Nonsingular bounce in modified gravity

We investigate bouncing solutions in the framework of the nonsingular gravity model of Brandenberger, Mukhanov and Sornborger. We show that a spatially flat universe filled with ordinary matter undergoing a phase of contraction reaches a stage of minimal expansion factor before bouncing in a regular way to reach the expanding phase. The expansion can be connected to the usual radiation-and matter-dominated epochs before reaching a final expanding de Sitter phase. In general relativity (GR), a bounce can only take place provided that the spatial sections are positively curved, a fact that has been shown to translate into a constraint on the characteristic duration of the bounce. In our model, on the other hand, a bounce can occur also in the absence of spatial curvature, which means that the time scale for the bounce can be made arbitrarily short or long. The implication is that constraints on the bounce characteristic time obtained in GR rely heavily on the assumed theory of gravity. Although the model we investigate is fourth order in the derivatives of the metric (and therefore unstable vis-a-vis the perturbations), this generic bounce dynamics should extend to string-motivated nonsingular models which can accommodate a spatially flat bounce.

Deformations of the Tracy-Widom distribution

In random matrix theory, the Tracy-Widom (TW) distribution describes the behavior of the largest eigenvalue. We consider here two models in which TW undergoes transformations. In the first one disorder is introduced in the Gaussian ensembles by superimposing an external source of randomness. A competition between TW and a normal (Gaussian) distribution results, depending on the spreading of the disorder. The second model consists of removing at random a fraction of (correlated) eigenvalues of a random matrix. The usual formalism of Fredholm determinants extends naturally. A continuous transition from TW to the Weilbull distribution, characteristic of extreme values of an uncorrelated sequence, is obtained.

Hydro-kinetic approach to relativistic heavy ion collisions

We develop a combined hydro-kinetic approach which incorporates a hydrodynamical expansion of the systems formed in A + A collisions and their dynamical decoupling described by escape probabilities. The method corresponds to a generalized relaxation time (tau(rel)) approximation for the Boltzmann equation applied to inhomogeneous expanding systems; at small tau(rel) it also allows one to catch the viscous effects in hadronic component-hadron-resonance gas. We demonstrate how the approximation of sudden freeze-out can be obtained within this dynamical picture of continuous emission and find that hypersurfaces, corresponding to a sharp freeze-out limit, are momentum dependent. The pion m(T) spectra are computed in the developed hydro-kinetic model, and compared with those obtained from ideal hydrodynamics with the Cooper-Frye isothermal prescription. Our results indicate that there does not exist a universal freeze-out temperature for pions with different momenta, and support an earlier decoupling of higher p(T) particles. By performing numerical simulations for various initial conditions and equations of state we identify several characteristic features of the bulk QCD matter evolution preferred in view of the current analysis of heavy ion collisions at RHIC energies.

Formation of atomic carbon chains from graphene nanoribbons

The formation of one-dimensional carbon chains from graphene nanoribbons is investigated using ab initio molecular dynamics. We show under what conditions it is possible to obtain a linear atomic chain via pulling of the graphene nanoribbons. The presence of dimers composed of two-coordinated carbon atoms at the edge of the ribbons is necessary for the formation of the linear chains, otherwise there is simply the full rupture of the structure. The presence of Stone-Wales defects close to these dimers may lead to the formation of longer chains. The local atomic configuration of the suspended atoms indicates the formation of single and triple bonds, which is a characteristic of polyynes.

Network of recurrent events for the Olami-Feder-Christensen model

We numerically study the dynamics of a discrete spring-block model introduced by Olami, Feder, and Christensen (OFC) to mimic earthquakes and investigate to what extent this simple model is able to reproduce the observed spatiotemporal clustering of seismicity. Following a recently proposed method to characterize such clustering by networks of recurrent events [J. Davidsen, P. Grassberger, and M. Paczuski, Geophys. Res. Lett. 33, L11304 (2006)], we find that for synthetic catalogs generated by the OFC model these networks have many nontrivial statistical properties. This includes characteristic degree distributions, very similar to what has been observed for real seismicity. There are, however, also significant differences between the OFC model and earthquake catalogs, indicating that this simple model is insufficient to account for certain aspects of the spatiotemporal clustering of seismicity.

Equivalence between Redfield- and master-equation approaches for a time-dependent quantum system and coherence control

We present a derivation of the Redfield formalism for treating the dissipative dynamics of a time-dependent quantum system coupled to a classical environment. We compare such a formalism with the master equation approach where the environments are treated quantum mechanically. Focusing on a time-dependent spin-1/2 system we demonstrate the equivalence between both approaches by showing that they lead to the same Bloch equations and, as a consequence, to the same characteristic times T(1) and T(2) (associated with the longitudinal and transverse relaxations, respectively). These characteristic times are shown to be related to the operator-sum representation and the equivalent phenomenological-operator approach. Finally, we present a protocol to circumvent the decoherence processes due to the loss of energy (and thus, associated with T(1)). To this end, we simply associate the time dependence of the quantum system to an easily achieved modulated frequency. A possible implementation of the protocol is also proposed in the context of nuclear magnetic resonance.

Communication structure of cortical networks

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).

