Bird evolution: testing the Metaves clade with six new mitochondrial genomes

Background Evolutionary biologists are often misled by convergence of morphology and this has been common in the study of bird evolution. However, the use of molecular data sets have their own problems and phylogenies based on short DNA sequences have the potential to mislead us too. The relationships among clades and timing of the evolution of modern birds (Neoaves) has not yet been well resolved. Evidence of convergence of morphology remain controversial. With six new bird mitochondrial genomes (hummingbird, swift, kagu, rail, flamingo and grebe) we test the proposed Metaves/Coronaves division within Neoaves and the parallel radiations in this primary avian clade. Results Our mitochondrial trees did not return the Metaves clade that had been proposed based on one nuclear intron sequence. We suggest that the high number of indels within the seventh intron of the β-fibrinogen gene at this phylogenetic level, which left a dataset with not a single site across the alignment shared by all taxa, resulted in artifacts during analysis. With respect to the overall avian tree, we find the flamingo and grebe are sister taxa and basal to the shorebirds (Charadriiformes). Using a novel site-stripping technique for noise-reduction we found this relationship to be stable. The hummingbird/swift clade is outside the large and very diverse group of raptors, shore and sea birds. Unexpectedly the kagu is not closely related to the rail in our analysis, but because neither the kagu nor the rail have close affinity to any taxa within this dataset of 41 birds, their placement is not yet resolved. Conclusion Our phylogenetic hypothesis based on 41 avian mitochondrial genomes (13,229 bp) rejects monophyly of seven Metaves species and we therefore conclude that the members of Metaves do not share a common evolutionary history within the Neoaves.

Meeting under the “Omei” Tree in the Torres Strait Islands : networks and funds of knowledge of mathematical ideas

This paper focuses on the turning point experiences that worked to transform the researcher during a preliminary consultation process to seek permission to conduct of a small pilot project on one Torres Strait Island. The project aimed to learn from parents how they support their children in their mathematics learning. Drawing on a community research design, a consultative meeting was held with one Torres Strait Islander community to discuss the possibility of piloting a small project that focused on working with parents and children to learn about early mathematics processes. Preliminary data indicated that parents use networks in their community. It highlighted the funds of knowledge of mathematics that exist in the community and which are used to teach their children. Such knowledges are situated within a community’s unique histories, culture and the voices of the people. “Omei” tree means the Tree of Wisdom in the Island community.

Composite SaaS placement and resource optimization in Cloud computing using evolutionary algorithms

Software as a Service (SaaS) is gaining more and more attention from software users and providers recently. This has raised many new challenges to SaaS providers in providing better SaaSes that suit everyone needs at minimum costs. One of the emerging approaches in tackling this challenge is by delivering the SaaS as a composite SaaS. Delivering it in such an approach has a number of benefits, including flexible offering of the SaaS functions and decreased cost of subscription for users. However, this approach also introduces new problems for SaaS resource management in a Cloud data centre. We present the problem of composite SaaS resource management in Cloud data centre, specifically on its initial placement and resource optimization problems aiming at improving the SaaS performance based on its execution time as well as minimizing the resource usage. Our approach differs from existing literature because it addresses the problems resulting from composite SaaS characteristics, where we focus on the SaaS requirements, constraints and interdependencies. The problems are tackled using evolutionary algorithms. Experimental results demonstrate the efficiency and the scalability of the proposed algorithms.

Evolutionary placement of continuously operating reference stations of network Real-Time Kinematic

Network RTK (Real-Time Kinematic) is a technology that is based on GPS (Global Positioning System) or more generally on GNSS (Global Navigation Satellite System) observations to achieve centimeter-level accuracy positioning in real time. It is enabled by a network of Continuously Operating Reference Stations (CORS). CORS placement is an important problem in the design of network RTK as it directly affects not only the installation and running costs of the network RTK, but also the Quality of Service (QoS) provided by the network RTK. In our preliminary research on the CORS placement, we proposed a polynomial heuristic algorithm for a so-called location-based CORS placement problem. From a computational point of view, the location-based CORS placement is a largescale combinatorial optimization problem. Thus, although the heuristic algorithm is efficient in computation time it may not be able to find an optimal or near optimal solution. Aiming at improving the quality of solutions, this paper proposes a repairing genetic algorithm (RGA) for the location-based CORS placement problem. The RGA has been implemented and compared to the heuristic algorithm by experiments. Experimental results have shown that the RGA produces better quality of solutions than the heuristic algorithm.

