual imprint shape was highly consistent within each category. We could thus verify that bone is rather homogeneous in its micromechanical properties and that indentation results are not strongly influenced by small deviations from an ideally flat surface.

Experimental and Theoretical Electron Density Analysis of Copper Pyrazine Nitrate Quasi-Low-Dimensional Quantum Magnets

The accurate electron density distribution and magnetic properties of two metal-organic polymeric magnets, the quasi-one-dimensional (1D) Cu(pyz)(NO3)2 and the quasi-two-dimensional (2D) [Cu(pyz)2(NO3)]NO3·H2O, have been investigated by high-resolution single-crystal X-ray diffraction and density functional theory calculations on the whole periodic systems and on selected fragments. Topological analyses, based on quantum theory of atoms in molecules, enabled the characterization of possible magnetic exchange pathways and the establishment of relationships between the electron (charge and spin) densities and the exchange-coupling constants. In both compounds, the experimentally observed antiferromagnetic coupling can be quantitatively explained by the Cu-Cu superexchange pathway mediated by the pyrazine bridging ligands, via a σ-type interaction. From topological analyses of experimental charge-density data, we show for the first time that the pyrazine tilt angle does not play a role in determining the strength of the magnetic interaction. Taken in combination with molecular orbital analysis and spin density calculations, we find a synergistic relationship between spin delocalization and spin polarization mechanisms and that both determine the bulk magnetic behavior of these Cu(II)-pyz coordination polymers.

Analysis of VirB4, a membrane-associated ATPase subunit essential for T -complex transport in Agrobacterium tumefaciens

Agrobacterium tumefaciens is a plant pathogen with the unique ability to export oncogenic DNA-protein complexes (T-complexes) to susceptible plant cells and cause crown gall tumors. Delivery of the T-complexes across the bacterial membranes requires eleven VirB proteins and VirD4, which are postulated to form a transmembrane transporter. This thesis examines the subcellular localization and oligomeric structure of the 87-kDa VirB4 protein, which is one of three essential ATPases proposed to energize T-complex transport and/or assembly. Results of subcellular localization studies showed that VirB4 is tightly associated with the cytoplasmic membrane, suggesting that it is a membrane-spanning protein. The membrane topology of VirB4 was determined by using a nested deletion strategy to generate random fusions between virB4 and the periplasmically-active alkaline phosphatase, $\sp\prime phoA$. Analysis of PhoA and complementary $\beta$-galactosidase reporter fusions identified two putative periplasmically-exposed regions in VirB4. A periplasmic exposure of one of these regions was further confirmed by protease susceptibility assays using A. tumefaciens spheroplasts. To gain insight into the structure of the transporter, the topological configurations of other VirB proteins were also examined. Results from hydropathy analyses, subcellular localization, protease susceptibility, and PhoA reporter fusion studies support a model that all of the VirB proteins localize at one or both of the bacterial membranes. Immunoprecipitation and Co$\sp{2+}$ affinity chromatography studies demonstrated that native VirB4 (87-kDa) and a functional N-terminally tagged HIS-VirB4 derivative (89-kDa) interact and that the interaction is independent of other VirB proteins. A $\lambda$ cI repressor fusion assay supplied further evidence for VirB4 dimer formation. A VirB4 dimerization domain was localized to the N-terminal third of the protein, as judged by: (i) transdominance of an allele that codes for this region of VirB4; (ii) co-retention of a His-tagged N-terminal truncation derivative and native VirB4 on Co$\sp{2+}$ affinity columns; and (iii) dimer formation of the N-terminal third of VirB4 fused to the cI repressor protein. Taken together, these findings are consistent with a model that VirB4 is topologically configured as an integral cytoplasmic membrane protein with two periplasmic domains and that VirB4 assembles as homodimers via an N-terminal dimerization domain. Dimer formation is postulated to be essential for stabilization of VirB4 monomers during T-complex transporter assembly. ^

Self-organizing cultured neural networks: Image analysis techniques for longitudinal tracking and modeling of the underlying network structure

