Exact bounds for distributed graph colouring

A distributed system is a collection of networked autonomous processing units which must work in a cooperative manner. Currently, large-scale distributed systems, such as various telecommunication and computer networks, are abundant and used in a multitude of tasks. The field of distributed computing studies what can be computed efficiently in such systems. Distributed systems are usually modelled as graphs where nodes represent the processors and edges denote communication links between processors. This thesis concentrates on the computational complexity of the distributed graph colouring problem. The objective of the graph colouring problem is to assign a colour to each node in such a way that no two nodes connected by an edge share the same colour. In particular, it is often desirable to use only a small number of colours. This task is a fundamental symmetry-breaking primitive in various distributed algorithms. A graph that has been coloured in this manner using at most k different colours is said to be k-coloured. This work examines the synchronous message-passing model of distributed computation: every node runs the same algorithm, and the system operates in discrete synchronous communication rounds. During each round, a node can communicate with its neighbours and perform local computation. In this model, the time complexity of a problem is the number of synchronous communication rounds required to solve the problem. It is known that 3-colouring any k-coloured directed cycle requires at least ½(log* k - 3) communication rounds and is possible in ½(log* k + 7) communication rounds for all k ≥ 3. This work shows that for any k ≥ 3, colouring a k-coloured directed cycle with at most three colours is possible in ½(log* k + 3) rounds. In contrast, it is also shown that for some values of k, colouring a directed cycle with at most three colours requires at least ½(log* k + 1) communication rounds. Furthermore, in the case of directed rooted trees, reducing a k-colouring into a 3-colouring requires at least log* k + 1 rounds for some k and possible in log* k + 3 rounds for all k ≥ 3. The new positive and negative results are derived using computational methods, as the existence of distributed colouring algorithms corresponds to the colourability of so-called neighbourhood graphs. The colourability of these graphs is analysed using Boolean satisfiability (SAT) solvers. Finally, this thesis shows that similar methods are applicable in capturing the existence of distributed algorithms for other graph problems, such as the maximal matching problem.

The hardness of approximating the boxicity, cubicity and threshold dimension of a graph

A k-dimensional box is the Cartesian product R-1 X R-2 X ... X R-k where each R-i is a closed interval on the real line. The boxicity of a graph G, denoted as box(G), is the minimum integer k such that G can be represented as the intersection graph of a collection of k-dimensional boxes. A unit cube in k-dimensional space or a k-cube is defined as the Cartesian product R-1 X R-2 X ... X R-k where each R-i is a closed interval oil the real line of the form a(i), a(i) + 1]. The cubicity of G, denoted as cub(G), is the minimum integer k such that G can be represented as the intersection graph of a collection of k-cubes. The threshold dimension of a graph G(V, E) is the smallest integer k such that E can be covered by k threshold spanning subgraphs of G. In this paper we will show that there exists no polynomial-time algorithm for approximating the threshold dimension of a graph on n vertices with a factor of O(n(0.5-epsilon)) for any epsilon > 0 unless NP = ZPP. From this result we will show that there exists no polynomial-time algorithm for approximating the boxicity and the cubicity of a graph on n vertices with factor O(n(0.5-epsilon)) for any epsilon > 0 unless NP = ZPP. In fact all these hardness results hold even for a highly structured class of graphs, namely the split graphs. We will also show that it is NP-complete to determine whether a given split graph has boxicity at most 3. (C) 2010 Elsevier B.V. All rights reserved.

Thermodynamic Stability of Potassium-beta-Alumina

The activity of K sub 2 O in a mixture of alpha -alumina and potassium beta -alumina has been determined using a solid state galvanic cell in the temperature range 600-1000K. The cell is written such that the right hand electrode is positive. The solid electrolyte consisted of a dispersion of alpha -alumina ( approx 15 vol.%) in a matrix of K beta -alumina. The emf of the cell was found to be reversible and to vary linearly with temperature. From the emf and auxiliary data on In sub 2 O sub 3 and K sub 2 O from the literature, the activity of K sub 2 O in the two-phase mixture is obtained. The standard free energy of formation of K beta -alumina from component oxides is given. Graphs.

Anti-apoptotic Protein BCL2 Down-regulates DNA End Joining in Cancer Cells

Cancer cells are often associated with secondary chromosomal rearrangements, such as deletions, inversions, and translocations, which could be the consequence of unrepaired/misrepaired DNA double strand breaks (DSBs). Nonhomologous DNA end joining is one of the most common pathways to repair DSBs in higher eukaryotes. By using oligomeric DNA substrates mimicking various endogenous DSBs in a cell-free system, we studied end joining (EJ) in different cancer cell lines. We found that the efficiency of EJ varies among cancer cells; however, there was no remarkable difference in the mechanism and expression of EJ proteins. Interestingly, cancer cells with lower levels of EJ possessed elevated expression of BCL2 and vice versa. Removal of BCL2 by immunoprecipitation or protein fractionation led to elevated EJ. More importantly, we show that overexpression of BCL2 or the addition of purified BCL2 led to the down-regulation of EJ. Further, we found that BCL2 interacts with KU proteins both in vitro and in vivo. Hence, our results suggest that EJ in cancer cells could be negatively regulated by the anti-apoptotic protein, BCL2, and this may contribute toward increased chromosomal abnormalities in cancer.

