87,442 research outputs found
Adaptive matrix algebras in unconstrained minimization
No full textIn this paper we study adaptive L(k)QNmethods, involving special matrix algebras of low complexity, to solve general (non-structured) unconstrained minimization problems. These methods, which generalize the classical BFGS method, are based on an iterative formula which exploits, at each step, an ad hocchosen matrix algebra L(k). A global convergence result is obtained under suitable assumptions on f
Total variation based community detection using a nonlinear optimization approach
No full textMaximizing the modularity of a network is a successful tool to identify an important community of nodes. However, this combinatorial optimization problem is known to be NP-complete. Inspired by recent nonlinear modularity eigenvector approaches, we introduce the modularity total variation TVQ and show that its box-constrained global maximum coincides with the maximum of the original discrete modularity function. Thus we describe a new nonlinear optimization approach to solve the equivalent problem leading to a community detection strategy based on TVQ. The proposed approach relies on the use of a fast first-order method that embeds a tailored active-set strategy. We report extensive numerical comparisons with standard matrix-based approaches and the Generalized RatioDCA approach for nonlinear modularity eigenvectors, showing that our new method compares favorably with state-of-the-art alternatives
A preconditioning approach to the pagerank computation problem
No full textSome spectral properties of the transition matrix of an oriented graph indicate the preconditioning of Euler-Richardson (ER) iterative scheme as a good way to compute efficiently the vertexrank vector associated with such graph. We choose the preconditioner from an algebra U of matrices, thereby obtaining an ERU method, and we observe that ERU can outperform ER in terms of rate of convergence. The proposed preconditioner can be updated at a very low cost whenever the graph changs, as is the case when it represents a generic set of information. The particular U utilized requires a surplus of operations per step and memory allocations, which make ERU superior to ER for not too wide graphs. However , the observed high improvement in convergence rate obtained by preconditining and the general theory developed, are a reason for investigating different choices of U, more efficient for huge graphs
Detection of plant species-specific dna (barley and soybean) in blood, muscle tissue, organs and gastrointestinal contents of rabbit
No full textThe aim of this study was to detect plant DNA sequences from low copy number genes of barley grain and soybean meal, the latter being subjected to solvent extraction process, in blood, liver, kidney, spleen, muscle tissue and digesta (duodenum, caecum and faeces from rectal ampulla) of rabbits. For fattening, Hyla rabbits (20 males and 20 females) were fed a diet including barley grain (15%) and soybean meal (12%). Animals were slaughtered at 74 d of age (2 ± 0.2 kg live weight) and samples collected from each animal. The quality of each DNA sample was verified using the UNIV P/Q primers used to amplify a mammalian specifi c portion of mtDNA 16S rRNA gene. The presence of plant DNA was subsequently ascertained on the same DNA samples, as well as on barley and soybean (control). Two classes of plant DNA sequences were monitored via real-time PCR, using SYBR(R) Green I Dye: a high copy number chloroplast gene (trnl) and a low copy number specific for barley (metal-dependent hydrolase-like protein) and soybean (lectin) genes. Melting curve analysis was used to identify the PCR products. The chloroplast fragment detection frequency was higher (P<0.01) in muscle (90%), liver (80%), kidney (80%) and spleen (80%) than in blood (40%) and digesta samples. In the latter, chloroplast DNA was found in 40 and 30% of duodenum and caecum contents respectively, and in 30% of faeces. The specificity of the amplicons obtained was checked by sequencing and annotation. In the samples positive for chloroplast fragments, the frequency of detection of barley specific sequence was higher (P<0.01) in liver (62.5%), kidney (62.5%), spleen (62.5%) and digesta (100%) than in blood (25%) and muscle (22.2%) samples. The soybean lectin gene was not detected in animal samples, although it was seen in plant samples. Results confirm that, except for gastrointestinal tract (GIT), plant single copy genes are more difficult to identify in animal samples.Tudisco, R.; Calabrò, S.; Bovera, F.; Cutrignelli, M.; Nizza, A.; Piccolo, V.; Infascelli, F. (2010). Detection of plant species-specific dna (barley and soybean) in blood, muscle tissue, organs and gastrointestinal contents of rabbit. World Rabbit Science. 18(2). https://doi.org/10.4995/wrs.2010.18.11182Aeschbacher K., Messikommer R., Meile L., Wenk C. 2005. Bt176 corn in poultry nutrition: physiological characteristics and fate of recombinant plant DNA in chickens. Poult. Sci., 84: 385-394.Altschul S.F., Madden T.L., Schäffer A.A., Zhang J., Zhang Z., Miller W., Lipman D.J. 1997. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acid Res., 25: 3389-3402.Association of Official Analytical Chemists, AOAC. 2000. 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Sensitive PCR analysis of animal tissue samples for fragments of endogenous and transgenic plant DNA. J. Agric. Food Chem., 52: 6129-6135.Netherwood T., Martín-Orúe S.M., O'Donnell A.G., Gockling S., Graham J., Mathers J.C., Gilbert H.J. 2004. Assessing the survival of transgenic plant DNA in the human gastrointestinal tract. Nat. Biotechnol., 22: 204-209.Phipps R.H., Deaville E.R., Maddison B.C. 2003. Detection of transgenic and endogenous plant DANN in rumen fluid, duodenal digesta, milk, blood, and faeces of lactating dairy cows. J. Dairy Sci., 86: 4070-4078.Sawyer J., Wood C., Shanahan D., Gout S., McDowell D. 2003. Realtime PCR for quantitative meat species testing. Food Cont., 14: 579-583.Terzi V., Infascelli F., Tudisco R., Russo G., Stanca A.M., Faccioli P. 2004. Quantitative detection of Secale cereale by real-time PCR amplification. Lebensm.