graph zeta function: Topics by Science.gov

Sample records for graph zeta function

Relating zeta functions of discrete and quantum graphs

NASA Astrophysics Data System (ADS)

Harrison, Jonathan; Weyand, Tracy

2018-02-01

We write the spectral zeta function of the Laplace operator on an equilateral metric graph in terms of the spectral zeta function of the normalized Laplace operator on the corresponding discrete graph. To do this, we apply a relation between the spectrum of the Laplacian on a discrete graph and that of the Laplacian on an equilateral metric graph. As a by-product, we determine how the multiplicity of eigenvalues of the quantum graph, that are also in the spectrum of the graph with Dirichlet conditions at the vertices, depends on the graph geometry. Finally we apply the result to calculate the vacuum energy and spectral determinant of a complete bipartite graph and compare our results with those for a star graph, a graph in which all vertices are connected to a central vertex by a single edge.
Graph characterization via Ihara coefficients.

PubMed

Ren, Peng; Wilson, Richard C; Hancock, Edwin R

2011-02-01

The novel contributions of this paper are twofold. First, we demonstrate how to characterize unweighted graphs in a permutation-invariant manner using the polynomial coefficients from the Ihara zeta function, i.e., the Ihara coefficients. Second, we generalize the definition of the Ihara coefficients to edge-weighted graphs. For an unweighted graph, the Ihara zeta function is the reciprocal of a quasi characteristic polynomial of the adjacency matrix of the associated oriented line graph. Since the Ihara zeta function has poles that give rise to infinities, the most convenient numerically stable representation is to work with the coefficients of the quasi characteristic polynomial. Moreover, the polynomial coefficients are invariant to vertex order permutations and also convey information concerning the cycle structure of the graph. To generalize the representation to edge-weighted graphs, we make use of the reduced Bartholdi zeta function. We prove that the computation of the Ihara coefficients for unweighted graphs is a special case of our proposed method for unit edge weights. We also present a spectral analysis of the Ihara coefficients and indicate their advantages over other graph spectral methods. We apply the proposed graph characterization method to capturing graph-class structure and clustering graphs. Experimental results reveal that the Ihara coefficients are more effective than methods based on Laplacian spectra.
A novel conductivity mechanism of highly disordered carbon systems based on an investigation of graph zeta function

NASA Astrophysics Data System (ADS)

Matsutani, Shigeki; Sato, Iwao

2017-09-01

In the previous report (Matsutani and Suzuki, 2000 [21]), by proposing the mechanism under which electric conductivity is caused by the activational hopping conduction with the Wigner surmise of the level statistics, the temperature-dependent of electronic conductivity of a highly disordered carbon system was evaluated including apparent metal-insulator transition. Since the system consists of small pieces of graphite, it was assumed that the reason why the level statistics appears is due to the behavior of the quantum chaos in each granular graphite. In this article, we revise the assumption and show another origin of the Wigner surmise, which is more natural for the carbon system based on a recent investigation of graph zeta function in graph theory. Our method can be applied to the statistical treatment of the electronic properties of the randomized molecular system in general.
Discrete geometric analysis of message passing algorithm on graphs

NASA Astrophysics Data System (ADS)

Watanabe, Yusuke

2010-04-01

We often encounter probability distributions given as unnormalized products of non-negative functions. The factorization structures are represented by hypergraphs called factor graphs. Such distributions appear in various fields, including statistics, artificial intelligence, statistical physics, error correcting codes, etc. Given such a distribution, computations of marginal distributions and the normalization constant are often required. However, they are computationally intractable because of their computational costs. One successful approximation method is Loopy Belief Propagation (LBP) algorithm. The focus of this thesis is an analysis of the LBP algorithm. If the factor graph is a tree, i.e. having no cycle, the algorithm gives the exact quantities. If the factor graph has cycles, however, the LBP algorithm does not give exact results and possibly exhibits oscillatory and non-convergent behaviors. The thematic question of this thesis is "How the behaviors of the LBP algorithm are affected by the discrete geometry of the factor graph?" The primary contribution of this thesis is the discovery of a formula that establishes the relation between the LBP, the Bethe free energy and the graph zeta function. This formula provides new techniques for analysis of the LBP algorithm, connecting properties of the graph and of the LBP and the Bethe free energy. We demonstrate applications of the techniques to several problems including (non) convexity of the Bethe free energy, the uniqueness and stability of the LBP fixed point. We also discuss the loop series initiated by Chertkov and Chernyak. The loop series is a subgraph expansion of the normalization constant, or partition function, and reflects the graph geometry. We investigate theoretical natures of the series. Moreover, we show a partial connection between the loop series and the graph zeta function.
Electrokinetic properties of PMAA functionalized NiFe2O4 nanoparticles synthesized by thermal plasma route

NASA Astrophysics Data System (ADS)

Bhosale, Shivaji V.; Mhaske, Pravin; Kanhe, N.; Navale, A. B.; Bhoraskar, S. V.; Mathe, V. L.; Bhatt, S. K.

2014-04-01

The magnetic nickel ferrite (NiFe2O4) nanoparticles with an average size of 30nm were synthesised by Transferred arc DC Thermal Plasma route. The synthesized nickel ferrite nanoparticles were characterized by TEM and FTIR techniques. The synthesized nickel ferrite nanoparticles were further functionalized with PMAA (polymethacrylic acid) by self emulsion polymerization method and subsequently were characterized by FTIR and Zeta Analyzer. The variation of zeta potential with pH was systematically studied for both PMAA functionalized (PNFO) and uncoated nickel ferrite nanoparticles (NFO). The IEP (isoelectric points) for PNFO and NFO was determined from the graph of zeta potential vs pH. It was observed that the IEP for NFO was at 7.20 and for PNFO it was 2.52. The decrease in IEP of PNFO was attributed to the COOH functional group of PMAA.
Orbit-product representation and correction of Gaussian belief propagation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, Jason K; Chertkov, Michael; Chernyak, Vladimir

We present a new interpretation of Gaussian belief propagation (GaBP) based on the 'zeta function' representation of the determinant as a product over orbits of a graph. We show that GaBP captures back-tracking orbits of the graph and consider how to correct this estimate by accounting for non-backtracking orbits. We show that the product over non-backtracking orbits may be interpreted as the determinant of the non-backtracking adjacency matrix of the graph with edge weights based on the solution of GaBP. An efficient method is proposed to compute a truncated correction factor including all non-backtracking orbits up to a specified length.
Regularized Laplacian determinants of self-similar fractals

NASA Astrophysics Data System (ADS)

Chen, Joe P.; Teplyaev, Alexander; Tsougkas, Konstantinos

2018-06-01

We study the spectral zeta functions of the Laplacian on fractal sets which are locally self-similar fractafolds, in the sense of Strichartz. These functions are known to meromorphically extend to the entire complex plane, and the locations of their poles, sometimes referred to as complex dimensions, are of special interest. We give examples of locally self-similar sets such that their complex dimensions are not on the imaginary axis, which allows us to interpret their Laplacian determinant as the regularized product of their eigenvalues. We then investigate a connection between the logarithm of the determinant of the discrete graph Laplacian and the regularized one.
A Schrödinger equation for solving the Bender-Brody-Müller conjecture

NASA Astrophysics Data System (ADS)

Moxley, Frederick Ira

2017-11-01

The Hamiltonian of a quantum mechanical system has an affiliated spectrum. If this spectrum is the sequence of prime numbers, a connection between quantum mechanics and the nontrivial zeros of the Riemann zeta function can be made. In this case, the Riemann zeta function is analogous to chaotic quantum systems, as the harmonic oscillator is for integrable quantum systems. Such quantum Riemann zeta function analogies have led to the Bender-Brody-Müller (BBM) conjecture, which involves a non-Hermitian Hamiltonian that maps to the zeros of the Riemann zeta function. If the BBM Hamiltonian can be shown to be Hermitian, then the Riemann Hypothesis follows. As such, herein we perform a symmetrization procedure of the BBM Hamiltonian to obtain a unique Hermitian Hamiltonian that maps to the zeros of the analytic continuation of the Riemann zeta function, and discuss the eigenvalues of the results. Moreover, a second quantization of the resulting Schrödinger equation is performed, and a convergent solution for the nontrivial zeros of the analytic continuation of the Riemann zeta function is obtained. Finally, the Hilbert-Pólya conjecture is discussed, and it is heuristically shown that the real part of every nontrivial zero of the Riemann zeta function converges at σ = 1/2.
Probability function of breaking-limited surface elevation. [wind generated waves of ocean

NASA Technical Reports Server (NTRS)

Tung, C. C.; Huang, N. E.; Yuan, Y.; Long, S. R.

1989-01-01

The effect of wave breaking on the probability function of surface elevation is examined. The surface elevation limited by wave breaking zeta sub b(t) is first related to the original wave elevation zeta(t) and its second derivative. An approximate, second-order, nonlinear, non-Gaussian model for zeta(t) of arbitrary but moderate bandwidth is presented, and an expression for the probability density function zeta sub b(t) is derived. The results show clearly that the effect of wave breaking on the probability density function of surface elevation is to introduce a secondary hump on the positive side of the probability density function, a phenomenon also observed in wind wave tank experiments.
Direct and converse theorems in problems of approximation by vectors of finite degree

DOE Office of Scientific and Technical Information (OSTI.GOV)

Radzievski, G V

1998-04-30

Let A be a linear operator in a complex Banach space X with domain D(A) and a non-empty resolvent set. An element g element of D{sub {infinity}}(A):= intersection{sub j=0,1,...}D(A{sup j}) is called a vector of degree at most {zeta}(>0) with respect to A if ||A{sup j}g||{sub X}{<=}c(g){zeta}{sup j}, j=0,1,.... The set of vectors of degree at most {zeta} is denoted by G{sub {zeta}}(A). The quantity E{sub {zeta}}(f,A){sub X}=inf{sub gelement} {sub of{sub G}{sub {zeta}}}{sub (A)}||f-g||{sub X} is introduced and estimated in terms of the K-functional K({zeta}{sup -r},f;X,D(A{sup r}))=inf{sub gelementof} {sub D(A{sup r})}(||f-g||{sub X}+{zeta}{sup -r}||A{sup r}f||{sub X}) (the direct theorem). An estimatemore » of this K-functional in terms of E{sub {zeta}}(f,A){sub X} and ||f||{sub x} is established (the converse theorem). Using the estimates obtained, necessary and sufficient conditions for the following properties are found in terms of E{sub {zeta}}(f,A){sub X}: 1) f element of D{sub {infinity}}(A); 2) the series e{sup zA}f:={sigma}{sub r=0}{sup {infinity}}(z{sup r}A{sup r}f)/(r{exclamation_point}) converges in some disc; 3) the series e{sup zA}f converges in the entire complex plane. The growth order and the type of the entire function e{sup zA}f are calculated in terms of E{sub {zeta}}(f,A){sub X}.« less
Direct and inverse theorems on approximation by root functions of a regular boundary-value problem

DOE Office of Scientific and Technical Information (OSTI.GOV)

Radzievskii, G V

2006-08-31

One considers the spectral problem x{sup (n)}+ Fx={lambda}x with boundary conditions U{sub j}(x)=0, j=1,...,n, for functions x on [0,1]. It is assumed that F is a linear bounded operator from the Hoelder space C{sup {gamma}}, {gamma} element of [0,n-1), into L{sub 1} and the U{sub j} are bounded linear functionals on C{sup k{sub j}} with k{sub j} element of {l_brace}0,...,n- 1{r_brace}. Let P{sub {zeta}} be the linear span of the root functions of the problem x{sup (n)}+ Fx={lambda}x, U{sub j}(x)=0, j=1,...,n, corresponding to the eigenvalues {lambda}{sub k} with |{lambda}{sub k}|<{zeta}{sup n}, and let E{sub {zeta}}(f){sub W{sub p}{sup l}}:=inf{l_brace}||f-g||{sub W{sub p}{supmore » l}}:g element of P{sub {zeta}}{r_brace}. An estimate of E{sub {zeta}}(f){sub W{sub p}{sup l}} is obtained in terms of the K-functional K({zeta}{sup -m},f;W{sub p}{sup l},W{sub p,U}{sup l+m}):= inf{l_brace}||f-x||{sub W{sub p}{sup l}}+{zeta}{sup -m}||x||{sub W{sub p}{sup l}{sup +}{sup m}}:x element of W{sub p}{sup l+m}, U{sub j}(x)=0 for k{sub j}
Activation-induced proteolysis of cytoplasmic domain of zeta in T cell receptors and Fc receptors.

PubMed

Taupin, J L; Anderson, P

1994-12-01

The CD3-T cell receptor (TCR) complex on T cells and the Fc gamma receptor type III (Fc gamma RIII)-zeta-gamma complex on natural killer cells are functionally analogous activation receptors that associate with a family of disulfide-linked dimers composed of the related subunits zeta and gamma. Immunochemical analysis of receptor complexes separated on two-dimensional diagonal gels allowed the identification of a previously uncharacterized zeta-p14 heterodimer. zeta-p14 is a component of both CD3-TCR and Fc gamma RIII-zeta-gamma. Peptide mapping analysis shows that p14 is structurally related to zeta, suggesting that it is either: (i) derived from zeta proteolytically or (ii) the product of an alternatively spliced mRNA. The observation that COS cells transformed with a cDNA encoding zeta express zeta-p14 supports the former possibility. The expression of CD3-TCR complexes including zeta-p14 increases following activation with phorbol 12-myristate 13-acetate or concanavalin A, suggesting that proteolysis of zeta may contribute to receptor modulation or desensitization.
A functional role for CD28 costimulation in tumor recognition by single-chain receptor-modified T cells.

PubMed

Moeller, Maria; Haynes, Nicole M; Trapani, Joseph A; Teng, Michele W L; Jackson, Jacob T; Tanner, Jane E; Cerutti, Loretta; Jane, Stephen M; Kershaw, Michael H; Smyth, Mark J; Darcy, Phillip K

2004-05-01

T cells engineered to express single-chain antibody receptors that incorporate TCR-zeta and cluster designation (CD)28 signaling domains (scFv-alpha-erbB2-CD28-zeta) can be redirected in vivo to cancer cells that lack triggering costimulatory molecules. To assess the contribution of CD28 signaling to the function of the scFv-CD28-zeta receptor, we expressed a series of mutated scFv-CD28-zeta receptors directed against erbB2. Residues known to be critical for CD28 signaling were mutated from tyrosine to phenylalanine at position 170 or proline to alanine at positions 187 and 190. Primary mouse T cells expressing either of the mutant receptors demonstrated impaired cytokine (IFN-gamma and GM-CSF) production and decreased proliferation after antigen ligation in vitro and decreased antitumor efficacy in vivo compared with T cells expressing the wild-type scFv-CD28-zeta receptor, suggesting a key signaling role for the CD28 component of the scFv-CD28-zeta receptor. Importantly, cell surface expression, binding capacity and cytolytic activity mediated by the scFv-CD28-zeta receptor were not diminished by either mutation. Overall, this study has definitively demonstrated a functional role for the CD28 component of the scFv-CD28-zeta receptor and has shown that incorporation of costimulatory activity in chimeric scFv receptors is a powerful approach for improving adoptive cancer immunotherapy.
Tunnel determinants from spectral zeta functions. Instanton effects in quantum mechanics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Izquierdo, A. Alonso; Guilarte, J. Mateos

2014-07-23

In this paper we develop an spectral zeta function regularization procedure on the determinants of instanton fluctuation operators that describe the semi-classical order of tunnel effects between degenerate vacua.
Estimation of the zeta potential and the dielectric constant using velocity measurements in the electroosmotic flows.

PubMed

Park, H M; Hong, S M

2006-12-15

In this paper we develop a method for the determination of the zeta potential zeta and the dielectric constant epsilon by exploiting velocity measurements of the electroosmotic flow in microchannels. The inverse problem is solved through the minimization of a performance function utilizing the conjugate gradient method. The present method is found to estimate zeta and epsilon with reasonable accuracy even with noisy velocity measurements.
Zeta Function Regularization in Casimir Effect Calculations and J. S. DOWKER's Contribution

NASA Astrophysics Data System (ADS)

Elizalde, Emilio

2012-06-01

A summary of relevant contributions, ordered in time, to the subject of operator zeta functions and their application to physical issues is provided. The description ends with the seminal contributions of Stephen Hawking and Stuart Dowker and collaborators, considered by many authors as the actual starting point of the introduction of zeta function regularization methods in theoretical physics, in particular, for quantum vacuum fluctuation and Casimir effect calculations. After recalling a number of the strengths of this powerful and elegant method, some of its limitations are discussed. Finally, recent results of the so-called operator regularization procedure are presented.
Zeta Function Regularization in Casimir Effect Calculations and J. S. Dowker's Contribution

NASA Astrophysics Data System (ADS)

Elizalde, Emilio

2012-07-01

A summary of relevant contributions, ordered in time, to the subject of operator zeta functions and their application to physical issues is provided. The description ends with the seminal contributions of Stephen Hawking and Stuart Dowker and collaborators, considered by many authors as the actual starting point of the introduction of zeta function regularization methods in theoretical physics, in particular, for quantum vacuum fluctuation and Casimir effect calculations. After recalling a number of the strengths of this powerful and elegant method, some of its limitations are discussed. Finally, recent results of the so called operator regularization procedure are presented.
Connecting Archimedean and Non-Archimedean AdS/CFT

NASA Astrophysics Data System (ADS)

Parikh, Sarthak

This thesis develops a non-Archimedean analog of the usual Archimedean anti-de Sitter (AdS)/conformal field theory (CFT) correspondence. AdS space gets replaced by a Bruhat-Tits tree, which is a regular graph with no cycles. The boundary of the Bruhat-Tits tree is described by an unramified extension of the p-adic numbers, which replaces the real valued Euclidean vector space on which the CFT lives. Conformal transformations on the boundary act as linear fractional transformations. In the first part of the thesis, correlation functions are computed in the simple case of massive, interacting scalars in the bulk. They are found to be surprisingly similar to standard holographic correlation functions down to precise numerical coefficients, when expressed in terms of local zeta functions. Along the way, we show that like in the Archimedean case, CFT conformal blocks are dual to geodesic bulk diagrams, which are bulk exchange diagrams with the bulk points of integration restricted to certain geodesics. Other than these intriguing similarities, significant simplifications also arise. Notably, all derivatives disappear from the operator product expansion, and the conformal block decomposition of the four-point function. Finally, a minimal bulk action is constructed on the Bruhat-Tits tree for a single scalar field with nearest neighbor interactions, which reproduces the two-, three-, and four-point functions of the free O(N) model. In the second part, the p-adic O(N) model is studied at the interacting fixed point. Leading order results for the anomalous dimensions of low dimension operators are obtained in two separate regimes: the epsilon-expansion and the large N limit. Remarkably, formulae for anomalous dimensions in the large N limit are valid equally for Archimedean and non-Archimedean field theories, when expressed in terms of local zeta functions. Finally, higher derivative versions of the O(N) model in the Archimedean case are considered, where the general formula for anomalous dimensions obtained earlier is still valid. Analogies with two-derivative theories hint at the existence of some interesting new field theories in four real Euclidean dimensions.
LETTER TO THE EDITOR: Fractal diffusion coefficient from dynamical zeta functions

NASA Astrophysics Data System (ADS)

Cristadoro, Giampaolo

2006-03-01

Dynamical zeta functions provide a powerful method to analyse low-dimensional dynamical systems when the underlying symbolic dynamics is under control. On the other hand, even simple one-dimensional maps can show an intricate structure of the grammar rules that may lead to a non-smooth dependence of global observables on parameters changes. A paradigmatic example is the fractal diffusion coefficient arising in a simple piecewise linear one-dimensional map of the real line. Using the Baladi-Ruelle generalization of the Milnor-Thurnston kneading determinant, we provide the exact dynamical zeta function for such a map and compute the diffusion coefficient from its smallest zero.
Asymptote Misconception on Graphing Functions: Does Graphing Software Resolve It?

ERIC Educational Resources Information Center

Öçal, Mehmet Fatih

2017-01-01

Graphing function is an important issue in mathematics education due to its use in various areas of mathematics and its potential roles for students to enhance learning mathematics. The use of some graphing software assists students' learning during graphing functions. However, the display of graphs of functions that students sketched by hand may…

A Revelation: Quantum-Statistics and Classical-Statistics are Analytic-Geometry Conic-Sections and Numbers/Functions: Euler, Riemann, Bernoulli Generating-Functions: Conics to Numbers/Functions Deep Subtle Connections

NASA Astrophysics Data System (ADS)

Descartes, R.; Rota, G.-C.; Euler, L.; Bernoulli, J. D.; Siegel, Edward Carl-Ludwig

2011-03-01

Quantum-statistics Dichotomy: Fermi-Dirac(FDQS) Versus Bose-Einstein(BEQS), respectively with contact-repulsion/non-condensation(FDCR) versus attraction/ condensationBEC are manifestly-demonstrated by Taylor-expansion ONLY of their denominator exponential, identified BOTH as Descartes analytic-geometry conic-sections, FDQS as Elllipse (homotopy to rectangle FDQS distribution-function), VIA Maxwell-Boltzmann classical-statistics(MBCS) to Parabola MORPHISM, VS. BEQS to Hyperbola, Archimedes' HYPERBOLICITY INEVITABILITY, and as well generating-functions[Abramowitz-Stegun, Handbook Math.-Functions--p. 804!!!], respectively of Euler-numbers/functions, (via Riemann zeta-function(domination of quantum-statistics: [Pathria, Statistical-Mechanics; Huang, Statistical-Mechanics]) VS. Bernoulli-numbers/ functions. Much can be learned about statistical-physics from Euler-numbers/functions via Riemann zeta-function(s) VS. Bernoulli-numbers/functions [Conway-Guy, Book of Numbers] and about Euler-numbers/functions, via Riemann zeta-function(s) MORPHISM, VS. Bernoulli-numbers/ functions, visa versa!!! Ex.: Riemann-hypothesis PHYSICS proof PARTLY as BEQS BEC/BEA!!!
Generalized zeta function representation of groups and 2-dimensional topological Yang-Mills theory: The example of GL(2, #Mathematical Double-Struck Capital F#{sub q}) and PGL(2, #Mathematical Double-Struck Capital F#{sub q})

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roche, Ph., E-mail: philippe.roche@univ-montp2.fr

We recall the relation between zeta function representation of groups and two-dimensional topological Yang-Mills theory through Mednikh formula. We prove various generalisations of Mednikh formulas and define generalization of zeta function representations of groups. We compute some of these functions in the case of the finite group GL(2, #Mathematical Double-Struck Capital F#{sub q}) and PGL(2, #Mathematical Double-Struck Capital F#{sub q}). We recall the table characters of these groups for any q, compute the Frobenius-Schur indicator of their irreducible representations, and give the explicit structure of their fusion rings.
Averages of ratios of the Riemann zeta-function and correlations of divisor sums

NASA Astrophysics Data System (ADS)

Conrey, Brian; Keating, Jonathan P.

2017-10-01

Nonlinearity has published articles containing a significant number-theoretic component since the journal was first established. We examine one thread, concerning the statistics of the zeros of the Riemann zeta function. We extend this by establishing a connection between the ratios conjecture for the Riemann zeta-function and a conjecture concerning correlations of convolutions of Möbius and divisor functions. Specifically, we prove that the ratios conjecture and an arithmetic correlations conjecture imply the same result. This provides new support for the ratios conjecture, which previously had been motivated by analogy with formulae in random matrix theory and by a heuristic recipe. Our main theorem generalises a recent calculation pertaining to the special case of two-over-two ratios.
Group entropies, correlation laws, and zeta functions.

PubMed

Tempesta, Piergiulio

2011-08-01

The notion of group entropy is proposed. It enables the unification and generaliztion of many different definitions of entropy known in the literature, such as those of Boltzmann-Gibbs, Tsallis, Abe, and Kaniadakis. Other entropic functionals are introduced, related to nontrivial correlation laws characterizing universality classes of systems out of equilibrium when the dynamics is weakly chaotic. The associated thermostatistics are discussed. The mathematical structure underlying our construction is that of formal group theory, which provides the general structure of the correlations among particles and dictates the associated entropic functionals. As an example of application, the role of group entropies in information theory is illustrated and generalizations of the Kullback-Leibler divergence are proposed. A new connection between statistical mechanics and zeta functions is established. In particular, Tsallis entropy is related to the classical Riemann zeta function.
In vitro phosphorylation of insulin receptor substrate 1 by protein kinase C-zeta: functional analysis and identification of novel phosphorylation sites.

PubMed

Sommerfeld, Mark R; Metzger, Sabine; Stosik, Magdalene; Tennagels, Norbert; Eckel, Jürgen

2004-05-18

Protein kinase C-zeta (PKC-zeta) participates both in downstream insulin signaling and in the negative feedback control of insulin action. Here we used an in vitro approach to identify PKC-zeta phosphorylation sites within insulin receptor substrate 1 (IRS-1) and to characterize the functional implications. A recombinant IRS-1 fragment (rIRS-1(449)(-)(664)) containing major tyrosine motifs for interaction with phosphatidylinositol (PI) 3-kinase strongly associated to the p85alpha subunit of PI 3-kinase after Tyr phosphorylation by the insulin receptor. Phosphorylation of rIRS-1(449)(-)(664) by PKC-zeta induced a prominent inhibition of this process with a mixture of classical PKC isoforms being less effective. Both PKC-zeta and the classical isoforms phosphorylated rIRS-1(449)(-)(664) on Ser(612). However, modification of this residue did not reduce the affinity of p85alpha binding to pTyr-containing peptides (amino acids 605-615 of rat IRS-1), as determined by surface plasmon resonance. rIRS-1(449)(-)(664) was then phosphorylated by PKC-zeta using [(32)P]ATP and subjected to tryptic phosphopeptide mapping based on two-dimensional HPLC coupled to mass spectrometry. Ser(498) and Ser(570) were identified as novel phosphoserine sites targeted by PKC-zeta. Both sites were additionally confirmed by phosphopeptide mapping of the corresponding Ser --> Ala mutants of rIRS-1(449)(-)(664). Ser(570) was specifically targeted by PKC-zeta, as shown by immunoblotting with a phosphospecific antiserum against Ser(570) of IRS-1. Binding of p85alpha to the S570A mutant was less susceptible to inhibition by PKC-zeta, when compared to the S612A mutant. In conclusion, our in vitro data demonstrate a strong inhibitory action of PKC-zeta at the level of IRS-1/PI 3-kinase interaction involving multiple serine phosphorylation sites. Whereas Ser(612) appears not to participate in the negative control of insulin signaling, Ser(570) may at least partly contribute to this process.
RATGRAPH: Computer Graphing of Rational Functions.

ERIC Educational Resources Information Center

Minch, Bradley A.

1987-01-01

Presents an easy-to-use Applesoft BASIC program that graphs rational functions and any asymptotes that the functions might have. Discusses the nature of rational functions, graphing them manually, employing a computer to graph rational functions, and describes how the program works. (TW)
Zeta functions on tori using contour integration

NASA Astrophysics Data System (ADS)

Elizalde, Emilio; Kirsten, Klaus; Robles, Nicolas; Williams, Floyd

2015-12-01

A new, seemingly useful presentation of zeta functions on complex tori is derived by using contour integration. It is shown to agree with the one obtained by using the Chowla-Selberg series formula, for which an alternative proof is thereby given. In addition, a new proof of the functional determinant on the torus results, which does not use the Kronecker first limit formula nor the functional equation of the non-holomorphic Eisenstein series. As a bonus, several identities involving the Dedekind eta function are obtained as well.
Computational strategies for the Riemann zeta function

NASA Astrophysics Data System (ADS)

Borwein, Jonathan M.; Bradley, David M.; Crandall, Richard E.

2000-09-01

We provide a compendium of evaluation methods for the Riemann zeta function, presenting formulae ranging from historical attempts to recently found convergent series to curious oddities old and new. We concentrate primarily on practical computational issues, such issues depending on the domain of the argument, the desired speed of computation, and the incidence of what we call "value recycling".
On small values of the Riemann zeta-function at Gram points

DOE Office of Scientific and Technical Information (OSTI.GOV)

Korolev, M A

In this paper, we prove the existence of a large set of Gram points t{sub n} such that the values ζ(0.5+it{sub n}) are 'anomalously' close to zero. A lower bound for the negative 'discrete' moment of the Riemann zeta-function on the critical line is also given. Bibliography: 13 titles.
Proving relations between modular graph functions

NASA Astrophysics Data System (ADS)

Basu, Anirban

2016-12-01

We consider modular graph functions that arise in the low energy expansion of the four graviton amplitude in type II string theory. The vertices of these graphs are the positions of insertions of vertex operators on the toroidal worldsheet, while the links are the scalar Green functions connecting the vertices. Graphs with four and five links satisfy several non-trivial relations, which have been proved recently. We prove these relations by using elementary properties of Green functions and the details of the graphs. We also prove a relation between modular graph functions with six links.
What energy functions can be minimized via graph cuts?

PubMed

Kolmogorov, Vladimir; Zabih, Ramin

2004-02-01

In the last few years, several new algorithms based on graph cuts have been developed to solve energy minimization problems in computer vision. Each of these techniques constructs a graph such that the minimum cut on the graph also minimizes the energy. Yet, because these graph constructions are complex and highly specific to a particular energy function, graph cuts have seen limited application to date. In this paper, we give a characterization of the energy functions that can be minimized by graph cuts. Our results are restricted to functions of binary variables. However, our work generalizes many previous constructions and is easily applicable to vision problems that involve large numbers of labels, such as stereo, motion, image restoration, and scene reconstruction. We give a precise characterization of what energy functions can be minimized using graph cuts, among the energy functions that can be written as a sum of terms containing three or fewer binary variables. We also provide a general-purpose construction to minimize such an energy function. Finally, we give a necessary condition for any energy function of binary variables to be minimized by graph cuts. Researchers who are considering the use of graph cuts to optimize a particular energy function can use our results to determine if this is possible and then follow our construction to create the appropriate graph. A software implementation is freely available.
A gene variation of 14-3-3 zeta isoform in rat hippocampus.

PubMed

Murakami, K; Situ, S Y; Eshete, F

1996-11-14

A variant form of 14-3-3 zeta was isolated from the rat hippocampal cDNA library. The cloned cDNA is 1687 bp in length and it contains an entire ORF (nt = 63-797) with 245 amino acids that is characteristic to 14-3-3 zeta subtype. By comparing with reported sequences of 14-3-3 zeta, we found three nucleotide substitutions within the coding sequence in our clone; C<-->T transition at nt = 325 and G<-->C transversions at nt = 387 and 388. Both are missense mutations, leading ACG (Thr) to ATG (Met) and CGT (Arg) to GCT (Ala) conversions at residue 88 and 109, respectively. Our results show that at least three different genetic variants of 14-3-3 zeta are present in rat species which results in protein variations. Such mutation in the amino acid sequence is an important indication of the diverse functions of this protein and may also contribute to the recent contradictory observations regarding the role of the 14-3-3 zeta subtype.
Functional Role of Tyr12 in the Catalytic Activity of Novel Zeta-like Glutathione S-transferase from Acidovorax sp. KKS102.

PubMed

Shehu, Dayyabu; Alias, Zazali

2018-05-19

Glutathione S-transferases (GSTs) are a family of enzymes that function in the detoxification of variety of electrophilic substrates. In the present work, we report a novel zeta-like GST (designated as KKSG9) from the biphenyl/polychlorobiphenyl degrading organism Acidovorax sp. KKS102. KKSG9 possessed low sequence similarity but similar biochemical properties to zeta class GSTs. Functional analysis showed that the enzyme exhibits wider substrate specificity compared to most zeta class GSTs by reacting with 1-chloro-2,4-dinitrobenzene (CDNB), p-nitrobenzyl chloride (NBC), ethacrynic acid (EA), hydrogen peroxide, and cumene hydroperoxide. The enzyme also displayed dehalogenation function against dichloroacetate, permethrin, and dieldrin. The functional role of Tyr12 was also investigated by site-directed mutagenesis. The mutant (Y12C) displayed low catalytic activity and dehalogenation function against all the substrates when compared with the wild type. Kinetic analysis using NBC and GSH as substrates showed that the mutant (Y12C) displayed a higher affinity for NBC when compared with the wild type, however, no significant change in GSH affinity was observed. These findings suggest that the presence of tyrosine residue in the motif might represent an evolutionary trend toward improving the catalytic activity of the enzyme. The enzyme as well could be useful in the bioremediation of various types of organochlorine pollutants.
Further summation formulae related to generalized harmonic numbers

NASA Astrophysics Data System (ADS)

Zheng, De-Yin

2007-11-01

By employing the univariate series expansion of classical hypergeometric series formulae, Shen [L.-C. Shen, Remarks on some integrals and series involving the Stirling numbers and [zeta](n), Trans. Amer. Math. Soc. 347 (1995) 1391-1399] and Choi and Srivastava [J. Choi, H.M. Srivastava, Certain classes of infinite series, Monatsh. Math. 127 (1999) 15-25; J. Choi, H.M. Srivastava, Explicit evaluation of Euler and related sums, Ramanujan J. 10 (2005) 51-70] investigated the evaluation of infinite series related to generalized harmonic numbers. More summation formulae have systematically been derived by Chu [W. Chu, Hypergeometric series and the Riemann Zeta function, Acta Arith. 82 (1997) 103-118], who developed fully this approach to the multivariate case. The present paper will explore the hypergeometric series method further and establish numerous summation formulae expressing infinite series related to generalized harmonic numbers in terms of the Riemann Zeta function [zeta](m) with m=5,6,7, including several known ones as examples.
Functional network organization of the human brain

PubMed Central

Power, Jonathan D; Cohen, Alexander L; Nelson, Steven M; Wig, Gagan S; Barnes, Kelly Anne; Church, Jessica A; Vogel, Alecia C; Laumann, Timothy O; Miezin, Fran M; Schlaggar, Bradley L; Petersen, Steven E

2011-01-01

Summary Real-world complex systems may be mathematically modeled as graphs, revealing properties of the system. Here we study graphs of functional brain organization in healthy adults using resting state functional connectivity MRI. We propose two novel brain-wide graphs, one of 264 putative functional areas, the other a modification of voxelwise networks that eliminates potentially artificial short-distance relationships. These graphs contain many subgraphs in good agreement with known functional brain systems. Other subgraphs lack established functional identities; we suggest possible functional characteristics for these subgraphs. Further, graph measures of the areal network indicate that the default mode subgraph shares network properties with sensory and motor subgraphs: it is internally integrated but isolated from other subgraphs, much like a “processing” system. The modified voxelwise graph also reveals spatial motifs in the patterning of systems across the cortex. PMID:22099467
An MBO Scheme for Minimizing the Graph Ohta-Kawasaki Functional

NASA Astrophysics Data System (ADS)

van Gennip, Yves

2018-06-01

We study a graph-based version of the Ohta-Kawasaki functional, which was originally introduced in a continuum setting to model pattern formation in diblock copolymer melts and has been studied extensively as a paradigmatic example of a variational model for pattern formation. Graph-based problems inspired by partial differential equations (PDEs) and variational methods have been the subject of many recent papers in the mathematical literature, because of their applications in areas such as image processing and data classification. This paper extends the area of PDE inspired graph-based problems to pattern-forming models, while continuing in the tradition of recent papers in the field. We introduce a mass conserving Merriman-Bence-Osher (MBO) scheme for minimizing the graph Ohta-Kawasaki functional with a mass constraint. We present three main results: (1) the Lyapunov functionals associated with this MBO scheme Γ -converge to the Ohta-Kawasaki functional (which includes the standard graph-based MBO scheme and total variation as a special case); (2) there is a class of graphs on which the Ohta-Kawasaki MBO scheme corresponds to a standard MBO scheme on a transformed graph and for which generalized comparison principles hold; (3) this MBO scheme allows for the numerical computation of (approximate) minimizers of the graph Ohta-Kawasaki functional with a mass constraint.
Mathematical Minute: Rotating a Function Graph

ERIC Educational Resources Information Center

Bravo, Daniel; Fera, Joseph

2013-01-01

Using calculus only, we find the angles you can rotate the graph of a differentiable function about the origin and still obtain a function graph. We then apply the solution to odd and even degree polynomials.
Spreadsheet Works: Graphing Functions on a Spreadsheet.

ERIC Educational Resources Information Center

Ramamurthi, V. S.

1989-01-01

Explains graphing functions when using LOTUS 1-2-3. Provides examples and explains keystroke entries needed to make the graphs. Notes up to six functions can be displayed on the same set of axes. (MVL)
Layer-by-layer assembly of graphene oxide on thermosensitive liposomes for photo-chemotherapy.

PubMed

Hashemi, Mohadeseh; Omidi, Meisam; Muralidharan, Bharadwaj; Tayebi, Lobat; Herpin, Matthew J; Mohagheghi, Mohammad Ali; Mohammadi, Javad; Smyth, Hugh D C; Milner, Thomas E

2018-01-01

Stimuli responsive polyelectrolyte nanoparticles have been developed for chemo-photothermal destruction of breast cancer cells. This novel system, called layer by layer Lipo-graph (LBL Lipo-graph), is composed of alternate layers of graphene oxide (GO) and graphene oxide conjugated poly (l-lysine) (GO-PLL) deposited on cationic liposomes encapsulating doxorubicin. Various concentrations of GO and GO-PLL were examined and the optimal LBL Lipo-graph was found to have a particle size of 267.9 ± 13 nm, zeta potential of +43.9 ± 6.9 mV and encapsulation efficiency of 86.4 ± 4.7%. The morphology of LBL Lipo-graph was examined by cryogenic-transmission electron microscopy (Cryo-TEM), atomic force microcopy (AFM) and scanning electron microscopy (SEM). The buildup of LBL Lipo-graph was confirmed via ultraviolet-visible (UV-Vis) spectrophotometry, thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) analysis. Infra-red (IR) response suggests that four layers are sufficient to induce a gel-to-liquid phase transition in response to near infra-red (NIR) laser irradiation. Light-matter interaction of LBL Lipo-graph was studied by calculating the absorption cross section in the frequency domain by utilizing Fourier analysis. Drug release assay indicates that the LBL Lipo-graph releases much faster in an acidic environment than a liposome control. A cytotoxicity assay was conducted to prove the efficacy of LBL Lipo-graph to destroy MD-MB-231 cells in response to NIR laser emission. Also, image stream flow cytometry and two photon microcopy provide supportive data for the potential application of LBL Lipo-graph for photothermal therapy. Study results suggest the novel dual-sensitive nanoparticles allow intracellular doxorubin delivery and respond to either acidic environments or NIR excitation. Stimuli sensitive hybrid nanoparticles have been synthesized using a layer-by-layer technique and demonstrated for dual chemo-photothermal destruction of breast cancer cells. The hybrid nanoparticles are composed of alternating layers of graphene oxide and graphene oxide conjugated poly-l-lysine coating the surface of a thermosensitive cationic liposome containing doxorubicin as a core. Data suggests that the hybrid nanoparticles may offer many advantages for chemo-photothermal therapy. Advantages include a decrease of the initial burst release which may result in the reduction in systemic toxicity, increase in pH responsivity around the tumor environment and improved NIR light absorption. Copyright © 2017 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.
A new gene deletion in the alpha-like globin gene cluster as the molecular basis for the rare alpha-thalassemia-1(--/alpha alpha) in blacks: HbH disease in sickle cell trait.

PubMed

Steinberg, M H; Coleman, M B; Adams, J G; Hartmann, R C; Saba, H; Anagnou, N P

1986-02-01

A novel deletion of at least 26 kilobase of DNA, including both alpha-globin genes, the psi alpha- and psi zeta-globin genes, but sparing the functional zeta-gene was found in a 10-year-old black boy with HbH disease and sickle cell trait. This particular deletion has not previously been described in blacks. Its existence makes it likely that the absence of Hb Barts hydrops fetalis in blacks is due to the rarity of the chromosome lacking two alpha-globin genes rather than a result of early embryonic death due to the failure to synthesize embryonic hemoglobins because of deletion of functional zeta-globin genes.

High quality Gaussian basis sets for fourth-row atoms

NASA Technical Reports Server (NTRS)

Partridge, Harry; Faegri, Knut, Jr.

1992-01-01

Energy optimized Gaussian basis sets of triple-zeta quality for the atoms Rb-Xe have been derived. Two series of basis sets are developed: (24s 16p 10d) and (26s 16p 10d) sets which were expanded to 13d and 19p functions as the 4d and 5p shells become occupied. For the atoms lighter than Cd, the (24s 16p 10d) sets with triple-zeta valence distributions are higher in energy than the corresponding double-zeta distribution. To ensure a triple-zeta distribution and a global energy minimum, the (26s 16p 10d) sets were derived. Total atomic energies from the largest basis sets are between 198 and 284 (mu)E(sub H) above the numerical Hartree-Fock energies.
Function plot response: A scalable system for teaching kinematics graphs

NASA Astrophysics Data System (ADS)

Laverty, James; Kortemeyer, Gerd

2012-08-01

Understanding and interpreting graphs are essential skills in all sciences. While students are mostly proficient in plotting given functions and reading values off graphs, they frequently lack the ability to construct and interpret graphs in a meaningful way. Students can use graphs as representations of value pairs, but often fail to interpret them as the representation of functions, and mostly fail to use them as representations of physical reality. Working with graphs in classroom settings has been shown to improve student abilities with graphs, particularly when the students can interact with them. We introduce a novel problem type in an online homework system, which requires students to construct the graphs themselves in free form, and requires no hand-grading by instructors. Initial experiences using the new problem type in an introductory physics course are reported.
Spectral fluctuations of quantum graphs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pluhař, Z.; Weidenmüller, H. A.

We prove the Bohigas-Giannoni-Schmit conjecture in its most general form for completely connected simple graphs with incommensurate bond lengths. We show that for graphs that are classically mixing (i.e., graphs for which the spectrum of the classical Perron-Frobenius operator possesses a finite gap), the generating functions for all (P,Q) correlation functions for both closed and open graphs coincide (in the limit of infinite graph size) with the corresponding expressions of random-matrix theory, both for orthogonal and for unitary symmetry.
Two Dimensional Dendritic Crystal Growth for Weak Undercooling

NASA Technical Reports Server (NTRS)

Tanveer, S.; Kunka, M. D.; Foster, M. R.

1999-01-01

We discuss the framework and issues brought forth in the recent work of Kunka, Foster & Tanveer, which incorporates small but nonzero surface energy effects in the nonlinear dynamics of a conformal mapping function z(zeta,t) that maps the upper-half zeta plane into the exterior of a dendrite. In this paper, surface energy effects on the singularities of z(zeta,t) in the lower-half plane were examined, as they move toward the real axis from below. In particular, the dynamics of complex singularities manifests itself in predictions on nature and growth rate of disturbances, as well as of coarsening.
Can one hear the Riemann zeros in black hole ringing?

NASA Astrophysics Data System (ADS)

Aros, Rodrigo; Bugini, Fabrizzio; Diaz, Danilo E.

2016-05-01

We elaborate on an entry of the AdS/CFT dictionary relating functional determinants: the determinant of the one-loop contribution to the effective gravitational action by bulk scalars in an asymptotically locally AdS background X, and the determinant of the two-point function of the dual operator (a.k.a. scattering matrix) at the conformal boundary M. The formula originates from AdS/CFT heuristics that map a quantum contribution in the bulk gravitational partition function to a subleading large-N contribution in the boundary CFT partition function: The formula applies to quotients of AdS as well [1]. In the particular case of the BTZ black hole, a closed expression can be worked out in terms of an associated Patterson-Selberg zeta function ZBTZ (λ) [2]. The determinants can then be thought of as regularized products of either zeta zeros, scattering resonances or quasinormal frequencies [3]. In this sense, one could say that the zeros of ZBTZ (λ) can be heard in the spectrum of quasinormal modes of the BTZ black hole. The question we want to pose is whether a similar situation might exist for the celebrated zeros of the Riemann zeta function.
Analysis of graphic representation ability in oscillation phenomena

NASA Astrophysics Data System (ADS)

Dewi, A. R. C.; Putra, N. M. D.; Susilo

2018-03-01

This study aims to investigates how the ability of students to representation graphs of linear function and harmonic function in understanding of oscillation phenomena. Method of this research used mix methods with concurrent embedded design. The subjects were 35 students of class X MIA 3 SMA 1 Bae Kudus. Data collection through giving essays and interviews that lead to the ability to read and draw graphs in material of Hooke's law and oscillation characteristics. The results of study showed that most of the students had difficulty in drawing graph of linear function and harmonic function of deviation with time. Students’ difficulties in drawing the graph of linear function is the difficulty of analyzing the variable data needed in graph making, confusing the placement of variable data on the coordinate axis, the difficulty of determining the scale interval on each coordinate, and the variation of how to connect the dots forming the graph. Students’ difficulties in representing the graph of harmonic function is to determine the time interval of sine harmonic function, the difficulty to determine the initial deviation point of the drawing, the difficulty of finding the deviation equation of the case of oscillation characteristics and the confusion to different among the maximum deviation (amplitude) with the length of the spring caused the load.Complexity of the characteristic attributes of the oscillation phenomena graphs, students tend to show less well the ability of graphical representation of harmonic functions than the performance of the graphical representation of linear functions.
Graph wavelet alignment kernels for drug virtual screening.

PubMed

Smalter, Aaron; Huan, Jun; Lushington, Gerald

2009-06-01

In this paper, we introduce a novel statistical modeling technique for target property prediction, with applications to virtual screening and drug design. In our method, we use graphs to model chemical structures and apply a wavelet analysis of graphs to summarize features capturing graph local topology. We design a novel graph kernel function to utilize the topology features to build predictive models for chemicals via Support Vector Machine classifier. We call the new graph kernel a graph wavelet-alignment kernel. We have evaluated the efficacy of the wavelet-alignment kernel using a set of chemical structure-activity prediction benchmarks. Our results indicate that the use of the kernel function yields performance profiles comparable to, and sometimes exceeding that of the existing state-of-the-art chemical classification approaches. In addition, our results also show that the use of wavelet functions significantly decreases the computational costs for graph kernel computation with more than ten fold speedup.
Tutte polynomial in functional magnetic resonance imaging

NASA Astrophysics Data System (ADS)

García-Castillón, Marlly V.

2015-09-01

Methods of graph theory are applied to the processing of functional magnetic resonance images. Specifically the Tutte polynomial is used to analyze such kind of images. Functional Magnetic Resonance Imaging provide us connectivity networks in the brain which are represented by graphs and the Tutte polynomial will be applied. The problem of computing the Tutte polynomial for a given graph is #P-hard even for planar graphs. For a practical application the maple packages "GraphTheory" and "SpecialGraphs" will be used. We will consider certain diagram which is depicting functional connectivity, specifically between frontal and posterior areas, in autism during an inferential text comprehension task. The Tutte polynomial for the resulting neural networks will be computed and some numerical invariants for such network will be obtained. Our results show that the Tutte polynomial is a powerful tool to analyze and characterize the networks obtained from functional magnetic resonance imaging.
Signal Processing for Time-Series Functions on a Graph

DTIC Science & Technology

2018-02-01

as filtering to functions supported on graphs. These methods can be applied to scalar functions with a domain that can be described by a fixed...classical signal processing such as filtering to account for the graph domain. This work essentially divides into 2 basic approaches: graph Laplcian...based filtering and weighted adjacency matrix-based filtering . In Shuman et al.,11 and elaborated in Bronstein et al.,13 filtering operators are
G-Hash: Towards Fast Kernel-based Similarity Search in Large Graph Databases.

PubMed

Wang, Xiaohong; Smalter, Aaron; Huan, Jun; Lushington, Gerald H

2009-01-01

Structured data including sets, sequences, trees and graphs, pose significant challenges to fundamental aspects of data management such as efficient storage, indexing, and similarity search. With the fast accumulation of graph databases, similarity search in graph databases has emerged as an important research topic. Graph similarity search has applications in a wide range of domains including cheminformatics, bioinformatics, sensor network management, social network management, and XML documents, among others.Most of the current graph indexing methods focus on subgraph query processing, i.e. determining the set of database graphs that contains the query graph and hence do not directly support similarity search. In data mining and machine learning, various graph kernel functions have been designed to capture the intrinsic similarity of graphs. Though successful in constructing accurate predictive and classification models for supervised learning, graph kernel functions have (i) high computational complexity and (ii) non-trivial difficulty to be indexed in a graph database.Our objective is to bridge graph kernel function and similarity search in graph databases by proposing (i) a novel kernel-based similarity measurement and (ii) an efficient indexing structure for graph data management. Our method of similarity measurement builds upon local features extracted from each node and their neighboring nodes in graphs. A hash table is utilized to support efficient storage and fast search of the extracted local features. Using the hash table, a graph kernel function is defined to capture the intrinsic similarity of graphs and for fast similarity query processing. We have implemented our method, which we have named G-hash, and have demonstrated its utility on large chemical graph databases. Our results show that the G-hash method achieves state-of-the-art performance for k-nearest neighbor (k-NN) classification. Most importantly, the new similarity measurement and the index structure is scalable to large database with smaller indexing size, faster indexing construction time, and faster query processing time as compared to state-of-the-art indexing methods such as C-tree, gIndex, and GraphGrep.
A novel mechanism of programmed cell death in bacteria by toxin-antitoxin systems corrupts peptidoglycan synthesis.

PubMed

Mutschler, Hannes; Gebhardt, Maike; Shoeman, Robert L; Meinhart, Anton

2011-03-01

Most genomes of bacteria contain toxin-antitoxin (TA) systems. These gene systems encode a toxic protein and its cognate antitoxin. Upon antitoxin degradation, the toxin induces cell stasis or death. TA systems have been linked with numerous functions, including growth modulation, genome maintenance, and stress response. Members of the epsilon/zeta TA family are found throughout the genomes of pathogenic bacteria and were shown not only to stabilize resistance plasmids but also to promote virulence. The broad distribution of epsilon/zeta systems implies that zeta toxins utilize a ubiquitous bacteriotoxic mechanism. However, whereas all other TA families known to date poison macromolecules involved in translation or replication, the target of zeta toxins remained inscrutable. We used in vivo techniques such as microscropy and permeability assays to show that pneumococcal zeta toxin PezT impairs cell wall synthesis and triggers autolysis in Escherichia coli. Subsequently, we demonstrated in vitro that zeta toxins in general phosphorylate the ubiquitous peptidoglycan precursor uridine diphosphate-N-acetylglucosamine (UNAG) and that this activity is counteracted by binding of antitoxin. After identification of the product we verified the kinase activity in vivo by analyzing metabolite extracts of cells poisoned by PezT using high pressure liquid chromatograpy (HPLC). We further show that phosphorylated UNAG inhibitis MurA, the enzyme catalyzing the initial step in bacterial peptidoglycan biosynthesis. Additionally, we provide what is to our knowledge the first crystal structure of a zeta toxin bound to its substrate. We show that zeta toxins are novel kinases that poison bacteria through global inhibition of peptidoglycan synthesis. This provides a fundamental understanding of how epsilon/zeta TA systems stabilize mobile genetic elements. Additionally, our results imply a mechanism that connects activity of zeta toxin PezT to virulence of pneumococcal infections. Finally, we discuss how phosphorylated UNAG likely poisons additional pathways of bacterial cell wall synthesis, making it an attractive lead compound for development of new antibiotics.
Output-Sensitive Construction of Reeb Graphs.

PubMed

Doraiswamy, H; Natarajan, V

2012-01-01

The Reeb graph of a scalar function represents the evolution of the topology of its level sets. This paper describes a near-optimal output-sensitive algorithm for computing the Reeb graph of scalar functions defined over manifolds or non-manifolds in any dimension. Key to the simplicity and efficiency of the algorithm is an alternate definition of the Reeb graph that considers equivalence classes of level sets instead of individual level sets. The algorithm works in two steps. The first step locates all critical points of the function in the domain. Critical points correspond to nodes in the Reeb graph. Arcs connecting the nodes are computed in the second step by a simple search procedure that works on a small subset of the domain that corresponds to a pair of critical points. The paper also describes a scheme for controlled simplification of the Reeb graph and two different graph layout schemes that help in the effective presentation of Reeb graphs for visual analysis of scalar fields. Finally, the Reeb graph is employed in four different applications-surface segmentation, spatially-aware transfer function design, visualization of interval volumes, and interactive exploration of time-varying data.
Singular perturbations with boundary conditions and the Casimir effect in the half space

NASA Astrophysics Data System (ADS)

Albeverio, S.; Cognola, G.; Spreafico, M.; Zerbini, S.

2010-06-01

We study the self-adjoint extensions of a class of nonmaximal multiplication operators with boundary conditions. We show that these extensions correspond to singular rank 1 perturbations (in the sense of Albeverio and Kurasov [Singular Perturbations of Differential Operaters (Cambridge University Press, Cambridge, 2000)]) of the Laplace operator, namely, the formal Laplacian with a singular delta potential, on the half space. This construction is the appropriate setting to describe the Casimir effect related to a massless scalar field in the flat space-time with an infinite conducting plate and in the presence of a pointlike "impurity." We use the relative zeta determinant (as defined in the works of Müller ["Relative zeta functions, relative determinants and scattering theory," Commun. Math. Phys. 192, 309 (1998)] and Spreafico and Zerbini ["Finite temperature quantum field theory on noncompact domains and application to delta interactions," Rep. Math. Phys. 63, 163 (2009)]) in order to regularize the partition function of this model. We study the analytic extension of the associated relative zeta function, and we present explicit results for the partition function and for the Casimir force.
Large-scale DCMs for resting-state fMRI.

PubMed

Razi, Adeel; Seghier, Mohamed L; Zhou, Yuan; McColgan, Peter; Zeidman, Peter; Park, Hae-Jeong; Sporns, Olaf; Rees, Geraint; Friston, Karl J

2017-01-01

This paper considers the identification of large directed graphs for resting-state brain networks based on biophysical models of distributed neuronal activity, that is, effective connectivity . This identification can be contrasted with functional connectivity methods based on symmetric correlations that are ubiquitous in resting-state functional MRI (fMRI). We use spectral dynamic causal modeling (DCM) to invert large graphs comprising dozens of nodes or regions. The ensuing graphs are directed and weighted, hence providing a neurobiologically plausible characterization of connectivity in terms of excitatory and inhibitory coupling. Furthermore, we show that the use of to discover the most likely sparse graph (or model) from a parent (e.g., fully connected) graph eschews the arbitrary thresholding often applied to large symmetric (functional connectivity) graphs. Using empirical fMRI data, we show that spectral DCM furnishes connectivity estimates on large graphs that correlate strongly with the estimates provided by stochastic DCM. Furthermore, we increase the efficiency of model inversion using functional connectivity modes to place prior constraints on effective connectivity. In other words, we use a small number of modes to finesse the potentially redundant parameterization of large DCMs. We show that spectral DCM-with functional connectivity priors-is ideally suited for directed graph theoretic analyses of resting-state fMRI. We envision that directed graphs will prove useful in understanding the psychopathology and pathophysiology of neurodegenerative and neurodevelopmental disorders. We will demonstrate the utility of large directed graphs in clinical populations in subsequent reports, using the procedures described in this paper.
Graphs in kinematics—a need for adherence to principles of algebraic functions

NASA Astrophysics Data System (ADS)

Sokolowski, Andrzej

2017-11-01

Graphs in physics are central to the analysis of phenomena and to learning about a system’s behavior. The ways students handle graphs are frequently researched. Students’ misconceptions are highlighted, and methods of improvement suggested. While kinematics graphs are to represent a real motion, they are also algebraic entities that must satisfy conditions for being algebraic functions. To be algebraic functions, they must pass certain tests before they can be used to infer more about motion. A preliminary survey of some physics resources has revealed that little attention is paid to verifying if the position, velocity and acceleration versus time graphs, that are to depict real motion, satisfy the most critical condition for being an algebraic function; the vertical line test. The lack of attention to this adherence shows as vertical segments in piecewise graphs. Such graphs generate unrealistic interpretations and may confuse students. A group of 25 college physics students was provided with such a graph and asked to analyse its adherence to reality. The majority of the students (N = 16, 64%) questioned the graph’s validity. It is inferred that such graphs might not only jeopardize the function principles studied in mathematics but also undermine the purpose of studying these principles. The aim of this study was to bring this idea forth and suggest a better alignment of physics and mathematics methods.
A Qualitative Approach to Sketch the Graph of a Function.

ERIC Educational Resources Information Center

Alson, Pedro

1992-01-01

Presents a qualitative and global method of graphing functions that involves transformations of the graph of a known function in the cartesian coordinate system referred to as graphic operators. Explains how the method has been taught to students and some comments about the results obtained. (MDH)
Asymptotic analysis on a pseudo-Hermitian Riemann-zeta Hamiltonian

NASA Astrophysics Data System (ADS)

Bender, Carl M.; Brody, Dorje C.

2018-04-01

The differential-equation eigenvalue problem associated with a recently-introduced Hamiltonian, whose eigenvalues correspond to the zeros of the Riemann zeta function, is analyzed using Fourier and WKB analysis. The Fourier analysis leads to a challenging open problem concerning the formulation of the eigenvalue problem in the momentum space. The WKB analysis gives the exact asymptotic behavior of the eigenfunction.
Zeta-potential Analyses using Micro Electrical Field Flow Fractionation with Fluorescent Nanoparticles

PubMed Central

Chang, Moon-Hwan; Dosev, Dosi; Kennedy, Ian M.

2007-01-01

Increasingly growing application of nanoparticles in biotechnology requires fast and accessible tools for their manipulation and for characterization of their colloidal properties. In this work we determine the zeta-potentials for polystyrene nanoparticles using micro electrical field flow fractionation (μ–EFFF) which is an efficient method for sorting of particles by size. The data obtained by μ–EFFF were compared to zeta potentials determined by standard capillary electrophoresis. For proof of concept, we used polystyrene nanoparticles of two different sizes, impregnated with two different fluorescent dyes. Fluorescent emission spectra were used to evaluate the particle separation in both systems. Using the theory of electrophoresis, we estimated the zeta-potentials as a function of size, dielectric permittivity, viscosity and electrophoretic mobility. The results obtained by the μ–EFFF technique were confirmed by the conventional capillary electrophoresis measurements. These results demonstrate the applicability of the μ–EFFF method not only for particle size separation but also as a simple and inexpensive tool for measurements of nanoparticles zeta potentials. PMID:18542710
Hydrodynamic dispersion in a combined magnetohydrodynamic- electroosmotic-driven flow through a microchannel with slowly varying wall zeta potentials

NASA Astrophysics Data System (ADS)

Vargas, C.; Arcos, J.; Bautista, O.; Méndez, F.

2017-09-01

The effective dispersion coefficient of a neutral solute in the combined electroosmotic (EO) and magnetohydrodynamic (MHD)-driven flow of a Newtonian fluid through a parallel flat plate microchannel is studied. The walls of the microchannel are assumed to have modulated and low zeta potentials that vary slowly in the axial direction in a sinusoidal manner. The flow field required to obtain the dispersion coefficient is solved using the lubrication approximation theory. The solution of the electrical potential is based on the Debye-Hückel approximation for a symmetric (Z :Z ) electrolyte solution. The EO and MHD effects, together with the variations in the zeta potentials of the walls, are observed to notably modify the axial distribution of the effective dispersion coefficient. The problem is formulated for two cases of the zeta potential function. Note that the dispersion coefficient primarily depends on the Hartmann number, on the ratio of the half height of the microchannel to the Debye length, and on the assumed variation in the zeta potentials of the walls.
The H0 function, a new index for detecting structural/topological complexity information in undirected graphs

NASA Astrophysics Data System (ADS)

Buscema, Massimo; Asadi-Zeydabadi, Masoud; Lodwick, Weldon; Breda, Marco

2016-04-01

Significant applications such as the analysis of Alzheimer's disease differentiated from dementia, or in data mining of social media, or in extracting information of drug cartel structural composition, are often modeled as graphs. The structural or topological complexity or lack of it in a graph is quite often useful in understanding and more importantly, resolving the problem. We are proposing a new index we call the H0function to measure the structural/topological complexity of a graph. To do this, we introduce the concept of graph pruning and its associated algorithm that is used in the development of our measure. We illustrate the behavior of our measure, the H0 function, through different examples found in the appendix. These examples indicate that the H0 function contains information that is useful and important characteristics of a graph. Here, we restrict ourselves to undirected.

Effects of image charges, interfacial charge discreteness, and surface roughness on the zeta potential of spherical electric double layers.

PubMed

Gan, Zecheng; Xing, Xiangjun; Xu, Zhenli

2012-07-21

We investigate the effects of image charges, interfacial charge discreteness, and surface roughness on spherical electric double layer structures in electrolyte solutions with divalent counterions in the setting of the primitive model. By using Monte Carlo simulations and the image charge method, the zeta potential profile and the integrated charge distribution function are computed for varying surface charge strengths and salt concentrations. Systematic comparisons were carried out between three distinct models for interfacial charges: (1) SURF1 with uniform surface charges, (2) SURF2 with discrete point charges on the interface, and (3) SURF3 with discrete interfacial charges and finite excluded volume. By comparing the integrated charge distribution function and the zeta potential profile, we argue that the potential at the distance of one ion diameter from the macroion surface is a suitable location to define the zeta potential. In SURF2 model, we find that image charge effects strongly enhance charge inversion for monovalent interfacial charges, and strongly suppress charge inversion for multivalent interfacial charges. For SURF3, the image charge effect becomes much smaller. Finally, with image charges in action, we find that excluded volumes (in SURF3) suppress charge inversion for monovalent interfacial charges and enhance charge inversion for multivalent interfacial charges. Overall, our results demonstrate that all these aspects, i.e., image charges, interfacial charge discreteness, their excluding volumes, have significant impacts on zeta potentials of electric double layers.
Time-dependence of graph theory metrics in functional connectivity analysis

PubMed Central

Chiang, Sharon; Cassese, Alberto; Guindani, Michele; Vannucci, Marina; Yeh, Hsiang J.; Haneef, Zulfi; Stern, John M.

2016-01-01

Brain graphs provide a useful way to computationally model the network structure of the connectome, and this has led to increasing interest in the use of graph theory to quantitate and investigate the topological characteristics of the healthy brain and brain disorders on the network level. The majority of graph theory investigations of functional connectivity have relied on the assumption of temporal stationarity. However, recent evidence increasingly suggests that functional connectivity fluctuates over the length of the scan. In this study, we investigate the stationarity of brain network topology using a Bayesian hidden Markov model (HMM) approach that estimates the dynamic structure of graph theoretical measures of whole-brain functional connectivity. In addition to extracting the stationary distribution and transition probabilities of commonly employed graph theory measures, we propose two estimators of temporal stationarity: the S-index and N-index. These indexes can be used to quantify different aspects of the temporal stationarity of graph theory measures. We apply the method and proposed estimators to resting-state functional MRI data from healthy controls and patients with temporal lobe epilepsy. Our analysis shows that several graph theory measures, including small-world index, global integration measures, and betweenness centrality, may exhibit greater stationarity over time and therefore be more robust. Additionally, we demonstrate that accounting for subject-level differences in the level of temporal stationarity of network topology may increase discriminatory power in discriminating between disease states. Our results confirm and extend findings from other studies regarding the dynamic nature of functional connectivity, and suggest that using statistical models which explicitly account for the dynamic nature of functional connectivity in graph theory analyses may improve the sensitivity of investigations and consistency across investigations. PMID:26518632
Time-dependence of graph theory metrics in functional connectivity analysis.

PubMed

Chiang, Sharon; Cassese, Alberto; Guindani, Michele; Vannucci, Marina; Yeh, Hsiang J; Haneef, Zulfi; Stern, John M

2016-01-15

Brain graphs provide a useful way to computationally model the network structure of the connectome, and this has led to increasing interest in the use of graph theory to quantitate and investigate the topological characteristics of the healthy brain and brain disorders on the network level. The majority of graph theory investigations of functional connectivity have relied on the assumption of temporal stationarity. However, recent evidence increasingly suggests that functional connectivity fluctuates over the length of the scan. In this study, we investigate the stationarity of brain network topology using a Bayesian hidden Markov model (HMM) approach that estimates the dynamic structure of graph theoretical measures of whole-brain functional connectivity. In addition to extracting the stationary distribution and transition probabilities of commonly employed graph theory measures, we propose two estimators of temporal stationarity: the S-index and N-index. These indexes can be used to quantify different aspects of the temporal stationarity of graph theory measures. We apply the method and proposed estimators to resting-state functional MRI data from healthy controls and patients with temporal lobe epilepsy. Our analysis shows that several graph theory measures, including small-world index, global integration measures, and betweenness centrality, may exhibit greater stationarity over time and therefore be more robust. Additionally, we demonstrate that accounting for subject-level differences in the level of temporal stationarity of network topology may increase discriminatory power in discriminating between disease states. Our results confirm and extend findings from other studies regarding the dynamic nature of functional connectivity, and suggest that using statistical models which explicitly account for the dynamic nature of functional connectivity in graph theory analyses may improve the sensitivity of investigations and consistency across investigations. Copyright © 2015 Elsevier Inc. All rights reserved.
The receptor protein tyrosine phosphatase (RPTP){beta}/{zeta} is expressed in different subtypes of human breast cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perez-Pinera, Pablo; Garcia-Suarez, Olivia; Instituto Universitario de Oncologia del Principado de Asturias, Oviedo

2007-10-12

Increasing evidence suggests mutations in human breast cancer cells that induce inappropriate expression of the 18-kDa cytokine pleiotrophin (PTN, Ptn) initiate progression of breast cancers to a more malignant phenotype. Pleiotrophin signals through inactivating its receptor, the receptor protein tyrosine phosphatase (RPTP){beta}/{zeta}, leading to increased tyrosine phosphorylation of different substrate proteins of RPTP{beta}/{zeta}, including {beta}-catenin, {beta}-adducin, Fyn, GIT1/Cat-1, and P190RhoGAP. PTN signaling thus has wide impact on different important cellular systems. Recently, PTN was found to activate anaplastic lymphoma kinase (ALK) through the PTN/RPTP{beta}/{zeta} signaling pathway; this discovery potentially is very important, since constitutive ALK activity of nucleophosmin (NPM)-ALK fusionmore » protein is causative of anaplastic large cell lymphomas, and, activated ALK is found in other malignant cancers. Recently ALK was identified in each of 63 human breast cancers from 22 subjects. We now demonstrate that RPTP{beta}/{zeta} is expressed in each of these same 63 human breast cancers that previously were found to express ALK and in 10 additional samples of human breast cancer. RPTP{beta}/{zeta} furthermore was localized not only in its normal association with the cell membrane but also scattered in cytoplasm and in nuclei in different breast cancer cells and, in the case of infiltrating ductal carcinomas, the distribution of RPTP{beta}/{zeta} changes as the breast cancer become more malignant. The data suggest that the PTN/RPTP{beta}/{zeta} signaling pathway may be constitutively activated and potentially function to constitutively activate ALK in human breast cancer.« less
Manipulations of Cartesian Graphs: A First Introduction to Analysis.

ERIC Educational Resources Information Center

Lowenthal, Francis; Vandeputte, Christiane

1989-01-01

Introduces an introductory module for analysis. Describes stock of basic functions and their graphs as part one and three methods as part two: transformations of simple graphs, the sum of stock functions, and upper and lower bounds. (YP)
Graphing Polar Curves

ERIC Educational Resources Information Center

Lawes, Jonathan F.

2013-01-01

Graphing polar curves typically involves a combination of three traditional techniques, all of which can be time-consuming and tedious. However, an alternative method--graphing the polar function on a rectangular plane--simplifies graphing, increases student understanding of the polar coordinate system, and reinforces graphing techniques learned…
Cryptographic Boolean Functions with Biased Inputs

DTIC Science & Technology

2015-07-31

theory of random graphs developed by Erdős and Rényi [2]. The graph properties in a random graph expressed as such Boolean functions are used by...distributed Bernoulli variates with the parameter p. Since our scope is within the area of cryptography , we initiate an analysis of cryptographic...Boolean functions with biased inputs, which we refer to as µp-Boolean functions, is a common generalization of Boolean functions which stems from the
smwrGraphs—An R package for graphing hydrologic data, version 1.1.2

USGS Publications Warehouse

Lorenz, David L.; Diekoff, Aliesha L.

2017-01-31

This report describes an R package called smwrGraphs, which consists of a collection of graphing functions for hydrologic data within R, a programming language and software environment for statistical computing. The functions in the package have been developed by the U.S. Geological Survey to create high-quality graphs for publication or presentation of hydrologic data that meet U.S. Geological Survey graphics guidelines.
Students' Interpretation of a Function Associated with a Real-Life Problem from Its Graph

ERIC Educational Resources Information Center

Mahir, Nevin

2010-01-01

The properties of a function such as limit, continuity, derivative, growth, or concavity can be determined more easily from its graph than by doing any algebraic operation. For this reason, it is important for students of mathematics to interpret some of the properties of a function from its graph. In this study, we investigated the competence of…
Quantum mechanics on Laakso spaces

NASA Astrophysics Data System (ADS)

Kauffman, Christopher J.; Kesler, Robert M.; Parshall, Amanda G.; Stamey, Evelyn A.; Steinhurst, Benjamin A.