Over-expression and purification strategies for recombinant multi-protein oligomers: A case study of Mycobacterium tuberculosis sigma/anti-sigma factor protein complexes

The function of a protein in a cell often involves coordinated interactions with one or several regulatory partners. It is thus imperative to characterize a protein both in isolation as well as in the context of its complex with an interacting partner. High resolution structural information determined by X-ray crystallography and Nuclear Magnetic Resonance offer the best route to characterize protein complexes. These techniques, however, require highly purified and homogenous protein samples at high concentration. This requirement often presents a major hurdle for structural studies. Here we present a strategy based on co-expression and co-purification to obtain recombinant multi-protein complexes in the quantity and concentration range that can enable hitherto intractable structural projects. The feasibility of this strategy was examined using the sigma factor/anti-sigma factor protein complexes from Mycobacterium tuberculosis. The approach was successful across a wide range of sigma factors and their cognate interacting partners. It thus appears likely that the analysis of these complexes based on variations in expression constructs and procedures for the purification and characterization of these recombinant protein samples would be widely applicable for other multi-protein systems. (C) 2010 Elsevier Inc. All rights reserved.

Design of nonequivalent self-routing networks based on a matrix model

In earlier work, nonisomorphic graphs have been converted into networks to realize Multistage Interconnection networks, which are topologically nonequivalent to the Baseline network. The drawback of this technique is that these nonequivalent networks are not guaranteed to be self-routing, because each node in the graph model can be replaced by a (2 × 2) switch in any one of the four different configurations. Hence, the problem of routing in these networks remains unsolved. Moreover, nonisomorphic graphs were obtained by interconnecting bipartite loops in a heuristic manner; the heuristic nature of this procedure makes it difficult to guarantee full connectivity in large networks. We solve these problems through a direct approach, in which a matrix model for self-routing networks is developed. An example is given to show that this model encompases nonequivalent self-routing networks. This approach has the additional advantage in that the matrix model itself ensures full connectivity.

Simulation and graph mining tools for improving gene mapping efficiency

Gene mapping is a systematic search for genes that affect observable characteristics of an organism. In this thesis we offer computational tools to improve the efficiency of (disease) gene-mapping efforts. In the first part of the thesis we propose an efficient simulation procedure for generating realistic genetical data from isolated populations. Simulated data is useful for evaluating hypothesised gene-mapping study designs and computational analysis tools. As an example of such evaluation, we demonstrate how a population-based study design can be a powerful alternative to traditional family-based designs in association-based gene-mapping projects. In the second part of the thesis we consider a prioritisation of a (typically large) set of putative disease-associated genes acquired from an initial gene-mapping analysis. Prioritisation is necessary to be able to focus on the most promising candidates. We show how to harness the current biomedical knowledge for the prioritisation task by integrating various publicly available biological databases into a weighted biological graph. We then demonstrate how to find and evaluate connections between entities, such as genes and diseases, from this unified schema by graph mining techniques. Finally, in the last part of the thesis, we define the concept of reliable subgraph and the corresponding subgraph extraction problem. Reliable subgraphs concisely describe strong and independent connections between two given vertices in a random graph, and hence they are especially useful for visualising such connections. We propose novel algorithms for extracting reliable subgraphs from large random graphs. The efficiency and scalability of the proposed graph mining methods are backed by extensive experiments on real data. While our application focus is in genetics, the concepts and algorithms can be applied to other domains as well. We demonstrate this generality by considering coauthor graphs in addition to biological graphs in the experiments.

Mixed Convection Induced in a Gas Flowing Past a Hot Horizontal Flat Plate

A boundary layer analysis of mixed convective motion over a hot horizontal flat plate is performed under the conditions of steady flow and low speed. Use of the Howarth-Dorodnytsyn transformation makes it possible to dispense with the usual Boussinesq approximation, and variable gas properties are accounted for via the assumption that dynamic viscosity and thermal conductivity are proportional to the absolute temperature. The formulation presented enables the entire mixed convection regime to be described by a single set of equations. Finite difference solutions when the Prandtl number is 0.72 are obtained over the entire range of the mixed convection parameter ξ from 0 (free convection) to 1 (forced convection) and heating parameter ▵ values from 2 to 12. The effects of both ξ and ▵on the velocity profiles, the temperature profiles, and the variation of skin friction and heat transfer functions are clearly illustrated in tables and graphs.

Almost Stable Matchings by Truncating the Gale–Shapley Algorithm

We show that the ratio of matched individuals to blocking pairs grows linearly with the number of propose–accept rounds executed by the Gale–Shapley algorithm for the stable marriage problem. Consequently, the participants can arrive at an almost stable matching even without full information about the problem instance; for each participant, knowing only its local neighbourhood is enough. In distributed-systems parlance, this means that if each person has only a constant number of acceptable partners, an almost stable matching emerges after a constant number of synchronous communication rounds. We apply our results to give a distributed (2 + ε)-approximation algorithm for maximum-weight matching in bicoloured graphs and a centralised randomised constant-time approximation scheme for estimating the size of a stable matching.

Distributed algorithms for edge dominating sets

An edge dominating set for a graph G is a set D of edges such that each edge of G is in D or adjacent to at least one edge in D. This work studies deterministic distributed approximation algorithms for finding minimum-size edge dominating sets. The focus is on anonymous port-numbered networks: there are no unique identifiers, but a node of degree d can refer to its neighbours by integers 1, 2, ..., d. The present work shows that in the port-numbering model, edge dominating sets can be approximated as follows: in d-regular graphs, to within 4 − 6/(d + 1) for an odd d and to within 4 − 2/d for an even d; and in graphs with maximum degree Δ, to within 4 − 2/(Δ − 1) for an odd Δ and to within 4 − 2/Δ for an even Δ. These approximation ratios are tight for all values of d and Δ: there are matching lower bounds.