Statistical inferences in phylogeography

In conventional phylogeographic studies, historical demographic processes are elucidated from the geographical distribution of individuals represented on an inferred gene tree. However, the interpretation of gene trees in this context can be difficult as the same demographic/geographical process can randomly lead to multiple different genealogies. Likewise, the same gene trees can arise under different demographic models. This problem has led to the emergence of many statistical methods for making phylogeographic inferences. A popular phylogeographic approach based on nested clade analysis is challenged by the fact that a certain amount of the interpretation of the data is left to the subjective choices of the user, and it has been argued that the method performs poorly in simulation studies. More rigorous statistical methods based on coalescence theory have been developed. However, these methods may also be challenged by computational problems or poor model choice. In this review, we will describe the development of statistical methods in phylogeographic analysis, and discuss some of the challenges facing these methods.

Inferring population history with DIY ABC: a user-friendly approach to approximate Bayesian computation

Genetic data obtained on population samples convey information about their evolutionary history. Inference methods can extract part of this information but they require sophisticated statistical techniques that have been made available to the biologist community (through computer programs) only for simple and standard situations typically involving a small number of samples. We propose here a computer program (DIY ABC) for inference based on approximate Bayesian computation (ABC), in which scenarios can be customized by the user to fit many complex situations involving any number of populations and samples. Such scenarios involve any combination of population divergences, admixtures and population size changes. DIY ABC can be used to compare competing scenarios, estimate parameters for one or more scenarios and compute bias and precision measures for a given scenario and known values of parameters (the current version applies to unlinked microsatellite data). This article describes key methods used in the program and provides its main features. The analysis of one simulated and one real dataset, both with complex evolutionary scenarios, illustrates the main possibilities of DIY ABC.

PGR forum: serving the crop wild relative user community

The Euro-Mediterranean region is an important centre for the diversity of crop wild relatives. Crops, such as oats (Avena sativa), sugar beet (Beta vulgaris), apple (Malus domestica), annual meadow grass (Festuca pratensis), white clover (Trifolium repens), arnica (Arnica montana), asparagus (Asparagus officinalis), lettuce (Lactuca sativa), and sage (Salvia officinalis) etc., all have wild relatives in the region. The European Community funded project, PGR Forum (www.pgrforum.org) is building an online information system to provide access to crop wild relative data to a broad user community; including plant breeders, protected area managers, policy-makers, conservationists, taxonomists and the wider public. The system will include data on uses, geographical distribution, biology, population and habitat information, threats (including IUCN Red List assessments) and conservation actions. This information is vital for the continued sustainable utilisation and conservation of crop wild relatives. Two major databases have been utilised as the backbone to a Euro-Mediterranean crop wild relative catalogue, which forms the core of the information system: Euro+Med PlantBase (www.euromed.org.uk) and Mansfeld’s World Database of Agricultural and Horticultural Crops (http://mansfeld.ipk-gatersleben.de). By matching the genera found within the two databases, a preliminary list of crop wild relatives has been produced. Around 20,000 of the 30,000+ species listed in Euro+Med PlantBase can be considered crop wild relatives, i.e. those species found within the same genus as a crop. The list is currently being refined by implementing a priority ranking system based on the degree of relatedness of taxa to the associated crop.

Constrained models of evolution lead to improved prediction of functional linkage from correlated gain and loss of genes

Motivation: We compare phylogenetic approaches for inferring functional gene links. The approaches detect independent instances of the correlated gain and loss of pairs of genes from species' genomes. We investigate the effect on results of basing evidence of correlations on two phylogenetic approaches, Dollo parsminony and maximum likelihood (ML). We further examine the effect of constraining the ML model by fixing the rate of gene gain at a low value, rather than estimating it from the data. Results: We detect correlated evolution among a test set of pairs of yeast (Saccharomyces cerevisiae) genes, with a case study of 21 eukaryotic genomes and test data derived from known yeast protein complexes. If the rate at which genes are gained is constrained to be low, ML achieves by far the best results at detecting known functional links. The model then has fewer parameters but it is more realistic by preventing genes from being gained more than once. Availability: BayesTraits by M. Pagel and A. Meade, and a script to configure and repeatedly launch it by D. Barker and M. Pagel, are available at http://www.evolution.reading.ac.uk .