2012-04-01

We first review the spectrum of the Laplacian operator on a general Laakso space before considering modified Hamiltonians for the infinite square well, parabola, and Coulomb potentials. Additionally, we compute the spectrum for the Laplacian and its multiplicities when certain regions of a Laakso space are compressed or stretched and calculate the Casimir force experienced by two uncharged conducting plates by imposing physically relevant boundary conditions and then analytically regularizing the resulting zeta function. Lastly, we derive a general formula for the spectral zeta function and its derivative for Laakso spaces with strict self-similar structure before listing explicit spectral values for some special cases
Calculation of Impedance Matrix Inner Integral to Prescribed Precision for the Magnetic Field Integral Equation

DTIC Science & Technology

2012-07-19

calculation point (z’, w) gives the size of the smallest cubature that provides w SD at the point z’ Figure F.1. The graph of the function f in (F.9...77 Figure F.2. The graph of the function g in (F.10...77 Figure F.3. The graph of the function h in (F.13
Casimir force in brane worlds: Coinciding results from Green's and zeta function approaches

DOE Office of Scientific and Technical Information (OSTI.GOV)

Linares, Roman; Morales-Tecotl, Hugo A.; Pedraza, Omar

2010-06-15

Casimir force encodes the structure of the field modes as vacuum fluctuations and so it is sensitive to the extra dimensions of brane worlds. Now, in flat spacetimes of arbitrary dimension the two standard approaches to the Casimir force, Green's function, and zeta function yield the same result, but for brane world models this was only assumed. In this work we show that both approaches yield the same Casimir force in the case of universal extra dimensions and Randall-Sundrum scenarios with one and two branes added by p compact dimensions. Essentially, the details of the mode eigenfunctions that enter themore » Casimir force in the Green's function approach get removed due to their orthogonality relations with a measure involving the right hypervolume of the plates, and this leaves just the contribution coming from the zeta function approach. The present analysis corrects previous results showing a difference between the two approaches for the single brane Randall-Sundrum; this was due to an erroneous hypervolume of the plates introduced by the authors when using the Green's function. For all the models we discuss here, the resulting Casimir force can be neatly expressed in terms of two four-dimensional Casimir force contributions: one for the massless mode and the other for a tower of massive modes associated with the extra dimensions.« less
Perchlorate adsorption and desorption on activated carbon and anion exchange resin.

PubMed

Yoon, In-Ho; Meng, Xiaoguang; Wang, Chao; Kim, Kyoung-Woong; Bang, Sunbaek; Choe, Eunyoung; Lippincott, Lee

2009-05-15

The mechanisms of perchlorate adsorption on activated carbon (AC) and anion exchange resin (SR-7 resin) were investigated using Raman, FTIR, and zeta potential analyses. Batch adsorption and desorption results demonstrated that the adsorption of perchlorate by AC and SR-7 resin was reversible. The reversibility of perchlorate adsorption by the resin was also proved by column regeneration test. Solution pH significantly affected perchlorate adsorption and the zeta potential of AC, while it did not influence perchlorate adsorption and the zeta potential of resin. Zeta potential measurements showed that perchlorate was adsorbed on the negatively charged AC surface. Raman spectra indicated the adsorption resulted in an obvious position shift of the perchlorate peak, suggesting that perchlorate was associated with functional groups on AC at neutral pH through interactions stronger than electrostatic interaction. The adsorbed perchlorate on the resin exhibited a Raman peak at similar position as the aqueous perchlorate, indicating that perchlorate was adsorbed on the resin through electrostatic attraction between the anion and positively charged surface sites.
Electrophoretic Study of the SnO2/Aqueous Solution Interface up to 260 degrees C.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rodriguez-Santiago, V; Fedkin, Mark V.; Wesolowski, David J

2009-01-01

An electrophoresis cell developed in our laboratory was utilized to determine the zeta potential at the SnO{sub 2} (cassiterite)/aqueous solution (10{sup -3} mol kg{sup -1} NaCl) interface over the temperature range from 25 to 260 C. Experimental techniques and methods for the calculation of zeta potential at elevated temperature are described. From the obtained zeta potential data as a function of pH, the isoelectric points (IEPs) of SnO{sub 2} were obtained for the first time. From these IEP values, the standard thermodynamic functions were calculated for the protonation-deprotonation equilibrium at the SnO{sub 2} surface, using the 1-pK surface complexation model.more » It was found that the IEP values for SnO{sub 2} decrease with increasing temperature, and this behavior is compared to the predicted values by the multisite complexation (MUSIC) model and other semitheoretical treatments, and were found to be in excellent agreement.« less
Ringo: Interactive Graph Analytics on Big-Memory Machines

PubMed Central

Perez, Yonathan; Sosič, Rok; Banerjee, Arijit; Puttagunta, Rohan; Raison, Martin; Shah, Pararth; Leskovec, Jure

2016-01-01

We present Ringo, a system for analysis of large graphs. Graphs provide a way to represent and analyze systems of interacting objects (people, proteins, webpages) with edges between the objects denoting interactions (friendships, physical interactions, links). Mining graphs provides valuable insights about individual objects as well as the relationships among them. In building Ringo, we take advantage of the fact that machines with large memory and many cores are widely available and also relatively affordable. This allows us to build an easy-to-use interactive high-performance graph analytics system. Graphs also need to be built from input data, which often resides in the form of relational tables. Thus, Ringo provides rich functionality for manipulating raw input data tables into various kinds of graphs. Furthermore, Ringo also provides over 200 graph analytics functions that can then be applied to constructed graphs. We show that a single big-memory machine provides a very attractive platform for performing analytics on all but the largest graphs as it offers excellent performance and ease of use as compared to alternative approaches. With Ringo, we also demonstrate how to integrate graph analytics with an iterative process of trial-and-error data exploration and rapid experimentation, common in data mining workloads. PMID:27081215
Computing Information Value from RDF Graph Properties

DOE Office of Scientific and Technical Information (OSTI.GOV)

al-Saffar, Sinan; Heileman, Gregory

2010-11-08

Information value has been implicitly utilized and mostly non-subjectively computed in information retrieval (IR) systems. We explicitly define and compute the value of an information piece as a function of two parameters, the first is the potential semantic impact the target information can subjectively have on its recipient's world-knowledge, and the second parameter is trust in the information source. We model these two parameters as properties of RDF graphs. Two graphs are constructed, a target graph representing the semantics of the target body of information and a context graph representing the context of the consumer of that information. We computemore » information value subjectively as a function of both potential change to the context graph (impact) and the overlap between the two graphs (trust). Graph change is computed as a graph edit distance measuring the dissimilarity between the context graph before and after the learning of the target graph. A particular application of this subjective information valuation is in the construction of a personalized ranking component in Web search engines. Based on our method, we construct a Web re-ranking system that personalizes the information experience for the information-consumer.« less
Ringo: Interactive Graph Analytics on Big-Memory Machines.

PubMed

Perez, Yonathan; Sosič, Rok; Banerjee, Arijit; Puttagunta, Rohan; Raison, Martin; Shah, Pararth; Leskovec, Jure

2015-01-01

We present Ringo, a system for analysis of large graphs. Graphs provide a way to represent and analyze systems of interacting objects (people, proteins, webpages) with edges between the objects denoting interactions (friendships, physical interactions, links). Mining graphs provides valuable insights about individual objects as well as the relationships among them. In building Ringo, we take advantage of the fact that machines with large memory and many cores are widely available and also relatively affordable. This allows us to build an easy-to-use interactive high-performance graph analytics system. Graphs also need to be built from input data, which often resides in the form of relational tables. Thus, Ringo provides rich functionality for manipulating raw input data tables into various kinds of graphs. Furthermore, Ringo also provides over 200 graph analytics functions that can then be applied to constructed graphs. We show that a single big-memory machine provides a very attractive platform for performing analytics on all but the largest graphs as it offers excellent performance and ease of use as compared to alternative approaches. With Ringo, we also demonstrate how to integrate graph analytics with an iterative process of trial-and-error data exploration and rapid experimentation, common in data mining workloads.
A clustering-based graph Laplacian framework for value function approximation in reinforcement learning.

PubMed

Xu, Xin; Huang, Zhenhua; Graves, Daniel; Pedrycz, Witold

2014-12-01

In order to deal with the sequential decision problems with large or continuous state spaces, feature representation and function approximation have been a major research topic in reinforcement learning (RL). In this paper, a clustering-based graph Laplacian framework is presented for feature representation and value function approximation (VFA) in RL. By making use of clustering-based techniques, that is, K-means clustering or fuzzy C-means clustering, a graph Laplacian is constructed by subsampling in Markov decision processes (MDPs) with continuous state spaces. The basis functions for VFA can be automatically generated from spectral analysis of the graph Laplacian. The clustering-based graph Laplacian is integrated with a class of approximation policy iteration algorithms called representation policy iteration (RPI) for RL in MDPs with continuous state spaces. Simulation and experimental results show that, compared with previous RPI methods, the proposed approach needs fewer sample points to compute an efficient set of basis functions and the learning control performance can be improved for a variety of parameter settings.
Comparison and Enumeration of Chemical Graphs

PubMed Central

Akutsu, Tatsuya; Nagamochi, Hiroshi

2013-01-01

Chemical compounds are usually represented as graph structured data in computers. In this review article, we overview several graph classes relevant to chemical compounds and the computational complexities of several fundamental problems for these graph classes. In particular, we consider the following problems: determining whether two chemical graphs are identical, determining whether one input chemical graph is a part of the other input chemical graph, finding a maximum common part of two input graphs, finding a reaction atom mapping, enumerating possible chemical graphs, and enumerating stereoisomers. We also discuss the relationship between the fifth problem and kernel functions for chemical compounds. PMID:24688697
Convex Graph Invariants

DTIC Science & Technology

2010-12-02

Motzkin, T. and Straus, E. (1965). Maxima for graphs and a new proof of a theorem of Turan . Canad. J. Math. 17 533–540. [33] Rendl, F. and Sotirov, R...Convex Graph Invariants Venkat Chandrasekaran, Pablo A . Parrilo, and Alan S. Willsky ∗ Laboratory for Information and Decision Systems Department of...this paper we study convex graph invariants, which are graph invariants that are convex functions of the adjacency matrix of a graph. Some examples

Clinical and pharmacogenomic data mining: 1. Generalized theory of expected information and application to the development of tools.

PubMed

Robson, Barry

2003-01-01

New scientific problems, arising from the human genome project, are challenging the classical means of using statistics. Yet quantified knowledge in the form of rules and rule strengths based on real relationships in data, as opposed to expert opinion, is urgently required for researcher and physician decision support. The problem is that with many parameters, the space to be analyzed is highly dimensional. That is, the combinations of data to examine are subject to a combinatorial explosion as the number of possible events (entries, items, sub-records) (a),(b),(c),... per record (a,b,c,..) increases, and hence much of the space is sparsely populated. These combinatorial considerations are particularly problematic for identifying those associations called "Unicorn Events" which occur significantly less than expected to the extent that they are never seen to be counted. To cope with the combinatorial explosion, a novel numerical "book keeping" approach is taken to generate information terms relating to the combinatorial subsets of events (a,b,c,..), and, most importantly, the zeta (Zeta) function is employed. The incomplete Zeta function zeta(s,n) with s = 1, in which frequencies of occurrence such as n = n(a,b,c,...) determine the range of summation n, is argued to be the natural choice of information function. It emerges from Bayesian integration, taken over the distribution of possible values of information measures for sparse and ample data alike. Expected mutual information l(a;b;c) in nats (i.e., natural units analogous to bits but based on the natural logarithm), such as is available to the observer, is measured as e.g., the difference zeta(s,o(a,b,c..)) - zeta(s,e(a,b,c..)) where o(a,b,c,..) and e(a,b,c,..) are, or relate to, the observed and expected frequencies of occurrence, respectively. For real values of s > 1 the qualitative impact of strongly (positively or negatively) ranked data is preserved despite several numerical approximations. As real s increases, and the output of the information functions converge into three values +1, 0, and -1 nats representing a trinary logic system. For quantitative data, a useful ad hoc method, to report sigma-normalized covariations in an analogous manner to mutual information for significance comparison purposes, is demonstrated. Finally, the potential ability to make use of mutual information in a complex biomedical study, and to include Bayesian prior information derived from statistical, tabular, anecdotal, and expert opinion is briefly illustrated.
Discrimination Power of Polynomial-Based Descriptors for Graphs by Using Functional Matrices.

PubMed

Dehmer, Matthias; Emmert-Streib, Frank; Shi, Yongtang; Stefu, Monica; Tripathi, Shailesh

2015-01-01

In this paper, we study the discrimination power of graph measures that are based on graph-theoretical matrices. The paper generalizes the work of [M. Dehmer, M. Moosbrugger. Y. Shi, Encoding structural information uniquely with polynomial-based descriptors by employing the Randić matrix, Applied Mathematics and Computation, 268(2015), 164-168]. We demonstrate that by using the new functional matrix approach, exhaustively generated graphs can be discriminated more uniquely than shown in the mentioned previous work.
Discrimination Power of Polynomial-Based Descriptors for Graphs by Using Functional Matrices

PubMed Central

Dehmer, Matthias; Emmert-Streib, Frank; Shi, Yongtang; Stefu, Monica; Tripathi, Shailesh

2015-01-01

In this paper, we study the discrimination power of graph measures that are based on graph-theoretical matrices. The paper generalizes the work of [M. Dehmer, M. Moosbrugger. Y. Shi, Encoding structural information uniquely with polynomial-based descriptors by employing the Randić matrix, Applied Mathematics and Computation, 268(2015), 164–168]. We demonstrate that by using the new functional matrix approach, exhaustively generated graphs can be discriminated more uniquely than shown in the mentioned previous work. PMID:26479495
DELTACON: A Principled Massive-Graph Similarity Function with Attribution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Koutra, Danai; Shah, Neil; Vogelstein, Joshua T.

How much did a network change since yesterday? How different is the wiring between Bob's brain (a left-handed male) and Alice's brain (a right-handed female)? Graph similarity with known node correspondence, i.e. the detection of changes in the connectivity of graphs, arises in numerous settings. In this work, we formally state the axioms and desired properties of the graph similarity functions, and evaluate when state-of-the-art methods fail to detect crucial connectivity changes in graphs. We propose DeltaCon, a principled, intuitive, and scalable algorithm that assesses the similarity between two graphs on the same nodes (e.g. employees of a company, customersmore » of a mobile carrier). In our experiments on various synthetic and real graphs we showcase the advantages of our method over existing similarity measures. We also employ DeltaCon to real applications: (a) we classify people to groups of high and low creativity based on their brain connectivity graphs, and (b) do temporal anomaly detection in the who-emails-whom Enron graph.« less
DELTACON: A Principled Massive-Graph Similarity Function with Attribution

DOE PAGES

Koutra, Danai; Shah, Neil; Vogelstein, Joshua T.; ...

2014-05-22

How much did a network change since yesterday? How different is the wiring between Bob's brain (a left-handed male) and Alice's brain (a right-handed female)? Graph similarity with known node correspondence, i.e. the detection of changes in the connectivity of graphs, arises in numerous settings. In this work, we formally state the axioms and desired properties of the graph similarity functions, and evaluate when state-of-the-art methods fail to detect crucial connectivity changes in graphs. We propose DeltaCon, a principled, intuitive, and scalable algorithm that assesses the similarity between two graphs on the same nodes (e.g. employees of a company, customersmore » of a mobile carrier). In our experiments on various synthetic and real graphs we showcase the advantages of our method over existing similarity measures. We also employ DeltaCon to real applications: (a) we classify people to groups of high and low creativity based on their brain connectivity graphs, and (b) do temporal anomaly detection in the who-emails-whom Enron graph.« less
High-concentration zeta potential measurements using light-scattering techniques

PubMed Central

Kaszuba, Michael; Corbett, Jason; Watson, Fraser Mcneil; Jones, Andrew

2010-01-01

Zeta potential is the key parameter that controls electrostatic interactions in particle dispersions. Laser Doppler electrophoresis is an accepted method for the measurement of particle electrophoretic mobility and hence zeta potential of dispersions of colloidal size materials. Traditionally, samples measured by this technique have to be optically transparent. Therefore, depending upon the size and optical properties of the particles, many samples will be too concentrated and will require dilution. The ability to measure samples at or close to their neat concentration would be desirable as it would minimize any changes in the zeta potential of the sample owing to dilution. However, the ability to measure turbid samples using light-scattering techniques presents a number of challenges. This paper discusses electrophoretic mobility measurements made on turbid samples at high concentration using a novel cell with reduced path length. Results are presented on two different sample types, titanium dioxide and a polyurethane dispersion, as a function of sample concentration. For both of the sample types studied, the electrophoretic mobility results show a gradual decrease as the sample concentration increases and the possible reasons for these observations are discussed. Further, a comparison of the data against theoretical models is presented and discussed. Conclusions and recommendations are made from the zeta potential values obtained at high concentrations. PMID:20732896
Gene function prediction with gene interaction networks: a context graph kernel approach.

PubMed

Li, Xin; Chen, Hsinchun; Li, Jiexun; Zhang, Zhu

2010-01-01

Predicting gene functions is a challenge for biologists in the postgenomic era. Interactions among genes and their products compose networks that can be used to infer gene functions. Most previous studies adopt a linkage assumption, i.e., they assume that gene interactions indicate functional similarities between connected genes. In this study, we propose to use a gene's context graph, i.e., the gene interaction network associated with the focal gene, to infer its functions. In a kernel-based machine-learning framework, we design a context graph kernel to capture the information in context graphs. Our experimental study on a testbed of p53-related genes demonstrates the advantage of using indirect gene interactions and shows the empirical superiority of the proposed approach over linkage-assumption-based methods, such as the algorithm to minimize inconsistent connected genes and diffusion kernels.
Flotation of algae for water reuse and biomass production: role of zeta potential and surfactant to separate algal particles.

PubMed

Kwak, Dong-Heui; Kim, Mi-Sug

2015-01-01

The effect of chemical coagulation and biological auto-flocculation relative to zeta potential was examined to compare flotation and sedimentation separation processes for algae harvesting. Experiments revealed that microalgae separation is related to auto-flocculation of Anabaena spp. and requires chemical coagulation for the whole period of microalgae cultivation. In addition, microalgae separation characteristics which are associated with surfactants demonstrated optimal microalgae cultivation time and separation efficiency of dissolved CO2 flotation (DCF) as an alternative to dissolved air flotation (DAF). Microalgae were significantly separated in response to anionic surfactant rather than cationic surfactant as a function of bubble size and zeta potential. DAF and DCF both showed slightly efficient flotation; however, application of anionic surfactant was required when using DCF.
Graph drawing using tabu search coupled with path relinking.

PubMed

Dib, Fadi K; Rodgers, Peter

2018-01-01

Graph drawing, or the automatic layout of graphs, is a challenging problem. There are several search based methods for graph drawing which are based on optimizing an objective function which is formed from a weighted sum of multiple criteria. In this paper, we propose a new neighbourhood search method which uses a tabu search coupled with path relinking to optimize such objective functions for general graph layouts with undirected straight lines. To our knowledge, before our work, neither of these methods have been previously used in general multi-criteria graph drawing. Tabu search uses a memory list to speed up searching by avoiding previously tested solutions, while the path relinking method generates new solutions by exploring paths that connect high quality solutions. We use path relinking periodically within the tabu search procedure to speed up the identification of good solutions. We have evaluated our new method against the commonly used neighbourhood search optimization techniques: hill climbing and simulated annealing. Our evaluation examines the quality of the graph layout (objective function's value) and the speed of layout in terms of the number of evaluated solutions required to draw a graph. We also examine the relative scalability of each method. Our experimental results were applied to both random graphs and a real-world dataset. We show that our method outperforms both hill climbing and simulated annealing by producing a better layout in a lower number of evaluated solutions. In addition, we demonstrate that our method has greater scalability as it can layout larger graphs than the state-of-the-art neighbourhood search methods. Finally, we show that similar results can be produced in a real world setting by testing our method against a standard public graph dataset.
A Graph Approach to Mining Biological Patterns in the Binding Interfaces.

PubMed

Cheng, Wen; Yan, Changhui

2017-01-01

Protein-RNA interactions play important roles in the biological systems. Searching for regular patterns in the Protein-RNA binding interfaces is important for understanding how protein and RNA recognize each other and bind to form a complex. Herein, we present a graph-mining method for discovering biological patterns in the protein-RNA interfaces. We represented known protein-RNA interfaces using graphs and then discovered graph patterns enriched in the interfaces. Comparison of the discovered graph patterns with UniProt annotations showed that the graph patterns had a significant overlap with residue sites that had been proven crucial for the RNA binding by experimental methods. Using 200 patterns as input features, a support vector machine method was able to classify protein surface patches into RNA-binding sites and non-RNA-binding sites with 84.0% accuracy and 88.9% precision. We built a simple scoring function that calculated the total number of the graph patterns that occurred in a protein-RNA interface. That scoring function was able to discriminate near-native protein-RNA complexes from docking decoys with a performance comparable with that of a state-of-the-art complex scoring function. Our work also revealed possible patterns that might be important for binding affinity.
Antiholomorphic perturbations of Weierstrass Zeta functions and Green’s function on tori

NASA Astrophysics Data System (ADS)

Bogdanov, Konstantin; Mamayusupov, Khudoyor; Mukherjee, Sabyasachi; Schleicher, Dierk

2017-08-01

In Bergweiler and Eremenko (2016 Proc. Am. Math. Soc. 144 2911-22), Bergweiler and Eremenko computed the number of critical points of the Green’s function on a torus by investigating the dynamics of a certain family of antiholomorphic meromorphic functions on tori. They also observed that hyperbolic maps are dense in this family of meromorphic functions in a rather trivial way. In this paper, we study the parameter space of this family of meromorphic functions, which can be written as antiholomorphic perturbations of Weierstrass Zeta functions. On the one hand, we give a complete topological description of the hyperbolic components and their boundaries, and on the other hand, we show that these sets admit natural parametrizations by associated dynamical invariants. This settles a conjecture, made in Lin and Wang (2010 Ann. Math. 172 911-54), on the topology of the regions in the upper half plane {H} where the number of critical points of the Green’s function remains constant.
Dispersion stability of a ceramic glaze achieved through ionic surfactant adsorption.

PubMed

Panya, Preecha; Arquero, Orn-anong; Franks, George V; Wanless, Erica J

2004-11-01

The adsorption of cetylpyridinium chloride (CPC) and sodium dodecylbenzenesulfonate (SDBS) onto a ceramic glaze mixture composed of limestone, feldspar, quartz, and kaolin has been investigated. Both adsorption isotherms and the average particle zeta potential have been studied in order to understand the suspension stability as a function of pH, ionic strength, and surfactant concentration. The adsorption of small amounts of cationic CPC onto the primarily negatively charged surfaces of the particles at pH 7 and 9 results in strong attraction and flocculation due to hydrophobic interactions. At higher surfactant concentrations a zeta potential of more than +60 mV results from the bilayered adsorbed surfactant, providing stability at salt concentrations < or = 0.01 M. At 0.1 M salt poor stability results despite substantial zeta potential values. Three mechanisms for SDBS adsorption have been identified. When anionic SDBS monomers either adsorb by electrostatic interactions with the few positive surface sites at high pH or adsorb onto like charged negative surface sites due to dispersion or hydrophobic interactions, the magnitude of the negative zeta potential increases slightly. At pH 9 this increase is enough to promote stability with an average zeta potential of more than -55 mV, whereas at pH 7 the zeta potential is lower at about -45 mV. The stability of suspensions at pH 7 is additionally due to steric repulsion caused by the adsorption of thick layers of neutrally charged Ca(DBS)2 complexes created when the surfactant interacts with dissolved calcium ions from the calcium carbonate component.
Learning graph matching.

PubMed

Caetano, Tibério S; McAuley, Julian J; Cheng, Li; Le, Quoc V; Smola, Alex J

2009-06-01

As a fundamental problem in pattern recognition, graph matching has applications in a variety of fields, from computer vision to computational biology. In graph matching, patterns are modeled as graphs and pattern recognition amounts to finding a correspondence between the nodes of different graphs. Many formulations of this problem can be cast in general as a quadratic assignment problem, where a linear term in the objective function encodes node compatibility and a quadratic term encodes edge compatibility. The main research focus in this theme is about designing efficient algorithms for approximately solving the quadratic assignment problem, since it is NP-hard. In this paper we turn our attention to a different question: how to estimate compatibility functions such that the solution of the resulting graph matching problem best matches the expected solution that a human would manually provide. We present a method for learning graph matching: the training examples are pairs of graphs and the 'labels' are matches between them. Our experimental results reveal that learning can substantially improve the performance of standard graph matching algorithms. In particular, we find that simple linear assignment with such a learning scheme outperforms Graduated Assignment with bistochastic normalisation, a state-of-the-art quadratic assignment relaxation algorithm.
Graphs in Kinematics--A Need for Adherence to Principles of Algebraic Functions

ERIC Educational Resources Information Center

Sokolowski, Andrzej

2017-01-01

Graphs in physics are central to the analysis of phenomena and to learning about a system's behavior. The ways students handle graphs are frequently researched. Students' misconceptions are highlighted, and methods of improvement suggested. While kinematics graphs are to represent a real motion, they are also algebraic entities that must satisfy…
Horizontal visibility graphs generated by type-I intermittency

NASA Astrophysics Data System (ADS)

Núñez, Ángel M.; Luque, Bartolo; Lacasa, Lucas; Gómez, Jose Patricio; Robledo, Alberto

2013-05-01

The type-I intermittency route to (or out of) chaos is investigated within the horizontal visibility (HV) graph theory. For that purpose, we address the trajectories generated by unimodal maps close to an inverse tangent bifurcation and construct their associated HV graphs. We show how the alternation of laminar episodes and chaotic bursts imprints a fingerprint in the resulting graph structure. Accordingly, we derive a phenomenological theory that predicts quantitative values for several network parameters. In particular, we predict that the characteristic power-law scaling of the mean length of laminar trend sizes is fully inherited by the variance of the graph degree distribution, in good agreement with the numerics. We also report numerical evidence on how the characteristic power-law scaling of the Lyapunov exponent as a function of the distance to the tangent bifurcation is inherited in the graph by an analogous scaling of block entropy functionals defined on the graph. Furthermore, we are able to recast the full set of HV graphs generated by intermittent dynamics into a renormalization-group framework, where the fixed points of its graph-theoretical renormalization-group flow account for the different types of dynamics. We also establish that the nontrivial fixed point of this flow coincides with the tangency condition and that the corresponding invariant graph exhibits extremal entropic properties.
The Impact of Using Technology on Student Achievement: Teaching Functions with the TI-Nspire to 9th Grade Algebra Students

ERIC Educational Resources Information Center

Buckner, Barbara Renee

2011-01-01

The purpose of this study was to determine the effect of TI-Nspire graphing calculator use on student achievement and on teacher behavior variables of planning, teaching, and assessing. This study investigated the teaching of functions by teachers using the TI-Nspire graphing calculator versus teachers using a non-graphing scientific calculator. …
Multidimensional Extension of the Generalized Chowla-Selberg Formula

NASA Astrophysics Data System (ADS)

Elizalde, E.

After recalling the precise existence conditions of the zeta function of a pseudodifferential operator, and the concept of reflection formula, an exponentially convergent expression for the analytic continuation of a multidimensional inhomogeneous Epstein-type zeta function of the general form with A the p×p$ matrix of a quadratic form, a p vector and q a constant, is obtained. It is valid on the whole complex s-plane, is exponentially convergent and provides the residua at the poles explicitly. It reduces to the famous formula of Chowla and Selberg in the particular case p=2, , q=0. Some variations of the formula and physical applications are considered.
Segmented all-electron Gaussian basis sets of double and triple zeta qualities for Fr, Ra, and Ac

NASA Astrophysics Data System (ADS)

Campos, C. T.; de Oliveira, A. Z.; Ferreira, I. B.; Jorge, F. E.; Martins, L. S. C.

2017-05-01

Segmented all-electron basis sets of valence double and triple zeta qualities plus polarization functions for the elements Fr, Ra, and Ac are generated using non-relativistic and Douglas-Kroll-Hess (DKH) Hamiltonians. The sets are augmented with diffuse functions with the purpose to describe appropriately the electrons far from the nuclei. At the DKH-B3LYP level, first atomic ionization energies and bond lengths, dissociation energies, and polarizabilities of a sample of diatomics are calculated. Comparison with theoretical and experimental data available in the literature is carried out. It is verified that despite the small sizes of the basis sets, they are yet reliable.
Electrokinetic pump

DOEpatents

Patel, Kamlesh D.

2007-11-20

A method for altering the surface properties of a particle bed. In application, the method pertains particularly to an electrokinetic pump configuration where nanoparticles are bonded to the surface of the stationary phase to alter the surface properties of the stationary phase including the surface area and/or the zeta potential and thus improve the efficiency and operating range of these pumps. By functionalizing the nanoparticles to change the zeta potential the electrokinetic pump is rendered capable of operating with working fluids having pH values that can range from 2-10 generally and acidic working fluids in particular. For applications in which the pump is intended to handle highly acidic solutions latex nanoparticles that are quaternary amine functionalized can be used.
Lysine-functionalized nanodiamonds: synthesis, physiochemical characterization, and nucleic acid binding studies

PubMed Central

Kaur, Randeep; Chitanda, Jackson M; Michel, Deborah; Maley, Jason; Borondics, Ferenc; Yang, Peng; Verrall, Ronald E; Badea, Ildiko

2012-01-01

Purpose: Detonation nanodiamonds (NDs) are carbon-based nanomaterials that, because of their size (4–5 nm), stable inert core, alterable surface chemistry, fluorescence, and biocompatibility, are emerging as bioimaging agents and promising tools for the delivery of biochemical molecules into cellular systems. However, diamond particles possess a strong propensity to aggregate in liquid formulation media, restricting their applicability in biomedical sciences. Here, the authors describe the covalent functionalization of NDs with lysine in an attempt to develop nanoparticles able to act as suitable nonviral vectors for transferring genetic materials across cellular membranes. Methods: NDs were oxidized and functionalized by binding lysine moieties attached to a three-carbon-length linker (1,3-diaminopropane) to their surfaces through amide bonds. Raman and Fourier transform infrared spectroscopy, zeta potential measurement, dynamic light scattering, atomic force microscopic imaging, and thermogravimetric analysis were used to characterize the lysine-functionalized NDs. Finally, the ability of the functionalized diamonds to bind plasmid DNA and small interfering RNA was investigated by gel electrophoresis assay and through size and zeta potential measurements. Results: NDs were successfully functionalized with the lysine linker, producing surface loading of 1.7 mmol g−1 of ND. These modified NDs formed highly stable aqueous dispersions with a zeta potential of 49 mV and particle size of approximately 20 nm. The functionalized NDs were found to be able to bind plasmid DNA and small interfering RNA by forming nanosized “diamoplexes”. Conclusion: The lysine-substituted ND particles generated in this study exhibit stable aqueous formulations and show potential for use as carriers for genetic materials. PMID:22904623

Graph Frequency Analysis of Brain Signals

PubMed Central

Huang, Weiyu; Goldsberry, Leah; Wymbs, Nicholas F.; Grafton, Scott T.; Bassett, Danielle S.; Ribeiro, Alejandro

2016-01-01

This paper presents methods to analyze functional brain networks and signals from graph spectral perspectives. The notion of frequency and filters traditionally defined for signals supported on regular domains such as discrete time and image grids has been recently generalized to irregular graph domains, and defines brain graph frequencies associated with different levels of spatial smoothness across the brain regions. Brain network frequency also enables the decomposition of brain signals into pieces corresponding to smooth or rapid variations. We relate graph frequency with principal component analysis when the networks of interest denote functional connectivity. The methods are utilized to analyze brain networks and signals as subjects master a simple motor skill. We observe that brain signals corresponding to different graph frequencies exhibit different levels of adaptability throughout learning. Further, we notice a strong association between graph spectral properties of brain networks and the level of exposure to tasks performed, and recognize the most contributing and important frequency signatures at different levels of task familiarity. PMID:28439325
Transformations of Mathematical and Stimulus Functions

PubMed Central

Ninness, Chris; Barnes-Holmes, Dermot; Rumph, Robin; McCuller, Glen; Ford, Angela M; Payne, Robert; Ninness, Sharon K; Smith, Ronald J; Ward, Todd A; Elliott, Marc P

2006-01-01

Following a pretest, 8 participants who were unfamiliar with algebraic and trigonometric functions received a brief presentation on the rectangular coordinate system. Next, they participated in a computer-interactive matching-to-sample procedure that trained formula-to-formula and formula-to-graph relations. Then, they were exposed to 40 novel formula-to-graph tests and 10 novel graph-to-formula tests. Seven of the 8 participants showed substantial improvement in identifying formula-to-graph relations; however, in the test of novel graph-to-formula relations, participants tended to select equations in their factored form. Next, we manipulated contextual cues in the form of rules regarding mathematical preferences. First, we informed participants that standard forms of equations were preferred over factored forms. In a subsequent test of 10 additional novel graph-to-formula relations, participants shifted their selections to favor equations in their standard form. This preference reversed during 10 more tests when financial reward was made contingent on correct identification of formulas in factored form. Formula preferences and transformation of novel mathematical and stimulus functions are discussed. PMID:17020211
Self-organizing maps for learning the edit costs in graph matching.

PubMed

Neuhaus, Michel; Bunke, Horst

2005-06-01

Although graph matching and graph edit distance computation have become areas of intensive research recently, the automatic inference of the cost of edit operations has remained an open problem. In the present paper, we address the issue of learning graph edit distance cost functions for numerically labeled graphs from a corpus of sample graphs. We propose a system of self-organizing maps (SOMs) that represent the distance measuring spaces of node and edge labels. Our learning process is based on the concept of self-organization. It adapts the edit costs in such a way that the similarity of graphs from the same class is increased, whereas the similarity of graphs from different classes decreases. The learning procedure is demonstrated on two different applications involving line drawing graphs and graphs representing diatoms, respectively.
Zeta Potential Measurements on Solid Surfaces for in Vitro Biomaterials Testing: Surface Charge, Reactivity Upon Contact With Fluids and Protein Absorption

PubMed Central

Ferraris, Sara; Cazzola, Martina; Peretti, Veronica; Stella, Barbara; Spriano, Silvia

2018-01-01

Surface properties of biomaterials (e.g., roughness, chemical composition, charge, wettability, and hydroxylation degree) are key features to understand and control the complex interface phenomena that happens upon contact with physiological fluids. Numerous physico-chemical techniques can be used in order to investigate in depth these crucial material features. Among them, zeta potential measurements are widely used for the characterization of colloidal suspensions, but actually poorly explored in the study of solid surfaces, even if they can give significant information about surface charge in function of pH and indirectly about surface functional groups and reactivity. The aim of the present research is application of zeta potential measurements of solid surfaces for the in vitro testing of biomaterials. In particular, bare and surface modified Ti6Al4V samples have been compared in order to evaluate their isoelectric points (IEPs), surface charge at physiological pH, in vitro bioactivity [in simulated body fluid (SBF)] and protein absorption. Zeta potential titration was demonstrated as a suitable technique for the surface characterization of surface treated Ti6Al4V substrates. Significant shift of the isoelectric point was recorded after a chemical surface treatment (because of the exposition of hydroxyl groups), SBF soaking (because of apatite precipitation IEP moves close to apatite one) and protein absorption (IEP moves close to protein ones). Moreover, the shape of the curve gives information about exposed functional groups (e.g., a plateau in the basic range appears due to the exposition of acidic OH groups and in the acidic range due to exposition of basic NH2 groups). PMID:29868575
A zeta potential value determines the aggregate's size of penta-substituted [60]fullerene derivatives in aqueous suspension whereas positive charge is required for toxicity against bacterial cells.

PubMed

Deryabin, Dmitry G; Efremova, Ludmila V; Vasilchenko, Alexey S; Saidakova, Evgeniya V; Sizova, Elena A; Troshin, Pavel A; Zhilenkov, Alexander V; Khakina, Ekaterina A; Khakina, Ekaterina E

2015-08-08

The cause-effect relationships between physicochemical properties of amphiphilic [60]fullerene derivatives and their toxicity against bacterial cells have not yet been clarified. In this study, we report how the differences in the chemical structure of organic addends in 10 originally synthesized penta-substituted [60]fullerene derivatives modulate their zeta potential and aggregate's size in salt-free and salt-added aqueous suspensions as well as how these physicochemical characteristics affect the bioenergetics of freshwater Escherichia coli and marine Photobacterium phosphoreum bacteria. Dynamic light scattering, laser Doppler micro-electrophoresis, agarose gel electrophoresis, atomic force microscopy, and bioluminescence inhibition assay were used to characterize the fullerene aggregation behavior in aqueous solution and their interaction with the bacterial cell surface, following zeta potential changes and toxic effects. Dynamic light scattering results indicated the formation of self-assembled [60]fullerene aggregates in aqueous suspensions. The measurement of the zeta potential of the particles revealed that they have different surface charges. The relationship between these physicochemical characteristics was presented as an exponential regression that correctly described the dependence of the aggregate's size of penta-substituted [60]fullerene derivatives in salt-free aqueous suspension from zeta potential value. The prevalence of DLVO-related effects was shown in salt-added aqueous suspension that decreased zeta potential values and affected the aggregation of [60]fullerene derivatives expressed differently for individual compounds. A bioluminescence inhibition assay demonstrated that the toxic effect of [60]fullerene derivatives against E. coli cells was strictly determined by their positive zeta potential charge value being weakened against P. phosphoreum cells in an aquatic system of high salinity. Atomic force microscopy data suggested that the activity of positively charged [60]fullerene derivatives against bacterial cells required their direct interaction. The following zeta potential inversion on the bacterial cells surface was observed as an early stage of toxicity mechanism that violates the membrane-associated energetic functions. The novel data about interrelations between physicochemical parameters and toxic properties of amphiphilic [60]fullerene derivatives make possible predicting their behavior in aquatic environment and their activity against bacterial cells.
Robust Algorithms for on Minor-Free Graphs Based on the Sherali-Adams Hierarchy

NASA Astrophysics Data System (ADS)

Magen, Avner; Moharrami, Mohammad

This work provides a Linear Programming-based Polynomial Time Approximation Scheme (PTAS) for two classical NP-hard problems on graphs when the input graph is guaranteed to be planar, or more generally Minor Free. The algorithm applies a sufficiently large number (some function of when approximation is required) of rounds of the so-called Sherali-Adams Lift-and-Project system. needed to obtain a -approximation, where f is some function that depends only on the graph that should be avoided as a minor. The problem we discuss are the well-studied problems, the and problems. An curious fact we expose is that in the world of minor-free graph, the is harder in some sense than the.
First insights into a type II toxin-antitoxin system from the clinical isolate Mycobacterium sp. MHSD3, similar to epsilon/zeta systems.

PubMed

Jaén-Luchoro, Daniel; Aliaga-Lozano, Francisco; Gomila, Rosa Maria; Gomila, Margarita; Salvà-Serra, Francisco; Lalucat, Jorge; Bennasar-Figueras, Antoni

2017-01-01

A putative type II toxin-antitoxin (TA) system was found in the clinical isolate Mycobacterium sp. MHSD3, a strain closely related to Mycobacterium chelonae. Further analyses of the protein sequences of the two genes revealed the presence of domains related to a TA system. BLAST analyses indicated the presence of closely related proteins in the genomes of other recently published M. chelonae strains. The functionality of both elements of the TA system was demonstrated when expressed in Escherichia coli cells, and the predicted structure of the toxin is very similar to those of well-known zeta-toxins, leading to the definition of a type II TA system similar to epsilon/zeta TA systems in strains that are closely related to M. chelonae.
Constructing Graphical Representations: Middle Schoolers' Intuitions and Developing Knowledge about Slope and Y-Intercept

ERIC Educational Resources Information Center

Hattikudur, Shanta; Prather, Richard W.; Asquith, Pamela; Alibali, Martha W.; Knuth, Eric J.; Nathan, Mitchell

2012-01-01

Middle-school students are expected to understand key components of graphs, such as slope and y-intercept. However, constructing graphs is a skill that has received relatively little research attention. This study examined students' construction of graphs of linear functions, focusing specifically on the relative difficulties of graphing slope and…
Visibility of quantum graph spectrum from the vertices

NASA Astrophysics Data System (ADS)

Kühn, Christian; Rohleder, Jonathan

2018-03-01

We investigate the relation between the eigenvalues of the Laplacian with Kirchhoff vertex conditions on a finite metric graph and a corresponding Titchmarsh-Weyl function (a parameter-dependent Neumann-to-Dirichlet map). We give a complete description of all real resonances, including multiplicities, in terms of the edge lengths and the connectivity of the graph, and apply it to characterize all eigenvalues which are visible for the Titchmarsh-Weyl function.
Functional determinants of radial operators in AdS 2

NASA Astrophysics Data System (ADS)

Aguilera-Damia, Jeremías; Faraggi, Alberto; Zayas, Leopoldo Pando; Rathee, Vimal; Silva, Guillermo A.

2018-06-01

We study the zeta-function regularization of functional determinants of Laplace and Dirac-type operators in two-dimensional Euclidean AdS 2 space. More specifically, we consider the ratio of determinants between an operator in the presence of background fields with circular symmetry and the free operator in which the background fields are absent. By Fourier-transforming the angular dependence, one obtains an infinite number of one-dimensional radial operators, the determinants of which are easy to compute. The summation over modes is then treated with care so as to guarantee that the result coincides with the two-dimensional zeta-function formalism. The method relies on some well-known techniques to compute functional determinants using contour integrals and the construction of the Jost function from scattering theory. Our work generalizes some known results in flat space. The extension to conformal AdS 2 geometries is also considered. We provide two examples, one bosonic and one fermionic, borrowed from the spectrum of fluctuations of the holographic 1/4 -BPS latitude Wilson loop.
College Students' Understanding of the Domain and Range of Functions on Graphs

ERIC Educational Resources Information Center

Cho, Young Doo

2013-01-01

The mathematical concept of function has been revisited and further developed with regularity since its introduction in ancient Babylonia (Kleiner, 1989). The difficulty of the concept of a function contributes to complications when students learn of functions and their graphs (Leinhardt, Zaslavsky, & Stein, 1990). To understand the concept of…
Interval Graph Limits

PubMed Central

Diaconis, Persi; Holmes, Susan; Janson, Svante

2015-01-01

We work out a graph limit theory for dense interval graphs. The theory developed departs from the usual description of a graph limit as a symmetric function W (x, y) on the unit square, with x and y uniform on the interval (0, 1). Instead, we fix a W and change the underlying distribution of the coordinates x and y. We find choices such that our limits are continuous. Connections to random interval graphs are given, including some examples. We also show a continuity result for the chromatic number and clique number of interval graphs. Some results on uniqueness of the limit description are given for general graph limits. PMID:26405368
Integration of biological data by kernels on graph nodes allows prediction of new genes involved in mitotic chromosome condensation

PubMed Central

Hériché, Jean-Karim; Lees, Jon G.; Morilla, Ian; Walter, Thomas; Petrova, Boryana; Roberti, M. Julia; Hossain, M. Julius; Adler, Priit; Fernández, José M.; Krallinger, Martin; Haering, Christian H.; Vilo, Jaak; Valencia, Alfonso; Ranea, Juan A.; Orengo, Christine; Ellenberg, Jan

2014-01-01

The advent of genome-wide RNA interference (RNAi)–based screens puts us in the position to identify genes for all functions human cells carry out. However, for many functions, assay complexity and cost make genome-scale knockdown experiments impossible. Methods to predict genes required for cell functions are therefore needed to focus RNAi screens from the whole genome on the most likely candidates. Although different bioinformatics tools for gene function prediction exist, they lack experimental validation and are therefore rarely used by experimentalists. To address this, we developed an effective computational gene selection strategy that represents public data about genes as graphs and then analyzes these graphs using kernels on graph nodes to predict functional relationships. To demonstrate its performance, we predicted human genes required for a poorly understood cellular function—mitotic chromosome condensation—and experimentally validated the top 100 candidates with a focused RNAi screen by automated microscopy. Quantitative analysis of the images demonstrated that the candidates were indeed strongly enriched in condensation genes, including the discovery of several new factors. By combining bioinformatics prediction with experimental validation, our study shows that kernels on graph nodes are powerful tools to integrate public biological data and predict genes involved in cellular functions of interest. PMID:24943848
Assessing dynamic brain graphs of time-varying connectivity in fMRI data: application to healthy controls and patients with schizophrenia

PubMed Central

Yu, Qingbao; Erhardt, Erik B.; Sui, Jing; Du, Yuhui; He, Hao; Hjelm, Devon; Cetin, Mustafa S.; Rachakonda, Srinivas; Miller, Robyn L.; Pearlson, Godfrey; Calhoun, Vince D.

2014-01-01

Graph theory-based analysis has been widely employed in brain imaging studies, and altered topological properties of brain connectivity have emerged as important features of mental diseases such as schizophrenia. However, most previous studies have focused on graph metrics of stationary brain graphs, ignoring that brain connectivity exhibits fluctuations over time. Here we develop a new framework for accessing dynamic graph properties of time-varying functional brain connectivity in resting state fMRI data and apply it to healthy controls (HCs) and patients with schizophrenia (SZs). Specifically, nodes of brain graphs are defined by intrinsic connectivity networks (ICNs) identified by group independent component analysis (ICA). Dynamic graph metrics of the time-varying brain connectivity estimated by the correlation of sliding time-windowed ICA time courses of ICNs are calculated. First- and second-level connectivity states are detected based on the correlation of nodal connectivity strength between time-varying brain graphs. Our results indicate that SZs show decreased variance in the dynamic graph metrics. Consistent with prior stationary functional brain connectivity works, graph measures of identified first-level connectivity states show lower values in SZs. In addition, more first-level connectivity states are disassociated with the second-level connectivity state which resembles the stationary connectivity pattern computed by the entire scan. Collectively, the findings provide new evidence about altered dynamic brain graphs in schizophrenia which may underscore the abnormal brain performance in this mental illness. PMID:25514514
Metric learning with spectral graph convolutions on brain connectivity networks.

PubMed

Ktena, Sofia Ira; Parisot, Sarah; Ferrante, Enzo; Rajchl, Martin; Lee, Matthew; Glocker, Ben; Rueckert, Daniel

2018-04-01

Graph representations are often used to model structured data at an individual or population level and have numerous applications in pattern recognition problems. In the field of neuroscience, where such representations are commonly used to model structural or functional connectivity between a set of brain regions, graphs have proven to be of great importance. This is mainly due to the capability of revealing patterns related to brain development and disease, which were previously unknown. Evaluating similarity between these brain connectivity networks in a manner that accounts for the graph structure and is tailored for a particular application is, however, non-trivial. Most existing methods fail to accommodate the graph structure, discarding information that could be beneficial for further classification or regression analyses based on these similarities. We propose to learn a graph similarity metric using a siamese graph convolutional neural network (s-GCN) in a supervised setting. The proposed framework takes into consideration the graph structure for the evaluation of similarity between a pair of graphs, by employing spectral graph convolutions that allow the generalisation of traditional convolutions to irregular graphs and operates in the graph spectral domain. We apply the proposed model on two datasets: the challenging ABIDE database, which comprises functional MRI data of 403 patients with autism spectrum disorder (ASD) and 468 healthy controls aggregated from multiple acquisition sites, and a set of 2500 subjects from UK Biobank. We demonstrate the performance of the method for the tasks of classification between matching and non-matching graphs, as well as individual subject classification and manifold learning, showing that it leads to significantly improved results compared to traditional methods. Copyright © 2017 Elsevier Inc. All rights reserved.
Application of kernel functions for accurate similarity search in large chemical databases.

PubMed

Wang, Xiaohong; Huan, Jun; Smalter, Aaron; Lushington, Gerald H

2010-04-29

Similarity search in chemical structure databases is an important problem with many applications in chemical genomics, drug design, and efficient chemical probe screening among others. It is widely believed that structure based methods provide an efficient way to do the query. Recently various graph kernel functions have been designed to capture the intrinsic similarity of graphs. Though successful in constructing accurate predictive and classification models, graph kernel functions can not be applied to large chemical compound database due to the high computational complexity and the difficulties in indexing similarity search for large databases. To bridge graph kernel function and similarity search in chemical databases, we applied a novel kernel-based similarity measurement, developed in our team, to measure similarity of graph represented chemicals. In our method, we utilize a hash table to support new graph kernel function definition, efficient storage and fast search. We have applied our method, named G-hash, to large chemical databases. Our results show that the G-hash method achieves state-of-the-art performance for k-nearest neighbor (k-NN) classification. Moreover, the similarity measurement and the index structure is scalable to large chemical databases with smaller indexing size, and faster query processing time as compared to state-of-the-art indexing methods such as Daylight fingerprints, C-tree and GraphGrep. Efficient similarity query processing method for large chemical databases is challenging since we need to balance running time efficiency and similarity search accuracy. Our previous similarity search method, G-hash, provides a new way to perform similarity search in chemical databases. Experimental study validates the utility of G-hash in chemical databases.
Local zeta factors and geometries under Spec Z

NASA Astrophysics Data System (ADS)

Manin, Yu I.

2016-08-01

The first part of this note shows that the odd-period polynomial of each Hecke cusp eigenform for the full modular group produces via the Rodriguez-Villegas transform ([1]) a polynomial satisfying the functional equation of zeta type and having non-trivial zeros only in the middle line of its critical strip. The second part discusses the Chebyshev lambda-structure of the polynomial ring as Borger's descent data to \\mathbf{F}_1 and suggests its role in a possible relation of the Γ\\mathbf{R}-factor to 'real geometry over \\mathbf{F}_1' (cf. [2]).
Theoretical Investigation of Thermo-Mechanical Behavior of Carbon Nanotube-Based Composites Using the Integral Transform Method

NASA Technical Reports Server (NTRS)

Pawloski, Janice S.

2001-01-01

This project uses the integral transform technique to model the problem of nanotube behavior as an axially symmetric system of shells. Assuming that the nanotube behavior can be described by the equations of elasticity, we seek a stress function x which satisfies the biharmonic equation: del(exp 4) chi = [partial deriv(r(exp 2)) + partial deriv(r) + partial deriv(z(exp 2))] chi = 0. The method of integral transformations is used to transform the differential equation. The symmetry with respect to the z-axis indicates that we only need to consider the sine transform of the stress function: X(bar)(r,zeta) = integral(from 0 to infinity) chi(r,z)sin(zeta,z) dz.
BioGraph: unsupervised biomedical knowledge discovery via automated hypothesis generation

PubMed Central

2011-01-01

We present BioGraph, a data integration and data mining platform for the exploration and discovery of biomedical information. The platform offers prioritizations of putative disease genes, supported by functional hypotheses. We show that BioGraph can retrospectively confirm recently discovered disease genes and identify potential susceptibility genes, outperforming existing technologies, without requiring prior domain knowledge. Additionally, BioGraph allows for generic biomedical applications beyond gene discovery. BioGraph is accessible at http://www.biograph.be. PMID:21696594
On the modular structure of the genus-one Type II superstring low energy expansion

NASA Astrophysics Data System (ADS)

D'Hoker, Eric; Green, Michael B.; Vanhove, Pierre

2015-08-01

The analytic contribution to the low energy expansion of Type II string amplitudes at genus-one is a power series in space-time derivatives with coefficients that are determined by integrals of modular functions over the complex structure modulus of the world-sheet torus. These modular functions are associated with world-sheet vacuum Feynman diagrams and given by multiple sums over the discrete momenta on the torus. In this paper we exhibit exact differential and algebraic relations for a certain infinite class of such modular functions by showing that they satisfy Laplace eigenvalue equations with inhomogeneous terms that are polynomial in non-holomorphic Eisenstein series. Furthermore, we argue that the set of modular functions that contribute to the coefficients of interactions up to order are linear sums of functions in this class and quadratic polynomials in Eisenstein series and odd Riemann zeta values. Integration over the complex structure results in coefficients of the low energy expansion that are rational numbers multiplying monomials in odd Riemann zeta values.

Lung vessel segmentation in CT images using graph-cuts

NASA Astrophysics Data System (ADS)

Zhai, Zhiwei; Staring, Marius; Stoel, Berend C.

2016-03-01

Accurate lung vessel segmentation is an important operation for lung CT analysis. Filters that are based on analyzing the eigenvalues of the Hessian matrix are popular for pulmonary vessel enhancement. However, due to their low response at vessel bifurcations and vessel boundaries, extracting lung vessels by thresholding the vesselness is not sufficiently accurate. Some methods turn to graph-cuts for more accurate segmentation, as it incorporates neighbourhood information. In this work, we propose a new graph-cuts cost function combining appearance and shape, where CT intensity represents appearance and vesselness from a Hessian-based filter represents shape. Due to the amount of voxels in high resolution CT scans, the memory requirement and time consumption for building a graph structure is very high. In order to make the graph representation computationally tractable, those voxels that are considered clearly background are removed from the graph nodes, using a threshold on the vesselness map. The graph structure is then established based on the remaining voxel nodes, source/sink nodes and the neighbourhood relationship of the remaining voxels. Vessels are segmented by minimizing the energy cost function with the graph-cuts optimization framework. We optimized the parameters used in the graph-cuts cost function and evaluated the proposed method with two manually labeled sub-volumes. For independent evaluation, we used 20 CT scans of the VESSEL12 challenge. The evaluation results of the sub-volume data show that the proposed method produced a more accurate vessel segmentation compared to the previous methods, with F1 score 0.76 and 0.69. In the VESSEL12 data-set, our method obtained a competitive performance with an area under the ROC curve of 0.975, especially among the binary submissions.
A toxin-antitoxin module as a target for antimicrobial development.

PubMed

Lioy, Virginia S; Rey, Oscar; Balsa, Dolors; Pellicer, Teresa; Alonso, Juan C

2010-01-01

The emergence and spread of pathogenic bacteria that have become resistant to multiple antibiotics through lateral gene transfer have created the need of novel antimicrobials. Toxin-antitoxin (TA) modules, which have been implicated in plasmid maintenance and stress management, are ubiquitous among plasmids from vancomycin or methicillin resistant bacteria. In the Streptococcus pyogenes pSM19035-encoded TA loci, the labile epsilon antitoxin binds to free zeta toxin and neutralizes it. When the zeta toxin is freed from the epsilon antitoxin, it induces a reversible state of growth arrest with a drastic reduction on the rate of replication, transcription and translation. However, upon prolonged zeta toxin action, the cells can no longer be rescued from their stasis state. A compound that disrupts the epsilon.zeta interaction can be considered as an attractive antimicrobial agent. Gene epsilon was fused to luc (Luc-epsilon antitoxin) and zeta to the gfp gene (zeta-GFP). Luc-epsilon or epsilon antitoxin neutralizes the toxic effect of the zeta or zeta-GFP toxin. In the absence of the antitoxin, free zeta or zeta-GFP triggers a reversible loss of cell proliferation, but the zetaK46A-GFP variant fails to block growth. Bioluminescence resonance energy transfer (BRET) assay was developed for high-throughput screening (HTS). To develop the proper controls, molecular dynamics studies were used to predict that the Asp18 and/or Glu22 residues might be relevant for epsilon.zeta interaction. Luc-epsilon efficiently transfers the excited energy to the fluorescent acceptor molecule (zeta-GFP or zetaK46A-GFP) and rendered high bioluminescence BRET signals. The exchange of Asp18 to Ala from zeta (D18A) affects Luc-epsilon.zetaD18A K46A-GFP interaction. In this study, we validate the hypothesis that it is possible to disrupt a TA module and offer a novel and unexploited targets to fight against antibiotic-resistant strains. Copyright 2009 Elsevier Inc. All rights reserved.
Development of a novel in silico model of zeta potential for metal oxide nanoparticles: a nano-QSPR approach

NASA Astrophysics Data System (ADS)

Wyrzykowska, Ewelina; Mikolajczyk, Alicja; Sikorska, Celina; Puzyn, Tomasz

2016-11-01

Once released into the aquatic environment, nanoparticles (NPs) are expected to interact (e.g. dissolve, agglomerate/aggregate, settle), with important consequences for NP fate and toxicity. A clear understanding of how internal and environmental factors influence the NP toxicity and fate in the environment is still in its infancy. In this study, a quantitative structure-property relationship (QSPR) approach was employed to systematically explore factors that affect surface charge (zeta potential) under environmentally realistic conditions. The nano-QSPR model developed with multiple linear regression (MLR) was characterized by high robustness ({{{Q}}{{2}}}{{CV}}=0.90) and external predictivity ({{{Q}}{{2}}}{{EXT}}=0.93). The results clearly showed that zeta potential values varied markedly as functions of the ionic radius of the metal atom in the metal oxides, confirming that agglomeration and the extent of release of free MexOy largely depend on their intrinsic properties. A developed nano-QSPR model was successfully applied to predict zeta potential in an ionized solution of NPs for which experimentally determined values of response have been unavailable. Hence, the application of our model is possible when the values of zeta potential in the ionized solution for metal oxide nanoparticles are undetermined, without the necessity of performing more time consuming and expensive experiments. We believe that our studies will be helpful in predicting the conditions under which MexOy is likely to become problematic for the environment and human health.
Reproducibility of graph metrics of human brain structural networks.

PubMed

Duda, Jeffrey T; Cook, Philip A; Gee, James C

2014-01-01

Recent interest in human brain connectivity has led to the application of graph theoretical analysis to human brain structural networks, in particular white matter connectivity inferred from diffusion imaging and fiber tractography. While these methods have been used to study a variety of patient populations, there has been less examination of the reproducibility of these methods. A number of tractography algorithms exist and many of these are known to be sensitive to user-selected parameters. The methods used to derive a connectivity matrix from fiber tractography output may also influence the resulting graph metrics. Here we examine how these algorithm and parameter choices influence the reproducibility of proposed graph metrics on a publicly available test-retest dataset consisting of 21 healthy adults. The dice coefficient is used to examine topological similarity of constant density subgraphs both within and between subjects. Seven graph metrics are examined here: mean clustering coefficient, characteristic path length, largest connected component size, assortativity, global efficiency, local efficiency, and rich club coefficient. The reproducibility of these network summary measures is examined using the intraclass correlation coefficient (ICC). Graph curves are created by treating the graph metrics as functions of a parameter such as graph density. Functional data analysis techniques are used to examine differences in graph measures that result from the choice of fiber tracking algorithm. The graph metrics consistently showed good levels of reproducibility as measured with ICC, with the exception of some instability at low graph density levels. The global and local efficiency measures were the most robust to the choice of fiber tracking algorithm.
Fractal dimensions of graph of Weierstrass-type function and local Hölder exponent spectra

NASA Astrophysics Data System (ADS)

Otani, Atsuya

2018-01-01

We study several fractal properties of the Weierstrass-type function where τ :[0, 1)\\to[0, 1) is a cookie cutter map with possibly fractal repeller, and λ and g are functions with proper regularity. In the first part, we determine the box dimension of the graph of W and Hausdorff dimension of its randomised version. In the second part, the Hausdorff spectrum of the local Hölder exponent is characterised in terms of thermodynamic formalism. Furthermore, in the randomised case, a novel formula for the lifted Hausdorff spectrum on the graph is provided.
Quantitative evaluation of simulated functional brain networks in graph theoretical analysis.

PubMed

Lee, Won Hee; Bullmore, Ed; Frangou, Sophia

2017-02-01

There is increasing interest in the potential of whole-brain computational models to provide mechanistic insights into resting-state brain networks. It is therefore important to determine the degree to which computational models reproduce the topological features of empirical functional brain networks. We used empirical connectivity data derived from diffusion spectrum and resting-state functional magnetic resonance imaging data from healthy individuals. Empirical and simulated functional networks, constrained by structural connectivity, were defined based on 66 brain anatomical regions (nodes). Simulated functional data were generated using the Kuramoto model in which each anatomical region acts as a phase oscillator. Network topology was studied using graph theory in the empirical and simulated data. The difference (relative error) between graph theory measures derived from empirical and simulated data was then estimated. We found that simulated data can be used with confidence to model graph measures of global network organization at different dynamic states and highlight the sensitive dependence of the solutions obtained in simulated data on the specified connection densities. This study provides a method for the quantitative evaluation and external validation of graph theory metrics derived from simulated data that can be used to inform future study designs. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.
Functional connectivity and graph theory in preclinical Alzheimer's disease.

PubMed

Brier, Matthew R; Thomas, Jewell B; Fagan, Anne M; Hassenstab, Jason; Holtzman, David M; Benzinger, Tammie L; Morris, John C; Ances, Beau M

2014-04-01

Alzheimer's disease (AD) has a long preclinical phase in which amyloid and tau cerebral pathology accumulate without producing cognitive symptoms. Resting state functional connectivity magnetic resonance imaging has demonstrated that brain networks degrade during symptomatic AD. It is unclear to what extent these degradations exist before symptomatic onset. In this study, we investigated graph theory metrics of functional integration (path length), functional segregation (clustering coefficient), and functional distinctness (modularity) as a function of disease severity. Further, we assessed whether these graph metrics were affected in cognitively normal participants with cerebrospinal fluid evidence of preclinical AD. Clustering coefficient and modularity, but not path length, were reduced in AD. Cognitively normal participants who harbored AD biomarker pathology also showed reduced values in these graph measures, demonstrating brain changes similar to, but smaller than, symptomatic AD. Only modularity was significantly affected by age. We also demonstrate that AD has a particular effect on hub-like regions in the brain. We conclude that AD causes large-scale disconnection that is present before onset of symptoms. Copyright © 2014 Elsevier Inc. All rights reserved.
Entropy of spatial network ensembles

NASA Astrophysics Data System (ADS)

Coon, Justin P.; Dettmann, Carl P.; Georgiou, Orestis

2018-04-01

We analyze complexity in spatial network ensembles through the lens of graph entropy. Mathematically, we model a spatial network as a soft random geometric graph, i.e., a graph with two sources of randomness, namely nodes located randomly in space and links formed independently between pairs of nodes with probability given by a specified function (the "pair connection function") of their mutual distance. We consider the general case where randomness arises in node positions as well as pairwise connections (i.e., for a given pair distance, the corresponding edge state is a random variable). Classical random geometric graph and exponential graph models can be recovered in certain limits. We derive a simple bound for the entropy of a spatial network ensemble and calculate the conditional entropy of an ensemble given the node location distribution for hard and soft (probabilistic) pair connection functions. Under this formalism, we derive the connection function that yields maximum entropy under general constraints. Finally, we apply our analytical framework to study two practical examples: ad hoc wireless networks and the US flight network. Through the study of these examples, we illustrate that both exhibit properties that are indicative of nearly maximally entropic ensembles.
GOGrapher: A Python library for GO graph representation and analysis.

PubMed

Muller, Brian; Richards, Adam J; Jin, Bo; Lu, Xinghua

2009-07-07

The Gene Ontology is the most commonly used controlled vocabulary for annotating proteins. The concepts in the ontology are organized as a directed acyclic graph, in which a node corresponds to a biological concept and a directed edge denotes the parent-child semantic relationship between a pair of terms. A large number of protein annotations further create links between proteins and their functional annotations, reflecting the contemporary knowledge about proteins and their functional relationships. This leads to a complex graph consisting of interleaved biological concepts and their associated proteins. What is needed is a simple, open source library that provides tools to not only create and view the Gene Ontology graph, but to analyze and manipulate it as well. Here we describe the development and use of GOGrapher, a Python library that can be used for the creation, analysis, manipulation, and visualization of Gene Ontology related graphs. An object-oriented approach was adopted to organize the hierarchy of the graphs types and associated classes. An Application Programming Interface is provided through which different types of graphs can be pragmatically created, manipulated, and visualized. GOGrapher has been successfully utilized in multiple research projects, e.g., a graph-based multi-label text classifier for protein annotation. The GOGrapher project provides a reusable programming library designed for the manipulation and analysis of Gene Ontology graphs. The library is freely available for the scientific community to use and improve.
Scale-space measures for graph topology link protein network architecture to function.

PubMed

Hulsman, Marc; Dimitrakopoulos, Christos; de Ridder, Jeroen

2014-06-15

The network architecture of physical protein interactions is an important determinant for the molecular functions that are carried out within each cell. To study this relation, the network architecture can be characterized by graph topological characteristics such as shortest paths and network hubs. These characteristics have an important shortcoming: they do not take into account that interactions occur across different scales. This is important because some cellular functions may involve a single direct protein interaction (small scale), whereas others require more and/or indirect interactions, such as protein complexes (medium scale) and interactions between large modules of proteins (large scale). In this work, we derive generalized scale-aware versions of known graph topological measures based on diffusion kernels. We apply these to characterize the topology of networks across all scales simultaneously, generating a so-called graph topological scale-space. The comprehensive physical interaction network in yeast is used to show that scale-space based measures consistently give superior performance when distinguishing protein functional categories and three major types of functional interactions-genetic interaction, co-expression and perturbation interactions. Moreover, we demonstrate that graph topological scale spaces capture biologically meaningful features that provide new insights into the link between function and protein network architecture. Matlab(TM) code to calculate the scale-aware topological measures (STMs) is available at http://bioinformatics.tudelft.nl/TSSA © The Author 2014. Published by Oxford University Press.
Change of Brain Functional Connectivity in Patients With Spinal Cord Injury: Graph Theory Based Approach.

PubMed

Min, Yu-Sun; Chang, Yongmin; Park, Jang Woo; Lee, Jong-Min; Cha, Jungho; Yang, Jin-Ju; Kim, Chul-Hyun; Hwang, Jong-Moon; Yoo, Ji-Na; Jung, Tae-Du

2015-06-01

To investigate the global functional reorganization of the brain following spinal cord injury with graph theory based approach by creating whole brain functional connectivity networks from resting state-functional magnetic resonance imaging (rs-fMRI), characterizing the reorganization of these networks using graph theoretical metrics and to compare these metrics between patients with spinal cord injury (SCI) and age-matched controls. Twenty patients with incomplete cervical SCI (14 males, 6 females; age, 55±14.1 years) and 20 healthy subjects (10 males, 10 females; age, 52.9±13.6 years) participated in this study. To analyze the characteristics of the whole brain network constructed with functional connectivity using rs-fMRI, graph theoretical measures were calculated including clustering coefficient, characteristic path length, global efficiency and small-worldness. Clustering coefficient, global efficiency and small-worldness did not show any difference between controls and SCIs in all density ranges. The normalized characteristic path length to random network was higher in SCI patients than in controls and reached statistical significance at 12%-13% of density (p<0.05, uncorrected). The graph theoretical approach in brain functional connectivity might be helpful to reveal the information processing after SCI. These findings imply that patients with SCI can build on preserved competent brain control. Further analyses, such as topological rearrangement and hub region identification, will be needed for better understanding of neuroplasticity in patients with SCI.
Multiclass Data Segmentation Using Diffuse Interface Methods on Graphs

DTIC Science & Technology

2014-01-01

interac- tive image segmentation using the solution to a combinatorial Dirichlet problem. Elmoataz et al . have developed general- izations of the graph...Laplacian [25] for image denoising and manifold smoothing. Couprie et al . in [18] define a conve- niently parameterized graph-based energy function that...over to the discrete graph representation. For general data segmentation, Bresson et al . in [8], present rigorous convergence results for two algorithms
Moments of zeta functions associated to hyperelliptic curves over finite fields

PubMed Central

Rubinstein, Michael O.; Wu, Kaiyu

2015-01-01

Let q be an odd prime power, and denote the set of square-free monic polynomials D(x)∈Fq[x] of degree d. Katz and Sarnak showed that the moments, over , of the zeta functions associated to the curves y2=D(x), evaluated at the central point, tend, as , to the moments of characteristic polynomials, evaluated at the central point, of matrices in USp(2⌊(d−1)/2⌋). Using techniques that were originally developed for studying moments of L-functions over number fields, Andrade and Keating conjectured an asymptotic formula for the moments for q fixed and . We provide theoretical and numerical evidence in favour of their conjecture. In some cases, we are able to work out exact formulae for the moments and use these to precisely determine the size of the remainder term in the predicted moments. PMID:25802418
Graph Kernels for Molecular Similarity.

PubMed

Rupp, Matthias; Schneider, Gisbert

2010-04-12

Molecular similarity measures are important for many cheminformatics applications like ligand-based virtual screening and quantitative structure-property relationships. Graph kernels are formal similarity measures defined directly on graphs, such as the (annotated) molecular structure graph. Graph kernels are positive semi-definite functions, i.e., they correspond to inner products. This property makes them suitable for use with kernel-based machine learning algorithms such as support vector machines and Gaussian processes. We review the major types of kernels between graphs (based on random walks, subgraphs, and optimal assignments, respectively), and discuss their advantages, limitations, and successful applications in cheminformatics. Copyright © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Methotrexate loading in chitosan nanoparticles at a novel pH: Response surface modeling, optimization and characterization.

PubMed

Hashad, Rania A; Ishak, Rania A H; Geneidi, Ahmed S; Mansour, Samar

2016-10-01

The aim of this study was to assess the feasibility of employing a novel but critical formulation pH (6.2) to encapsulate an anionic model drug (methotrexate, MTX) into chitosan(Cs)-tripolyphosphate nanoparticles(NPs). A response surface methodology using a three-level full factorial design was applied studying the effects of two independent variables namely; Cs concentration and MTX concentration. The responses investigated were the entrapment efficiency (EE%), mean hydrodynamic particle size (PS), polydispersity index (PDI) and zeta potential (ZP). In order to simultaneously optimize the series of models obtained, the desirability function approach was applied with a goal to produce high percent of MTX encapsulated into highly charged Cs-TPP NPs of homogenous optimum PS. MTX-loaded CsNPs were successfully prepared at the novel pH applied. The suggested significant models were found quadratic for EE, PS and ZP responses, while 2-factor interaction model for PDI. The optimization overlay graph showed that the maximum global desirability, D=0.856, was reached when the conditions were set at high Cs and MTX concentration. Thus, the use of such optimized conditions, at this novel pH, achieved a maximum drug EE% (73.38%) into NPs characterized by optimum PS (232.6nm), small PDI value (0.195) and highly surface charged (+18.4mV). Copyright © 2016 Elsevier B.V. All rights reserved.
Similarity-balanced discriminant neighbor embedding and its application to cancer classification based on gene expression data.

PubMed

Zhang, Li; Qian, Liqiang; Ding, Chuntao; Zhou, Weida; Li, Fanzhang

2015-09-01

The family of discriminant neighborhood embedding (DNE) methods is typical graph-based methods for dimension reduction, and has been successfully applied to face recognition. This paper proposes a new variant of DNE, called similarity-balanced discriminant neighborhood embedding (SBDNE) and applies it to cancer classification using gene expression data. By introducing a novel similarity function, SBDNE deals with two data points in the same class and the different classes with different ways. The homogeneous and heterogeneous neighbors are selected according to the new similarity function instead of the Euclidean distance. SBDNE constructs two adjacent graphs, or between-class adjacent graph and within-class adjacent graph, using the new similarity function. According to these two adjacent graphs, we can generate the local between-class scatter and the local within-class scatter, respectively. Thus, SBDNE can maximize the between-class scatter and simultaneously minimize the within-class scatter to find the optimal projection matrix. Experimental results on six microarray datasets show that SBDNE is a promising method for cancer classification. Copyright © 2015 Elsevier Ltd. All rights reserved.
Stationary waves on nonlinear quantum graphs. II. Application of canonical perturbation theory in basic graph structures.

