961 resultados para MAPPING MOLECULAR NETWORKS


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The adsorption of atomic and molecular hydrogen on armchair and zigzag boron carbonitride nanotubes is investigated within the ab initio density functional theory. The adsorption of atomic H on the BC(2)N nanotubes presents properties which are promising for nanoelectronic applications. Depending on the adsorption site for the H, the Fermi energy moves toward the bottom of the conduction band or toward the top of the valence band, leading the system to exhibit donor or acceptor characteristics, respectively. The H(2) molecules are physisorbed on the BC(2)N surface for both chiralities. The binding energies for the H(2) molecules are slightly dependent on the adsorption site, and they are near to the range to work as a hydrogen storage medium.

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Large-scale cortical networks exhibit characteristic topological properties that shape communication between brain regions and global cortical dynamics. Analysis of complex networks allows the description of connectedness, distance, clustering, and centrality that reveal different aspects of how the network's nodes communicate. Here, we focus on a novel analysis of complex walks in a series of mammalian cortical networks that model potential dynamics of information flow between individual brain regions. We introduce two new measures called absorption and driftness. Absorption is the average length of random walks between any two nodes, and takes into account all paths that may diffuse activity throughout the network. Driftness is the ratio between absorption and the corresponding shortest path length. For a given node of the network, we also define four related measurements, namely in-and out-absorption as well as in-and out-driftness, as the averages of the corresponding measures from all nodes to that node, and from that node to all nodes, respectively. We find that the cat thalamo-cortical system incorporates features of two classic network topologies, Erdos-Renyi graphs with respect to in-absorption and in-driftness, and configuration models with respect to out-absorption and out-driftness. Moreover, taken together these four measures separate the network nodes based on broad functional roles (visual, auditory, somatomotor, and frontolimbic).

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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.

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Contrasting responses for the temperature tuning of the electronic structure in semiconductor quantum wells are discussed for heterolayered structures grown along (001) and (113) directions. The temperature affects the strain modulation of the deformation potentials and the effective optical gap is tuned along with the intersub-band splitting in the valence band. A multiband theoretical model accounts for the characterization of the electronic structure, highlighting the main qualitative and quantitative differences between the two systems under study. The microscopic source of strain fields and the detailed mapping of their distribution are provided by a simulation using classical molecular-dynamics technics.

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We analyze the dynamical behavior of a quantum system under the actions of two counteracting baths: the inevitable energy draining reservoir and, in opposition, exciting the system, an engineered Glauber's amplifier. We follow the system dynamics towards equilibrium to map its distinctive behavior arising from the interplay of attenuation and amplification. Such a mapping, with the corresponding parameter regimes, is achieved by calculating the evolution of both the excitation and the Glauber-Sudarshan P function. Techniques to compute the decoherence and the fidelity of quantum states under the action of both counteracting baths, based on the Wigner function rather than the density matrix, are also presented. They enable us to analyze the similarity of the evolved state vector of the system with respect to the original one, for all regimes of parameters. Applications of this attenuation-amplification interplay are discussed.

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Biological neuronal networks constitute a special class of dynamical systems, as they are formed by individual geometrical components, namely the neurons. In the existing literature, relatively little attention has been given to the influence of neuron shape on the overall connectivity and dynamics of the emerging networks. The current work addresses this issue by considering simplified neuronal shapes consisting of circular regions (soma/axons) with spokes (dendrites). Networks are grown by placing these patterns randomly in the two-dimensional (2D) plane and establishing connections whenever a piece of dendrite falls inside an axon. Several topological and dynamical properties of the resulting graph are measured, including the degree distribution, clustering coefficients, symmetry of connections, size of the largest connected component, as well as three hierarchical measurements of the local topology. By varying the number of processes of the individual basic patterns, we can quantify relationships between the individual neuronal shape and the topological and dynamical features of the networks. Integrate-and-fire dynamics on these networks is also investigated with respect to transient activation from a source node, indicating that long-range connections play an important role in the propagation of avalanches.