Environmental quality and the productive workplace

A good working environment will help to provide the user with a good sense of wellbeing, inspiration and comfort. The main advantages of good environments is in terms of reduced upgrading investment, reduced sickness absence, an optimum level of productivity and improved overall satisfaction. Individuals respond very differently to their environments and research suggests a correlation between worker productivity and well-being, environmental, social and organisational factors. Research shows the occupants who report a high level of dissatisfaction about their job are usually the people who suffer more work and office environment related illnesses which affect their wellbeing, but not always so. Well-being expresses overall satisfaction. There is a connection between dissatisfied staff and low productivity; and a good sense of well-being is very important as it can lead to substantial productivity gain. If the environment is particularly bad people will be dissatisfied irrespective of job satisfaction. This paper describes research showing how environment affects productivity.

Architect and user interaction: The spoken representation of form and functional meaning

The paper is an investigation of the exchange of ideas and information between an architect and building users in the early stages of the building design process before the design brief or any drawings have been produced. The purpose of the research is to gain insight into the type of information users exchange with architects in early design conversations and to better understand the influence the format of design interactions and interactional behaviours have on the exchange of information. We report an empirical study of pre-briefing conversations in which the overwhelming majority of the exchanges were about the functional or structural attributes of space, discussion that touched on the phenomenological, perceptual and the symbolic meanings of space were rare. We explore the contextual features of meetings and the conversational strategies taken by the architect to prompt the users for information and the influence these had on the information provided. Recommendations are made on the format and structure of pre-briefing conversations and on designers' strategies for raising the level of information provided by the user beyond the functional or structural attributes of space.

A comparison of the Oxford and Manus intelligent hand prostheses

Historically, commercial hand prosthesis have adopted a low level of innovation mainly due to the strict conditions such a system must undergo. The difficult feedback to the prosthesis user has limited the functional range of commercial systems. Nevertheless, the use of advanced sensors in combination with performing hand mechanisms and microcontrollers could lead to more natural and functional prototypes. The Oxford and Manus intelligent hand prostheses are examples of innovative approaches. This paper compares and contrasts the technological solutions implemented in both systems to address the design conditions.

User-intimate requirements hierarchy resolution framework (UI-REF)

Abstract. This paper presents the User-Intimate Requirements Hierarchy Resolution Framework (UI-REF) based on earlier work (Badii 1997-2008) to optimise the requirements engineering process particularly to support userintimate interactive systems co-design. The stages of the UI- EF framework for requirements resolution-and-prioritisation are described. UI-REF has been established to ensure that the most-deeply-valued needs of the majority of stakeholders are elicited and ranked, and the root rationale for requirements evolution is trace-able and contextualised so as to help resolve stakeholder conflicts. UI-REF supports the dynamically evolving requirements of the users in the context of digital economy as under-pinned by online service provisioning. Requirements prioritisation in UI-REF is fully resolved while a promotion path for lower priority requirements is delineated so as to ensure that as the requirements evolve so will their resolution and prioritisation.

Increasing detection rate of user-to-root attacks using genetic algorithms

An extensive set of machine learning and pattern classification techniques trained and tested on KDD dataset failed in detecting most of the user-to-root attacks. This paper aims to provide an approach for mitigating negative aspects of the mentioned dataset, which led to low detection rates. Genetic algorithm is employed to implement rules for detecting various types of attacks. Rules are formed of the features of the dataset identified as the most important ones for each attack type. In this way we introduce high level of generality and thus achieve high detection rates, but also gain high reduction of the system training time. Thenceforth we re-check the decision of the user-to- root rules with the rules that detect other types of attacks. In this way we decrease the false-positive rate. The model was verified on KDD 99, demonstrating higher detection rates than those reported by the state- of-the-art while maintaining low false-positive rate.

Towards natural human computer interaction in BCI

BCI systems require correct classification of signals interpreted from the brain for useful operation. To this end this paper investigates a method proposed in [1] to correctly classify a series of images presented to a group of subjects in [2]. We show that it is possible to use the proposed methods to correctly recognise the original stimuli presented to a subject from analysis of their EEG. Additionally we use a verification set to show that the trained classification method can be applied to a different set of data. We go on to investigate the issue of invariance in EEG signals. That is, the brain representation of similar stimuli is recognisable across different subjects. Finally we consider the usefulness of the methods investigated towards an improved BCI system and discuss how it could potentially lead to great improvements in the ease of use for the end user by offering an alternative, more intuitive control based mode of operation.