PubMed

Gnutzmann, Sven; Waltner, Daniel

2016-12-01

We consider exact and asymptotic solutions of the stationary cubic nonlinear Schrödinger equation on metric graphs. We focus on some basic example graphs. The asymptotic solutions are obtained using the canonical perturbation formalism developed in our earlier paper [S. Gnutzmann and D. Waltner, Phys. Rev. E 93, 032204 (2016)2470-004510.1103/PhysRevE.93.032204]. For closed example graphs (interval, ring, star graph, tadpole graph), we calculate spectral curves and show how the description of spectra reduces to known characteristic functions of linear quantum graphs in the low-intensity limit. Analogously for open examples, we show how nonlinear scattering of stationary waves arises and how it reduces to known linear scattering amplitudes at low intensities. In the short-wavelength asymptotics we discuss how genuine nonlinear effects may be described using the leading order of canonical perturbation theory: bifurcation of spectral curves (and the corresponding solutions) in closed graphs and multistability in open graphs.
The Full Ward-Takahashi Identity for Colored Tensor Models

NASA Astrophysics Data System (ADS)

Pérez-Sánchez, Carlos I.

2018-03-01

Colored tensor models (CTM) is a random geometrical approach to quantum gravity. We scrutinize the structure of the connected correlation functions of general CTM-interactions and organize them by boundaries of Feynman graphs. For rank- D interactions including, but not restricted to, all melonic φ^4 -vertices—to wit, solely those quartic vertices that can lead to dominant spherical contributions in the large- N expansion—the aforementioned boundary graphs are shown to be precisely all (possibly disconnected) vertex-bipartite regularly edge- D-colored graphs. The concept of CTM-compatible boundary-graph automorphism is introduced and an auxiliary graph calculus is developed. With the aid of these constructs, certain U (∞)-invariance of the path integral measure is fully exploited in order to derive a strong Ward-Takahashi Identity for CTMs with a symmetry-breaking kinetic term. For the rank-3 φ^4 -theory, we get the exact integral-like equation for the 2-point function. Similarly, exact equations for higher multipoint functions can be readily obtained departing from this full Ward-Takahashi identity. Our results hold for some Group Field Theories as well. Altogether, our non-perturbative approach trades some graph theoretical methods for analytical ones. We believe that these tools can be extended to tensorial SYK-models.
Applied Graph-Mining Algorithms to Study Biomolecular Interaction Networks

PubMed Central

2014-01-01

Protein-protein interaction (PPI) networks carry vital information on the organization of molecular interactions in cellular systems. The identification of functionally relevant modules in PPI networks is one of the most important applications of biological network analysis. Computational analysis is becoming an indispensable tool to understand large-scale biomolecular interaction networks. Several types of computational methods have been developed and employed for the analysis of PPI networks. Of these computational methods, graph comparison and module detection are the two most commonly used strategies. This review summarizes current literature on graph kernel and graph alignment methods for graph comparison strategies, as well as module detection approaches including seed-and-extend, hierarchical clustering, optimization-based, probabilistic, and frequent subgraph methods. Herein, we provide a comprehensive review of the major algorithms employed under each theme, including our recently published frequent subgraph method, for detecting functional modules commonly shared across multiple cancer PPI networks. PMID:24800226
Detecting community structure via the maximal sub-graphs and belonging degrees in complex networks

NASA Astrophysics Data System (ADS)

Cui, Yaozu; Wang, Xingyuan; Eustace, Justine

2014-12-01

Community structure is a common phenomenon in complex networks, and it has been shown that some communities in complex networks often overlap each other. So in this paper we propose a new algorithm to detect overlapping community structure in complex networks. To identify the overlapping community structure, our algorithm firstly extracts fully connected sub-graphs which are maximal sub-graphs from original networks. Then two maximal sub-graphs having the key pair-vertices can be merged into a new larger sub-graph using some belonging degree functions. Furthermore we extend the modularity function to evaluate the proposed algorithm. In addition, overlapping nodes between communities are founded successfully. Finally we report the comparison between the modularity and the computational complexity of the proposed algorithm with some other existing algorithms. The experimental results show that the proposed algorithm gives satisfactory results.

Functional determinants of radial operators in AdS2

DOE PAGES

Aguilera-Damia, Jeremías; Faraggi, Alberto; Zayas, Leopoldo Pando; ...

2018-06-01

We study the zeta-function regularization of functional determinants of Laplace and Dirac-type operators in two-dimensional Euclidean AdS2 space. More specifically, we consider the ratio of determinants between an operator in the presence of background fields with circular symmetry and the free operator in which the background fields are absent. By Fourier-transforming the angular dependence, one obtains an infinite number of one-dimensional radial operators, the determinants of which are easy to compute. The summation over modes is then treated with care so as to guarantee that the result coincides with the two-dimensional zeta-function formalism. The method relies on some well-known techniquesmore » to compute functional determinants using contour integrals and the construction of the Jost function from scattering theory. Our work generalizes some known results in flat space. The extension to conformal AdS2 geometries is also considered. We provide two examples, one bosonic and one fermionic, borrowed from the spectrum of fluctuations of the holographic 1/4-BPS latitude Wilson loop.« less
Stimulation and inhibition of enzymatic hydrolysis by organosolv lignins as determined by zeta potential and hydrophobicity.

PubMed

Huang, Yang; Sun, Shaolong; Huang, Chen; Yong, Qiang; Elder, Thomas; Tu, Maobing

2017-01-01

Lignin typically inhibits enzymatic hydrolysis of cellulosic biomass, but certain organosolv lignins or lignosulfonates enhance enzymatic hydrolysis. The hydrophobic and electrostatic interactions between lignin and cellulases play critical roles in the enzymatic hydrolysis process. However, how to incorporate these two interactions into the consideration of lignin effects has not been investigated. We examined the physicochemical properties and the structures of ethanol organosolv lignins (EOL) from hardwood and softwood and ascertained the association between lignin properties and their inhibitory and stimulatory effects on enzymatic hydrolysis. The zeta potential and hydrophobicity of EOL lignin samples, isolated from organosolv pretreatment of cottonwood (CW), black willow (BW), aspen (AS), eucalyptus (EH), and loblolly pine (LP), were determined and correlated with their effects on enzymatic hydrolysis of Avicel. EOLs from CW, BW, and AS improved the 72 h hydrolysis yield by 8-12%, while EOLs from EH and LP decreased the 72 h hydrolysis yield by 6 and 16%, respectively. The results showed a strong correlation between the 72 h hydrolysis yield with hydrophobicity and zeta potential. The correlation indicated that the hydrophobicity of EOL had a negative effect and the negative zeta potential of EOL had a positive effect. HSQC NMR spectra showed that β- O -4 linkages in lignin react with ethanol to form an α -ethoxylated β- O -4' substructure (A') during organosolv pretreatment. Considerable amounts of C 2,6 -H 2,6 correlation in p -hydroxybenzoate (PB) units were observed for EOL-CW, EOL-BW, and EOL-AS, but not for EOL-EH and EOL-LP. This study revealed that the effect of lignin on enzymatic hydrolysis is a function of both hydrophobic interactions and electrostatic repulsions. The lignin inhibition is controlled by lignin hydrophobicity and the lignin stimulation is governed by the negative zeta potential. The net effect of lignin depends on the combined influence of hydrophobicity and zeta potential. This study has potential implications in biomass pretreatment for the reduction of lignin inhibition by increasing lignin negative zeta potential and decreasing hydrophobicity.
Hierarchical graphs for rule-based modeling of biochemical systems

PubMed Central

2011-01-01

Background In rule-based modeling, graphs are used to represent molecules: a colored vertex represents a component of a molecule, a vertex attribute represents the internal state of a component, and an edge represents a bond between components. Components of a molecule share the same color. Furthermore, graph-rewriting rules are used to represent molecular interactions. A rule that specifies addition (removal) of an edge represents a class of association (dissociation) reactions, and a rule that specifies a change of a vertex attribute represents a class of reactions that affect the internal state of a molecular component. A set of rules comprises an executable model that can be used to determine, through various means, the system-level dynamics of molecular interactions in a biochemical system. Results For purposes of model annotation, we propose the use of hierarchical graphs to represent structural relationships among components and subcomponents of molecules. We illustrate how hierarchical graphs can be used to naturally document the structural organization of the functional components and subcomponents of two proteins: the protein tyrosine kinase Lck and the T cell receptor (TCR) complex. We also show that computational methods developed for regular graphs can be applied to hierarchical graphs. In particular, we describe a generalization of Nauty, a graph isomorphism and canonical labeling algorithm. The generalized version of the Nauty procedure, which we call HNauty, can be used to assign canonical labels to hierarchical graphs or more generally to graphs with multiple edge types. The difference between the Nauty and HNauty procedures is minor, but for completeness, we provide an explanation of the entire HNauty algorithm. Conclusions Hierarchical graphs provide more intuitive formal representations of proteins and other structured molecules with multiple functional components than do the regular graphs of current languages for specifying rule-based models, such as the BioNetGen language (BNGL). Thus, the proposed use of hierarchical graphs should promote clarity and better understanding of rule-based models. PMID:21288338
Graph drawing using tabu search coupled with path relinking

PubMed Central

Rodgers, Peter

2018-01-01

Graph drawing, or the automatic layout of graphs, is a challenging problem. There are several search based methods for graph drawing which are based on optimizing an objective function which is formed from a weighted sum of multiple criteria. In this paper, we propose a new neighbourhood search method which uses a tabu search coupled with path relinking to optimize such objective functions for general graph layouts with undirected straight lines. To our knowledge, before our work, neither of these methods have been previously used in general multi-criteria graph drawing. Tabu search uses a memory list to speed up searching by avoiding previously tested solutions, while the path relinking method generates new solutions by exploring paths that connect high quality solutions. We use path relinking periodically within the tabu search procedure to speed up the identification of good solutions. We have evaluated our new method against the commonly used neighbourhood search optimization techniques: hill climbing and simulated annealing. Our evaluation examines the quality of the graph layout (objective function’s value) and the speed of layout in terms of the number of evaluated solutions required to draw a graph. We also examine the relative scalability of each method. Our experimental results were applied to both random graphs and a real-world dataset. We show that our method outperforms both hill climbing and simulated annealing by producing a better layout in a lower number of evaluated solutions. In addition, we demonstrate that our method has greater scalability as it can layout larger graphs than the state-of-the-art neighbourhood search methods. Finally, we show that similar results can be produced in a real world setting by testing our method against a standard public graph dataset. PMID:29746576
Method for concurrent execution of primitive operations by dynamically assigning operations based upon computational marked graph and availability of data

NASA Technical Reports Server (NTRS)

Mielke, Roland V. (Inventor); Stoughton, John W. (Inventor)

1990-01-01

Computationally complex primitive operations of an algorithm are executed concurrently in a plurality of functional units under the control of an assignment manager. The algorithm is preferably defined as a computationally marked graph contianing data status edges (paths) corresponding to each of the data flow edges. The assignment manager assigns primitive operations to the functional units and monitors completion of the primitive operations to determine data availability using the computational marked graph of the algorithm. All data accessing of the primitive operations is performed by the functional units independently of the assignment manager.
Novel Method for Finding [zeta](2[rho]) from a Product of Sines

ERIC Educational Resources Information Center

Osler, Thomas J.

2006-01-01

Euler gave a simple method for showing that [zeta](2)=1/1[superscript 2] + 1/2[superscript 2] + 1/3[superscript 2] + ... = [pi][superscript 2]/6. He generalized his method so as to find [zeta](4), [zeta](6), [zeta](8),.... His computations became increasingly more complex as the arguments increased. In this note we show a different generalization…
Mapping the functional connectome in traumatic brain injury: What can graph metrics tell us?

PubMed

Caeyenberghs, Karen; Verhelst, Helena; Clemente, Adam; Wilson, Peter H

2017-10-15

Traumatic brain injury (TBI) is associated with cognitive and motor deficits, and poses a significant personal, societal, and economic burden. One mechanism by which TBI is thought to affect cognition and behavior is through changes in functional connectivity. Graph theory is a powerful framework for quantifying topological features of neuroimaging-derived functional networks. The objective of this paper is to review studies examining functional connectivity in TBI with an emphasis on graph theoretical analysis that is proving to be valuable in uncovering network abnormalities in this condition. We review studies that have examined TBI-related alterations in different properties of the functional brain network, including global integration, segregation, centrality and resilience. We focus on functional data using task-related fMRI or resting-state fMRI in patients with TBI of different severity and recovery phase, and consider how graph metrics may inform rehabilitation and enhance efficacy. Moreover, we outline some methodological challenges associated with the examination of functional connectivity in patients with brain injury, including the sample size, parcellation scheme used, node definition and subgroup analyses. The findings suggest that TBI is associated with hyperconnectivity and a suboptimal global integration, characterized by increased connectivity degree and strength and reduced efficiency of functional networks. This altered functional connectivity, also evident in other clinical populations, is attributable to diffuse white matter pathology and reductions in gray and white matter volume. These functional alterations are implicated in post-concussional symptoms, posttraumatic stress and neurocognitive dysfunction after TBI. Finally, the effects of focal lesions have been found to depend critically on topological position and their role in the network. Graph theory is a unique and powerful tool for exploring functional connectivity in brain-injured patients. One limitation is that its results do not provide specific measures about the biophysical mechanism underlying TBI. Continued work in this field will hopefully see graph metrics used as biomarkers to provide more accurate diagnosis and help guide treatment at the individual patient level. Copyright © 2016. Published by Elsevier Inc.
GOGrapher: A Python library for GO graph representation and analysis

PubMed Central

Muller, Brian; Richards, Adam J; Jin, Bo; Lu, Xinghua

2009-01-01

Background The Gene Ontology is the most commonly used controlled vocabulary for annotating proteins. The concepts in the ontology are organized as a directed acyclic graph, in which a node corresponds to a biological concept and a directed edge denotes the parent-child semantic relationship between a pair of terms. A large number of protein annotations further create links between proteins and their functional annotations, reflecting the contemporary knowledge about proteins and their functional relationships. This leads to a complex graph consisting of interleaved biological concepts and their associated proteins. What is needed is a simple, open source library that provides tools to not only create and view the Gene Ontology graph, but to analyze and manipulate it as well. Here we describe the development and use of GOGrapher, a Python library that can be used for the creation, analysis, manipulation, and visualization of Gene Ontology related graphs. Findings An object-oriented approach was adopted to organize the hierarchy of the graphs types and associated classes. An Application Programming Interface is provided through which different types of graphs can be pragmatically created, manipulated, and visualized. GOGrapher has been successfully utilized in multiple research projects, e.g., a graph-based multi-label text classifier for protein annotation. Conclusion The GOGrapher project provides a reusable programming library designed for the manipulation and analysis of Gene Ontology graphs. The library is freely available for the scientific community to use and improve. PMID:19583843
Weights and topology: a study of the effects of graph construction on 3D image segmentation.

PubMed

Grady, Leo; Jolly, Marie-Pierre

2008-01-01

Graph-based algorithms have become increasingly popular for medical image segmentation. The fundamental process for each of these algorithms is to use the image content to generate a set of weights for the graph and then set conditions for an optimal partition of the graph with respect to these weights. To date, the heuristics used for generating the weighted graphs from image intensities have largely been ignored, while the primary focus of attention has been on the details of providing the partitioning conditions. In this paper we empirically study the effects of graph connectivity and weighting function on the quality of the segmentation results. To control for algorithm-specific effects, we employ both the Graph Cuts and Random Walker algorithms in our experiments.
[A graph cuts-based interactive method for segmentation of magnetic resonance images of meningioma].

PubMed

Li, Shuan-qiang; Feng, Qian-jin; Chen, Wu-fan; Lin, Ya-zhong

2011-06-01

For accurate segmentation of the magnetic resonance (MR) images of meningioma, we propose a novel interactive segmentation method based on graph cuts. The high dimensional image features was extracted, and for each pixel, the probabilities of its origin, either the tumor or the background regions, were estimated by exploiting the weighted K-nearest neighborhood classifier. Based on these probabilities, a new energy function was proposed. Finally, a graph cut optimal framework was used for the solution of the energy function. The proposed method was evaluated by application in the segmentation of MR images of meningioma, and the results showed that the method significantly improved the segmentation accuracy compared with the gray level information-based graph cut method.
smoothG

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barker, Andrew T.; Gelever, Stephan A.; Lee, Chak S.

2017-12-12

smoothG is a collection of parallel C++ classes/functions that algebraically constructs reduced models of different resolutions from a given high-fidelity graph model. In addition, smoothG also provides efficient linear solvers for the reduced models. Other than pure graph problem, the software finds its application in subsurface flow and power grid simulations in which graph Laplacians are found
Learning Mathematics with Interactive Whiteboards and Computer-Based Graphing Utility

ERIC Educational Resources Information Center

Erbas, Ayhan Kursat; Ince, Muge; Kaya, Sukru

2015-01-01

The purpose of this study was to explore the effect of a technology-supported learning environment utilizing an interactive whiteboard (IWB) and NuCalc graphing software compared to a traditional direct instruction-based environment on student achievement in graphs of quadratic functions and attitudes towards mathematics and technology. Sixty-five…
Brain Graph Topology Changes Associated with Anti-Epileptic Drug Use

PubMed Central

Levin, Harvey S.; Chiang, Sharon

2015-01-01

Abstract Neuroimaging studies of functional connectivity using graph theory have furthered our understanding of the network structure in temporal lobe epilepsy (TLE). Brain network effects of anti-epileptic drugs could influence such studies, but have not been systematically studied. Resting-state functional MRI was analyzed in 25 patients with TLE using graph theory analysis. Patients were divided into two groups based on anti-epileptic medication use: those taking carbamazepine/oxcarbazepine (CBZ/OXC) (n=9) and those not taking CBZ/OXC (n=16) as a part of their medication regimen. The following graph topology metrics were analyzed: global efficiency, betweenness centrality (BC), clustering coefficient, and small-world index. Multiple linear regression was used to examine the association of CBZ/OXC with graph topology. The two groups did not differ from each other based on epilepsy characteristics. Use of CBZ/OXC was associated with a lower BC. Longer epilepsy duration was also associated with a lower BC. These findings can inform graph theory-based studies in patients with TLE. The changes observed are discussed in relation to the anti-epileptic mechanism of action and adverse effects of CBZ/OXC. PMID:25492633
Analyzing functional brain connectivity by means of commute times: a new approach and its application to track event-related dynamics.

PubMed

Dimitriadis, S I; Laskaris, N A; Tzelepi, A; Economou, G

2012-05-01

There is growing interest in studying the association of functional connectivity patterns with particular cognitive tasks. The ability of graphs to encapsulate relational data has been exploited in many related studies, where functional networks (sketched by different neural synchrony estimators) are characterized by a rich repertoire of graph-related metrics. We introduce commute times (CTs) as an alternative way to capture the true interplay between the nodes of a functional connectivity graph (FCG). CT is a measure of the time taken for a random walk to setout and return between a pair of nodes on a graph. Its computation is considered here as a robust and accurate integration, over the FCG, of the individual pairwise measurements of functional coupling. To demonstrate the benefits from our approach, we attempted the characterization of time evolving connectivity patterns derived from EEG signals recorded while the subject was engaged in an eye-movement task. With respect to standard ways, which are currently employed to characterize connectivity, an improved detection of event-related dynamical changes is noticeable. CTs appear to be a promising technique for deriving temporal fingerprints of the brain's dynamic functional organization.
Graph analysis of functional brain networks: practical issues in translational neuroscience

PubMed Central

De Vico Fallani, Fabrizio; Richiardi, Jonas; Chavez, Mario; Achard, Sophie

2014-01-01

The brain can be regarded as a network: a connected system where nodes, or units, represent different specialized regions and links, or connections, represent communication pathways. From a functional perspective, communication is coded by temporal dependence between the activities of different brain areas. In the last decade, the abstract representation of the brain as a graph has allowed to visualize functional brain networks and describe their non-trivial topological properties in a compact and objective way. Nowadays, the use of graph analysis in translational neuroscience has become essential to quantify brain dysfunctions in terms of aberrant reconfiguration of functional brain networks. Despite its evident impact, graph analysis of functional brain networks is not a simple toolbox that can be blindly applied to brain signals. On the one hand, it requires the know-how of all the methodological steps of the pipeline that manipulate the input brain signals and extract the functional network properties. On the other hand, knowledge of the neural phenomenon under study is required to perform physiologically relevant analysis. The aim of this review is to provide practical indications to make sense of brain network analysis and contrast counterproductive attitudes. PMID:25180301
Red blood cell membrane viscoelasticity, agglutination and zeta potential measurements with double optical tweezers

NASA Astrophysics Data System (ADS)

Fontes, Adriana; Fernandes, Heloise P.; Barjas-Castro, Maria L.; de Thomaz, André A.; de Ysasa Pozzo, Liliana; Barbosa, Luiz C.; Cesar, Carlos L.

2006-02-01

The red blood cell (RBC) viscoelastic membrane contains proteins and glycolproteins embedded in, or attached, to a fluid lipid bilayer and are negatively charged, which creates a repulsive electric (zeta) potential between the cells and prevents their aggregation in the blood stream. There are techniques, however, to decrease the zeta potential to allow cell agglutination which are the basis of most of the tests of antigen-antibody interactions in blood banks. This report shows the use of a double optical tweezers to measure RBC membrane viscosity, agglutination and zeta potential. In our technique one of the optical tweezers trap a silica bead that binds strongly to a RBC at the end of a RBCs rouleaux and, at the same time, acts as a pico-Newton force transducer, after calibration through its displacement from the equilibrium position. The other optical tweezers trap the RBC at the other end. To measure the membrane viscosity the optical force is measured as a function of the velocity between the RBCs. To measure the adhesion the tweezers are slowly displaced apart until the RBCs disagglutination happens. The RBC zeta potential is measured in two complimentary ways, by the force on the silica bead attached to a single RBC in response to an applied electric field, and the conventional way, by the measurement of terminal velocity of the RBC after released from the optical trap. These two measurements provide information about the RBC charges and, also, electrolytic solution properties. We believe this can improve the methods of diagnosis in blood banks.
Does Type Matter: Evaluating the Effectiveness of Four-Function and Graphing Calculators

ERIC Educational Resources Information Center

Bouck, Emily

2010-01-01

Calculators are a controversial, yet widely used tool in mathematics education for all students and especially for students with disabilities. However, little research has explored calculators and students with disabilities. This paper explored the influence of calculator type (four-function and graphing) on the mathematical performance of…
Effects of age condition on the distribution and integrity of inorganic fillers in dental resin composites.

PubMed

D'Alpino, Paulo Henrique Perlatti; Svizero, Nádia da Rocha; Bim Júnior, Odair; Valduga, Claudete Justina; Graeff, Carlos Frederico de Oliveira; Sauro, Salvatore

2016-06-01

The aim of this study is to evaluate the distribution of the filler size along with the zeta potential, and the integrity of silane-bonded filler surface in different types of restorative dental composites as a function of the material age condition. Filtek P60 (hybrid composite), Filtek Z250 (small-particle filled composite), Filtek Z350XT (nanofilled composite), and Filtek Silorane (silorane composite) (3M ESPE) were tested at different stage condition (i.e., fresh/new, aged, and expired). Composites were submitted to an accelerated aging protocol (Arrhenius model). Specimens were obtained by first diluting each composite specimen in ethanol and then dispersed in potassium chloride solution (0.001 mol%). Composite fillers were characterized for their zeta potential, mean particle size, size distribution, via poly-dispersion dynamic light scattering. The integrity of the silane-bonded surface of the fillers was characterized by FTIR. The material age influenced significantly the outcomes; Zeta potential, filler characteristics, and silane integrity varied both after aging and expiration. Silorane presented the broadest filler distribution and lowest zeta potential. Nanofilled and silorane composites exhibited decreased peak intensities in the FTIR analysis, indicating a deficiency of the silane integrity after aging or expiry time. Regardless to the material condition, the hybrid and the small-particle-filled composites were more stable overtime as no significant alteration in filler size distribution, diameter, and zeta potential occurred. A deficiency in the silane integrity in the nanofilled and silorane composites seems to be affected by the material stage condition. The materials conditions tested in this study influenced the filler size distribution, the zeta potential, and integrity of the silane adsorbed on fillers in the nanofilled and silorane composites. Thus, this may result in a decrease of the clinical performance of aforementioned composites, in particular, if these are used after inappropriate storage conditions.
From brain topography to brain topology: relevance of graph theory to functional neuroscience.

PubMed

Minati, Ludovico; Varotto, Giulia; D'Incerti, Ludovico; Panzica, Ferruccio; Chan, Dennis

2013-07-10

Although several brain regions show significant specialization, higher functions such as cross-modal information integration, abstract reasoning and conscious awareness are viewed as emerging from interactions across distributed functional networks. Analytical approaches capable of capturing the properties of such networks can therefore enhance our ability to make inferences from functional MRI, electroencephalography and magnetoencephalography data. Graph theory is a branch of mathematics that focuses on the formal modelling of networks and offers a wide range of theoretical tools to quantify specific features of network architecture (topology) that can provide information complementing the anatomical localization of areas responding to given stimuli or tasks (topography). Explicit modelling of the architecture of axonal connections and interactions among areas can furthermore reveal peculiar topological properties that are conserved across diverse biological networks, and highly sensitive to disease states. The field is evolving rapidly, partly fuelled by computational developments that enable the study of connectivity at fine anatomical detail and the simultaneous interactions among multiple regions. Recent publications in this area have shown that graph-based modelling can enhance our ability to draw causal inferences from functional MRI experiments, and support the early detection of disconnection and the modelling of pathology spread in neurodegenerative disease, particularly Alzheimer's disease. Furthermore, neurophysiological studies have shown that network topology has a profound link to epileptogenesis and that connectivity indices derived from graph models aid in modelling the onset and spread of seizures. Graph-based analyses may therefore significantly help understand the bases of a range of neurological conditions. This review is designed to provide an overview of graph-based analyses of brain connectivity and their relevance to disease aimed principally at general neuroscientists and clinicians.
The interstellar line spectra of zeta Ophiuchi and zeta Persei and their relation to the short wavelength microwave background radiation. Ph.D. Thesis - N. Y. Univ.

NASA Technical Reports Server (NTRS)

Bortolot, V. J., Jr.

1972-01-01

Thirty-one high dispersion Coude spectrograms of zeta Ophiuchi and seven of zeta Persei were numerically synthesized to produce high resolution, low noise spectra in the interval 3650 A to 4350 that yield data on atomic and molecular absorption in well-defined regions of the interstellar medium. The detection threshold is improved by as much as a factor 5 over single plates. Several interstellar lines were discovered in the zeta Oph - 15km/sec cloud and the zeta Per + 13 km/sec cloud.

A binary linear programming formulation of the graph edit distance.

PubMed

Justice, Derek; Hero, Alfred

2006-08-01

A binary linear programming formulation of the graph edit distance for unweighted, undirected graphs with vertex attributes is derived and applied to a graph recognition problem. A general formulation for editing graphs is used to derive a graph edit distance that is proven to be a metric, provided the cost function for individual edit operations is a metric. Then, a binary linear program is developed for computing this graph edit distance, and polynomial time methods for determining upper and lower bounds on the solution of the binary program are derived by applying solution methods for standard linear programming and the assignment problem. A recognition problem of comparing a sample input graph to a database of known prototype graphs in the context of a chemical information system is presented as an application of the new method. The costs associated with various edit operations are chosen by using a minimum normalized variance criterion applied to pairwise distances between nearest neighbors in the database of prototypes. The new metric is shown to perform quite well in comparison to existing metrics when applied to a database of chemical graphs.
Toxicity and Metabolism of Zeta-Cypermethrin in Field-Collected and Laboratory Strains of the Neotropical Predator Chrysoperla externa Hagen (Neuroptera: Chrysopidae).

PubMed

Haramboure, M; Smagghe, G; Niu, J; Christiaens, O; Spanoghe, P; Alzogaray, R A

2017-06-01

Resistance to pesticides has been studied in several insect pests, but information on the natural enemies of pests-including the Neotropical predator Chrysoperla externa Hagen (Neuroptera: Chrysopidae), a major biological control agent in South America-is lacking. We report here a comparative study between a field-collected strain of C. externa subjected to monthly sprayings of pyrethroids and neonicotinoids and a laboratory strain without exposure to pesticides. The tolerance of both strains against zeta-cypermethrin was similar, and addition of the synergist piperonyl butoxide increased the toxicity by 30% in both strains. Gas-chromatography analyses and mixed-function-oxidase measurements indicated similar values in both strains and also confirmed the key role of oxidative metabolism in this species. Because C. externa has maintained a tolerance to zeta-cypermethrin without previous pesticide exposure, this species could potentially be mass-reared and released in fields in the presence of pesticide pressure.
Preserving Differential Privacy in Degree-Correlation based Graph Generation

PubMed Central

Wang, Yue; Wu, Xintao

2014-01-01

Enabling accurate analysis of social network data while preserving differential privacy has been challenging since graph features such as cluster coefficient often have high sensitivity, which is different from traditional aggregate functions (e.g., count and sum) on tabular data. In this paper, we study the problem of enforcing edge differential privacy in graph generation. The idea is to enforce differential privacy on graph model parameters learned from the original network and then generate the graphs for releasing using the graph model with the private parameters. In particular, we develop a differential privacy preserving graph generator based on the dK-graph generation model. We first derive from the original graph various parameters (i.e., degree correlations) used in the dK-graph model, then enforce edge differential privacy on the learned parameters, and finally use the dK-graph model with the perturbed parameters to generate graphs. For the 2K-graph model, we enforce the edge differential privacy by calibrating noise based on the smooth sensitivity, rather than the global sensitivity. By doing this, we achieve the strict differential privacy guarantee with smaller magnitude noise. We conduct experiments on four real networks and compare the performance of our private dK-graph models with the stochastic Kronecker graph generation model in terms of utility and privacy tradeoff. Empirical evaluations show the developed private dK-graph generation models significantly outperform the approach based on the stochastic Kronecker generation model. PMID:24723987
Functional Brain Networks Develop from a “Local to Distributed” Organization

PubMed Central

Power, Jonathan D.; Dosenbach, Nico U. F.; Church, Jessica A.; Miezin, Francis M.; Schlaggar, Bradley L.; Petersen, Steven E.

2009-01-01

The mature human brain is organized into a collection of specialized functional networks that flexibly interact to support various cognitive functions. Studies of development often attempt to identify the organizing principles that guide the maturation of these functional networks. In this report, we combine resting state functional connectivity MRI (rs-fcMRI), graph analysis, community detection, and spring-embedding visualization techniques to analyze four separate networks defined in earlier studies. As we have previously reported, we find, across development, a trend toward ‘segregation’ (a general decrease in correlation strength) between regions close in anatomical space and ‘integration’ (an increased correlation strength) between selected regions distant in space. The generalization of these earlier trends across multiple networks suggests that this is a general developmental principle for changes in functional connectivity that would extend to large-scale graph theoretic analyses of large-scale brain networks. Communities in children are predominantly arranged by anatomical proximity, while communities in adults predominantly reflect functional relationships, as defined from adult fMRI studies. In sum, over development, the organization of multiple functional networks shifts from a local anatomical emphasis in children to a more “distributed” architecture in young adults. We argue that this “local to distributed” developmental characterization has important implications for understanding the development of neural systems underlying cognition. Further, graph metrics (e.g., clustering coefficients and average path lengths) are similar in child and adult graphs, with both showing “small-world”-like properties, while community detection by modularity optimization reveals stable communities within the graphs that are clearly different between young children and young adults. These observations suggest that early school age children and adults both have relatively efficient systems that may solve similar information processing problems in divergent ways. PMID:19412534
Functional brain networks develop from a "local to distributed" organization.

PubMed

Fair, Damien A; Cohen, Alexander L; Power, Jonathan D; Dosenbach, Nico U F; Church, Jessica A; Miezin, Francis M; Schlaggar, Bradley L; Petersen, Steven E

2009-05-01

The mature human brain is organized into a collection of specialized functional networks that flexibly interact to support various cognitive functions. Studies of development often attempt to identify the organizing principles that guide the maturation of these functional networks. In this report, we combine resting state functional connectivity MRI (rs-fcMRI), graph analysis, community detection, and spring-embedding visualization techniques to analyze four separate networks defined in earlier studies. As we have previously reported, we find, across development, a trend toward 'segregation' (a general decrease in correlation strength) between regions close in anatomical space and 'integration' (an increased correlation strength) between selected regions distant in space. The generalization of these earlier trends across multiple networks suggests that this is a general developmental principle for changes in functional connectivity that would extend to large-scale graph theoretic analyses of large-scale brain networks. Communities in children are predominantly arranged by anatomical proximity, while communities in adults predominantly reflect functional relationships, as defined from adult fMRI studies. In sum, over development, the organization of multiple functional networks shifts from a local anatomical emphasis in children to a more "distributed" architecture in young adults. We argue that this "local to distributed" developmental characterization has important implications for understanding the development of neural systems underlying cognition. Further, graph metrics (e.g., clustering coefficients and average path lengths) are similar in child and adult graphs, with both showing "small-world"-like properties, while community detection by modularity optimization reveals stable communities within the graphs that are clearly different between young children and young adults. These observations suggest that early school age children and adults both have relatively efficient systems that may solve similar information processing problems in divergent ways.
Binding of phosphoinositide-specific phospholipase C-zeta (PLC-zeta) to phospholipid membranes: potential role of an unstructured cluster of basic residues.

PubMed

Nomikos, Michail; Mulgrew-Nesbitt, Anna; Pallavi, Payal; Mihalyne, Gyongyi; Zaitseva, Irina; Swann, Karl; Lai, F Anthony; Murray, Diana; McLaughlin, Stuart

2007-06-01

Phospholipase C-zeta (PLC-zeta) is a sperm-specific enzyme that initiates the Ca2+ oscillations in mammalian eggs that activate embryo development. It shares considerable sequence homology with PLC-delta1, but lacks the PH domain that anchors PLC-delta1 to phosphatidylinositol 4,5-bisphosphate, PIP2. Thus it is unclear how PLC-zeta interacts with membranes. The linker region between the X and Y catalytic domains of PLC-zeta, however, contains a cluster of basic residues not present in PLC-delta1. Application of electrostatic theory to a homology model of PLC-zeta suggests this basic cluster could interact with acidic lipids. We measured the binding of catalytically competent mouse PLC-zeta to phospholipid vesicles: for 2:1 phosphatidylcholine/phosphatidylserine (PC/PS) vesicles, the molar partition coefficient, K, is too weak to be of physiological significance. Incorporating 1% PIP2 into the 2:1 PC/PS vesicles increases K about 10-fold, to 5x10(3) M-1, a biologically relevant value. Expressed fragments corresponding to the PLC-zeta X-Y linker region also bind with higher affinity to polyvalent than monovalent phosphoinositides on nitrocellulose filters. A peptide corresponding to the basic cluster (charge=+7) within the linker region, PLC-zeta-(374-385), binds to PC/PS vesicles with higher affinity than PLC-zeta, but its binding is less sensitive to incorporating PIP2. The acidic residues flanking this basic cluster in PLC-zeta may account for both these phenomena. FRET experiments suggest the basic cluster could not only anchor the protein to the membrane, but also enhance the local concentration of PIP2 adjacent to the catalytic domain.
Improving Graduate Students' Graphing Skills of Multiple Baseline Designs with Microsoft[R] Excel 2007

ERIC Educational Resources Information Center

Lo, Ya-yu; Starling, A. Leyf Peirce

2009-01-01

This study examined the effects of a graphing task analysis using the Microsoft[R] Office Excel 2007 program on the single-subject multiple baseline graphing skills of three university graduate students. Using a multiple probe across participants design, the study demonstrated a functional relationship between the number of correct graphing…
Automatic Molecular Design using Evolutionary Techniques

NASA Technical Reports Server (NTRS)

Globus, Al; Lawton, John; Wipke, Todd; Saini, Subhash (Technical Monitor)

1998-01-01

Molecular nanotechnology is the precise, three-dimensional control of materials and devices at the atomic scale. An important part of nanotechnology is the design of molecules for specific purposes. This paper describes early results using genetic software techniques to automatically design molecules under the control of a fitness function. The fitness function must be capable of determining which of two arbitrary molecules is better for a specific task. The software begins by generating a population of random molecules. The population is then evolved towards greater fitness by randomly combining parts of the better individuals to create new molecules. These new molecules then replace some of the worst molecules in the population. The unique aspect of our approach is that we apply genetic crossover to molecules represented by graphs, i.e., sets of atoms and the bonds that connect them. We present evidence suggesting that crossover alone, operating on graphs, can evolve any possible molecule given an appropriate fitness function and a population containing both rings and chains. Prior work evolved strings or trees that were subsequently processed to generate molecular graphs. In principle, genetic graph software should be able to evolve other graph representable systems such as circuits, transportation networks, metabolic pathways, computer networks, etc.
Multiple graph regularized protein domain ranking.

PubMed

Wang, Jim Jing-Yan; Bensmail, Halima; Gao, Xin

2012-11-19

Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods. To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods. The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications.
Multiple graph regularized protein domain ranking

PubMed Central

2012-01-01

Background Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods. Results To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods. Conclusion The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications. PMID:23157331
Reflecting on Graphs: Attributes of Graph Choice and Construction Practices in Biology

PubMed Central

Angra, Aakanksha; Gardner, Stephanie M.

2017-01-01

Undergraduate biology education reform aims to engage students in scientific practices such as experimental design, experimentation, and data analysis and communication. Graphs are ubiquitous in the biological sciences, and creating effective graphical representations involves quantitative and disciplinary concepts and skills. Past studies document student difficulties with graphing within the contexts of classroom or national assessments without evaluating student reasoning. Operating under the metarepresentational competence framework, we conducted think-aloud interviews to reveal differences in reasoning and graph quality between undergraduate biology students, graduate students, and professors in a pen-and-paper graphing task. All professors planned and thought about data before graph construction. When reflecting on their graphs, professors and graduate students focused on the function of graphs and experimental design, while most undergraduate students relied on intuition and data provided in the task. Most undergraduate students meticulously plotted all data with scaled axes, while professors and some graduate students transformed the data, aligned the graph with the research question, and reflected on statistics and sample size. Differences in reasoning and approaches taken in graph choice and construction corroborate and extend previous findings and provide rich targets for undergraduate and graduate instruction. PMID:28821538
Supporting Generative Thinking about Number Lines, the Cartesian Plane, and Graphs of Linear Functions

ERIC Educational Resources Information Center

Earnest, Darrell Steven

2012-01-01

This dissertation explores fifth and eighth grade students' interpretations of three kinds of mathematical representations: number lines, the Cartesian plane, and graphs of linear functions. Two studies were conducted. In Study 1, I administered the paper-and-pencil Linear Representations Assessment (LRA) to examine students'…
Zeta potential of microfluidic substrates: 1. Theory, experimental techniques, and effects on separations.

PubMed

Kirby, Brian J; Hasselbrink, Ernest F

2004-01-01

This paper summarizes theory, experimental techniques, and the reported data pertaining to the zeta potential of silica and silicon with attention to use as microfluidic substrate materials, particularly for microchip chemical separations. Dependence on cation concentration, buffer and cation type, pH, cation valency, and temperature are discussed. The Debye-Hückel limit, which is often correctly treated as a good approximation for describing the ion concentration in the double layer, can lead to serious errors if it is extended to predict the dependence of zeta potential on the counterion concentration. For indifferent univalent electrolytes (e.g., sodium and potassium), two simple scalings for the dependence of zeta potential on counterion concentration can be derived in high- and low-zeta limits of the nonlinear Poisson-Boltzman equation solution in the double layer. It is shown that for most situations relevant to microchip separations, the high-zeta limit is most applicable, leading to the conclusion that the zeta potential on silica substrates is approximately proportional to the logarithm of the molar counterion concentration. The zeta vs. pH dependence measurements from several experiments are compared by normalizing the zeta based on concentration.
User-Assisted Store Recycling for Dynamic Task Graph Schedulers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kurt, Mehmet Can; Krishnamoorthy, Sriram; Agrawal, Gagan

The emergence of the multi-core era has led to increased interest in designing effective yet practical parallel programming models. Models based on task graphs that operate on single-assignment data are attractive in several ways: they can support dynamic applications and precisely represent the available concurrency. However, they also require nuanced algorithms for scheduling and memory management for efficient execution. In this paper, we consider memory-efficient dynamic scheduling of task graphs. Specifically, we present a novel approach for dynamically recycling the memory locations assigned to data items as they are produced by tasks. We develop algorithms to identify memory-efficient store recyclingmore » functions by systematically evaluating the validity of a set of (user-provided or automatically generated) alternatives. Because recycling function can be input data-dependent, we have also developed support for continued correct execution of a task graph in the presence of a potentially incorrect store recycling function. Experimental evaluation demonstrates that our approach to automatic store recycling incurs little to no overheads, achieves memory usage comparable to the best manually derived solutions, often produces recycling functions valid across problem sizes and input parameters, and efficiently recovers from an incorrect choice of store recycling functions.« less
Dynamic interaction between 14-3-3zeta and bax during TNF-α-induced apoptosis in living cells

NASA Astrophysics Data System (ADS)

Gao, Xuejuan; Xing, Da; Chen, Tongsheng

2006-09-01

Bax, a proapoptotic member of the Bcl-2 family, localizes largely in the cytoplasm but redistributes to mitochondria and undergoes oligomerization to induce the release of apoptogenic factors such as cytochrome c in response to apoptotic stimuli. Cytoplasmic protein 14-3-3zeta binds to Bax and, upon apoptotic stimulation, releases Bax by a caspase-independent mechanism. However, the direct interaction of the cytoplasmic 14-3-3zeta and Bax in living cells has not been observed. In present study, to monitor the dynamic interaction between 14-3-3zeta and Bax in living cells in real time during apoptosis induced by tumor necrosis factor (TNF-α), DsRed-14-3-3zeta plasmid is constructed. By cotransfecting DsRed- 14-3-3zeta and GFP-Bax plasmids into human lung adenocarcinoma cells (ASTC-a-1), we observe the dynamic interaction between Bax and 14-3-3zeta using fluorescence resonance energy transfer (FRET) technique on laser scanning confocal microscope. The results show that 14-3-3zeta remains in the cytoplasm but GFP-Bax translocates to mitochondria completely after TNF-α stimulation. These results reveal that 14-3-3zeta binds directly to Bax in healthy cells, and that 14-3-3zeta negatively regulates Bax translocation to mitochondria during TNF-α-induced apoptosis.
Secondary electroosmotic flow in microchannels with nonuniform and asymmetric Zeta potential

NASA Astrophysics Data System (ADS)

Zhang, Jinbai; He, Guowei; Liu, Feng

2004-11-01

Microfluidics has a broad range of applications in biotechnology, such as sample injection, drug delivering, solution mixing, and separations. All of these techniques require handling fluids in the low Reynolds number (Re) regime. Electroosmotic flow (EOF) or electroosmocitcs is the bulk movement of liquid relative to a stationary surface due to an externally applied electronic field. It is an alternative to pressure-driven flows with convenient implementation The driving force for EOF is dependent on the zeta potential. Previous reseraches focus on the nonuniform Zeta potential. In the present work, we consider nonuniform and asymmetric Zeta potential. The effects of asymmetric Zeta potential on the EOF are investigated analytically and simulated numerically. It is demonstrated that the nonuniform and asymmetric Zeta potential can generate more flow patterns for microfluidic control compared to symmetric Zeta potential.
Application-Specific Graph Sampling for Frequent Subgraph Mining and Community Detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Purohit, Sumit; Choudhury, Sutanay; Holder, Lawrence B.

Graph mining is an important data analysis methodology, but struggles as the input graph size increases. The scalability and usability challenges posed by such large graphs make it imperative to sample the input graph and reduce its size. The critical challenge in sampling is to identify the appropriate algorithm to insure the resulting analysis does not suffer heavily from the data reduction. Predicting the expected performance degradation for a given graph and sampling algorithm is also useful. In this paper, we present different sampling approaches for graph mining applications such as Frequent Subgrpah Mining (FSM), and Community Detection (CD). Wemore » explore graph metrics such as PageRank, Triangles, and Diversity to sample a graph and conclude that for heterogeneous graphs Triangles and Diversity perform better than degree based metrics. We also present two new sampling variations for targeted graph mining applications. We present empirical results to show that knowledge of the target application, along with input graph properties can be used to select the best sampling algorithm. We also conclude that performance degradation is an abrupt, rather than gradual phenomena, as the sample size decreases. We present the empirical results to show that the performance degradation follows a logistic function.« less
Graph-cut based discrete-valued image reconstruction.

PubMed

Tuysuzoglu, Ahmet; Karl, W Clem; Stojanovic, Ivana; Castañòn, David; Ünlü, M Selim

2015-05-01

Efficient graph-cut methods have been used with great success for labeling and denoising problems occurring in computer vision. Unfortunately, the presence of linear image mappings has prevented the use of these techniques in most discrete-amplitude image reconstruction problems. In this paper, we develop a graph-cut based framework for the direct solution of discrete amplitude linear image reconstruction problems cast as regularized energy function minimizations. We first analyze the structure of discrete linear inverse problem cost functions to show that the obstacle to the application of graph-cut methods to their solution is the variable mixing caused by the presence of the linear sensing operator. We then propose to use a surrogate energy functional that overcomes the challenges imposed by the sensing operator yet can be utilized efficiently in existing graph-cut frameworks. We use this surrogate energy functional to devise a monotonic iterative algorithm for the solution of discrete valued inverse problems. We first provide experiments using local convolutional operators and show the robustness of the proposed technique to noise and stability to changes in regularization parameter. Then we focus on nonlocal, tomographic examples where we consider limited-angle data problems. We compare our technique with state-of-the-art discrete and continuous image reconstruction techniques. Experiments show that the proposed method outperforms state-of-the-art techniques in challenging scenarios involving discrete valued unknowns.
Revealing Long-Range Interconnected Hubs in Human Chromatin Interaction Data Using Graph Theory

NASA Astrophysics Data System (ADS)

Boulos, R. E.; Arneodo, A.; Jensen, P.; Audit, B.

2013-09-01

We use graph theory to analyze chromatin interaction (Hi-C) data in the human genome. We show that a key functional feature of the genome—“master” replication origins—corresponds to DNA loci of maximal network centrality. These loci form a set of interconnected hubs both within chromosomes and between different chromosomes. Our results open the way to a fruitful use of graph theory concepts to decipher DNA structural organization in relation to genome functions such as replication and transcription. This quantitative information should prove useful to discriminate between possible polymer models of nuclear organization.
Influence of hydrolysis behaviour and microfluidisation on the functionality and structural properties of collagen hydrolysates.

PubMed

Zhang, Yehui; Zhang, Yousheng; Liu, Xueming; Huang, Lihua; Chen, Zhiyi; Cheng, Jingrong

2017-07-15

The functionality and structural properties of pig skin hydrolysates with different degrees of hydrolysis (DH, 10% and 20%) and microfluidisation (120MPa), prepared by pepsin and Alcalase® have been investigated in this study. Extensive hydrolysis can significantly improve the absolute value of the zeta potential and surface hydrophobicity. The particle distribution of hydrolysates decreased with increasing DH. The numbers of free sulfhydryl (SH) and disulfide bonds (SS) were significantly increased with increasing DH (p<0.05). Hydrolysates with a lower DH showed a better emulsifying property than those with a higher DH. Microfluidisation led to the transformation of structural and interfacial properties of the hydrolysates and increased the value of the zeta potential, S 0 , and gel strength. Microfluidisation results in limited breakage of chemical bonds, the number of SS and SH bonds unchanged in the treatment. These results reflect the functionality and structural properties of collagen-rich pig skin hydrolysates. Copyright © 2017 Elsevier Ltd. All rights reserved.

Convergence of the Graph Allen-Cahn Scheme

NASA Astrophysics Data System (ADS)

Luo, Xiyang; Bertozzi, Andrea L.

2017-05-01

The graph Laplacian and the graph cut problem are closely related to Markov random fields, and have many applications in clustering and image segmentation. The diffuse interface model is widely used for modeling in material science, and can also be used as a proxy to total variation minimization. In Bertozzi and Flenner (Multiscale Model Simul 10(3):1090-1118, 2012), an algorithm was developed to generalize the diffuse interface model to graphs to solve the graph cut problem. This work analyzes the conditions for the graph diffuse interface algorithm to converge. Using techniques from numerical PDE and convex optimization, monotonicity in function value and convergence under an a posteriori condition are shown for a class of schemes under a graph-independent stepsize condition. We also generalize our results to incorporate spectral truncation, a common technique used to save computation cost, and also to the case of multiclass classification. Various numerical experiments are done to compare theoretical results with practical performance.
On cordial labeling of double duplication for some families of graph

NASA Astrophysics Data System (ADS)

Shobana, L.; Remigius Perpetua Mary, F.

2018-04-01

Let G (V, E) be a simple undirected graph where V,E are its vertex set and edge set respectively. Consider a labeling where f bea function from the vertices of G to {0, 1} and for each edge xy assign the label|f(x)-f(y)|. Then f is called cordial of G if the number of vertices labeled 0 and the number of vertices labeled 1 differs by at most 1 and the number of edges labeled 0 and the number of edges labeled 1 differs by at most 1. In this paper we proved the existence of cordial labeling for double duplication of path graph Pn: n≥2, cycle graph Cn: n≥3 except for n≡2 (mod 4), wheel graph Wn:n≥5 except for n≥3 (mod 4), flower graph Fn: n≥5 and bistar graph Bm,n: m,n≥2.
Studying red blood cell agglutination by measuring electrical and mechanical properties with a double optical tweezers

NASA Astrophysics Data System (ADS)

Fontes, Adriana; Fernandes, Heloise P.; de Thomaz, André A.; Barbosa, Luiz C.; Barjas-Castro, Maria L.; Cesar, Carlos L.

2007-07-01

The red blood cell (RBC) viscoelastic membrane contains proteins and glycolproteins embedded in, or attached, to a fluid lipid bilayer and are negatively charged, which creates a repulsive electric (zeta) potential between the cells and prevents their aggregation in the blood stream. The basis of the immunohematologic tests is the interaction between antigens and antibodies that causes hemagglutination. The identification of antibodies and antigens is of fundamental importance for the transfusional routine. This agglutination is induced by decreasing the zeta-potential through the introduction of artificial potential substances. This report proposes the use of the optical tweezers to measure the membrane viscosity, the cell adhesion, the zeta-potential and the size of the double layer of charges (CLC) formed around the cell in an electrolytic solution. The adhesion was quantified by slowly displacing two RBCs apart until the disagglutination. The CLC was measured using the force on the bead attached to a single RBC in response to an applied voltage. The zeta-potential was obtained by measuring the terminal velocity after releasing the RBC from the optical trap at the last applied voltage. For the membrane viscosity experiment, we trapped a bead attached to RBCs and measured the force to slide one RBC over the other as a function of the relative velocity. After we tested the methodology, we performed measurements using antibody and potential substances. We observed that this experiment can provide information about cell agglutination that helps to improve the tests usually performed in blood banks. We also believe that this methodology can be applied for measurements of zeta-potentials in other kind of samples.
Bio-field array: a dielectrophoretic electromagnetic toroidal excitation to restore and maintain the golden ratio in human erythrocytes.

PubMed

Purnell, Marcy C; Butawan, Matthew B A; Ramsey, Risa D

2018-06-01

Erythrocytes must maintain a biconcave discoid shape in order to efficiently deliver oxygen (O 2 ) molecules and to recycle carbon dioxide (CO 2 ) molecules. The erythrocyte is a small toroidal dielectrophoretic (DEP) electromagnetic field (EMF) driven cell that maintains its zeta potential (ζ) with a dielectric constant (ԑ) between a negatively charged plasma membrane surface and the positively charged adjacent Stern layer. Here, we propose that zeta potential is also driven by both ferroelectric influences (chloride ion) and ferromagnetic influences (serum iron driven). The Golden Ratio, a function of Phi φ, offers a geometrical mathematical measure within the distinct and desired curvature of the red blood cell that is governed by this zeta potential and is required for the efficient recycling of CO 2 in our bodies. The Bio-Field Array (BFA) shows potential to both drive/fuel the zeta potential and restore the Golden Ratio in human erythrocytes thereby leading to more efficient recycling of CO 2 . Live Blood Analyses and serum CO 2 levels from twenty human subjects that participated in immersion therapy sessions with the BFA for 2 weeks (six sessions) were analyzed. Live Blood Analyses (LBA) and serum blood analyses performed before and after the BFA immersion therapy sessions in the BFA pilot study participants showed reversal of erythrocyte rheological alterations (per RBC metric; P = 0.00000075), a morphological return to the Golden Ratio and a significant decrease in serum CO 2 (P = 0.017) in these participants. Immersion therapy sessions with the BFA show potential to modulate zeta potential, restore this newly defined Golden Ratio and reduce rheological alterations in human erythrocytes. © 2018 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of The Physiological Society and the American Physiological Society.
The C-12/C-13 isotope ratio of the interstellar medium in the neighborhood of the sun

NASA Technical Reports Server (NTRS)

Hawkins, Isabel; Jura, Michael

1987-01-01

Data from observations of Xi Per, P Cyg, 20 Tau, and 23 Tau, obtained at 4232 and 3957 A using a coude spectrograph and a 1872-element reticon on the 3-m Shane telescope at Lick Observatory during 1984-1985, are combined with data on Zeta Oph (Hawkins et al., 1985) and used to estimate the C isotope ratio of the ISM near the sun. The results are presented in extensive tables and graphs and characterized in detail. The (C-12)H(+)/(C-13)H(+) abundance ratios toward the five stars are found to agree to within 12 percent and shown to be representative of the C-12/C-13 ratios in the gas, strongly indicating that the local ISM is homogeneous. The difference between the ISM ratio (43 + or - 4) and the solar-system value (89) is attributed to the chemical evolution of the ISM in the 4.9 Gyr since the formation of the sun.
Differentiated Learning Environment--A Classroom for Quadratic Equation, Function and Graphs

ERIC Educational Resources Information Center

Dinç, Emre

2017-01-01

This paper will cover the design of a learning environment as a classroom regarding the Quadratic Equations, Functions and Graphs. The goal of the learning environment offered in the paper is to design a classroom where students will enjoy the process, use their skills they already have during the learning process, control and plan their learning…
Impact of Geometer's Sketchpad on Students Achievement in Graph Functions

ERIC Educational Resources Information Center

Eu, Leong Kwan

2013-01-01

The purpose of this study is to investigate the effect of using the Geometer's Sketchpad software in the teaching and learning of graph functions among Form Six (Grade 12) students in a Malaysian secondary school. This study utilized a quasi-experimental design using intact group of students from two classes in an urban secondary school. Two…
On Vieta's Formulas and the Determination of a Set of Positive Integers by Their Sum and Product

ERIC Educational Resources Information Center

Valahas, Theodoros; Boukas, Andreas

2011-01-01

In Years 9 and 10 of secondary schooling students are typically introduced to quadratic expressions and functions and related modelling, algebra, and graphing. This includes work on the expansion and factorisation of quadratic expressions (typically with integer values of coefficients), graphing quadratic functions, finding the roots of quadratic…
Retention of membrane charge attributes by cryopreserved-thawed sperm and zeta selection.

PubMed

Kam, Tricia L; Jacobson, John D; Patton, William C; Corselli, Johannah U; Chan, Philip J

2007-09-01

Mature sperm can be selected based on their negative zeta electrokinetic potential. The zeta selection of cryopreserved sperm is unknown. The objective was to study the effect of zeta processing on the morphology and kinematic parameters of cryopreserved-thawed sperm. Colloid-washed sperm (N = 9 cases) were cryopreserved for 24 h, thawed and diluted in serum-free medium in positive-charged tubes. After centrifugation, the tubes were decanted, serum-supplemented medium was added and the resuspended sperm were analyzed. Untreated sperm and fresh sperm served as the controls. There were improvements in strict normal morphology in fresh (11.8 +/- 0.3 versus control 8.8 +/- 0.3 %, mean +/- SEM) and thawed (8.7 +/- 0.2 versus control 5.4 +/- 0.2%) sperm after zeta processing. Percent sperm necrosis was reduced after zeta processing (66.0 +/- 0.6 versus unprocessed 74.6 +/- 0.3%). Progression decreased by 50% but not total motility after zeta processing of thawed sperm. The results suggested that the cryopreservation process did not impact the sperm membrane net zeta potential and higher percentages of sperm with normal strict morphology, acrosome integrity and reduced necrosis were recovered. The zeta method was simple and improved the selection of quality sperm after cryopreservation but more studies would be needed before routine clinical application.
NEFI: Network Extraction From Images

PubMed Central

Dirnberger, M.; Kehl, T.; Neumann, A.

2015-01-01

Networks are amongst the central building blocks of many systems. Given a graph of a network, methods from graph theory enable a precise investigation of its properties. Software for the analysis of graphs is widely available and has been applied to study various types of networks. In some applications, graph acquisition is relatively simple. However, for many networks data collection relies on images where graph extraction requires domain-specific solutions. Here we introduce NEFI, a tool that extracts graphs from images of networks originating in various domains. Regarding previous work on graph extraction, theoretical results are fully accessible only to an expert audience and ready-to-use implementations for non-experts are rarely available or insufficiently documented. NEFI provides a novel platform allowing practitioners to easily extract graphs from images by combining basic tools from image processing, computer vision and graph theory. Thus, NEFI constitutes an alternative to tedious manual graph extraction and special purpose tools. We anticipate NEFI to enable time-efficient collection of large datasets. The analysis of these novel datasets may open up the possibility to gain new insights into the structure and function of various networks. NEFI is open source and available at http://nefi.mpi-inf.mpg.de. PMID:26521675
Constraints on Black Hole Spin in a Sample of Broad Iron Line AGN

NASA Technical Reports Server (NTRS)

Brenneman, Laura W.; Reynolds, Christopher S.

2008-01-01

We present a uniform X-ray spectral analysis of nine type-1 active galactic nuclei (AGN) that have been previously found to harbor relativistically broadened iron emission lines. We show that the need for relativistic effects in the spectrum is robust even when one includes continuum "reflection" from the accretion disk. We then proceed to model these relativistic effects in order to constrain the spin of the supermassive black holes in these AGN. Our principal assumption, supported by recent simulations of geometrically-thin accretion disks, is that no iron line emission (or any associated Xray reflection features) can originate from the disk within the innermost stable circular orbit. Under this assumption, which tends to lead to constraints in the form of lower limits on the spin parameter, we obtain non-trivial spin constraints on five AGN. The spin parameters of these sources range from moderate (a approximates 0.6) to high (a > 0.96). Our results allow, for the first time, an observational constraint on the spin distribution function of local supermassive black holes. Parameterizing this as a power-law in dimensionless spin parameter (f(a) varies as absolute value of (a) exp zeta), we present the probability distribution for zeta implied by our results. Our results suggest 90% and 95% confidence limits of zeta > -0.09 and zeta > -0.3 respectively.
A graph-based approach to inequality assessment

NASA Astrophysics Data System (ADS)

Palestini, Arsen; Pignataro, Giuseppe

2016-08-01

In a population consisting of heterogeneous types, whose income factors are indicated by nonnegative vectors, policies aggregating different factors can be represented by coalitions in a cooperative game, whose characteristic function is a multi-factor inequality index. When it is not possible to form all coalitions, the feasible ones can be indicated by a graph. We redefine Shapley and Banzhaf values on graph games to deduce some properties involving the degrees of the graph vertices and marginal contributions to overall inequality. An example is finally provided based on a modified multi-factor Atkinson index.
On finding bicliques in bipartite graphs: a novel algorithm and its application to the integration of diverse biological data types

PubMed Central

2014-01-01

Background Integrating and analyzing heterogeneous genome-scale data is a huge algorithmic challenge for modern systems biology. Bipartite graphs can be useful for representing relationships across pairs of disparate data types, with the interpretation of these relationships accomplished through an enumeration of maximal bicliques. Most previously-known techniques are generally ill-suited to this foundational task, because they are relatively inefficient and without effective scaling. In this paper, a powerful new algorithm is described that produces all maximal bicliques in a bipartite graph. Unlike most previous approaches, the new method neither places undue restrictions on its input nor inflates the problem size. Efficiency is achieved through an innovative exploitation of bipartite graph structure, and through computational reductions that rapidly eliminate non-maximal candidates from the search space. An iterative selection of vertices for consideration based on non-decreasing common neighborhood sizes boosts efficiency and leads to more balanced recursion trees. Results The new technique is implemented and compared to previously published approaches from graph theory and data mining. Formal time and space bounds are derived. Experiments are performed on both random graphs and graphs constructed from functional genomics data. It is shown that the new method substantially outperforms the best previous alternatives. Conclusions The new method is streamlined, efficient, and particularly well-suited to the study of huge and diverse biological data. A robust implementation has been incorporated into GeneWeaver, an online tool for integrating and analyzing functional genomics experiments, available at http://geneweaver.org. The enormous increase in scalability it provides empowers users to study complex and previously unassailable gene-set associations between genes and their biological functions in a hierarchical fashion and on a genome-wide scale. This practical computational resource is adaptable to almost any applications environment in which bipartite graphs can be used to model relationships between pairs of heterogeneous entities. PMID:24731198
A DFT and ab initio benchmarking study of metal-alkane interactions and the activation of carbon-hydrogen bonds.

PubMed

Flener-Lovitt, Charity; Woon, David E; Dunning, Thom H; Girolami, Gregory S

2010-02-04

Density functional theory and ab initio methods have been used to calculate the structures and energies of minima and transition states for the reactions of methane coordinated to a transition metal. The reactions studied are reversible C-H bond activation of the coordinated methane ligand to form a transition metal methyl hydride complex and dissociation of the coordinated methane ligand. The reaction sequence can be summarized as L(x)M(CH(3))H <==> L(x)M(CH(4)) <==> L(x)M + CH(4), where L(x)M is the osmium-containing fragment (C(5)H(5))Os(R(2)PCH(2)PR(2))(+) and R is H or CH(3). Three-center metal-carbon-hydrogen interactions play an important role in this system. Both basis sets and functionals have been benchmarked in this work, including new correlation consistent basis sets for a third transition series element, osmium. Double zeta quality correlation consistent basis sets yield energies close to those from calculations with quadruple-zeta basis sets, with variations that are smaller than the differences between functionals. The energies of important species on the potential energy surface, calculated by using 10 DFT functionals, are compared both to experimental values and to CCSD(T) single point calculations. Kohn-Sham natural bond orbital descriptions are used to understand the differences between functionals. Older functionals favor electrostatic interactions over weak donor-acceptor interactions and, therefore, are not particularly well suited for describing systems--such as sigma-complexes--in which the latter are dominant. Newer kinetic and dispersion-corrected functionals such as MPW1K and M05-2X provide significantly better descriptions of the bonding interactions, as judged by their ability to predict energies closer to CCSD(T) values. Kohn-Sham and natural bond orbitals are used to differentiate between bonding descriptions. Our evaluations of these basis sets and DFT functionals lead us to recommend the use of dispersion corrected functionals in conjunction with double-zeta or larger basis sets with polarization functions for calculations involving weak interactions, such as those found in sigma-complexes with transition metals.
The Use of Graphs in Specific Situations of the Initial Conditions of Linear Differential Equations

ERIC Educational Resources Information Center

Buendía, Gabriela; Cordero, Francisco

2013-01-01

In this article, we present a discussion on the role of graphs and its significance in the relation between the number of initial conditions and the order of a linear differential equation, which is known as the initial value problem. We propose to make a functional framework for the use of graphs that intends to broaden the explanations of the…
DOE Office of Scientific and Technical Information (OSTI.GOV)

Birmingham, D.; Kantowski, R.; Milton, K.A.

We use two methods of computing the unique logarithmically divergent part of the Casimir energy for massive scalar and spinor fields defined on even-dimensional Kaluza-Klein spaces of the form M/sup 4/ x S/sup N//sup 1/ x S/sup N//sup 2/ x xxx. Both methods (heat kernel and direct) give identical results. The first evaluates the required internal zeta function by identifying it in the asymptotic expansion of the trace of the heat kernel, and the second evaluates the zeta function directly using the Euler-Maclaurin sum formula. In Appendix C we tabulate these energies for all spaces of total internal dimension lessmore » than or equal to6. These methods are easily applied to vector and tensor fields needed in computing one-loop vacuum gravitational energies on these spaces. Stable solutions are given for internal structure S/sup 2/ x S/sup 2/.« less
Movement Forms: A Graph-Dynamic Perspective

PubMed Central

Saltzman, Elliot; Holt, Ken

2014-01-01

The focus of this paper is on characterizing the physical movement forms (e.g., walk, crawl, roll, etc.) that can be used to actualize abstract, functionally-specified behavioral goals (e.g., locomotion). Emphasis is placed on how such forms are distinguished from one another, in part, by the set of topological patterns of physical contact between agent and environment (i.e., the set of physical graphs associated with each form) and the transitions among these patterns displayed over the course of performance (i.e., the form’s physical graph dynamics). Crucial in this regard is the creation and dissolution of loops in these graphs, which can be related to the distinction between open and closed kinematic chains. Formal similarities are described within the theoretical framework of task-dynamics between physically-closed kinematic chains (physical loops) that are created during various movement forms and functionally-closed kinematic chains (functional loops) that are associated with task-space control of end-effectors; it is argued that both types of loop must be flexibly incorporated into the coordinative structures that govern skilled action. Final speculation is focused on the role of graphs and their dynamics, not only in processes of coordination and control for individual agents, but also in processes of inter-agent coordination and the coupling of agents with (non-sentient) environmental objects. PMID:24910507
Movement Forms: A Graph-Dynamic Perspective.

PubMed

Saltzman, Elliot; Holt, Ken

2014-01-01

The focus of this paper is on characterizing the physical movement forms (e.g., walk, crawl, roll, etc.) that can be used to actualize abstract, functionally-specified behavioral goals (e.g., locomotion). Emphasis is placed on how such forms are distinguished from one another, in part, by the set of topological patterns of physical contact between agent and environment (i.e., the set of physical graphs associated with each form) and the transitions among these patterns displayed over the course of performance (i.e., the form's physical graph dynamics ). Crucial in this regard is the creation and dissolution of loops in these graphs, which can be related to the distinction between open and closed kinematic chains. Formal similarities are described within the theoretical framework of task-dynamics between physically-closed kinematic chains (physical loops) that are created during various movement forms and functionally-closed kinematic chains (functional loops) that are associated with task-space control of end-effectors; it is argued that both types of loop must be flexibly incorporated into the coordinative structures that govern skilled action. Final speculation is focused on the role of graphs and their dynamics, not only in processes of coordination and control for individual agents, but also in processes of inter-agent coordination and the coupling of agents with (non-sentient) environmental objects.
FUSE: a profit maximization approach for functional summarization of biological networks.

PubMed

Seah, Boon-Siew; Bhowmick, Sourav S; Dewey, C Forbes; Yu, Hanry

2012-03-21

The availability of large-scale curated protein interaction datasets has given rise to the opportunity to investigate higher level organization and modularity within the protein interaction network (PPI) using graph theoretic analysis. Despite the recent progress, systems level analysis of PPIS remains a daunting task as it is challenging to make sense out of the deluge of high-dimensional interaction data. Specifically, techniques that automatically abstract and summarize PPIS at multiple resolutions to provide high level views of its functional landscape are still lacking. We present a novel data-driven and generic algorithm called FUSE (Functional Summary Generator) that generates functional maps of a PPI at different levels of organization, from broad process-process level interactions to in-depth complex-complex level interactions, through a pro t maximization approach that exploits Minimum Description Length (MDL) principle to maximize information gain of the summary graph while satisfying the level of detail constraint. We evaluate the performance of FUSE on several real-world PPIS. We also compare FUSE to state-of-the-art graph clustering methods with GO term enrichment by constructing the biological process landscape of the PPIS. Using AD network as our case study, we further demonstrate the ability of FUSE to quickly summarize the network and identify many different processes and complexes that regulate it. Finally, we study the higher-order connectivity of the human PPI. By simultaneously evaluating interaction and annotation data, FUSE abstracts higher-order interaction maps by reducing the details of the underlying PPI to form a functional summary graph of interconnected functional clusters. Our results demonstrate its effectiveness and superiority over state-of-the-art graph clustering methods with GO term enrichment.
Connectomics and neuroticism: an altered functional network organization.

PubMed

Servaas, Michelle N; Geerligs, Linda; Renken, Remco J; Marsman, Jan-Bernard C; Ormel, Johan; Riese, Harriëtte; Aleman, André

2015-01-01

The personality trait neuroticism is a potent risk marker for psychopathology. Although the neurobiological basis remains unclear, studies have suggested that alterations in connectivity may underlie it. Therefore, the aim of the current study was to shed more light on the functional network organization in neuroticism. To this end, we applied graph theory on resting-state functional magnetic resonance imaging (fMRI) data in 120 women selected based on their neuroticism score. Binary and weighted brain-wide graphs were constructed to examine changes in the functional network structure and functional connectivity strength. Furthermore, graphs were partitioned into modules to specifically investigate connectivity within and between functional subnetworks related to emotion processing and cognitive control. Subsequently, complex network measures (ie, efficiency and modularity) were calculated on the brain-wide graphs and modules, and correlated with neuroticism scores. Compared with low neurotic individuals, high neurotic individuals exhibited a whole-brain network structure resembling more that of a random network and had overall weaker functional connections. Furthermore, in these high neurotic individuals, functional subnetworks could be delineated less clearly and the majority of these subnetworks showed lower efficiency, while the affective subnetwork showed higher efficiency. In addition, the cingulo-operculum subnetwork demonstrated more ties with other functional subnetworks in association with neuroticism. In conclusion, the 'neurotic brain' has a less than optimal functional network organization and shows signs of functional disconnectivity. Moreover, in high compared with low neurotic individuals, emotion and salience subnetworks have a more prominent role in the information exchange, while sensory(-motor) and cognitive control subnetworks have a less prominent role.

