Persistence of multiple genetic lineages within intra-host populations of Ross River virus

We examined the structure and extent of genetic diversity in intrahost populations of Ross River virus (RRV) in samples from six human patients, focusing on the nonstructural (nsP3) and structural (E2) protein genes. Strikingly, although the samples were collected from contrasting ecological settings 3,000 kilometers apart in Australia, we observed multiple viral lineages in four of the six individuals, which is indicative of widespread mixed infections. In addition, a comparison with previously published RRV sequences revealed that these distinct lineages have been in circulation for at least 5 years, and we were able to document their long-term persistence over extensive geographical distances

Mitochondrial genome deletions and minicircles are common in lice (Insecta: Phthiraptera)

Background The gene composition, gene order and structure of the mitochondrial genome are remarkably stable across bilaterian animals. Lice (Insecta: Phthiraptera) are a major exception to this genomic stability in that the canonical single chromosome with 37 genes found in almost all other bilaterians has been lost in multiple lineages in favour of multiple, minicircular chromosomes with less than 37 genes on each chromosome. Results Minicircular mt genomes are found in six of the ten louse species examined to date and three types of minicircles were identified: heteroplasmic minicircles which coexist with full sized mt genomes (type 1); multigene chromosomes with short, simple control regions, we infer that the genome consists of several such chromosomes (type 2); and multiple, single to three gene chromosomes with large, complex control regions (type 3). Mapping minicircle types onto a phylogenetic tree of lice fails to show a pattern of their occurrence consistent with an evolutionary series of minicircle types. Analysis of the nuclear-encoded, mitochondrially-targetted genes inferred from the body louse, Pediculus, suggests that the loss of mitochondrial single-stranded binding protein (mtSSB) may be responsible for the presence of minicircles in at least species with the most derived type 3 minicircles (Pediculus, Damalinia). Conclusions Minicircular mt genomes are common in lice and appear to have arisen multiple times within the group. Life history adaptive explanations which attribute minicircular mt genomes in lice to the adoption of blood-feeding in the Anoplura are not supported by this expanded data set as minicircles are found in multiple non-blood feeding louse groups but are not found in the blood-feeding genus Heterodoxus. In contrast, a mechanist explanation based on the loss of mtSSB suggests that minicircles may be selectively favoured due to the incapacity of the mt replisome to synthesize long replicative products without mtSSB and thus the loss of this gene lead to the formation of minicircles in lice.

Operational semantics of aspects in business process management

Aspect orientation is an important approach to address complexity of cross-cutting concerns in Information Systems. This approach encapsulates these concerns separately and compose them to the main module when needed. Although there a different works which shows how this separation should be performed in process models, the composition of them is an open area. In this paper, we demonstrate the semantics of a service which enables this composition. The result can also be used as a blueprint to implement the service to support aspect orientation in Business Process Management area.

Dynamic weaving of aspects for business process management systems

Reducing complexity in Information Systems is a main concern in both research and industry. One strategy for reducing complexity is separation of concerns. This strategy advocates separating various concerns, like security and privacy, from the main concern. It results in less complex, easily maintainable, and more reusable Information Systems. Separation of concerns is addressed through the Aspect Oriented paradigm. This paradigm has been well researched and implemented in programming, where languages such as AspectJ have been developed. However, the rsearch on aspect orientation for Business Process Management is still at its beginning. While some efforts have been made proposing Aspect Oriented Business Process Modelling, it has not yet been investigated how to enact such process models in a Workflow Management System. In this paper, we define a set of requirements that specifies the execution of aspect oriented business process models. We create a Coloured Petri Net specification for the semantics of so-called Aspect Service that fulfils these requirements. Such a service extends the capability of a Workflow Management System with support for execution of aspect oriented business process models. The design specification of the Aspect Service is also inspected through state space analysis.

Correlation-based damage detection for complicated truss bridges using multi-layer genetic algorithms

The study presents a multi-layer genetic algorithm (GA) approach using correlation-based methods to facilitate damage determination for through-truss bridge structures. To begin, the structure’s damage-suspicious elements are divided into several groups. In the first GA layer, the damage is initially optimised for all groups using correlation objective function. In the second layer, the groups are combined to larger groups and the optimisation starts over at the normalised point of the first layer result. Then the identification process repeats until reaching the final layer where one group includes all structural elements and only minor optimisations are required to fine tune the final result. Several damage scenarios on a complicated through-truss bridge example are nominated to address the proposed approach’s effectiveness. Structural modal strain energy has been employed as the variable vector in the correlation function for damage determination. Simulations and comparison with the traditional single-layer optimisation shows that the proposed approach is efficient and feasible for complicated truss bridge structures when the measurement noise is taken into account.

