150 resultados para Topological


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Intrinsically disordered proteins, IDPs, are proteins that lack a rigid 3D structure under physiological conditions, at least in vitro. Despite the lack of structure, IDPs play important roles in biological processes and transition from disorder to order upon binding to their targets. With multiple conformational states and rapid conformational dynamics, they engage in myriad and often ``promiscuous'' interactions. These stochastic interactions between IDPs and their partners, defined here as conformational noise, is an inherent characteristic of IDP interactions. The collective effect of conformational noise is an ensemble of protein network configurations, from which the most suitable can be explored in response to perturbations, conferring protein networks with remarkable flexibility and resilience. Moreover, the ubiquitous presence of IDPs as transcriptional factors and, more generally, as hubs in protein networks, is indicative of their role in propagation of transcriptional (genetic) noise. As effectors of transcriptional and conformational noise, IDPs rewire protein networks and unmask latent interactions in response to perturbations. Thus, noise-driven activation of latent pathways could underlie state-switching events such as cellular transformation in cancer. To test this hypothesis, we created a model of a protein network with the topological characteristics of a cancer protein network and tested its response to a perturbation in presence of IDP hubs and conformational noise. Because numerous IDPs are found to be epigenetic modifiers and chromatin remodelers, we hypothesize that they could further channel noise into stable, heritable genotypic changes.

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Points-to analysis is a key compiler analysis. Several memory related optimizations use points-to information to improve their effectiveness. Points-to analysis is performed by building a constraint graph of pointer variables and dynamically updating it to propagate more and more points-to information across its subset edges. So far, the structure of the constraint graph has been only trivially exploited for efficient propagation of information, e.g., in identifying cyclic components or to propagate information in topological order. We perform a careful study of its structure and propose a new inclusion-based flow-insensitive context-sensitive points-to analysis algorithm based on the notion of dominant pointers. We also propose a new kind of pointer-equivalence based on dominant pointers which provides significantly more opportunities for reducing the number of pointers tracked during the analysis. Based on this hitherto unexplored form of pointer-equivalence, we develop a new context-sensitive flow-insensitive points-to analysis algorithm which uses incremental dominator update to efficiently compute points-to information. Using a large suite of programs consisting of SPEC 2000 benchmarks and five large open source programs we show that our points-to analysis is 88% faster than BDD-based Lazy Cycle Detection and 2x faster than Deep Propagation. We argue that our approach of detecting dominator-based pointer-equivalence is a key to improve points-to analysis efficiency.

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We present a unified study of the effect of periodic, quasiperiodic, and disordered potentials on topological phases that are characterized by Majorana end modes in one-dimensional p-wave superconducting systems. We define a topological invariant derived from the equations of motion for Majorana modes and, as our first application, employ it to characterize the phase diagram for simple periodic structures. Our general result is a relation between the topological invariant and the normal state localization length. This link allows us to leverage the considerable literature on localization physics and obtain the topological phase diagrams and their salient features for quasiperiodic and disordered systems for the entire region of parameter space. DOI: 10.1103/PhysRevLett.110.146404

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Three new compounds of bismuth, C4N2H10]center dotBi(C7H4NO4)(C7H3NO4)]center dot H2O, I, Bi(C5H3N2O4) (C5H2N2O4)], II, and Bi(mu(2)-OH)(C7H3NO4)], III, have been prepared by the reaction between bismuth nitrate and heterocyclic aromatic dicarboxylic acids, 2,6-pyridinedicarboxylic acid, 4,5-imidazoledicarboxylic acid, and 3,4-pyridinedicarboxylic acid, respectively, under hydrothermal conditions. The structures of all the compounds have linkages between Bi2O2 and the corresponding dicarboxylate forming a simple molecular unit in I, a bilayer arrangement in II, and a three-dimensional extended structure in III. The topological arrangement of the nodal building units in the structures indicates that a brucite-related layer (II) and fluorite-related arrangement (III) can be realized in these structures. By utilizing the secondary interactions, one can correlate the structure of III to a Kagome-related one. The observation of such classical inorganic related structures in the bismuth carboxylates is noteworthy. Lewis acid catalytic studies on the formation of ketal suggest the possible participatory role of the lone pair of electrons. All the compounds are characterized employing elemental analysis, IR, UV-vis, and thermal studies.