Comparing brain graphs in which nodes are regions of interest or independent components: A simulation study.

PubMed

Yu, Qingbao; Du, Yuhui; Chen, Jiayu; He, Hao; Sui, Jing; Pearlson, Godfrey; Calhoun, Vince D

2017-11-01

A key challenge in building a brain graph using fMRI data is how to define the nodes. Spatial brain components estimated by independent components analysis (ICA) and regions of interest (ROIs) determined by brain atlas are two popular methods to define nodes in brain graphs. It is difficult to evaluate which method is better in real fMRI data. Here we perform a simulation study and evaluate the accuracies of a few graph metrics in graphs with nodes of ICA components, ROIs, or modified ROIs in four simulation scenarios. Graph measures with ICA nodes are more accurate than graphs with ROI nodes in all cases. Graph measures with modified ROI nodes are modulated by artifacts. The correlations of graph metrics across subjects between graphs with ICA nodes and ground truth are higher than the correlations between graphs with ROI nodes and ground truth in scenarios with large overlapped spatial sources. Moreover, moving the location of ROIs would largely decrease the correlations in all scenarios. Evaluating graphs with different nodes is promising in simulated data rather than real data because different scenarios can be simulated and measures of different graphs can be compared with a known ground truth. Since ROIs defined using brain atlas may not correspond well to real functional boundaries, overall findings of this work suggest that it is more appropriate to define nodes using data-driven ICA than ROI approaches in real fMRI data. Copyright © 2017 Elsevier B.V. All rights reserved.
An Unusual Exponential Graph

ERIC Educational Resources Information Center

Syed, M. Qasim; Lovatt, Ian

2014-01-01

This paper is an addition to the series of papers on the exponential function begun by Albert Bartlett. In particular, we ask how the graph of the exponential function y = e[superscript -t/t] would appear if y were plotted versus ln t rather than the normal practice of plotting ln y versus t. In answering this question, we find a new way to…
Metaphors in Mathematics Classrooms: Analyzing the Dynamic Process of Teaching and Learning of Graph Functions

ERIC Educational Resources Information Center

Font, Vicenc; Bolite, Janete; Acevedo, Jorge

2010-01-01

This article presents an analysis of a phenomenon that was observed within the dynamic processes of teaching and learning to read and elaborate Cartesian graphs for functions at high-school level. Two questions were considered during this investigation: What types of metaphors does the teacher use to explain the graphic representation of functions…
Function Plotters for Secondary Math Teachers. A MicroSIFT Quarterly Report.

ERIC Educational Resources Information Center

Weaver, Dave; And Others

This report examines mathematical graphing utilities or function plotters for use in introductory algebra classes of more advanced courses. Each product selected for inclusion in this report is able to construct the graph of a given equation on the screen and serves as a utility which may be used by the student for an open-ended exploration of a…
The Roles of Visualization and Symbolism in the Potential and Actual Infinity of the Limit Process

ERIC Educational Resources Information Center

Kidron, Ivy; Tall, David

2015-01-01

A teaching experiment-using Mathematica to investigate the convergence of sequence of functions visually as a sequence of objects (graphs) converging onto a fixed object (the graph of the limit function)-is here used to analyze how the approach can support the dynamic blending of visual and symbolic representations that has the potential to lead…
Complete sequence of Enterococcus faecium pVEF3 and the detection of an omega-epsilon-zeta toxin-antitoxin module and an ABC transporter.

PubMed

Sletvold, H; Johnsen, P J; Hamre, I; Simonsen, G S; Sundsfjord, A; Nielsen, K M

2008-07-01

Glycopeptide resistant Enterococcus faecium (GREF) persists on Norwegian poultry farms despite the ban on the growth promoter avoparcin. The biological basis for long-term persistence of avoparcin resistance is not fully understood. This study presents the complete DNA sequence of the E. faecium R-plasmid pVEF3 and functional studies of some plasmid-encoded traits (a toxin-antitoxin (TA) system and an ABC transporter) that may be of importance for plasmid persistence. The pVEF3 (63.1 kbp), isolated from an E. faecium strain of poultry origin sampled in Norway in 1999, has 71 coding sequences including the vanA avoparcin/vancomycin resistance encoding gene cluster. pVEF3 encodes the TA system omega-epsilon-zeta, and plasmid stability tests and transcription analysis show that omega-epsilon-zeta is functional in Enterococcus faecalis OGIX, although with decreasing effect over time. The predicted ABC transporter was not found to confer reduced susceptibility to any of the 28 substances tested. The TA system identified in the pVEF-type plasmids may contribute to vanA plasmid persistence on Norwegian poultry farms. However, size and compositional heterogeneity among E. faecium vanA plasmids suggest that additional plasmid maintenance systems in combination with host specific factors and frequent horizontal gene transfer and rearrangement causes the observed plasmid composition and distribution patterns.
zeta 1 and zeta 2 Reticuli and the existence of the zeta Herculis group

NASA Astrophysics Data System (ADS)

del Peloso, E. F.; da Silva, L.; Porto de Mello, G. F.

2000-06-01

We report the detailed analysis of the solar type stars zeta 1 and zeta 2 Reticuli. We obtained accurate effective temperatures (T_eff = 5746 +/- 27 K and 5859 +/- 27 K respectively) and surface gravities (log g = 4.54 +/- 0.02 and 4.46 +/- 0.01 respectively). Both stars are slightly metal deficient ([Fe/H] = -0.22 +/- 0.05) and their element abundance patterns are compatible with one another and with the Sun. The hypothesis, suggested by previous detailed analyses, that these stars could be helium rich relative to the Sun, was investigated. The stars were found to have a normal, solar helium abundance. We analysed the stars' membership of the zeta Herculis stellar kinematic group (SKG). Some probable members have nearly the same galactic orbital parameters, chemical composition and evolutionary states, which confirm the existence of a metal deficient SKG. Since we determined that zeta Herculis does not belong to this group, we propose it be renamed zeta Reticuli SKG. Based on observations collected at the European Southern Observatory, La Silla, Chile, and at the Observatório do Pico dos Dias, operated by the Laboratório Nacional de Astrofísica, CNPq, Brazil.
Breaking of Ensemble Equivalence in Networks

NASA Astrophysics Data System (ADS)

Squartini, Tiziano; de Mol, Joey; den Hollander, Frank; Garlaschelli, Diego

2015-12-01

It is generally believed that, in the thermodynamic limit, the microcanonical description as a function of energy coincides with the canonical description as a function of temperature. However, various examples of systems for which the microcanonical and canonical ensembles are not equivalent have been identified. A complete theory of this intriguing phenomenon is still missing. Here we show that ensemble nonequivalence can manifest itself also in random graphs with topological constraints. We find that, while graphs with a given number of links are ensemble equivalent, graphs with a given degree sequence are not. This result holds irrespective of whether the energy is nonadditive (as in unipartite graphs) or additive (as in bipartite graphs). In contrast with previous expectations, our results show that (1) physically, nonequivalence can be induced by an extensive number of local constraints, and not necessarily by long-range interactions or nonadditivity, (2) mathematically, nonequivalence is determined by a different large-deviation behavior of microcanonical and canonical probabilities for a single microstate, and not necessarily for almost all microstates. The latter criterion, which is entirely local, is not restricted to networks and holds in general.
Functional neural networks of honesty and dishonesty in children: Evidence from graph theory analysis.

PubMed

Ding, Xiao Pan; Wu, Si Jia; Liu, Jiangang; Fu, Genyue; Lee, Kang

2017-09-21

The present study examined how different brain regions interact with each other during spontaneous honest vs. dishonest communication. More specifically, we took a complex network approach based on the graph-theory to analyze neural response data when children are spontaneously engaged in honest or dishonest acts. Fifty-nine right-handed children between 7 and 12 years of age participated in the study. They lied or told the truth out of their own volition. We found that lying decreased both the global and local efficiencies of children's functional neural network. This finding, for the first time, suggests that lying disrupts the efficiency of children's cortical network functioning. Further, it suggests that the graph theory based network analysis is a viable approach to study the neural development of deception.
Mean Curvature, Threshold Dynamics, and Phase Field Theory on Finite Graphs

DTIC Science & Technology

2013-06-28

of the graph in a low dimensional space . Of course, the various definitions of curvature in the ... with a velocity depending on the mean curvature of the front. Recently, there has been an increasing interest in using ideas from continuum PDEs...functions V → R and E the space of all skew-symmetric4 functions E → R. Again to simplify notation, we extend each ϕ ∈ E to a function ϕ : V 2 → R
Fifth Graders' Additive and Multiplicative Reasoning: Establishing Connections across Conceptual Fields Using a Graph

ERIC Educational Resources Information Center

Caddle, Mary C.; Brizuela, Barbara M.

2011-01-01

This paper looks at 21 fifth grade students as they discuss a linear graph in the Cartesian plane. The problem presented to students depicted a graph showing distance as a function of elapsed time for a person walking at a constant rate of 5 miles/h. The question asked students to consider how many more hours, after having already walked 4 h,…
Hybrid coexpression link similarity graph clustering for mining biological modules from multiple gene expression datasets.

PubMed

Salem, Saeed; Ozcaglar, Cagri

2014-01-01

Advances in genomic technologies have enabled the accumulation of vast amount of genomic data, including gene expression data for multiple species under various biological and environmental conditions. Integration of these gene expression datasets is a promising strategy to alleviate the challenges of protein functional annotation and biological module discovery based on a single gene expression data, which suffers from spurious coexpression. We propose a joint mining algorithm that constructs a weighted hybrid similarity graph whose nodes are the coexpression links. The weight of an edge between two coexpression links in this hybrid graph is a linear combination of the topological similarities and co-appearance similarities of the corresponding two coexpression links. Clustering the weighted hybrid similarity graph yields recurrent coexpression link clusters (modules). Experimental results on Human gene expression datasets show that the reported modules are functionally homogeneous as evident by their enrichment with biological process GO terms and KEGG pathways.
Estimation of zeta potential of electroosmotic flow in a microchannel using a reduced-order model.

PubMed

Park, H M; Hong, S M; Lee, J S

2007-10-01

A reduced-order model is derived for electroosmotic flow in a microchannel of nonuniform cross section using the Karhunen-Loève Galerkin (KLG) procedure. The resulting reduced-order model is shown to predict electroosmotic flows accurately with minimal consumption of computer time for a wide range of zeta potential zeta and dielectric constant epsilon. Using the reduced-order model, a practical method is devised to estimate zeta from the velocity measurements of the electroosmotic flow in the microchannel. The proposed method is found to estimate zeta with reasonable accuracy even with noisy velocity measurements.
Organization of the human [zeta]-crystallin/quinone reductase gene (CRYZ)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gonzalez, P.; Rao, P.V.; Zigler, J.S. Jr.

1994-05-15

[zeta]-Crystallin is a protein highly expressed in the lens of guinea pigs and camels, where it comprises about 10% of the total soluble protein. It has recently been characterized as a novel quinone oxidoreductase present in a variety of mammalian tissues. The authors report here the isolation and characterization of the human [zeta]-crystallin gene (CRYZ) and its processed pseudogene. The functional gene is composed of nine exons and spans about 20 kb. The 5[prime]-flanking region of the gene is rich in G and C (58%) and lacks TATA and CAAT boxes. Previous analysis of the guinea pig gene revealed themore » presence of two different promoters, one responsible for the high lens-specific expression and the other for expression at the enzymatic level in numerous tissues. Comparative analysis with the guinea pig gene shows that a region of [approximately]2.5 kb that includes the promoter responsible for the high expression in the lens in guinea pig is not present in the human gene. 34 refs., 6 figs., 1 tab.« less
GenoLink: a graph-based querying and browsing system for investigating the function of genes and proteins.

PubMed

Durand, Patrick; Labarre, Laurent; Meil, Alain; Divo, Jean-Louis; Vandenbrouck, Yves; Viari, Alain; Wojcik, Jérôme

2006-01-17

A large variety of biological data can be represented by graphs. These graphs can be constructed from heterogeneous data coming from genomic and post-genomic technologies, but there is still need for tools aiming at exploring and analysing such graphs. This paper describes GenoLink, a software platform for the graphical querying and exploration of graphs. GenoLink provides a generic framework for representing and querying data graphs. This framework provides a graph data structure, a graph query engine, allowing to retrieve sub-graphs from the entire data graph, and several graphical interfaces to express such queries and to further explore their results. A query consists in a graph pattern with constraints attached to the vertices and edges. A query result is the set of all sub-graphs of the entire data graph that are isomorphic to the pattern and satisfy the constraints. The graph data structure does not rely upon any particular data model but can dynamically accommodate for any user-supplied data model. However, for genomic and post-genomic applications, we provide a default data model and several parsers for the most popular data sources. GenoLink does not require any programming skill since all operations on graphs and the analysis of the results can be carried out graphically through several dedicated graphical interfaces. GenoLink is a generic and interactive tool allowing biologists to graphically explore various sources of information. GenoLink is distributed either as a standalone application or as a component of the Genostar/Iogma platform. Both distributions are free for academic research and teaching purposes and can be requested at academy@genostar.com. A commercial licence form can be obtained for profit company at info@genostar.com. See also http://www.genostar.org.
GenoLink: a graph-based querying and browsing system for investigating the function of genes and proteins

PubMed Central

Durand, Patrick; Labarre, Laurent; Meil, Alain; Divo1, Jean-Louis; Vandenbrouck, Yves; Viari, Alain; Wojcik, Jérôme

2006-01-01

Background A large variety of biological data can be represented by graphs. These graphs can be constructed from heterogeneous data coming from genomic and post-genomic technologies, but there is still need for tools aiming at exploring and analysing such graphs. This paper describes GenoLink, a software platform for the graphical querying and exploration of graphs. Results GenoLink provides a generic framework for representing and querying data graphs. This framework provides a graph data structure, a graph query engine, allowing to retrieve sub-graphs from the entire data graph, and several graphical interfaces to express such queries and to further explore their results. A query consists in a graph pattern with constraints attached to the vertices and edges. A query result is the set of all sub-graphs of the entire data graph that are isomorphic to the pattern and satisfy the constraints. The graph data structure does not rely upon any particular data model but can dynamically accommodate for any user-supplied data model. However, for genomic and post-genomic applications, we provide a default data model and several parsers for the most popular data sources. GenoLink does not require any programming skill since all operations on graphs and the analysis of the results can be carried out graphically through several dedicated graphical interfaces. Conclusion GenoLink is a generic and interactive tool allowing biologists to graphically explore various sources of information. GenoLink is distributed either as a standalone application or as a component of the Genostar/Iogma platform. Both distributions are free for academic research and teaching purposes and can be requested at academy@genostar.com. A commercial licence form can be obtained for profit company at info@genostar.com. See also . PMID:16417636
Statistics of Gaussian packets on metric and decorated graphs.

PubMed

Chernyshev, V L; Shafarevich, A I

2014-01-28

We study a semiclassical asymptotics of the Cauchy problem for a time-dependent Schrödinger equation on metric and decorated graphs with a localized initial function. A decorated graph is a topological space obtained from a graph via replacing vertices with smooth Riemannian manifolds. The main term of an asymptotic solution at an arbitrary finite time is a sum of Gaussian packets and generalized Gaussian packets (localized near a certain set of codimension one). We study the number of packets as time tends to infinity. We prove that under certain assumptions this number grows in time as a polynomial and packets fill the graph uniformly. We discuss a simple example of the opposite situation: in this case, a numerical experiment shows a subexponential growth.
Disconnection of network hubs and cognitive impairment after traumatic brain injury.

PubMed

Fagerholm, Erik D; Hellyer, Peter J; Scott, Gregory; Leech, Robert; Sharp, David J

2015-06-01

Traumatic brain injury affects brain connectivity by producing traumatic axonal injury. This disrupts the function of large-scale networks that support cognition. The best way to describe this relationship is unclear, but one elegant approach is to view networks as graphs. Brain regions become nodes in the graph, and white matter tracts the connections. The overall effect of an injury can then be estimated by calculating graph metrics of network structure and function. Here we test which graph metrics best predict the presence of traumatic axonal injury, as well as which are most highly associated with cognitive impairment. A comprehensive range of graph metrics was calculated from structural connectivity measures for 52 patients with traumatic brain injury, 21 of whom had microbleed evidence of traumatic axonal injury, and 25 age-matched controls. White matter connections between 165 grey matter brain regions were defined using tractography, and structural connectivity matrices calculated from skeletonized diffusion tensor imaging data. This technique estimates injury at the centre of tract, but is insensitive to damage at tract edges. Graph metrics were calculated from the resulting connectivity matrices and machine-learning techniques used to select the metrics that best predicted the presence of traumatic brain injury. In addition, we used regularization and variable selection via the elastic net to predict patient behaviour on tests of information processing speed, executive function and associative memory. Support vector machines trained with graph metrics of white matter connectivity matrices from the microbleed group were able to identify patients with a history of traumatic brain injury with 93.4% accuracy, a result robust to different ways of sampling the data. Graph metrics were significantly associated with cognitive performance: information processing speed (R(2) = 0.64), executive function (R(2) = 0.56) and associative memory (R(2) = 0.25). These results were then replicated in a separate group of patients without microbleeds. The most influential graph metrics were betweenness centrality and eigenvector centrality, which provide measures of the extent to which a given brain region connects other regions in the network. Reductions in betweenness centrality and eigenvector centrality were particularly evident within hub regions including the cingulate cortex and caudate. Our results demonstrate that betweenness centrality and eigenvector centrality are reduced within network hubs, due to the impact of traumatic axonal injury on network connections. The dominance of betweenness centrality and eigenvector centrality suggests that cognitive impairment after traumatic brain injury results from the disconnection of network hubs by traumatic axonal injury. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain.
14-3-3 sigma and 14-3-3 zeta plays an opposite role in cell growth inhibition mediated by transforming growth factor-beta 1.

PubMed

Hong, Hye-Young; Jeon, Woo-Kwang; Bae, Eun-Jin; Kim, Shin-Tae; Lee, Ho-Jae; Kim, Seong-Jin; Kim, Byung-Chul

2010-03-01

The expression of 14-3-3 proteins is dysregulated in various types of cancer. This study was undertaken to investigate the effects of 14-3-3 zeta and 14-3-3 sigma on cell growth inhibition mediated by transforming growth factor-beta 1 (TGF-beta1). Mouse mammary epithelial cells (Eph4) that are transformed with oncogenic c-H-Ras (EpRas) and no longer sensitive to TGF-beta1-mediated growth inhibition displayed increased expression of 14-3-3 zeta and decreased expression of 14-3-3 sigma compared with parental Eph4 cells. Using small interfering RNA-mediated knockdown and overexpression of 14-3-3 sigma or 14-3-3 zeta, we showed that 14-3-3 sigma is required for TGF-beta1-mediated growth inhibition whereas 14-3-3 zeta negatively modulates this growth inhibitory response. Notably, overexpression of 14-3-3 zeta increased the level of Smad3 protein that is phosphorylated at linker regions and cannot mediate the TGF-beta1 growth inhibitory response. Consistent with this finding, mutation of the 14-3-3 zeta phosphorylation sites in Smad3 markedly reduced the 14-3-3 zeta-mediated inhibition of TGF-beta1-induced p15 promoter-reporter activity and cell cycle arrest, suggesting that these residues are critical targets of 14-3-3 zeta in the suppression of TGF-beta1-mediated growth. Taken together, our findings indicate that dysregulation of 14-3-3 sigma or 14-3-3 zeta contributes to TGF-beta1 resistance in cancer cells.
Functional brain networks in Alzheimer's disease: EEG analysis based on limited penetrable visibility graph and phase space method

NASA Astrophysics Data System (ADS)

Wang, Jiang; Yang, Chen; Wang, Ruofan; Yu, Haitao; Cao, Yibin; Liu, Jing

2016-10-01

In this paper, EEG series are applied to construct functional connections with the correlation between different regions in order to investigate the nonlinear characteristic and the cognitive function of the brain with Alzheimer's disease (AD). First, limited penetrable visibility graph (LPVG) and phase space method map single EEG series into networks, and investigate the underlying chaotic system dynamics of AD brain. Topological properties of the networks are extracted, such as average path length and clustering coefficient. It is found that the network topology of AD in several local brain regions are different from that of the control group with no statistically significant difference existing all over the brain. Furthermore, in order to detect the abnormality of AD brain as a whole, functional connections among different brain regions are reconstructed based on similarity of clustering coefficient sequence (CCSS) of EEG series in the four frequency bands (delta, theta, alpha, and beta), which exhibit obvious small-world properties. Graph analysis demonstrates that for both methodologies, the functional connections between regions of AD brain decrease, particularly in the alpha frequency band. AD causes the graph index complexity of the functional network decreased, the small-world properties weakened, and the vulnerability increased. The obtained results show that the brain functional network constructed by LPVG and phase space method might be more effective to distinguish AD from the normal control than the analysis of single series, which is helpful for revealing the underlying pathological mechanism of the disease.

Spectral mapping of brain functional connectivity from diffusion imaging.

PubMed

Becker, Cassiano O; Pequito, Sérgio; Pappas, George J; Miller, Michael B; Grafton, Scott T; Bassett, Danielle S; Preciado, Victor M

2018-01-23

Understanding the relationship between the dynamics of neural processes and the anatomical substrate of the brain is a central question in neuroscience. On the one hand, modern neuroimaging technologies, such as diffusion tensor imaging, can be used to construct structural graphs representing the architecture of white matter streamlines linking cortical and subcortical structures. On the other hand, temporal patterns of neural activity can be used to construct functional graphs representing temporal correlations between brain regions. Although some studies provide evidence that whole-brain functional connectivity is shaped by the underlying anatomy, the observed relationship between function and structure is weak, and the rules by which anatomy constrains brain dynamics remain elusive. In this article, we introduce a methodology to map the functional connectivity of a subject at rest from his or her structural graph. Using our methodology, we are able to systematically account for the role of structural walks in the formation of functional correlations. Furthermore, in our empirical evaluations, we observe that the eigenmodes of the mapped functional connectivity are associated with activity patterns associated with different cognitive systems.
The graph neural network model.

PubMed

Scarselli, Franco; Gori, Marco; Tsoi, Ah Chung; Hagenbuchner, Markus; Monfardini, Gabriele

2009-01-01

Many underlying relationships among data in several areas of science and engineering, e.g., computer vision, molecular chemistry, molecular biology, pattern recognition, and data mining, can be represented in terms of graphs. In this paper, we propose a new neural network model, called graph neural network (GNN) model, that extends existing neural network methods for processing the data represented in graph domains. This GNN model, which can directly process most of the practically useful types of graphs, e.g., acyclic, cyclic, directed, and undirected, implements a function tau(G,n) is an element of IR(m) that maps a graph G and one of its nodes n into an m-dimensional Euclidean space. A supervised learning algorithm is derived to estimate the parameters of the proposed GNN model. The computational cost of the proposed algorithm is also considered. Some experimental results are shown to validate the proposed learning algorithm, and to demonstrate its generalization capabilities.
New method of computing the contributions of graphs without lepton loops to the electron anomalous magnetic moment in QED

NASA Astrophysics Data System (ADS)

Volkov, Sergey

2017-11-01

This paper presents a new method of numerical computation of the mass-independent QED contributions to the electron anomalous magnetic moment which arise from Feynman graphs without closed electron loops. The method is based on a forestlike subtraction formula that removes all ultraviolet and infrared divergences in each Feynman graph before integration in Feynman-parametric space. The integration is performed by an importance sampling Monte-Carlo algorithm with the probability density function that is constructed for each Feynman graph individually. The method is fully automated at any order of the perturbation series. The results of applying the method to 2-loop, 3-loop, 4-loop Feynman graphs, and to some individual 5-loop graphs are presented, as well as the comparison of this method with other ones with respect to Monte Carlo convergence speed.
Influence of surface conductivity on the apparent zeta potential of calcite.

PubMed

Li, Shuai; Leroy, Philippe; Heberling, Frank; Devau, Nicolas; Jougnot, Damien; Chiaberge, Christophe

2016-04-15

Zeta potential is a physicochemical parameter of particular importance in describing the surface electrical properties of charged porous media. However, the zeta potential of calcite is still poorly known because of the difficulty to interpret streaming potential experiments. The Helmholtz-Smoluchowski (HS) equation is widely used to estimate the apparent zeta potential from these experiments. However, this equation neglects the influence of surface conductivity on streaming potential. We present streaming potential and electrical conductivity measurements on a calcite powder in contact with an aqueous NaCl electrolyte. Our streaming potential model corrects the apparent zeta potential of calcite by accounting for the influence of surface conductivity and flow regime. We show that the HS equation seriously underestimates the zeta potential of calcite, particularly when the electrolyte is diluted (ionic strength ⩽ 0.01 M) because of calcite surface conductivity. The basic Stern model successfully predicted the corrected zeta potential by assuming that the zeta potential is located at the outer Helmholtz plane, i.e. without considering a stagnant diffuse layer at the calcite-water interface. The surface conductivity of calcite crystals was inferred from electrical conductivity measurements and computed using our basic Stern model. Surface conductivity was also successfully predicted by our surface complexation model. Copyright © 2016 Elsevier Inc. All rights reserved.
Determining similarity in histological images using graph-theoretic description and matching methods for content-based image retrieval in medical diagnostics.

PubMed

Sharma, Harshita; Alekseychuk, Alexander; Leskovsky, Peter; Hellwich, Olaf; Anand, R S; Zerbe, Norman; Hufnagl, Peter

2012-10-04

Computer-based analysis of digitalized histological images has been gaining increasing attention, due to their extensive use in research and routine practice. The article aims to contribute towards the description and retrieval of histological images by employing a structural method using graphs. Due to their expressive ability, graphs are considered as a powerful and versatile representation formalism and have obtained a growing consideration especially by the image processing and computer vision community. The article describes a novel method for determining similarity between histological images through graph-theoretic description and matching, for the purpose of content-based retrieval. A higher order (region-based) graph-based representation of breast biopsy images has been attained and a tree-search based inexact graph matching technique has been employed that facilitates the automatic retrieval of images structurally similar to a given image from large databases. The results obtained and evaluation performed demonstrate the effectiveness and superiority of graph-based image retrieval over a common histogram-based technique. The employed graph matching complexity has been reduced compared to the state-of-the-art optimal inexact matching methods by applying a pre-requisite criterion for matching of nodes and a sophisticated design of the estimation function, especially the prognosis function. The proposed method is suitable for the retrieval of similar histological images, as suggested by the experimental and evaluation results obtained in the study. It is intended for the use in Content Based Image Retrieval (CBIR)-requiring applications in the areas of medical diagnostics and research, and can also be generalized for retrieval of different types of complex images. The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1224798882787923.
Determining similarity in histological images using graph-theoretic description and matching methods for content-based image retrieval in medical diagnostics

PubMed Central

2012-01-01

Background Computer-based analysis of digitalized histological images has been gaining increasing attention, due to their extensive use in research and routine practice. The article aims to contribute towards the description and retrieval of histological images by employing a structural method using graphs. Due to their expressive ability, graphs are considered as a powerful and versatile representation formalism and have obtained a growing consideration especially by the image processing and computer vision community. Methods The article describes a novel method for determining similarity between histological images through graph-theoretic description and matching, for the purpose of content-based retrieval. A higher order (region-based) graph-based representation of breast biopsy images has been attained and a tree-search based inexact graph matching technique has been employed that facilitates the automatic retrieval of images structurally similar to a given image from large databases. Results The results obtained and evaluation performed demonstrate the effectiveness and superiority of graph-based image retrieval over a common histogram-based technique. The employed graph matching complexity has been reduced compared to the state-of-the-art optimal inexact matching methods by applying a pre-requisite criterion for matching of nodes and a sophisticated design of the estimation function, especially the prognosis function. Conclusion The proposed method is suitable for the retrieval of similar histological images, as suggested by the experimental and evaluation results obtained in the study. It is intended for the use in Content Based Image Retrieval (CBIR)-requiring applications in the areas of medical diagnostics and research, and can also be generalized for retrieval of different types of complex images. Virtual Slides The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1224798882787923. PMID:23035717
Design and assembly of ternary Pt/Re/SnO2 NPs by controlling the zeta potential of individual Pt, Re, and SnO2 NPs

NASA Astrophysics Data System (ADS)

Drzymała, Elżbieta; Gruzeł, Grzegorz; Pajor-Świerzy, Anna; Depciuch, Joanna; Socha, Robert; Kowal, Andrzej; Warszyński, Piotr; Parlinska-Wojtan, Magdalena

2018-05-01

In this study Pt, Re, and SnO2 nanoparticles (NPs) were combined in a controlled manner into binary and ternary combinations for a possible application for ethanol oxidation. For this purpose, zeta potentials as a function of the pH of the individual NPs solutions were measured. In order to successfully combine the NPs into Pt/SnO2 and Re/SnO2 NPs, the solutions were mixed together at a pH guaranteeing opposite zeta potentials of the metal and oxide NPs. The individually synthesized NPs and their binary/ternary combinations were characterized by Fourier transform infrared spectroscopy (FTIR) and scanning transmission electron microscopy (STEM) combined with energy dispersive X-ray spectroscopy (EDS) analysis. FTIR and XPS spectroscopy showed that the individually synthesized Pt and Re NPs are metallic and the Sn component was oxidized to SnO2. STEM showed that all NPs are well crystallized and the sizes of the Pt, Re, and SnO2 NPs were 2.2, 1.0, and 3.4 nm, respectively. Moreover, EDS analysis confirmed the successful formation of binary Pt/SnO2 and Re/SnO2 NP, as well as ternary Pt/Re/SnO2 NP combinations. This study shows that by controlling the zeta potential of individual metal and oxide NPs, it is possible to assemble them into binary and ternary combinations. [Figure not available: see fulltext.
RAG-3D: A search tool for RNA 3D substructures

DOE PAGES

Zahran, Mai; Sevim Bayrak, Cigdem; Elmetwaly, Shereef; ...

2015-08-24

In this study, to address many challenges in RNA structure/function prediction, the characterization of RNA's modular architectural units is required. Using the RNA-As-Graphs (RAG) database, we have previously explored the existence of secondary structure (2D) submotifs within larger RNA structures. Here we present RAG-3D—a dataset of RNA tertiary (3D) structures and substructures plus a web-based search tool—designed to exploit graph representations of RNAs for the goal of searching for similar 3D structural fragments. The objects in RAG-3D consist of 3D structures translated into 3D graphs, cataloged based on the connectivity between their secondary structure elements. Each graph is additionally describedmore » in terms of its subgraph building blocks. The RAG-3D search tool then compares a query RNA 3D structure to those in the database to obtain structurally similar structures and substructures. This comparison reveals conserved 3D RNA features and thus may suggest functional connections. Though RNA search programs based on similarity in sequence, 2D, and/or 3D structural elements are available, our graph-based search tool may be advantageous for illuminating similarities that are not obvious; using motifs rather than sequence space also reduces search times considerably. Ultimately, such substructuring could be useful for RNA 3D structure prediction, structure/function inference and inverse folding.« less
RAG-3D: a search tool for RNA 3D substructures

PubMed Central

Zahran, Mai; Sevim Bayrak, Cigdem; Elmetwaly, Shereef; Schlick, Tamar

2015-01-01

To address many challenges in RNA structure/function prediction, the characterization of RNA's modular architectural units is required. Using the RNA-As-Graphs (RAG) database, we have previously explored the existence of secondary structure (2D) submotifs within larger RNA structures. Here we present RAG-3D—a dataset of RNA tertiary (3D) structures and substructures plus a web-based search tool—designed to exploit graph representations of RNAs for the goal of searching for similar 3D structural fragments. The objects in RAG-3D consist of 3D structures translated into 3D graphs, cataloged based on the connectivity between their secondary structure elements. Each graph is additionally described in terms of its subgraph building blocks. The RAG-3D search tool then compares a query RNA 3D structure to those in the database to obtain structurally similar structures and substructures. This comparison reveals conserved 3D RNA features and thus may suggest functional connections. Though RNA search programs based on similarity in sequence, 2D, and/or 3D structural elements are available, our graph-based search tool may be advantageous for illuminating similarities that are not obvious; using motifs rather than sequence space also reduces search times considerably. Ultimately, such substructuring could be useful for RNA 3D structure prediction, structure/function inference and inverse folding. PMID:26304547
RAG-3D: A search tool for RNA 3D substructures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zahran, Mai; Sevim Bayrak, Cigdem; Elmetwaly, Shereef

In this study, to address many challenges in RNA structure/function prediction, the characterization of RNA's modular architectural units is required. Using the RNA-As-Graphs (RAG) database, we have previously explored the existence of secondary structure (2D) submotifs within larger RNA structures. Here we present RAG-3D—a dataset of RNA tertiary (3D) structures and substructures plus a web-based search tool—designed to exploit graph representations of RNAs for the goal of searching for similar 3D structural fragments. The objects in RAG-3D consist of 3D structures translated into 3D graphs, cataloged based on the connectivity between their secondary structure elements. Each graph is additionally describedmore » in terms of its subgraph building blocks. The RAG-3D search tool then compares a query RNA 3D structure to those in the database to obtain structurally similar structures and substructures. This comparison reveals conserved 3D RNA features and thus may suggest functional connections. Though RNA search programs based on similarity in sequence, 2D, and/or 3D structural elements are available, our graph-based search tool may be advantageous for illuminating similarities that are not obvious; using motifs rather than sequence space also reduces search times considerably. Ultimately, such substructuring could be useful for RNA 3D structure prediction, structure/function inference and inverse folding.« less
Oscillatory electroosmotic flow in a parallel-plate microchannel under asymmetric zeta potentials

NASA Astrophysics Data System (ADS)

Peralta, M.; Arcos, J.; Méndez, F.; Bautista, O.

2017-06-01

In this work, we conduct a theoretical analysis of the start-up of an oscillatory electroosmotic flow (EOF) in a parallel-plate microchannel under asymmetric zeta potentials. It is found that the transient evolution of the flow field is controlled by the parameters {R}ω , {R}\\zeta , and \\bar{κ }, which represent the dimensionless frequency, the ratio of the zeta potentials of the microchannel walls, and the electrokinetic parameter, which is defined as the ratio of the microchannel height to the Debye length. The analysis is performed for both low and high zeta potentials; in the former case, an analytical solution is derived, whereas in the latter, a numerical solution is obtained. These solutions provide the fundamental characteristics of the oscillatory EOFs for which, with suitable adjustment of the zeta potential and the dimensionless frequency, the velocity profiles of the fluid flow exhibit symmetric or asymmetric shapes.
Line identifications in the ultraviolet spectra of Tau Herculis, B5 IV, and Zeta Draconis, B6 III

NASA Technical Reports Server (NTRS)

Underhill, A. B.; Adelman, S. J.

1976-01-01

Tables of the lines found on two tracings each of the ultraviolet spectrum of Tau Her, B5 IV, and Zeta Dra, B6 III, made by the Copernicus satellite and possible identifications are given. The ranges 1025-1451A for Tau Her and 1035 to 1425A for Zeta Dra are covered by the U2 spectrometer at a resolution of 0.2A; the ranges 2028 to 2959A for Tau Her and 2000 to 3000A for Zeta Dra are covered by the V2 spectrometer at a resolution of 0.4A. The observed density of lines in the U2 region is 1.1 lines/A for Tau Her and 1.7 lines/A for Zeta Dra. In the V2 region it is 0.8 lines/A for Tau Her and 0.9 lines/A for Zeta Dra.
GraphCrunch 2: Software tool for network modeling, alignment and clustering.

PubMed

Kuchaiev, Oleksii; Stevanović, Aleksandar; Hayes, Wayne; Pržulj, Nataša

2011-01-19

Recent advancements in experimental biotechnology have produced large amounts of protein-protein interaction (PPI) data. The topology of PPI networks is believed to have a strong link to their function. Hence, the abundance of PPI data for many organisms stimulates the development of computational techniques for the modeling, comparison, alignment, and clustering of networks. In addition, finding representative models for PPI networks will improve our understanding of the cell just as a model of gravity has helped us understand planetary motion. To decide if a model is representative, we need quantitative comparisons of model networks to real ones. However, exact network comparison is computationally intractable and therefore several heuristics have been used instead. Some of these heuristics are easily computable "network properties," such as the degree distribution, or the clustering coefficient. An important special case of network comparison is the network alignment problem. Analogous to sequence alignment, this problem asks to find the "best" mapping between regions in two networks. It is expected that network alignment might have as strong an impact on our understanding of biology as sequence alignment has had. Topology-based clustering of nodes in PPI networks is another example of an important network analysis problem that can uncover relationships between interaction patterns and phenotype. We introduce the GraphCrunch 2 software tool, which addresses these problems. It is a significant extension of GraphCrunch which implements the most popular random network models and compares them with the data networks with respect to many network properties. Also, GraphCrunch 2 implements the GRAph ALigner algorithm ("GRAAL") for purely topological network alignment. GRAAL can align any pair of networks and exposes large, dense, contiguous regions of topological and functional similarities far larger than any other existing tool. Finally, GraphCruch 2 implements an algorithm for clustering nodes within a network based solely on their topological similarities. Using GraphCrunch 2, we demonstrate that eukaryotic and viral PPI networks may belong to different graph model families and show that topology-based clustering can reveal important functional similarities between proteins within yeast and human PPI networks. GraphCrunch 2 is a software tool that implements the latest research on biological network analysis. It parallelizes computationally intensive tasks to fully utilize the potential of modern multi-core CPUs. It is open-source and freely available for research use. It runs under the Windows and Linux platforms.
Anisotropic Laplace-Beltrami Eigenmaps: Bridging Reeb Graphs and Skeletons*

PubMed Central

Shi, Yonggang; Lai, Rongjie; Krishna, Sheila; Sicotte, Nancy; Dinov, Ivo; Toga, Arthur W.

2010-01-01

In this paper we propose a novel approach of computing skeletons of robust topology for simply connected surfaces with boundary by constructing Reeb graphs from the eigenfunctions of an anisotropic Laplace-Beltrami operator. Our work brings together the idea of Reeb graphs and skeletons by incorporating a flux-based weight function into the Laplace-Beltrami operator. Based on the intrinsic geometry of the surface, the resulting Reeb graph is pose independent and captures the global profile of surface geometry. Our algorithm is very efficient and it only takes several seconds to compute on neuroanatomical structures such as the cingulate gyrus and corpus callosum. In our experiments, we show that the Reeb graphs serve well as an approximate skeleton with consistent topology while following the main body of conventional skeletons quite accurately. PMID:21339850
(q,{mu}) and (p,q,{zeta})-exponential functions: Rogers-Szego'' polynomials and Fourier-Gauss transform

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hounkonnou, Mahouton Norbert; Nkouankam, Elvis Benzo Ngompe

2010-10-15

From the realization of q-oscillator algebra in terms of generalized derivative, we compute the matrix elements from deformed exponential functions and deduce generating functions associated with Rogers-Szego polynomials as well as their relevant properties. We also compute the matrix elements associated with the (p,q)-oscillator algebra (a generalization of the q-one) and perform the Fourier-Gauss transform of a generalization of the deformed exponential functions.
On Connected Diagrams and Cumulants of Erdős-Rényi Matrix Models

NASA Astrophysics Data System (ADS)

Khorunzhiy, O.

2008-08-01

Regarding the adjacency matrices of n-vertex graphs and related graph Laplacian we introduce two families of discrete matrix models constructed both with the help of the Erdős-Rényi ensemble of random graphs. Corresponding matrix sums represent the characteristic functions of the average number of walks and closed walks over the random graph. These sums can be considered as discrete analogues of the matrix integrals of random matrix theory. We study the diagram structure of the cumulant expansions of logarithms of these matrix sums and analyze the limiting expressions as n → ∞ in the cases of constant and vanishing edge probabilities.
Counting the number of Feynman graphs in QCD

NASA Astrophysics Data System (ADS)

Kaneko, T.

2018-05-01

Information about the number of Feynman graphs for a given physical process in a given field theory is especially useful for confirming the result of a Feynman graph generator used in an automatic system of perturbative calculations. A method of counting the number of Feynman graphs with weight of symmetry factor was established based on zero-dimensional field theory, and was used in scalar theories and QED. In this article this method is generalized to more complicated models by direct calculation of generating functions on a computer algebra system. This method is applied to QCD with and without counter terms, where many higher order are being calculated automatically.
Markov models for fMRI correlation structure: Is brain functional connectivity small world, or decomposable into networks?

PubMed

Varoquaux, G; Gramfort, A; Poline, J B; Thirion, B

2012-01-01

Correlations in the signal observed via functional Magnetic Resonance Imaging (fMRI), are expected to reveal the interactions in the underlying neural populations through hemodynamic response. In particular, they highlight distributed set of mutually correlated regions that correspond to brain networks related to different cognitive functions. Yet graph-theoretical studies of neural connections give a different picture: that of a highly integrated system with small-world properties: local clustering but with short pathways across the complete structure. We examine the conditional independence properties of the fMRI signal, i.e. its Markov structure, to find realistic assumptions on the connectivity structure that are required to explain the observed functional connectivity. In particular we seek a decomposition of the Markov structure into segregated functional networks using decomposable graphs: a set of strongly-connected and partially overlapping cliques. We introduce a new method to efficiently extract such cliques on a large, strongly-connected graph. We compare methods learning different graph structures from functional connectivity by testing the goodness of fit of the model they learn on new data. We find that summarizing the structure as strongly-connected networks can give a good description only for very large and overlapping networks. These results highlight that Markov models are good tools to identify the structure of brain connectivity from fMRI signals, but for this purpose they must reflect the small-world properties of the underlying neural systems. Copyright © 2012 Elsevier Ltd. All rights reserved.
Global Binary Optimization on Graphs for Classification of High Dimensional Data

DTIC Science & Technology

2014-09-01

Buades et al . in [10] introduce a new non-local means algorithm for image denoising and compare it to some of the best methods. In [28], Grady de...scribes a random walk algorithm for image seg- mentation using the solution to a Dirichlet prob- lem. Elmoataz et al . present generalizations of the...graph Laplacian [19] for image denoising and man- ifold smoothing. Couprie et al . in [16] propose a parameterized graph-based energy function that unifies
Discriminative graph embedding for label propagation.

PubMed

Nguyen, Canh Hao; Mamitsuka, Hiroshi

2011-09-01

In many applications, the available information is encoded in graph structures. This is a common problem in biological networks, social networks, web communities and document citations. We investigate the problem of classifying nodes' labels on a similarity graph given only a graph structure on the nodes. Conventional machine learning methods usually require data to reside in some Euclidean spaces or to have a kernel representation. Applying these methods to nodes on graphs would require embedding the graphs into these spaces. By embedding and then learning the nodes on graphs, most methods are either flexible with different learning objectives or efficient enough for large scale applications. We propose a method to embed a graph into a feature space for a discriminative purpose. Our idea is to include label information into the embedding process, making the space representation tailored to the task. We design embedding objective functions that the following learning formulations become spectral transforms. We then reformulate these spectral transforms into multiple kernel learning problems. Our method, while being tailored to the discriminative tasks, is efficient and can scale to massive data sets. We show the need of discriminative embedding on some simulations. Applying to biological network problems, our method is shown to outperform baselines.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Khvorostukhin, A. S.; Joint Institute for Nuclear Research, 141980 Dubna; Institute of Applied Physics, Moldova Academy of Science, MD-2028 Kishineu

Shear {eta} and bulk {zeta} viscosities are calculated in a quasiparticle model within a relaxation-time approximation for pure gluon matter. Below T{sub c}, the confined sector is described within a quasiparticle glueball model. The constructed equation of state reproduces the first-order phase transition for the glue matter. It is shown that with this equation of state, it is possible to describe the temperature dependence of the shear viscosity to entropy ratio {eta}/s and the bulk viscosity to entropy ratio {zeta}/s in reasonable agreement with available lattice data, but absolute values of the {zeta}/s ratio underestimate the upper limits of thismore » ratio in the lattice measurements typically by an order of magnitude.« less
Protein-protein interaction network-based detection of functionally similar proteins within species.

PubMed

Song, Baoxing; Wang, Fen; Guo, Yang; Sang, Qing; Liu, Min; Li, Dengyun; Fang, Wei; Zhang, Deli

2012-07-01

Although functionally similar proteins across species have been widely studied, functionally similar proteins within species showing low sequence similarity have not been examined in detail. Identification of these proteins is of significant importance for understanding biological functions, evolution of protein families, progression of co-evolution, and convergent evolution and others which cannot be obtained by detection of functionally similar proteins across species. Here, we explored a method of detecting functionally similar proteins within species based on graph theory. After denoting protein-protein interaction networks using graphs, we split the graphs into subgraphs using the 1-hop method. Proteins with functional similarities in a species were detected using a method of modified shortest path to compare these subgraphs and to find the eligible optimal results. Using seven protein-protein interaction networks and this method, some functionally similar proteins with low sequence similarity that cannot detected by sequence alignment were identified. By analyzing the results, we found that, sometimes, it is difficult to separate homologous from convergent evolution. Evaluation of the performance of our method by gene ontology term overlap showed that the precision of our method was excellent. Copyright © 2012 Wiley Periodicals, Inc.
Analysis of Resting-State fMRI Topological Graph Theory Properties in Methamphetamine Drug Users Applying Box-Counting Fractal Dimension.

PubMed

Siyah Mansoory, Meysam; Oghabian, Mohammad Ali; Jafari, Amir Homayoun; Shahbabaie, Alireza

2017-01-01

Graph theoretical analysis of functional Magnetic Resonance Imaging (fMRI) data has provided new measures of mapping human brain in vivo. Of all methods to measure the functional connectivity between regions, Linear Correlation (LC) calculation of activity time series of the brain regions as a linear measure is considered the most ubiquitous one. The strength of the dependence obligatory for graph construction and analysis is consistently underestimated by LC, because not all the bivariate distributions, but only the marginals are Gaussian. In a number of studies, Mutual Information (MI) has been employed, as a similarity measure between each two time series of the brain regions, a pure nonlinear measure. Owing to the complex fractal organization of the brain indicating self-similarity, more information on the brain can be revealed by fMRI Fractal Dimension (FD) analysis. In the present paper, Box-Counting Fractal Dimension (BCFD) is introduced for graph theoretical analysis of fMRI data in 17 methamphetamine drug users and 18 normal controls. Then, BCFD performance was evaluated compared to those of LC and MI methods. Moreover, the global topological graph properties of the brain networks inclusive of global efficiency, clustering coefficient and characteristic path length in addict subjects were investigated too. Compared to normal subjects by using statistical tests (P<0.05), topological graph properties were postulated to be disrupted significantly during the resting-state fMRI. Based on the results, analyzing the graph topological properties (representing the brain networks) based on BCFD is a more reliable method than LC and MI.
Effect of pH and ionic strength on exposure and toxicity of encapsulated lambda-cyhalothrin to Daphnia magna.

PubMed

Son, Jino; Hooven, Louisa A; Harper, Bryan; Harper, Stacey L

2015-12-15

Encapsulation of pesticide active ingredients in polymers has been widely employed to control the release of poorly water-soluble active ingredients. Given the high dispersibility of these encapsulated pesticides in water, they are expected to behave differently compared to their active ingredients; however, our current understanding of the fate and effects of encapsulated pesticides is still limited. In this study, we employed a central composite design (CCD) to investigate how pH and ionic strength (IS) affect the hydrodynamic diameter (HDD) and zeta potential of encapsulated λ-cyhalothrin and how those changes affect the exposure and toxicity to Daphnia magna. R(2) values greater than 0.82 and 0.84 for HDD and zeta potential, respectively, irrespective of incubation time suggest those changes could be predicted as a function of pH and IS. For HDD, the linear factor of pH and quadratic factor of pH×pH were found to be the most significant factors affecting the change of HDD at the beginning of incubation, whereas the effects of IS and IS×IS became significant as incubation time increased. For zeta potential, the linear factor of IS and quadratic factor of IS×IS were found to be the most dominant factors affecting the change of zeta potential of encapsulated λ-cyhalothrin, irrespective of incubation time. The toxicity tests with D. magna under exposure conditions in which HDD or zeta potential of encapsulated λ-cyhalothrin was maximized or minimized in the overlying water also clearly showed the worst-case exposure condition to D. magna was when the encapsulated λ-cyhalothrin is either stable or small in the overlying water. Our results show that water quality could modify the fate and toxicity of encapsulated λ-cyhalothrin in aquatic environments, suggesting understanding their aquatic interactions are critical in environmental risk assessment. Herein, we discuss the implications of our findings for risk assessment. Copyright © 2015 Elsevier B.V. All rights reserved.
The Construction of {P}_{2}\\vartriangleright H-antimagic graph using smaller edge-antimagic vertex labeling

NASA Astrophysics Data System (ADS)

Prihandini, Rafiantika M.; Agustin, I. H.; Dafik

2018-04-01

In this paper we use simple and non trivial graph. If there exist a bijective function g:V(G) \\cup E(G)\\to \\{1,2,\\ldots,|V(G)|+|E(G)|\\}, such that for all subgraphs {P}2\\vartriangleright H of G isomorphic to H, then graph G is called an (a, b)-{P}2\\vartriangleright H-antimagic total graph. Furthermore, we can consider the total {P}2\\vartriangleright H-weights W({P}2\\vartriangleright H)={\\sum }v\\in V({P2\\vartriangleright H)}f(v)+{\\sum }e\\in E({P2\\vartriangleright H)}f(e) which should form an arithmetic sequence {a, a + d, a + 2d, …, a + (n ‑ 1)d}, where a and d are positive integers and n is the number of all subgraphs isomorphic to H. Our paper describes the existence of super (a, b)-{P}2\\vartriangleright H antimagic total labeling for graph operation of comb product namely of G=L\\vartriangleright H, where L is a (b, d*)-edge antimagic vertex labeling graph and H is a connected graph.
Test-Retest Reliability of Graph Metrics in Functional Brain Networks: A Resting-State fNIRS Study

PubMed Central

Niu, Haijing; Li, Zhen; Liao, Xuhong; Wang, Jinhui; Zhao, Tengda; Shu, Ni; Zhao, Xiaohu; He, Yong

2013-01-01

Recent research has demonstrated the feasibility of combining functional near-infrared spectroscopy (fNIRS) and graph theory approaches to explore the topological attributes of human brain networks. However, the test-retest (TRT) reliability of the application of graph metrics to these networks remains to be elucidated. Here, we used resting-state fNIRS and a graph-theoretical approach to systematically address TRT reliability as it applies to various features of human brain networks, including functional connectivity, global network metrics and regional nodal centrality metrics. Eighteen subjects participated in two resting-state fNIRS scan sessions held ∼20 min apart. Functional brain networks were constructed for each subject by computing temporal correlations on three types of hemoglobin concentration information (HbO, HbR, and HbT). This was followed by a graph-theoretical analysis, and then an intraclass correlation coefficient (ICC) was further applied to quantify the TRT reliability of each network metric. We observed that a large proportion of resting-state functional connections (∼90%) exhibited good reliability (0.6< ICC <0.74). For global and nodal measures, reliability was generally threshold-sensitive and varied among both network metrics and hemoglobin concentration signals. Specifically, the majority of global metrics exhibited fair to excellent reliability, with notably higher ICC values for the clustering coefficient (HbO: 0.76; HbR: 0.78; HbT: 0.53) and global efficiency (HbO: 0.76; HbR: 0.70; HbT: 0.78). Similarly, both nodal degree and efficiency measures also showed fair to excellent reliability across nodes (degree: 0.52∼0.84; efficiency: 0.50∼0.84); reliability was concordant across HbO, HbR and HbT and was significantly higher than that of nodal betweenness (0.28∼0.68). Together, our results suggest that most graph-theoretical network metrics derived from fNIRS are TRT reliable and can be used effectively for brain network research. This study also provides important guidance on the choice of network metrics of interest for future applied research in developmental and clinical neuroscience. PMID:24039763
Hybrid coexpression link similarity graph clustering for mining biological modules from multiple gene expression datasets

PubMed Central

2014-01-01

Background Advances in genomic technologies have enabled the accumulation of vast amount of genomic data, including gene expression data for multiple species under various biological and environmental conditions. Integration of these gene expression datasets is a promising strategy to alleviate the challenges of protein functional annotation and biological module discovery based on a single gene expression data, which suffers from spurious coexpression. Results We propose a joint mining algorithm that constructs a weighted hybrid similarity graph whose nodes are the coexpression links. The weight of an edge between two coexpression links in this hybrid graph is a linear combination of the topological similarities and co-appearance similarities of the corresponding two coexpression links. Clustering the weighted hybrid similarity graph yields recurrent coexpression link clusters (modules). Experimental results on Human gene expression datasets show that the reported modules are functionally homogeneous as evident by their enrichment with biological process GO terms and KEGG pathways. PMID:25221624
Robust Joint Graph Sparse Coding for Unsupervised Spectral Feature Selection.

PubMed

Zhu, Xiaofeng; Li, Xuelong; Zhang, Shichao; Ju, Chunhua; Wu, Xindong

2017-06-01

In this paper, we propose a new unsupervised spectral feature selection model by embedding a graph regularizer into the framework of joint sparse regression for preserving the local structures of data. To do this, we first extract the bases of training data by previous dictionary learning methods and, then, map original data into the basis space to generate their new representations, by proposing a novel joint graph sparse coding (JGSC) model. In JGSC, we first formulate its objective function by simultaneously taking subspace learning and joint sparse regression into account, then, design a new optimization solution to solve the resulting objective function, and further prove the convergence of the proposed solution. Furthermore, we extend JGSC to a robust JGSC (RJGSC) via replacing the least square loss function with a robust loss function, for achieving the same goals and also avoiding the impact of outliers. Finally, experimental results on real data sets showed that both JGSC and RJGSC outperformed the state-of-the-art algorithms in terms of k -nearest neighbor classification performance.
Density-functional theory of spherical electric double layers and zeta potentials of colloidal particles in restricted-primitive-model electrolyte solutions.

PubMed

Yu, Yang-Xin; Wu, Jianzhong; Gao, Guang-Hua

2004-04-15

A density-functional theory is proposed to describe the density profiles of small ions around an isolated colloidal particle in the framework of the restricted primitive model where the small ions have uniform size and the solvent is represented by a dielectric continuum. The excess Helmholtz energy functional is derived from a modified fundamental measure theory for the hard-sphere repulsion and a quadratic functional Taylor expansion for the electrostatic interactions. The theoretical predictions are in good agreement with the results from Monte Carlo simulations and from previous investigations using integral-equation theory for the ionic density profiles and the zeta potentials of spherical particles at a variety of solution conditions. Like the integral-equation approaches, the density-functional theory is able to capture the oscillatory density profiles of small ions and the charge inversion (overcharging) phenomena for particles with elevated charge density. In particular, our density-functional theory predicts the formation of a second counterion layer near the surface of highly charged spherical particle. Conversely, the nonlinear Poisson-Boltzmann theory and its variations are unable to represent the oscillatory behavior of small ion distributions and charge inversion. Finally, our density-functional theory predicts charge inversion even in a 1:1 electrolyte solution as long as the salt concentration is sufficiently high. (c) 2004 American Institute of Physics.
Descriptions of Free and Freeware Software in the Mathematics Teaching

NASA Astrophysics Data System (ADS)

Antunes de Macedo, Josue; Neves de Almeida, Samara; Voelzke, Marcos Rincon

2016-05-01

This paper presents the analysis and the cataloging of free and freeware mathematical software available on the internet, a brief explanation of them, and types of licenses for use in teaching and learning. The methodology is based on the qualitative research. Among the different types of software found, it stands out in algebra, the Winmat, that works with linear algebra, matrices and linear systems. In geometry, the GeoGebra, which can be used in the study of functions, plan and spatial geometry, algebra and calculus. For graphing, can quote the Graph and Graphequation. With Graphmatica software, it is possible to build various graphs of mathematical equations on the same screen, representing cartesian equations, inequalities, parametric among other functions. The Winplot allows the user to build graphics in two and three dimensions functions and mathematical equations. Thus, this work aims to present the teachers some free math software able to be used in the classroom.
Polyglycerol-functionalized nanodiamond as a platform for gene delivery: Derivatization, characterization, and hybridization with DNA

PubMed Central

Zhao, Li; Nakae, Yuki; Qin, Hongmei; Ito, Tadamasa; Kimura, Takahide; Kojima, Hideto; Chan, Lawrence

2014-01-01

Summary A gene vector consisting of nanodiamond, polyglycerol, and basic polypeptide (ND-PG-BPP) has been designed, synthesized, and characterized. The ND-PG-BPP was synthesized by PG functionalization of ND through ring-opening polymerization of glycidol on the ND surface, multistep organic transformations (–OH → –OTs (tosylate) → –N3) in the PG layer, and click conjugation of the basic polypeptides (Arg8, Lys8 or His8) terminated with propargyl glycine. The ND-PG-BPP exhibited good dispersibility in water (>1.0 mg/mL) and positive zeta potential ranging from +14.2 mV to +44.1 mV at neutral pH in Milli-Q water. It was confirmed by gel retardation assay that ND-PG-Arg8 and ND-PG-Lys8 with higher zeta potential hybridized with plasmid DNA (pDNA) through electrostatic attraction, making them promising as nonviral vectors for gene delivery. PMID:24778723
A model of the general ocean circulation determined from a joint solution for the Earth's gravity field

NASA Technical Reports Server (NTRS)

Nerem, R. S.; Tapley, B. D.; Shum, C. K.; Yuan, D. N.

1989-01-01

If the geoid and the satellite position are known accurately, satellite altimetry can be used to determine the geostrophic velocity of the surface ocean currents. The purpose of this investigation is to simultaneously estimate the sea surface topography, zeta, the model for the gravity field, and the satellite orbit. Satellite tracking data from fourteen satellites were used; along with Seasat and Geosat altimeter data as well as surface gravity data for the solution. The estimated model of zeta compares well at long wavelengths with the hydrographic model of zeta. Covariance studies show that the geoid is separable from zeta up to degree 9, at which point geoid error becomes comparable to the signal of zeta.
Measuring graph similarity through continuous-time quantum walks and the quantum Jensen-Shannon divergence.

PubMed

Rossi, Luca; Torsello, Andrea; Hancock, Edwin R

2015-02-01

In this paper we propose a quantum algorithm to measure the similarity between a pair of unattributed graphs. We design an experiment where the two graphs are merged by establishing a complete set of connections between their nodes and the resulting structure is probed through the evolution of continuous-time quantum walks. In order to analyze the behavior of the walks without causing wave function collapse, we base our analysis on the recently introduced quantum Jensen-Shannon divergence. In particular, we show that the divergence between the evolution of two suitably initialized quantum walks over this structure is maximum when the original pair of graphs is isomorphic. We also prove that under special conditions the divergence is minimum when the sets of eigenvalues of the Hamiltonians associated with the two original graphs have an empty intersection.
Effect of Graph Scale on Risky Choice: Evidence from Preference and Process in Decision-Making

PubMed Central

Sun, Yan; Li, Shu; Bonini, Nicolao; Liu, Yang

2016-01-01

We investigate the effect of graph scale on risky choices. By (de)compressing the scale, we manipulate the relative physical distance between options on a given attribute in a coordinate graphical context. In Experiment 1, the risky choice changes as a function of the scale in the graph. In Experiment 2, we show that the type of graph scale also affects decision times. In Experiment 3, we examine the graph scale effect by using real money among students who have taken statistics courses. Consequently, the scale effects still appear even when we control the variations in calculation ability and increase the gravity with which participants view the consequence of their decisions. This finding is inconsistent with descriptive invariance of preference. The theoretical implications and practical applications of the findings are discussed. PMID:26771530
Upper bound for the span of pencil graph

NASA Astrophysics Data System (ADS)

Parvathi, N.; Vimala Rani, A.

2018-04-01

An L(2,1)-Coloring or Radio Coloring or λ coloring of a graph is a function f from the vertex set V(G) to the set of all nonnegative integers such that |f(x) ‑ f(y)| ≥ 2 if d(x,y) = 1 and |f(x) ‑ f(y)| ≥ 1 if d(x,y)=2, where d(x,y) denotes the distance between x and y in G. The L(2,1)-coloring number or span number λ(G) of G is the smallest number k such that G has an L(2,1)-coloring with max{f(v) : v ∈ V(G)} = k. [2]The minimum number of colors used in L(2,1)-coloring is called the radio number rn(G) of G (Positive integer). Griggs and yeh conjectured that λ(G) ≤ Δ2 for any simple graph with maximum degree Δ>2. In this article, we consider some special graphs like, n-sunlet graph, pencil graph families and derive its upper bound of (G) and rn(G).
Unimodular lattice triangulations as small-world and scale-free random graphs

NASA Astrophysics Data System (ADS)

Krüger, B.; Schmidt, E. M.; Mecke, K.

2015-02-01

Real-world networks, e.g., the social relations or world-wide-web graphs, exhibit both small-world and scale-free behaviour. We interpret lattice triangulations as planar graphs by identifying triangulation vertices with graph nodes and one-dimensional simplices with edges. Since these triangulations are ergodic with respect to a certain Pachner flip, applying different Monte Carlo simulations enables us to calculate average properties of random triangulations, as well as canonical ensemble averages, using an energy functional that is approximately the variance of the degree distribution. All considered triangulations have clustering coefficients comparable with real-world graphs; for the canonical ensemble there are inverse temperatures with small shortest path length independent of system size. Tuning the inverse temperature to a quasi-critical value leads to an indication of scale-free behaviour for degrees k≥slant 5. Using triangulations as a random graph model can improve the understanding of real-world networks, especially if the actual distance of the embedded nodes becomes important.
Zeta Ophiuchi -- Runaway Star Plowing through Space Dust

NASA Image and Video Library

2011-01-24

The blue star near the center of this image is Zeta Ophiuchi. Zeta Ophiuchi is actually a very massive, hot, bright blue star plowing its way through a large cloud of interstellar dust and gas in this image from NASA Wide-field Infrared Survey Explorer.
Implementation of the Baldwin-Barth turbulence model into the ZETA code and its diagnosis. M.S. Thesis

NASA Technical Reports Server (NTRS)

Low, Scott L.

1993-01-01

The Baldwin-Barth turbulence model was implemented into Zeta, a time-accurate, zonal, integro-differential code for incompressible laminar and turbulent flows. The implementation procedure is patterned after the model subroutine in ARC2D. The results of ZETA with the Baldwin-Barth turbulence model were compared with experimental data, with ZETA using Baldwin-Lomax model, and with ARC2D using the Baldwin-Barth model. The Baldwin-Barth model subroutine was tested by inputting an ARC2D velocity solution of an NACA-0012 airfoil at R(sub e) = 3.9 x 10(exp 6) and alpha = 5 deg. The resultant turbulent viscosity and Reynolds stresses compared favorably with the original data. For the same grid having grid points inside the laminar sublayer, which is necessary due to the one-equation nature of the model, ZETA however predicts early separation. It was found that the current ZETA has problem with such a fine grid. Further work is in progress to solve this problem.
Graph pyramids for protein function prediction

PubMed Central

2015-01-01

Background Uncovering the hidden organizational characteristics and regularities among biological sequences is the key issue for detailed understanding of an underlying biological phenomenon. Thus pattern recognition from nucleic acid sequences is an important affair for protein function prediction. As proteins from the same family exhibit similar characteristics, homology based approaches predict protein functions via protein classification. But conventional classification approaches mostly rely on the global features by considering only strong protein similarity matches. This leads to significant loss of prediction accuracy. Methods Here we construct the Protein-Protein Similarity (PPS) network, which captures the subtle properties of protein families. The proposed method considers the local as well as the global features, by examining the interactions among 'weakly interacting proteins' in the PPS network and by using hierarchical graph analysis via the graph pyramid. Different underlying properties of the protein families are uncovered by operating the proposed graph based features at various pyramid levels. Results Experimental results on benchmark data sets show that the proposed hierarchical voting algorithm using graph pyramid helps to improve computational efficiency as well the protein classification accuracy. Quantitatively, among 14,086 test sequences, on an average the proposed method misclassified only 21.1 sequences whereas baseline BLAST score based global feature matching method misclassified 362.9 sequences. With each correctly classified test sequence, the fast incremental learning ability of the proposed method further enhances the training model. Thus it has achieved more than 96% protein classification accuracy using only 20% per class training data. PMID:26044522
Graph pyramids for protein function prediction.

PubMed

Sandhan, Tushar; Yoo, Youngjun; Choi, Jin; Kim, Sun

2015-01-01

Uncovering the hidden organizational characteristics and regularities among biological sequences is the key issue for detailed understanding of an underlying biological phenomenon. Thus pattern recognition from nucleic acid sequences is an important affair for protein function prediction. As proteins from the same family exhibit similar characteristics, homology based approaches predict protein functions via protein classification. But conventional classification approaches mostly rely on the global features by considering only strong protein similarity matches. This leads to significant loss of prediction accuracy. Here we construct the Protein-Protein Similarity (PPS) network, which captures the subtle properties of protein families. The proposed method considers the local as well as the global features, by examining the interactions among 'weakly interacting proteins' in the PPS network and by using hierarchical graph analysis via the graph pyramid. Different underlying properties of the protein families are uncovered by operating the proposed graph based features at various pyramid levels. Experimental results on benchmark data sets show that the proposed hierarchical voting algorithm using graph pyramid helps to improve computational efficiency as well the protein classification accuracy. Quantitatively, among 14,086 test sequences, on an average the proposed method misclassified only 21.1 sequences whereas baseline BLAST score based global feature matching method misclassified 362.9 sequences. With each correctly classified test sequence, the fast incremental learning ability of the proposed method further enhances the training model. Thus it has achieved more than 96% protein classification accuracy using only 20% per class training data.

Electricity from Coal Combustion: Improving the hydrophobicity of oxidized coals

NASA Astrophysics Data System (ADS)

Seehra, Mohindar; Singh, Vivek

2011-03-01

To reduce pollution and improve efficiency, undesirable mineral impurities in coals are usually removed in coal preparation plants prior to combustion first by crushing and grinding coals followed by gravity separation using surfactant aided water flotation. However certain coals in the US are not amendable to this process because of their poor flotation characteristics resulting in a major loss of an energy resource. This problem has been linked to surface oxidation of mined coals which make these coals hydrophilic. In this project, we are investigating the surface and water flotation properties of the eight Argonne Premium (AP) coals using x-ray diffraction, IR spectroscopy and zeta potential measurements. The role of the surface functional groups, (phenolic -OH and carboxylic -COOH), produced as a result of chemisorptions of O2 on coals in determining their flotation behavior is being explored. The isoelectric point (IEP) in zeta potential measurements of good vs. poor floaters is being examined in order to improved the hydrophobicity of poor floating coals (e.g. Illinois #6). Results from XRD and IR will be presented along with recent findings from zeta potential measurements, and use of additives to improve hydrophobicity. Supported by USDOE/CAST, Contract #DE-FC26-05NT42457.
Reflecting on Graphs: Attributes of Graph Choice and Construction Practices in Biology.

PubMed

Angra, Aakanksha; Gardner, Stephanie M

2017-01-01

Undergraduate biology education reform aims to engage students in scientific practices such as experimental design, experimentation, and data analysis and communication. Graphs are ubiquitous in the biological sciences, and creating effective graphical representations involves quantitative and disciplinary concepts and skills. Past studies document student difficulties with graphing within the contexts of classroom or national assessments without evaluating student reasoning. Operating under the metarepresentational competence framework, we conducted think-aloud interviews to reveal differences in reasoning and graph quality between undergraduate biology students, graduate students, and professors in a pen-and-paper graphing task. All professors planned and thought about data before graph construction. When reflecting on their graphs, professors and graduate students focused on the function of graphs and experimental design, while most undergraduate students relied on intuition and data provided in the task. Most undergraduate students meticulously plotted all data with scaled axes, while professors and some graduate students transformed the data, aligned the graph with the research question, and reflected on statistics and sample size. Differences in reasoning and approaches taken in graph choice and construction corroborate and extend previous findings and provide rich targets for undergraduate and graduate instruction. © 2017 A. Angra and S. M. Gardner. CBE—Life Sciences Education © 2017 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).
Atmospheric absorption of sound - Update

NASA Technical Reports Server (NTRS)

Bass, H. E.; Sutherland, L. C.; Zuckerwar, A. J.

1990-01-01

Best current expressions for the vibrational relaxation times of oxygen and nitrogen in the atmosphere are used to compute total absorption. The resulting graphs of total absorption as a function of frequency for different humidities should be used in lieu of the graph published earlier by Evans et al (1972).
Protein domain organisation: adding order.

PubMed

Kummerfeld, Sarah K; Teichmann, Sarah A

2009-01-29

Domains are the building blocks of proteins. During evolution, they have been duplicated, fused and recombined, to produce proteins with novel structures and functions. Structural and genome-scale studies have shown that pairs or groups of domains observed together in a protein are almost always found in only one N to C terminal order and are the result of a single recombination event that has been propagated by duplication of the multi-domain unit. Previous studies of domain organisation have used graph theory to represent the co-occurrence of domains within proteins. We build on this approach by adding directionality to the graphs and connecting nodes based on their relative order in the protein. Most of the time, the linear order of domains is conserved. However, using the directed graph representation we have identified non-linear features of domain organization that are over-represented in genomes. Recognising these patterns and unravelling how they have arisen may allow us to understand the functional relationships between domains and understand how the protein repertoire has evolved. We identify groups of domains that are not linearly conserved, but instead have been shuffled during evolution so that they occur in multiple different orders. We consider 192 genomes across all three kingdoms of life and use domain and protein annotation to understand their functional significance. To identify these features and assess their statistical significance, we represent the linear order of domains in proteins as a directed graph and apply graph theoretical methods. We describe two higher-order patterns of domain organisation: clusters and bi-directionally associated domain pairs and explore their functional importance and phylogenetic conservation. Taking into account the order of domains, we have derived a novel picture of global protein organization. We found that all genomes have a higher than expected degree of clustering and more domain pairs in forward and reverse orientation in different proteins relative to random graphs with identical degree distributions. While these features were statistically over-represented, they are still fairly rare. Looking in detail at the proteins involved, we found strong functional relationships within each cluster. In addition, the domains tended to be involved in protein-protein interaction and are able to function as independent structural units. A particularly striking example was the human Jak-STAT signalling pathway which makes use of a set of domains in a range of orders and orientations to provide nuanced signaling functionality. This illustrated the importance of functional and structural constraints (or lack thereof) on domain organisation.
Graph Laplacian Regularization for Image Denoising: Analysis in the Continuous Domain.