Genetic algorithms to schedule container transfers at multimodal terminals

Optimising the container transfer schedule at the multimodal terminals is known to be NP-hard, which implies that the best solution becomes computationally infeasible as problem sizes increase. Genetic Algorithm (GA) techniques are used to reduce container handling/transfer times and ships' time at the port by speeding up handling operations. The GA is chosen due to the relatively good results that have been reported even with the simplest GA implementations to obtain near-optimal solutions in reasonable time. Also discussed, is the application of the model to assess the consequences of increased scheduled throughput time as well as different strategies such as the alternative plant layouts, storage policies and number of yard machines. A real data set used for the solution and subsequent sensitivity analysis is applied to the alternative plant layouts, storage policies and number of yard machines.

A hybrid model for studying spatial aspects of infectious diseases

We consider a hybrid model, created by coupling a continuum and an agent-based model of infectious disease. The framework of the hybrid model provides a mechanism to study the spread of infection at both the individual and population levels. This approach captures the stochastic spatial heterogeneity at the individual level, which is directly related to deterministic population level properties. This facilitates the study of spatial aspects of the epidemic process. A spatial analysis, involving counting the number of infectious agents in equally sized bins, reveals when the spatial domain is nonhomogeneous.

A penalty-based grouping genetic algorithm for multiple composite SaaS components clustering in Cloud

Software as a Service (SaaS) in Cloud is getting more and more significant among software users and providers recently. A SaaS that is delivered as composite application has many benefits including reduced delivery costs, flexible offers of the SaaS functions and decreased subscription cost for users. However, this approach has introduced a new problem in managing the resources allocated to the composite SaaS. The resource allocation that has been done at the initial stage may be overloaded or wasted due to the dynamic environment of a Cloud. A typical data center resource management usually triggers a placement reconfiguration for the SaaS in order to maintain its performance as well as to minimize the resource used. Existing approaches for this problem often ignore the underlying dependencies between SaaS components. In addition, the reconfiguration also has to comply with SaaS constraints in terms of its resource requirements, placement requirement as well as its SLA. To tackle the problem, this paper proposes a penalty-based Grouping Genetic Algorithm for multiple composite SaaS components clustering in Cloud. The main objective is to minimize the resource used by the SaaS by clustering its component without violating any constraint. Experimental results demonstrate the feasibility and the scalability of the proposed algorithm.

Energy-efficient virtual machine placement in data centers by genetic algorithm

Server consolidation using virtualization technology has become an important technology to improve the energy efficiency of data centers. Virtual machine placement is the key in the server consolidation. In the past few years, many approaches to the virtual machine placement have been proposed. However, existing virtual machine placement approaches to the virtual machine placement problem consider the energy consumption by physical machines in a data center only, but do not consider the energy consumption in communication network in the data center. However, the energy consumption in the communication network in a data center is not trivial, and therefore should be considered in the virtual machine placement in order to make the data center more energy-efficient. In this paper, we propose a genetic algorithm for a new virtual machine placement problem that considers the energy consumption in both the servers and the communication network in the data center. Experimental results show that the genetic algorithm performs well when tackling test problems of different kinds, and scales up well when the problem size increases.

Engagement, persistence, progress and success as theoretically distinct aspects of business creation processes

Starting from the vantage point that explaining success at creating a venture should be the unique contribution—or at least one unique contribution—of entrepreneurship research, we argue that this success construct has not yet been adequately defined an operationalized. We thus offer suggestions for more precise conceptualization and measurement of this central construct. Rather than regarding various success proxies used in prior research as poor operationalizations of success we argue that they represent other important aspects of the venture creation process: engagement, persistence and progress. We hold that in order to attain a better understanding of venture creation these constructs also need to be theoretically defined. Further, their respective drivers need to be theorized and tested separately. We suggest theoretical definitions of each. We then develop and test hypotheses concerning how human capital, venture idea novelty and business planning has different impact on the different assessments of the process represented by engagement, persistence, progress and success. The results largely confirm the stated hypotheses, suggesting that the conceptual and empirical approach we are suggesting is a path towards improved understanding of the central entrepreneurship phenomenon of new venture creation.

Australian lungfish (Neoceratodus forsteri: Dipnoi) have low genetic variation at allozyme and mitochondrial DNA loci : a conservation alert?

Genetic variation at allozyme and mitochondrial DNA loci was investigated in the Australian lungfish, Neoceratodus forsteri Krefft 1870. Tissue samples for genetic analysis were taken non-lethally from 278 individuals representing two spatially distinct endemic populations (Mary and Burnett rivers), as well as one population thought to be derived from an anthropogenic translocation in the 1890's (Brisbane river). Two of 24 allozyme loci resolved from muscle tissue were polymorphic. Mitochondrial DNA nucleotide sequence diversity estimated across 2,235 base pairs in each of 40 individuals ranged between 0.000423 and 0.001470 per river. Low genetic variation at allozyme and mitochondrial loci could be attributed to population bottlenecks, possibly induced by Pleistocene aridity. Limited genetic differentiation was detected among rivers using nuclear and mitochondrial markers suggesting that admixture may have occurred between the endemic Mary and Burnett populations during periods of low sea level when the drainages may have converged before reaching the ocean. Genetic data was consistent with the explanation that lungfish were introduced to the Brisbane river from the Mary river. Further research using more variable genetic loci is needed before the conservation status of populations can be determined, particularly as anthropogenic demands on lungfish habitat are increasing. In the interim we recommend a management strategy aimed at conserving existing genetic variation within and between rivers.