-Wiss. u.-Technol., 37: 239-246.Tudisco R., Infascelli F., Cutrignelli M.I., Bovera F., Morcia C., Faccioli P., Terzi V. 2006a. Fate of feed plant DNA monitored in water buffalo (Bubalus bubalis) and rabbit (Oryctolagus cuniculus). Liv. Sci., 105: 12-18.Tudisco R., Lombardi P., Bovera F., D'Angelo D., Cutrignelli M.I., Mastellone V., Terzi V., Avallone L., Infascelli F. 2006b. Genetically modified soybean in rabbit feeding: detection of DNA fragments and evaluation of metabolic effects by enzymatic analysis. Anim. Sci., 82: 193-197.Tudisco R., Cutrignelli MI., Bovera F., Calabrò S., Piccolo G., D'Urso S., Infascelli F. 2007. Influence of pellet process of concentrate on the fate of feed plant DNA in the rabbit. Vet. Res. Comm., 31 (suppl. 1): 409-412
Extrapolation Methods for fixed-point Multilinear PageRank computations
No full textNonnegative tensors arise very naturally in many applications that involve large and complex data flows. Due to the relatively small requirement in terms of memory storage and number of operations per step, the (shifted) higher-order power method is one of the most commonly used technique for the computation of positive Z-eigenvectors of this type of tensors. However, unlike the matrix case, the method may fail to converge even for irreducible tensors. Moreover, when it converges, its convergence rate can be very slow. These two drawbacks often make the computation of the eigenvectors demanding or unfeasible for large problems. In this work we consider a particular class of nonnegative tensors associated to the multilinear PageRank modification of higher-order Markov chains. Based on the simplified topological epsilon-algorithm in its restarted form, we introduce an extrapolation-based acceleration of power method type algorithms, namely the shifted fixed-point method and the inner-outer method. The accelerated methods show remarkably better performance, with faster convergence rates and reduced overall computational time. Extensive numerical experiments on synthetic and real-world datasets demonstrate the advantages of the introduced extrapolation techniques
Euler-Richardson method preconditioned by weakly stochastic matrix algebras: a potential contribution to Pagerank computation
No full textLet S be a column stochastic matrix with at least one full row. Then S describes a Pagerank-like random walk since the computation of the Perron vector x of S can be tackled by solving a suitable M-matrix linear system Mx = y, where M = I − τ A, A is a column stochastic matrix and τ is a positive coefficient smaller than one. The Pagerank centrality index on graphs is a relevant example where these two formulations appear. Previous investigations have shown that the Euler- Richardson (ER) method can be considered in order to approach the Pagerank computation problem by means of preconditioning strategies. In this work, it is observed indeed that the classical power method can be embedded into the ER scheme, through a suitable simple preconditioner. Therefore, a new preconditioner is proposed based on fast Householder transformations and the concept of low complexity weakly stochastic algebras, which gives rise to an effective alternative to the power method for large-scale sparse problems. Detailed mathematical reasonings for this choice are given and the convergence properties discussed. Numerical tests performed on real-world datasets are presented, showing the advantages given by the use of the proposed Householder-Richardson method
Preparation of exploitation of medium-size tokamaks under European roadmap for the realization of fusion energy
No full textA Variance-aware Multiobjective Louvain-like Method for Community Detection in Multiplex Networks
No full textIn this paper, we focus on the community detection problem in multiplex
networks, i.e., networks with multiple layers having same node sets and no
inter-layer connections. In particular, we look for groups of nodes that can be
recognized as communities consistently across the layers. To this end, we
propose a new approach that generalizes the Louvain method by (a)
simultaneously updating average and variance of the modularity scores across
the layers, and (b) reformulating the greedy search procedure in terms of a
filter-based multiobjective optimization scheme. Unlike many previous
modularity maximization strategies, which rely on some form of aggregation of
the various layers, our multiobjective approach aims at maximizing the
individual modularities on each layer simultaneously. We report experiments on
synthetic and real-world networks, showing the effectiveness and the robustness
of the proposed strategies both in the informative case, where all layers show
the same community structure, and in the noisy case, where some layers
represent only noise
Nodal domain count for the generalized graph p-Laplacian
No full textInspired by the linear Schrödinger operator, we consider a generalized p-Laplacian operator on discrete graphs and present new results that characterize several spectral properties of this operator with particular attention to the nodal domain count of its eigenfunctions. Just like the one-dimensional continuous p-Laplacian, we prove that the variational spectrum of the discrete generalized p-Laplacian on forests is the entire spectrum. Moreover, we show how to transfer Weyl's inequalities for the Laplacian operator to the nonlinear case and prove new upper and lower bounds on the number of nodal domains of every eigenfunction of the generalized p-Laplacian on generic graphs, including variational eigenpairs. In particular, when applied to the linear case p=2, in addition to recovering well-known features, the new results provide novel properties of the linear Schrödinger operator
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