Esta tesis estudia la evolución estructural de conjuntos de neuronas como la capacidad de auto-organización desde conjuntos de neuronas separadas hasta que forman una red (clusterizada) compleja. Esta tesis contribuye con el diseño e implementación de un algoritmo no supervisado de segmentación basado en grafos con un coste computacional muy bajo. Este algoritmo proporciona de forma automática la estructura completa de la red a partir de imágenes de cultivos neuronales tomadas con microscopios de fase con una resolución muy alta. La estructura de la red es representada mediante un objeto matemático (matriz) cuyos nodos representan a las neuronas o grupos de neuronas y los enlaces son las conexiones reconstruidas entre ellos. Este algoritmo extrae también otras medidas morfológicas importantes que caracterizan a las neuronas y a las neuritas. A diferencia de otros algoritmos hasta el momento, que necesitan de fluorescencia y técnicas inmunocitoquímicas, el algoritmo propuesto permite el estudio longitudinal de forma no invasiva posibilitando el estudio durante la formación de un cultivo. Además, esta tesis, estudia de forma sistemática un grupo de variables topológicas que garantizan la posibilidad de cuantificar e investigar la progresión de las características principales durante el proceso de auto-organización del cultivo. Nuestros resultados muestran la existencia de un estado concreto correspondiente a redes con configuracin small-world y la emergencia de propiedades a micro- y meso-escala de la estructura de la red. Finalmente, identificamos los procesos físicos principales que guían las transformaciones morfológicas de los cultivos y proponemos un modelo de crecimiento de red que reproduce el comportamiento cuantitativamente de las observaciones experimentales. ABSTRACT The thesis analyzes the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. In particular, it contributes with the design and implementation of a graph-based unsupervised segmentation algorithm, having an associated very low computational cost. The processing automatically retrieves the whole network structure from large scale phase-contrast images taken at high resolution throughout the entire life of a cultured neuronal network. The network structure is represented by a mathematical object (a matrix) in which nodes are identified neurons or neurons clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocyto- chemistry techniques, our measures are non invasive and entitle us to carry out a fully longitudinal analysis during the maturation of a single culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main networks characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graphs micro- and meso-scale properties emerge. Finally, we identify the main physical processes taking place during the cultures morphological transformations, and embed them into a simplified growth model that quantitatively reproduces the overall set of experimental observations.

Self-organizing cultured neural networks: Image analysis techniques for longitudinal tracking and modeling of the underlying network structure (versión actualizada)

Esta tesis estudia la evolución estructural de conjuntos de neuronas como la capacidad de auto-organización desde conjuntos de neuronas separadas hasta que forman una red (clusterizada) compleja. Esta tesis contribuye con el diseño e implementación de un algoritmo no supervisado de segmentación basado en grafos con un coste computacional muy bajo. Este algoritmo proporciona de forma automática la estructura completa de la red a partir de imágenes de cultivos neuronales tomadas con microscopios de fase con una resolución muy alta. La estructura de la red es representada mediante un objeto matemático (matriz) cuyos nodos representan a las neuronas o grupos de neuronas y los enlaces son las conexiones reconstruidas entre ellos. Este algoritmo extrae también otras medidas morfológicas importantes que caracterizan a las neuronas y a las neuritas. A diferencia de otros algoritmos hasta el momento, que necesitan de fluorescencia y técnicas inmunocitoquímicas, el algoritmo propuesto permite el estudio longitudinal de forma no invasiva posibilitando el estudio durante la formación de un cultivo. Además, esta tesis, estudia de forma sistemática un grupo de variables topológicas que garantizan la posibilidad de cuantificar e investigar la progresión de las características principales durante el proceso de auto-organización del cultivo. Nuestros resultados muestran la existencia de un estado concreto correspondiente a redes con configuracin small-world y la emergencia de propiedades a micro- y meso-escala de la estructura de la red. Finalmente, identificamos los procesos físicos principales que guían las transformaciones morfológicas de los cultivos y proponemos un modelo de crecimiento de red que reproduce el comportamiento cuantitativamente de las observaciones experimentales. ABSTRACT The thesis analyzes the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. In particular, it contributes with the design and implementation of a graph-based unsupervised segmentation algorithm, having an associated very low computational cost. The processing automatically retrieves the whole network structure from large scale phase-contrast images taken at high resolution throughout the entire life of a cultured neuronal network. The network structure is represented by a mathematical object (a matrix) in which nodes are identified neurons or neurons clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocyto- chemistry techniques, our measures are non invasive and entitle us to carry out a fully longitudinal analysis during the maturation of a single culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main networks characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graphs micro- and meso-scale properties emerge. Finally, we identify the main physical processes taking place during the cultures morphological transformations, and embed them into a simplified growth model that quantitatively reproduces the overall set of experimental observations.

Phylogenetic analysis of tmRNA genes within a bacterial subgroup reveals a specific structural signature

Bacterial tmRNA mediates a trans-translation reaction, which permits the recycling of stalled ribosomes and probably also contributes to the regulated expression of a subset of genes. Its action results in the addition of a small number of C-terminal amino acids to protein whose synthesis had stalled and these constitute a proteolytic recognition tag for the degradation of these incompletely synthesized proteins. Previous work has identified pseudoknots and stem–loops that are widely conserved in divergent bacteria. In the present work an alignment of tmRNA gene sequences within 13 β-proteobacteria reveals an additional sub-structure specific for this bacterial group. This sub-structure is in pseudoknot Pk2, and consists of one to two additional stem–loop(s) capped by stable GNRA tetraloop(s). Three-dimensional models of tmRNA pseudoknot 2 (Pk2) containing various topological versions of the additional sub-structure suggest that the sub-structures likely point away from the core of the RNA, containing both the tRNA and the mRNA domains. A putative tertiary interaction has also been identified.