Kallikrein 14 is down-regulated by androgen receptor signalling and harbours genetic variation that is associated with prostate tumour aggressiveness

Kallikrein 14 (KLK14) has been proposed as a useful prognostic marker in prostate cancer, with expression reported to be associated with tumour characteristics such as higher stage and Gleason score. KLK14 tumour expression has also shown the potential to predict prostate cancer patients at risk of disease recurrence after radical prostatectomy. The KLKs are a remarkably hormone-responsive family of genes, although detailed studies of androgen regulation of KLK14 in prostate cancer have not been undertaken to date. Using in vitro studies, we have demonstrated that unlike many other prostatic KLK genes that are strictly androgen responsive, KLK14 is more broadly expressed and inversely androgen regulated in prostate cancer cells. Given these results and evidence that KLK14 may play a role in prostate cancer prognosis, we also investigated whether common genetic variants in the KLK14 locus are associated with risk and/or aggressiveness of prostate cancer in approximately 1200 prostate cancer cases and 1300 male controls. Of 41 single nucleotide polymorphisms assessed, three were associated with higher Gleason score (≥7): rs17728459 and rs4802765, both located upstream of KLK14, and rs35287116, which encodes a p.Gln33Arg substitution in the KLK14 signal peptide region. Our findings provide further support for KLK14 as a marker of prognosis in prostate cancer.

Genetic analysis of maize streak virus isolates from Uganda reveals widespread distribution of a recombinant variant

Maize streak virus (MSV) contributes significantly to the problem of extremely low African maize yields. Whilst a diverse range of MSV and MSV-like viruses are endemic in sub-Saharan Africa and neighbouring islands, only a single group of maize-adapted variants - MSV subtypes A1 -A6 - causes severe enough disease in maize to influence yields substantially. In order to assist in designing effective strategies to control MSV in maize, a large survey covering 155 locations was conducted to assess the diversity, distribution and genetic characteristics of the Ugandan MSV-A population. PCR-restriction fragment-length polymorphism analyses of 391 virus isolates identified 49 genetic variants. Sixty-two full-genome sequences were determined, 52 of which were detectably recombinant. All but two recombinants contained predominantly MSV-A1-like sequences. Of the ten distinct recombination events observed, seven involved inter-MSV-A subtype recombination and three involved intra-MSV-A1 recombination. One of the intra-MSV-A1 recombinants, designated MSV-A1 UgIII, accounted for >60% of all MSV infections sampled throughout Uganda. Although recombination may be an important factor in the emergence of novel geminivirus variants, it is demonstrated that its characteristics in MSV are quite different from those observed in related African cassava-infecting geminivirus species. © 2007 SGM.

Global genetic diversity and geographical and host-species distribution of beak and feather disease virus isolates

Psittacine beak and feather disease (PBFD) has a broad host range and is widespread in wild and captive psittacine populations in Asia, Africa, the Americas, Europe and Australasia. Beak and feather disease circovirus (BFDV) is the causative agent. BFDV has an ~2 kb single stranded circular DNA genome encoding just two proteins (Rep and CP). In this study we provide support for demarcation of BFDV strains by phylogenetic analysis of 65 complete genomes from databases and 22 new BFDV sequences isolated from infected psittacines in South Africa. We propose 94% genome-wide sequence identity as a strain demarcation threshold, with isolates sharing > 94% identity belonging to the same strain, and strain subtypes sharing> 98% identity. Currently, BFDV diversity falls within 14 strains, with five highly divergent isolates from budgerigars probably representing a new species of circovirus with three strains (budgerigar circovirus; BCV-A, -B and -C). The geographical distribution of BFDV and BCV strains is strongly linked to the international trade in exotic birds; strains with more than one host are generally located in the same geographical area. Lastly, we examined BFDV and BCV sequences for evidence of recombination, and determined that recombination had occurred in most BFDV and BCV strains. We established that there were two globally significant recombination hotspots in the viral genome: the first is along the entire intergenic region and the second is in the C-terminal portion of the CP ORF. The implications of our results for the taxonomy and classification of circoviruses are discussed. © 2011 SGM.

Adaptive sizing of populations and number of islands in distributed genetic algorithms

Deciding the appropriate population size and number of is- lands for distributed island-model genetic algorithms is often critical to the algorithm’s success. This paper outlines a method that automatically searches for good combinations of island population sizes and the number of islands. The method is based on a race between competing parameter sets, and collaborative seeding of new parameter sets. This method is applicable to any problem, and makes distributed genetic algorithms easier to use by reducing the number of user-set parameters. The experimental results show that the proposed method robustly and reliably finds population and islands settings that are comparable to those found with traditional trial-and-error approaches.