Taxonomy, systematics and ecology of the phylum Tardigrada

This thesis is based on published papers, however there have been issues encountered with copyright permissions, therefore a fuller version may be submitted in the future.I conducted a series of research programmes on various aspects of Tardigrada biology. The published results of which are hereby presented as part fulfilment of my submission for a PhD by publications at Plymouth University. In this thesis my research publications are grouped into four chapters: Ecology & Faunistics, Alpha Taxonomy, Freshwater Fauna – a taxonomic challenge, and Superfamilies. In the first, I highlight my early papers which dealt with the faunistic surveys as I trained in systematics and taxonomy of the phylum. Amongst the key findings reported were the protozoan symphoriant, Pyxidium tardigradum van der Land, 1966, Marley and Wright (1994); a new addition to the reported fauna of the United Kingdom, Greaves & Marley(1996); and my first work on international samples from Arctic Canada, Sutcliffe et al.(2000). In the second chapter, Alpha Taxonomy, I have included five papers. The first, Marley and Wright (1996), illustrates my work with one of the Royal Museums of Scotland’s collections, where I updated the diagnoses of their specimens and described a new addition to the Icelandic fauna. The second paper, Russell, Marley & Hockings (2001), demonstrates how I was searching for new research methods to apply to tardigrades. It was because of similar exploration, with methods of SEM preparation, that I was invited to join the Australian-Anglo team working on sediment core samples from Antarctic freshwater lakes, Gibson et al. 2009. The remaining two papers in the chapter describe species new to science, Echiniscus ollantaytamboensis Nickel, Miller and Marley, 2001, and my first sole authored paper describing a species new to science, Platicrista ramsayi Marley, 2006. The third chapter, Freshwater Fauna – a taxonomic challenge, deals with a programme of research based initially on my findings at the Royal Museums of Scotland, Edinburgh. This then required subsequent visits the USA and Italy to work on the taxonomic issues with original authors on their more recently described genera. I prepared the original Case for the ICZN, but this was then held by the commission for several years pending their amendments to the Code. I then rewrote the Case into the final paper, Marley, Bertolani & Nelson (2008). The final chapter consists of two papers in which I worked on combining my expertise on the morphological characters of the buccal apparatus and claws, and combining this with new molecular dataset derived from sequencing individual specimens. My colleagues on these papers were Dr S.J. McInnes and Mr C.J. Sands, both from the British Antarctic Survey. Overall I am including 14 published papers and 5 published conference abstracts and three online articles. The following taxa were erected during this work: Pseudobiotus kathmanae, Echiniscus ollantaytamboensis, Platicrista ramsayi, Ramazzottidae, Isohypsibiidae, Macrobiotoidea, Eohypsibioidea, Hypsibioidea, and Isohypsibioidea. Plus the following taxa were re-described, Pseudobiotus, Thulinius, Thulinius augusti, Thulinius ruffoi, and Thulinius stephanae

The National Transport Data Framework

Report by Professor Peter Landshoff (Cambridge University) and Professor John Polak (Imperial College London) on a project for the Department for Transport. emails: [email protected] [email protected] NTDF is designed to be a resource for data owners to deposit descriptions into a central catalogue, so that people can search for data and find data and understand their characteristics. The value of this is to individuals, to commercial organizations, and to public bodies. For example, services that provide better information to travellers will help to make their journey less stressful and persuade them to make more use of public transport. Transport operators need very diverse information to help them plan developments to their services: demographic, geographical, economic etc. And policy makers need a similar range of information to help them decide how to divide their budget and afterwards to evaluate how valuable it has been.This work was supported by the Department for Transport (DfT)

