Core-based Methodology: An Automated Approach for Implementing a Complete System From Algorithms to a Heterogeneous Network Including FPGAs

In this paper, we present a methodology for implementing a complete Digital Signal Processing (DSP) system onto a heterogeneous network including Field Programmable Gate Arrays (FPGAs) automatically. The methodology aims to allow design refinement and real time verification at the system level. The DSP application is constructed in the form of a Data Flow Graph (DFG) which provides an entry point to the methodology. The netlist for parts that are mapped onto the FPGA(s) together with the corresponding software and hardware Application Protocol Interface (API) are also generated. Using a set of case studies, we demonstrate that the design and development time can be significantly reduced using the methodology developed.

Parallel and nonparallel ecological, morphological and genetic divergence in lake-stream stickleback from a single catchment

Parallel phenotypic evolution in similar environments has been well studied in evolutionary biology; however, comparatively little is known about the influence of determinism and historical contingency on the nature, extent and generality of this divergence. Taking advantage of a novel system containing multiple lake-stream stickleback populations, we examined the extent of ecological, morphological and genetic divergence between three-spined stickleback present in parapatric environments. Consistent with other lake-stream studies, we found a shift towards a deeper body and shorter gill rakers in stream fish. Morphological shifts were concurrent with changes in diet, indicated by both stable isotope and stomach contents analysis. Performing a multivariate test for shared and unique components of evolutionary response to the distance gradient from the lake, we found a strong signature of parallel adaptation. Nonparallel divergence was also present, attributable mainly to differences between river locations. We additionally found evidence of genetic substructuring across five lake-stream transitions, indicating that some level of reproductive isolation occurs between populations in these habitats. Strong correlations between pairwise measures of morphological, ecological and genetic distance between lake and stream populations supports the hypothesis that divergent natural selection between habitats drives adaptive divergence and reproductive isolation. Lake-stream stickleback divergence in Lough Neagh provides evidence for the deterministic role of selection and supports the hypothesis that parallel selection in similar environments may initiate parallel speciation.

Genotypic and phenotypic diversity of the noncapsulated Haemophilus influenzae:Adaptation and pathogenesis in the human airways

The human respiratory tract contains a highly adapted microbiota including commensal and opportunistic pathogens. Noncapsulated or nontypable Haemophilus influenzae (NTHi) is a human-restricted member of the normal airway microbiota in healthy carriers and an opportunistic pathogen in immunocompromised individuals. The duality of NTHi as a colonizer and as a symptomatic infectious agent is closely related to its adaptation to the host, which in turn greatly relies on the genetic plasticity of the bacterium and is facilitated by its condition as a natural competent. The variable genotype of NTHi accounts for its heterogeneous gene expression and variable phenotype, leading to differential host-pathogen interplay among isolates. Here we review our current knowledge of NTHi diversity in terms of genotype, gene expression, antigenic variation, and the phenotypes associated with colonization and pathogenesis. The potential benefits of NTHi diversity studies discussed herein include the unraveling of pathogenicity clues, the generation of tools to predict virulence from genomic data, and the exploitation of a unique natural system for the continuous monitoring of long-term bacterial evolution in human airways exposed to noxious agents. Finally, we highlight the challenge of monitoring both the pathogen and the host in longitudinal studies, and of applying comparative genomics to clarify the meaning of the vast NTHi genetic diversity and its translation to virulence phenotypes.

Swarm scheduling approaches for work-flow applications with security constraints in distributed data-intensive computing environments

The scheduling problem in distributed data-intensive computing environments has become an active research topic due to the tremendous growth in grid and cloud computing environments. As an innovative distributed intelligent paradigm, swarm intelligence provides a novel approach to solving these potentially intractable problems. In this paper, we formulate the scheduling problem for work-flow applications with security constraints in distributed data-intensive computing environments and present a novel security constraint model. Several meta-heuristic adaptations to the particle swarm optimization algorithm are introduced to deal with the formulation of efficient schedules. A variable neighborhood particle swarm optimization algorithm is compared with a multi-start particle swarm optimization and multi-start genetic algorithm. Experimental results illustrate that population based meta-heuristics approaches usually provide a good balance between global exploration and local exploitation and their feasibility and effectiveness for scheduling work-flow applications. © 2010 Elsevier Inc. All rights reserved.

Pan-genome analysis of the emerging foodborne pathogen Cronobacter spp. suggests a species-level bidirectional divergence driven by niche adaptation

Background: Members of the genus Cronobacter are causes of rare but severe illness in neonates and preterm infants following the ingestion of contaminated infant formula. Seven species have been described and two of the species genomes were subsequently published. In this study, we performed comparative genomics on eight strains of Cronobacter, including six that we sequenced (representing six of the seven species) and two previously published, closed genomes.