Automatic Network Fingerprinting through Single-Node Motifs

Complex networks have been characterised by their specific connectivity patterns (network motifs), but their building blocks can also be identified and described by node-motifs-a combination of local network features. One technique to identify single node-motifs has been presented by Costa et al. (L. D. F. Costa, F. A. Rodrigues, C. C. Hilgetag, and M. Kaiser, Europhys. Lett., 87, 1, 2009). Here, we first suggest improvements to the method including how its parameters can be determined automatically. Such automatic routines make high-throughput studies of many networks feasible. Second, the new routines are validated in different network-series. Third, we provide an example of how the method can be used to analyse network time-series. In conclusion, we provide a robust method for systematically discovering and classifying characteristic nodes of a network. In contrast to classical motif analysis, our approach can identify individual components (here: nodes) that are specific to a network. Such special nodes, as hubs before, might be found to play critical roles in real-world networks.

Internal Strain Distribution in Freestanding Porous Silicon

Elastic properties of freestanding porous silicon layers fabricated by electrochemical anodization were studied by Raman scattering. Different anodization currents provided different degrees of porosity in the nanometer scale. Raman lines corresponding to the longitudinal optical phonons of crystalline and amorphous phases were observed. The amorphous volume fraction increased and the phonon frequencies for both phases decreased with increasing porosity. A strain distribution model is proposed whose fit to the experimental results indicates that the increasing nanoscale porosity causes strain relaxation in the amorphous domains and strain buildup in the crystalline ones. The present analysis has significant implications on the estimation of the crystalline Si domain's characteristic size from Raman scattering data. (C) 2009 The Electrochemical Society. [DOI: 10.1149/1.3225832] All rights reserved.

Effect of Mn concentration and atomic structure on the magnetic properties of Ge thin films

This work reports on the magnetic properties of Ge(100-x)Mn(x) (x=0-24 at. %) films prepared by cosputtering a Ge+Mn target and submitted to cumulative thermal annealing treatments up to 500 degrees C. Both as-deposited and annealed films were investigated by means of compositional analysis, Raman scattering spectroscopy, magnetic force microscopy, superconducting quantum interference device magnetometry, and electrical resistivity measurements. All as-deposited films (either pure or containing Mn) exhibit an amorphous structure, which changes to crystalline as the annealing treatments are performed at increasing temperatures. In fact, the magnetic properties of the present Ge(100-x)Mn(x) films are very sensitive to the Mn content and whether their atomic structure is amorphous or crystalline. More specifically: whereas the amorphous Ge(100-x)Mn(x) films (with high x) present a characteristic spin glass behavior at low temperature; after crystallization, the films (with moderate Mn contents) are ferromagnetic at room temperature. Moreover, the magnetic behavior of the films scales with their Mn concentration and tends to be more pronounced after crystallization. Finally, the semiconducting behavior of the films, experienced by previous optical studies, was confirmed through electrical measurements, which also indicate the dependence of the resistivity with the atomic composition of the films. (C) 2010 American Institute of Physics. [doi: 10.1063/1.3520661]

Sublattice magnetism in sigma-phase Fe(100-x)Vx (x=34.4, 39.9, and 47.9) studied via zero-field (51)V NMR

The successful measurements of a sublattice magnetism with (51)V NMR techniques in the sigma-phase Fe(100-x)V(x) alloys with x=34.4, 39.9, and 47.9 are reported. Vanadium atoms, which were revealed to be present on all five crystallographic sites, are found to be under the action of the hyperfine magnetic fields produced by the neighboring Fe atoms, which allow the observation of (51)V NMR signals. Their nuclear magnetic properties are characteristic of a given site, which strongly depend on the composition. Site A exhibits the strongest magnetism while site D is the weakest. The estimated average magnetic moment per V atom decreases from 0.36 mu(B) for x=34.4 to 0.20 mu(B) for x=47.9. The magnetism revealed at V atoms is linearly correlated with the magnetic moment of Fe atoms, which implies that the former is induced by the latter.

Novel pathogenic mutations and skin biopsy analysis in Knobloch syndrome

Purpose: To facilitate future diagnosis of Knobloch syndrome (KS) and better understand its etiology, we sought to identify not yet described COL18A1 mutations in KS patients. In addition, we tested whether mutations in this gene lead to absence of the COL18A1 gene product and attempted to better characterize the functional effect of a previously reported missense mutation. Methods: Direct sequencing of COL18A1 exons was performed in KS patients from four unrelated pedigrees. We used immunofluorescent histochemistry in skin biopsies to evaluate the presence of type XVIII collagen in four KS patients carrying two already described mutations: c. 3277C>T, a nonsense mutation, and c. 3601G>A, a missense mutation. Furthermore, we determined the binding properties of the mutated endostatin domain p.A1381T (c.3601G>A) to extracellular matrix proteins using ELISA and surface plasmon resonance assays. Results: We identified four novel mutations in COL18A1, including a large deletion involving exon 41. Skin biopsies from KS patients revealed lack of type XVIII collagen in epithelial basement membranes and blood vessels. We also found a reduced affinity of p.A1381T endostatin to some extracellular matrix components. Conclusions: COL18A1 mutations involved in Knobloch syndrome have a distribution bias toward the coding exons of the C-terminal end. Large deletions must also be considered when point mutations are not identified in patients with characteristic KS phenotype. We report, for the first time, lack of type XVIII collagen in KS patients by immunofluorescent histochemistry in skin biopsy samples. As a final point, we suggest the employment of this technique as a preliminary and complementary test for diagnosis of KS in cases when mutation screening either does not detect mutations or reveals mutations of uncertain effect, such as the p.A1381T change.