A parallel cooperative co-evolutionary genetic algorithm for the composite SaaS placement problem in Cloud computing

A composite SaaS (Software as a Service) is a software that is comprised of several software components and data components. The composite SaaS placement problem is to determine where each of the components should be deployed in a cloud computing environment such that the performance of the composite SaaS is optimal. From the computational point of view, the composite SaaS placement problem is a large-scale combinatorial optimization problem. Thus, an Iterative Cooperative Co-evolutionary Genetic Algorithm (ICCGA) was proposed. The ICCGA can find reasonable quality of solutions. However, its computation time is noticeably slow. Aiming at improving the computation time, we propose an unsynchronized Parallel Cooperative Co-evolutionary Genetic Algorithm (PCCGA) in this paper. Experimental results have shown that the PCCGA not only has quicker computation time, but also generates better quality of solutions than the ICCGA.

A simulated annealing algorithm for energy efficient virtual machine placement

Improving energy efficiency has become increasingly important in data centers in recent years to reduce the rapidly growing tremendous amounts of electricity consumption. The power dissipation of the physical servers is the root cause of power usage of other systems, such as cooling systems. Many efforts have been made to make data centers more energy efficient. One of them is to minimize the total power consumption of these servers in a data center through virtual machine consolidation, which is implemented by virtual machine placement. The placement problem is often modeled as a bin packing problem. Due to the NP-hard nature of the problem, heuristic solutions such as First Fit and Best Fit algorithms have been often used and have generally good results. However, their performance leaves room for further improvement. In this paper we propose a Simulated Annealing based algorithm, which aims at further improvement from any feasible placement. This is the first published attempt of using SA to solve the VM placement problem to optimize the power consumption. Experimental results show that this SA algorithm can generate better results, saving up to 25 percentage more energy than First Fit Decreasing in an acceptable time frame.

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.

The benefits of tree-based models for stock selection

The identification of the primary drivers of stock returns has been of great interest to both financial practitioners and academics alike for many decades. Influenced by classical financial theories such as the CAPM (Sharp, 1964; Lintner, 1965) and APT (Ross, 1976), a linear relationship is conventionally assumed between company characteristics as derived from their financial accounts and forward returns. Whilst this assumption may be a fair approximation to the underlying structural relationship, it is often adopted for the purpose of convenience. It is actually quite rare that the assumptions of distributional normality and a linear relationship are explicitly assessed in advance even though this information would help to inform the appropriate choice of modelling technique. Non-linear models have nevertheless been applied successfully to the task of stock selection in the past (Sorensen et al, 2000). However, their take-up by the investment community has been limited despite the fact that researchers in other fields have found them to be a useful way to express knowledge and aid decision-making...

Abundance of Natural Riparian Forests and Tree Plantations in the Amudarya Delta of Uzbekistan and their impact on emissions of soil-borne greenhouse gases

Through a forest inventory in parts of the Amudarya river delta, Central Asia, we assessed the impact of ongoing forest degradation on the emissions of greenhouse gases (GHG) from soils. Interpretation of aerial photographs from 2001, combined with data on forest inventory in 1990 and field survey in 2003 provided comprehensive information about the extent and changes of the natural tugai riparian forests and tree plantations in the delta. The findings show an average annual deforestation rate of almost 1.3% and an even higher rate of land use change from tugai forests to land with only sparse tree cover. These annual rates of deforestation and forest degradation are higher than the global annual forest loss. By 2003, the tugai forest area had drastically decreased to about 60% compared to an inventory in 1990. Significant differences in soil GHG emissions between forest and agricultural land use underscore the impact of the ongoing land use change on the emission of soil-borne GHGs. The conversion of tugai forests into irrigated croplands will release 2.5 t CO2 equivalents per hectare per year due to elevated emissions of N2O and CH4. This demonstrates that the ongoing transformation of tugai forests into agricultural land-use systems did not only lead to a loss of biodiversity and of a unique ecosystem, but substantially impacts the biosphere-atmosphere exchange of GHG and soil C and N turnover processes.

Licensed to sell : product placement in the James Bond film series

As one of the longest running franchises in cinema history, and with its well-established use of product placements, the James Bond film series provides an ideal framework within which to measure and catalogue the number and types of products used within a particular timeframe. This case study will draw upon extensive content analysis of the James Bond film series in order to chart the evolution of product placement across the franchise's 50 year history.

