Modelling heterotachy in phylogenetic inference by reversible-jump Markov chain Monte Carlo

The rate at which a given site in a gene sequence alignment evolves over time may vary. This phenomenon-known as heterotachy-can bias or distort phylogenetic trees inferred from models of sequence evolution that assume rates of evolution are constant. Here, we describe a phylogenetic mixture model designed to accommodate heterotachy. The method sums the likelihood of the data at each site over more than one set of branch lengths on the same tree topology. A branch-length set that is best for one site may differ from the branch-length set that is best for some other site, thereby allowing different sites to have different rates of change throughout the tree. Because rate variation may not be present in all branches, we use a reversible-jump Markov chain Monte Carlo algorithm to identify those branches in which reliable amounts of heterotachy occur. We implement the method in combination with our 'pattern-heterogeneity' mixture model, applying it to simulated data and five published datasets. We find that complex evolutionary signals of heterotachy are routinely present over and above variation in the rate or pattern of evolution across sites, that the reversible-jump method requires far fewer parameters than conventional mixture models to describe it, and serves to identify the regions of the tree in which heterotachy is most pronounced. The reversible-jump procedure also removes the need for a posteriori tests of 'significance' such as the Akaike or Bayesian information criterion tests, or Bayes factors. Heterotachy has important consequences for the correct reconstruction of phylogenies as well as for tests of hypotheses that rely on accurate branch-length information. These include molecular clocks, analyses of tempo and mode of evolution, comparative studies and ancestral state reconstruction. The model is available from the authors' website, and can be used for the analysis of both nucleotide and morphological data.

Inference on microsatellite mutation processes in the invasive mite, Varroa destructor, using reversible jump Markov chain Monte Carlo

Varroa destructor is a parasitic mite of the Eastern honeybee Apis cerana. Fifty years ago, two distinct evolutionary lineages (Korean and Japanese) invaded the Western honeybee Apis mellifera. This haplo-diploid parasite species reproduces mainly through brother sister matings, a system which largely favors the fixation of new mutations. In a worldwide sample of 225 individuals from 21 locations collected on Western honeybees and analyzed at 19 microsatellite loci, a series of de novo mutations was observed. Using historical data concerning the invasion, this original biological system has been exploited to compare three mutation models with allele size constraints for microsatellite markers: stepwise (SMM) and generalized (GSM) mutation models, and a model with mutation rate increasing exponentially with microsatellite length (ESM). Posterior probabilities of the three models have been estimated for each locus individually using reversible jump Markov Chain Monte Carlo. The relative support of each model varies widely among loci, but the GSM is the only model that always receives at least 9% support, whatever the locus. The analysis also provides robust estimates of mutation parameters for each locus and of the divergence time of the two invasive lineages (67,000 generations with a 90% credibility interval of 35,000-174,000). With an average of 10 generations per year, this divergence time fits with the last post-glacial Korea Japan land separation. (c) 2005 Elsevier Inc. All rights reserved.

Bayesian analysis of correlated evolution of discrete characters by reversible-jump Markov chain Monte Carlo

We describe a Bayesian method for investigating correlated evolution of discrete binary traits on phylogenetic trees. The method fits a continuous-time Markov model to a pair of traits, seeking the best fitting models that describe their joint evolution on a phylogeny. We employ the methodology of reversible-jump ( RJ) Markov chain Monte Carlo to search among the large number of possible models, some of which conform to independent evolution of the two traits, others to correlated evolution. The RJ Markov chain visits these models in proportion to their posterior probabilities, thereby directly estimating the support for the hypothesis of correlated evolution. In addition, the RJ Markov chain simultaneously estimates the posterior distributions of the rate parameters of the model of trait evolution. These posterior distributions can be used to test among alternative evolutionary scenarios to explain the observed data. All results are integrated over a sample of phylogenetic trees to account for phylogenetic uncertainty. We implement the method in a program called RJ Discrete and illustrate it by analyzing the question of whether mating system and advertisement of estrus by females have coevolved in the Old World monkeys and great apes.

Reversible phase variation in the phnE gene, which is required for phosphonate metabolism in Escherichia coli K-12

It is known that Escherichia coli K-12 is cryptic (Phn(-)) for utilization of methyl phosphonate (MePn) and that Phn(+) variants can be selected for growth on MePn as the sole P source. Variants arise from deletion via a possible slip strand mechanism of one of three direct 8-bp repeat sequences in phnE, which restores function to a component of a putative ABC type transporter. Here we show that Phn(+) variants are present at the surprisingly high frequency of >10(-2) in K-12 strains. Amplified-fragment length polymorphism analysis was used to monitor instability in phnE in various strains growing under different conditions. This revealed that, once selection for growth on MePn is removed, Phn(+) revertants reappear and accumulate at high levels through reinsertion of the 8-bp repeat element sequence. It appears that, in K-12, phnE contains a high-frequency reversible gene switch, producing phase variation which either allows ("on" form) or blocks ("off" form) MePn utilization. The switch can also block usage of other metabolizable alkyl phosphonates, including the naturally occurring 2-aminoethylphosphonate. All K-12 strains, obtained from collections, appear in the "off" form even when bearing mutations in mutS, mutD, or dnaQ which are known to enhance slip strand events between repetitive sequences. The ability to inactivate the phnE gene appears to be unique to K-12 strains since the B strain is naturally Phn(+) and lacks the inactivating 8-bp insertion in phnE, as do important pathogenic strains for which genome sequences are known and also strains isolated recently from environmental sources.