PubMed

Pang, Jiahao; Cheung, Gene

2017-04-01

Inverse imaging problems are inherently underdetermined, and hence, it is important to employ appropriate image priors for regularization. One recent popular prior-the graph Laplacian regularizer-assumes that the target pixel patch is smooth with respect to an appropriately chosen graph. However, the mechanisms and implications of imposing the graph Laplacian regularizer on the original inverse problem are not well understood. To address this problem, in this paper, we interpret neighborhood graphs of pixel patches as discrete counterparts of Riemannian manifolds and perform analysis in the continuous domain, providing insights into several fundamental aspects of graph Laplacian regularization for image denoising. Specifically, we first show the convergence of the graph Laplacian regularizer to a continuous-domain functional, integrating a norm measured in a locally adaptive metric space. Focusing on image denoising, we derive an optimal metric space assuming non-local self-similarity of pixel patches, leading to an optimal graph Laplacian regularizer for denoising in the discrete domain. We then interpret graph Laplacian regularization as an anisotropic diffusion scheme to explain its behavior during iterations, e.g., its tendency to promote piecewise smooth signals under certain settings. To verify our analysis, an iterative image denoising algorithm is developed. Experimental results show that our algorithm performs competitively with state-of-the-art denoising methods, such as BM3D for natural images, and outperforms them significantly for piecewise smooth images.
A comparative study of theoretical graph models for characterizing structural networks of human brain.

PubMed

Li, Xiaojin; Hu, Xintao; Jin, Changfeng; Han, Junwei; Liu, Tianming; Guo, Lei; Hao, Wei; Li, Lingjiang

2013-01-01

Previous studies have investigated both structural and functional brain networks via graph-theoretical methods. However, there is an important issue that has not been adequately discussed before: what is the optimal theoretical graph model for describing the structural networks of human brain? In this paper, we perform a comparative study to address this problem. Firstly, large-scale cortical regions of interest (ROIs) are localized by recently developed and validated brain reference system named Dense Individualized Common Connectivity-based Cortical Landmarks (DICCCOL) to address the limitations in the identification of the brain network ROIs in previous studies. Then, we construct structural brain networks based on diffusion tensor imaging (DTI) data. Afterwards, the global and local graph properties of the constructed structural brain networks are measured using the state-of-the-art graph analysis algorithms and tools and are further compared with seven popular theoretical graph models. In addition, we compare the topological properties between two graph models, namely, stickiness-index-based model (STICKY) and scale-free gene duplication model (SF-GD), that have higher similarity with the real structural brain networks in terms of global and local graph properties. Our experimental results suggest that among the seven theoretical graph models compared in this study, STICKY and SF-GD models have better performances in characterizing the structural human brain network.
Protein adsorption on dopamine-melanin films: role of electrostatic interactions inferred from zeta-potential measurements versus chemisorption.

PubMed

Bernsmann, Falk; Frisch, Benoît; Ringwald, Christian; Ball, Vincent

2010-04-01

We recently showed the possibility to build dopamine-melanin films of controlled thickness by successive immersions of a substrate in alkaline solutions of dopamine [F. Bernsmann, A. Ponche, C. Ringwald, J. Hemmerlé, J. Raya, B. Bechinger, J.-C. Voegel, P. Schaaf, V. Ball, J. Phys. Chem. C 113 (2009) 8234-8242]. In this work the structure and properties of such films are further explored. The zeta-potential of dopamine-melanin films is measured as a function of the total immersion time to build the film. It appears that the film bears a constant zeta-potential of (-39+/-3) mV after 12 immersion steps. These data are used to calculate the surface density of charged groups of the dopamine-melanin films at pH 8.5 that are mostly catechol or quinone imine chemical groups. Furthermore the zeta-potential is used to explain the adsorption of three model proteins (lysozyme, myoglobin, alpha-lactalbumin), which is monitored by quartz crystal microbalance. We come to the conclusion that protein adsorption on dopamine-melanin is not only determined by possible covalent binding between amino groups of the proteins and catechol groups of dopamine-melanin but that electrostatic interactions contribute to protein binding. Part of the adsorbed proteins can be desorbed by sodium dodecylsulfate solutions at the critical micellar concentration. The fraction of weakly bound proteins decreases with their isoelectric point. Additionally the number of available sites for covalent binding of amino groups on melanin grains is quantified. Copyright 2009 Elsevier Inc. All rights reserved.
Expanding our understanding of students' use of graphs for learning physics

NASA Astrophysics Data System (ADS)

Laverty, James T.

It is generally agreed that the ability to visualize functional dependencies or physical relationships as graphs is an important step in modeling and learning. However, several studies in Physics Education Research (PER) have shown that many students in fact do not master this form of representation and even have misconceptions about the meaning of graphs that impede learning physics concepts. Working with graphs in classroom settings has been shown to improve student abilities with graphs, particularly when the students can interact with them. We introduce a novel problem type in an online homework system, which requires students to construct the graphs themselves in free form, and requires no hand-grading by instructors. A study of pre/post-test data using the Test of Understanding Graphs in Kinematics (TUG-K) over several semesters indicates that students learn significantly more from these graph construction problems than from the usual graph interpretation problems, and that graph interpretation alone may not have any significant effect. The interpretation of graphs, as well as the representation translation between textual, mathematical, and graphical representations of physics scenarios, are frequently listed among the higher order thinking skills we wish to convey in an undergraduate course. But to what degree do we succeed? Do students indeed employ higher order thinking skills when working through graphing exercises? We investigate students working through a variety of graph problems, and, using a think-aloud protocol, aim to reconstruct the cognitive processes that the students go through. We find that to a certain degree, these problems become commoditized and do not trigger the desired higher order thinking processes; simply translating ``textbook-like'' problems into the graphical realm will not achieve any additional educational goals. Whether the students have to interpret or construct a graph makes very little difference in the methods used by the students. We will also look at the results of using graph problems in an online learning environment. We will show evidence that construction problems lead to a higher degree of difficulty and degree of discrimination than other graph problems and discuss the influence the course has on these variables.
Metacoder: An R package for visualization and manipulation of community taxonomic diversity data.

PubMed

Foster, Zachary S L; Sharpton, Thomas J; Grünwald, Niklaus J

2017-02-01

Community-level data, the type generated by an increasing number of metabarcoding studies, is often graphed as stacked bar charts or pie graphs that use color to represent taxa. These graph types do not convey the hierarchical structure of taxonomic classifications and are limited by the use of color for categories. As an alternative, we developed metacoder, an R package for easily parsing, manipulating, and graphing publication-ready plots of hierarchical data. Metacoder includes a dynamic and flexible function that can parse most text-based formats that contain taxonomic classifications, taxon names, taxon identifiers, or sequence identifiers. Metacoder can then subset, sample, and order this parsed data using a set of intuitive functions that take into account the hierarchical nature of the data. Finally, an extremely flexible plotting function enables quantitative representation of up to 4 arbitrary statistics simultaneously in a tree format by mapping statistics to the color and size of tree nodes and edges. Metacoder also allows exploration of barcode primer bias by integrating functions to run digital PCR. Although it has been designed for data from metabarcoding research, metacoder can easily be applied to any data that has a hierarchical component such as gene ontology or geographic location data. Our package complements currently available tools for community analysis and is provided open source with an extensive online user manual.
GAT: a graph-theoretical analysis toolbox for analyzing between-group differences in large-scale structural and functional brain networks.

PubMed

Hosseini, S M Hadi; Hoeft, Fumiko; Kesler, Shelli R

2012-01-01

In recent years, graph theoretical analyses of neuroimaging data have increased our understanding of the organization of large-scale structural and functional brain networks. However, tools for pipeline application of graph theory for analyzing topology of brain networks is still lacking. In this report, we describe the development of a graph-analysis toolbox (GAT) that facilitates analysis and comparison of structural and functional network brain networks. GAT provides a graphical user interface (GUI) that facilitates construction and analysis of brain networks, comparison of regional and global topological properties between networks, analysis of network hub and modules, and analysis of resilience of the networks to random failure and targeted attacks. Area under a curve (AUC) and functional data analyses (FDA), in conjunction with permutation testing, is employed for testing the differences in network topologies; analyses that are less sensitive to the thresholding process. We demonstrated the capabilities of GAT by investigating the differences in the organization of regional gray-matter correlation networks in survivors of acute lymphoblastic leukemia (ALL) and healthy matched Controls (CON). The results revealed an alteration in small-world characteristics of the brain networks in the ALL survivors; an observation that confirm our hypothesis suggesting widespread neurobiological injury in ALL survivors. Along with demonstration of the capabilities of the GAT, this is the first report of altered large-scale structural brain networks in ALL survivors.
Network discovery with DCM

PubMed Central

Friston, Karl J.; Li, Baojuan; Daunizeau, Jean; Stephan, Klaas E.

2011-01-01

This paper is about inferring or discovering the functional architecture of distributed systems using Dynamic Causal Modelling (DCM). We describe a scheme that recovers the (dynamic) Bayesian dependency graph (connections in a network) using observed network activity. This network discovery uses Bayesian model selection to identify the sparsity structure (absence of edges or connections) in a graph that best explains observed time-series. The implicit adjacency matrix specifies the form of the network (e.g., cyclic or acyclic) and its graph-theoretical attributes (e.g., degree distribution). The scheme is illustrated using functional magnetic resonance imaging (fMRI) time series to discover functional brain networks. Crucially, it can be applied to experimentally evoked responses (activation studies) or endogenous activity in task-free (resting state) fMRI studies. Unlike conventional approaches to network discovery, DCM permits the analysis of directed and cyclic graphs. Furthermore, it eschews (implausible) Markovian assumptions about the serial independence of random fluctuations. The scheme furnishes a network description of distributed activity in the brain that is optimal in the sense of having the greatest conditional probability, relative to other networks. The networks are characterised in terms of their connectivity or adjacency matrices and conditional distributions over the directed (and reciprocal) effective connectivity between connected nodes or regions. We envisage that this approach will provide a useful complement to current analyses of functional connectivity for both activation and resting-state studies. PMID:21182971
Metacoder: An R package for visualization and manipulation of community taxonomic diversity data

PubMed Central

Foster, Zachary S. L.; Sharpton, Thomas J.

2017-01-01

Community-level data, the type generated by an increasing number of metabarcoding studies, is often graphed as stacked bar charts or pie graphs that use color to represent taxa. These graph types do not convey the hierarchical structure of taxonomic classifications and are limited by the use of color for categories. As an alternative, we developed metacoder, an R package for easily parsing, manipulating, and graphing publication-ready plots of hierarchical data. Metacoder includes a dynamic and flexible function that can parse most text-based formats that contain taxonomic classifications, taxon names, taxon identifiers, or sequence identifiers. Metacoder can then subset, sample, and order this parsed data using a set of intuitive functions that take into account the hierarchical nature of the data. Finally, an extremely flexible plotting function enables quantitative representation of up to 4 arbitrary statistics simultaneously in a tree format by mapping statistics to the color and size of tree nodes and edges. Metacoder also allows exploration of barcode primer bias by integrating functions to run digital PCR. Although it has been designed for data from metabarcoding research, metacoder can easily be applied to any data that has a hierarchical component such as gene ontology or geographic location data. Our package complements currently available tools for community analysis and is provided open source with an extensive online user manual. PMID:28222096
University Students' Grasp of Inflection Points

ERIC Educational Resources Information Center

Tsamir, Pessia; Ovodenko, Regina

2013-01-01

This paper describes university students' grasp of inflection points. The participants were asked what inflection points are, to mark inflection points on graphs, to judge the validity of related statements, and to find inflection points by investigating (1) a function, (2) the derivative, and (3) the graph of the derivative. We found four…
Dynamical graph theory networks techniques for the analysis of sparse connectivity networks in dementia

NASA Astrophysics Data System (ADS)

Tahmassebi, Amirhessam; Pinker-Domenig, Katja; Wengert, Georg; Lobbes, Marc; Stadlbauer, Andreas; Romero, Francisco J.; Morales, Diego P.; Castillo, Encarnacion; Garcia, Antonio; Botella, Guillermo; Meyer-Bäse, Anke

2017-05-01

Graph network models in dementia have become an important computational technique in neuroscience to study fundamental organizational principles of brain structure and function of neurodegenerative diseases such as dementia. The graph connectivity is reflected in the connectome, the complete set of structural and functional connections of the graph network, which is mostly based on simple Pearson correlation links. In contrast to simple Pearson correlation networks, the partial correlations (PC) only identify direct correlations while indirect associations are eliminated. In addition to this, the state-of-the-art techniques in brain research are based on static graph theory, which is unable to capture the dynamic behavior of the brain connectivity, as it alters with disease evolution. We propose a new research avenue in neuroimaging connectomics based on combining dynamic graph network theory and modeling strategies at different time scales. We present the theoretical framework for area aggregation and time-scale modeling in brain networks as they pertain to disease evolution in dementia. This novel paradigm is extremely powerful, since we can derive both static parameters pertaining to node and area parameters, as well as dynamic parameters, such as system's eigenvalues. By implementing and analyzing dynamically both disease driven PC-networks and regular concentration networks, we reveal differences in the structure of these network that play an important role in the temporal evolution of this disease. The described research is key to advance biomedical research on novel disease prediction trajectories and dementia therapies.
Zeta potential control for electrophoresis cells

NASA Technical Reports Server (NTRS)

Fogal, G. L.

1973-01-01

Zeta potential arises from fact that ions tend to be adsorbed on surface of cell walls. This potential interfaces with electric field sensed by migrating particles and degrades resolution of separation. By regulating sign and magnitude of applied potential induced charge can be used to increase or decrease effective wall zeta potential.
Identifying patients with Alzheimer's disease using resting-state fMRI and graph theory.

PubMed

Khazaee, Ali; Ebrahimzadeh, Ata; Babajani-Feremi, Abbas

2015-11-01

Study of brain network on the basis of resting-state functional magnetic resonance imaging (fMRI) has provided promising results to investigate changes in connectivity among different brain regions because of diseases. Graph theory can efficiently characterize different aspects of the brain network by calculating measures of integration and segregation. In this study, we combine graph theoretical approaches with advanced machine learning methods to study functional brain network alteration in patients with Alzheimer's disease (AD). Support vector machine (SVM) was used to explore the ability of graph measures in diagnosis of AD. We applied our method on the resting-state fMRI data of twenty patients with AD and twenty age and gender matched healthy subjects. The data were preprocessed and each subject's graph was constructed by parcellation of the whole brain into 90 distinct regions using the automated anatomical labeling (AAL) atlas. The graph measures were then calculated and used as the discriminating features. Extracted network-based features were fed to different feature selection algorithms to choose most significant features. In addition to the machine learning approach, statistical analysis was performed on connectivity matrices to find altered connectivity patterns in patients with AD. Using the selected features, we were able to accurately classify patients with AD from healthy subjects with accuracy of 100%. Results of this study show that pattern recognition and graph of brain network, on the basis of the resting state fMRI data, can efficiently assist in the diagnosis of AD. Classification based on the resting-state fMRI can be used as a non-invasive and automatic tool to diagnosis of Alzheimer's disease. Copyright © 2015 International Federation of Clinical Neurophysiology. All rights reserved.
NeAT: a toolbox for the analysis of biological networks, clusters, classes and pathways.

PubMed

Brohée, Sylvain; Faust, Karoline; Lima-Mendez, Gipsi; Sand, Olivier; Janky, Rekin's; Vanderstocken, Gilles; Deville, Yves; van Helden, Jacques

2008-07-01

The network analysis tools (NeAT) (http://rsat.ulb.ac.be/neat/) provide a user-friendly web access to a collection of modular tools for the analysis of networks (graphs) and clusters (e.g. microarray clusters, functional classes, etc.). A first set of tools supports basic operations on graphs (comparison between two graphs, neighborhood of a set of input nodes, path finding and graph randomization). Another set of programs makes the connection between networks and clusters (graph-based clustering, cliques discovery and mapping of clusters onto a network). The toolbox also includes programs for detecting significant intersections between clusters/classes (e.g. clusters of co-expression versus functional classes of genes). NeAT are designed to cope with large datasets and provide a flexible toolbox for analyzing biological networks stored in various databases (protein interactions, regulation and metabolism) or obtained from high-throughput experiments (two-hybrid, mass-spectrometry and microarrays). The web interface interconnects the programs in predefined analysis flows, enabling to address a series of questions about networks of interest. Each tool can also be used separately by entering custom data for a specific analysis. NeAT can also be used as web services (SOAP/WSDL interface), in order to design programmatic workflows and integrate them with other available resources.
Optimal graph search segmentation using arc-weighted graph for simultaneous surface detection of bladder and prostate.

PubMed

Song, Qi; Wu, Xiaodong; Liu, Yunlong; Smith, Mark; Buatti, John; Sonka, Milan

2009-01-01

We present a novel method for globally optimal surface segmentation of multiple mutually interacting objects, incorporating both edge and shape knowledge in a 3-D graph-theoretic approach. Hard surface interacting constraints are enforced in the interacting regions, preserving the geometric relationship of those partially interacting surfaces. The soft smoothness a priori shape compliance is introduced into the energy functional to provide shape guidance. The globally optimal surfaces can be simultaneously achieved by solving a maximum flow problem based on an arc-weighted graph representation. Representing the segmentation problem in an arc-weighted graph, one can incorporate a wider spectrum of constraints into the formulation, thus increasing segmentation accuracy and robustness in volumetric image data. To the best of our knowledge, our method is the first attempt to introduce the arc-weighted graph representation into the graph-searching approach for simultaneous segmentation of multiple partially interacting objects, which admits a globally optimal solution in a low-order polynomial time. Our new approach was applied to the simultaneous surface detection of bladder and prostate. The result was quite encouraging in spite of the low saliency of the bladder and prostate in CT images.
Weighted graph cuts without eigenvectors a multilevel approach.

PubMed

Dhillon, Inderjit S; Guan, Yuqiang; Kulis, Brian

2007-11-01

A variety of clustering algorithms have recently been proposed to handle data that is not linearly separable; spectral clustering and kernel k-means are two of the main methods. In this paper, we discuss an equivalence between the objective functions used in these seemingly different methods--in particular, a general weighted kernel k-means objective is mathematically equivalent to a weighted graph clustering objective. We exploit this equivalence to develop a fast, high-quality multilevel algorithm that directly optimizes various weighted graph clustering objectives, such as the popular ratio cut, normalized cut, and ratio association criteria. This eliminates the need for any eigenvector computation for graph clustering problems, which can be prohibitive for very large graphs. Previous multilevel graph partitioning methods, such as Metis, have suffered from the restriction of equal-sized clusters; our multilevel algorithm removes this restriction by using kernel k-means to optimize weighted graph cuts. Experimental results show that our multilevel algorithm outperforms a state-of-the-art spectral clustering algorithm in terms of speed, memory usage, and quality. We demonstrate that our algorithm is applicable to large-scale clustering tasks such as image segmentation, social network analysis and gene network analysis.
GraphMeta: Managing HPC Rich Metadata in Graphs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dai, Dong; Chen, Yong; Carns, Philip

High-performance computing (HPC) systems face increasingly critical metadata management challenges, especially in the approaching exascale era. These challenges arise not only from exploding metadata volumes, but also from increasingly diverse metadata, which contains data provenance and arbitrary user-defined attributes in addition to traditional POSIX metadata. This ‘rich’ metadata is becoming critical to supporting advanced data management functionality such as data auditing and validation. In our prior work, we identified a graph-based model as a promising solution to uniformly manage HPC rich metadata due to its flexibility and generality. However, at the same time, graph-based HPC rich metadata anagement also introducesmore » significant challenges to the underlying infrastructure. In this study, we first identify the challenges on the underlying infrastructure to support scalable, high-performance rich metadata management. Based on that, we introduce GraphMeta, a graphbased engine designed for this use case. It achieves performance scalability by introducing a new graph partitioning algorithm and a write-optimal storage engine. We evaluate GraphMeta under both synthetic and real HPC metadata workloads, compare it with other approaches, and demonstrate its advantages in terms of efficiency and usability for rich metadata management in HPC systems.« less

MadDM: Computation of dark matter relic abundance

NASA Astrophysics Data System (ADS)

Backović, Mihailo; Kong, Kyoungchul; McCaskey, Mathew

2017-12-01

MadDM computes dark matter relic abundance and dark matter nucleus scattering rates in a generic model. The code is based on the existing MadGraph 5 architecture and as such is easily integrable into any MadGraph collider study. A simple Python interface offers a level of user-friendliness characteristic of MadGraph 5 without sacrificing functionality. MadDM is able to calculate the dark matter relic abundance in models which include a multi-component dark sector, resonance annihilation channels and co-annihilations. The direct detection module of MadDM calculates spin independent / spin dependent dark matter-nucleon cross sections and differential recoil rates as a function of recoil energy, angle and time. The code provides a simplified simulation of detector effects for a wide range of target materials and volumes.
The role of ZAP70 kinase in acute lymphoblastic leukemia infiltration into the central nervous system.

PubMed

Alsadeq, Ameera; Fedders, Henning; Vokuhl, Christian; Belau, Nele M; Zimmermann, Martin; Wirbelauer, Tim; Spielberg, Steffi; Vossen-Gajcy, Michaela; Cario, Gunnar; Schrappe, Martin; Schewe, Denis M

2017-02-01

Central nervous system infiltration and relapse are poorly understood in childhood acute lymphoblastic leukemia. We examined the role of zeta-chain-associated protein kinase 70 in preclinical models of central nervous system leukemia and performed correlative studies in patients. Zeta-chain-associated protein kinase 70 expression in acute lymphoblastic leukemia cells was modulated using short hairpin ribonucleic acid-mediated knockdown or ectopic expression. We show that zeta-chain-associated protein kinase 70 regulates CCR7/CXCR4 via activation of extracellular signal-regulated kinases. High expression of zeta-chain-associated protein kinase 70 in acute lymphoblastic leukemia cells resulted in a higher proportion of central nervous system leukemia in xenografts as compared to zeta-chain-associated protein kinase 70 low expressing counterparts. High zeta-chain-associated protein kinase 70 also enhanced the migration potential towards CCL19/CXCL12 gradients in vitro CCR7 blockade almost abrogated homing of acute lymphoblastic leukemia cells to the central nervous system in xenografts. In 130 B-cell precursor acute lymphoblastic leukemia and 117 T-cell acute lymphoblastic leukemia patients, zeta-chain-associated protein kinase 70 and CCR7/CXCR4 expression levels were significantly correlated. Zeta-chain-associated protein kinase 70 expression correlated with central nervous system disease in B-cell precursor acute lymphoblastic leukemia, and CCR7/CXCR4 correlated with central nervous system involvement in T-cell acute lymphoblastic leukemia patients. In multivariate analysis, zeta-chain-associated protein kinase 70 expression levels in the upper third and fourth quartiles were associated with central nervous system involvement in B-cell precursor acute lymphoblastic leukemia (odds ratio=7.48, 95% confidence interval, 2.06-27.17; odds ratio=6.86, 95% confidence interval, 1.86-25.26, respectively). CCR7 expression in the upper fourth quartile correlated with central nervous system positivity in T-cell acute lymphoblastic leukemia (odds ratio=11.00, 95% confidence interval, 2.00-60.62). We propose zeta-chain-associated protein kinase 70, CCR7 and CXCR4 as markers of central nervous system infiltration in acute lymphoblastic leukemia warranting prospective investigation. Copyright© Ferrata Storti Foundation.
Basis set and electron correlation effects on the polarizability and second hyperpolarizability of model open-shell π-conjugated systems

NASA Astrophysics Data System (ADS)

Champagne, Benoı̂t; Botek, Edith; Nakano, Masayoshi; Nitta, Tomoshige; Yamaguchi, Kizashi

2005-03-01

The basis set and electron correlation effects on the static polarizability (α) and second hyperpolarizability (γ) are investigated ab initio for two model open-shell π-conjugated systems, the C5H7 radical and the C6H8 radical cation in their doublet state. Basis set investigations evidence that the linear and nonlinear responses of the radical cation necessitate the use of a less extended basis set than its neutral analog. Indeed, double-zeta-type basis sets supplemented by a set of d polarization functions but no diffuse functions already provide accurate (hyper)polarizabilities for C6H8 whereas diffuse functions are compulsory for C5H7, in particular, p diffuse functions. In addition to the 6-31G*+pd basis set, basis sets resulting from removing not necessary diffuse functions from the augmented correlation consistent polarized valence double zeta basis set have been shown to provide (hyper)polarizability values of similar quality as more extended basis sets such as augmented correlation consistent polarized valence triple zeta and doubly augmented correlation consistent polarized valence double zeta. Using the selected atomic basis sets, the (hyper)polarizabilities of these two model compounds are calculated at different levels of approximation in order to assess the impact of including electron correlation. As a function of the method of calculation antiparallel and parallel variations have been demonstrated for α and γ of the two model compounds, respectively. For the polarizability, the unrestricted Hartree-Fock and unrestricted second-order Møller-Plesset methods bracket the reference value obtained at the unrestricted coupled cluster singles and doubles with a perturbative inclusion of the triples level whereas the projected unrestricted second-order Møller-Plesset results are in much closer agreement with the unrestricted coupled cluster singles and doubles with a perturbative inclusion of the triples values than the projected unrestricted Hartree-Fock results. Moreover, the differences between the restricted open-shell Hartree-Fock and restricted open-shell second-order Møller-Plesset methods are small. In what concerns the second hyperpolarizability, the unrestricted Hartree-Fock and unrestricted second-order Møller-Plesset values remain of similar quality while using spin-projected schemes fails for the charged system but performs nicely for the neutral one. The restricted open-shell schemes, and especially the restricted open-shell second-order Møller-Plesset method, provide for both compounds γ values close to the results obtained at the unrestricted coupled cluster level including singles and doubles with a perturbative inclusion of the triples. Thus, to obtain well-converged α and γ values at low-order electron correlation levels, the removal of spin contamination is a necessary but not a sufficient condition. Density-functional theory calculations of α and γ have also been carried out using several exchange-correlation functionals. Those employing hybrid exchange-correlation functionals have been shown to reproduce fairly well the reference coupled cluster polarizability and second hyperpolarizability values. In addition, inclusion of Hartree-Fock exchange is of major importance for determining accurate polarizability whereas for the second hyperpolarizability the gradient corrections are large.
Nonunitary and unitary approach to Eigenvalue problem of Boson operators and squeezed coherent states

NASA Technical Reports Server (NTRS)

Wunsche, A.

1993-01-01

The eigenvalue problem of the operator a + zeta(boson creation operator) is solved for arbitrarily complex zeta by applying a nonunitary operator to the vacuum state. This nonunitary approach is compared with the unitary approach leading for the absolute value of zeta less than 1 to squeezed coherent states.
An induced current method for measuring zeta potential of electrolyte solution-air interface.

PubMed

Song, Yongxin; Zhao, Kai; Wang, Junsheng; Wu, Xudong; Pan, Xinxiang; Sun, Yeqing; Li, Dongqing

2014-02-15

This paper reports a novel and very simple method for measuring the zeta potential of electrolyte solution-air interface. When a measuring electrode contacts the electrolyte solution-air interface, an electrical current will be generated due to the potential difference between the electrode-air surface and the electrolyte solution-air interface. The amplitude of the measured electric signal is linearly proportional to this potential difference; and depends only on the zeta potential at the electrolyte solution-air interface, regardless of the types and concentrations of the electrolyte. A correlation between the zeta potential and the measured voltage signal is obtained based on the experimental data. Using this equation, the zeta potential of any electrolyte solution-air interface can be evaluated quickly and easily by inserting an electrode through the electrolyte solution-air interface and measuring the electrical signal amplitude. This method was verified by comparing the obtained results of NaCl, MgCl2 and CaCl2 solutions of different pH values and concentrations with the zeta potential data reported in the published journal papers. Copyright © 2013 Elsevier Inc. All rights reserved.
Water quality monitoring: A comparative case study of municipal and Curtin Sarawak's lake samples

NASA Astrophysics Data System (ADS)

Anand Kumar, A.; Jaison, J.; Prabakaran, K.; Nagarajan, R.; Chan, Y. S.

2016-03-01

In this study, particle size distribution and zeta potential of the suspended particles in municipal water and lake surface water of Curtin Sarawak's lake were compared and the samples were analysed using dynamic light scattering method. High concentration of suspended particles affects the water quality as well as suppresses the aquatic photosynthetic systems. A new approach has been carried out in the current work to determine the particle size distribution and zeta potential of the suspended particles present in the water samples. The results for the lake samples showed that the particle size ranges from 180nm to 1345nm and the zeta potential values ranges from -8.58 mV to -26.1 mV. High zeta potential value was observed in the surface water samples of Curtin Sarawak's lake compared to the municipal water. The zeta potential values represent that the suspended particles are stable and chances of agglomeration is lower in lake water samples. Moreover, the effects of physico-chemical parameters on zeta potential of the water samples were also discussed.
Matched signal detection on graphs: Theory and application to brain imaging data classification.

PubMed

Hu, Chenhui; Sepulcre, Jorge; Johnson, Keith A; Fakhri, Georges E; Lu, Yue M; Li, Quanzheng

2016-01-15

Motivated by recent progress in signal processing on graphs, we have developed a matched signal detection (MSD) theory for signals with intrinsic structures described by weighted graphs. First, we regard graph Laplacian eigenvalues as frequencies of graph-signals and assume that the signal is in a subspace spanned by the first few graph Laplacian eigenvectors associated with lower eigenvalues. The conventional matched subspace detector can be applied to this case. Furthermore, we study signals that may not merely live in a subspace. Concretely, we consider signals with bounded variation on graphs and more general signals that are randomly drawn from a prior distribution. For bounded variation signals, the test is a weighted energy detector. For the random signals, the test statistic is the difference of signal variations on associated graphs, if a degenerate Gaussian distribution specified by the graph Laplacian is adopted. We evaluate the effectiveness of the MSD on graphs both with simulated and real data sets. Specifically, we apply MSD to the brain imaging data classification problem of Alzheimer's disease (AD) based on two independent data sets: 1) positron emission tomography data with Pittsburgh compound-B tracer of 30 AD and 40 normal control (NC) subjects, and 2) resting-state functional magnetic resonance imaging (R-fMRI) data of 30 early mild cognitive impairment and 20 NC subjects. Our results demonstrate that the MSD approach is able to outperform the traditional methods and help detect AD at an early stage, probably due to the success of exploiting the manifold structure of the data. Copyright © 2015. Published by Elsevier Inc.
Dynamical Graph Theory Networks Methods for the Analysis of Sparse Functional Connectivity Networks and for Determining Pinning Observability in Brain Networks

PubMed Central

Meyer-Bäse, Anke; Roberts, Rodney G.; Illan, Ignacio A.; Meyer-Bäse, Uwe; Lobbes, Marc; Stadlbauer, Andreas; Pinker-Domenig, Katja

2017-01-01

Neuroimaging in combination with graph theory has been successful in analyzing the functional connectome. However almost all analysis are performed based on static graph theory. The derived quantitative graph measures can only describe a snap shot of the disease over time. Neurodegenerative disease evolution is poorly understood and treatment strategies are consequently only of limited efficiency. Fusing modern dynamic graph network theory techniques and modeling strategies at different time scales with pinning observability of complex brain networks will lay the foundation for a transformational paradigm in neurodegnerative diseases research regarding disease evolution at the patient level, treatment response evaluation and revealing some central mechanism in a network that drives alterations in these diseases. We model and analyze brain networks as two-time scale sparse dynamic graph networks with hubs (clusters) representing the fast sub-system and the interconnections between hubs the slow sub-system. Alterations in brain function as seen in dementia can be dynamically modeled by determining the clusters in which disturbance inputs have entered and the impact they have on the large-scale dementia dynamic system. Observing a small fraction of specific nodes in dementia networks such that the others can be recovered is accomplished by the novel concept of pinning observability. In addition, how to control this complex network seems to be crucial in understanding the progressive abnormal neural circuits in many neurodegenerative diseases. Detecting the controlling regions in the networks, which serve as key nodes to control the aberrant dynamics of the networks to a desired state and thus influence the progressive abnormal behavior, will have a huge impact in understanding and developing therapeutic solutions and also will provide useful information about the trajectory of the disease. In this paper, we present the theoretical framework and derive the necessary conditions for (1) area aggregation and time-scale modeling in brain networks and for (2) pinning observability of nodes in dynamic graph networks. Simulation examples are given to illustrate the theoretical concepts. PMID:29051730
Dynamical Graph Theory Networks Methods for the Analysis of Sparse Functional Connectivity Networks and for Determining Pinning Observability in Brain Networks.

PubMed

Meyer-Bäse, Anke; Roberts, Rodney G; Illan, Ignacio A; Meyer-Bäse, Uwe; Lobbes, Marc; Stadlbauer, Andreas; Pinker-Domenig, Katja

2017-01-01

Neuroimaging in combination with graph theory has been successful in analyzing the functional connectome. However almost all analysis are performed based on static graph theory. The derived quantitative graph measures can only describe a snap shot of the disease over time. Neurodegenerative disease evolution is poorly understood and treatment strategies are consequently only of limited efficiency. Fusing modern dynamic graph network theory techniques and modeling strategies at different time scales with pinning observability of complex brain networks will lay the foundation for a transformational paradigm in neurodegnerative diseases research regarding disease evolution at the patient level, treatment response evaluation and revealing some central mechanism in a network that drives alterations in these diseases. We model and analyze brain networks as two-time scale sparse dynamic graph networks with hubs (clusters) representing the fast sub-system and the interconnections between hubs the slow sub-system. Alterations in brain function as seen in dementia can be dynamically modeled by determining the clusters in which disturbance inputs have entered and the impact they have on the large-scale dementia dynamic system. Observing a small fraction of specific nodes in dementia networks such that the others can be recovered is accomplished by the novel concept of pinning observability. In addition, how to control this complex network seems to be crucial in understanding the progressive abnormal neural circuits in many neurodegenerative diseases. Detecting the controlling regions in the networks, which serve as key nodes to control the aberrant dynamics of the networks to a desired state and thus influence the progressive abnormal behavior, will have a huge impact in understanding and developing therapeutic solutions and also will provide useful information about the trajectory of the disease. In this paper, we present the theoretical framework and derive the necessary conditions for (1) area aggregation and time-scale modeling in brain networks and for (2) pinning observability of nodes in dynamic graph networks. Simulation examples are given to illustrate the theoretical concepts.
A technology mapping based on graph of excitations and outputs for finite state machines

NASA Astrophysics Data System (ADS)

Kania, Dariusz; Kulisz, Józef

2017-11-01

A new, efficient technology mapping method of FSMs, dedicated for PAL-based PLDs is proposed. The essence of the method consists in searching for the minimal set of PAL-based logic blocks that cover a set of multiple-output implicants describing the transition and output functions of an FSM. The method is based on a new concept of graph: the Graph of Excitations and Outputs. The proposed algorithm was tested using the FSM benchmarks. The obtained results were compared with the classical technology mapping of FSM.
Multiple directed graph large-class multi-spectral processor

NASA Technical Reports Server (NTRS)

Casasent, David; Liu, Shiaw-Dong; Yoneyama, Hideyuki

1988-01-01

Numerical analysis techniques for the interpretation of high-resolution imaging-spectrometer data are described and demonstrated. The method proposed involves the use of (1) a hierarchical classifier with a tree structure generated automatically by a Fisher linear-discriminant-function algorithm and (2) a novel multiple-directed-graph scheme which reduces the local maxima and the number of perturbations required. Results for a 500-class test problem involving simulated imaging-spectrometer data are presented in tables and graphs; 100-percent-correct classification is achieved with an improvement factor of 5.
The neighbourhood polynomial of some families of dendrimers

NASA Astrophysics Data System (ADS)

Nazri Husin, Mohamad; Hasni, Roslan

2018-04-01

The neighbourhood polynomial N(G,x) is generating function for the number of faces of each cardinality in the neighbourhood complex of a graph and it is defined as (G,x)={\\sum }U\\in N(G){x}|U|, where N(G) is neighbourhood complex of a graph, whose vertices of the graph and faces are subsets of vertices that have a common neighbour. A dendrimers is an artificially manufactured or synthesized molecule built up from branched units called monomers. In this paper, we compute this polynomial for some families of dendrimer.
Pair correlation and twin primes revisited.

PubMed

Conrey, Brian; Keating, Jonathan P

2016-10-01

We establish a connection between the conjectural two-over-two ratios formula for the Riemann zeta-function and a conjecture concerning correlations of a certain arithmetic function. Specifically, we prove that the ratios conjecture and the arithmetic correlations conjecture imply the same result. This casts a new light on the underpinnings of the ratios conjecture, which previously had been motivated by analogy with formulae in random matrix theory and by a heuristic recipe.
Pair correlation and twin primes revisited

NASA Astrophysics Data System (ADS)

Conrey, Brian; Keating, Jonathan P.

2016-10-01

We establish a connection between the conjectural two-over-two ratios formula for the Riemann zeta-function and a conjecture concerning correlations of a certain arithmetic function. Specifically, we prove that the ratios conjecture and the arithmetic correlations conjecture imply the same result. This casts a new light on the underpinnings of the ratios conjecture, which previously had been motivated by analogy with formulae in random matrix theory and by a heuristic recipe.
Algebraic independence results for reciprocal sums of Fibonacci and Lucas numbers

NASA Astrophysics Data System (ADS)

Stein, Martin

2011-09-01

Let Fn and Ln denote the Fibonacci and Lucas numbers, respectively. D. Duverney, Ke. Nishioka, Ku. Nishioka and I. Shiokawa proved that the values of the Fibonacci zeta function ζF(2s) = Σn = 1∞Fn-2s are transcendental for any s∈N using Nesterenko's theorem on Ramanujan functions P(q), Q(q), and R(q). They obtained similar results for the Lucas zeta function ζL(2s) = Σn = 1∞Ln-2s and some related series. Later, C. Elsner, S. Shimomura and I. Shiokawa found conditions for the algebraic independence of these series. In my PhD thesis I generalized their approach and treated the following problem: We investigate all subsets of { ∑ n = 1∞1/Fn2s1, ∑ n = 1∞(-1)n+1/Fn2s2, ∑ n = 1∞1/Ln2s3, ∑ n = 1∞(-1)n+1/Ln2s4:s1,s2,s3,s4∈N} and decide on their algebraic independence over Q. Actually this is a special case of a more general theorem for reciprocal sums of binary recurrent sequences.
Thiol-reactive amphiphilic block copolymer for coating gold nanoparticles with neutral and functionable surfaces

PubMed Central

Chen, Hongwei; Zou, Hao; Paholak, Hayley J.; Ito, Masayuki; Qian, Wei; Che, Yong; Sun, Duxin

2014-01-01

Nanoparticles designed for biomedical applications are often coated with polymers containing reactive functional groups, such as –COOH and –NH2, to conjugate targeting ligands or drugs. However, introducing highly charged surfaces promotes binding of the nanoparticles to biomolecules in biological systems through ionic interactions, causing the nanoparticles to aggregate in biological environments and consequently undergo strong non-specific binding to off-target cells and tissues. Developing a unique polymer with neutral surfaces that can be further functionalized directly would be critical to develop suitable nanomaterials for nanomedicine. Here, we report a thiol-reactive amphiphilic block copolymer poly(ethylene oxide)-block-poly(pyridyldisulfide ethylmeth acrylate) (PEO-b-PPDSM) for coating gold nanoparticles (AuNPs). The resultant polymer-coated AuNPs have almost neutral surfaces with slightly negative zeta potentials from -10 to 0 mV over a wide pH range from 2 to 12. Although the zeta potential is close to zero we show that the PEO-b-PPDSM copolymer-coated AuNPs have both good stability in various physiological conditions and reduced non-specific adsorption of proteins/biomolecules. Because of the multiple pyridyldisulfide groups on the PPDSM block, these individually dispersed nanocomplexes with an overall hydrodynamic size around 43.8 nm can be directly functionalized via disulfide-thiol exchange chemistry. PMID:24729795
Feature Grouping and Selection Over an Undirected Graph.

PubMed

Yang, Sen; Yuan, Lei; Lai, Ying-Cheng; Shen, Xiaotong; Wonka, Peter; Ye, Jieping

2012-01-01

High-dimensional regression/classification continues to be an important and challenging problem, especially when features are highly correlated. Feature selection, combined with additional structure information on the features has been considered to be promising in promoting regression/classification performance. Graph-guided fused lasso (GFlasso) has recently been proposed to facilitate feature selection and graph structure exploitation, when features exhibit certain graph structures. However, the formulation in GFlasso relies on pairwise sample correlations to perform feature grouping, which could introduce additional estimation bias. In this paper, we propose three new feature grouping and selection methods to resolve this issue. The first method employs a convex function to penalize the pairwise l ∞ norm of connected regression/classification coefficients, achieving simultaneous feature grouping and selection. The second method improves the first one by utilizing a non-convex function to reduce the estimation bias. The third one is the extension of the second method using a truncated l 1 regularization to further reduce the estimation bias. The proposed methods combine feature grouping and feature selection to enhance estimation accuracy. We employ the alternating direction method of multipliers (ADMM) and difference of convex functions (DC) programming to solve the proposed formulations. Our experimental results on synthetic data and two real datasets demonstrate the effectiveness of the proposed methods.
Functional Organization of the Action Observation Network in Autism: A Graph Theory Approach.

PubMed

Alaerts, Kaat; Geerlings, Franca; Herremans, Lynn; Swinnen, Stephan P; Verhoeven, Judith; Sunaert, Stefan; Wenderoth, Nicole

2015-01-01

The ability to recognize, understand and interpret other's actions and emotions has been linked to the mirror system or action-observation-network (AON). Although variations in these abilities are prevalent in the neuro-typical population, persons diagnosed with autism spectrum disorders (ASD) have deficits in the social domain and exhibit alterations in this neural network. Here, we examined functional network properties of the AON using graph theory measures and region-to-region functional connectivity analyses of resting-state fMRI-data from adolescents and young adults with ASD and typical controls (TC). Overall, our graph theory analyses provided convergent evidence that the network integrity of the AON is altered in ASD, and that reductions in network efficiency relate to reductions in overall network density (i.e., decreased overall connection strength). Compared to TC, individuals with ASD showed significant reductions in network efficiency and increased shortest path lengths and centrality. Importantly, when adjusting for overall differences in network density between ASD and TC groups, participants with ASD continued to display reductions in network integrity, suggesting that also network-level organizational properties of the AON are altered in ASD. While differences in empirical connectivity contributed to reductions in network integrity, graph theoretical analyses provided indications that also changes in the high-level network organization reduced integrity of the AON.
Social Trust Prediction Using Heterogeneous Networks

PubMed Central

HUANG, JIN; NIE, FEIPING; HUANG, HENG; TU, YI-CHENG; LEI, YU

2014-01-01

Along with increasing popularity of social websites, online users rely more on the trustworthiness information to make decisions, extract and filter information, and tag and build connections with other users. However, such social network data often suffer from severe data sparsity and are not able to provide users with enough information. Therefore, trust prediction has emerged as an important topic in social network research. Traditional approaches are primarily based on exploring trust graph topology itself. However, research in sociology and our life experience suggest that people who are in the same social circle often exhibit similar behaviors and tastes. To take advantage of the ancillary information for trust prediction, the challenge then becomes what to transfer and how to transfer. In this article, we address this problem by aggregating heterogeneous social networks and propose a novel joint social networks mining (JSNM) method. Our new joint learning model explores the user-group-level similarity between correlated graphs and simultaneously learns the individual graph structure; therefore, the shared structures and patterns from multiple social networks can be utilized to enhance the prediction tasks. As a result, we not only improve the trust prediction in the target graph but also facilitate other information retrieval tasks in the auxiliary graphs. To optimize the proposed objective function, we use the alternative technique to break down the objective function into several manageable subproblems. We further introduce the auxiliary function to solve the optimization problems with rigorously proved convergence. The extensive experiments have been conducted on both synthetic and real- world data. All empirical results demonstrate the effectiveness of our method. PMID:24729776
Social Trust Prediction Using Heterogeneous Networks.

PubMed

Huang, Jin; Nie, Feiping; Huang, Heng; Tu, Yi-Cheng; Lei, Yu

2013-11-01

Along with increasing popularity of social websites, online users rely more on the trustworthiness information to make decisions, extract and filter information, and tag and build connections with other users. However, such social network data often suffer from severe data sparsity and are not able to provide users with enough information. Therefore, trust prediction has emerged as an important topic in social network research. Traditional approaches are primarily based on exploring trust graph topology itself. However, research in sociology and our life experience suggest that people who are in the same social circle often exhibit similar behaviors and tastes. To take advantage of the ancillary information for trust prediction, the challenge then becomes what to transfer and how to transfer. In this article, we address this problem by aggregating heterogeneous social networks and propose a novel joint social networks mining (JSNM) method. Our new joint learning model explores the user-group-level similarity between correlated graphs and simultaneously learns the individual graph structure; therefore, the shared structures and patterns from multiple social networks can be utilized to enhance the prediction tasks. As a result, we not only improve the trust prediction in the target graph but also facilitate other information retrieval tasks in the auxiliary graphs. To optimize the proposed objective function, we use the alternative technique to break down the objective function into several manageable subproblems. We further introduce the auxiliary function to solve the optimization problems with rigorously proved convergence. The extensive experiments have been conducted on both synthetic and real- world data. All empirical results demonstrate the effectiveness of our method.

Observations of H II regions around Zeta OPH and other O-B stars

NASA Astrophysics Data System (ADS)

Shestakova, L. I.; Kutirev, A. S.; Ataev, A. Sh.

1988-01-01

A Fabry-Perot spectrometer was used to measure the emission intensities in H-beta near Zeta Oph, Alpha Vir, Alpha Cam, and HD 188209. The spectrometer sensitivity is 0.2 rayleighs, the intensity measurement accuracy is 20 percent. Ionization zone boundaries are determined for Zeta Oph and Alpha Vir; the angular diameters of both regions are about 15 deg. The contour of the H II region near Zeta Oph on the level of the double background in the southwest does not close; instead, it expands again and incorporates the region associated with the B-association II Sco.
From Number Lines to Graphs in the Coordinate Plane: Investigating Problem Solving across Mathematical Representations

ERIC Educational Resources Information Center

Earnest, Darrell

2015-01-01

This article reports on students' problem-solving approaches across three representations--number lines, coordinate planes, and function graphs--the axes of which conventional mathematics treats in terms of consistent geometric and numeric coordinations. I consider these representations to be a part of a "hierarchical representational…
Graphing in Groups: Learning about Lines in a Collaborative Classroom Network Environment

ERIC Educational Resources Information Center

White, Tobin; Wallace, Matthew; Lai, Kevin

2012-01-01

This article presents a design experiment in which we explore new structures for classroom collaboration supported by a classroom network of handheld graphing calculators. We describe a design for small group investigations of linear functions and present findings from its implementation in three high school algebra classrooms. Our coding of the…
Graphical Response Exercises for Teaching Physics

ERIC Educational Resources Information Center

Bonham, Scott

2007-01-01

What is physics without graphs and diagrams? The web is becoming ubiquitous, but how can one expect students to make graphs and diagrams on the web? The solution is to extend functionality through Java applets. Four examples of exercises using the Physics Applets for Drawing (PADs) will illustrate how these can be used for physics instruction to…
The Gauss-Bonnet operator of an infinite graph

NASA Astrophysics Data System (ADS)

Anné, Colette; Torki-Hamza, Nabila

2015-06-01

We propose a general condition, to ensure essential self-adjointness for the Gauss-Bonnet operator , based on a notion of completeness as Chernoff. This gives essential self-adjointness of the Laplace operator both for functions and 1-forms on infinite graphs. This is used to extend Flanders result concerning solutions of Kirchhoff's laws.
A mass graph-based approach for the identification of modified proteoforms using top-down tandem mass spectra

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kou, Qiang; Wu, Si; Tolić, Nikola

Motivation: Although proteomics has rapidly developed in the past decade, researchers are still in the early stage of exploring the world of complex proteoforms, which are protein products with various primary structure alterations resulting from gene mutations, alternative splicing, post-translational modifications, and other biological processes. Proteoform identification is essential to mapping proteoforms to their biological functions as well as discovering novel proteoforms and new protein functions. Top-down mass spectrometry is the method of choice for identifying complex proteoforms because it provides a “bird’s eye view” of intact proteoforms. The combinatorial explosion of various alterations on a protein may result inmore » billions of possible proteoforms, making proteoform identification a challenging computational problem. Results: We propose a new data structure, called the mass graph, for efficient representation of proteoforms and design mass graph alignment algorithms. We developed TopMG, a mass graph-based software tool for proteoform identification by top-down mass spectrometry. Experiments on top-down mass spectrometry data sets showed that TopMG outperformed existing methods in identifying complex proteoforms.« less
High temperature microelectrophoresis studies of the solid oxide/water interface

NASA Astrophysics Data System (ADS)

Fedkin, Mark Valentinovich

Metal oxides are abundant components of geo-environmental systems and are widely used materials in industry. Many practical applications of oxide materials require the knowledge of their surface properties at both ambient and elevated temperatures. Due to substantial technical challenges associated with experimental studies of solid/water interfaces at elevated temperatures, consistent data on adsorption, surface charge, and zeta potential for most oxide materials are limited to temperatures less than 100°C. A high temperature microelectrophoresis technique, developed in this study, made it possible to extend the zeta potential measurements at the solid oxide/water interface to 200°C. The design of the high temperature electrophoresis cell allowed for the visual microscopic observation of the electrophoretic movement of suspended particles through pressure-tight sapphire windows. The electrophoretic mobilities of metal oxide particles suspended in aqueous solutions were measured in a DC electric field as a function of pH, ionic strength, and temperature. The experimental procedure and methods for evaluation of the main experimental parameters (electrophoretic mobility, electric field strength, high temperature pH, and cell constant) have been developed. Zeta potentials were calculated from the experimental data using O'Brien and White's (1978) numerical solution for electrophoretic mobility equation. Zeta potentials and isoelectric points (IEP) of the metal oxide/aqueous solution interface were experimentally determined for ZrO2, TiO 2(rutile), and alphaAl2O3 at 25, 120, and 200°C. The background solutions used for the preparation of suspensions were pure H2O, NaCl(aq) (10-4--10-2 mol.kg-1), and SrCl2 (10-4 mol.kg, for TiO2). For all studied materials, the IEPs were found to regularly decrease with increasing temperature, which agrees with available theoretical predictions. Thermodynamic functions, including Gibbs energy, enthalpy, and heat capacity, were estimated for the H +/OH- adsorption from the experimental IEP data using the 1-pK model of the oxide/water interface. The experimental information obtained in this study combined with data from potentiometric titration and other experimental methods form the basis for future theoretical studies of the electrical double layer at the oxide/water interface.
Surface charge control for zwitterionic polymer brushes: Tailoring surface properties to antifouling applications.

PubMed

Guo, Shanshan; Jańczewski, Dominik; Zhu, Xiaoying; Quintana, Robert; He, Tao; Neoh, Koon Gee

2015-08-15

Electrostatic interactions play an important role in adhesion phenomena particularly for biomacromolecules and microorganisms. Zero charge valence of zwitterions has been claimed as the key to their antifouling properties. However, due to the differences in the relative strength of their acid and base components, zwitterionic materials may not be charge neutral in aqueous environments. Thus, their charge on surfaces should be further adjusted for a specific pH environment, e.g. physiological pH typical in biomedical applications. Surface zeta potential for thin polymeric films composed of polysulfobetaine methacrylate (pSBMA) brushes is controlled through copolymerizing zwitterionic SBMA and cationic methacryloyloxyethyltrimethyl ammonium chloride (METAC) via surface-initiated atom transfer polymerization. Surface properties including zeta potential, roughness, free energy and thickness are measured and the antifouling performance of these surfaces is assessed. The zeta potential of pSBMA brushes is -40 mV across a broad pH range. By adding 2% METAC, the zeta potential of pSBMA can be tuned to zero at physiological pH while minimally affecting other physicochemical properties including dry brush thickness, surface free energy and surface roughness. Surfaces with zero and negative zeta potential best resist fouling by bovine serum albumin, Escherichia coli and Staphylococcus aureus. Surfaces with zero zeta potential also reduce fouling by lysozyme more effectively than surfaces with negative and positive zeta potential. Copyright © 2015 Elsevier Inc. All rights reserved.
Graph partitions and cluster synchronization in networks of oscillators

PubMed Central

Schaub, Michael T.; O’Clery, Neave; Billeh, Yazan N.; Delvenne, Jean-Charles; Lambiotte, Renaud; Barahona, Mauricio

2017-01-01

Synchronization over networks depends strongly on the structure of the coupling between the oscillators. When the coupling presents certain regularities, the dynamics can be coarse-grained into clusters by means of External Equitable Partitions of the network graph and their associated quotient graphs. We exploit this graph-theoretical concept to study the phenomenon of cluster synchronization, in which different groups of nodes converge to distinct behaviors. We derive conditions and properties of networks in which such clustered behavior emerges, and show that the ensuing dynamics is the result of the localization of the eigenvectors of the associated graph Laplacians linked to the existence of invariant subspaces. The framework is applied to both linear and non-linear models, first for the standard case of networks with positive edges, before being generalized to the case of signed networks with both positive and negative interactions. We illustrate our results with examples of both signed and unsigned graphs for consensus dynamics and for partial synchronization of oscillator networks under the master stability function as well as Kuramoto oscillators. PMID:27781454
EFFECT OF AQUEOUS PHASE PROPERTIES ON CLAY PARTICLE ZETA POTENTIAL AND ELECTRO-OSMOTIC PERMEABILITY: IMPLICATIONS FOR ELECTRO-KINETIC SOIL REMEDIATION PROCESSES

EPA Science Inventory

The influence of aqueous phase properties (pH, ionic strength and divalent metal ion concentration) on clay particle zeta potential and packed-bed electro-osmotic permeability was quantified. Although pH strongly altered the zeta potential of a Georgia kaolinite, it did not signi...
Hearing the shape of the Ising model with a programmable superconducting-flux annealer.

PubMed

Vinci, Walter; Markström, Klas; Boixo, Sergio; Roy, Aidan; Spedalieri, Federico M; Warburton, Paul A; Severini, Simone

2014-07-16

Two objects can be distinguished if they have different measurable properties. Thus, distinguishability depends on the Physics of the objects. In considering graphs, we revisit the Ising model as a framework to define physically meaningful spectral invariants. In this context, we introduce a family of refinements of the classical spectrum and consider the quantum partition function. We demonstrate that the energy spectrum of the quantum Ising Hamiltonian is a stronger invariant than the classical one without refinements. For the purpose of implementing the related physical systems, we perform experiments on a programmable annealer with superconducting flux technology. Departing from the paradigm of adiabatic computation, we take advantage of a noisy evolution of the device to generate statistics of low energy states. The graphs considered in the experiments have the same classical partition functions, but different quantum spectra. The data obtained from the annealer distinguish non-isomorphic graphs via information contained in the classical refinements of the functions but not via the differences in the quantum spectra.
Semantic graphs and associative memories

NASA Astrophysics Data System (ADS)

Pomi, Andrés; Mizraji, Eduardo

2004-12-01

Graphs have been increasingly utilized in the characterization of complex networks from diverse origins, including different kinds of semantic networks. Human memories are associative and are known to support complex semantic nets; these nets are represented by graphs. However, it is not known how the brain can sustain these semantic graphs. The vision of cognitive brain activities, shown by modern functional imaging techniques, assigns renewed value to classical distributed associative memory models. Here we show that these neural network models, also known as correlation matrix memories, naturally support a graph representation of the stored semantic structure. We demonstrate that the adjacency matrix of this graph of associations is just the memory coded with the standard basis of the concept vector space, and that the spectrum of the graph is a code invariant of the memory. As long as the assumptions of the model remain valid this result provides a practical method to predict and modify the evolution of the cognitive dynamics. Also, it could provide us with a way to comprehend how individual brains that map the external reality, almost surely with different particular vector representations, are nevertheless able to communicate and share a common knowledge of the world. We finish presenting adaptive association graphs, an extension of the model that makes use of the tensor product, which provides a solution to the known problem of branching in semantic nets.
Algebraic Topology of Multi-Brain Connectivity Networks Reveals Dissimilarity in Functional Patterns during Spoken Communications

PubMed Central

Tadić, Bosiljka; Andjelković, Miroslav; Boshkoska, Biljana Mileva; Levnajić, Zoran

2016-01-01

Human behaviour in various circumstances mirrors the corresponding brain connectivity patterns, which are suitably represented by functional brain networks. While the objective analysis of these networks by graph theory tools deepened our understanding of brain functions, the multi-brain structures and connections underlying human social behaviour remain largely unexplored. In this study, we analyse the aggregate graph that maps coordination of EEG signals previously recorded during spoken communications in two groups of six listeners and two speakers. Applying an innovative approach based on the algebraic topology of graphs, we analyse higher-order topological complexes consisting of mutually interwoven cliques of a high order to which the identified functional connections organise. Our results reveal that the topological quantifiers provide new suitable measures for differences in the brain activity patterns and inter-brain synchronisation between speakers and listeners. Moreover, the higher topological complexity correlates with the listener’s concentration to the story, confirmed by self-rating, and closeness to the speaker’s brain activity pattern, which is measured by network-to-network distance. The connectivity structures of the frontal and parietal lobe consistently constitute distinct clusters, which extend across the listener’s group. Formally, the topology quantifiers of the multi-brain communities exceed the sum of those of the participating individuals and also reflect the listener’s rated attributes of the speaker and the narrated subject. In the broader context, the presented study exposes the relevance of higher topological structures (besides standard graph measures) for characterising functional brain networks under different stimuli. PMID:27880802
Investigating the clinical potential for 14-3-3 zeta protein to serve as a biomarker for epithelial ovarian cancer

PubMed Central

2013-01-01

Objective Recently, 14-3-3 zeta protein was identified as a potential serum biomarker of epithelial ovarian cancer (EOC). The goal of this study was to investigate the clinical potential of 14-3-3 zeta protein for monitoring EOC progression compared with CA-125 and HE4. Design Prospective follow-up study. Setting University of Pecs Medical Center Department of Obstetrics and Gynecology/Oncology (Pecs, Hungary). Population Thirteen EOC patients with advanced stage (FIGO IIb-IIIc) epithelial ovarian cancer that underwent radical surgery and received six consecutive cycles of first line chemotherapy (paclitaxel, carboplatin) in 21-day intervals. Methods Pre- and post-chemotherapy computed tomography (CT) scans were performed. Serum levels of CA-125, HE4, and 14-3-3 zeta protein were detected by enzyme-linked immunosorbent assay (ELISA) and quantitative electrochemiluminescence assay (ECLIA). Main outcome measures Serum levels of CA-125, HE4, and 14-3-3 zeta protein, as well as lesion size according to pre- and post-chemotherapy CT scans. Results Serum levels of CA-125 and HE4 were found to significantly decrease following chemotherapy, and this was consistent with the decrease in lesion size detected post-chemotherapy. In contrast, 14-3-3 zeta protein levels did not significantly differ in healthy postmenopausal patients versus EOC patients. Conclusions Determination of CA-125 and HE4 serum levels for the determination of the risk of ovarian malignancy algorithm (ROMA) represents a useful tool for the prediction of chemotherapy efficacy for EOC patients. However, levels of 14-3-3 zeta protein were not found to vary significantly as a consequence of treatment. Therefore we question if 14-3-3 zeta protein is a reliable biomarker, which correlates with the clinical behavior of EOC. PMID:24238270
Cosmic-ray Induced Destruction of CO in Star-forming Galaxies

NASA Astrophysics Data System (ADS)

Bisbas, Thomas G.; van Dishoeck, Ewine F.; Papadopoulos, Padelis P.; Szűcs, László; Bialy, Shmuel; Zhang, Zhi-Yu

2017-04-01

We explore the effects of the expected higher cosmic ray (CR) ionization rates {\\zeta }{CR} on the abundances of carbon monoxide (CO), atomic carbon (C), and ionized carbon (C+) in the H2 clouds of star-forming galaxies. The study of Bisbas et al. is expanded by (a) using realistic inhomogeneous giant molecular cloud (GMC) structures, (b) a detailed chemical analysis behind the CR-induced destruction of CO, and (c) exploring the thermal state of CR-irradiated molecular gas. CRs permeating the interstellar medium with {\\zeta }{CR}≳ 10× ({Galactic}) are found to significantly reduce the [CO]/[H2] abundance ratios throughout the mass of a GMC. CO rotational line imaging will then show much clumpier structures than the actual ones. For {\\zeta }{CR}≳ 100 × (Galactic) this bias becomes severe, limiting the usefulness of CO lines for recovering structural and dynamical characteristics of H2-rich galaxies throughout the universe, including many of the so-called main-sequence galaxies where the bulk of cosmic star formation occurs. Both C+ and C abundances increase with rising {\\zeta }{CR}, with C remaining the most abundant of the two throughout H2 clouds, when {\\zeta }{CR}˜ (1-100) × (Galactic). C+ starts to dominate for {\\zeta }{CR}≳ {10}3 × (Galactic). The thermal state of the gas in the inner and denser regions of GMCs is invariant with {T}{gas}˜ 10 {{K}} for {\\zeta }{CR}˜ (1-10) × (Galactic). For {\\zeta }{CR}˜ {10}3 × (Galactic) this is no longer the case and {T}{gas}˜ 30{--}50 {{K}} are reached. Finally, we identify OH as the key species whose T gas-sensitive abundance could mitigate the destruction of CO at high temperatures.
Zeta Sperm Selection Improves Pregnancy Rate and Alters Sex Ratio in Male Factor Infertility Patients: A Double-Blind, Randomized Clinical Trial

PubMed Central

Nasr Esfahani, Mohammad Hossein; Deemeh, Mohammad Reza; Tavalaee, Marziyeh; Sekhavati, Mohammad Hadi; Gourabi, Hamid

2016-01-01

Background Selection of sperm for intra-cytoplasmic sperm injection (ICSI) is usually considered as the ultimate technique to alleviate male-factor infertility. In routine ICSI, selection is based on morphology and viability which does not necessarily preclude the chance injection of DNA-damaged or apoptotic sperm into the oocyte. Sperm with high negative surface electrical charge, named “Zeta potential”, are mature and more likely to have intact chromatin. In addition, X-bearing spermatozoa carry more negative charge. Therefore, we aimed to compare the clinical outcomes of Zeta procedure with routine sperm selection in infertile men candidate for ICSI. Materials and Methods From a total of 203 ICSI cycles studied, 101 cycles were allocated to density gradient centrifugation (DGC)/Zeta group and the remaining 102 were included in the DGC group in this prospective study. Clinical outcomes were com- pared between the two groups. The ratios of Xand Y bearing sperm were assessed by fluorescence in situ hybridization (FISH) and quantitative polymerase chain reaction (qPCR) methods in 17 independent semen samples. Results In the present double-blind randomized clinical trial, a significant increase in top quality embryos and pregnancy rate were observed in DGC/Zeta group compared to DGC group. Moreover, sex ratio (XY/XX) at birth significantly was lower in the DGC/Zeta group compared to DGC group despite similar ratio of X/Y bearings sper- matozoa following Zeta selection. Conclusion Zeta method not only improves the percentage of top embryo quality and pregnancy outcome but also alters the sex ratio compared to the conventional DGC method, despite no significant change in the ratio of Xand Ybearing sperm population (Registration number: IRCT201108047223N1). PMID:27441060
The Structural Evolution of Milky-Way-Like Star-Forming Galaxies zeta is approximately 1.3

NASA Technical Reports Server (NTRS)

Patel, Shannon G.; Fumagalli, Mattia; Franx, Marun; VanDokkum, Pieter G.; VanDerWel, Arjen; Leja, Joel; Labbe, Ivo; Brammr, Gabriel; Whitaker, Katherine E.; Skelton, Rosalind E.;

2013-01-01

We follow the structural evolution of star-forming galaxies (SFGs) like the Milky Way by selecting progenitors to zeta is approx. 1.3 based on the stellar mass growth inferred from the evolution of the star-forming sequence. We select our sample from the 3D-HT survey, which utilizes spectroscopy from the HST-WFC3 G141 near-IR grism and enables precise redshift measurements for our sample of SFGs. Structural properties are obtained from Sersic profile fits to CANDELS WFC3 imaging. The progenitors of zeta = 0 SFGs with stellar mass M = 10(exp 10.5) solar mass are typically half as massive at zeta is approx. 1. This late-time stellar mass grow is consistent with recent studies that employ abundance matching techniques. The descendant SFGs at zeta is approx. 0 have grown in half-light radius by a factor of approx. 1.4 zeta is approx. 1. The half-light radius grows with stellar mass as r(sub e) alpha stellar mass(exp 0.29). While most of the stellar mass is clearly assembling at large radii, the mass surface density profiles reveal ongoing mass growth also in the central regions where bulges and pseudobulges are common features in present day late-type galaxies. Some portion of this growth in the central regions is due to star formation as recent observations of H(a) maps for SFGs at zeta approx. are found to be extended but centrally peaked. Connecting our lookback study with galactic archeology, we find the stellar mass surface density at R - 8 kkpc to have increased by a factor of approx. 2 since zeta is approx. 1, in good agreement with measurements derived for the solar neighborhood of the Milky Way.

A Comparison of Streaming and Microelectrophoresis Methods for Obtaining the zeta Potential of Granular Porous Media Surfaces.

PubMed

Johnson

1999-01-01

The electrokinetic behavior of granular quartz sand in aqueous solution is investigated by both microelectrophoresis and streaming potential methods. zeta potentials of surfaces composed of granular quartz obtained via streaming potential methods are compared to electrophoretic mobility zeta potential values of colloid-sized quartz fragments. The zeta values generated by these alternate methods are in close agreement over a wide pH range and electrolyte concentrations spanning several orders of magnitude. Streaming measurements performed on chemically heterogeneous mixtures of physically homogeneous sand are shown to obey a simple mixing model based on the surface area-weighted average of the streaming potentials associated with the individual end members. These experimental results support the applicability of the streaming potential method as a means of determining the zeta potential of granular porous media surfaces. Copyright 1999 Academic Press.
Building pathway graphs from BioPAX data in R.

PubMed

Benis, Nirupama; Schokker, Dirkjan; Kramer, Frank; Smits, Mari A; Suarez-Diez, Maria

2016-01-01

Biological pathways are increasingly available in the BioPAX format which uses an RDF model for data storage. One can retrieve the information in this data model in the scripting language R using the package rBiopaxParser , which converts the BioPAX format to one readable in R. It also has a function to build a regulatory network from the pathway information. Here we describe an extension of this function. The new function allows the user to build graphs of entire pathways, including regulated as well as non-regulated elements, and therefore provides a maximum of information. This function is available as part of the rBiopaxParser distribution from Bioconductor.
D-Optimal mixture experimental design for stealth biodegradable crosslinked docetaxel-loaded poly-ε-caprolactone nanoparticles manufactured by dispersion polymerization.

PubMed

Ogunwuyi, O; Adesina, S; Akala, E O

2015-03-01

We report here our efforts on the development of stealth biodegradable crosslinked poly-ε-caprolactone nanoparticles by free radical dispersion polymerization suitable for the delivery of bioactive agents. The uniqueness of the dispersion polymerization technique is that it is surfactant free, thereby obviating the problems known to be associated with the use of surfactants in the fabrication of nanoparticles for biomedical applications. Aided by a statistical software for experimental design and analysis, we used D-optimal mixture statistical experimental design to generate thirty batches of nanoparticles prepared by varying the proportion of the components (poly-ε-caprolactone macromonomer, crosslinker, initiators and stabilizer) in acetone/water system. Morphology of the nanoparticles was examined using scanning electron microscopy (SEM). Particle size and zeta potential were measured by dynamic light scattering (DLS). Scheffe polynomial models were generated to predict particle size (nm) and particle surface zeta potential (mV) as functions of the proportion of the components. Solutions were returned from simultaneous optimization of the response variables for component combinations to (a) minimize nanoparticle size (small nanoparticles are internalized into disease organs easily, avoid reticuloendothelial clearance and lung filtration) and (b) maximization of the negative zeta potential values, as it is known that, following injection into the blood stream, nanoparticles with a positive zeta potential pose a threat of causing transient embolism and rapid clearance compared to negatively charged particles. In vitro availability isotherms show that the nanoparticles sustained the release of docetaxel for 72 to 120 hours depending on the formulation. The data show that nanotechnology platforms for controlled delivery of bioactive agents can be developed based on the nanoparticles.

A general framework for regularized, similarity-based image restoration.

PubMed

Kheradmand, Amin; Milanfar, Peyman

2014-12-01

Any image can be represented as a function defined on a weighted graph, in which the underlying structure of the image is encoded in kernel similarity and associated Laplacian matrices. In this paper, we develop an iterative graph-based framework for image restoration based on a new definition of the normalized graph Laplacian. We propose a cost function, which consists of a new data fidelity term and regularization term derived from the specific definition of the normalized graph Laplacian. The normalizing coefficients used in the definition of the Laplacian and associated regularization term are obtained using fast symmetry preserving matrix balancing. This results in some desired spectral properties for the normalized Laplacian such as being symmetric, positive semidefinite, and returning zero vector when applied to a constant image. Our algorithm comprises of outer and inner iterations, where in each outer iteration, the similarity weights are recomputed using the previous estimate and the updated objective function is minimized using inner conjugate gradient iterations. This procedure improves the performance of the algorithm for image deblurring, where we do not have access to a good initial estimate of the underlying image. In addition, the specific form of the cost function allows us to render the spectral analysis for the solutions of the corresponding linear equations. In addition, the proposed approach is general in the sense that we have shown its effectiveness for different restoration problems, including deblurring, denoising, and sharpening. Experimental results verify the effectiveness of the proposed algorithm on both synthetic and real examples.
Graph-based network analysis of resting-state functional MRI.