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The ground states of a few electrons confined in two vertically coupled quantum rings in the presence of an external magnetic field are studied systematically within the current spin-density functional theory. Electron-electron interactions combined with inter-ring tunneling affect the electronic structure and the persistent current. For small values of the external magnetic field, we recover the zero magnetic field molecular quantum ring ground state configurations. Increasing the magnetic field many angular momentum, spin, and isospin transitions are predicted to occur in the ground state. We show that these transitions follow certain rules, which are governed by the parity of the number of electrons, the single-particle picture, Hund's rules, and many-body effects. (C) 2009 American Institute of Physics. [doi:10.1063/1.3223360]

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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.

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A combined analytical and numerical study is performed of the mapping between strongly interacting fermions and weakly interacting spins, in the framework of the Hubbard, t-J, and Heisenberg models. While for spatially homogeneous models in the thermodynamic limit the mapping is thoroughly understood, we here focus on aspects that become relevant in spatially inhomogeneous situations, such as the effect of boundaries, impurities, superlattices, and interfaces. We consider parameter regimes that are relevant for traditional applications of these models, such as electrons in cuprates and manganites, and for more recent applications to atoms in optical lattices. The rate of the mapping as a function of the interaction strength is determined from the Bethe-Ansatz for infinite systems and from numerical diagonalization for finite systems. We show analytically that if translational symmetry is broken through the presence of impurities, the mapping persists and is, in a certain sense, as local as possible, provided the spin-spin interaction between two sites of the Heisenberg model is calculated from the harmonic mean of the onsite Coulomb interaction on adjacent sites of the Hubbard model. Numerical calculations corroborate these findings also in interfaces and superlattices, where analytical calculations are more complicated.

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Background: Cystatins are inhibitors of cysteine proteases. The majority are only weak inhibitors of human cathepsin B, which has been associated with cancer, Alzheimer's disease and arthritis. Results: Starting from the sequences of oryzacystatin-1 and canecystatin-1, a shuffling library was designed and a hybrid clone obtained, which presented higher inhibitory activity towards cathepsin B. This clone presented two unanticipated point mutations as well as an N-terminal deletion. Reversing each point mutation independently or both simultaneously abolishes the inhibitory activity towards cathepsin B. Homology modeling together with experimental studies of the reverse mutants revealed the likely molecular determinants of the improved inhibitory activity to be related to decreased protein stability. Conclusion: A combination of experimental approaches including gene shuffling, enzyme assays and reverse mutation allied to molecular modeling has shed light upon the unexpected inhibitory properties of certain cystatin mutants against Cathepsin B. We conclude that mutations disrupting the hydrophobic core of phytocystatins increase the flexibility of the N-terminus, leading to an increase in inhibitory activity. Such mutations need not affect the inhibitory site directly but may be observed distant from it and manifest their effects via an uncoupling of its three components as a result of increased protein flexibility.

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The title 2:1 complex of 3-nitrophenol (MNP) and 4,4'-bipyridyl N, N'-dioxide (DPNO), 2C(6)H(5)NO(3)center dot C(10)H(8)N(2)O(2) or 2MNP center dot DPNO, crystallizes as a centrosymmetric three-component adduct with a dihedral angle of 59.40 (8)degrees between the planes of the benzene rings of MNP and DPNO (the DPNO moiety lies across a crystallographic inversion centre located at the mid-point of the C-C bond linking its aromatic rings). The complex owes its formation to O-H center dot center dot center dot O hydrogen bonds [O center dot center dot center dot O = 2.605 (3) angstrom]. Molecules are linked by intermolecular C-H center dot center dot center dot O and C-H center dot center dot center dot N interactions forming R(2)(1) (6) and R(2)(2) (10) rings, and R(6)(6) (34) and R(4)(4) (26) macro-rings, all of which are aligned along the [(1) over bar 01] direction, and R(2)(2) (10) and R(2)(1) (7) rings aligned along the [010] direction. The combination of chains of rings along the [(1) over bar 01] and [010] directions generates the three-dimensional structure. A total of 27 systems containing the DNPO molecule and forming molecular complexes of an organic nature were analysed and compared with the structural characteristics of the dioxide reported here. The N-O distance [1.325 (2) angstrom] depends not only on the interactions involving the O atom at the N-O group, but also on the structural ordering and additional three-dimensional interactions in the crystal structure. A density functional theory (DFT) optimized structure at the B3LYP/6-311G(d,p) level is compared with the molecular structure in the solid state.