Reversible, nondegradative conversion of crystalline aromatic poly(ether ketone)s into organo-soluble poly(ether dithioketal)s

Crystalline aromatic poly(ether ketone)s Such as PEEK and PEK may be cleanly and reversibly derivatized by dithioketalization of the carbonyl groups With 1,2-ethanedithiol or 1,3-propanedithiol under strong acid conditions. The resulting 1,3-dithiolane and 1,3-dithiane polymers are hydrolytically stable, amorphous, and readily soluble in organic solvents such as chloroform and THF and are thus (unlike their parent polymers) easily characterized by gel permeation chromatography (GPC). GPC analysis of a range of derivatized PEEK samples using light-scattering detection revealed, in some instances, a bimodal molecular weight distribution with a small but potentially significant (and previously undetected) very high-molecular-weight fraction.

Tin and tin-titanium as catalyst components for reversible hydrogen storage of sodium aluminium hydride

This paper is concerned with the effects of adding tin and/or titanium dopant to sodium aluminium hydride for both dehydrogenation and re-hydrogenation reactions during their reversible storage of molecular hydrogen. Temperature programmed decomposition (TPD) measurements show that the dehydrogenation kinetics of NaAlH4 are significantly enhanced upon doping the material with 2 mol% of tributyltin hydride, Sn(Bu)(3)H but the tin catalyst dopant is shown to be inferior than titanium. On the other hand, in this preliminary work, a significant synergetic catalytic effect is clearly revealed in material co-doped with both titanium and tin catalysts which shows the highest reversible rates of dehydrogenation and re-hydrogenation (after their hydrogen depletion). The re-hydrogenation rates of depleted Sn/Ti/NaAlH4 evaluated at both 9.5 and 140 bars hydrogen are also found to be favourable compared to the Ti/NaAlH4, which clearly suggest the importance of the catalyst choice. Basing on these results some mechanistic insights for the catalytic reversible dehydrogenation and re-hydrogenation processes of Sn/Ti/NaAlH4 are therefore made. (C) 2006 Elsevier Ltd. All rights reserved.

Intelligent wireless web services: context-aware computing in construction-logistics supply chain

The construction industry has incurred a considerable amount of waste as a result of poor logistics supply chain network management. Therefore, managing logistics in the construction industry is critical. An effective logistic system ensures delivery of the right products and services to the right players at the right time while minimising costs and rewarding all sectors based on value added to the supply chain. This paper reports on an on-going research study on the concept of context-aware services delivery in the construction project supply chain logistics. As part of the emerging wireless technologies, an Intelligent Wireless Web (IWW) using context-aware computing capability represents the next generation ICT application to construction-logistics management. This intelligent system has the potential of serving and improving the construction logistics through access to context-specific data, information and services. Existing mobile communication deployments in the construction industry rely on static modes of information delivery and do not take into account the worker’s changing context and dynamic project conditions. The major problems in these applications are lack of context-specificity in the distribution of information, services and other project resources, and lack of cohesion with the existing desktop based ICT infrastructure. The research works focus on identifying the context dimension such as user context, environmental context and project context, selection of technologies to capture context-parameters such wireless sensors and RFID, selection of supporting technologies such as wireless communication, Semantic Web, Web Services, agents, etc. The process of integration of Context-Aware Computing and Web-Services to facilitate the creation of intelligent collaboration environment for managing construction logistics will take into account all the necessary critical parameters such as storage, transportation, distribution, assembly, etc. within off and on-site project.

Parallel and distributed computing with Java

The Java language first came to public attention in 1995. Within a year, it was being speculated that Java may be a good language for parallel and distributed computing. Its core features, including being objected oriented and platform independence, as well as having built-in network support and threads, has encouraged this view. Today, Java is being used in almost every type of computer-based system, ranging from sensor networks to high performance computing platforms, and from enterprise applications through to complex research-based.simulations. In this paper the key features that make Java a good language for parallel and distributed computing are first discussed. Two Java-based middleware systems, namely MPJ Express, an MPI-like Java messaging system, and Tycho, a wide-area asynchronous messaging framework with an integrated virtual registry are then discussed. The paper concludes by highlighting the advantages of using Java as middleware to support distributed applications.

Building collaborative environments for advanced computing

Synchronous collaborative systems allow geographically distributed users to form a virtual work environment enabling cooperation between peers and enriching the human interaction. The technology facilitating this interaction has been studied for several years and various solutions can be found at present. In this paper, we discuss our experiences with one such widely adopted technology, namely the Access Grid [1]. We describe our experiences with using this technology, identify key problem areas and propose our solution to tackle these issues appropriately. Moreover, we propose the integration of Access Grid with an Application Sharing tool, developed by the authors. Our approach allows these integrated tools to utilise the enhanced features provided by our underlying dynamic transport layer.

Autonomous execution of tasks by swarm carrier agents in swarm-array computing

How can a bridge be built between autonomic computing approaches and parallel computing system? The work reported in this paper is motivated towards bridging this gap by proposing swarm-array computing, a novel technique to achieve autonomy for distributed parallel computing systems. Among three proposed approaches, the second approach, namely 'Intelligent Agents' is of focus in this paper. The task to be executed on parallel computing cores is considered as a swarm of autonomous agents. A task is carried to a computing core by carrier. agents and can be seamlessly transferred between cores in the event of a pre-dicted failure, thereby achieving self-ware objectives of autonomic computing. The feasibility of the proposed approach is validated on a multi-agent simulator.