PubMed

Wang, Jinhui; Zuo, Xinian; He, Yong

2010-01-01

In the past decade, resting-state functional MRI (R-fMRI) measures of brain activity have attracted considerable attention. Based on changes in the blood oxygen level-dependent signal, R-fMRI offers a novel way to assess the brain's spontaneous or intrinsic (i.e., task-free) activity with both high spatial and temporal resolutions. The properties of both the intra- and inter-regional connectivity of resting-state brain activity have been well documented, promoting our understanding of the brain as a complex network. Specifically, the topological organization of brain networks has been recently studied with graph theory. In this review, we will summarize the recent advances in graph-based brain network analyses of R-fMRI signals, both in typical and atypical populations. Application of these approaches to R-fMRI data has demonstrated non-trivial topological properties of functional networks in the human brain. Among these is the knowledge that the brain's intrinsic activity is organized as a small-world, highly efficient network, with significant modularity and highly connected hub regions. These network properties have also been found to change throughout normal development, aging, and in various pathological conditions. The literature reviewed here suggests that graph-based network analyses are capable of uncovering system-level changes associated with different processes in the resting brain, which could provide novel insights into the understanding of the underlying physiological mechanisms of brain function. We also highlight several potential research topics in the future.
On Functional Module Detection in Metabolic Networks

PubMed Central

Koch, Ina; Ackermann, Jörg

2013-01-01

Functional modules of metabolic networks are essential for understanding the metabolism of an organism as a whole. With the vast amount of experimental data and the construction of complex and large-scale, often genome-wide, models, the computer-aided identification of functional modules becomes more and more important. Since steady states play a key role in biology, many methods have been developed in that context, for example, elementary flux modes, extreme pathways, transition invariants and place invariants. Metabolic networks can be studied also from the point of view of graph theory, and algorithms for graph decomposition have been applied for the identification of functional modules. A prominent and currently intensively discussed field of methods in graph theory addresses the Q-modularity. In this paper, we recall known concepts of module detection based on the steady-state assumption, focusing on transition-invariants (elementary modes) and their computation as minimal solutions of systems of Diophantine equations. We present the Fourier-Motzkin algorithm in detail. Afterwards, we introduce the Q-modularity as an example for a useful non-steady-state method and its application to metabolic networks. To illustrate and discuss the concepts of invariants and Q-modularity, we apply a part of the central carbon metabolism in potato tubers (Solanum tuberosum) as running example. The intention of the paper is to give a compact presentation of known steady-state concepts from a graph-theoretical viewpoint in the context of network decomposition and reduction and to introduce the application of Q-modularity to metabolic Petri net models. PMID:24958145
Flux control coefficients determined by inhibitor titration: the design and analysis of experiments to minimize errors.

PubMed Central

Small, J R

1993-01-01

This paper is a study into the effects of experimental error on the estimated values of flux control coefficients obtained using specific inhibitors. Two possible techniques for analysing the experimental data are compared: a simple extrapolation method (the so-called graph method) and a non-linear function fitting method. For these techniques, the sources of systematic errors are identified and the effects of systematic and random errors are quantified, using both statistical analysis and numerical computation. It is shown that the graph method is very sensitive to random errors and, under all conditions studied, that the fitting method, even under conditions where the assumptions underlying the fitted function do not hold, outperformed the graph method. Possible ways of designing experiments to minimize the effects of experimental errors are analysed and discussed. PMID:8257434
Effect of double-layer polarization on the forces that act on a nanosized cylindrical particle in an ac electrical field.

PubMed

Zhao, Hui; Bau, Haim H

2008-06-17

The polarization of, the forces acting on, and the electroosmotic flow field around a cylindrical particle of radius a* and uniform zeta potential zeta* submerged in an electrolyte solution and subjected to alternating electric fields are computed by solving the Poisson-Nernst-Planck (PNP) equations (the standard model). The dipole coefficient and the electrostatic and hydrodynamic forces are calculated as functions of the electric field's frequency, the solute concentration, and the particle's surface charge. The calculations are not restricted to small Debye screening lengths (lambdaD*). At relatively low frequencies, the polarization coefficient is nearly frequency-independent. As the frequency increases above D*/a*(2), where D* is the effective diffusion coefficient, the polarization coefficient initially increases, attains a maximum, and then decreases to an asymptotic value (when the frequency exceeds (1+Du)D*/lambdaD(*2), where Du is the Dukhin number). At low frequencies, when (lambdaD*/a*)(2)e(|zeta*F*/(2R*T*)|) < 1, the PNP calculations are in excellent agreement with the predictions of the Dukhin-Shilov (DS) low-frequency theory. At high frequencies, when lambda D*/a* < 1, the PNP calculations are in excellent agreement with the Maxwell-Wagner-O'Konski (MWO) theory.
p62 modulates Akt activity via association with PKC{zeta} in neuronal survival and differentiation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Joung, Insil; Kim, Hak Jae; Kwon, Yunhee Kim

2005-08-26

p62 is a ubiquitously expressed phosphoprotein that interacts with a number of signaling molecules and a major component of neurofibrillary tangles in the brain of Alzheimer's disease patients. It has been implicated in important cellular functions such as cell proliferation and anti-apoptotic pathways. In this study, we have addressed the potential role of p62 during neuronal differentiation and survival using HiB5, a rat neuronal progenitor cell. We generated a recombinant adenovirus encoding T7-epitope tagged p62 to reliably transfer p62 cDNA into the neuronal cells. The results show that an overexpression of p62 led not only to neuronal differentiation, but alsomore » to decreased cell death induced by serum withdrawal in HiB5 cells. In this process p62-dependent Akt phosphorylation occurred via the release of Akt from PKC{zeta} by association of p62 and PKC{zeta}, which is known as a negative regulator of Akt activation. These findings indicate that p62 facilitates cell survival through novel signaling cascades that result in Akt activation. Furthermore, we found that p62 expression was induced during neuronal differentiation. Taken together, the data suggest p62 is a regulator of neuronal cell survival and differentiation.« less
MADM, a novel adaptor protein that mediates phosphorylation of the 14-3-3 binding site of myeloid leukemia factor 1.

PubMed

Lim, Raelene; Winteringham, Louise N; Williams, James H; McCulloch, Ross K; Ingley, Evan; Tiao, Jim Y-H; Lalonde, Jean-Philippe; Tsai, Schickwann; Tilbrook, Peta A; Sun, Yi; Wu, Xiaohua; Morris, Stephan W; Klinken, S Peter

2002-10-25

A yeast two-hybrid screen was conducted to identify binding partners of Mlf1, an oncoprotein recently identified in a translocation with nucleophosmin that causes acute myeloid leukemia. Two proteins isolated in this screen were 14-3-3zeta and a novel adaptor, Madm. Mlf1 contains a classic RSXSXP sequence for 14-3-3 binding and is associated with 14-3-3zeta via this phosphorylated motif. Madm co-immunoprecipitated with Mlf1 and co-localized in the cytoplasm. In addition, Madm recruited a serine kinase, which phosphorylated both Madm and Mlf1 including the RSXSXP motif. In contrast to wild-type Mlf1, the oncogenic fusion protein nucleophosmin (NPM)-MLF1 did not bind 14-3-3zeta, had altered Madm binding, and localized exclusively in the nucleus. Ectopic expression of Madm in M1 myeloid cells suppressed cytokine-induced differentiation unlike Mlf1, which promotes maturation. Because the Mlf1 binding region of Madm and its own dimerization domain overlapped, the levels of Madm and Mlf1 may affect complex formation and regulate differentiation. In summary, this study has identified two partner proteins of Mlf1 that may influence its subcellular localization and biological function.
Joule heating effects on electromagnetohydrodynamic flow through a peristaltically induced micro-channel with different zeta potential and wall slip

NASA Astrophysics Data System (ADS)

Ranjit, N. K.; Shit, G. C.

2017-09-01

This paper aims to develop a mathematical model for magnetohydrodynamic flow of biofluids through a hydrophobic micro-channel with periodically contracting and expanding walls under the influence of an axially applied electric field. The velocity slip effects have been taken into account at the channel walls by employing different slip lengths due to hydrophobic gating. Different temperature jump factors have also been used to investigate the thermomechanical interactions at the fluid-solid interface. The electromagnetohydrodynamic flow in a microchannel is simplified under the framework of Debye-Hückel linearization approximation. We have derived the closed-form solutions for the linearized dimensionless boundary value problem under the assumptions of long wave length and low Reynolds number. The axial velocity, temperature, pressure distribution, stream function, wall shear stress and the Nusselt number have been appraised for diverse values of the parameters approaching into the problem. Our main focus is to determine the effects of different zeta potential on the axial velocity and temperature distribution under electromagnetic environment. This study puts forward an important observation that the different zeta potential plays an important role in controlling fluid velocity. The study further reveals that the temperature increases significantly with the Joule heating parameter and the Brinkman number (arises due to the dissipation of energy).
Quantifying fluctuations in market liquidity: analysis of the bid-ask spread.

PubMed

Plerou, Vasiliki; Gopikrishnan, Parameswaran; Stanley, H Eugene

2005-04-01

Quantifying the statistical features of the bid-ask spread offers the possibility of understanding some aspects of market liquidity. Using quote data for the 116 most frequently traded stocks on the New York Stock Exchange over the two-year period 1994-1995, we analyze the fluctuations of the average bid-ask spread S over a time interval deltat. We find that S is characterized by a distribution that decays as a power law P[S>x] approximately x(-zeta(S) ), with an exponent zeta(S) approximately = 3 for all 116 stocks analyzed. Our analysis of the autocorrelation function of S shows long-range power-law correlations, (S(t)S(t + tau)) approximately tau(-mu(s)), similar to those previously found for the volatility. We next examine the relationship between the bid-ask spread and the volume Q, and find that S approximately ln Q; we find that a similar logarithmic relationship holds between the transaction-level bid-ask spread and the trade size. We then study the relationship between S and other indicators of market liquidity such as the frequency of trades N and the frequency of quote updates U, and find S approximately ln N and S approximately ln U. Lastly, we show that the bid-ask spread and the volatility are also related logarithmically.
Insights into the activation mechanism of calcium ions on the sericite surface: A combined experimental and computational study

NASA Astrophysics Data System (ADS)

Hu, Yuehua; He, Jianyong; Zhang, Chenhu; Zhang, Chenyang; Sun, Wei; Zhao, Dongbo; Chen, Pan; Han, Haisheng; Gao, Zhiyong; Liu, Runqing; Wang, Li

2018-01-01

The adsorption behaviors and the activation mechanism of calcium ions (Ca2+) on sericite surface have been investigated by Zeta potential measurements, Fourier transform infrared spectroscopy (FT-IR), Micro-flotation tests and First principle calculations. Zeta potential tests results show that the sericite surface potential increases due to the adsorption of calcium ions on the surface. Micro-flotation tests demonstrate that sericite recovery remarkably rise by 10% due to the calcium ions activation on sericite surface. However, the characteristic adsorption bands of calcium oleate do not appear in the FT-IR spectrum, suggesting that oleate ions just physically adsorb on the sericite surface. The first principle calculations based on the density functional theory (DFT) further reveals the microscopic adsorption mechanism of calcium ions on the sericite surface before and after hydration.
Synthesis of Polyferrocenylsilane Block Copolymers and their Crystallization-Driven Self-Assembly in Protic Solvents

NASA Astrophysics Data System (ADS)

Zhou, Hang

Quantum walks are the quantum mechanical analogue of classical random walks. Discrete-time quantum walks have been introduced and studied mostly on the line Z or higher dimensional space Zd but rarely defined on graphs with fractal dimensions because the coin operator depends on the position and the Fourier transform on the fractals is not defined. Inspired by its nature of classical walks, different quantum walks will be defined by choosing different shift and coin operators. When the coin operator is uniform, the results of classical walks will be obtained upon measurement at each step. Moreover, with measurement at each step, our results reveal more information about the classical random walks. In this dissertation, two graphs with fractal dimensions will be considered. The first one is Sierpinski gasket, a degree-4 regular graph with Hausdorff dimension of df = ln 3/ ln 2. The second is the Cantor graph derived like Cantor set, with Hausdorff dimension of df = ln 2/ ln 3. The definitions and amplitude functions of the quantum walks will be introduced. The main part of this dissertation is to derive a recursive formula to compute the amplitude Green function. The exiting probability will be computed and compared with the classical results. When the generation of graphs goes to infinity, the recursion of the walks will be investigated and the convergence rates will be obtained and compared with the classical counterparts.
PDB2Graph: A toolbox for identifying critical amino acids map in proteins based on graph theory.

PubMed

Niknam, Niloofar; Khakzad, Hamed; Arab, Seyed Shahriar; Naderi-Manesh, Hossein

2016-05-01

The integrative and cooperative nature of protein structure involves the assessment of topological and global features of constituent parts. Network concept takes complete advantage of both of these properties in the analysis concomitantly. High compatibility to structural concepts or physicochemical properties in addition to exploiting a remarkable simplification in the system has made network an ideal tool to explore biological systems. There are numerous examples in which different protein structural and functional characteristics have been clarified by the network approach. Here, we present an interactive and user-friendly Matlab-based toolbox, PDB2Graph, devoted to protein structure network construction, visualization, and analysis. Moreover, PDB2Graph is an appropriate tool for identifying critical nodes involved in protein structural robustness and function based on centrality indices. It maps critical amino acids in protein networks and can greatly aid structural biologists in selecting proper amino acid candidates for manipulating protein structures in a more reasonable and rational manner. To introduce the capability and efficiency of PDB2Graph in detail, the structural modification of Calmodulin through allosteric binding of Ca(2+) is considered. In addition, a mutational analysis for three well-identified model proteins including Phage T4 lysozyme, Barnase and Ribonuclease HI, was performed to inspect the influence of mutating important central residues on protein activity. Copyright © 2016 Elsevier Ltd. All rights reserved.
An analogue of Weyl’s law for quantized irreducible generalized flag manifolds

DOE Office of Scientific and Technical Information (OSTI.GOV)

Matassa, Marco, E-mail: marco.matassa@gmail.com, E-mail: mmatassa@math.uio.no

2015-09-15

We prove an analogue of Weyl’s law for quantized irreducible generalized flag manifolds. This is formulated in terms of a zeta function which, similarly to the classical setting, satisfies the following two properties: as a functional on the quantized algebra it is proportional to the Haar state and its first singularity coincides with the classical dimension. The relevant formulas are given for the more general case of compact quantum groups.
The Effect of Graphing Calculators on Student Achievement in College Algebra and Pre-Calculus Mathematics Courses

ERIC Educational Resources Information Center

Hatem, Neil

2010-01-01

This study investigates the relationship between the use of graphing calculators employed as Type II technology and student achievement, as determined by assessing students' problem solving skills associated with the concept of function, at the college algebra and pre-calculus level. In addition, this study explores the integration of graphing…
Tangent Lines without Calculus

ERIC Educational Resources Information Center

Rabin, Jeffrey M.

2008-01-01

This article presents a problem that can help high school students develop the concept of instantaneous velocity and connect it with the slope of a tangent line to the graph of position versus time. It also gives a method for determining the tangent line to the graph of a polynomial function at any point without using calculus. (Contains 1 figure.)
On total irregularity strength of caterpillar graphs with two leaves on each internal vertex

NASA Astrophysics Data System (ADS)

Rosyida, I.; Widodo; Indriati, D.

2018-04-01

Let G(V, E) be a graph. A function f from V(G)\\cup E(G) to the set {1, 2, …, k} is said to be a totally irregular total k-labeling of G if the weights of any two different vertices x and y in V (G) satisfy {w}f(x)\
Numerical Solutions of the Complete Navier-Stokes Equations

NASA Technical Reports Server (NTRS)

Robinson, David F.; Hassan, H. A.

1997-01-01

This report details the development of a new two-equation turbulence closure model based on the exact turbulent kinetic energy k and the variance of vorticity, zeta. The model, which is applicable to three dimensional flowfields, employs one set of model constants and does not use damping or wall functions, or geometric factors.
Product shipping information using graceful labeling on undirected tree graph approach

NASA Astrophysics Data System (ADS)

Kuan, Yoong Kooi; Ghani, Ahmad Termimi Ab

2017-08-01

Product shipping information is the related information of an ordered product that ready to be shipped to the foreign customer's company, where the information represents as an irrefutable proof in black and white to the local manufacturer by E-mails. This messy and unordered list of information is stored in E-mail folders by the people incharge, which do not function in collating the information properly. So, in this paper, an algorithm is proposed on how to rearrange the messy information from the sequence of a path graph structure into a concise version of a caterpillar graph with achieving the concept of graceful labeling. The final graceful caterpillar graph consists of the full listed information together with the numbering, which able to assist people get the information fleetly for shipping arrangement procedure.
Simulator for heterogeneous dataflow architectures

NASA Technical Reports Server (NTRS)

Malekpour, Mahyar R.

1993-01-01

A new simulator is developed to simulate the execution of an algorithm graph in accordance with the Algorithm to Architecture Mapping Model (ATAMM) rules. ATAMM is a Petri Net model which describes the periodic execution of large-grained, data-independent dataflow graphs and which provides predictable steady state time-optimized performance. This simulator extends the ATAMM simulation capability from a heterogenous set of resources, or functional units, to a more general heterogenous architecture. Simulation test cases show that the simulator accurately executes the ATAMM rules for both a heterogenous architecture and a homogenous architecture, which is the special case for only one processor type. The simulator forms one tool in an ATAMM Integrated Environment which contains other tools for graph entry, graph modification for performance optimization, and playback of simulations for analysis.
Synthesis, characterization, and protein labeling of difunctional magnetic nanoparticles modified with thiazole orange dye

NASA Astrophysics Data System (ADS)

Fei, Xuening; Zhu, Huifang; Zhou, Jianguo; Yu, Lu

2014-03-01

A dual functional nanoparticle was designed and synthesized by encapsulating magnetic core inside silica particles and subsequently a thiazole orange (TO) dye derivative was modified on the surface of the nanoparticles. The obtained particles were characterized by Fourier transform infrared spectroscope, Uv-Vis spectrophotometer, fluorescence spectrophotometer, transmission electron microscope, dynamic light scattering, etc. The size of preliminary magnetic particles is ca. 7 nm, but after coating a silica layer and dye, the size of particles is increased to ca. 60 nm. The hydrodynamic diameter, water dispersibility, and zeta potential were also determined. The hydrodynamic diameter of particles with silica and dye is 65.2 and 70.5 nm, respectively, with positive zeta potential (25.1, 38.5 mV). Furthermore magnetic properties of the particles were measured and the experimental results suggested that it could meet the requirement of application as magnetic resonance imaging agent. Finally to verify the availability of the particles as fluorescent labeling, protein labeling experiment was performed using bovine serum albumin (BSA) protein and the results showed that the dual functional particle has higher affinity with BSA than TO molecule itself.

Pleiotrophin and its receptor protein tyrosine phosphatase beta/zeta as regulators of angiogenesis and cancer.

PubMed

Papadimitriou, Evangelia; Pantazaka, Evangelia; Castana, Penelope; Tsalios, Thomas; Polyzos, Alexandros; Beis, Dimitris

2016-12-01

Pleiotrophin (PTN) is a secreted heparin-binding growth factor that through its receptor protein tyrosine phosphatase beta/zeta (RPTPβ/ζ) has a significant regulatory effect on angiogenesis and cancer. PTN and RPTPβ/ζ are over-expressed in several types of human cancers and regulate important cancer cell functions in vitro and cancer growth in vivo. This review begins with a brief introduction of PTN and the regulation of its expression. PTN receptors are described with special emphasis on RPTPβ/ζ, which also interacts with and/or affects the function of other important targets for cancer therapy, such as vascular endothelial growth factor A, α ν β 3 and cell surface nucleolin. PTN biological activities related to angiogenesis and cancer are extensively discussed. Finally, up to date approaches of targeting PTN or RPTPβ/ζ for cancer treatment are presented. Insights into the regulatory role of PTN/RPTPβ/ζ on angiogenesis will be extremely beneficial for future development of alternative anti-angiogenic approaches in cancer therapy. Copyright Â© 2016 Elsevier B.V. All rights reserved.
Surface Complexation Modeling of Calcite Zeta Potential Measurement in Mixed Brines for Carbonate Wettability Characterization

NASA Astrophysics Data System (ADS)

Song, J.; Zeng, Y.; Biswal, S. L.; Hirasaki, G. J.

2017-12-01

We presents zeta potential measurements and surface complexation modeling (SCM) of synthetic calcite in various conditions. The systematic zeta potential measurement and the proposed SCM provide insight into the role of four potential determining cations (Mg2+, SO42- , Ca2+ and CO32-) and CO2 partial pressure in calcite surface charge formation and facilitate the revealing of calcite wettability alteration induced by brines with designed ionic composition ("smart water"). Brines with varying potential determining ions (PDI) concentration in two different CO2 partial pressure (PCO2) are investigated in experiments. Then, a double layer SCM is developed to model the zeta potential measurements. Moreover, we propose a definition for contribution of charged surface species and quantitatively analyze the variation of charged species contribution when changing brine composition. After showing our model can accurately predict calcite zeta potential in brines containing mixed PDIs, we apply it to predict zeta potential in ultra-low and pressurized CO2 environments for potential applications in carbonate enhanced oil recovery including miscible CO2 flooding and CO2 sequestration in carbonate reservoirs. Model prediction reveals that pure calcite surface will be positively charged in all investigated brines in pressurized CO2 environment (>1atm). Moreover, the sensitivity of calcite zeta potential to CO2 partial pressure in the various brine is found to be in the sequence of Na2CO3 > Na2SO4 > NaCl > MgCl2 > CaCl2 (Ionic strength=0.1M).
A graph-based approach for designing extensible pipelines

PubMed Central

2012-01-01

Background In bioinformatics, it is important to build extensible and low-maintenance systems that are able to deal with the new tools and data formats that are constantly being developed. The traditional and simplest implementation of pipelines involves hardcoding the execution steps into programs or scripts. This approach can lead to problems when a pipeline is expanding because the incorporation of new tools is often error prone and time consuming. Current approaches to pipeline development such as workflow management systems focus on analysis tasks that are systematically repeated without significant changes in their course of execution, such as genome annotation. However, more dynamism on the pipeline composition is necessary when each execution requires a different combination of steps. Results We propose a graph-based approach to implement extensible and low-maintenance pipelines that is suitable for pipeline applications with multiple functionalities that require different combinations of steps in each execution. Here pipelines are composed automatically by compiling a specialised set of tools on demand, depending on the functionality required, instead of specifying every sequence of tools in advance. We represent the connectivity of pipeline components with a directed graph in which components are the graph edges, their inputs and outputs are the graph nodes, and the paths through the graph are pipelines. To that end, we developed special data structures and a pipeline system algorithm. We demonstrate the applicability of our approach by implementing a format conversion pipeline for the fields of population genetics and genetic epidemiology, but our approach is also helpful in other fields where the use of multiple software is necessary to perform comprehensive analyses, such as gene expression and proteomics analyses. The project code, documentation and the Java executables are available under an open source license at http://code.google.com/p/dynamic-pipeline. The system has been tested on Linux and Windows platforms. Conclusions Our graph-based approach enables the automatic creation of pipelines by compiling a specialised set of tools on demand, depending on the functionality required. It also allows the implementation of extensible and low-maintenance pipelines and contributes towards consolidating openness and collaboration in bioinformatics systems. It is targeted at pipeline developers and is suited for implementing applications with sequential execution steps and combined functionalities. In the format conversion application, the automatic combination of conversion tools increased both the number of possible conversions available to the user and the extensibility of the system to allow for future updates with new file formats. PMID:22788675
The signed permutation group on Feynman graphs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Purkart, Julian, E-mail: purkart@physik.hu-berlin.de

2016-08-15

The Feynman rules assign to every graph an integral which can be written as a function of a scaling parameter L. Assuming L for the process under consideration is very small, so that contributions to the renormalization group are small, we can expand the integral and only consider the lowest orders in the scaling. The aim of this article is to determine specific combinations of graphs in a scalar quantum field theory that lead to a remarkable simplification of the first non-trivial term in the perturbation series. It will be seen that the result is independent of the renormalization schememore » and the scattering angles. To achieve that goal we will utilize the parametric representation of scalar Feynman integrals as well as the Hopf algebraic structure of the Feynman graphs under consideration. Moreover, we will present a formula which reduces the effort of determining the first-order term in the perturbation series for the specific combination of graphs to a minimum.« less
Graph-Based Semantic Web Service Composition for Healthcare Data Integration.

PubMed

Arch-Int, Ngamnij; Arch-Int, Somjit; Sonsilphong, Suphachoke; Wanchai, Paweena

2017-01-01

Within the numerous and heterogeneous web services offered through different sources, automatic web services composition is the most convenient method for building complex business processes that permit invocation of multiple existing atomic services. The current solutions in functional web services composition lack autonomous queries of semantic matches within the parameters of web services, which are necessary in the composition of large-scale related services. In this paper, we propose a graph-based Semantic Web Services composition system consisting of two subsystems: management time and run time. The management-time subsystem is responsible for dependency graph preparation in which a dependency graph of related services is generated automatically according to the proposed semantic matchmaking rules. The run-time subsystem is responsible for discovering the potential web services and nonredundant web services composition of a user's query using a graph-based searching algorithm. The proposed approach was applied to healthcare data integration in different health organizations and was evaluated according to two aspects: execution time measurement and correctness measurement.
Graph-Based Semantic Web Service Composition for Healthcare Data Integration

PubMed Central

2017-01-01

Within the numerous and heterogeneous web services offered through different sources, automatic web services composition is the most convenient method for building complex business processes that permit invocation of multiple existing atomic services. The current solutions in functional web services composition lack autonomous queries of semantic matches within the parameters of web services, which are necessary in the composition of large-scale related services. In this paper, we propose a graph-based Semantic Web Services composition system consisting of two subsystems: management time and run time. The management-time subsystem is responsible for dependency graph preparation in which a dependency graph of related services is generated automatically according to the proposed semantic matchmaking rules. The run-time subsystem is responsible for discovering the potential web services and nonredundant web services composition of a user's query using a graph-based searching algorithm. The proposed approach was applied to healthcare data integration in different health organizations and was evaluated according to two aspects: execution time measurement and correctness measurement. PMID:29065602
Graph Design via Convex Optimization: Online and Distributed Perspectives

NASA Astrophysics Data System (ADS)

Meng, De

Network and graph have long been natural abstraction of relations in a variety of applications, e.g. transportation, power system, social network, communication, electrical circuit, etc. As a large number of computation and optimization problems are naturally defined on graphs, graph structures not only enable important properties of these problems, but also leads to highly efficient distributed and online algorithms. For example, graph separability enables the parallelism for computation and operation as well as limits the size of local problems. More interestingly, graphs can be defined and constructed in order to take best advantage of those problem properties. This dissertation focuses on graph structure and design in newly proposed optimization problems, which establish a bridge between graph properties and optimization problem properties. We first study a new optimization problem called Geodesic Distance Maximization Problem (GDMP). Given a graph with fixed edge weights, finding the shortest path, also known as the geodesic, between two nodes is a well-studied network flow problem. We introduce the Geodesic Distance Maximization Problem (GDMP): the problem of finding the edge weights that maximize the length of the geodesic subject to convex constraints on the weights. We show that GDMP is a convex optimization problem for a wide class of flow costs, and provide a physical interpretation using the dual. We present applications of the GDMP in various fields, including optical lens design, network interdiction, and resource allocation in the control of forest fires. We develop an Alternating Direction Method of Multipliers (ADMM) by exploiting specific problem structures to solve large-scale GDMP, and demonstrate its effectiveness in numerical examples. We then turn our attention to distributed optimization on graph with only local communication. Distributed optimization arises in a variety of applications, e.g. distributed tracking and localization, estimation problems in sensor networks, multi-agent coordination. Distributed optimization aims to optimize a global objective function formed by summation of coupled local functions over a graph via only local communication and computation. We developed a weighted proximal ADMM for distributed optimization using graph structure. This fully distributed, single-loop algorithm allows simultaneous updates and can be viewed as a generalization of existing algorithms. More importantly, we achieve faster convergence by jointly designing graph weights and algorithm parameters. Finally, we propose a new problem on networks called Online Network Formation Problem: starting with a base graph and a set of candidate edges, at each round of the game, player one first chooses a candidate edge and reveals it to player two, then player two decides whether to accept it; player two can only accept limited number of edges and make online decisions with the goal to achieve the best properties of the synthesized network. The network properties considered include the number of spanning trees, algebraic connectivity and total effective resistance. These network formation games arise in a variety of cooperative multiagent systems. We propose a primal-dual algorithm framework for the general online network formation game, and analyze the algorithm performance by the competitive ratio and regret.
Survival time of the susceptible-infected-susceptible infection process on a graph.

PubMed

van de Bovenkamp, Ruud; Van Mieghem, Piet

2015-09-01

The survival time T is the longest time that a virus, a meme, or a failure can propagate in a network. Using the hitting time of the absorbing state in an uniformized embedded Markov chain of the continuous-time susceptible-infected-susceptible (SIS) Markov process, we derive an exact expression for the average survival time E[T] of a virus in the complete graph K_{N} and the star graph K_{1,N-1}. By using the survival time, instead of the average fraction of infected nodes, we propose a new method to approximate the SIS epidemic threshold τ_{c} that, at least for K_{N} and K_{1,N-1}, correctly scales with the number of nodes N and that is superior to the epidemic threshold τ_{c}^{(1)}=1/λ_{1} of the N-intertwined mean-field approximation, where λ_{1} is the spectral radius of the adjacency matrix of the graph G. Although this new approximation of the epidemic threshold offers a more intuitive understanding of the SIS process, it remains difficult to compare outbreaks in different graph types. For example, the survival in an arbitrary graph seems upper bounded by the complete graph and lower bounded by the star graph as a function of the normalized effective infection rate τ/τ_{c}^{(1)}. However, when the average fraction of infected nodes is used as a basis for comparison, the virus will survive in the star graph longer than in any other graph, making the star graph the worst-case graph instead of the complete graph. Finally, in non-Markovian SIS, the distribution of the spreading attempts over the infectious period of a node influences the survival time, even if the expected number of spreading attempts during an infectious period (the non-Markovian equivalent of the effective infection rate) is kept constant. Both early and late infection attempts lead to shorter survival times. Interestingly, just as in Markovian SIS, the survival times appear to be exponentially distributed, regardless of the infection and curing time distributions.
Effect of axial load on mode shapes and frequencies of beams

NASA Technical Reports Server (NTRS)

Shaker, F. J.

1975-01-01

An investigation of the effect of axial load on the natural frequencies and mode shapes of uniform beams and of a cantilevered beam with a concentrated mass at the tip is presented. Characteristic equations which yield the frequencies and mode shape functions for the various cases are given. The solutions to these equations are presented by a series of graphs so that frequency as a function of axial load can readily be determined. The effect of axial load on the mode shapes are also depicted by another series of graphs.
SAR-based change detection using hypothesis testing and Markov random field modelling

NASA Astrophysics Data System (ADS)

Cao, W.; Martinis, S.

2015-04-01

The objective of this study is to automatically detect changed areas caused by natural disasters from bi-temporal co-registered and calibrated TerraSAR-X data. The technique in this paper consists of two steps: Firstly, an automatic coarse detection step is applied based on a statistical hypothesis test for initializing the classification. The original analytical formula as proposed in the constant false alarm rate (CFAR) edge detector is reviewed and rewritten in a compact form of the incomplete beta function, which is a builtin routine in commercial scientific software such as MATLAB and IDL. Secondly, a post-classification step is introduced to optimize the noisy classification result in the previous step. Generally, an optimization problem can be formulated as a Markov random field (MRF) on which the quality of a classification is measured by an energy function. The optimal classification based on the MRF is related to the lowest energy value. Previous studies provide methods for the optimization problem using MRFs, such as the iterated conditional modes (ICM) algorithm. Recently, a novel algorithm was presented based on graph-cut theory. This method transforms a MRF to an equivalent graph and solves the optimization problem by a max-flow/min-cut algorithm on the graph. In this study this graph-cut algorithm is applied iteratively to improve the coarse classification. At each iteration the parameters of the energy function for the current classification are set by the logarithmic probability density function (PDF). The relevant parameters are estimated by the method of logarithmic cumulants (MoLC). Experiments are performed using two flood events in Germany and Australia in 2011 and a forest fire on La Palma in 2009 using pre- and post-event TerraSAR-X data. The results show convincing coarse classifications and considerable improvement by the graph-cut post-classification step.
Functional Organization of the Action Observation Network in Autism: A Graph Theory Approach

PubMed Central

Alaerts, Kaat; Geerlings, Franca; Herremans, Lynn; Swinnen, Stephan P.; Verhoeven, Judith; Sunaert, Stefan; Wenderoth, Nicole

2015-01-01

Background The ability to recognize, understand and interpret other’s actions and emotions has been linked to the mirror system or action-observation-network (AON). Although variations in these abilities are prevalent in the neuro-typical population, persons diagnosed with autism spectrum disorders (ASD) have deficits in the social domain and exhibit alterations in this neural network. Method Here, we examined functional network properties of the AON using graph theory measures and region-to-region functional connectivity analyses of resting-state fMRI-data from adolescents and young adults with ASD and typical controls (TC). Results Overall, our graph theory analyses provided convergent evidence that the network integrity of the AON is altered in ASD, and that reductions in network efficiency relate to reductions in overall network density (i.e., decreased overall connection strength). Compared to TC, individuals with ASD showed significant reductions in network efficiency and increased shortest path lengths and centrality. Importantly, when adjusting for overall differences in network density between ASD and TC groups, participants with ASD continued to display reductions in network integrity, suggesting that also network-level organizational properties of the AON are altered in ASD. Conclusion While differences in empirical connectivity contributed to reductions in network integrity, graph theoretical analyses provided indications that also changes in the high-level network organization reduced integrity of the AON. PMID:26317222
Visibility graph analysis on quarterly macroeconomic series of China based on complex network theory

NASA Astrophysics Data System (ADS)

Wang, Na; Li, Dong; Wang, Qiwen

2012-12-01

The visibility graph approach and complex network theory provide a new insight into time series analysis. The inheritance of the visibility graph from the original time series was further explored in the paper. We found that degree distributions of visibility graphs extracted from Pseudo Brownian Motion series obtained by the Frequency Domain algorithm exhibit exponential behaviors, in which the exponential exponent is a binomial function of the Hurst index inherited in the time series. Our simulations presented that the quantitative relations between the Hurst indexes and the exponents of degree distribution function are different for different series and the visibility graph inherits some important features of the original time series. Further, we convert some quarterly macroeconomic series including the growth rates of value-added of three industry series and the growth rates of Gross Domestic Product series of China to graphs by the visibility algorithm and explore the topological properties of graphs associated from the four macroeconomic series, namely, the degree distribution and correlations, the clustering coefficient, the average path length, and community structure. Based on complex network analysis we find degree distributions of associated networks from the growth rates of value-added of three industry series are almost exponential and the degree distributions of associated networks from the growth rates of GDP series are scale free. We also discussed the assortativity and disassortativity of the four associated networks as they are related to the evolutionary process of the original macroeconomic series. All the constructed networks have “small-world” features. The community structures of associated networks suggest dynamic changes of the original macroeconomic series. We also detected the relationship among government policy changes, community structures of associated networks and macroeconomic dynamics. We find great influences of government policies in China on the changes of dynamics of GDP and the three industries adjustment. The work in our paper provides a new way to understand the dynamics of economic development.
Constructing the L2-Graph for Robust Subspace Learning and Subspace Clustering.

PubMed

Peng, Xi; Yu, Zhiding; Yi, Zhang; Tang, Huajin

2017-04-01

Under the framework of graph-based learning, the key to robust subspace clustering and subspace learning is to obtain a good similarity graph that eliminates the effects of errors and retains only connections between the data points from the same subspace (i.e., intrasubspace data points). Recent works achieve good performance by modeling errors into their objective functions to remove the errors from the inputs. However, these approaches face the limitations that the structure of errors should be known prior and a complex convex problem must be solved. In this paper, we present a novel method to eliminate the effects of the errors from the projection space (representation) rather than from the input space. We first prove that l 1 -, l 2 -, l ∞ -, and nuclear-norm-based linear projection spaces share the property of intrasubspace projection dominance, i.e., the coefficients over intrasubspace data points are larger than those over intersubspace data points. Based on this property, we introduce a method to construct a sparse similarity graph, called L2-graph. The subspace clustering and subspace learning algorithms are developed upon L2-graph. We conduct comprehensive experiment on subspace learning, image clustering, and motion segmentation and consider several quantitative benchmarks classification/clustering accuracy, normalized mutual information, and running time. Results show that L2-graph outperforms many state-of-the-art methods in our experiments, including L1-graph, low rank representation (LRR), and latent LRR, least square regression, sparse subspace clustering, and locally linear representation.
Application of the zeta potential for stationary phase characterization in ion chromatography.

PubMed

Buszewski, Bogusław; Jaćkowska, Magdalena; Bocian, Szymon; Dziubakiewicz, Ewelina

2013-01-01

Two series of homemade stationary bonded phases for ion chromatography were investigated according to their zeta potential. One set of dendrimer anion exchanger was synthesized on the polymer support whereas the second material was prepared on the silica gel. The zeta potential data in water environment as well as buffered water solution were obtained. The influence of the length of anion-exchanger chains, the type of the support of the modified surface, and charge distribution on these data was investigated. Additionally, the zeta potential was correlated with retention factor of inorganic ions to describe their influence on the retention mechanism in ion chromatography. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Exactly solved models on planar graphs with vertices in {Z}^3

NASA Astrophysics Data System (ADS)

Kels, Andrew P.

2017-12-01

It is shown how exactly solved edge interaction models on the square lattice, may be extended onto more general planar graphs, with edges connecting a subset of next nearest neighbour vertices of {Z}3 . This is done by using local deformations of the square lattice, that arise through the use of the star-triangle relation. Similar to Baxter’s Z-invariance property, these local deformations leave the partition function invariant up to some simple factors coming from the star-triangle relation. The deformations used here extend the usual formulation of Z-invariance, by requiring the introduction of oriented rapidity lines which form directed closed paths in the rapidity graph of the model. The quasi-classical limit is also considered, in which case the deformations imply a classical Z-invariance property, as well as a related local closure relation, for the action functional of a system of classical discrete Laplace equations.
Graphical method to design multilayer phase retarders.

PubMed

Apfel, J H

1981-03-15

When multilayer reflectors are used at nonnormal incidence, the two planes of polarization generally have different phase shifts. This difference, known as phase retardance, depends on the multilayer design, the incidence angle, and the wavelength. Heretofore, the design of reflectors with specific phase retardance has been carried out by computer optimization except for the case of a single layer on a metal substrate. A graph of phase retardance D vs the average phase shift A as a function of layer thickness provides a means for visualization that is useful in reflector designs. A D-A graph predicts the phase properties of a reflector as a function of the index and thickness of an added layer. Graphs of phase retardance vs average phase for two different materials can be superposed to predict the composite performance of a multilayer reflector. This graphical technique is employed to design and analyze reflectors with specified phase retardance.
FPFH-based graph matching for 3D point cloud registration

NASA Astrophysics Data System (ADS)

Zhao, Jiapeng; Li, Chen; Tian, Lihua; Zhu, Jihua

2018-04-01

Correspondence detection is a vital step in point cloud registration and it can help getting a reliable initial alignment. In this paper, we put forward an advanced point feature-based graph matching algorithm to solve the initial alignment problem of rigid 3D point cloud registration with partial overlap. Specifically, Fast Point Feature Histograms are used to determine the initial possible correspondences firstly. Next, a new objective function is provided to make the graph matching more suitable for partially overlapping point cloud. The objective function is optimized by the simulated annealing algorithm for final group of correct correspondences. Finally, we present a novel set partitioning method which can transform the NP-hard optimization problem into a O(n3)-solvable one. Experiments on the Stanford and UWA public data sets indicates that our method can obtain better result in terms of both accuracy and time cost compared with other point cloud registration methods.
Generic strategies for chemical space exploration.

PubMed

Andersen, Jakob L; Flamm, Christoph; Merkle, Daniel; Stadler, Peter F

2014-01-01

The chemical universe of molecules reachable from a set of start compounds by iterative application of a finite number of reactions is usually so vast, that sophisticated and efficient exploration strategies are required to cope with the combinatorial complexity. A stringent analysis of (bio)chemical reaction networks, as approximations of these complex chemical spaces, forms the foundation for the understanding of functional relations in Chemistry and Biology. Graphs and graph rewriting are natural models for molecules and reactions. Borrowing the idea of partial evaluation from functional programming, we introduce partial applications of rewrite rules. A framework for the specification of exploration strategies in graph-rewriting systems is presented. Using key examples of complex reaction networks from carbohydrate chemistry we demonstrate the feasibility of this high-level strategy framework. While being designed for chemical applications, the framework can also be used to emulate higher-level transformation models such as illustrated in a small puzzle game.
Optimized Graph Learning Using Partial Tags and Multiple Features for Image and Video Annotation.

PubMed

Song, Jingkuan; Gao, Lianli; Nie, Feiping; Shen, Heng Tao; Yan, Yan; Sebe, Nicu

2016-11-01

In multimedia annotation, due to the time constraints and the tediousness of manual tagging, it is quite common to utilize both tagged and untagged data to improve the performance of supervised learning when only limited tagged training data are available. This is often done by adding a geometry-based regularization term in the objective function of a supervised learning model. In this case, a similarity graph is indispensable to exploit the geometrical relationships among the training data points, and the graph construction scheme essentially determines the performance of these graph-based learning algorithms. However, most of the existing works construct the graph empirically and are usually based on a single feature without using the label information. In this paper, we propose a semi-supervised annotation approach by learning an optimized graph (OGL) from multi-cues (i.e., partial tags and multiple features), which can more accurately embed the relationships among the data points. Since OGL is a transductive method and cannot deal with novel data points, we further extend our model to address the out-of-sample issue. Extensive experiments on image and video annotation show the consistent superiority of OGL over the state-of-the-art methods.
Distribution of diameters for Erdős-Rényi random graphs.

PubMed

Hartmann, A K; Mézard, M

2018-03-01

We study the distribution of diameters d of Erdős-Rényi random graphs with average connectivity c. The diameter d is the maximum among all the shortest distances between pairs of nodes in a graph and an important quantity for all dynamic processes taking place on graphs. Here we study the distribution P(d) numerically for various values of c, in the nonpercolating and percolating regimes. Using large-deviation techniques, we are able to reach small probabilities like 10^{-100} which allow us to obtain the distribution over basically the full range of the support, for graphs up to N=1000 nodes. For values c<1, our results are in good agreement with analytical results, proving the reliability of our numerical approach. For c>1 the distribution is more complex and no complete analytical results are available. For this parameter range, P(d) exhibits an inflection point, which we found to be related to a structural change of the graphs. For all values of c, we determined the finite-size rate function Φ(d/N) and were able to extrapolate numerically to N→∞, indicating that the large-deviation principle holds.

Distribution of diameters for Erdős-Rényi random graphs

NASA Astrophysics Data System (ADS)

Hartmann, A. K.; Mézard, M.

2018-03-01

We study the distribution of diameters d of Erdős-Rényi random graphs with average connectivity c . The diameter d is the maximum among all the shortest distances between pairs of nodes in a graph and an important quantity for all dynamic processes taking place on graphs. Here we study the distribution P (d ) numerically for various values of c , in the nonpercolating and percolating regimes. Using large-deviation techniques, we are able to reach small probabilities like 10-100 which allow us to obtain the distribution over basically the full range of the support, for graphs up to N =1000 nodes. For values c <1 , our results are in good agreement with analytical results, proving the reliability of our numerical approach. For c >1 the distribution is more complex and no complete analytical results are available. For this parameter range, P (d ) exhibits an inflection point, which we found to be related to a structural change of the graphs. For all values of c , we determined the finite-size rate function Φ (d /N ) and were able to extrapolate numerically to N →∞ , indicating that the large-deviation principle holds.
Influence of molecular weight and pH on adsorption of chitosan at the surface of large and giant vesicles.

PubMed

Quemeneur, Francois; Rinaudo, Marguerite; Pépin-Donat, Brigitte

2008-01-01

This paper describes the mechanisms of adsorption of chitosan, a positively charged polyelectrolyte, on the DOPC lipid membrane of large and giant unilamellar vesicles (respectively, LUVs and GUVs). We observe that the variation of the zeta potential of LUVs as a function of chitosan concentration is independent on the chitosan molecular weight (Mw). This result is interpreted in terms of electrostatic interactions, which induce a flat adsorption of the chitosan on the surface of the membrane. The role of electrostatic interactions is further studied by observing the variation of the zeta potential as a function of the chitosan concentration for two different charge densities tuned by the pH. Results show a stronger chitosan-membrane affinity at pH 6 (lipids are negatively charged, and 40% chitosan amino groups are protonated) than at pH 3.4 (100% of protonated amino groups but zwitterionic lipids are positively charged) which confirms that adsorption is of electrostatic origin. Then, we investigate the stability of decorated LUVs and GUVs in a large range of pH (6.0 < pH < 12.0) in order to complete a previous study made in acidic conditions [Quemeneur et al. Biomacromolecules 2007, 8, 2512-2519]. A comparative study of the variation of the zeta potential as a function of the pH (2.0 < pH < 12.0) reveals a difference in behavior between naked and chitosan-decorated LUVs. This result is further confirmed by a comparative observation by optical microscopy of naked and chitosan-decorated GUVs in basic conditions (6.0 < pH < 12.0): at pH > 10.0, in the absence of chitosan, the vesicles present complex shapes, contrary to the chitosan-decorated vesicles which remain spherical, confirming thus that chitosan remains adsorbed on vesicles in basic conditions up to pH = 12.0. These results, in addition with our previous data, show that the chitosan-decorated vesicles are stable over a very broad range of pH (2.0 < pH < 12.0), which holds promise for their in vivo applications. Finally, the quantification of the chitosan adsorption on a LUV membrane is performed by zeta potential and fluorescence measurements. The fraction of membrane surface covered by chitosan is estimated to be lower than 40 %, which corresponds to the formation of a flat layer of chitosan on the membrane surface on an electrostatic basis.
Alphabet Soup

ERIC Educational Resources Information Center

Rebholz, Joachim A.

2017-01-01

Graphing functions is an important topic in algebra and precalculus high school courses. The functions that are usually discussed include polynomials, rational, exponential, and trigonometric functions along with their inverses. These functions can be used to teach different aspects of function theory: domain, range, monotonicity, inverse…
Predicting activity approach based on new atoms similarity kernel function.

PubMed

Abu El-Atta, Ahmed H; Moussa, M I; Hassanien, Aboul Ella

2015-07-01

Drug design is a high cost and long term process. To reduce time and costs for drugs discoveries, new techniques are needed. Chemoinformatics field implements the informational techniques and computer science like machine learning and graph theory to discover the chemical compounds properties, such as toxicity or biological activity. This is done through analyzing their molecular structure (molecular graph). To overcome this problem there is an increasing need for algorithms to analyze and classify graph data to predict the activity of molecules. Kernels methods provide a powerful framework which combines machine learning with graph theory techniques. These kernels methods have led to impressive performance results in many several chemoinformatics problems like biological activity prediction. This paper presents a new approach based on kernel functions to solve activity prediction problem for chemical compounds. First we encode all atoms depending on their neighbors then we use these codes to find a relationship between those atoms each other. Then we use relation between different atoms to find similarity between chemical compounds. The proposed approach was compared with many other classification methods and the results show competitive accuracy with these methods. Copyright © 2015 Elsevier Inc. All rights reserved.
Efficient, graph-based white matter connectivity from orientation distribution functions via multi-directional graph propagation

NASA Astrophysics Data System (ADS)

Boucharin, Alexis; Oguz, Ipek; Vachet, Clement; Shi, Yundi; Sanchez, Mar; Styner, Martin

2011-03-01

The use of regional connectivity measurements derived from diffusion imaging datasets has become of considerable interest in the neuroimaging community in order to better understand cortical and subcortical white matter connectivity. Current connectivity assessment methods are based on streamline fiber tractography, usually applied in a Monte-Carlo fashion. In this work we present a novel, graph-based method that performs a fully deterministic, efficient and stable connectivity computation. The method handles crossing fibers and deals well with multiple seed regions. The computation is based on a multi-directional graph propagation method applied to sampled orientation distribution function (ODF), which can be computed directly from the original diffusion imaging data. We show early results of our method on synthetic and real datasets. The results illustrate the potential of our method towards subjectspecific connectivity measurements that are performed in an efficient, stable and reproducible manner. Such individual connectivity measurements would be well suited for application in population studies of neuropathology, such as Autism, Huntington's Disease, Multiple Sclerosis or leukodystrophies. The proposed method is generic and could easily be applied to non-diffusion data as long as local directional data can be derived.
Understanding regulatory networks requires more than computing a multitude of graph statistics. Comment on "Drivers of structural features in gene regulatory networks: From biophysical constraints to biological function" by O.C. Martin et al.

NASA Astrophysics Data System (ADS)

Tkačik, Gašper

2016-07-01

The article by O. Martin and colleagues provides a much needed systematic review of a body of work that relates the topological structure of genetic regulatory networks to evolutionary selection for function. This connection is very important. Using the current wealth of genomic data, statistical features of regulatory networks (e.g., degree distributions, motif composition, etc.) can be quantified rather easily; it is, however, often unclear how to interpret the results. On a graph theoretic level the statistical significance of the results can be evaluated by comparing observed graphs to ;randomized; ones (bravely ignoring the issue of how precisely to randomize!) and comparing the frequency of appearance of a particular network structure relative to a randomized null expectation. While this is a convenient operational test for statistical significance, its biological meaning is questionable. In contrast, an in-silico genotype-to-phenotype model makes explicit the assumptions about the network function, and thus clearly defines the expected network structures that can be compared to the case of no selection for function and, ultimately, to data.
Fuzzy-PI-based centralised control of semi-isolated FP-SEPIC/ZETA BDC in a PV/battery hybrid system

NASA Astrophysics Data System (ADS)

Mahendran, Venmathi; Ramabadran, Ramaprabha

2016-11-01

Multiport converters with centralised controller have been most commonly used in stand-alone photovoltaic (PV)/battery hybrid system to supply the load smoothly without any disturbances. This study presents the performance analysis of four-port SEPIC/ZETA bidirectional converter (FP-SEPIC/ZETA BDC) using various types of centralised control schemes like Fuzzy tuned proportional integral controller (Fuzzy-PI), fuzzy logic controller (FLC) and conventional proportional integral (PI) controller. The proposed FP-SEPIC/ZETA BDC with various control strategy is derived for simultaneous power management of a PV source using distributed maximum power point tracking (DMPPT) algorithm, a rechargeable battery, and a load by means of centralised controller. The steady state and the dynamic response of the FP-SEPIC/ZETA BDC are analysed using three different types of controllers under line and load regulation. The Fuzzy-PI-based control scheme improves the dynamic response of the system when compared with the FLC and the conventional PI controller. The power balance between the ports is achieved by pseudorandom carrier modulation scheme. The response of the FP-SEPIC/ZETA BDC is also validated experimentally using hardware prototype model of 500 W system. The effectiveness of the control strategy is validated using simulation and experimental results.
Optimizing the physical-chemical properties of carbon nanotubes (CNT) and graphene nanoplatelets (GNP) on Cu(II) adsorption.

PubMed

Rosenzweig, Shirley; Sorial, George A; Sahle-Demessie, Endalkachew; McAvoy, Drew C

2014-08-30

Systematic experiments of copper adsorption on 10 different commercially available nanomaterials were studied for the influence of physical-chemical properties and their interactions. Design of experiment and response surface methodology was used to develop a polynomial model to predict maximum copper adsorption (initial concentration, Co=10mg/L) per mass of nanomaterial, qe, using multivariable regression and maximum R-square criterion. The best subsets of properties to predict qe in order of significant contribution to the model were: bulk density, ID, mesopore volume, tube length, pore size, zeta-charge, specific surface area and OD. The highest experimental qe observed was for an alcohol-functionalized MWCNT (16.7mg/g) with relative high bulk density (0.48g/cm(3)), ID (2-5nm), 10-30μm long and OD<8nm. Graphene nanoplatelets (GNP) showed poor adsorptive capacity associated to stacked-nanoplatelets, but good colloidal stability due to high functionalized surface. Good adsorption results for pristine SWCNT indicated that tubes with small diameter were more associated with good adsorption than functionalized surface. XPS and ICP analysis explored surface chemistry and purity, but pHpzc and zeta-charge were ultimately applied to indicate the degree of functionalization. Optimum CNT were identified in the scatter plot, but actual manufacturing processes introduced size and shape variations which interfered with final property results. Copyright © 2014 Elsevier B.V. All rights reserved.
Two-point correlation function for Dirichlet L-functions

NASA Astrophysics Data System (ADS)

Bogomolny, E.; Keating, J. P.

2013-03-01

The two-point correlation function for the zeros of Dirichlet L-functions at a height E on the critical line is calculated heuristically using a generalization of the Hardy-Littlewood conjecture for pairs of primes in arithmetic progression. The result matches the conjectured random-matrix form in the limit as E → ∞ and, importantly, includes finite-E corrections. These finite-E corrections differ from those in the case of the Riemann zeta-function, obtained in Bogomolny and Keating (1996 Phys. Rev. Lett. 77 1472), by certain finite products of primes which divide the modulus of the primitive character used to construct the L-function in question.
Zeta potential in oil-brine-sandstone system and its role in oil recovery during controlled salinity waterflooding

NASA Astrophysics Data System (ADS)

Li, S.; Jackson, M.

2017-12-01

Wettability alteration is widely recognised as a primary role in improved oil recovery (IOR) during controlled salinity waterflooding (CSW) by modifying brine composition. The change of wettability of core sample depends on adsorption of polar oil compounds into the mineral surface which influences its surface charge density and zeta potential. It has been proved that zeta potentials can be useful to quantify the wettability and incremental oil recovery in natural carbonates. However, the study of zeta potential in oil-brine-sandstone system has not investigated yet. In this experimental study, the zeta potential is used to examine the controlled salinity effects on IOR in nature sandstone (Doddington) aged with two types of crude oils (Oil T and Oil D) over 4 weeks at 80 °C. Results show that the zeta potential measured in the Oil T-brine-sandstone system following primary waterflooding decreases compared to that in fully water saturation, which is consistent with the negative oil found in carbonates study, and IOR response during secondary waterflooding using diluted seawater was observed. In the case of negative oil, the injected low salinity brine induces a more repulsive electrostatic force between the mineral-brine interface and oil-brine interface, which results in an increase disjoining pressure and alters the rock surface to be more water-wet. For Oil D with a positive oil-brine interface, the zeta potential becomes more positive compared to that under single phase condition. The conventional waterflooding fails to observe the IOR in Oil D-brine-sandstone system due to a less repulsive electrostatic force built up between the two interfaces. After switching the injection brine from low salinity brine to formation brine, the IOR was observed. Measured zeta potentials shed some light on the mechanism of wettability alteration in the oil-brine-sandstone system and oil recovery during CSW.
Differential interaction and aggregation of 3-repeat and 4-repeat tau isoforms with 14-3-3{zeta} protein

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sadik, Golam; Tanaka, Toshihisa, E-mail: tanaka@psy.med.osaka-u.ac.jp; Kato, Kiyoko

2009-05-22

Tau isoforms, 3-repeat (3R) and 4-repeat tau (4R), are differentially involved in neuronal development and in several tauopathies. 14-3-3 protein binds to tau and 14-3-3/tau association has been found both in the development and in tauopathies. To understand the role of 14-3-3 in the differential regulation of tau isoforms, we have performed studies on the interaction and aggregation of 3R-tau and 4R-tau, either phosphorylated or unphosphorylated, with 14-3-3{zeta}. We show by surface plasmon resonance studies that the interaction between unphosphorylated 3R-tau and 14-3-3{zeta} is {approx}3-folds higher than that between unphosphorylated 4R-tau and 14-3-3{zeta}. Phosphorylation of tau by protein kinase Amore » (PKA) increases the affinity of both 3R- and 4R-tau for 14-3-3{zeta} to a similar level. An in vitro aggregation assay employing both transmission electron microscopy and fluorescence spectroscopy revealed the aggregation of unphosphorylated 4R-tau to be significantly higher than that of unphosphorylated 3R-tau following the induction of 14-3-3{zeta}. The filaments formed from 3R- and 4R-tau were almost similar in morphology. In contrast, the aggregation of both 3R- and 4R-tau was reduced to a similar low level after phosphorylation with PKA. Taken together, these results suggest that 14-3-3{zeta} exhibits a similar role for tau isoforms after PKA-phosphorylation, but a differential role for unphosphorylated tau. The significant aggregation of 4R-tau by 14-3-3{zeta} suggests that 14-3-3 may act as an inducer in the generation of 4R-tau-predominant neurofibrillary tangles in tauopathies.« less
Properties of Riesz fractional derivatives for Korteweg-de Vries solitons

NASA Astrophysics Data System (ADS)

Varlamov, Vladimir

2010-12-01

Riesz fractional derivatives are defined as fractional powers of the Laplacian, D α = (-Δ) α/2 for {α in mathbb{R}}. For the soliton solution of the Korteweg-de Vries equation, u 0( X) with X = x - 4 t, these derivatives, u α ( X) = D α u 0( X), and their Hilbert transforms, v α ( X) = - HD α u 0( X), can be expressed in terms of the full range Hurwitz Zeta functions ζ+( s, a) and ζ-( s, a), respectively. New properties are established for u α ( X) and v α ( X). It is proved that the functions w α ( X) = u α ( X) + iv α ( X) with α > -1 are solutions of the differential equation -fracd{dX}left(P_{α}(X)dw/dXright)+Q_{α}(X)w = λρ_{α}(X)w,qquad X in mathbb{R}, for λ = 1. Here P α ( X), ρ α ( X) > 0 and Q α ( X) is real. The Wronskian W[ u α , v α ] is proved to be positive for all α > -1 and {X in mathbb{R}}. An estimate is given of the number of zeros of u α ( X) and v α ( X) on any finite interval. The fact that W[ u α , v α ] > 0 leads to a new inequality for the Hurwitz Zeta functions.
Neuro-symbolic representation learning on biological knowledge graphs.

PubMed

Alshahrani, Mona; Khan, Mohammad Asif; Maddouri, Omar; Kinjo, Akira R; Queralt-Rosinach, Núria; Hoehndorf, Robert

2017-09-01

Biological data and knowledge bases increasingly rely on Semantic Web technologies and the use of knowledge graphs for data integration, retrieval and federated queries. In the past years, feature learning methods that are applicable to graph-structured data are becoming available, but have not yet widely been applied and evaluated on structured biological knowledge. Results: We develop a novel method for feature learning on biological knowledge graphs. Our method combines symbolic methods, in particular knowledge representation using symbolic logic and automated reasoning, with neural networks to generate embeddings of nodes that encode for related information within knowledge graphs. Through the use of symbolic logic, these embeddings contain both explicit and implicit information. We apply these embeddings to the prediction of edges in the knowledge graph representing problems of function prediction, finding candidate genes of diseases, protein-protein interactions, or drug target relations, and demonstrate performance that matches and sometimes outperforms traditional approaches based on manually crafted features. Our method can be applied to any biological knowledge graph, and will thereby open up the increasing amount of Semantic Web based knowledge bases in biology to use in machine learning and data analytics. https://github.com/bio-ontology-research-group/walking-rdf-and-owl. robert.hoehndorf@kaust.edu.sa. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.
Linear game non-contextuality and Bell inequalities—a graph-theoretic approach

NASA Astrophysics Data System (ADS)

Rosicka, M.; Ramanathan, R.; Gnaciński, P.; Horodecki, K.; Horodecki, M.; Horodecki, P.; Severini, S.

2016-04-01

We study the classical and quantum values of a class of one- and two-party unique games, that generalizes the well-known XOR games to the case of non-binary outcomes. In the bipartite case the generalized XOR (XOR-d) games we study are a subclass of the well-known linear games. We introduce a ‘constraint graph’ associated to such a game, with the constraints defining the game represented by an edge-coloring of the graph. We use the graph-theoretic characterization to relate the task of finding equivalent games to the notion of signed graphs and switching equivalence from graph theory. We relate the problem of computing the classical value of single-party anti-correlation XOR games to finding the edge bipartization number of a graph, which is known to be MaxSNP hard, and connect the computation of the classical value of XOR-d games to the identification of specific cycles in the graph. We construct an orthogonality graph of the game from the constraint graph and study its Lovász theta number as a general upper bound on the quantum value even in the case of single-party contextual XOR-d games. XOR-d games possess appealing properties for use in device-independent applications such as randomness of the local correlated outcomes in the optimal quantum strategy. We study the possibility of obtaining quantum algebraic violation of these games, and show that no finite XOR-d game possesses the property of pseudo-telepathy leaving the frequently used chained Bell inequalities as the natural candidates for such applications. We also show this lack of pseudo-telepathy for multi-party XOR-type inequalities involving two-body correlation functions.
Chlorine adsorption on the InAs (001) surface

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bakulin, A. V.; Eremeev, S. V.; Tereshchenko, O. E.

2011-01-15

Chlorine adsorption on the In-stabilized InAs(001) surface with {zeta}-(4 Multiplication-Sign 2) and {beta}3 Prime -(4 Multiplication-Sign 2) reconstructions and on the Ga-stabilized GaAs (001)-{zeta}-(4 Multiplication-Sign 2) surface has been studied within the electron density functional theory. The equilibrium structural parameters of these reconstructions, surface atom positions, bond lengths in dimers, and their changes upon chlorine adsorption are determined. The electronic characteristics of the clean surface and the surface with adsorbed chlorine are calculated. It is shown that the most energetically favorable positions for chlorine adsorption are top positions over dimerized indium or gallium atoms. The mechanism of chlorine binding withmore » In(Ga)-stabilized surface is explained. The interaction of chlorine atoms with dimerized surface atoms weakens surface atom bonds and controls the initial stage of surface etching.« less
Adsorption of polyethyleneimine and polymethacrylic acid onto synthesized hematite.

PubMed

Chibowski, S; Patkowski, J; Grzadka, E

2009-01-01

An influence of different functional groups of polymer, its molecular weight, polydispersity ratio (M(w)/M(n)) and presence of impurities on its adsorption in different pH values (3, 6 and 9) onto synthesized hematite (Fe(2)O(3)) was measured. A structure of adsorbed macromolecules of PMA and PEI was obtained according to S-F theory. Two polymers were used: polymethacrylic acid (PMA) of 6500 and 75,100 molecular weight as well as polyethyleneimine (PEI) 25,000 commercial and fractionated. Electrokinetic properties of the interface oxide-polymer solution (surface charge density and zeta potential) were also measured as well as adsorption layer thicknesses (with use of viscosimetric measurements). Obtained data show, that all above-mentioned factors do influence not only the adsorption process itself but also a surface charge, zeta potential and structure of adsorbed polymer layers on polymer/hematite interface.
Fabrication of hydroxyapatite ceramics with controlled pore characteristics by slip casting.

PubMed

Yao, Xiumin; Tan, Shouhong; Jiang, Dongliang

2005-02-01

Porous hydroxyapatite (HAp) ceramics with controlled pore characteristics were fabricated using slip casting method by mixing PMMA with HAp powder. The optimum conditions of HAp slip for slip casting was achieved by employing various experimental techniques, zeta potential and sedimentation, as a function of pH of the slips in the pH range of 4-12. HAp suspensions displayed an absolute maximum in zeta potential values and a minimum in sedimentation height at pH 11.5. The optimal amount of dispersant for the HAp suspensions was found at 1.0 wt% according to the viscosity of 25 vol% HAp slurry. The rheological behaviour of HAp slurry displays a shear-thinning behavior without thixotropy, which is needed in slip casting processing. The pore characteristics of sintered porous hydroxyapatite bioceramics can be controlled by added PMMA particle size and volume. The obtained ceramics exhibit higher strength than those obtained by dry pressing.
Multi-phase simultaneous segmentation of tumor in lung 4D-CT data with context information.

PubMed

Shen, Zhengwen; Wang, Huafeng; Xi, Weiwen; Deng, Xiaogang; Chen, Jin; Zhang, Yu

2017-01-01

Lung 4D computed tomography (4D-CT) plays an important role in high-precision radiotherapy because it characterizes respiratory motion, which is crucial for accurate target definition. However, the manual segmentation of a lung tumor is a heavy workload for doctors because of the large number of lung 4D-CT data slices. Meanwhile, tumor segmentation is still a notoriously challenging problem in computer-aided diagnosis. In this paper, we propose a new method based on an improved graph cut algorithm with context information constraint to find a convenient and robust approach of lung 4D-CT tumor segmentation. We combine all phases of the lung 4D-CT into a global graph, and construct a global energy function accordingly. The sub-graph is first constructed for each phase. A context cost term is enforced to achieve segmentation results in every phase by adding a context constraint between neighboring phases. A global energy function is finally constructed by combining all cost terms. The optimization is achieved by solving a max-flow/min-cut problem, which leads to simultaneous and robust segmentation of the tumor in all the lung 4D-CT phases. The effectiveness of our approach is validated through experiments on 10 different lung 4D-CT cases. The comparison with the graph cut without context constraint, the level set method and the graph cut with star shape prior demonstrates that the proposed method obtains more accurate and robust segmentation results.
Comparing genomes to computer operating systems in terms of the topology and evolution of their regulatory control networks

PubMed Central

Yan, Koon-Kiu; Fang, Gang; Bhardwaj, Nitin; Alexander, Roger P.; Gerstein, Mark

2010-01-01

The genome has often been called the operating system (OS) for a living organism. A computer OS is described by a regulatory control network termed the call graph, which is analogous to the transcriptional regulatory network in a cell. To apply our firsthand knowledge of the architecture of software systems to understand cellular design principles, we present a comparison between the transcriptional regulatory network of a well-studied bacterium (Escherichia coli) and the call graph of a canonical OS (Linux) in terms of topology and evolution. We show that both networks have a fundamentally hierarchical layout, but there is a key difference: The transcriptional regulatory network possesses a few global regulators at the top and many targets at the bottom; conversely, the call graph has many regulators controlling a small set of generic functions. This top-heavy organization leads to highly overlapping functional modules in the call graph, in contrast to the relatively independent modules in the regulatory network. We further develop a way to measure evolutionary rates comparably between the two networks and explain this difference in terms of network evolution. The process of biological evolution via random mutation and subsequent selection tightly constrains the evolution of regulatory network hubs. The call graph, however, exhibits rapid evolution of its highly connected generic components, made possible by designers’ continual fine-tuning. These findings stem from the design principles of the two systems: robustness for biological systems and cost effectiveness (reuse) for software systems. PMID:20439753
Complementary Network-Based Approaches for Exploring Genetic Structure and Functional Connectivity in Two Vulnerable, Endemic Ground Squirrels

PubMed Central

Zero, Victoria H.; Barocas, Adi; Jochimsen, Denim M.; Pelletier, Agnès; Giroux-Bougard, Xavier; Trumbo, Daryl R.; Castillo, Jessica A.; Evans Mack, Diane; Linnell, Mark A.; Pigg, Rachel M.; Hoisington-Lopez, Jessica; Spear, Stephen F.; Murphy, Melanie A.; Waits, Lisette P.

2017-01-01

The persistence of small populations is influenced by genetic structure and functional connectivity. We used two network-based approaches to understand the persistence of the northern Idaho ground squirrel (Urocitellus brunneus) and the southern Idaho ground squirrel (U. endemicus), two congeners of conservation concern. These graph theoretic approaches are conventionally applied to social or transportation networks, but here are used to study population persistence and connectivity. Population graph analyses revealed that local extinction rapidly reduced connectivity for the southern species, while connectivity for the northern species could be maintained following local extinction. Results from gravity models complemented those of population graph analyses, and indicated that potential vegetation productivity and topography drove connectivity in the northern species. For the southern species, development (roads) and small-scale topography reduced connectivity, while greater potential vegetation productivity increased connectivity. Taken together, the results of the two network-based methods (population graph analyses and gravity models) suggest the need for increased conservation action for the southern species, and that management efforts have been effective at maintaining habitat quality throughout the current range of the northern species. To prevent further declines, we encourage the continuation of management efforts for the northern species, whereas conservation of the southern species requires active management and additional measures to curtail habitat fragmentation. Our combination of population graph analyses and gravity models can inform conservation strategies of other species exhibiting patchy distributions. PMID:28659969

Comparing genomes to computer operating systems in terms of the topology and evolution of their regulatory control networks.

PubMed

Yan, Koon-Kiu; Fang, Gang; Bhardwaj, Nitin; Alexander, Roger P; Gerstein, Mark

2010-05-18

The genome has often been called the operating system (OS) for a living organism. A computer OS is described by a regulatory control network termed the call graph, which is analogous to the transcriptional regulatory network in a cell. To apply our firsthand knowledge of the architecture of software systems to understand cellular design principles, we present a comparison between the transcriptional regulatory network of a well-studied bacterium (Escherichia coli) and the call graph of a canonical OS (Linux) in terms of topology and evolution. We show that both networks have a fundamentally hierarchical layout, but there is a key difference: The transcriptional regulatory network possesses a few global regulators at the top and many targets at the bottom; conversely, the call graph has many regulators controlling a small set of generic functions. This top-heavy organization leads to highly overlapping functional modules in the call graph, in contrast to the relatively independent modules in the regulatory network. We further develop a way to measure evolutionary rates comparably between the two networks and explain this difference in terms of network evolution. The process of biological evolution via random mutation and subsequent selection tightly constrains the evolution of regulatory network hubs. The call graph, however, exhibits rapid evolution of its highly connected generic components, made possible by designers' continual fine-tuning. These findings stem from the design principles of the two systems: robustness for biological systems and cost effectiveness (reuse) for software systems.
Complementary Network-Based Approaches for Exploring Genetic Structure and Functional Connectivity in Two Vulnerable, Endemic Ground Squirrels.

