Clustering in diffusively coupled networks

This paper shows how different mechanisms may lead to clustering behavior in connected networks consisting of diffusively coupled agents. In contrast to the widely studied synchronization processes, in which the states of all the coupled agents converge to the same value asymptotically, in the cluster synchronization problem studied in this paper, we require all the interconnected agents to evolve into several clusters and each agent only to synchronize within its cluster. The first mechanism is that agents have different self-dynamics, and those agents having the same self-dynamics may evolve into the same cluster. When the agents' self-dynamics are identical, we present two other mechanisms under which cluster synchronization might be achieved. One is the presence of delays and the other is the existence of both positive and negative couplings between the agents. Some sufficient and/or necessary conditions are constructed to guarantee n-cluster synchronization. Simulation results are presented to illustrate the effectiveness of the theoretical analysis. (C) 2011 Elsevier Ltd. All rights reserved

Products of Generalized Stochastic Sarymsakov Matrices

In the set of stochastic, indecomposable, aperiodic (SIA) matrices, the class of stochastic Sarymsakov matrices is the largest known subset (i) that is closed under matrix multiplication and (ii) the infinitely long left-product of the elements from a compact subset converges to a rank-one matrix. In this paper, we show that a larger subset with these two properties can be derived by generalizing the standard definition for Sarymsakov matrices. The generalization is achieved either by introducing an "SIA index", whose value is one for Sarymsakov matrices, and then looking at those stochastic matrices with larger SIA indices, or by considering matrices that are not even SIA. Besides constructing a larger set, we give sufficient conditions for generalized Sarymsakov matrices so that their products converge to rank-one matrices. The new insight gained through studying generalized Sarymsakov matrices and their products has led to a new understanding of the existing results on consensus algorithms and will be helpful for the design of network coordination algorithms

Dissecting endonuclease and exonuclease activities in endonuclease V from Thermotoga maritima

Endonuclease V is an enzyme that initiates a conserved DNA repair pathway by making an endonucleolytic incision at the 3′-side 1 nt from a deaminated base lesion. DNA cleavage analysis using mutants defective in DNA binding and Mn2+ as a metal cofactor reveals a novel 3′-exonuclease activity in endonuclease V [Feng,H., Dong,L., Klutz,A.M., Aghaebrahim,N. and Cao,W. (2005) Defining amino acid residues involved in DNA-protein interactions and revelation of 3′-exonuclease activity in endonuclease V. Biochemistry, 44, 11486–11495.]. This study defines the enzymatic nature of the endonuclease and exonuclease activity in endonuclease V from Thermotoga maritima. In addition to its well-known inosine-dependent endonuclease, Tma endonuclease V also exhibits inosine-dependent 3′-exonuclease activity. The dependence on an inosine site and the exonuclease nature of the 3′-exonuclease activity was demonstrated using 5′-labeled and internally-labeled inosine-containing DNA and a H214D mutant that is defective in non-specific nuclease activity. Detailed kinetic analysis using 3′-labeled DNA indicates that Tma endonuclease V also possesses non-specific 5′-exonuclease activity. The multiplicity of the endonuclease and exonuclease activity is discussed with respect to deaminated base repair

Random Asynchronous Iterations in Distributed Coordination Algorithms

Distributed coordination algorithms (DCA) carry out information processing processes among a group of networked agents without centralized information fusion. Though it is well known that DCA characterized by an SIA (stochastic, indecomposable, aperiodic) matrix generate consensus asymptotically via synchronous iterations, the dynamics of DCA with asynchronous iterations have not been studied extensively, especially when viewed as stochastic processes. This paper aims to show that for any given irreducible stochastic matrix, even non-SIA, the corresponding DCA lead to consensus successfully via random asynchronous iterations under a wide range of conditions on the transition probability. Particularly, the transition probability is neither required to be independent and identically distributed, nor characterized by a Markov chain

Methods to Improve the Teaching Effect of the Professional Course of the University

Aiming at the poor teaching effect of professional course in university, student interest is not high and show how to improve the important measures of the teaching effect of professional course in university and universities, starting from the view of teachers, effective preparation is the prerequisite to improve the professional teaching, effective classroom teaching is the effective guarantee to improve the teaching of professional course, advanced teaching methods is the fundamental guarantee to enhance the teaching of professional courses, starting from the perspective of students, learning interest is the basic power, improve the teaching of professional courses ability is the fundamental aim of improve the teaching of professional courses

Compound-specific delta D and its hydrological and environmental implication in the lakes on the Tibetan Plateau

The hydrogen isotopic composition (delta D) of n-alkanes in lacustrine sediments is widely used in palaeoenvironmental studies, but the heterogeneous origins and relative contributions of these lipids provide challenges for the interpretation of the increasing dataset as an environment and climatic proxy. We systematically investigated n-alkane delta D values from 51 submerged plants (39 Potamogeton, 1 Myriophyllum, and 11 Ruppia), 13 algae (5 Chara, 3 Cladophora, and 5 Spirogyra) and 20 terrestrial plants (10 grasses and 10 shrubs) in and around 15 lakes on the Tibetan Plateau. Our results demonstrate that delta D values of C-29 n-alkane are correlated significantly with the lake water delta D values both for algae (R (2)=0.85, p < 0.01, n=9) and submerged plants (R (2)=0.90, p < 0.01, n=25), indicating that delta D values of these algae and submerged plants reflect the delta D variation of lake water. We find that apparent hydrogen isotope fractionation factors between individual n-alkanes and water (epsilon (a/w)) are not constant among different algae and submerged plants, as well as in a single genus under different liminological conditions, indicating that the biosynthesis or environmental conditions (e.g. salinity) may affect their delta D values. The delta D values of submerged plant Ruppia in the Xiligou Lake (a closed lake) are significant enriched in D than those of terrestrial grasses around the lake (one-way ANOVA, p < 0.01), but the algae Chara in the Keluke Lake (an open lake) display similar delta D values with grasses around the lake (one-way ANOVA, p=0.826 > 0.05), suggesting that the n-alkane delta D values of the algae and submerged plants record the signal of D enrichment in lake water relative to precipitation only in closed lakes in arid and semi-arid area. For each algae and submerged plant sample, we find uniformed delta D values of different chain length n-alkanes, implying that, in combination with other proxies such as Paq and Average Chain Length, the offset between the delta D values of different chain length n-alkanes can help determine the source of sedimentary n-alkanes as well as inferring the hydrological characteristics of an ancient lake basin (open vs closed lake)

Understanding and predicting synthetic lethal genetic interactions in Saccharomyces cerevisiae using domain genetic interactions

Genetic interactions have been widely used to define functional relationships between proteins and pathways. In this study, we demonstrated that yeast synthetic lethal genetic interactions can be explained by the genetic interactions between domains of those proteins. The domain genetic interactions rarely overlap with the domain physical interactions from iPfam database and provide a complementary view about domain relationships. Moreover, we found that domains in multidomain yeast proteins contribute to their genetic interactions differently. The domain genetic interactions help more precisely define the function related to the synthetic lethal genetic interactions, and then help understand how domains contribute to different functionalities of multidomain proteins. Using the probabilities of domain genetic interactions, we were able to predict novel yeast synthetic lethal genetic interactions. Furthermore, we had also identified novel compensatory pathways from the predicted synthetic lethal genetic interactions. Our study significantly improved the understanding of yeast mulitdomain proteins, the synthetic lethal genetic interactions and the functional relationships between proteins and pathways.Comment: 36 page, 4 figure