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Schistosomes are unable to synthesize purines de novo and depend exclusively on the salvage pathway for their purine requirements. It has been suggested that blockage of this pathway could lead to parasite death. The enzyme purine nucleoside phosphorylase (PNP) is one of its key components and molecules designed to inhibit the low-molecular-weight (LMW) PNPs, which include both the human and schistosome enzymes, are typically analogues of the natural substrates inosine and guanosine. Here, it is shown that adenosine both binds to Schistosoma mansoni PNP and behaves as a weak micromolar inhibitor of inosine phosphorolysis. Furthermore, the first crystal structures of complexes of an LMW PNP with adenosine and adenine are reported, together with those with inosine and hypoxanthine. These are used to propose a structural explanation for the selective binding of adenosine to some LMW PNPs but not to others. The results indicate that transition-state analogues based on adenosine or other 6-amino nucleosides should not be discounted as potential starting points for alternative inhibitors.

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The mapping, exact or approximate, of a many-body problem onto an effective single-body problem is one of the most widely used conceptual and computational tools of physics. Here, we propose and investigate the inverse map of effective approximate single-particle equations onto the corresponding many-particle system. This approach allows us to understand which interacting system a given single-particle approximation is actually describing, and how far this is from the original physical many-body system. We illustrate the resulting reverse engineering process by means of the Kohn-Sham equations of density-functional theory. In this application, our procedure sheds light on the nonlocality of the density-potential mapping of density-functional theory, and on the self-interaction error inherent in approximate density functionals.

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The origin of the unique geometry for nitric oxide (NO) adsorption on Pd(111) and Pt(111) surfaces as well as the effect of temperature were studied by density functional theory calculations and ab initio molecular dynamics at finite temperature. We found that at low coverage, the adsorption geometry is determined by electronic interactions, depending sensitively on the adsorption sites and coverages, and the effect of temperature on geometries is significant. At coverage of 0.25 monolayer (ML), adsorbed NO at hollow sites prefer an upright configuration, while NO adsorbed at top sites prefer a tilting configuration. With increase in the coverage up to 0.50 ML, the enhanced steric repulsion lead to the tilting of hollow NO. We found that the tilting was enhanced by the thermal effects. At coverage of 0.75 ML with p(2 x 2)-3NO(fcc+hcp+top) structure, we found that there was no preferential orientation for tilted top NO. The interplay of the orbital hybridization, thermal effects, steric repulsion, and their effects on the adsorption geometries were highlighted at the end.

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This paper describes a new and simple method to determine the molecular weight of proteins in dilute solution, with an error smaller than similar to 10%, by using the experimental data of a single small-angle X-ray scattering (SAXS) curve measured on a relative scale. This procedure does not require the measurement of SAXS intensity on an absolute scale and does not involve a comparison with another SAXS curve determined from a known standard protein. The proposed procedure can be applied to monodisperse systems of proteins in dilute solution, either in monomeric or multimeric state, and it has been successfully tested on SAXS data experimentally determined for proteins with known molecular weights. It is shown here that the molecular weights determined by this procedure deviate from the known values by less than 10% in each case and the average error for the test set of 21 proteins was 5.3%. Importantly, this method allows for an unambiguous determination of the multimeric state of proteins with known molecular weights.