PubMed

Zero, Victoria H; Barocas, Adi; Jochimsen, Denim M; Pelletier, Agnès; Giroux-Bougard, Xavier; Trumbo, Daryl R; Castillo, Jessica A; Evans Mack, Diane; Linnell, Mark A; Pigg, Rachel M; Hoisington-Lopez, Jessica; Spear, Stephen F; Murphy, Melanie A; Waits, Lisette P

2017-01-01

The persistence of small populations is influenced by genetic structure and functional connectivity. We used two network-based approaches to understand the persistence of the northern Idaho ground squirrel ( Urocitellus brunneus) and the southern Idaho ground squirrel ( U. endemicus ), two congeners of conservation concern. These graph theoretic approaches are conventionally applied to social or transportation networks, but here are used to study population persistence and connectivity. Population graph analyses revealed that local extinction rapidly reduced connectivity for the southern species, while connectivity for the northern species could be maintained following local extinction. Results from gravity models complemented those of population graph analyses, and indicated that potential vegetation productivity and topography drove connectivity in the northern species. For the southern species, development (roads) and small-scale topography reduced connectivity, while greater potential vegetation productivity increased connectivity. Taken together, the results of the two network-based methods (population graph analyses and gravity models) suggest the need for increased conservation action for the southern species, and that management efforts have been effective at maintaining habitat quality throughout the current range of the northern species. To prevent further declines, we encourage the continuation of management efforts for the northern species, whereas conservation of the southern species requires active management and additional measures to curtail habitat fragmentation. Our combination of population graph analyses and gravity models can inform conservation strategies of other species exhibiting patchy distributions.
Properties of heuristic search strategies

NASA Technical Reports Server (NTRS)

Vanderbrug, G. J.

1973-01-01

A directed graph is used to model the search space of a state space representation with single input operators, an AND/OR is used for problem reduction representations, and a theorem proving graph is used for state space representations with multiple input operators. These three graph models and heuristic strategies for searching them are surveyed. The completeness, admissibility, and optimality properties of search strategies which use the evaluation function f = (1 - omega)g = omega(h) are presented and interpreted using a representation of the search process in the plane. The use of multiple output operators to imply dependent successors, and thus obtain a formalism which includes all three types of representations, is discussed.
jSquid: a Java applet for graphical on-line network exploration.

PubMed

Klammer, Martin; Roopra, Sanjit; Sonnhammer, Erik L L

2008-06-15

jSquid is a graph visualization tool for exploring graphs from protein-protein interaction or functional coupling networks. The tool was designed for the FunCoup web site, but can be used for any similar network exploring purpose. The program offers various visualization and graph manipulation techniques to increase the utility for the user. jSquid is available for direct usage and download at http://jSquid.sbc.su.se including source code under the GPLv3 license, and input examples. It requires Java version 5 or higher to run properly. erik.sonnhammer@sbc.su.se Supplementary data are available at Bioinformatics online.
The Packing Property

DTIC Science & Technology

2000-11-01

Discrete Math . 115, 141-152. [7] Edmonds J., Giles R. (1977) A Min-Max relation for submodular functions on graphs, Annals of Discrete Math . 1, 185...projective planes, handwritten man- uscript, published: (1990) Polyhedral Combinatorics (W. Cook, P.D. Seymour eds.), DIMACS Series in Discrete Math . and...Theoretical Computer Science 1, 101-105. [11] Lovasz L. (1972) Normal hypergraphs and the perfect graph conjecture, Discrete Math . 2, 253-267. [12
Finding Multiple Internal Rates of Return for a Project with Non-Conventional Cash Flows: Utilizing Popular Financial/Graphing Calculators and Spreadsheet Software

ERIC Educational Resources Information Center

Chen, Jeng-Hong

2008-01-01

This study demonstrates that a popular graphing calculator among students, TI-83 Plus, has a powerful function to draw the NPV profile and find the accurate multiple IRRs for a project with non-conventional cash flows. However, finance textbooks or related supplementary materials do not provide students instructions for this part. The detailed…
Dissolving variables in connectionist combinatory logic

NASA Technical Reports Server (NTRS)

Barnden, John; Srinivas, Kankanahalli

1990-01-01

A connectionist system which can represent and execute combinator expressions to elegantly solve the variable binding problem in connectionist networks is presented. This system is a graph reduction machine utilizing graph representations and traversal mechanisms similar to ones described in the BoltzCONS system of Touretzky (1986). It is shown that, as combinators eliminate variables by introducing special functions, these functions can be connectionistically implemented without reintroducing variable binding. This approach 'dissolves' an important part of the variable binding problem, in that a connectionist system still has to manipulate complex data structures, but those structures and their manipulations are rendered more uniform.
Hierarchical graphs for better annotations of rule-based models of biochemical systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hu, Bin; Hlavacek, William

2009-01-01

In the graph-based formalism of the BioNetGen language (BNGL), graphs are used to represent molecules, with a colored vertex representing a component of a molecule, a vertex label representing the internal state of a component, and an edge representing a bond between components. Components of a molecule share the same color. Furthermore, graph-rewriting rules are used to represent molecular interactions, with a rule that specifies addition (removal) of an edge representing a class of association (dissociation) reactions and with a rule that specifies a change of vertex label representing a class of reactions that affect the internal state of amore » molecular component. A set of rules comprises a mathematical/computational model that can be used to determine, through various means, the system-level dynamics of molecular interactions in a biochemical system. Here, for purposes of model annotation, we propose an extension of BNGL that involves the use of hierarchical graphs to represent (1) relationships among components and subcomponents of molecules and (2) relationships among classes of reactions defined by rules. We illustrate how hierarchical graphs can be used to naturally document the structural organization of the functional components and subcomponents of two proteins: the protein tyrosine kinase Lck and the T cell receptor (TCR)/CD3 complex. Likewise, we illustrate how hierarchical graphs can be used to document the similarity of two related rules for kinase-catalyzed phosphorylation of a protein substrate. We also demonstrate how a hierarchical graph representing a protein can be encoded in an XML-based format.« less
Building an Understanding of Functions: A Series of Activities for Pre-Calculus

ERIC Educational Resources Information Center

Carducci, Olivia M.

2008-01-01

Building block toys can be used to illustrate various concepts connected with functions including graphs and rates of change of linear and exponential functions, piecewise functions, and composition of functions. Five brief activities suitable for a pre-calculus course are described.
Sign changes in sums of the Liouville function

NASA Astrophysics Data System (ADS)

Borwein, Peter; Ferguson, Ron; Mossinghoff, Michael J.

2008-09-01

The Liouville function λ(n) is the completely multiplicative function whose value is -1 at each prime. We develop some algorithms for computing the sum T(n)Dsum_{kD1}^n λ(k)/k , and use these methods to determine the smallest positive integer n where T(n)<0 . This answers a question originating in some work of Turan, who linked the behavior of T(n) to questions about the Riemann zeta function. We also study the problem of evaluating Polya's sum L(n)Dsum_{kD1}^nλ(k) , and we determine some new local extrema for this function, including some new positive values.
Interfacial and emulsifying properties of designed β-strand peptides.

PubMed

Dexter, Annette F

2010-12-07

The structural and surfactant properties of a series of amphipathic β-strand peptides have been studied as a function of pH. Each nine-residue peptide has a framework of hydrophobic proline and phenylalanine amino acid residues, alternating with acidic or basic amino acids to give a sequence closely related to known β-sheet formers. Surface activity, interfacial mechanical properties, electronic circular dichroism (ECD), droplet sizing and zeta potential measurements were used to gain an overview of the peptide behavior as the molecular charge varied from ±4 to 0 with pH. ECD data suggest that the peptides form polyproline-type helices in bulk aqueous solution when highly charged, but may fold to β-hairpins rather than β-sheets when uncharged. In the uncharged state, the peptides adsorb readily at a macroscopic fluid interface to form mechanically strong interfacial films, but tend to give large droplet sizes on emulsification, apparently due to flocculation at a low droplet zeta potential. In contrast, highly charged peptide states gave a low interfacial coverage, but retained good emulsifying activity as judged by droplet size. Best emulsification was generally seen for intermediate charged states of the peptides, possibly representing a compromise between droplet zeta potential and interfacial binding affinity. The emulsifying properties of β-strand peptides have not been previously reported. Understanding the interfacial properties of such peptides is important to their potential development as biosurfactants.
High mobility group box-1 is phosphorylated by protein kinase C zeta and secreted in colon cancer cells

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Hanna; Park, Minhee; Shin, Nara

2012-07-27

Highlights: Black-Right-Pointing-Pointer Specific enzyme for HMGB1 phosphorylation and its secretion is proposed. Black-Right-Pointing-Pointer Inhibition of PKC-{zeta} leads to significant reduction of the secreted HMGB1. Black-Right-Pointing-Pointer Phosphorylation of specific site of HMGB1 redirects its secretion in cancer cells. Black-Right-Pointing-Pointer Activation of PKC-{zeta} in cancers explains the enhanced HMGB1 secretion. -- Abstract: High mobility group box-1 (HMGB1), a nuclear protein, is overexpressed and secreted in cancer cells. Phosphorylation on two different nuclear localization signal regions are known to be important for the nuclear-to-cytoplasmic transport and secretion of HMGB1. However, little is known about the biochemical mechanism of HMGB1 modifications and its subsequentmore » secretion from cancer cells. To identify the specific enzyme and important sites for HMGB1 phosphorylation, we screened the protein kinase C (PKC) family in a colon cancer cell line (HCT116) for HMGB1 binding by pull-down experiments using a 3XFLAG-HMGB1 construct. Strong interactions between atypical PKCs (PKC-{zeta}, {lambda}, and {iota}) and cytoplasmic HMGB1 were observed in HCT116 cells. We further identified the most critical PKC isotype that regulates HMGB1 secretion is PKC-{zeta} by using PKC inhibitors and siRNA experiments. The serine residues at S39, S53 and S181 of HMGB1 were related to enhancing HMGB1 secretion. We also demonstrated overexpression and activation of PKC-{zeta} in colon cancer tissues. Our findings suggest that PKC-{zeta} is involved in the phosphorylation of HMGB1, and the phosphorylation of specific serine residues in the nuclear localization signal regions is related to enhanced HMGB1 secretion in colon cancer cells.« less
An Improved Graph Model for Conflict Resolution Based on Option Prioritization and Its Application

PubMed Central

Yin, Kedong; Li, Xuemei

2017-01-01

In order to quantitatively depict differences regarding the preferences of decision makers for different states, a score function is proposed. As a foundation, coalition motivation and real-coalition analysis are discussed when external circumstance or opportunity costs are considering. On the basis of a confidence-level function, we establish the score function using a “preference tree”. We not only measure the preference for each state, but we also build a collation improvement function to measure coalition motivation and to construct a coordinate system in which to analyze real-coalition stability. All of these developments enhance the applicability of the graph model for conflict resolution (GMCR). Finally, an improved GMCR is applied in the “Changzhou Conflict” to demonstrate how it can be conveniently utilized in practice. PMID:29077049
An Improved Graph Model for Conflict Resolution Based on Option Prioritization and Its Application.

PubMed

Yin, Kedong; Yu, Li; Li, Xuemei

2017-10-27

In order to quantitatively depict differences regarding the preferences of decision makers for different states, a score function is proposed. As a foundation, coalition motivation and real-coalition analysis are discussed when external circumstance or opportunity costs are considering. On the basis of a confidence-level function, we establish the score function using a "preference tree". We not only measure the preference for each state, but we also build a collation improvement function to measure coalition motivation and to construct a coordinate system in which to analyze real-coalition stability. All of these developments enhance the applicability of the graph model for conflict resolution (GMCR). Finally, an improved GMCR is applied in the "Changzhou Conflict" to demonstrate how it can be conveniently utilized in practice.
Functional grouping of similar genes using eigenanalysis on minimum spanning tree based neighborhood graph.

PubMed

Jothi, R; Mohanty, Sraban Kumar; Ojha, Aparajita

2016-04-01

Gene expression data clustering is an important biological process in DNA microarray analysis. Although there have been many clustering algorithms for gene expression analysis, finding a suitable and effective clustering algorithm is always a challenging problem due to the heterogeneous nature of gene profiles. Minimum Spanning Tree (MST) based clustering algorithms have been successfully employed to detect clusters of varying shapes and sizes. This paper proposes a novel clustering algorithm using Eigenanalysis on Minimum Spanning Tree based neighborhood graph (E-MST). As MST of a set of points reflects the similarity of the points with their neighborhood, the proposed algorithm employs a similarity graph obtained from k(') rounds of MST (k(')-MST neighborhood graph). By studying the spectral properties of the similarity matrix obtained from k(')-MST graph, the proposed algorithm achieves improved clustering results. We demonstrate the efficacy of the proposed algorithm on 12 gene expression datasets. Experimental results show that the proposed algorithm performs better than the standard clustering algorithms. Copyright © 2016 Elsevier Ltd. All rights reserved.
Inference of Spatio-Temporal Functions Over Graphs via Multikernel Kriged Kalman Filtering

NASA Astrophysics Data System (ADS)

Ioannidis, Vassilis N.; Romero, Daniel; Giannakis, Georgios B.

2018-06-01

Inference of space-time varying signals on graphs emerges naturally in a plethora of network science related applications. A frequently encountered challenge pertains to reconstructing such dynamic processes, given their values over a subset of vertices and time instants. The present paper develops a graph-aware kernel-based kriged Kalman filter that accounts for the spatio-temporal variations, and offers efficient online reconstruction, even for dynamically evolving network topologies. The kernel-based learning framework bypasses the need for statistical information by capitalizing on the smoothness that graph signals exhibit with respect to the underlying graph. To address the challenge of selecting the appropriate kernel, the proposed filter is combined with a multi-kernel selection module. Such a data-driven method selects a kernel attuned to the signal dynamics on-the-fly within the linear span of a pre-selected dictionary. The novel multi-kernel learning algorithm exploits the eigenstructure of Laplacian kernel matrices to reduce computational complexity. Numerical tests with synthetic and real data demonstrate the superior reconstruction performance of the novel approach relative to state-of-the-art alternatives.
Inspection of aeronautical mechanical parts with a pan-tilt-zoom camera: an approach guided by the computer-aided design model

NASA Astrophysics Data System (ADS)

Viana, Ilisio; Orteu, Jean-José; Cornille, Nicolas; Bugarin, Florian

2015-11-01

We focus on quality control of mechanical parts in aeronautical context using a single pan-tilt-zoom (PTZ) camera and a computer-aided design (CAD) model of the mechanical part. We use the CAD model to create a theoretical image of the element to be checked, which is further matched with the sensed image of the element to be inspected, using a graph theory-based approach. The matching is carried out in two stages. First, the two images are used to create two attributed graphs representing the primitives (ellipses and line segments) in the images. In the second stage, the graphs are matched using a similarity function built from the primitive parameters. The similarity scores of the matching are injected in the edges of a bipartite graph. A best-match-search procedure in the bipartite graph guarantees the uniqueness of the match solution. The method achieves promising performance in tests with synthetic data including missing elements, displaced elements, size changes, and combinations of these cases. The results open good prospects for using the method with realistic data.
A New Wrist Clinical Evaluation Score.

PubMed

Herzberg, Guillaume; Burnier, Marion; Nakamura, Toshiyasu

2018-04-01

Background The number of available wrist scoring systems is limited; some of them do not include forearm rotation criteria. Purpose To describe a new electronic wrist clinical score and to present a new patient's generated wrist evaluation criterion, the subjective wrist value (SWV). Materials and Methods A new electronic wrist clinical score, the Lyon wrist score (LWS) including wrist VAS pain and function, active range of motion and strength was built into an excel file. VAS flexion-extension pain and function were evaluated independently from pronation-supination pain and function. A new patient's generated wrist evaluation criterion, SWV was described. Results The LWS is available in two versions, standard and full (the latter including forearm rotation strength). Both standard and full LWS are displayed into an automatically generated diamond-shaped graph providing a comprehensive visual display of the clinical status of most osteoarticular wrist disorders. The graph also includes SWV. The LWS, combined with SWV into a graph that may be directly exported to a PowerPoint presentation, provide a new practical and comprehensive tool for following/comparing wrist osteoarticular clinical status/outcomes. Both standard and full LWS charts are available in colored versions on a related website for free download. Conclusion A comprehensive updated electronic display of osteoarticular wrist clinical status including forearm rotation criteria is provided and displayed into a graph which may be exported as such into a PowerPoint presentation for clinical analysis/comparisons. Level of Evidence Level II.
A Factor Graph Approach to Automated GO Annotation

PubMed Central

Spetale, Flavio E.; Tapia, Elizabeth; Krsticevic, Flavia; Roda, Fernando; Bulacio, Pilar

2016-01-01

As volume of genomic data grows, computational methods become essential for providing a first glimpse onto gene annotations. Automated Gene Ontology (GO) annotation methods based on hierarchical ensemble classification techniques are particularly interesting when interpretability of annotation results is a main concern. In these methods, raw GO-term predictions computed by base binary classifiers are leveraged by checking the consistency of predefined GO relationships. Both formal leveraging strategies, with main focus on annotation precision, and heuristic alternatives, with main focus on scalability issues, have been described in literature. In this contribution, a factor graph approach to the hierarchical ensemble formulation of the automated GO annotation problem is presented. In this formal framework, a core factor graph is first built based on the GO structure and then enriched to take into account the noisy nature of GO-term predictions. Hence, starting from raw GO-term predictions, an iterative message passing algorithm between nodes of the factor graph is used to compute marginal probabilities of target GO-terms. Evaluations on Saccharomyces cerevisiae, Arabidopsis thaliana and Drosophila melanogaster protein sequences from the GO Molecular Function domain showed significant improvements over competing approaches, even when protein sequences were naively characterized by their physicochemical and secondary structure properties or when loose noisy annotation datasets were considered. Based on these promising results and using Arabidopsis thaliana annotation data, we extend our approach to the identification of most promising molecular function annotations for a set of proteins of unknown function in Solanum lycopersicum. PMID:26771463
A Factor Graph Approach to Automated GO Annotation.

PubMed

Spetale, Flavio E; Tapia, Elizabeth; Krsticevic, Flavia; Roda, Fernando; Bulacio, Pilar

2016-01-01

As volume of genomic data grows, computational methods become essential for providing a first glimpse onto gene annotations. Automated Gene Ontology (GO) annotation methods based on hierarchical ensemble classification techniques are particularly interesting when interpretability of annotation results is a main concern. In these methods, raw GO-term predictions computed by base binary classifiers are leveraged by checking the consistency of predefined GO relationships. Both formal leveraging strategies, with main focus on annotation precision, and heuristic alternatives, with main focus on scalability issues, have been described in literature. In this contribution, a factor graph approach to the hierarchical ensemble formulation of the automated GO annotation problem is presented. In this formal framework, a core factor graph is first built based on the GO structure and then enriched to take into account the noisy nature of GO-term predictions. Hence, starting from raw GO-term predictions, an iterative message passing algorithm between nodes of the factor graph is used to compute marginal probabilities of target GO-terms. Evaluations on Saccharomyces cerevisiae, Arabidopsis thaliana and Drosophila melanogaster protein sequences from the GO Molecular Function domain showed significant improvements over competing approaches, even when protein sequences were naively characterized by their physicochemical and secondary structure properties or when loose noisy annotation datasets were considered. Based on these promising results and using Arabidopsis thaliana annotation data, we extend our approach to the identification of most promising molecular function annotations for a set of proteins of unknown function in Solanum lycopersicum.

TSAR, a new graph-theoretical approach to computational modeling of protein side-chain flexibility: modeling of ionization properties of proteins.

PubMed

Stroganov, Oleg V; Novikov, Fedor N; Zeifman, Alexey A; Stroylov, Viktor S; Chilov, Ghermes G

2011-09-01

A new graph-theoretical approach called thermodynamic sampling of amino acid residues (TSAR) has been elaborated to explicitly account for the protein side chain flexibility in modeling conformation-dependent protein properties. In TSAR, a protein is viewed as a graph whose nodes correspond to structurally independent groups and whose edges connect the interacting groups. Each node has its set of states describing conformation and ionization of the group, and each edge is assigned an array of pairwise interaction potentials between the adjacent groups. By treating the obtained graph as a belief-network-a well-established mathematical abstraction-the partition function of each node is found. In the current work we used TSAR to calculate partition functions of the ionized forms of protein residues. A simplified version of a semi-empirical molecular mechanical scoring function, borrowed from our Lead Finder docking software, was used for energy calculations. The accuracy of the resulting model was validated on a set of 486 experimentally determined pK(a) values of protein residues. The average correlation coefficient (R) between calculated and experimental pK(a) values was 0.80, ranging from 0.95 (for Tyr) to 0.61 (for Lys). It appeared that the hydrogen bond interactions and the exhaustiveness of side chain sampling made the most significant contribution to the accuracy of pK(a) calculations. Copyright © 2011 Wiley-Liss, Inc.
Optimal graph based segmentation using flow lines with application to airway wall segmentation.

PubMed

Petersen, Jens; Nielsen, Mads; Lo, Pechin; Saghir, Zaigham; Dirksen, Asger; de Bruijne, Marleen

2011-01-01

This paper introduces a novel optimal graph construction method that is applicable to multi-dimensional, multi-surface segmentation problems. Such problems are often solved by refining an initial coarse surface within the space given by graph columns. Conventional columns are not well suited for surfaces with high curvature or complex shapes but the proposed columns, based on properly generated flow lines, which are non-intersecting, guarantee solutions that do not self-intersect and are better able to handle such surfaces. The method is applied to segment human airway walls in computed tomography images. Comparison with manual annotations on 649 cross-sectional images from 15 different subjects shows significantly smaller contour distances and larger area of overlap than are obtained with recently published graph based methods. Airway abnormality measurements obtained with the method on 480 scan pairs from a lung cancer screening trial are reproducible and correlate significantly with lung function.
On the mixing time of geographical threshold graphs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bradonjic, Milan

In this paper, we study the mixing time of random graphs generated by the geographical threshold graph (GTG) model, a generalization of random geometric graphs (RGG). In a GTG, nodes are distributed in a Euclidean space, and edges are assigned according to a threshold function involving the distance between nodes as well as randomly chosen node weights. The motivation for analyzing this model is that many real networks (e.g., wireless networks, the Internet, etc.) need to be studied by using a 'richer' stochastic model (which in this case includes both a distance between nodes and weights on the nodes). Wemore » specifically study the mixing times of random walks on 2-dimensional GTGs near the connectivity threshold. We provide a set of criteria on the distribution of vertex weights that guarantees that the mixing time is {Theta}(n log n).« less
Measurement of Zeta-Potential at Microchannel Wall by a Nanoscale Laser Induced Fluorescence Imaging

NASA Astrophysics Data System (ADS)

Kazoe, Yutaka; Sato, Yohei

A nanoscale laser induced fluorescence imaging was proposed by using fluorescent dye and the evanescent wave with total internal reflection of a laser beam. The present study focused on the two-dimensional measurement of zeta-potential at the microchannel wall, which is an electrostatic potential at the wall surface and a dominant parameter of electroosmotic flow. The evanescent wave, which decays exponentially from the wall, was used as an excitation light of the fluorescent dye. The fluorescent intensity detected by a CCD camera is closely related to the zeta-potential. Two kinds of fluorescent dye solution at different ionic concentrations were injected into a T-shaped microchannel, and formed a mixing flow field in the junction area. The two-dimensional distribution of zeta-potential at the microchannel wall in the pressure-driven flow field was measured. The obtained zeta-potential distribution has a transverse gradient toward the mixing flow field and was changed by the difference in the averaged velocity of pressure-driven flow. To understand the ion motion in the mixing flow field, the three-dimensional flow structure was analyzed by the velocity measurement using micron-resolution particle image velocimetry and the numerical simulation. It is concluded that the two-dimensional distribution of zeta-potential at the microchannel wall was dependent on the ion motion in the flow field, which was governed by the convection and molecular diffusion.
Atomic-scale study of stacking faults in Zr hydrides and implications on hydride formation.

PubMed

Besson, Remy; Thuinet, L; Louchez, Marc-Antoine

2018-06-25

We performed atomic-scale ab initio calculations to investigate the stacking fault (SF) properties of the metastable zeta-Zr2H zirconium hydride. The effect of H near the SF was found to entail the existence of negative SF energies, showing that the zeta compound is probably unstable with respect to shearing in the basal plane. The effect of temperature on SFs was investigated by means of free energy calculations in the quasiharmonic approximation. This evidenced unexpectedly large temperature effects, confirming the main conclusions drawn at 0 K, in particular the zeta mechanical instability. The complex behaviour of H atoms during the shear process suggested zeta-hcp --> Zr2H[111]-fcc as a plausible shear path leading to an fcc compound with same composition as zeta. Finally, as shown by an analysis based on microelasticity, this Zr2H[111]-fcc intermediate compound may be relevant for better interpreting the currently intricate issue of hydride habit planes in zirconium. © 2018 IOP Publishing Ltd.
The ng_ζ1 toxin of the gonococcal epsilon/zeta toxin/antitoxin system drains precursors for cell wall synthesis.

PubMed

Rocker, Andrea; Peschke, Madeleine; Kittilä, Tiia; Sakson, Roman; Brieke, Clara; Meinhart, Anton

2018-04-27

Bacterial toxin-antitoxin complexes are emerging as key players modulating bacterial physiology as activation of toxins induces stasis or programmed cell death by interference with vital cellular processes. Zeta toxins, which are prevalent in many bacterial genomes, were shown to interfere with cell wall formation by perturbing peptidoglycan synthesis in Gram-positive bacteria. Here, we characterize the epsilon/zeta toxin-antitoxin (TA) homologue from the Gram-negative pathogen Neisseria gonorrhoeae termed ng_ɛ1 / ng_ζ1. Contrary to previously studied streptococcal epsilon/zeta TA systems, ng_ɛ1 has an epsilon-unrelated fold and ng_ζ1 displays broader substrate specificity and phosphorylates multiple UDP-activated sugars that are precursors of peptidoglycan and lipopolysaccharide synthesis. Moreover, the phosphorylation site is different from the streptococcal zeta toxins, resulting in a different interference with cell wall synthesis. This difference most likely reflects adaptation to the individual cell wall composition of Gram-negative and Gram-positive organisms but also the distinct involvement of cell wall components in virulence.
Scaling Up Graph-Based Semisupervised Learning via Prototype Vector Machines

PubMed Central

Zhang, Kai; Lan, Liang; Kwok, James T.; Vucetic, Slobodan; Parvin, Bahram

2014-01-01

When the amount of labeled data are limited, semi-supervised learning can improve the learner's performance by also using the often easily available unlabeled data. In particular, a popular approach requires the learned function to be smooth on the underlying data manifold. By approximating this manifold as a weighted graph, such graph-based techniques can often achieve state-of-the-art performance. However, their high time and space complexities make them less attractive on large data sets. In this paper, we propose to scale up graph-based semisupervised learning using a set of sparse prototypes derived from the data. These prototypes serve as a small set of data representatives, which can be used to approximate the graph-based regularizer and to control model complexity. Consequently, both training and testing become much more efficient. Moreover, when the Gaussian kernel is used to define the graph affinity, a simple and principled method to select the prototypes can be obtained. Experiments on a number of real-world data sets demonstrate encouraging performance and scaling properties of the proposed approach. It also compares favorably with models learned via ℓ1-regularization at the same level of model sparsity. These results demonstrate the efficacy of the proposed approach in producing highly parsimonious and accurate models for semisupervised learning. PMID:25720002
The Effects of rTMS Combined with Motor Training on Functional Connectivity in Alpha Frequency Band.

PubMed

Jin, Jing-Na; Wang, Xin; Li, Ying; Jin, Fang; Liu, Zhi-Peng; Yin, Tao

2017-01-01

It has recently been reported that repetitive transcranial magnetic stimulation combined with motor training (rTMS-MT) could improve motor function in post-stroke patients. However, the effects of rTMS-MT on cortical function using functional connectivity and graph theoretical analysis remain unclear. Ten healthy subjects were recruited to receive rTMS immediately before application of MT. Low frequency rTMS was delivered to the dominant hemisphere and non-dominant hand performed MT over 14 days. The reaction time of Nine-Hole Peg Test and electroencephalography (EEG) in resting condition with eyes closed were recorded before and after rTMS-MT. Functional connectivity was assessed by phase synchronization index (PSI), and subsequently thresholded to construct undirected graphs in alpha frequency band (8-13 Hz). We found a significant decrease in reaction time after rTMS-MT. The functional connectivity between the parietal and frontal cortex, and the graph theory statistics of node degree and efficiency in the parietal cortex increased. Besides the functional connectivity between premotor and frontal cortex, the degree and efficiency of premotor cortex showed opposite results. In addition, the number of connections significantly increased within inter-hemispheres and inter-regions. In conclusion, this study could be helpful in our understanding of how rTMS-MT modulates brain activity. The methods and results in this study could be taken as reference in future studies of the effects of rTMS-MT in stroke patients.
A surface-charge study on cellular-uptake behavior of F3-peptide-conjugated iron oxide nanoparticles.

PubMed

Zhang, Yu; Yang, Mo; Park, Ji-Ho; Singelyn, Jennifer; Ma, Huiqing; Sailor, Michael J; Ruoslahti, Erkki; Ozkan, Mihrimah; Ozkan, Cengiz

2009-09-01

Surface-charge measurements of mammalian cells in terms of Zeta potential are demonstrated as a useful biological characteristic in identifying cellular interactions with specific nanomaterials. A theoretical model of the changes in Zeta potential of cells after incubation with nanoparticles is established to predict the possible patterns of Zeta-potential change to reveal the binding and internalization effects. The experimental results show a distinct pattern of Zeta-potential change that allows the discrimination of human normal breast epithelial cells (MCF-10A) from human cancer breast epithelial cells (MCF-7) when the cells are incubated with dextran coated iron oxide nanoparticles that contain tumor-homing F3 peptides, where the tumor-homing F3 peptide specifically bound to nucleolin receptors that are overexpressed in cancer breast cells.
Catalytic properties of an expressed and purified higher plant type zeta-carotene desaturase from Capsicum annuum.

PubMed

Breitenbach, J; Kuntz, M; Takaichi, S; Sandmann, G

1999-10-01

The zeta-carotene desaturase from Capsicum annuum (EC 1.14.99.-) was expressed in Escherichia coli, purified and characterized biochemically. The enzyme acts as a monomer with lipophilic quinones as cofactors. Km values for the substrate zeta-carotene or the intermediate neurosporene in the two-step desaturation reaction are almost identical. Product analysis showed that different lycopene isomers are formed, including substantial amounts of the all-trans form, together with 7,7',9,9'-tetracis prolycopene via the corresponding neurosporene isomers. The application of different geometric isomers as substrates revealed that the zeta-carotene desaturase has no preference for certain isomers and that the nature of the isomers formed during catalysis depends strictly on the isomeric composition of the substrate.
Cold sensitivity in rice (Oryza sativa L.) is strongly correlated with a naturally occurring I99V mutation in the multifunctional glutathione transferase isoenzyme GSTZ2

USDA-ARS?s Scientific Manuscript database

GSTZs (zeta class glutathione transferases) belong to a highly conserved subfamily of soluble GSTs found in species ranging from fungi and plants to animals. GSTZ is identical to MAAI (maleylacetoacetate isomerase), which functions in tyrosine catabolism by catalyzing the isomerization of MAA (maley...
Organic particulate matter formation at varying relative humidity using surrogate secondary and primary organic compounds with activity corrections in the condensed phase obtained using a method based on the Wilson equation

NASA Astrophysics Data System (ADS)

Chang, E. I.; Pankow, J. F.

2008-01-01

Secondary organic aerosol (SOA) formation in the atmosphere is currently often modeled using a multiple lumped "two-product" (N·2p) approach. The N·2p approach neglects: 1) variation of activity coefficient (ζi) values and mean molecular weight MW in the particulate matter (PM) phase; 2) water uptake into the PM; and 3) the possibility of phase separation in the PM. This study considers these effects by adopting an (N·2p)ζ, MW ,θ approach (θ is a phase index). Specific chemical structures are assigned to 25 lumped SOA compounds and to 15 representative primary organic aerosol (POA) compounds to allow calculation of ζi and MW values. The SOA structure assignments are based on chamber-derived 2p gas/particle partition coefficient values coupled with known effects of structure on vapor pressure pL,i° (atm). To facilitate adoption of the (N·2p)ζ, MW, θ approach in large-scale models, this study also develops CP-Wilson.1, a group-contribution ζi-prediction method that is more computationally economical than the UNIFAC model of Fredenslund et al. (1975). Group parameter values required by CP-Wilson.1 are obtained by fitting ζi values to predictions from UNIFAC. The (N·2p)ζ,MW, θ approach is applied (using CP-Wilson.1) to several real α-pinene/O3 chamber cases for high reacted hydrocarbon levels (ΔHC≍400 to 1000 μg m-3) when relative humidity (RH) ≍50%. Good agreement between the chamber and predicted results is obtained using both the (N·2p)ζ, MW, θ and N·2p approaches, indicating relatively small water effects under these conditions. However, for a hypothetical α-pinene/O3 case at ΔHC=30 μg m-3 and RH=50%, the (N·2p)ζ, MW, θ approach predicts that water uptake will lead to an organic PM level that is more double that predicted by the N·2p approach. Adoption of the (N·2p)ζ, MW, θ approach using reasonable lumped structures for SOA and POA compounds is recommended for ambient PM modeling.
The correlation of metrics in complex networks with applications in functional brain networks

NASA Astrophysics Data System (ADS)

Li, C.; Wang, H.; de Haan, W.; Stam, C. J.; Van Mieghem, P.

2011-11-01

An increasing number of network metrics have been applied in network analysis. If metric relations were known better, we could more effectively characterize networks by a small set of metrics to discover the association between network properties/metrics and network functioning. In this paper, we investigate the linear correlation coefficients between widely studied network metrics in three network models (Bárabasi-Albert graphs, Erdös-Rényi random graphs and Watts-Strogatz small-world graphs) as well as in functional brain networks of healthy subjects. The metric correlations, which we have observed and theoretically explained, motivate us to propose a small representative set of metrics by including only one metric from each subset of mutually strongly dependent metrics. The following contributions are considered important. (a) A network with a given degree distribution can indeed be characterized by a small representative set of metrics. (b) Unweighted networks, which are obtained from weighted functional brain networks with a fixed threshold, and Erdös-Rényi random graphs follow a similar degree distribution. Moreover, their metric correlations and the resultant representative metrics are similar as well. This verifies the influence of degree distribution on metric correlations. (c) Most metric correlations can be explained analytically. (d) Interestingly, the most studied metrics so far, the average shortest path length and the clustering coefficient, are strongly correlated and, thus, redundant. Whereas spectral metrics, though only studied recently in the context of complex networks, seem to be essential in network characterizations. This representative set of metrics tends to both sufficiently and effectively characterize networks with a given degree distribution. In the study of a specific network, however, we have to at least consider the representative set so that important network properties will not be neglected.
A mass graph-based approach for the identification of modified proteoforms using top-down tandem mass spectra.

PubMed

Kou, Qiang; Wu, Si; Tolic, Nikola; Paša-Tolic, Ljiljana; Liu, Yunlong; Liu, Xiaowen

2017-05-01

Although proteomics has rapidly developed in the past decade, researchers are still in the early stage of exploring the world of complex proteoforms, which are protein products with various primary structure alterations resulting from gene mutations, alternative splicing, post-translational modifications, and other biological processes. Proteoform identification is essential to mapping proteoforms to their biological functions as well as discovering novel proteoforms and new protein functions. Top-down mass spectrometry is the method of choice for identifying complex proteoforms because it provides a 'bird's eye view' of intact proteoforms. The combinatorial explosion of various alterations on a protein may result in billions of possible proteoforms, making proteoform identification a challenging computational problem. We propose a new data structure, called the mass graph, for efficient representation of proteoforms and design mass graph alignment algorithms. We developed TopMG, a mass graph-based software tool for proteoform identification by top-down mass spectrometry. Experiments on top-down mass spectrometry datasets showed that TopMG outperformed existing methods in identifying complex proteoforms. http://proteomics.informatics.iupui.edu/software/topmg/. xwliu@iupui.edu. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com
Two's company, three (or more) is a simplex : Algebraic-topological tools for understanding higher-order structure in neural data.

PubMed

Giusti, Chad; Ghrist, Robert; Bassett, Danielle S

2016-08-01

The language of graph theory, or network science, has proven to be an exceptional tool for addressing myriad problems in neuroscience. Yet, the use of networks is predicated on a critical simplifying assumption: that the quintessential unit of interest in a brain is a dyad - two nodes (neurons or brain regions) connected by an edge. While rarely mentioned, this fundamental assumption inherently limits the types of neural structure and function that graphs can be used to model. Here, we describe a generalization of graphs that overcomes these limitations, thereby offering a broad range of new possibilities in terms of modeling and measuring neural phenomena. Specifically, we explore the use of simplicial complexes: a structure developed in the field of mathematics known as algebraic topology, of increasing applicability to real data due to a rapidly growing computational toolset. We review the underlying mathematical formalism as well as the budding literature applying simplicial complexes to neural data, from electrophysiological recordings in animal models to hemodynamic fluctuations in humans. Based on the exceptional flexibility of the tools and recent ground-breaking insights into neural function, we posit that this framework has the potential to eclipse graph theory in unraveling the fundamental mysteries of cognition.
Simulation Of Wave Function And Probability Density Of Modified Poschl Teller Potential Derived Using Supersymmetric Quantum Mechanics

NASA Astrophysics Data System (ADS)

Angraini, Lily Maysari; Suparmi, Variani, Viska Inda

2010-12-01

SUSY quantum mechanics can be applied to solve Schrodinger equation for high dimensional system that can be reduced into one dimensional system and represented in lowering and raising operators. Lowering and raising operators can be obtained using relationship between original Hamiltonian equation and the (super) potential equation. In this paper SUSY quantum mechanics is used as a method to obtain the wave function and the energy level of the Modified Poschl Teller potential. The graph of wave function equation and probability density is simulated by using Delphi 7.0 programming language. Finally, the expectation value of quantum mechanics operator could be calculated analytically using integral form or probability density graph resulted by the programming.
Neighborhood graph and learning discriminative distance functions for clinical decision support.

PubMed

Tsymbal, Alexey; Zhou, Shaohua Kevin; Huber, Martin

2009-01-01

There are two essential reasons for the slow progress in the acceptance of clinical case retrieval and similarity search-based decision support systems; the especial complexity of clinical data making it difficult to define a meaningful and effective distance function on them and the lack of transparency and explanation ability in many existing clinical case retrieval decision support systems. In this paper, we try to address these two problems by introducing a novel technique for visualizing inter-patient similarity based on a node-link representation with neighborhood graphs and by considering two techniques for learning discriminative distance function that help to combine the power of strong "black box" learners with the transparency of case retrieval and nearest neighbor classification.
The asymptotics of large constrained graphs

NASA Astrophysics Data System (ADS)

Radin, Charles; Ren, Kui; Sadun, Lorenzo

2014-05-01

We show, through local estimates and simulation, that if one constrains simple graphs by their densities ɛ of edges and τ of triangles, then asymptotically (in the number of vertices) for over 95% of the possible range of those densities there is a well-defined typical graph, and it has a very simple structure: the vertices are decomposed into two subsets V1 and V2 of fixed relative size c and 1 - c, and there are well-defined probabilities of edges, gjk, between vj ∈ Vj, and vk ∈ Vk. Furthermore the four parameters c, g11, g22 and g12 are smooth functions of (ɛ, τ) except at two smooth ‘phase transition’ curves.
Some constructions of biharmonic maps and Chen’s conjecture on biharmonic hypersurfaces

NASA Astrophysics Data System (ADS)

Ou, Ye-Lin

2012-04-01

We give several construction methods and use them to produce many examples of proper biharmonic maps including biharmonic tori of any dimension in Euclidean spheres (Theorem 2.2, Corollaries 2.3, 2.4 and 2.6), biharmonic maps between spheres (Theorem 2.9) and into spheres (Theorem 2.10) via orthogonal multiplications and eigenmaps. We also study biharmonic graphs of maps, derive the equation for a function whose graph is a biharmonic hypersurface in a Euclidean space, and give an equivalent formulation of Chen's conjecture on biharmonic hypersurfaces by using the biharmonic graph equation (Theorem 4.1) which paves a way for the analytic study of the conjecture.
Nonlinear optimization simplified by hypersurface deformation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stillinger, F.H.; Weber, T.A.

1988-09-01

A general strategy is advanced for simplifying nonlinear optimization problems, the ant-lion method. This approach exploits shape modifications of the cost-function hypersurface which distend basins surrounding low-lying minima (including global minima). By intertwining hypersurface deformations with steepest-descent displacements, the search is concentrated on a small relevant subset of all minima. Specific calculations demonstrating the value of this method are reported for the partitioning of two classes of irregular but nonrandom graphs, the prime-factor graphs and the pi graphs. We also indicate how this approach can be applied to the traveling salesman problem and to design layout optimization, and that itmore » may be useful in combination with simulated annealing strategies.« less

A simplifying feature of the heterotic one loop four graviton amplitude

NASA Astrophysics Data System (ADS)

Basu, Anirban

2018-01-01

We show that the weight four modular graph functions that contribute to the integrand of the t8t8D4R4 term at one loop in heterotic string theory do not require regularization, and hence the integrand is simple. This is unlike the graphs that contribute to the integrands of the other gravitational terms at this order in the low momentum expansion, and these integrands require regularization. This property persists for an infinite number of terms in the effective action, and their integrands do not require regularization. We find non-trivial relations between weight four graphs of distinct topologies that do not require regularization by performing trivial manipulations using auxiliary diagrams.
State transfer in highly connected networks and a quantum Babinet principle

NASA Astrophysics Data System (ADS)

Tsomokos, D. I.; Plenio, M. B.; de Vega, I.; Huelga, S. F.

2008-12-01

The transfer of a quantum state between distant nodes in two-dimensional networks is considered. The fidelity of state transfer is calculated as a function of the number of interactions in networks that are described by regular graphs. It is shown that perfect state transfer is achieved in a network of size N , whose structure is that of an (N/2) -cross polytope graph, if N is a multiple of 4 . The result is reminiscent of the Babinet principle of classical optics. A quantum Babinet principle is derived, which allows for the identification of complementary graphs leading to the same fidelity of state transfer, in analogy with complementary screens providing identical diffraction patterns.
Graph theoretical analysis of EEG functional connectivity during music perception.

PubMed

Wu, Junjie; Zhang, Junsong; Liu, Chu; Liu, Dongwei; Ding, Xiaojun; Zhou, Changle

2012-11-05

The present study evaluated the effect of music on large-scale structure of functional brain networks using graph theoretical concepts. While most studies on music perception used Western music as an acoustic stimulus, Guqin music, representative of Eastern music, was selected for this experiment to increase our knowledge of music perception. Electroencephalography (EEG) was recorded from non-musician volunteers in three conditions: Guqin music, noise and silence backgrounds. Phase coherence was calculated in the alpha band and between all pairs of EEG channels to construct correlation matrices. Each resulting matrix was converted into a weighted graph using a threshold, and two network measures: the clustering coefficient and characteristic path length were calculated. Music perception was found to display a higher level mean phase coherence. Over the whole range of thresholds, the clustering coefficient was larger while listening to music, whereas the path length was smaller. Networks in music background still had a shorter characteristic path length even after the correction for differences in mean synchronization level among background conditions. This topological change indicated a more optimal structure under music perception. Thus, prominent small-world properties are confirmed in functional brain networks. Furthermore, music perception shows an increase of functional connectivity and an enhancement of small-world network organizations. Copyright © 2012 Elsevier B.V. All rights reserved.
Differences in graph theory functional connectivity in left and right temporal lobe epilepsy.

PubMed

Chiang, Sharon; Stern, John M; Engel, Jerome; Levin, Harvey S; Haneef, Zulfi

2014-12-01

To investigate lateralized differences in limbic system functional connectivity between left and right temporal lobe epilepsy (TLE) using graph theory. Interictal resting state fMRI was performed in 14 left TLE patients, 11 right TLE patients, and 12 controls. Graph theory analysis of 10 bilateral limbic regions of interest was conducted. Changes in edgewise functional connectivity, network topology, and regional topology were quantified, and then left and right TLE were compared. Limbic edgewise functional connectivity was predominantly reduced in both left and right TLE. More regional connections were reduced in right TLE, most prominently involving reduced interhemispheric connectivity between the bilateral insula and bilateral hippocampi. A smaller number of limbic connections were increased in TLE, more so in left than in right TLE. Topologically, the most pronounced change was a reduction in average network betweenness centrality and concurrent increase in left hippocampal betweenness centrality in right TLE. In contrast, left TLE exhibited a weak trend toward increased right hippocampal betweenness centrality, with no change in average network betweenness centrality. Limbic functional connectivity is predominantly reduced in both left and right TLE, with more pronounced reductions in right TLE. In contrast, left TLE exhibits both edgewise and topological changes that suggest a tendency toward reorganization. Network changes in TLE and lateralized differences thereof may have important diagnostic and prognostic implications. Published by Elsevier B.V.
Visualizing Ecosystem Energy Flow in Complex Food Web Networks: A Comparison of Three Alaskan Large Marine Ecosystems

NASA Astrophysics Data System (ADS)

Kearney, K.; Aydin, K.

2016-02-01

Oceanic food webs are often depicted as network graphs, with the major organisms or functional groups displayed as nodes and the fluxes of between them as the edges. However, the large number of nodes and edges and high connectance of many management-oriented food webs coupled with graph layout algorithms poorly-suited to certain desired characteristics of food web visualizations often lead to hopelessly tangled diagrams that convey little information other than, "It's complex." Here, I combine several new graph visualization techniques- including a new node layout alorithm based on a trophic similarity (quantification of shared predator and prey) and trophic level, divided edge bundling for edge routing, and intelligent automated placement of labels- to create a much clearer visualization of the important fluxes through a food web. The technique will be used to highlight the differences in energy flow within three Alaskan Large Marine Ecosystems (the Bering Sea, Gulf of Alaska, and Aleutian Islands) that include very similar functional groups but unique energy pathways.
Statistical properties of multi-theta polymer chains

NASA Astrophysics Data System (ADS)

Uehara, Erica; Deguchi, Tetsuo

2018-04-01

We study statistical properties of polymer chains with complex structures whose chemical connectivities are expressed by graphs. The multi-theta curve of m subchains with two branch points connected by them is one of the simplest graphs among those graphs having closed paths, i.e. loops. We denoted it by θm , and for m = 2 it is given by a ring. We derive analytically the pair distribution function and the scattering function for the θm -shaped polymer chains consisting of m Gaussian random walks of n steps. Surprisingly, it is shown rigorously that the mean-square radius of gyration for the Gaussian θm -shaped polymer chain does not depend on the number m of subchains if each subchain has the same fixed number of steps. For m = 3 we show the Kratky plot for the theta-shaped polymer chain consisting of hard cylindrical segments by the Monte-Carlo method including reflection at trivalent vertices.
Role models for complex networks

NASA Astrophysics Data System (ADS)

Reichardt, J.; White, D. R.

2007-11-01

We present a framework for automatically decomposing (“block-modeling”) the functional classes of agents within a complex network. These classes are represented by the nodes of an image graph (“block model”) depicting the main patterns of connectivity and thus functional roles in the network. Using a first principles approach, we derive a measure for the fit of a network to any given image graph allowing objective hypothesis testing. From the properties of an optimal fit, we derive how to find the best fitting image graph directly from the network and present a criterion to avoid overfitting. The method can handle both two-mode and one-mode data, directed and undirected as well as weighted networks and allows for different types of links to be dealt with simultaneously. It is non-parametric and computationally efficient. The concepts of structural equivalence and modularity are found as special cases of our approach. We apply our method to the world trade network and analyze the roles individual countries play in the global economy.
Extraction and characterization of oil bodies from soy beans: a natural source of pre-emulsified soybean oil.

PubMed

Iwanaga, Daigo; Gray, David A; Fisk, Ian D; Decker, Eric Andrew; Weiss, Jochen; McClements, David Julian

2007-10-17

Soybeans contain oil bodies that are coated by a layer of oleosin proteins. In nature, this protein coating protects the oil bodies from environmental stresses and may be utilized by food manufacturers for the same purpose. In this study, oil bodies were extracted from soybean using an aqueous extraction method that involved blending, dispersion (pH 8.6), filtration, and centrifugation steps. The influence of NaCl (0-250 mM), thermal processing (30-90 degrees C, 20 min) and pH (2-8) on the properties and stability of the oil bodies was analyzed using zeta-potential, particle size, and creaming stability measurements. The extracted oil bodies were relatively small ( d 32 approximately 250 nm), and their zeta-potential went from around +12 mV to -20 mV as the pH was increased from 2 to 8, with an isoelectric point around pH 4. The oil bodies were stable to aggregation and creaming at low (pH = 2) and high (pH >/= 6) pH values but were unstable at intermediate values (3
Graph Theoretical Analysis Reveals: Women's Brains Are Better Connected than Men's.

PubMed

Szalkai, Balázs; Varga, Bálint; Grolmusz, Vince

2015-01-01

Deep graph-theoretic ideas in the context with the graph of the World Wide Web led to the definition of Google's PageRank and the subsequent rise of the most popular search engine to date. Brain graphs, or connectomes, are being widely explored today. We believe that non-trivial graph theoretic concepts, similarly as it happened in the case of the World Wide Web, will lead to discoveries enlightening the structural and also the functional details of the animal and human brains. When scientists examine large networks of tens or hundreds of millions of vertices, only fast algorithms can be applied because of the size constraints. In the case of diffusion MRI-based structural human brain imaging, the effective vertex number of the connectomes, or brain graphs derived from the data is on the scale of several hundred today. That size facilitates applying strict mathematical graph algorithms even for some hard-to-compute (or NP-hard) quantities like vertex cover or balanced minimum cut. In the present work we have examined brain graphs, computed from the data of the Human Connectome Project, recorded from male and female subjects between ages 22 and 35. Significant differences were found between the male and female structural brain graphs: we show that the average female connectome has more edges, is a better expander graph, has larger minimal bisection width, and has more spanning trees than the average male connectome. Since the average female brain weighs less than the brain of males, these properties show that the female brain has better graph theoretical properties, in a sense, than the brain of males. It is known that the female brain has a smaller gray matter/white matter ratio than males, that is, a larger white matter/gray matter ratio than the brain of males; this observation is in line with our findings concerning the number of edges, since the white matter consists of myelinated axons, which, in turn, roughly correspond to the connections in the brain graph. We have also found that the minimum bisection width, normalized with the edge number, is also significantly larger in the right and the left hemispheres in females: therefore, the differing bisection widths are independent from the difference in the number of edges.
Graph Theoretical Analysis Reveals: Women’s Brains Are Better Connected than Men’s

PubMed Central

Szalkai, Balázs; Varga, Bálint; Grolmusz, Vince

2015-01-01

Deep graph-theoretic ideas in the context with the graph of the World Wide Web led to the definition of Google’s PageRank and the subsequent rise of the most popular search engine to date. Brain graphs, or connectomes, are being widely explored today. We believe that non-trivial graph theoretic concepts, similarly as it happened in the case of the World Wide Web, will lead to discoveries enlightening the structural and also the functional details of the animal and human brains. When scientists examine large networks of tens or hundreds of millions of vertices, only fast algorithms can be applied because of the size constraints. In the case of diffusion MRI-based structural human brain imaging, the effective vertex number of the connectomes, or brain graphs derived from the data is on the scale of several hundred today. That size facilitates applying strict mathematical graph algorithms even for some hard-to-compute (or NP-hard) quantities like vertex cover or balanced minimum cut. In the present work we have examined brain graphs, computed from the data of the Human Connectome Project, recorded from male and female subjects between ages 22 and 35. Significant differences were found between the male and female structural brain graphs: we show that the average female connectome has more edges, is a better expander graph, has larger minimal bisection width, and has more spanning trees than the average male connectome. Since the average female brain weighs less than the brain of males, these properties show that the female brain has better graph theoretical properties, in a sense, than the brain of males. It is known that the female brain has a smaller gray matter/white matter ratio than males, that is, a larger white matter/gray matter ratio than the brain of males; this observation is in line with our findings concerning the number of edges, since the white matter consists of myelinated axons, which, in turn, roughly correspond to the connections in the brain graph. We have also found that the minimum bisection width, normalized with the edge number, is also significantly larger in the right and the left hemispheres in females: therefore, the differing bisection widths are independent from the difference in the number of edges. PMID:26132764
Light-induced cross-linking and post-cross-linking modification of polyglycidol.

PubMed

Marquardt, F; Bruns, M; Keul, H; Yagci, Y; Möller, M

2018-02-08

The photoinduced radical generation process has received renewed interest due to its economic and ecological appeal. Herein the light-induced cross-linking of functional polyglycidol and its post-cross-linking modification are presented. Linear polyglycidol was first functionalized with a tertiary amine in a two-step reaction. Dimethylaminopropyl functional polyglycidol was cross-linked in a UV-light mediated reaction with camphorquinone as a type II photoinitiator. The cross-linked polyglycidol was further functionalized by quaternization with various organoiodine compounds. Aqueous dispersions of the cross-linked polymers were investigated by means of DLS and zeta potential measurements. Polymer films were evaluated by DSC and XPS.
Density functional theory calculations of the lowest energy quintet and triplet states of model hemes: role of functional, basis set, and zero-point energy corrections.

PubMed

Khvostichenko, Daria; Choi, Andrew; Boulatov, Roman

2008-04-24

We investigated the effect of several computational variables, including the choice of the basis set, application of symmetry constraints, and zero-point energy (ZPE) corrections, on the structural parameters and predicted ground electronic state of model 5-coordinate hemes (iron(II) porphines axially coordinated by a single imidazole or 2-methylimidazole). We studied the performance of B3LYP and B3PW91 with eight Pople-style basis sets (up to 6-311+G*) and B97-1, OLYP, and TPSS functionals with 6-31G and 6-31G* basis sets. Only hybrid functionals B3LYP, B3PW91, and B97-1 reproduced the quintet ground state of the model hemes. With a given functional, the choice of the basis set caused up to 2.7 kcal/mol variation of the quintet-triplet electronic energy gap (DeltaEel), in several cases, resulting in the inversion of the sign of DeltaEel. Single-point energy calculations with triple-zeta basis sets of the Pople (up to 6-311G++(2d,2p)), Ahlrichs (TZVP and TZVPP), and Dunning (cc-pVTZ) families showed the same trend. The zero-point energy of the quintet state was approximately 1 kcal/mol lower than that of the triplet, and accounting for ZPE corrections was crucial for establishing the ground state if the electronic energy of the triplet state was approximately 1 kcal/mol less than that of the quintet. Within a given model chemistry, effects of symmetry constraints and of a "tense" structure of the iron porphine fragment coordinated to 2-methylimidazole on DeltaEel were limited to 0.3 kcal/mol. For both model hemes the best agreement with crystallographic structural data was achieved with small 6-31G and 6-31G* basis sets. Deviation of the computed frequency of the Fe-Im stretching mode from the experimental value with the basis set decreased in the order: nonaugmented basis sets, basis sets with polarization functions, and basis sets with polarization and diffuse functions. Contraction of Pople-style basis sets (double-zeta or triple-zeta) affected the results insignificantly for iron(II) porphyrin coordinated with imidazole. Poor performance of a "locally dense" basis set with a large number of basis functions on the Fe center was observed in calculation of quintet-triplet gaps. Our results lead to a series of suggestions for density functional theory calculations of quintet-triplet energy gaps in ferrohemes with a single axial imidazole; these suggestions are potentially applicable for other transition-metal complexes.
Graph theory analysis of complex brain networks: new concepts in brain mapping applied to neurosurgery.

PubMed

Hart, Michael G; Ypma, Rolf J F; Romero-Garcia, Rafael; Price, Stephen J; Suckling, John

2016-06-01

Neuroanatomy has entered a new era, culminating in the search for the connectome, otherwise known as the brain's wiring diagram. While this approach has led to landmark discoveries in neuroscience, potential neurosurgical applications and collaborations have been lagging. In this article, the authors describe the ideas and concepts behind the connectome and its analysis with graph theory. Following this they then describe how to form a connectome using resting state functional MRI data as an example. Next they highlight selected insights into healthy brain function that have been derived from connectome analysis and illustrate how studies into normal development, cognitive function, and the effects of synthetic lesioning can be relevant to neurosurgery. Finally, they provide a précis of early applications of the connectome and related techniques to traumatic brain injury, functional neurosurgery, and neurooncology.
Some notes on the Roman domination number and Italian domination number in graphs

NASA Astrophysics Data System (ADS)

Hajibaba, Maryam; Jafari Rad, Nader

2017-09-01

An Italian dominating function (or simply, IDF) on a graph G = (V, E) is a function f : V → {0, 1, 2} that satisfies the property that for every vertex v ∈ V, with f(v) = 0, Σ u∈N(v) f(u) ≥ 2. The weight of an Italian dominating function f is defined as w(f) = f(V ) = Σ u∈V f(u). The minimum weight among all of the Italian dominating functions on a graph G is called the Italian domination number of G, and is denoted by γI (G). A double Roman dominating function (or simply, DRDF) is a function f : V → {0, 1, 2, 3} having the property that if f(v) = 0 for a vertex v, then v has at least two adjacent vertices assigned 2 under f or one adjacent vertex assigned 3 under f, and if f(v) = 1, then v has at least one neighbor with f(w) ≥ 2. The weight of a DRDF f is defined as the sum f(V) = Σ v∈V f(v), and the minimum weight of a DRDF on G is the double Roman domination number of G, denoted by γdR (G). In this paper we show that γdR (G)/2 ≤ γI (G) ≤ 2γdR (G)/3, and characterize all trees T with γI (T) = 2γdR (T)/3.
Feynman graphs and the large dimensional limit of multipartite entanglement

NASA Astrophysics Data System (ADS)

Di Martino, Sara; Facchi, Paolo; Florio, Giuseppe

2018-01-01

In this paper, we extend the analysis of multipartite entanglement, based on techniques from classical statistical mechanics, to a system composed of n d-level parties (qudits). We introduce a suitable partition function at a fictitious temperature with the average local purity of the system as Hamiltonian. In particular, we analyze the high-temperature expansion of this partition function, prove the convergence of the series, and study its asymptotic behavior as d → ∞. We make use of a diagrammatic technique, classify the graphs, and study their degeneracy. We are thus able to evaluate their contributions and estimate the moments of the distribution of the local purity.
SBEToolbox: A Matlab Toolbox for Biological Network Analysis

PubMed Central

Konganti, Kranti; Wang, Gang; Yang, Ence; Cai, James J.

2013-01-01

We present SBEToolbox (Systems Biology and Evolution Toolbox), an open-source Matlab toolbox for biological network analysis. It takes a network file as input, calculates a variety of centralities and topological metrics, clusters nodes into modules, and displays the network using different graph layout algorithms. Straightforward implementation and the inclusion of high-level functions allow the functionality to be easily extended or tailored through developing custom plugins. SBEGUI, a menu-driven graphical user interface (GUI) of SBEToolbox, enables easy access to various network and graph algorithms for programmers and non-programmers alike. All source code and sample data are freely available at https://github.com/biocoder/SBEToolbox/releases. PMID:24027418
SBEToolbox: A Matlab Toolbox for Biological Network Analysis.

PubMed

Konganti, Kranti; Wang, Gang; Yang, Ence; Cai, James J

2013-01-01

We present SBEToolbox (Systems Biology and Evolution Toolbox), an open-source Matlab toolbox for biological network analysis. It takes a network file as input, calculates a variety of centralities and topological metrics, clusters nodes into modules, and displays the network using different graph layout algorithms. Straightforward implementation and the inclusion of high-level functions allow the functionality to be easily extended or tailored through developing custom plugins. SBEGUI, a menu-driven graphical user interface (GUI) of SBEToolbox, enables easy access to various network and graph algorithms for programmers and non-programmers alike. All source code and sample data are freely available at https://github.com/biocoder/SBEToolbox/releases.
Characterisation of the protein corona using tunable resistive pulse sensing: determining the change and distribution of a particle's surface charge.

PubMed

Blundell, Emma L C J; Healey, Matthew J; Holton, Elizabeth; Sivakumaran, Muttuswamy; Manstana, Sarabjit; Platt, Mark

2016-08-01

The zeta potential of the protein corona around carboxyl particles has been measured using tunable resistive pulse sensing (TRPS). A simple and rapid assay for characterising zeta potentials within buffer, serum and plasma is presented monitoring the change, magnitude and distribution of proteins on the particle surface. First, we measure the change in zeta potential of carboxyl-functionalised nanoparticles in solutions that contain biologically relevant concentrations of individual proteins, typically constituted in plasma and serum, and observe a significant difference in distributions and zeta values between room temperature and 37 °C assays. The effect is protein dependent, and the largest difference between the two temperatures is recorded for the γ-globulin protein where the mean zeta potential changes from -16.7 to -9.0 mV for 25 and 37 °C, respectively. This method is further applied to monitor particles placed into serum and/or plasma. A temperature-dependent change is again observed with serum showing a 4.9 mV difference in zeta potential between samples incubated at 25 and 37 °C; this shift was larger than that observed for samples in plasma (0.4 mV). Finally, we monitor the kinetics of the corona reorientation for particles initially placed into serum and then adding 5 % (V/V) plasma. The technology presented offers an interesting insight into protein corona structure and kinetics of formation measured in biologically relevant solutions, i.e. high protein, high salt levels, and its particle-by-particle analysis gives a measure of the distribution of particle zeta potential that may offer a better understanding of the behaviour of nanoparticles in solution. Graphical Abstract The relative velocity of a nanoparticle as it traverses a nanopore can be used to determine its zeta potential. Monitoring the changes in translocation speeds can therefore be used to follow changes to the surface chemistry/composition of 210 nm particles that were placed into protein rich solutions, serum and plasma. The particle-by-particle measurements allow the zeta potential and distribution of the particles to be characterised, illustrating the effects of protein concentration and temperature on the protein corona. When placed into a solution containing a mixture of proteins, the affinity of the protein to the particle's surface determines the corona structure, and is not dependent on the protein concentration.
Parallel habitat acclimatization is realized by the expression of different genes in two closely related salamander species (genus Salamandra).

PubMed

Goedbloed, D J; Czypionka, T; Altmüller, J; Rodriguez, A; Küpfer, E; Segev, O; Blaustein, L; Templeton, A R; Nolte, A W; Steinfartz, S

2017-12-01

The utilization of similar habitats by different species provides an ideal opportunity to identify genes underlying adaptation and acclimatization. Here, we analysed the gene expression of two closely related salamander species: Salamandra salamandra in Central Europe and Salamandra infraimmaculata in the Near East. These species inhabit similar habitat types: 'temporary ponds' and 'permanent streams' during larval development. We developed two species-specific gene expression microarrays, each targeting over 12 000 transcripts, including an overlapping subset of 8331 orthologues. Gene expression was examined for systematic differences between temporary ponds and permanent streams in larvae from both salamander species to establish gene sets and functions associated with these two habitat types. Only 20 orthologues were associated with a habitat in both species, but these orthologues did not show parallel expression patterns across species more than expected by chance. Functional annotation of a set of 106 genes with the highest effect size for a habitat suggested four putative gene function categories associated with a habitat in both species: cell proliferation, neural development, oxygen responses and muscle capacity. Among these high effect size genes was a single orthologue (14-3-3 protein zeta/YWHAZ) that was downregulated in temporary ponds in both species. The emergence of four gene function categories combined with a lack of parallel expression of orthologues (except 14-3-3 protein zeta) suggests that parallel habitat adaptation or acclimatization by larvae from S. salamandra and S. infraimmaculata to temporary ponds and permanent streams is mainly realized by different genes with a converging functionality.
A graph-based approach for the retrieval of multi-modality medical images.

PubMed

Kumar, Ashnil; Kim, Jinman; Wen, Lingfeng; Fulham, Michael; Feng, Dagan

2014-02-01

In this paper, we address the retrieval of multi-modality medical volumes, which consist of two different imaging modalities, acquired sequentially, from the same scanner. One such example, positron emission tomography and computed tomography (PET-CT), provides physicians with complementary functional and anatomical features as well as spatial relationships and has led to improved cancer diagnosis, localisation, and staging. The challenge of multi-modality volume retrieval for cancer patients lies in representing the complementary geometric and topologic attributes between tumours and organs. These attributes and relationships, which are used for tumour staging and classification, can be formulated as a graph. It has been demonstrated that graph-based methods have high accuracy for retrieval by spatial similarity. However, naïvely representing all relationships on a complete graph obscures the structure of the tumour-anatomy relationships. We propose a new graph structure derived from complete graphs that structurally constrains the edges connected to tumour vertices based upon the spatial proximity of tumours and organs. This enables retrieval on the basis of tumour localisation. We also present a similarity matching algorithm that accounts for different feature sets for graph elements from different imaging modalities. Our method emphasises the relationships between a tumour and related organs, while still modelling patient-specific anatomical variations. Constraining tumours to related anatomical structures improves the discrimination potential of graphs, making it easier to retrieve similar images based on tumour location. We evaluated our retrieval methodology on a dataset of clinical PET-CT volumes. Our results showed that our method enabled the retrieval of multi-modality images using spatial features. Our graph-based retrieval algorithm achieved a higher precision than several other retrieval techniques: gray-level histograms as well as state-of-the-art methods such as visual words using the scale- invariant feature transform (SIFT) and relational matrices representing the spatial arrangements of objects. Copyright © 2013 Elsevier B.V. All rights reserved.

The evolution of grain mantles and silicate dust growth at high redshift

NASA Astrophysics Data System (ADS)

Ceccarelli, Cecilia; Viti, Serena; Balucani, Nadia; Taquet, Vianney

2018-05-01

In dense molecular clouds, interstellar grains are covered by mantles of iced molecules. The formation of the grain mantles has two important consequences: it removes species from the gas phase and promotes the synthesis of new molecules on the grain surfaces. The composition of the mantle is a strong function of the environment that the cloud belongs to. Therefore, clouds in high-zeta galaxies, where conditions - like temperature, metallicity, and cosmic ray flux - are different from those in the Milky Way, will have different grain mantles. In the last years, several authors have suggested that silicate grains might grow by accretion of silicon-bearing species on smaller seeds. This would occur simultaneously with the formation of the iced mantles and be greatly affected by its composition as a function of time. In this work, we present a numerical study of the grain mantle formation in high-zeta galaxies, and we quantitatively address the possibility of silicate growth. We find that the mantle thickness decreases with increasing redshift, from about 120 to 20 layers for z varying from 0 to 8. Furthermore, the mantle composition is also a strong function of the cloud redshift, with the relative importance of CO, CO2, ammonia, methane, and methanol highly varying with z. Finally, being Si-bearing species always a very minor component of the mantle, the formation of silicates in molecular clouds is practically impossible.
EEG sensorimotor rhythms' variation and functional connectivity measures during motor imagery: linear relations and classification approaches.

PubMed

Stefano Filho, Carlos A; Attux, Romis; Castellano, Gabriela

2017-01-01

Hands motor imagery (MI) has been reported to alter synchronization patterns amongst neurons, yielding variations in the mu and beta bands' power spectral density (PSD) of the electroencephalography (EEG) signal. These alterations have been used in the field of brain-computer interfaces (BCI), in an attempt to assign distinct MI tasks to commands of such a system. Recent studies have highlighted that information may be missing if knowledge about brain functional connectivity is not considered. In this work, we modeled the brain as a graph in which each EEG electrode represents a node. Our goal was to understand if there exists any linear correlation between variations in the synchronization patterns-that is, variations in the PSD of mu and beta bands-induced by MI and alterations in the corresponding functional networks. Moreover, we (1) explored the feasibility of using functional connectivity parameters as features for a classifier in the context of an MI-BCI; (2) investigated three different types of feature selection (FS) techniques; and (3) compared our approach to a more traditional method using the signal PSD as classifier inputs. Ten healthy subjects participated in this study. We observed significant correlations ( p < 0.05) with values ranging from 0.4 to 0.9 between PSD variations and functional network alterations for some electrodes, prominently in the beta band. The PSD method performed better for data classification, with mean accuracies of (90 ± 8)% and (87 ± 7)% for the mu and beta band, respectively, versus (83 ± 8)% and (83 ± 7)% for the same bands for the graph method. Moreover, the number of features for the graph method was considerably larger. However, results for both methods were relatively close, and even overlapped when the uncertainties of the accuracy rates were considered. Further investigation regarding a careful exploration of other graph metrics may provide better alternatives.
Single-chain antigen recognition receptors that costimulate potent rejection of established experimental tumors.

PubMed

Haynes, Nicole M; Trapani, Joseph A; Teng, Michèle W L; Jackson, Jacob T; Cerruti, Loretta; Jane, Stephen M; Kershaw, Michael H; Smyth, Mark J; Darcy, Phillip K

2002-11-01

Tumor cells are usually weakly immunogenic as they largely express self-antigens and can down-regulate major histocompatability complex/peptide molecules and critical costimulatory ligands. The challenge for immunotherapies has been to provide vigorous immune effector cells that circumvent these tumor escape mechanisms and eradicate established tumors. One promising approach is to engineer T cells with single-chain antibody receptors, and since T cells require 2 distinct signals for optimal activation, we have compared the therapeutic efficacy of erbB2-reactive chimeric receptors that contain either T-cell receptor zeta (TCR-zeta) or CD28/TCR-zeta signaling domains. We have demonstrated that primary mouse CD8(+) T lymphocytes expressing the single-chain Fv (scFv)-CD28-zeta receptor have a greater capacity to secrete Tc1 cytokines, induce T-cell proliferation, and inhibit established tumor growth and metastases in vivo. The suppression of established tumor burden by cytotoxic T cells expressing the CD28/TCR-zeta chimera was critically dependent upon their interferon gamma (IFN-gamma) secretion. Our study has illustrated the practical advantage of engineering a T-cell signaling complex that codelivers CD28 activation, dependent only upon the tumor's expression of the appropriate tumor associated antigen.
Influence of the Dukhin and Reynolds numbers on the apparent zeta potential of granular porous media.

