The automation and evaluation of nested clade phylogeographic analysis

Nested clade phylogeographic analysis (NCPA) is a popular method for reconstructing the demographic history of spatially distributed populations from genetic data. Although some parts of the analysis are automated, there is no unique and widely followed algorithm for doing this in its entirety, beginning with the data, and ending with the inferences drawn from the data. This article describes a method that automates NCPA, thereby providing a framework for replicating analyses in an objective way. To do so, a number of decisions need to be made so that the automated implementation is representative of previous analyses. We review how the NCPA procedure has evolved since its inception and conclude that there is scope for some variability in the manual application of NCPA. We apply the automated software to three published datasets previously analyzed manually and replicate many details of the manual analyses, suggesting that the current algorithm is representative of how a typical user will perform NCPA. We simulate a large number of replicate datasets for geographically distributed, but entirely random-mating, populations. These are then analyzed using the automated NCPA algorithm. Results indicate that NCPA tends to give a high frequency of false positives. In our simulations we observe that 14% of the clades give a conclusive inference that a demographic event has occurred, and that 75% of the datasets have at least one clade that gives such an inference. This is mainly due to the generation of multiple statistics per clade, of which only one is required to be significant to apply the inference key. We survey the inferences that have been made in recent publications and show that the most commonly inferred processes (restricted gene flow with isolation by distance and contiguous range expansion) are those that are commonly inferred in our simulations. However, published datasets typically yield a richer set of inferences with NCPA than obtained in our random-mating simulations, and further testing of NCPA with models of structured populations is necessary to examine its accuracy.

The automation of nested clade phylogeographic analysis

ANeCA is a fully automated implementation of Nested Clade Phylogeographic Analysis. This was originally developed by Templeton and colleagues, and has been used to infer, from the pattern of gene sequence polymorphisms in a geographically structured population, the historical demographic processes that have shaped its evolution. Until now it has been necessary to perform large parts of the procedure manually. We provide a program that will take data in Nexus sequential format, and directly output a set of inferences. The software also includes TCS v1.18 and GeoDis v2.2 as part of automation.

Integrative workflow-embedded support for process automation and management

This paper presents the on-going research performed in order to integrate process automation and process management support in the context of media production. This has been addressed on the basis of a holistic approach to software engineering applied to media production modelling to ensure design correctness, completeness and effectiveness. The focus of the research and development has been to enhance the metadata management throughout the process in a similar fashion to that achieved in Decision Support Systems (DSS) to facilitate well-grounded business decisions. The paper sets out the aims and objectives and the methodology deployed. The paper describes the solution in some detail and sets out some preliminary conclusions and the planned future work.

Creating a world class business through a merger of two equals: an interview with Paul Walsh, Chief Executive Officer of Diageo Plc

Purpose – The purpose of this paper is to explore, from a practical point-of-view, a number of key strategic issues that critically influence organisations' competitiveness. Design/methodology/approach – The paper is based on a semi-structured interview with Mr Paul Walsh, CEO of Diageo. Diageo is a highly successful company and Mr Walsh has played a central role in making Diageo the number one branded drink company in the world. Findings – The paper discusses the key attributes of successful merger, lessons from a complex cross boarder acquisition, rationale for strategic alliance with competitors, distinctive resources, and the role of corporate social responsibility. Research limitations/implications – It is not too often that management scholars have the opportunity to discuss with the CEOs of large multinationals the rational of key strategic decisions. In this paper these issues are explored from the perspective of a CEO of a large and successful company. The lessons, while not generalisable, offer unique insights to students of management and management researchers. Originality/value – The paper offers a bridge between theory and practice. It demonstrates that from Diageo's perspective the distinctive capabilities are intangible. It also offers insight into how to successfully execute strategic decision. In terms of originality it offers a view from the top, which is often missing from strategy research.

Risking the ire of investors in pursuit of long-term value: an interview with Cynthia Carroll, the CEO of Anglo American plc

Purpose – The purpose of this paper is to demonstrate how key strategic decisions are made in practice at successful FTSE 100 companies. Design/methodology/approach – The paper is based on a semi-structured interview with Ms Cynthia Carroll, Chief Executive of Anglo American plc. Findings – The interview outlines a number of important factors on: the evolution of strategy within Anglo American, strategy execution, leadership at board and executive levels, and capturing synergies within the company. Originality/value – The paper bridges the gap between theory and practice. It provides a practical view and demonstrates how corporate leaders think about key strategic issues

BSkyB transformation from a new loss-making venture to a successful organisation: case study and interview with Jeremy Darroch, Chief Executive of British Sky Broadcasting Group Plc

Purpose – This paper aims to articulate strategic dilemmas faced by a Chief Executive of a highly successful company and how such dilemmas were resolved. Design/methodology/approach – The case is based on a semi-structured interview with Mr Jeremy Darroch – Chief Executive of BSkyB – and analysis of documentary evidence. Findings – It is often difficult to implement strategies that simultaneously yield high organic growth rate, innovation, and a healthy balance-sheet. The paper sheds light on how Sky has met this challenge. Research limitations/implications – The research offers a unique insight into the views of a principal strategist and articulates the background to offer context, however, because of its design the findings are not generalisable. Originality/value – Very few articles offer insight into the thinking of those with principal responsibility for design and delivery of strategy. This paper offers such an insight based on a detailed interview with a highly successful Chief Executive.

Bio-inspired ant colony optimization based clustering algorithm with mobile sinks for applications in consumer home automation networks

With the fast development of wireless communications, ZigBee and semiconductor devices, home automation networks have recently become very popular. Since typical consumer products deployed in home automation networks are often powered by tiny and limited batteries, one of the most challenging research issues is concerning energy reduction and the balancing of energy consumption across the network in order to prolong the home network lifetime for consumer devices. The introduction of clustering and sink mobility techniques into home automation networks have been shown to be an efficient way to improve the network performance and have received significant research attention. Taking inspiration from nature, this paper proposes an Ant Colony Optimization (ACO) based clustering algorithm specifically with mobile sink support for home automation networks. In this work, the network is divided into several clusters and cluster heads are selected within each cluster. Then, a mobile sink communicates with each cluster head to collect data directly through short range communications. The ACO algorithm has been utilized in this work in order to find the optimal mobility trajectory for the mobile sink. Extensive simulation results from this research show that the proposed algorithm significantly improves home network performance when using mobile sinks in terms of energy consumption and network lifetime as compared to other routing algorithms currently deployed for home automation networks.