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In a quantum system, there may be many density matrices associated with a state on an algebra of observables. For each density matrix, one can compute its entropy. These are, in general, different. Therefore, one reaches the remarkable possibility that there may be many entropies for a given state R. Sorkin (private communication)]. This ambiguity in entropy can often be traced to a gauge symmetry emergent from the nontrivial topological character of the configuration space of the underlying system. It can also happen in finite-dimensional matrix models. In the present work, we discuss this entropy ambiguity and its consequences for an ethylene molecule. This is a very simple and well-known system, where these notions can be put to tests. Of particular interest in this discussion is the fact that the change of the density matrix with the corresponding entropy increase drives the system towards the maximally disordered state with maximum entropy, where Boltzman's formula applies. Besides its intrinsic conceptual interest, the simplicity of this model can serve as an introduction to a similar discussion of systems such as colored monopoles and the breaking of color symmetry.

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State estimation is one of the most important functions in an energy control centre. An computationally efficient state estimator which is free from numerical instability/ill-conditioning is essential for security assessment of electric power grid. Whereas approaches to successfully overcome the numerical ill-conditioning issues have been proposed, an efficient algorithm for addressing the convergence issues in the presence of topological errors is yet to be evolved. Trust region (TR) methods have been successfully employed to overcome the divergence problem to certain extent. In this study, case studies are presented where the conventional algorithms including the existing TR methods would fail to converge. A linearised model-based TR method for successfully overcoming the convergence issues is proposed. On the computational front, unlike the existing TR methods for state estimation which employ quadratic models, the proposed linear model-based estimator is computationally efficient because the model minimiser can be computed in a single step. The model minimiser at each step is computed by minimising the linearised model in the presence of TR and measurement mismatch constraints. The infinity norm is used to define the geometry of the TR. Measurement mismatch constraints are employed to improve the accuracy. The proposed algorithm is compared with the quadratic model-based TR algorithm with case studies on the IEEE 30-bus system, 205-bus and 514-bus equivalent systems of part of Indian grid.

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The contour tree is a topological abstraction of a scalar field that captures evolution in level set connectivity. It is an effective representation for visual exploration and analysis of scientific data. We describe a work-efficient, output sensitive, and scalable parallel algorithm for computing the contour tree of a scalar field defined on a domain that is represented using either an unstructured mesh or a structured grid. A hybrid implementation of the algorithm using the GPU and multi-core CPU can compute the contour tree of an input containing 16 million vertices in less than ten seconds with a speedup factor of upto 13. Experiments based on an implementation in a multi-core CPU environment show near-linear speedup for large data sets.

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This paper reports the first observations of transition from a pre-vortex breakdown (Pre-VB) flowreversal to a fully developed central toroidal recirculation zone in a non-reacting, double-concentric swirling jet configuration and its response to longitudinal acoustic excitation. This transition proceeds with the formation of two intermediate, critical flow regimes. First, a partially penetrated vortex breakdown bubble (VBB) is formed that indicates the first occurrence of an enclosed structure as the centre jet penetration is suppressed by the growing outer roll-up eddy; resulting in an opposed flow stagnation region. Second, a metastable transition structure is formed that marks the collapse of inner mixing vortices. In this study, the time-averaged topological changes in the coherent recirculation structures are discussed based on the non-dimensional modified Rossby number (Ro(m)) which appears to describe the spreading of the zone of swirl influence in different flow regimes. Further, the time-mean global acoustic response of pre-VB and VBB is measured as a function of pulsing frequency using the relative aerodynamic blockage factor (i.e., maximum radial width of the inner recirculation zone). It is observed that all flow modes except VBB are structurally unstable as they exhibit severe transverse radial shrinkage (similar to 20%) at the burner Helmholtz resonant modes (100-110 Hz). In contrast, all flow regimes show positional instability as seen by the large-scale, asymmetric spatial shifting of the vortex core centres. Finally, the mixing transfer function M (f) and magnitude squared coherence lambda(2)(f) analysis is presented to determine the natural couplingmodes of the system dynamic parameters (u', p'), i.e., local acoustic response. It is seen that the pre-VB flow mode exhibits a narrow-band, low pass filter behavior with a linear response window of 100-105 Hz. However, in the VBB structure, presence of critical regions such as the opposed flow stagnation region alters the linearity range with the structure showing a response even at higher pulsing frequencies (100-300 Hz). (C) 2013 AIP Publishing LLC.