PubMed

Crespy, A; Bolève, A; Revil, A

2007-01-01

The Helmholtz-Smoluchowski (HS) equation is widely used to determine the apparent zeta potential of porous materials using the streaming potential method. We present a model able to correct this apparent zeta potential of granular media of the influence of the Dukhin and Reynolds numbers. The Dukhin number represents the ratio between the surface conductivity (mainly occurring in the Stern layer) and the pore water conductivity. The Reynolds number represents the ratio between inertial and viscous forces in the Navier-Stokes equation. We show here that the HS equation can lead to serious errors if it is used to predict the dependence of zeta potential on flow in the inertial laminar flow regime without taking into account these corrections. For indifferent 1:1 electrolytes (such as sodium chloride), we derived two simple scaling laws for the dependence of the streaming potential coupling coefficient (or the apparent zeta potential) on the Dukhin and Reynolds numbers. Our model is compared with a new set of experimental data obtained on glass bead packs saturated with NaCl solutions at different salinities and pH. We find fairly good agreement between the model and these experimental data.
Rule-based graph theory to enable exploration of the space system architecture design space

NASA Astrophysics Data System (ADS)

Arney, Dale Curtis

The primary goal of this research is to improve upon system architecture modeling in order to enable the exploration of design space options. A system architecture is the description of the functional and physical allocation of elements and the relationships, interactions, and interfaces between those elements necessary to satisfy a set of constraints and requirements. The functional allocation defines the functions that each system (element) performs, and the physical allocation defines the systems required to meet those functions. Trading the functionality between systems leads to the architecture-level design space that is available to the system architect. The research presents a methodology that enables the modeling of complex space system architectures using a mathematical framework. To accomplish the goal of improved architecture modeling, the framework meets five goals: technical credibility, adaptability, flexibility, intuitiveness, and exhaustiveness. The framework is technically credible, in that it produces an accurate and complete representation of the system architecture under consideration. The framework is adaptable, in that it provides the ability to create user-specified locations, steady states, and functions. The framework is flexible, in that it allows the user to model system architectures to multiple destinations without changing the underlying framework. The framework is intuitive for user input while still creating a comprehensive mathematical representation that maintains the necessary information to completely model complex system architectures. Finally, the framework is exhaustive, in that it provides the ability to explore the entire system architecture design space. After an extensive search of the literature, graph theory presents a valuable mechanism for representing the flow of information or vehicles within a simple mathematical framework. Graph theory has been used in developing mathematical models of many transportation and network flow problems in the past, where nodes represent physical locations and edges represent the means by which information or vehicles travel between those locations. In space system architecting, expressing the physical locations (low-Earth orbit, low-lunar orbit, etc.) and steady states (interplanetary trajectory) as nodes and the different means of moving between the nodes (propulsive maneuvers, etc.) as edges formulates a mathematical representation of this design space. The selection of a given system architecture using graph theory entails defining the paths that the systems take through the space system architecture graph. A path through the graph is defined as a list of edges that are traversed, which in turn defines functions performed by the system. A structure to compactly represent this information is a matrix, called the system map, in which the column indices are associated with the systems that exist and row indices are associated with the edges, or functions, to which each system has access. Several contributions have been added to the state of the art in space system architecture analysis. The framework adds the capability to rapidly explore the design space without the need to limit trade options or the need for user interaction during the exploration process. The unique mathematical representation of a system architecture, through the use of the adjacency, incidence, and system map matrices, enables automated design space exploration using stochastic optimization processes. The innovative rule-based graph traversal algorithm ensures functional feasibility of each system architecture that is analyzed, and the automatic generation of the system hierarchy eliminates the need for the user to manually determine the relationships between systems during or before the design space exploration process. Finally, the rapid evaluation of system architectures for various mission types enables analysis of the system architecture design space for multiple destinations within an evolutionary exploration program. (Abstract shortened by UMI.).
Automatic segmentation of pulmonary fissures in x-ray CT images using anatomic guidance

NASA Astrophysics Data System (ADS)

Ukil, Soumik; Sonka, Milan; Reinhardt, Joseph M.

2006-03-01

The pulmonary lobes are the five distinct anatomic divisions of the human lungs. The physical boundaries between the lobes are called the lobar fissures. Detection of lobar fissure positions in pulmonary X-ray CT images is of increasing interest for the early detection of pathologies, and also for the regional functional analysis of the lungs. We have developed a two-step automatic method for the accurate segmentation of the three pulmonary fissures. In the first step, an approximation of the actual fissure locations is made using a 3-D watershed transform on the distance map of the segmented vasculature. Information from the anatomically labeled human airway tree is used to guide the watershed segmentation. These approximate fissure boundaries are then used to define the region of interest (ROI) for a more exact 3-D graph search to locate the fissures. Within the ROI the fissures are enhanced by computing a ridgeness measure, and this is used as the cost function for the graph search. The fissures are detected as the optimal surface within the graph defined by the cost function, which is computed by transforming the problem to the problem of finding a minimum s-t cut on a derived graph. The accuracy of the lobar borders is assessed by comparing the automatic results to manually traced lobe segments. The mean distance error between manually traced and computer detected left oblique, right oblique and right horizontal fissures is 2.3 +/- 0.8 mm, 2.3 +/- 0.7 mm and 1.0 +/- 0.1 mm, respectively.
The Influence of Preprocessing Steps on Graph Theory Measures Derived from Resting State fMRI

PubMed Central

Gargouri, Fatma; Kallel, Fathi; Delphine, Sebastien; Ben Hamida, Ahmed; Lehéricy, Stéphane; Valabregue, Romain

2018-01-01

Resting state functional MRI (rs-fMRI) is an imaging technique that allows the spontaneous activity of the brain to be measured. Measures of functional connectivity highly depend on the quality of the BOLD signal data processing. In this study, our aim was to study the influence of preprocessing steps and their order of application on small-world topology and their efficiency in resting state fMRI data analysis using graph theory. We applied the most standard preprocessing steps: slice-timing, realign, smoothing, filtering, and the tCompCor method. In particular, we were interested in how preprocessing can retain the small-world economic properties and how to maximize the local and global efficiency of a network while minimizing the cost. Tests that we conducted in 54 healthy subjects showed that the choice and ordering of preprocessing steps impacted the graph measures. We found that the csr (where we applied realignment, smoothing, and tCompCor as a final step) and the scr (where we applied realignment, tCompCor and smoothing as a final step) strategies had the highest mean values of global efficiency (eg). Furthermore, we found that the fscr strategy (where we applied realignment, tCompCor, smoothing, and filtering as a final step), had the highest mean local efficiency (el) values. These results confirm that the graph theory measures of functional connectivity depend on the ordering of the processing steps, with the best results being obtained using smoothing and tCompCor as the final steps for global efficiency with additional filtering for local efficiency. PMID:29497372
The Influence of Preprocessing Steps on Graph Theory Measures Derived from Resting State fMRI.

PubMed

Gargouri, Fatma; Kallel, Fathi; Delphine, Sebastien; Ben Hamida, Ahmed; Lehéricy, Stéphane; Valabregue, Romain

2018-01-01

Resting state functional MRI (rs-fMRI) is an imaging technique that allows the spontaneous activity of the brain to be measured. Measures of functional connectivity highly depend on the quality of the BOLD signal data processing. In this study, our aim was to study the influence of preprocessing steps and their order of application on small-world topology and their efficiency in resting state fMRI data analysis using graph theory. We applied the most standard preprocessing steps: slice-timing, realign, smoothing, filtering, and the tCompCor method. In particular, we were interested in how preprocessing can retain the small-world economic properties and how to maximize the local and global efficiency of a network while minimizing the cost. Tests that we conducted in 54 healthy subjects showed that the choice and ordering of preprocessing steps impacted the graph measures. We found that the csr (where we applied realignment, smoothing, and tCompCor as a final step) and the scr (where we applied realignment, tCompCor and smoothing as a final step) strategies had the highest mean values of global efficiency (eg) . Furthermore, we found that the fscr strategy (where we applied realignment, tCompCor, smoothing, and filtering as a final step), had the highest mean local efficiency (el) values. These results confirm that the graph theory measures of functional connectivity depend on the ordering of the processing steps, with the best results being obtained using smoothing and tCompCor as the final steps for global efficiency with additional filtering for local efficiency.
Graph theoretical modeling of baby brain networks.

PubMed

Zhao, Tengda; Xu, Yuehua; He, Yong

2018-06-12

The human brain undergoes explosive growth during the prenatal period and the first few postnatal years, establishing an early infrastructure for the later development of behaviors and cognitions. Revealing the developmental rules during the early phrase is essential in understanding the emergence of brain function and the origin of developmental disorders. The graph-theoretical network modeling in combination with multiple neuroimaging probes provides an important research framework to explore early development of the topological wiring and organizational paradigms of the brain. Here, we reviewed studies which employed neuroimaging and graph-theoretical modeling to investigate brain network development from approximately 20 gestational weeks to 2 years of age. Specifically, the structural and functional brain networks have evolved to highly efficient topological architectures in the early stage; where the structural network remains ahead and paves the way for the development of functional network. The brain network develops in a heterogeneous order, from primary to higher-order systems and from a tendency of network segregation to network integration in the prenatal and postnatal periods. The early brain network topologies show abilities in predicting certain cognitive and behavior performance in later life, and their impairments are likely to continue into childhood and even adulthood. These macroscopic topological changes are found to be associated with possible microstructural maturations, such as axonal growth and myelinations. Collectively, this review provides a detailed delineation of the early changes of the baby brains in the graph-theoretical modeling framework, which opens up a new avenue to understand the developmental principles of the connectome. Copyright © 2018. Published by Elsevier Inc.
Curvature of Super Diff(S/sup 1/)/S/sup 1/

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oh, P.; Ramond, P.

Motivated by the work of Bowick and Rajeev, we calculate the curvature of the infinite-dimensional flag manifolds DiffS/sup 1//S/sup 1/ and Super DiffS/sup 1//S/sup 1/ using standard finite-dimensional coset space techniques. We regularize the infinity by zeta-function regularization and recover the conformal and superconformal anomalies respectively for a specific choice of the torsion.
Integrating atlas and graph cut methods for right ventricle blood-pool segmentation from cardiac cine MRI

NASA Astrophysics Data System (ADS)

Dangi, Shusil; Linte, Cristian A.

2017-03-01

Segmentation of right ventricle from cardiac MRI images can be used to build pre-operative anatomical heart models to precisely identify regions of interest during minimally invasive therapy. Furthermore, many functional parameters of right heart such as right ventricular volume, ejection fraction, myocardial mass and thickness can also be assessed from the segmented images. To obtain an accurate and computationally efficient segmentation of right ventricle from cardiac cine MRI, we propose a segmentation algorithm formulated as an energy minimization problem in a graph. Shape prior obtained by propagating label from an average atlas using affine registration is incorporated into the graph framework to overcome problems in ill-defined image regions. The optimal segmentation corresponding to the labeling with minimum energy configuration of the graph is obtained via graph-cuts and is iteratively refined to produce the final right ventricle blood pool segmentation. We quantitatively compare the segmentation results obtained from our algorithm to the provided gold-standard expert manual segmentation for 16 cine-MRI datasets available through the MICCAI 2012 Cardiac MR Right Ventricle Segmentation Challenge according to several similarity metrics, including Dice coefficient, Jaccard coefficient, Hausdorff distance, and Mean absolute distance error.
Probabilistic graphs as a conceptual and computational tool in hydrology and water management

NASA Astrophysics Data System (ADS)

Schoups, Gerrit

2014-05-01

Originally developed in the fields of machine learning and artificial intelligence, probabilistic graphs constitute a general framework for modeling complex systems in the presence of uncertainty. The framework consists of three components: 1. Representation of the model as a graph (or network), with nodes depicting random variables in the model (e.g. parameters, states, etc), which are joined together by factors. Factors are local probabilistic or deterministic relations between subsets of variables, which, when multiplied together, yield the joint distribution over all variables. 2. Consistent use of probability theory for quantifying uncertainty, relying on basic rules of probability for assimilating data into the model and expressing unknown variables as a function of observations (via the posterior distribution). 3. Efficient, distributed approximation of the posterior distribution using general-purpose algorithms that exploit model structure encoded in the graph. These attributes make probabilistic graphs potentially useful as a conceptual and computational tool in hydrology and water management (and beyond). Conceptually, they can provide a common framework for existing and new probabilistic modeling approaches (e.g. by drawing inspiration from other fields of application), while computationally they can make probabilistic inference feasible in larger hydrological models. The presentation explores, via examples, some of these benefits.
Graph theory findings in the pathophysiology of temporal lobe epilepsy

PubMed Central

Chiang, Sharon; Haneef, Zulfi

2014-01-01

Temporal lobe epilepsy (TLE) is the most common form of adult epilepsy. Accumulating evidence has shown that TLE is a disorder of abnormal epileptogenic networks, rather than focal sources. Graph theory allows for a network-based representation of TLE brain networks, and has potential to illuminate characteristics of brain topology conducive to TLE pathophysiology, including seizure initiation and spread. We review basic concepts which we believe will prove helpful in interpreting results rapidly emerging from graph theory research in TLE. In addition, we summarize the current state of graph theory findings in TLE as they pertain its pathophysiology. Several common findings have emerged from the many modalities which have been used to study TLE using graph theory, including structural MRI, diffusion tensor imaging, surface EEG, intracranial EEG, magnetoencephalography, functional MRI, cell cultures, simulated models, and mouse models, involving increased regularity of the interictal network configuration, altered local segregation and global integration of the TLE network, and network reorganization of temporal lobe and limbic structures. As different modalities provide different views of the same phenomenon, future studies integrating data from multiple modalities are needed to clarify findings and contribute to the formation of a coherent theory on the pathophysiology of TLE. PMID:24831083
Minimum nonuniform graph partitioning with unrelated weights

NASA Astrophysics Data System (ADS)

Makarychev, K. S.; Makarychev, Yu S.

2017-12-01

We give a bi-criteria approximation algorithm for the Minimum Nonuniform Graph Partitioning problem, recently introduced by Krauthgamer, Naor, Schwartz and Talwar. In this problem, we are given a graph G=(V,E) and k numbers ρ_1,\\dots, ρ_k. The goal is to partition V into k disjoint sets (bins) P_1,\\dots, P_k satisfying \\vert P_i\\vert≤ ρi \\vert V\\vert for all i, so as to minimize the number of edges cut by the partition. Our bi-criteria algorithm gives an O(\\sqrt{log \\vert V\\vert log k}) approximation for the objective function in general graphs and an O(1) approximation in graphs excluding a fixed minor. The approximate solution satisfies the relaxed capacity constraints \\vert P_i\\vert ≤ (5+ \\varepsilon)ρi \\vert V\\vert. This algorithm is an improvement upon the O(log \\vert V\\vert)-approximation algorithm by Krauthgamer, Naor, Schwartz and Talwar. We extend our results to the case of 'unrelated weights' and to the case of 'unrelated d-dimensional weights'. A preliminary version of this work was presented at the 41st International Colloquium on Automata, Languages and Programming (ICALP 2014). Bibliography: 7 titles.
Coloring geographical threshold graphs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bradonjic, Milan; Percus, Allon; Muller, Tobias

We propose a coloring algorithm for sparse random graphs generated by the geographical threshold graph (GTG) model, a generalization of random geometric graphs (RGG). In a GTG, nodes are distributed in a Euclidean space, and edges are assigned according to a threshold function involving the distance between nodes as well as randomly chosen node weights. The motivation for analyzing this model is that many real networks (e.g., wireless networks, the Internet, etc.) need to be studied by using a 'richer' stochastic model (which in this case includes both a distance between nodes and weights on the nodes). Here, we analyzemore » the GTG coloring algorithm together with the graph's clique number, showing formally that in spite of the differences in structure between GTG and RGG, the asymptotic behavior of the chromatic number is identical: {chi}1n 1n n / 1n n (1 + {omicron}(1)). Finally, we consider the leading corrections to this expression, again using the coloring algorithm and clique number to provide bounds on the chromatic number. We show that the gap between the lower and upper bound is within C 1n n / (1n 1n n){sup 2}, and specify the constant C.« less
Precalculus teachers' perspectives on using graphing calculators: an example from one curriculum

NASA Astrophysics Data System (ADS)

Karadeniz, Ilyas; Thompson, Denisse R.

2018-01-01

Graphing calculators are hand-held technological tools currently used in mathematics classrooms. Teachers' perspectives on using graphing calculators are important in terms of exploring what teachers think about using such technology in advanced mathematics courses, particularly precalculus courses. A descriptive intrinsic case study was conducted to analyse the perspectives of 11 teachers using graphing calculators with potential Computer Algebra System (CAS) capability while teaching Functions, Statistics, and Trigonometry, a precalculus course for 11th-grade students developed by the University of Chicago School Mathematics Project. Data were collected from multiple sources as part of a curriculum evaluation study conducted during the 2007-2008 school year. Although all teachers were using the same curriculum that integrated CAS into the instructional materials, teachers had mixed views about the technology. Graphing calculator features were used much more than CAS features, with many teachers concerned about the use of CAS because of pressures from external assessments. In addition, several teachers found it overwhelming to learn a new technology at the same time they were learning a new curriculum. The results have implications for curriculum developers and others working with teachers to update curriculum and the use of advanced technologies simultaneously.
A Glimpse into Secondary Students' Understanding of Functions

ERIC Educational Resources Information Center

Brendefur, Jonathan L.; Hughes, Gwyneth; Ely, Robert

2015-01-01

In this article we examine how secondary school students think about functional relationships. More specifically, we examined seven students' intuitive knowledge in regards to representing two real-world situations with functions. We found students do not tend to represent functional relationships with coordinate graphs even though they are able…
Abnormalities of functional brain networks in pathological gambling: a graph-theoretical approach

PubMed Central

Tschernegg, Melanie; Crone, Julia S.; Eigenberger, Tina; Schwartenbeck, Philipp; Fauth-Bühler, Mira; Lemènager, Tagrid; Mann, Karl; Thon, Natasha; Wurst, Friedrich M.; Kronbichler, Martin

2013-01-01

Functional neuroimaging studies of pathological gambling (PG) demonstrate alterations in frontal and subcortical regions of the mesolimbic reward system. However, most investigations were performed using tasks involving reward processing or executive functions. Little is known about brain network abnormalities during task-free resting state in PG. In the present study, graph-theoretical methods were used to investigate network properties of resting state functional magnetic resonance imaging data in PG. We compared 19 patients with PG to 19 healthy controls (HCs) using the Graph Analysis Toolbox (GAT). None of the examined global metrics differed between groups. At the nodal level, pathological gambler showed a reduced clustering coefficient in the left paracingulate cortex and the left juxtapositional lobe (supplementary motor area, SMA), reduced local efficiency in the left SMA, as well as an increased node betweenness for the left and right paracingulate cortex and the left SMA. At an uncorrected threshold level, the node betweenness in the left inferior frontal gyrus was decreased and increased in the caudate. Additionally, increased functional connectivity between fronto-striatal regions and within frontal regions has also been found for the gambling patients. These findings suggest that regions associated with the reward system demonstrate reduced segregation but enhanced integration while regions associated with executive functions demonstrate reduced integration. The present study makes evident that PG is also associated with abnormalities in the topological network structure of the brain during rest. Since alterations in PG cannot be explained by direct effects of abused substances on the brain, these findings will be of relevance for understanding functional connectivity in other addictive disorders. PMID:24098282
Corrections Regarding the Impedance of Distance Functions for Several g(d) Functions

ERIC Educational Resources Information Center

Beaman, Jay

1976-01-01

Five functions were introduced for modeling travel behavior in the Beaman article "Distance and the 'Reaction' to Distance as a Function of Distance" published in Vol. 6, No. 3 of "Journal of Leisure Research" with the graphs of the functions printed incorrectly. This is a corrected version. (MM)
Super (a*, d*)-ℋ-antimagic total covering of second order of shackle graphs

NASA Astrophysics Data System (ADS)

Hesti Agustin, Ika; Dafik; Nisviasari, Rosanita; Prihandini, R. M.

2017-12-01

Let H be a simple and connected graph. A shackle of graph H, denoted by G = shack(H, v, n), is a graph G constructed by non-trivial graphs H 1, H 2, …, H n such that, for every 1 ≤ s, t ≤ n, H s and Ht have no a common vertex with |s - t| ≥ 2 and for every 1 ≤ i ≤ n - 1, Hi and H i+1 share exactly one common vertex v, called connecting vertex, and those k - 1 connecting vertices are all distinct. The graph G is said to be an (a*, d*)-H-antimagic total graph of second order if there exist a bijective function f : V(G) ∪ E(G) → {1, 2, …, |V(G)| + |E(G)|} such that for all subgraphs isomorphic to H, the total H-weights W(H)=\\displaystyle {\\sum }v\\in V(H)f(v)+\\displaystyle {\\sum }e\\in E(H)f(e) form an arithmetic sequence of second order of \\{a* ,a* +d* ,a* +3d* ,a* +6d* ,\\ldots ,a* +(\\frac{{n}2-n}{2})d* \\}, where a* and d* are positive integers and n is the number of all subgraphs isomorphic to H. An (a*, d*)-H-antimagic total labeling of second order f is called super if the smallest labels appear in the vertices. In this paper, we study a super (a*, d*)-H antimagic total labeling of second order of G = shack(H, v, n) by using a partition technique of second order.

A simple proof of a lemma of Coleman

NASA Astrophysics Data System (ADS)

Saikia, A.

2001-03-01

Let p be an odd prime. The results in this paper concern the units of the infinite extension of Qp generated by all p-power roots of unity. Letformula herewhere [mu]pn+1 denote the pn+1th roots of 1. Let [script p]n be the maximal ideal of the ring of integers of [Phi]n and let Un be the units congruent to 1 modulo [script p]n.Let [zeta]n be a fixed primitive pn+1th root of unity such that [zeta]pn = [zeta]n [minus sign] 1, [for all]n [gt-or-equal, slanted] 1. Put [pi]n = [zeta]n [minus sign] 1. Thus [pi]n is a local parameter for [Phi]n. Letformula hereKummer already exploited the obvious fact that every u0 [set membership] U0 can be written in the formformula herewhere f0(T) is some power series in Zp[[T
Genetically engineered T cells to target EGFRvIII expressing glioblastoma.

PubMed

Bullain, Szofia S; Sahin, Ayguen; Szentirmai, Oszkar; Sanchez, Carlos; Lin, Ning; Baratta, Elizabeth; Waterman, Peter; Weissleder, Ralph; Mulligan, Richard C; Carter, Bob S

2009-09-01

Glioblastoma remains a significant therapeutic challenge, warranting further investigation of novel therapies. We describe an immunotherapeutic strategy to treat glioblastoma based on adoptive transfer of genetically modified T-lymphocytes (T cells) redirected to kill EGFRvIII expressing gliomas. We constructed a chimeric immune receptor (CIR) specific to EGFRvIII, (MR1-zeta). After in vitro selection and expansion, MR1-zeta genetically modified primary human T-cells specifically recognized EGFRvIII-positive tumor cells as demonstrated by IFN-gamma secretion and efficient tumor lysis compared to control CIRs defective in EGFRvIII binding (MRB-zeta) or signaling (MR1-delzeta). MR1-zeta expressing T cells also inhibited EGFRvIII-positive tumor growth in vivo in a xenografted mouse model. Successful targeting of EGFRvIII-positive tumors via adoptive transfer of genetically modified T cells may represent a new immunotherapy strategy with great potential for clinical applications.
Development of Multifunctional Nanoparticles for Cancer Therapy Applications

NASA Astrophysics Data System (ADS)

Huth, Christopher

The focus of this thesis is the functionalization and tailoring of nanoparticle surfaces to perform specific objectives in a biological environment. The nanoparticles examined include carbon nanotubes (CNTs), superparamagnetic iron oxide nanoparticles and superparamagnetic iron oxide nanocomposites. The unique nanomaterials have been developed to address continued issues in cancer therapy, including cancer diagnosis and efficient drug delivery. CNT surfaces were modified by plasma polymerization, providing functional groups for conjugation. Luminescent amine labeled quantum dots were fixed to the surface of the CNTs to aid in cancer diagnosis by in vivo imaging. Mice, injected with the quantum dot functionalized carbon nanotubes, were imaged displaying the in vivo imaging capability. In addition, the drug loading and drug release capabilities were examined by incorporating the drug paclitaxel into PLGA-coated CNTs, which showed much higher cytotoxicity to PC-3MM2 human prostate carcinoma cells compared to CNTs without paclitaxel. Paclitaxel was loaded at 112.5 microg/mg of PLGA-coated CNTs. Iron oxide nanocomposites were functionalized with quantum dots for diagnosis applications. Because the nanocomposites contain iron oxide, the nanoparticle provides the opportunity for magnetic hyperthermia, creating a unique material for diagnosis and therapy. Mice, injected with the quantum dot functionalized iron oxide nanocomposites, were imaged displaying the in vivo imaging capability. The magnetic hyperthermic property of the quantum dot functionalized nanocomposites was observed with the attainment of temperatures above 50°C during exposure to an alternating magnetic field. Thermoresponsive nanoparticles were prepared by immobilizing a 2 - 3 nm thick phospholipid layer on the surface of superparamagnetic Fe3O 4 nanoparticles via high affinity avidin/biotin interactions. Morphological and physicochemical surface properties were assessed using TEM, confocal laser scanning microscopy, differential scanning calorimetry, and ATR-FTIR. The zeta potential of Fe3O4 colloids in phosphate buffered saline (PBS) decreased from -23.6 to -5.0 mV as a consequence of phospholipid immobilization. Hyperthermia-relevant temperatures greater than 40°C were achieved within 10--15 min using a 7-mT magnetic field alternating at a frequency of 1MHz. Loading of the surface-associated phospholipid layer with the hydrophobic dye dansylcadaverine was accomplished at an efficiency of 479 ng/mg Fe3O4. Release of this drug surrogate was temperature-dependent, resulting in a 2.5-fold greater release rate when nanoparticles were exposed to temperatures above the experimentally determined melting temperature of 39.7°C. In vitro cytotoxicity studies by release of the cytotoxic drug, doxorubicin, from the thermoresponsive nanoparticles was lastly intended. However, colloidal stability became an issue, prompting a thorough review of nanoparticle stabilization. Factors affecting stabilization, including dispersant, the nanoparticle, and the thermoresponsive coating, were characterized by dynamic light scattering and zeta potential. PBS was compared to two dispersants containing lower ionic concentrations, HBSS and HEPES, using the original iron oxide nanoparticles compared to an iron oxide nanocomposite. The nanocomposite in the HEPES buffer displayed the greatest stability with a zeta potential of -30.47 mV and particle size of 155.4 nm. Stabilization of the immobilized phospholipid bilayer was examined with and without incorporation of the cationic lipid stearylamine. Zeta potential (33.6 mV) and size (315 nm) data indicate that stearylamine incorporated DPPC coated nanoparticles provide better stability.
CONSTRUCTING AND DERIVING RECIPROCAL TRIGONOMETRIC RELATIONS: A FUNCTIONAL ANALYTIC APPROACH

PubMed Central

Ninness, Chris; Dixon, Mark; Barnes-Holmes, Dermot; Rehfeldt, Ruth Anne; Rumph, Robin; McCuller, Glen; Holland, James; Smith, Ronald; Ninness, Sharon K; McGinty, Jennifer

2009-01-01

Participants were pretrained and tested on mutually entailed trigonometric relations and combinatorially entailed relations as they pertained to positive and negative forms of sine, cosine, secant, and cosecant. Experiment 1 focused on training and testing transformations of these mathematical functions in terms of amplitude and frequency followed by tests of novel relations. Experiment 2 addressed training in accordance with frames of coordination (same as) and frames of opposition (reciprocal of) followed by more tests of novel relations. All assessments of derived and novel formula-to-graph relations, including reciprocal functions with diversified amplitude and frequency transformations, indicated that all 4 participants demonstrated substantial improvement in their ability to identify increasingly complex trigonometric formula-to-graph relations pertaining to same as and reciprocal of to establish mathematically complex repertoires. PMID:19949509
Constructing and deriving reciprocal trigonometric relations: a functional analytic approach.

PubMed

Ninness, Chris; Dixon, Mark; Barnes-Holmes, Dermot; Rehfeldt, Ruth Anne; Rumph, Robin; McCuller, Glen; Holland, James; Smith, Ronald; Ninness, Sharon K; McGinty, Jennifer

2009-01-01

Participants were pretrained and tested on mutually entailed trigonometric relations and combinatorially entailed relations as they pertained to positive and negative forms of sine, cosine, secant, and cosecant. Experiment 1 focused on training and testing transformations of these mathematical functions in terms of amplitude and frequency followed by tests of novel relations. Experiment 2 addressed training in accordance with frames of coordination (same as) and frames of opposition (reciprocal of) followed by more tests of novel relations. All assessments of derived and novel formula-to-graph relations, including reciprocal functions with diversified amplitude and frequency transformations, indicated that all 4 participants demonstrated substantial improvement in their ability to identify increasingly complex trigonometric formula-to-graph relations pertaining to same as and reciprocal of to establish mathematically complex repertoires.
A study of structural properties of gene network graphs for mathematical modeling of integrated mosaic gene networks.

PubMed

Petrovskaya, Olga V; Petrovskiy, Evgeny D; Lavrik, Inna N; Ivanisenko, Vladimir A

2017-04-01

Gene network modeling is one of the widely used approaches in systems biology. It allows for the study of complex genetic systems function, including so-called mosaic gene networks, which consist of functionally interacting subnetworks. We conducted a study of a mosaic gene networks modeling method based on integration of models of gene subnetworks by linear control functionals. An automatic modeling of 10,000 synthetic mosaic gene regulatory networks was carried out using computer experiments on gene knockdowns/knockouts. Structural analysis of graphs of generated mosaic gene regulatory networks has revealed that the most important factor for building accurate integrated mathematical models, among those analyzed in the study, is data on expression of genes corresponding to the vertices with high properties of centrality.
Automatic Nanodesign Using Evolutionary Techniques

NASA Technical Reports Server (NTRS)

Globus, Al; Saini, Subhash (Technical Monitor)

1998-01-01

Many problems associated with the development of nanotechnology require custom designed molecules. We use genetic graph software, a new development, to automatically evolve molecules of interest when only the requirements are known. Genetic graph software designs molecules, and potentially nanoelectronic circuits, given a fitness function that determines which of two molecules is better. A set of molecules, the first generation, is generated at random then tested with the fitness function, Subsequent generations are created by randomly choosing two parent molecules with a bias towards high scoring molecules, tearing each molecules in two at random, and mating parts from the mother and father to create two children. This procedure is repeated until a satisfactory molecule is found. An atom pair similarity test is currently used as the fitness function to evolve molecules similar to existing pharmaceuticals.
Heuristic-driven graph wavelet modeling of complex terrain

NASA Astrophysics Data System (ADS)

Cioacǎ, Teodor; Dumitrescu, Bogdan; Stupariu, Mihai-Sorin; Pǎtru-Stupariu, Ileana; Nǎpǎrus, Magdalena; Stoicescu, Ioana; Peringer, Alexander; Buttler, Alexandre; Golay, François

2015-03-01

We present a novel method for building a multi-resolution representation of large digital surface models. The surface points coincide with the nodes of a planar graph which can be processed using a critically sampled, invertible lifting scheme. To drive the lazy wavelet node partitioning, we employ an attribute aware cost function based on the generalized quadric error metric. The resulting algorithm can be applied to multivariate data by storing additional attributes at the graph's nodes. We discuss how the cost computation mechanism can be coupled with the lifting scheme and examine the results by evaluating the root mean square error. The algorithm is experimentally tested using two multivariate LiDAR sets representing terrain surface and vegetation structure with different sampling densities.
Kernel approach to molecular similarity based on iterative graph similarity.

PubMed

Rupp, Matthias; Proschak, Ewgenij; Schneider, Gisbert

2007-01-01

Similarity measures for molecules are of basic importance in chemical, biological, and pharmaceutical applications. We introduce a molecular similarity measure defined directly on the annotated molecular graph, based on iterative graph similarity and optimal assignments. We give an iterative algorithm for the computation of the proposed molecular similarity measure, prove its convergence and the uniqueness of the solution, and provide an upper bound on the required number of iterations necessary to achieve a desired precision. Empirical evidence for the positive semidefiniteness of certain parametrizations of our function is presented. We evaluated our molecular similarity measure by using it as a kernel in support vector machine classification and regression applied to several pharmaceutical and toxicological data sets, with encouraging results.
Figure-ground segmentation based on class-independent shape priors

NASA Astrophysics Data System (ADS)

Li, Yang; Liu, Yang; Liu, Guojun; Guo, Maozu

2018-01-01

We propose a method to generate figure-ground segmentation by incorporating shape priors into the graph-cuts algorithm. Given an image, we first obtain a linear representation of an image and then apply directional chamfer matching to generate class-independent, nonparametric shape priors, which provide shape clues for the graph-cuts algorithm. We then enforce shape priors in a graph-cuts energy function to produce object segmentation. In contrast to previous segmentation methods, the proposed method shares shape knowledge for different semantic classes and does not require class-specific model training. Therefore, the approach obtains high-quality segmentation for objects. We experimentally validate that the proposed method outperforms previous approaches using the challenging PASCAL VOC 2010/2012 and Berkeley (BSD300) segmentation datasets.
MODELING STATISTICAL PROPERTIES OF SOLAR ACTIVE REGIONS THROUGH DIRECT NUMERICAL SIMULATIONS OF 3D-MHD TURBULENCE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Malapaka, Shiva Kumar; Mueller, Wolf-Christian

Statistical properties of the Sun's photospheric turbulent magnetic field, especially those of the active regions (ARs), have been studied using the line-of-sight data from magnetograms taken by the Solar and Heliospheric Observatory and several other instruments. This includes structure functions and their exponents, flatness curves, and correlation functions. In these works, the dependence of structure function exponents ({zeta}{sub p}) of the order of the structure functions (p) was modeled using a non-intermittent K41 model. It is now well known that the ARs are highly turbulent and are associated with strong intermittent events. In this paper, we compare some of themore » observations from Abramenko et al. with the log-Poisson model used for modeling intermittent MHD turbulent flows. Next, we analyze the structure function data obtained from the direct numerical simulations (DNS) of homogeneous, incompressible 3D-MHD turbulence in three cases: sustained by forcing, freely decaying, and a flow initially driven and later allowed to decay (case 3). The respective DNS replicate the properties seen in the plots of {zeta}{sub p} against p of ARs. We also reproduce the trends and changes observed in intermittency in flatness and correlation functions of ARs. It is suggested from this analysis that an AR in the onset phase of a flare can be treated as a forced 3D-MHD turbulent system in its simplest form and that the flaring stage is representative of decaying 3D-MHD turbulence. It is also inferred that significant changes in intermittency from the initial onset phase of a flare to its final peak flaring phase are related to the time taken by the system to reach the initial onset phase.« less
Cluster Tails for Critical Power-Law Inhomogeneous Random Graphs

NASA Astrophysics Data System (ADS)

van der Hofstad, Remco; Kliem, Sandra; van Leeuwaarden, Johan S. H.

2018-04-01

Recently, the scaling limit of cluster sizes for critical inhomogeneous random graphs of rank-1 type having finite variance but infinite third moment degrees was obtained in Bhamidi et al. (Ann Probab 40:2299-2361, 2012). It was proved that when the degrees obey a power law with exponent τ \\in (3,4), the sequence of clusters ordered in decreasing size and multiplied through by n^{-(τ -2)/(τ -1)} converges as n→ ∞ to a sequence of decreasing non-degenerate random variables. Here, we study the tails of the limit of the rescaled largest cluster, i.e., the probability that the scaling limit of the largest cluster takes a large value u, as a function of u. This extends a related result of Pittel (J Combin Theory Ser B 82(2):237-269, 2001) for the Erdős-Rényi random graph to the setting of rank-1 inhomogeneous random graphs with infinite third moment degrees. We make use of delicate large deviations and weak convergence arguments.
Graph Curvature for Differentiating Cancer Networks

PubMed Central

Sandhu, Romeil; Georgiou, Tryphon; Reznik, Ed; Zhu, Liangjia; Kolesov, Ivan; Senbabaoglu, Yasin; Tannenbaum, Allen

2015-01-01

Cellular interactions can be modeled as complex dynamical systems represented by weighted graphs. The functionality of such networks, including measures of robustness, reliability, performance, and efficiency, are intrinsically tied to the topology and geometry of the underlying graph. Utilizing recently proposed geometric notions of curvature on weighted graphs, we investigate the features of gene co-expression networks derived from large-scale genomic studies of cancer. We find that the curvature of these networks reliably distinguishes between cancer and normal samples, with cancer networks exhibiting higher curvature than their normal counterparts. We establish a quantitative relationship between our findings and prior investigations of network entropy. Furthermore, we demonstrate how our approach yields additional, non-trivial pair-wise (i.e. gene-gene) interactions which may be disrupted in cancer samples. The mathematical formulation of our approach yields an exact solution to calculating pair-wise changes in curvature which was computationally infeasible using prior methods. As such, our findings lay the foundation for an analytical approach to studying complex biological networks. PMID:26169480
Bipartite graphs in systems biology and medicine: a survey of methods and applications.

PubMed

Pavlopoulos, Georgios A; Kontou, Panagiota I; Pavlopoulou, Athanasia; Bouyioukos, Costas; Markou, Evripides; Bagos, Pantelis G

2018-04-01

The latest advances in high-throughput techniques during the past decade allowed the systems biology field to expand significantly. Today, the focus of biologists has shifted from the study of individual biological components to the study of complex biological systems and their dynamics at a larger scale. Through the discovery of novel bioentity relationships, researchers reveal new information about biological functions and processes. Graphs are widely used to represent bioentities such as proteins, genes, small molecules, ligands, and others such as nodes and their connections as edges within a network. In this review, special focus is given to the usability of bipartite graphs and their impact on the field of network biology and medicine. Furthermore, their topological properties and how these can be applied to certain biological case studies are discussed. Finally, available methodologies and software are presented, and useful insights on how bipartite graphs can shape the path toward the solution of challenging biological problems are provided.
Synthesis of nanoparticle emulsion collector HNP and its application in microfine chalcopyrite flotation

NASA Astrophysics Data System (ADS)

He, G. C.; Ding, J.; Huang, C. H.; Kang, Q.

2018-01-01

Hydrophobic polystyrene nanoparticles bearing thiazole groups named HNP were used as collectors to improve recovery of microfine chalcopyrite in flotation. HNP adsorbs onto microfine particles selectively, which were modified hydrophobically to induce flotation effectively. Particle size and scanning electron microscope analysis for HNP show that HNP is a spherical nano particles with small size, uniform distribution and good dispersion. Infrared spectrum analysis for HNP proved that functional monomer 2-mercapto styrene acrylic thiazole was bonded chemically onto styrene. Flotation test results indicate that HNP is the right collector of chalcopyrite. Especially, the recovery of chalcopyrite is higher than 95% in neutral and acid media. FTIR results reveal that the flotation selectivity of collector HNP is due to strong chemical absorption onto chalcopyrite surface. Zeta potential analysis shows that the zeta potential of chalcopyrite decreased more quickly after interaction with HNP with the increase of pulp pH value, confirming that collector HNP is an anionic collector. Scanning electron microscope conform that HNP has good selective adsorption on chalcopyrite.
First ultraviolet spectropolarimetry of Be stars from the Wisconsin Ultraviolet Photo-Polarimeter Experiment

NASA Technical Reports Server (NTRS)

Bjorkman, K. S.; Nordsieck, K. H.; Code, A. D.; Anderson, C. M.; Babler, B. L.; Clayton, G. C.; Magalhaes, A. M.; Meade, M. R.; Nook, M. A.; Schulte-Ladbeck, R. E.

1991-01-01

The first UV spectropolarimetric observations of Be stars are presented. They were obtained with the Wisconsin Ultraviolet Photo-Polarimeter Experiment (WUPPE) aboard the Astro-1 mission. WUPPE data on the Be stars Zeta Tau and Pi Aqr, along with near-simultaneous optical data obtained at the Pine Bluff Observatory (PBO). Combined WUPPE and PBO data give polarization as a function of wavelength across a very broad spectral region, from 1400 to 7600 A. Existing Be star models predicted increasing polarization toward shorter wavelengths in the UV, but this is not supported by the WUPPE observations. Instead, the observations show a constant or slightly declining continuum polarization shortward of the Balmer jump, and broad UV polarization dips around 1700 and 1900 A, which may be a result of Fe-line-attenuation effects on the polarized flux. Supporting evidence for this conclusion comes from the optical data, in which decreases in polarization across Fe II lines in Zeta Tau were discovered.
Chaotic nature of the spin-glass phase

NASA Technical Reports Server (NTRS)

Bray, A. J.; Moore, M. A.

1987-01-01

The microscopic structure of the ordered phase of spin glasses is investigated theoretically in the framework of the T = 0 fixed-point model (McMillan, 1984; Fisher and Huse, 1986; and Bray and Moore, 1986). The sensitivity of the ground state to changes in the interaction strengths at T = 0 is explored, and it is found that for sufficiently large length scales the ground state is unstable against arbitrarily weak perturbations to the bonds. Explicit results are derived for d = 1, and the implications for d = 2 and d = 3 are considered in detail. It is concluded that there is no hidden order pattern for spin glasses at all T less than T(C), the ordered-phase spin correlations being chaotic functions of spin separation at fixed temperature or of temperature (for a given pair of spins) at scale lengths L greater than (T delta T) exp -1/zeta, where zeta = d(s)/2 - y, d(s) is the interfacial fractal dimension, and -y is the thermal eigenvalue at T = 0.
Graph cuts with invariant object-interaction priors: application to intervertebral disc segmentation.

PubMed

Ben Ayed, Ismail; Punithakumar, Kumaradevan; Garvin, Gregory; Romano, Walter; Li, Shuo

2011-01-01

This study investigates novel object-interaction priors for graph cut image segmentation with application to intervertebral disc delineation in magnetic resonance (MR) lumbar spine images. The algorithm optimizes an original cost function which constrains the solution with learned prior knowledge about the geometric interactions between different objects in the image. Based on a global measure of similarity between distributions, the proposed priors are intrinsically invariant with respect to translation and rotation. We further introduce a scale variable from which we derive an original fixed-point equation (FPE), thereby achieving scale-invariance with only few fast computations. The proposed priors relax the need of costly pose estimation (or registration) procedures and large training sets (we used a single subject for training), and can tolerate shape deformations, unlike template-based priors. Our formulation leads to an NP-hard problem which does not afford a form directly amenable to graph cut optimization. We proceeded to a relaxation of the problem via an auxiliary function, thereby obtaining a nearly real-time solution with few graph cuts. Quantitative evaluations over 60 intervertebral discs acquired from 10 subjects demonstrated that the proposed algorithm yields a high correlation with independent manual segmentations by an expert. We further demonstrate experimentally the invariance of the proposed geometric attributes. This supports the fact that a single subject is sufficient for training our algorithm, and confirms the relevance of the proposed priors to disc segmentation.
On Learning Cluster Coefficient of Private Networks

PubMed Central

Wang, Yue; Wu, Xintao; Zhu, Jun; Xiang, Yang

2013-01-01

Enabling accurate analysis of social network data while preserving differential privacy has been challenging since graph features such as clustering coefficient or modularity often have high sensitivity, which is different from traditional aggregate functions (e.g., count and sum) on tabular data. In this paper, we treat a graph statistics as a function f and develop a divide and conquer approach to enforce differential privacy. The basic procedure of this approach is to first decompose the target computation f into several less complex unit computations f1, …, fm connected by basic mathematical operations (e.g., addition, subtraction, multiplication, division), then perturb the output of each fi with Laplace noise derived from its own sensitivity value and the distributed privacy threshold εi, and finally combine those perturbed fi as the perturbed output of computation f. We examine how various operations affect the accuracy of complex computations. When unit computations have large global sensitivity values, we enforce the differential privacy by calibrating noise based on the smooth sensitivity, rather than the global sensitivity. By doing this, we achieve the strict differential privacy guarantee with smaller magnitude noise. We illustrate our approach by using clustering coefficient, which is a popular statistics used in social network analysis. Empirical evaluations on five real social networks and various synthetic graphs generated from three random graph models show the developed divide and conquer approach outperforms the direct approach. PMID:24429843
3D segmentation of lung CT data with graph-cuts: analysis of parameter sensitivities

NASA Astrophysics Data System (ADS)

Cha, Jung won; Dunlap, Neal; Wang, Brian; Amini, Amir

2016-03-01

Lung boundary image segmentation is important for many tasks including for example in development of radiation treatment plans for subjects with thoracic malignancies. In this paper, we describe a method and parameter settings for accurate 3D lung boundary segmentation based on graph-cuts from X-ray CT data1. Even though previously several researchers have used graph-cuts for image segmentation, to date, no systematic studies have been performed regarding the range of parameter that give accurate results. The energy function in the graph-cuts algorithm requires 3 suitable parameter settings: K, a large constant for assigning seed points, c, the similarity coefficient for n-links, and λ, the terminal coefficient for t-links. We analyzed the parameter sensitivity with four lung data sets from subjects with lung cancer using error metrics. Large values of K created artifacts on segmented images, and relatively much larger value of c than the value of λ influenced the balance between the boundary term and the data term in the energy function, leading to unacceptable segmentation results. For a range of parameter settings, we performed 3D image segmentation, and in each case compared the results with the expert-delineated lung boundaries. We used simple 6-neighborhood systems for n-link in 3D. The 3D image segmentation took 10 minutes for a 512x512x118 ~ 512x512x190 lung CT image volume. Our results indicate that the graph-cuts algorithm was more sensitive to the K and λ parameter settings than to the C parameter and furthermore that amongst the range of parameters tested, K=5 and λ=0.5 yielded good results.

Novel Wearable Seismocardiography and Machine Learning Algorithms Can Assess Clinical Status of Heart Failure Patients.

PubMed

Inan, Omer T; Baran Pouyan, Maziyar; Javaid, Abdul Q; Dowling, Sean; Etemadi, Mozziyar; Dorier, Alexis; Heller, J Alex; Bicen, A Ozan; Roy, Shuvo; De Marco, Teresa; Klein, Liviu

2018-01-01

Remote monitoring of patients with heart failure (HF) using wearable devices can allow patient-specific adjustments to treatments and thereby potentially reduce hospitalizations. We aimed to assess HF state using wearable measurements of electrical and mechanical aspects of cardiac function in the context of exercise. Patients with compensated (outpatient) and decompensated (hospitalized) HF were fitted with a wearable ECG and seismocardiogram sensing patch. Patients stood at rest for an initial recording, performed a 6-minute walk test, and then stood at rest for 5 minutes of recovery. The protocol was performed at the time of outpatient visit or at 2 time points (admission and discharge) during an HF hospitalization. To assess patient state, we devised a method based on comparing the similarity of the structure of seismocardiogram signals after exercise compared with rest using graph mining (graph similarity score). We found that graph similarity score can assess HF patient state and correlates to clinical improvement in 45 patients (13 decompensated, 32 compensated). A significant difference was found between the groups in the graph similarity score metric (44.4±4.9 [decompensated HF] versus 35.2±10.5 [compensated HF]; P <0.001). In the 6 decompensated patients with longitudinal data, we found a significant change in graph similarity score from admission (decompensated) to discharge (compensated; 44±4.1 [admitted] versus 35±3.9 [discharged]; P <0.05). Wearable technologies recording cardiac function and machine learning algorithms can assess compensated and decompensated HF states by analyzing cardiac response to submaximal exercise. These techniques can be tested in the future to track the clinical status of outpatients with HF and their response to pharmacological interventions. © 2018 American Heart Association, Inc.
Cliques of Neurons Bound into Cavities Provide a Missing Link between Structure and Function.

PubMed

Reimann, Michael W; Nolte, Max; Scolamiero, Martina; Turner, Katharine; Perin, Rodrigo; Chindemi, Giuseppe; Dłotko, Paweł; Levi, Ran; Hess, Kathryn; Markram, Henry

2017-01-01

The lack of a formal link between neural network structure and its emergent function has hampered our understanding of how the brain processes information. We have now come closer to describing such a link by taking the direction of synaptic transmission into account, constructing graphs of a network that reflect the direction of information flow, and analyzing these directed graphs using algebraic topology. Applying this approach to a local network of neurons in the neocortex revealed a remarkably intricate and previously unseen topology of synaptic connectivity. The synaptic network contains an abundance of cliques of neurons bound into cavities that guide the emergence of correlated activity. In response to stimuli, correlated activity binds synaptically connected neurons into functional cliques and cavities that evolve in a stereotypical sequence toward peak complexity. We propose that the brain processes stimuli by forming increasingly complex functional cliques and cavities.
Graph Theoretical Analysis of Functional Brain Networks: Test-Retest Evaluation on Short- and Long-Term Resting-State Functional MRI Data

PubMed Central

Wang, Jin-Hui; Zuo, Xi-Nian; Gohel, Suril; Milham, Michael P.; Biswal, Bharat B.; He, Yong

2011-01-01

Graph-based computational network analysis has proven a powerful tool to quantitatively characterize functional architectures of the brain. However, the test-retest (TRT) reliability of graph metrics of functional networks has not been systematically examined. Here, we investigated TRT reliability of topological metrics of functional brain networks derived from resting-state functional magnetic resonance imaging data. Specifically, we evaluated both short-term (<1 hour apart) and long-term (>5 months apart) TRT reliability for 12 global and 6 local nodal network metrics. We found that reliability of global network metrics was overall low, threshold-sensitive and dependent on several factors of scanning time interval (TI, long-term>short-term), network membership (NM, networks excluding negative correlations>networks including negative correlations) and network type (NT, binarized networks>weighted networks). The dependence was modulated by another factor of node definition (ND) strategy. The local nodal reliability exhibited large variability across nodal metrics and a spatially heterogeneous distribution. Nodal degree was the most reliable metric and varied the least across the factors above. Hub regions in association and limbic/paralimbic cortices showed moderate TRT reliability. Importantly, nodal reliability was robust to above-mentioned four factors. Simulation analysis revealed that global network metrics were extremely sensitive (but varying degrees) to noise in functional connectivity and weighted networks generated numerically more reliable results in compared with binarized networks. For nodal network metrics, they showed high resistance to noise in functional connectivity and no NT related differences were found in the resistance. These findings provide important implications on how to choose reliable analytical schemes and network metrics of interest. PMID:21818285
Functional classification of protein structures by local structure matching in graph representation.

PubMed

Mills, Caitlyn L; Garg, Rohan; Lee, Joslynn S; Tian, Liang; Suciu, Alexandru; Cooperman, Gene; Beuning, Penny J; Ondrechen, Mary Jo

2018-03-31

As a result of high-throughput protein structure initiatives, over 14,400 protein structures have been solved by structural genomics (SG) centers and participating research groups. While the totality of SG data represents a tremendous contribution to genomics and structural biology, reliable functional information for these proteins is generally lacking. Better functional predictions for SG proteins will add substantial value to the structural information already obtained. Our method described herein, Graph Representation of Active Sites for Prediction of Function (GRASP-Func), predicts quickly and accurately the biochemical function of proteins by representing residues at the predicted local active site as graphs rather than in Cartesian coordinates. We compare the GRASP-Func method to our previously reported method, structurally aligned local sites of activity (SALSA), using the ribulose phosphate binding barrel (RPBB), 6-hairpin glycosidase (6-HG), and Concanavalin A-like Lectins/Glucanase (CAL/G) superfamilies as test cases. In each of the superfamilies, SALSA and the much faster method GRASP-Func yield similar correct classification of previously characterized proteins, providing a validated benchmark for the new method. In addition, we analyzed SG proteins using our SALSA and GRASP-Func methods to predict function. Forty-one SG proteins in the RPBB superfamily, nine SG proteins in the 6-HG superfamily, and one SG protein in the CAL/G superfamily were successfully classified into one of the functional families in their respective superfamily by both methods. This improved, faster, validated computational method can yield more reliable predictions of function that can be used for a wide variety of applications by the community. © 2018 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.
Eigenanalysis and Graph Theory Combined to Determine the Seasonal and Solar-Cycle Variations of Polar Magnetic Fields

NASA Astrophysics Data System (ADS)

Shore, R. M.; Freeman, M. P.; Gjerloev, J. W.

2017-12-01

We apply the meteorological analysis method of Empirical Orthogonal Functions (EOF) to ground magnetometer measurements, and subsequently use graph theory to classify the results. The EOF method is used to characterise and separate contributions to the variability of the Earth's external magnetic field (EMF) in the northern polar region. EOFs decompose the noisy EMF data into a small number of independent spatio-temporal basis functions, which collectively describe the majority of the magnetic field variance. We use these basis functions (computed monthly) to infill where data are missing, providing a self-consistent description of the EMF at 5-minute resolution spanning 1997-2009 (solar cycle 23). The EOF basis functions are calculated independently for each of the 144 months (i.e. 1997-2009) analysed. Since (by definition) the basis vectors are ranked by their contribution to the total variance, their rank will change from month to month. We use graph theory to find clusters of quantifiably-similar spatial basis functions, and thereby track similar patterns throughout the span of 144 months. We find that the discovered clusters can be associated with well-known individual Disturbance Polar (DP)-type equivalent current systems (e.g. DP2, DP1, DPY, NBZ), or with the motion of these systems. Via this method, we thus describe the varying behaviour of these current systems over solar cycle 23. We present their seasonal and solar cycle variations and examine the response of each current system to solar wind driving.
A Statistical Method to Distinguish Functional Brain Networks

PubMed Central

Fujita, André; Vidal, Maciel C.; Takahashi, Daniel Y.

2017-01-01

One major problem in neuroscience is the comparison of functional brain networks of different populations, e.g., distinguishing the networks of controls and patients. Traditional algorithms are based on search for isomorphism between networks, assuming that they are deterministic. However, biological networks present randomness that cannot be well modeled by those algorithms. For instance, functional brain networks of distinct subjects of the same population can be different due to individual characteristics. Moreover, networks of subjects from different populations can be generated through the same stochastic process. Thus, a better hypothesis is that networks are generated by random processes. In this case, subjects from the same group are samples from the same random process, whereas subjects from different groups are generated by distinct processes. Using this idea, we developed a statistical test called ANOGVA to test whether two or more populations of graphs are generated by the same random graph model. Our simulations' results demonstrate that we can precisely control the rate of false positives and that the test is powerful to discriminate random graphs generated by different models and parameters. The method also showed to be robust for unbalanced data. As an example, we applied ANOGVA to an fMRI dataset composed of controls and patients diagnosed with autism or Asperger. ANOGVA identified the cerebellar functional sub-network as statistically different between controls and autism (p < 0.001). PMID:28261045
A Statistical Method to Distinguish Functional Brain Networks.

PubMed

Fujita, André; Vidal, Maciel C; Takahashi, Daniel Y

2017-01-01

One major problem in neuroscience is the comparison of functional brain networks of different populations, e.g., distinguishing the networks of controls and patients. Traditional algorithms are based on search for isomorphism between networks, assuming that they are deterministic. However, biological networks present randomness that cannot be well modeled by those algorithms. For instance, functional brain networks of distinct subjects of the same population can be different due to individual characteristics. Moreover, networks of subjects from different populations can be generated through the same stochastic process. Thus, a better hypothesis is that networks are generated by random processes. In this case, subjects from the same group are samples from the same random process, whereas subjects from different groups are generated by distinct processes. Using this idea, we developed a statistical test called ANOGVA to test whether two or more populations of graphs are generated by the same random graph model. Our simulations' results demonstrate that we can precisely control the rate of false positives and that the test is powerful to discriminate random graphs generated by different models and parameters. The method also showed to be robust for unbalanced data. As an example, we applied ANOGVA to an fMRI dataset composed of controls and patients diagnosed with autism or Asperger. ANOGVA identified the cerebellar functional sub-network as statistically different between controls and autism ( p < 0.001).
Loop series for discrete statistical models on graphs

NASA Astrophysics Data System (ADS)

Chertkov, Michael; Chernyak, Vladimir Y.

2006-06-01

In this paper we present the derivation details, logic, and motivation for the three loop calculus introduced in Chertkov and Chernyak (2006 Phys. Rev. E 73 065102(R)). Generating functions for each of the three interrelated discrete statistical models are expressed in terms of a finite series. The first term in the series corresponds to the Bethe-Peierls belief-propagation (BP) contribution; the other terms are labelled by loops on the factor graph. All loop contributions are simple rational functions of spin correlation functions calculated within the BP approach. We discuss two alternative derivations of the loop series. One approach implements a set of local auxiliary integrations over continuous fields with the BP contribution corresponding to an integrand saddle-point value. The integrals are replaced by sums in the complementary approach, briefly explained in Chertkov and Chernyak (2006 Phys. Rev. E 73 065102(R)). Local gauge symmetry transformations that clarify an important invariant feature of the BP solution are revealed in both approaches. The individual terms change under the gauge transformation while the partition function remains invariant. The requirement for all individual terms to be nonzero only for closed loops in the factor graph (as opposed to paths with loose ends) is equivalent to fixing the first term in the series to be exactly equal to the BP contribution. Further applications of the loop calculus to problems in statistical physics, computer and information sciences are discussed.
In situ functionalization and PEO coating of iron oxide nanocrystals using seeded emulsion polymerization.

PubMed

Kloust, Hauke; Schmidtke, Christian; Feld, Artur; Schotten, Theo; Eggers, Robin; Fittschen, Ursula E A; Schulz, Florian; Pöselt, Elmar; Ostermann, Johannes; Bastús, Neus G; Weller, Horst

2013-04-16

Herein we demonstrate that seeded emulsion polymerization is a powerful tool to produce multiply functionalized PEO coated iron oxide nanocrystals. Advantageously, by simple addition of functional surfactants, functional monomers, or functional polymerizable linkers-solely or in combinations thereof-during the seeded emulsion polymerization process, a broad range of in situ functionalized polymer-coated iron oxide nanocrystals were obtained. This was demonstrated by purposeful modulation of the zeta potential of encapsulated iron oxide nanocrystals and conjugation of a dyestuff. Successful functionalization was unequivocally proven by TXRF. Furthermore, the spatial position of the functional groups can be controlled by choosing the appropriate spacers. In conclusion, this methodology is highly amenable for combinatorial strategies and will spur rapid expedited synthesis and purposeful optimization of a broad scope of nanocrystals.
Transforming the Way We Teach Function Transformations

ERIC Educational Resources Information Center

Faulkenberry, Eileen Durand; Faulkenberry, Thomas J.

2010-01-01

In this article, the authors discuss "function," a well-defined rule that relates inputs to outputs. They have found that by using the input-output definition of "function," they can examine transformations of functions simply by looking at changes to input or output and the respective changes to the graph. Applying transformations to the input…
Investigation of the influence of the zeta-potential on the filtration rate in the presence of collectors

NASA Technical Reports Server (NTRS)

Provirnina, E. V.; Barbin, M. B.

1984-01-01

The value of the zeta-potential does not have an explicit effect, which is expressed by a simple math correlation, on filtration rate when a solution of the tested collector is filtered through a cake prepared under standard conditions from the examined particulate material. The zeta-potential measurements and filtration tests were carried out on silica and galena with solutions contg. a cationic container ANP and Et xanthane, resp. at PH = 6.5, varying concentration of the agent (0-2500 g/ton), and under a vacuum of 100 to 600 mm Hg.
The adsorption of cationic and amphoteric copolymers on glass surfaces: zeta potential measurements, adsorption isotherm determination, and FT Raman characterization.

PubMed

Tartakovsky, Alla; Drutis, Dane M; Carnali, Joseph O

2003-07-15

The adsorption of cationic and amphoteric copolymers onto controlled pore glass (CPG) powders has been studied by measurement of the powder particle zeta (zeta) potential, by determination of the adsorption isotherm, and by FT Raman measurements of the polymer-coated powder. The cationic polymers consisted chiefly of homopolymers of dimethyldiallylammonium chloride (DMDAAC) or copolymers of DMDAAC and acrylamide. The amphoteric polymers studied included copolymers of DMDAAC and acrylic acid. The comonomer ratio was varied to explore the dependence of cationic charge density on the extent and effect of adsorption. Both types of polymers adsorb onto the anionic glass surface via an ion-exchange mechanism. Consequently, a correspondingly higher mass of a low-charge-density copolymer adsorbs than of a cationic homopolymer. The presence of the anionic portion in the amphoteric polymers does not significantly alter this picture. The zeta potential, however, reflects the overall nature of the polymer. Cationic polymers effectively neutralize the glass surface, while amphoteric polymers leave the zeta potential net negative. Adsorption isotherms, determined via the depletion technique using colloidal titration, were used to "calibrate" a FT Raman method. The latter was used to determined the amount of adsorbed polymer under solution conditions in which colloidal titration could not be performed.
Synthesis, bioactivity and zeta potential investigations of chlorine and fluorine substituted hydroxyapatite.

PubMed

Fahami, Abbas; Beall, Gary W; Betancourt, Tania

2016-02-01

Chlorine and fluorine substituted hydroxyapatites (HA-Cl-F) with different degrees of ion replacement were successfully prepared by the one step mechanochemical activation method. X-ray diffraction (XRD) and FT-IR spectra indicated that substitution of these anions in milled powders resulted in the formation of pure hydroxyapatite phase except for the small observed change in the lattice parameters and unit cell volumes of the resultant hydroxyapatite. Microscopic observations showed that the milled product had a cluster-like structure made up of polygonal and spherical particles with an average particle size of approximately ranged from 20±5 to 70±5nm. The zeta potential of milled samples was performed at three different pH (5, 7.4, and 9). The obtained zeta potential values were negative for all three pH values. Negative zeta potential was described to favor osseointegration, apatite nucleation, and bone regeneration. The bioactivity of samples was investigated on sintered pellets soaked in simulated body fluid (SBF) solution and apatite crystals formed on the surface of the pellets after being incubated for 14days. Zeta potential analysis and bioactivity experiment suggested that HA-Cl-F will lead to the formation of new apatite particles and therefore be a potential implant material. Copyright © 2015 Elsevier B.V. All rights reserved.
Investigating the time-dependent zeta potential of wood surfaces.

PubMed

Muff, Livius F; Luxbacher, Thomas; Burgert, Ingo; Michen, Benjamin

2018-05-15

This work reports on streaming potential measurements through natural capillaries in wood and investigates the cause of a time-dependent zeta potential measured during the equilibration of wood cell-walls with an electrolyte solution. For the biomaterial, this equilibration phase takes several hours, which is much longer than for many other materials that have been characterized by electrokinetic measurements. During this equilibration phase the zeta potential magnitude is decaying due to two parallel mechanisms: (i) the swelling of the cell-wall which causes a dimensional change reducing the charge density at the capillary interface; (ii) the transport of ions from the electrolyte solution into the permeable cell-wall which alters the electrical potential at the interface by internal charge compensation. The obtained results demonstrate the importance of equilibration kinetics for an accurate determination of the zeta potential, especially for materials that interact strongly with the measurement electrolyte. Moreover, the change in zeta potential with time can be correlated with the bulk swelling of wood if the effect of electrolyte ion diffusion is excluded. This study shows the potential of streaming potential measurements of wood, and possibly of other hygroscopic and nanoporous materials, to reveal kinetic information about their interaction with liquids, such as swelling and ion uptake. Copyright © 2018 Elsevier Inc. All rights reserved.
Stabilization of Gold Nanorods (GNRs) in Aqueous and Organic Environments by Select Surface Functionalization

DTIC Science & Technology

2016-01-01

collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. 1...SPONSOR/MONITOR’S REPORT NUMBER(S) 12. DISTRIBUTION/ AVAILABILITY STATEMENT Approved for public release; distribution is unlimited. 13...is confirmed by ultraviolet-visible and zeta-potential measurements. Additionally, 3 different methods are applied to achieve self-assembly of GNRs
Electrokinetic flows through a parallel-plate channel with slipping stripes on walls

NASA Astrophysics Data System (ADS)

Chu, Henry C. W.; Ng, Chiu-On

2011-11-01

Electrohydrodynamic flows through a periodically-micropatterned plane channel are considered. One unit of wall pattern consists of a slipping and non-slipping stripe, each with a distinct zeta potential. The problems are solved semi-analytically by eigenfunction expansion and point collocation. In the regime of linear response, the Onsager relation for the fluid and current fluxes are deduced as linear functions of the hydrodynamic and electric forcings. The phenomenological coefficients are explicitly expressed as functions of the channel height, the Debye parameter, the slipping area fraction of the wall, the intrinsic slip length, and the zeta potentials. We generalize the theoretical limits made in previous studies on electrokinetic flow over an inhomogeneously slipping surface. One should be cautious when applying these limits. First, when a surface is not 100% uniformly slipping but has a small fraction of area being covered by no-slip slots, the electroosmotic enhancement can be appreciably reduced. Second, when the electric double layer is only moderately thin, slipping-uncharged regions on a surface will have finite inhibition effect on the electroosmotic flow. Financial support by the RGC of the HKSAR, China: Project Nos. HKU715609E, HKU715510E; and the HKU under the Seed Funding Programme for Basic Research: Project Code 200911159024.
Casimir effect in rugby-ball type flux compactifications

NASA Astrophysics Data System (ADS)

Elizalde, Emilio; Minamitsuji, Masato; Naylor, Wade

2007-03-01

As a continuation of the work by Minamitsuji, Naylor, and Sasaki [J. High Energy Phys.JHEPFG1029-8479 12 (2006) 07910.1088/1126-6708/2006/12/079], we discuss the Casimir effect for a massless bulk scalar field in a 4D toy model of a 6D warped flux compactification model, to stabilize the volume modulus. The one-loop effective potential for the volume modulus has a form similar to the Coleman-Weinberg potential. The stability of the volume modulus against quantum corrections is related to an appropriate heat kernel coefficient. However, to make any physical predictions after volume stabilization, knowledge of the derivative of the zeta function, ζ'(0) (in a conformally related spacetime) is also required. By adding up the exact mass spectrum using zeta-function regularization, we present a revised analysis of the effective potential. Finally, we discuss some physical implications, especially concerning the degree of the hierarchy between the fundamental energy scales on the branes. For a larger degree of warping our new results are very similar to the ones given by Minamitsuji, Naylor, and Sasaki [J. High Energy Phys.JHEPFG1029-8479 12 (2006) 07910.1088/1126-6708/2006/12/079] and imply a larger hierarchy. In the nonwarped (rugby ball) limit the ratio tends to converge to the same value, independently of the bulk dilaton coupling.
Graph Theoretical Framework of Brain Networks in Multiple Sclerosis: A Review of Concepts.

PubMed

Fleischer, Vinzenz; Radetz, Angela; Ciolac, Dumitru; Muthuraman, Muthuraman; Gonzalez-Escamilla, Gabriel; Zipp, Frauke; Groppa, Sergiu

2017-11-01

Network science provides powerful access to essential organizational principles of the human brain. It has been applied in combination with graph theory to characterize brain connectivity patterns. In multiple sclerosis (MS), analysis of the brain networks derived from either structural or functional imaging provides new insights into pathological processes within the gray and white matter. Beyond focal lesions and diffuse tissue damage, network connectivity patterns could be important for closely tracking and predicting the disease course. In this review, we describe concepts of graph theory, highlight novel issues of tissue reorganization in acute and chronic neuroinflammation and address pitfalls with regard to network analysis in MS patients. We further provide an outline of functional and structural connectivity patterns observed in MS, spanning from disconnection and disruption on one hand to adaptation and compensation on the other. Moreover, we link network changes and their relation to clinical disability based on the current literature. Finally, we discuss the perspective of network science in MS for future research and postulate its role in the clinical framework. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.
Mild traumatic brain injury: graph-model characterization of brain networks for episodic memory.

PubMed

Tsirka, Vasso; Simos, Panagiotis G; Vakis, Antonios; Kanatsouli, Kassiani; Vourkas, Michael; Erimaki, Sofia; Pachou, Ellie; Stam, Cornelis Jan; Micheloyannis, Sifis

2011-02-01

Episodic memory is among the cognitive functions that can be affected in the acute phase following mild traumatic brain injury (MTBI). The present study used EEG recordings to evaluate global synchronization and network organization of rhythmic activity during the encoding and recognition phases of an episodic memory task varying in stimulus type (kaleidoscope images, pictures, words, and pseudowords). Synchronization of oscillatory activity was assessed using a linear and nonlinear connectivity estimator and network analyses were performed using algorithms derived from graph theory. Twenty five MTBI patients (tested within days post-injury) and healthy volunteers were closely matched on demographic variables, verbal ability, psychological status variables, as well as on overall task performance. Patients demonstrated sub-optimal network organization, as reflected by changes in graph parameters in the theta and alpha bands during both encoding and recognition. There were no group differences in spectral energy during task performance or on network parameters during a control condition (rest). Evidence of less optimally organized functional networks during memory tasks was more prominent for pictorial than for verbal stimuli. Copyright © 2010 Elsevier B.V. All rights reserved.
Network representation of protein interactions: Theory of graph description and analysis.

PubMed

Kurzbach, Dennis

2016-09-01

A methodological framework is presented for the graph theoretical interpretation of NMR data of protein interactions. The proposed analysis generalizes the idea of network representations of protein structures by expanding it to protein interactions. This approach is based on regularization of residue-resolved NMR relaxation times and chemical shift data and subsequent construction of an adjacency matrix that represents the underlying protein interaction as a graph or network. The network nodes represent protein residues. Two nodes are connected if two residues are functionally correlated during the protein interaction event. The analysis of the resulting network enables the quantification of the importance of each amino acid of a protein for its interactions. Furthermore, the determination of the pattern of correlations between residues yields insights into the functional architecture of an interaction. This is of special interest for intrinsically disordered proteins, since the structural (three-dimensional) architecture of these proteins and their complexes is difficult to determine. The power of the proposed methodology is demonstrated at the example of the interaction between the intrinsically disordered protein osteopontin and its natural ligand heparin. © 2016 The Protein Society.

Some links on this page may take you to non-federal websites. Their policies may differ from this site.