Systematics and biology of the iconic Australian scribbly gum moths Ogmograptis Meyrick (Lepidoptera: Bucculatricidae) and their unique insect-plant interaction

The larvae of particular Ogmograptis spp. produce distinctive scribbles on some smooth-barked Eucalyptus spp. which are a common feature on many ornamental and forest trees in Australia. However, although they are conspicuous in the environment the systematics and biology of the genus has been poorly studied. This has been addressed through detailed field and laboratory studies of their biology of three species (O. racemosa Horak sp. nov., O. fraxinoides Horak sp. nov., O. scribula Meyrick), in conjunction with a comprehensive taxonomic revision support by a molecular phylogeny utilising the mitochondrial Cox1 and nuclear 18S genes. In brief, eggs are laid in bark depressions and the first instar larvae bore into the bark to the level where the future cork cambium forms (the phellegen). Early instar larvae bore wide, arcing tracks in this layer before forming a tighter zig-zag shaped pattern. The second last instar turns and bores either closely parallel to the initial mine or doubles its width, along the zig-zag shaped mine. The final instar possesses legs and a spinneret (unlike the earlier instars) and feeds exclusively on callus tissue which forms within the zig-zag shaped mine formed by the previous instar, before emerging from the bark to pupate at the base of the tree. The scars of mines them become visible scribble following the shedding of bark. Sequence data confirm the placement of Ogmograptis within the Bucculatricidae, suggest that the larvae responsible for the ‘ghost scribbles’ (unpigmented, raised scars found on smooth-barked eucalypts) are members of the genus Tritymba, and support the morphology-based species groups proposed for Ogmograptis. The formerly monotypic genus Ogmograptis Meyrick is revised and divided into three species groups. Eleven new species are described: Ogmograptis fraxinoides Horak sp. nov., Ogmograptis racemosa Horak sp. nov. and Ogmograptis pilularis Horak sp. nov. forming the scribula group with Ogmograptis scribula Meyrick; Ogmograptis maxdayi Horak sp. nov., Ogmograptis barloworum Horak sp. nov., Ogmograptis paucidentatus Horak sp. nov., Ogmograptis rodens Horak sp. nov., Ogmograptis bignathifer Horak sp. nov. and Ogmograptis inornatus Horak sp. nov. as the maxdayi group; Ogmograptis bipunctatus Horak sp. nov., Ogmograptis pulcher Horak sp. nov., Ogmograptis triradiata (Turner) comb. nov. and Ogmograptis centrospila (Turner) comb. nov. as the triradiata group. Ogmograptis notosema (Meyrick) cannot be assigned to a species group as the holotype has not been located. Three unique synapomorphies, all derived from immatures, redefine the family Bucculatricidae, uniting Ogmograptis, Tritymba Meyrick (both Australian) and Leucoedemia Scoble & Scholtz (African) with Bucculatrix Zeller, which is the sister group of the southern hemisphere genera. The systematic history of Ogmograptis and the Bucculatricidae is discussed.

Inferring kangaroo phylogeny from incongruent nuclear and mitochondrial genes

The marsupial genus Macropus includes three subgenera, the familiar large grazing kangaroos and wallaroos of M. (Macropus) and M. (Osphranter), as well as the smaller mixed grazing/browsing wallabies of M. (Notamacropus). A recent study of five concatenated nuclear genes recommended subsuming the predominantly browsing Wallabia bicolor (swamp wallaby) into Macropus. To further examine this proposal we sequenced partial mitochondrial genomes for kangaroos and wallabies. These sequences strongly favour the morphological placement of W. bicolor as sister to Macropus, although place M. irma (black-gloved wallaby) within M. (Osphranter) rather than as expected, with M. (Notamacropus). Species tree estimation from separately analysed mitochondrial and nuclear genes favours retaining Macropus and Wallabia as separate genera. A simulation study finds that incomplete lineage sorting among nuclear genes is a plausible explanation for incongruence with the mitochondrial placement of W. bicolor, while mitochondrial introgression from a wallaroo into M. irma is the deepest such event identified in marsupials. Similar such coalescent simulations for interpreting gene tree conflicts will increase in both relevance and statistical power as species-level phylogenetics enters the genomic age. Ecological considerations in turn, hint at a role for selection in accelerating the fixation of introgressed or incompletely sorted loci. More generally the inclusion of the mitochondrial sequences substantially enhanced phylogenetic resolution. However, we caution that the evolutionary dynamics that enhance mitochondria as speciation indicators in the presence of incomplete lineage sorting may also render them especially susceptible to introgression.

Energy efficient virtual machine placement in data centers

Electricity cost has become a major expense for running data centers and server consolidation using virtualization technology has been used as an important technology to improve the energy efficiency of data centers. In this research, a genetic algorithm and a simulation-annealing algorithm are proposed for the static virtual machine placement problem that considers the energy consumption in both the servers and the communication network, and a trading algorithm is proposed for dynamic virtual machine placement. Experimental results have shown that the proposed methods are more energy efficient than existing solutions.