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Entropy is a fundamental thermodynamic property that has attracted a wide attention across domains, including chemistry. Inference of entropy of chemical compounds using various approaches has been a widely studied topic. However, many aspects of entropy in chemical compounds remain unexplained. In the present work, we propose two new information-theoretical molecular descriptors for the prediction of gas phase thermal entropy of organic compounds. The descriptors reflect the bulk and size of the compounds as well as the gross topological symmetry in their structures, all of which are believed to determine entropy. A high correlation () between the entropy values and our information-theoretical indices have been found and the predicted entropy values, obtained from the corresponding statistically significant regression model, have been found to be within acceptable approximation. We provide additional mathematical result in the form of a theorem and proof that might further help in assessing changes in gas phase thermal entropy values with the changes in molecular structures. The proposed information-theoretical molecular descriptors, regression model and the mathematical result are expected to augment predictions of gas phase thermal entropy for a large number of chemical compounds.

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We present a comprehensive study of two of the most experimentally relevant extensions of Kitaev's spinless model of a one-dimensional p-wave superconductor: those involving (i) longer-range hopping and superconductivity and (ii) inhomogeneous potentials. We commence with a pedagogical review of the spinless model and, as a means of characterizing topological phases exhibited by the systems studied here, we introduce bulk topological invariants as well as those derived from an explicit consideration of boundary modes. In time-reversal symmetric systems, we find that the longer range hopping leads to topological phases characterized by multiple Majorana modes. In particular, we investigate a spin model that respects a duality and maps to a fermionic model with multiple Majorana modes; we highlight the connection between these topological phases and the broken symmetry phases in the original spin model. In the presence of time-reversal symmetry breaking terms, we show that the topological phase diagram is characterized by an extended gapless regime. For the case of inhomogeneous potentials, we explore phase diagrams of periodic, quasiperiodic, and disordered systems. We present a detailed mapping between normal state localization properties of such systems and the topological phases of the corresponding superconducting systems. This powerful tool allows us to leverage the analyses of Hofstadter's butterfly and the vast literature on Anderson localization to the question of Majorana modes in superconducting quasiperiodic and disordered systems, respectively. We briefly touch upon the synergistic effects that can be expected in cases where long-range hopping and disorder are both present.

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Network theory applied to protein structures provides insights into numerous problems of biological relevance. The explosion in structural data available from PDB and simulations establishes a need to introduce a standalone-efficient program that assembles network concepts/parameters under one hood in an automated manner. Herein, we discuss the development/application of an exhaustive, user-friendly, standalone program package named PSN-Ensemble, which can handle structural ensembles generated through molecular dynamics (MD) simulation/NMR studies or from multiple X-ray structures. The novelty in network construction lies in the explicit consideration of side-chain interactions among amino acids. The program evaluates network parameters dealing with topological organization and long-range allosteric communication. The introduction of a flexible weighing scheme in terms of residue pairwise cross-correlation/interaction energy in PSN-Ensemble brings in dynamical/chemical knowledge into the network representation. Also, the results are mapped on a graphical display of the structure, allowing an easy access of network analysis to a general biological community. The potential of PSN-Ensemble toward examining structural ensemble is exemplified using MD trajectories of an ubiquitin-conjugating enzyme (UbcH5b). Furthermore, insights derived from network parameters evaluated using PSN-Ensemble for single-static structures of active/inactive states of 2-adrenergic receptor and the ternary tRNA complexes of tyrosyl tRNA synthetases (from organisms across kingdoms) are discussed. PSN-Ensemble is freely available from http://vishgraph.mbu.iisc.ernet.in/PSN-Ensemble/psn_index.html.

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Visualizing symmetric patterns in the data often helps the domain scientists make important observations and gain insights about the underlying experiment. Detecting symmetry in scalar fields is a nascent area of research and existing methods that detect symmetry are either not robust in the presence of noise or computationally costly. We propose a data structure called the augmented extremum graph and use it to design a novel symmetry detection method based on robust estimation of distances. The augmented extremum graph captures both topological and geometric information of the scalar field and enables robust and computationally efficient detection of symmetry. We apply the proposed method to detect symmetries in cryo-electron microscopy datasets and the experiments demonstrate that the algorithm is capable of detecting symmetry even in the presence of significant noise. We describe novel applications that use the detected symmetry to enhance visualization of scalar field data and facilitate their exploration.

