Graph measures and network robustness

Network robustness research aims at finding a measure to quantify network robustness. Once such a measure has been established, we will be able to compare networks, to improve existing networks and to design new networks that are able to continue to perform well when it is subject to failures or attacks. In this paper we survey a large amount of robustness measures on simple, undirected and unweighted graphs, in order to offer a tool for network administrators to evaluate and improve the robustness of their network. The measures discussed in this paper are based on the concepts of connectivity (including reliability polynomials), distance, betweenness and clustering. Some other measures are notions from spectral graph theory, more precisely, they are functions of the Laplacian eigenvalues. In addition to surveying these graph measures, the paper also contains a discussion of their functionality as a measure for topological network robustness

Stochastic methods for measurement-based network control

The main task of network administrators is to ensure that their network functions properly. Whether they manage a telecommunication or a road network, they generally base their decisions on the analysis of measurement data. Inspired by such network control applications, this dissertation investigates several stochastic modelling techniques for data analysis. The focus is on two areas within the field of stochastic processes: change point detection and queueing theory. Part I deals with statistical methods for the automatic detection of change points, being changes in the probability distribution underlying a data sequence. This part starts with a review of existing change point detection methods for data sequences consisting of independent observations. The main contribution of this part is the generalisation of the classic cusum method to account for dependence within data sequences. We analyse the false alarm probability of the resulting methods using a large deviations approach. The part also discusses numerical tests of the new methods and a cyber attack detection application, in which we investigate how to detect dns tunnels. The main contribution of Part II is the application of queueing models (probabilistic models for waiting lines) to situations in which the system to be controlled can only be observed partially. We consider two types of partial information. Firstly, we develop a procedure to get insight into the performance of queueing systems between consecutive system-state measurements and apply it in a numerical study, which was motivated by capacity management in cable access networks. Secondly, inspired by dynamic road control applications, we study routing policies in a queueing system for which just part of the jobs are observable and controllable

Preferential adsorption of high density lipoprotein (HDL) in blood plasma/polymer interaction

A few studies on the adsorption of plasma proteins to polymeric surfaces show that major plasma proteins: albumin (Alb), fibrinogen (Fb) and immunoglobulin (IgG) are adsorbed in much smaller quantities from plasma than from protein solutions (1,2). Present results show that this difference in adsorption is due to the preferential adsorption of high density lipoprotein from plasma onto the material surfaces studied (PVC and PS)

Effective graph resistance

AbstractThis paper studies an interesting graph measure that we call the effective graph resistance. The notion of effective graph resistance is derived from the field of electric circuit analysis where it is defined as the accumulated effective resistance between all pairs of vertices. The objective of the paper is twofold. First, we survey known formulae of the effective graph resistance and derive other representations as well. The derivation of new expressions is based on the analysis of the associated random walk on the graph and applies tools from Markov chain theory. This approach results in a new method to approximate the effective graph resistance. A second objective of this paper concerns the optimisation of the effective graph resistance for graphs with given number of vertices and diameter, and for optimal edge addition. A set of analytical results is described, as well as results obtained by exhaustive search. One of the foremost applications of the effective graph resistance we have in mind, is the analysis of robustness-related problems. However, with our discussion of this informative graph measure we hope to open up a wealth of possibilities of applying the effective graph resistance to all kinds of networks problems

Distributed flow optimization and cascading effects in weighted complex networks

We investigate the effect of a specific edge weighting scheme $\sim (k_i k_j)^{\beta}$ on distributed flow efficiency and robustness to cascading failures in scale-free networks. In particular, we analyze a simple, yet fundamental distributed flow model: current flow in random resistor networks. By the tuning of control parameter $\beta$ and by considering two general cases of relative node processing capabilities as well as the effect of bandwidth, we show the dependence of transport efficiency upon the correlations between the topology and weights. By studying the severity of cascades for different control parameter $\beta$, we find that network resilience to cascading overloads and network throughput is optimal for the same value of $\beta$ over the range of node capacities and available bandwidth

Mitochondrial and plastidial COG0354 proteins have folate-dependent functions in iron–sulphur cluster metabolism

COG0354 proteins have been implicated in synthesis or repair of iron/sulfur (Fe/S) clusters in all domains of life, and those of bacteria, animals, and protists have been shown to require a tetrahydrofolate to function. Two COG0354 proteins were identified in Arabidopsis and many other plants, one (At4g12130) related to those of α-proteobacteria and predicted to be mitochondrial, the other (At1g60990) related to those of cyanobacteria and predicted to be plastidial. Grasses and poplar appear to lack the latter. The predicted subcellular locations of the Arabidopsis proteins were validated by in vitro import assays with purified pea organelles and by targeting assays in Arabidopsis and tobacco protoplasts using green fluorescent protein fusions. The At4g12130 protein was shown to be expressed mainly in flowers, siliques, and seeds, whereas the At1g60990 protein was expressed mainly in young leaves. The folate dependence of both Arabidopsis proteins was established by functional complementation of an Escherichia coli COG0354 (ygfZ) deletant; both plant genes restored in vivo activity of the Fe/S enzyme MiaB but restoration was abrogated when folates were eliminated by deleting folP. Insertional inactivation of At4g12130 was embryo lethal; this phenotype was reversed by genetic complementation of the mutant. These data establish that COG0354 proteins have a folate-dependent function in mitochondria and plastids, and that the mitochondrial protein is essential. That plants retain mitochondrial and plastidial COG0354 proteins with distinct phylogenetic origins emphasizes how deeply the extant Fe/S cluster assembly machinery still reflects the ancient endosymbioses that gave rise to plants

Nit1 is a metabolite repair enzyme that hydrolyzes deaminated glutathione

The mammalian gene Nit1 (nitrilase-like protein 1) encodes a protein that is highly conserved in eukaryotes and is thought to act as a tumor suppressor. Despite being ∼35% sequence identical to ω-amidase (Nit2), the Nit1 protein does not hydrolyze efficiently α-ketoglutaramate (a known physiological substrate of Nit2), and its actual enzymatic function has so far remained a puzzle. In the present study, we demonstrate that both the mammalian Nit1 and its yeast ortholog are amidases highly active toward deaminated glutathione (dGSH; i.e., a form of glutathione in which the free amino group has been replaced by a carbonyl group). We further show that Nit1-KO mutants of both human and yeast cells accumulate dGSH and the same compound is excreted in large amounts in the urine of Nit1-KO mice. Finally, we show that several mammalian aminotransferases (transaminases), both cytosolic and mitochondrial, can form dGSH via a common (if slow) side-reaction and provide indirect evidence that transaminases are mainly responsible for dGSH formation in cultured mammalian cells. Altogether, these findings delineate a typical instance of metabolite repair, whereby the promiscuous activity of some abundant enzymes of primary metabolism leads to the formation of a useless and potentially harmful compound, which needs a suitable “repair enzyme” to be destroyed or reconverted into a useful metabolite. The need for a dGSH repair reaction does not appear to be limited to eukaryotes: We demonstrate that Nit1 homologs acting as excellent dGSH amidases also occur in Escherichia coli and other glutathione-producing bacteria