An algorithmic Friedman-Pippenger theorem on tree embeddings and applications

An (n, d)-expander is a graph G = (V, E) such that for every X subset of V with vertical bar X vertical bar <= 2n - 2 we have vertical bar Gamma(G)(X) vertical bar >= (d + 1) vertical bar X vertical bar. A tree T is small if it has at most n vertices and has maximum degree at most d. Friedman and Pippenger (1987) proved that any ( n; d)- expander contains every small tree. However, their elegant proof does not seem to yield an efficient algorithm for obtaining the tree. In this paper, we give an alternative result that does admit a polynomial time algorithm for finding the immersion of any small tree in subgraphs G of (N, D, lambda)-graphs Lambda, as long as G contains a positive fraction of the edges of Lambda and lambda/D is small enough. In several applications of the Friedman-Pippenger theorem, including the ones in the original paper of those authors, the (n, d)-expander G is a subgraph of an (N, D, lambda)-graph as above. Therefore, our result suffices to provide efficient algorithms for such previously non-constructive applications. As an example, we discuss a recent result of Alon, Krivelevich, and Sudakov (2007) concerning embedding nearly spanning bounded degree trees, the proof of which makes use of the Friedman-Pippenger theorem. We shall also show a construction inspired on Wigderson-Zuckerman expander graphs for which any sufficiently dense subgraph contains all trees of sizes and maximum degrees achieving essentially optimal parameters. Our algorithmic approach is based on a reduction of the tree embedding problem to a certain on-line matching problem for bipartite graphs, solved by Aggarwal et al. (1996).

TESTING STATISTICAL HYPOTHESIS ON RANDOM TREES AND APPLICATIONS TO THE PROTEIN CLASSIFICATION PROBLEM

Efficient automatic protein classification is of central importance in genomic annotation. As an independent way to check the reliability of the classification, we propose a statistical approach to test if two sets of protein domain sequences coming from two families of the Pfam database are significantly different. We model protein sequences as realizations of Variable Length Markov Chains (VLMC) and we use the context trees as a signature of each protein family. Our approach is based on a Kolmogorov-Smirnov-type goodness-of-fit test proposed by Balding et at. [Limit theorems for sequences of random trees (2008), DOI: 10.1007/s11749-008-0092-z]. The test statistic is a supremum over the space of trees of a function of the two samples; its computation grows, in principle, exponentially fast with the maximal number of nodes of the potential trees. We show how to transform this problem into a max-flow over a related graph which can be solved using a Ford-Fulkerson algorithm in polynomial time on that number. We apply the test to 10 randomly chosen protein domain families from the seed of Pfam-A database (high quality, manually curated families). The test shows that the distributions of context trees coming from different families are significantly different. We emphasize that this is a novel mathematical approach to validate the automatic clustering of sequences in any context. We also study the performance of the test via simulations on Galton-Watson related processes.

Functional microarray analysis suggests repressed cell-cell signaling and cell survival-related modules inhibit progression of head and neck squamous cell carcinoma

Background: Cancer shows a great diversity in its clinical behavior which cannot be easily predicted using the currently available clinical or pathological markers. The identification of pathways associated with lymph node metastasis (N+) and recurrent head and neck squamous cell carcinoma (HNSCC) may increase our understanding of the complex biology of this disease. Methods: Tumor samples were obtained from untreated HNSCC patients undergoing surgery. Patients were classified according to pathologic lymph node status (positive or negative) or tumor recurrence (recurrent or non-recurrent tumor) after treatment (surgery with neck dissection followed by radiotherapy). Using microarray gene expression, we screened tumor samples according to modules comprised by genes in the same pathway or functional category. Results: The most frequent alterations were the repression of modules in negative lymph node (N0) and in non-recurrent tumors rather than induction of modules in N+ or in recurrent tumors. N0 tumors showed repression of modules that contain cell survival genes and in non-recurrent tumors cell-cell signaling and extracellular region modules were repressed. Conclusions: The repression of modules that contain cell survival genes in N0 tumors reinforces the important role that apoptosis plays in the regulation of metastasis. In addition, because tumor samples used here were not microdissected, tumor gene expression data are represented together with the stroma, which may reveal signaling between the microenvironment and tumor cells. For instance, in non-recurrent tumors, extracellular region module was repressed, indicating that the stroma and tumor cells may have fewer interactions, which disable metastasis development. Finally, the genes highlighted in our analysis can be implicated in more than one pathway or characteristic, suggesting that therapeutic approaches to prevent tumor progression should target more than one gene or pathway, specially apoptosis and interactions between tumor cells and the stroma.