Results: We identified and characterized the features associated with the core and pan genome of the genus Cronobacter in an attempt to understand the evolution of these bacteria and the genetic content of each species. We identified 84 genomic regions that are present in two or more Cronobacter genomes, along with 45 unique genomic regions. Many potentially horizontally transferred genes, such as lysogenic prophages, were also identified. Most notable among these were several type six secretion system gene clusters, transposons that carried tellurium, copper and/or silver resistance genes, and a novel integrative conjugative element.

Conclusions: Cronobacter have diverged into two clusters, one consisting of C. dublinensis and C. muytjensii (Cdub-Cmuy) and the other comprised of C. sakazakii, C. malonaticus, C. universalis, and C. turicensis, (Csak-Cmal-Cuni-Ctur) from the most recent common ancestral species. While several genetic determinants for plant-association and human virulence could be found in the core genome of Cronobacter, the four Cdub-Cmuy clade genomes contained several accessory genomic regions important for survival in a plant-associated environmental niche, while the Csak-Cmal-Cuni-Ctur clade genomes harbored numerous virulence-related genetic traits.

On the Complexity of Universal Leader Election

Electing a leader is a fundamental task in distributed computing. In its implicit version, only the leader must know who is the elected leader. This paper focuses on studying the message and time complexity of randomized implicit leader election in synchronous distributed networks. Surprisingly, the most "obvious" complexity bounds have not been proven for randomized algorithms. The "obvious" lower bounds of O(m) messages (m is the number of edges in the network) and O(D) time (D is the network diameter) are non-trivial to show for randomized (Monte Carlo) algorithms. (Recent results that show that even O(n) (n is the number of nodes in the network) is not a lower bound on the messages in complete networks, make the above bounds somewhat less obvious). To the best of our knowledge, these basic lower bounds have not been established even for deterministic algorithms (except for the limited case of comparison algorithms, where it was also required that some nodes may not wake up spontaneously, and that D and n were not known).

We establish these fundamental lower bounds in this paper for the general case, even for randomized Monte Carlo algorithms. Our lower bounds are universal in the sense that they hold for all universal algorithms (such algorithms should work for all graphs), apply to every D, m, and n, and hold even if D, m, and n are known, all the nodes wake up simultaneously, and the algorithms can make anyuse of node's identities. To show that these bounds are tight, we present an O(m) messages algorithm. An O(D) time algorithm is known. A slight adaptation of our lower bound technique gives rise to an O(m) message lower bound for randomized broadcast algorithms.

An interesting fundamental problem is whether both upper bounds (messages and time) can be reached simultaneously in the randomized setting for all graphs. (The answer is known to be negative in the deterministic setting). We answer this problem partially by presenting a randomized algorithm that matches both complexities in some cases. This already separates (for some cases) randomized algorithms from deterministic ones. As first steps towards the general case, we present several universal leader election algorithms with bounds that trade-off messages versus time. We view our results as a step towards understanding the complexity of universal leader election in distributed networks.

Genetic basis of Congenital Erythrocytosis:mutation update and online databases

Congenital Erythrocytosis (CE), or congenital polycythemia, represents a rare and heterogeneous clinical entity. It is caused by deregulated red blood cell production where erythrocyte overproduction results in elevated hemoglobin and hematocrit levels. Primary congenital familial erythrocytosis is associated with low erythropoietin (Epo) levels and results from mutations in the Epo receptor gene (EPOR). Secondary congenital erythrocytosis arises from conditions causing tissue hypoxia and results in increased Epo production. These include hemoglobin variants with increased affinity for oxygen (HBB, HBA mutations), decreased production of 2,3-bisphosphoglycerate due to BPGM mutations, or mutations in the genes involved in the hypoxia sensing pathway (VHL, EPAS1 and EGLN1). Depending on the affected gene, CE can be inherited either in an autosomal dominant or recessive mode, with sporadic cases arising de novo. Despite recent important discoveries in the molecular pathogenesis of CE, the molecular causes remain to be identified in about 70% of the patients. With the objective of collecting all the published and unpublished cases of CE the COST action MPN&MPNr-Euronet developed a comprehensive internet-based database focusing on the registration of clinical history, hematological, biochemical and molecular data (http://www.erythrocytosis.org/). In addition, unreported mutations are also curated in the corresponding Leiden Open Variation Database (LOVD). This article is protected by copyright. All rights reserved.

Computing lower and upper expectations under epistemic independence

This paper investigates the computation of lower/upper expectations that must cohere with a collection of probabilistic assessments and a collection of judgements of epistemic independence. New algorithms, based on multilinear programming, are presented, both for independence among events and among random variables. Separation properties of graphical models are also investigated.