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Engineering at the molecular level is one of the most exciting new developments for the generation of functional materials. However, the concept of designing polynuclear extended structures from bottom up is still not mature. Although progress has been made with secondary building units (SBUs) in metal organic frameworks (MOFs), the control seems to be just an illusion when it comes to bridging ligands such as the azide ion. When we say that the azido ligand is versatile in its bridging capabilities, what we mean is that it would be difficult to predict or control its bridging properties. However, this kind of serendipity is not always bad news. For example, scientists have shown that the azido ligand can mediate magnetic exchanges between paramagnetic metals in a predictable fashion (usually depending upon the bonding geometries). Therefore, it is a well-respected ligand in polynuclear assemblies. Serendipitous assemblies offer new magnetic structures that we may not otherwise even think about synthesizing. The azido ligand forms a variety of complexes with copper(II) using different blocking amines or pyridine based ligands. Its structural nature changes upon changing the substitution on amine, as well as the amount of blocking ligand. In principle, if we take any of these complexes and provide more coordination sites to the bridging azido ligands by removing a fraction of the blocking ligands, we can get new complexes with intricate structural networks and therefore different magnetic properties with the same components as used for the parent complex. In this Account, we mainly discuss the development of a number of new topological and magnetic exchange systems synthesized using this concept. Not all of these new complexes can be grouped according to their basic building structures or even by the ratio of the metal to blocking ligand. Therefore, we divided the discussion by the nuclearity of the basic building structures. Some of the complexes with the same nuclearities have very similar or even almost identical basic structures. However, the way these building units are joined together (by the azido bridges) to form the overall extended structures differ almost in every case. The complexes having the Cu-6 core are particularly interesting from a structural point of view. Although they have almost identical basic structures, some of them are extended in three dimensions, but two of them are extended in two dimensions by two different bridging networks. In the complexes having linear Cu-4 basic units, we find that using similar ligands does not always give the same bridging networks even within the basic building structures. These complexes have also enriched the field of molecular magnetism. One of the complexes with a Cu-3 building unit has provided us with the opportunity to study the competing behavior of two different kinds of magnetic exchange mechanism (ferromagnetic and antiferromagnetic) acting simultaneously between two metal ions. Through density functional theory calculations, we showed how they work independently and their additive nature to produce the overall effect. The exciting methodology for the generation of copper(II) polyclusters presented in this Account will provide the opportunity to explore analogous serendipitous assembly of diverse structures with interesting magnetic behavior using other transition metal ions having more than one unpaired electrons.

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Stochastic modelling is a useful way of simulating complex hard-rock aquifers as hydrological properties (permeability, porosity etc.) can be described using random variables with known statistics. However, very few studies have assessed the influence of topological uncertainty (i.e. the variability of thickness of conductive zones in the aquifer), probably because it is not easy to retrieve accurate statistics of the aquifer geometry, especially in hard rock context. In this paper, we assessed the potential of using geophysical surveys to describe the geometry of a hard rock-aquifer in a stochastic modelling framework. The study site was a small experimental watershed in South India, where the aquifer consisted of a clayey to loamy-sandy zone (regolith) underlain by a conductive fissured rock layer (protolith) and the unweathered gneiss (bedrock) at the bottom. The spatial variability of the thickness of the regolith and fissured layers was estimated by electrical resistivity tomography (ERT) profiles, which were performed along a few cross sections in the watershed. For stochastic analysis using Monte Carlo simulation, the generated random layer thickness was made conditional to the available data from the geophysics. In order to simulate steady state flow in the irregular domain with variable geometry, we used an isoparametric finite element method to discretize the flow equation over an unstructured grid with irregular hexahedral elements. The results indicated that the spatial variability of the layer thickness had a significant effect on reducing the simulated effective steady seepage flux and that using the conditional simulations reduced the uncertainty of the simulated seepage flux. As a conclusion, combining information on the aquifer geometry obtained from geophysical surveys with stochastic modelling is a promising methodology to improve the simulation of groundwater flow in complex hard-rock aquifers. (C) 2013 Elsevier B.V. All rights reserved.

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Stone-Wales (SW) defects in materials having hexagonal lattice are the most common topological defects that affect the electronic and mechanical properties. Using first principles density functional theory based calculations, we study the formation energy and kinetic barrier of SW-defect in infinite and finite sheets of silicene. The formation energies as well as the barriers in both the cases are significantly lower than those of graphene. Furthermore, compared with the infinite sheets, the energy barriers and formation energies are lower for finite sheets. However, due to low barriers these defects are expected to heal out of the finite sheets. (C) 2013 Elsevier B.V. All rights reserved.