A Field Guide to Genetic Programming

xiv, 233 p. : il. ; 23 cm.Libro ElectrónicoA Field Guide to Genetic Programming (ISBN 978-1-4092-0073-4) is an introduction to genetic programming (GP). GP is a systematic, domain-independent method for getting computers to solve problems automatically starting from a high-level statement of what needs to be done. Using ideas from natural evolution, GP starts from an ooze of random computer programs, and progressively refines them through processes of mutation and sexual recombination, until solutions emerge. All this without the user having to know or specify the form or structure of solutions in advance. GP has generated a plethora of human-competitive results and applications, including novel scientific discoveries and patentable inventions. The authorsIntroduction -- Representation, initialisation and operators in Tree-based GP -- Getting ready to run genetic programming -- Example genetic programming run -- Alternative initialisations and operators in Tree-based GP -- Modular, grammatical and developmental Tree-based GP -- Linear and graph genetic programming -- Probalistic genetic programming -- Multi-objective genetic programming -- Fast and distributed genetic programming -- GP theory and its applications -- Applications -- Troubleshooting GP -- Conclusions.Contents xi 1 Introduction 1.1 Genetic Programming in a Nutshell 1.2 Getting Started 1.3 Prerequisites 1.4 Overview of this Field Guide I Basics 2 Representation, Initialisation and GP 2.1 Representation 2.2 Initialising the Population 2.3 Selection 2.4 Recombination and Mutation Operators in Tree-based 3 Getting Ready to Run Genetic Programming 19 3.1 Step 1: Terminal Set 19 3.2 Step 2: Function Set 20 3.2.1 Closure 21 3.2.2 Sufficiency 23 3.2.3 Evolving Structures other than Programs 23 3.3 Step 3: Fitness Function 24 3.4 Step 4: GP Parameters 26 3.5 Step 5: Termination and solution designation 27 4 Example Genetic Programming Run 4.1 Preparatory Steps 29 4.2 Step-by-Step Sample Run 31 4.2.1 Initialisation 31 4.2.2 Fitness Evaluation Selection, Crossover and Mutation Termination and Solution Designation Advanced Genetic Programming 5 Alternative Initialisations and Operators in 5.1 Constructing the Initial Population 5.1.1 Uniform Initialisation 5.1.2 Initialisation may Affect Bloat 5.1.3 Seeding 5.2 GP Mutation 5.2.1 Is Mutation Necessary? 5.2.2 Mutation Cookbook 5.3 GP Crossover 5.4 Other Techniques 32 5.5 Tree-based GP 39 6 Modular, Grammatical and Developmental Tree-based GP 47 6.1 Evolving Modular and Hierarchical Structures 47 6.1.1 Automatically Defined Functions 48 6.1.2 Program Architecture and Architecture-Altering 50 6.2 Constraining Structures 51 6.2.1 Enforcing Particular Structures 52 6.2.2 Strongly Typed GP 52 6.2.3 Grammar-based Constraints 53 6.2.4 Constraints and Bias 55 6.3 Developmental Genetic Programming 57 6.4 Strongly Typed Autoconstructive GP with PushGP 59 7 Linear and Graph Genetic Programming 61 7.1 Linear Genetic Programming 61 7.1.1 Motivations 61 7.1.2 Linear GP Representations 62 7.1.3 Linear GP Operators 64 7.2 Graph-Based Genetic Programming 65 7.2.1 Parallel Distributed GP (PDGP) 65 7.2.2 PADO 67 7.2.3 Cartesian GP 67 7.2.4 Evolving Parallel Programs using Indirect Encodings 68 8 Probabilistic Genetic Programming 8.1 Estimation of Distribution Algorithms 69 8.2 Pure EDA GP 71 8.3 Mixing Grammars and Probabilities 74 9 Multi-objective Genetic Programming 75 9.1 Combining Multiple Objectives into a Scalar Fitness Function 75 9.2 Keeping the Objectives Separate 76 9.2.1 Multi-objective Bloat and Complexity Control 77 9.2.2 Other Objectives 78 9.2.3 Non-Pareto Criteria 80 9.3 Multiple Objectives via Dynamic and Staged Fitness Functions 80 9.4 Multi-objective Optimisation via Operator Bias 81 10 Fast and Distributed Genetic Programming 83 10.1 Reducing Fitness Evaluations/Increasing their Effectiveness 83 10.2 Reducing Cost of Fitness with Caches 86 10.3 Parallel and Distributed GP are Not Equivalent 88 10.4 Running GP on Parallel Hardware 89 10.4.1 Master–slave GP 89 10.4.2 GP Running on GPUs 90 10.4.3 GP on FPGAs 92 10.4.4 Sub-machine-code GP 93 10.5 Geographically Distributed GP 93 11 GP Theory and its Applications 97 11.1 Mathematical Models 98 11.2 Search Spaces 99 11.3 Bloat 101 11.3.1 Bloat in Theory 101 11.3.2 Bloat Control in Practice 104 III Practical Genetic Programming 12 Applications 12.1 Where GP has Done Well 12.2 Curve Fitting, Data Modelling and Symbolic Regression 12.3 Human Competitive Results – the Humies 12.4 Image and Signal Processing 12.5 Financial Trading, Time Series, and Economic Modelling 12.6 Industrial Process Control 12.7 Medicine, Biology and Bioinformatics 12.8 GP to Create Searchers and Solvers – Hyper-heuristics xiii 12.9 Entertainment and Computer Games 127 12.10The Arts 127 12.11Compression 128 13 Troubleshooting GP 13.1 Is there a Bug in the Code? 13.2 Can you Trust your Results? 13.3 There are No Silver Bullets 13.4 Small Changes can have Big Effects 13.5 Big Changes can have No Effect 13.6 Study your Populations 13.7 Encourage Diversity 13.8 Embrace Approximation 13.9 Control Bloat 13.10 Checkpoint Results 13.11 Report Well 13.12 Convince your Customers 14 Conclusions Tricks of the Trade A Resources A.1 Key Books A.2 Key Journals A.3 Key International Meetings A.4 GP Implementations A.5 On-Line Resources 145 B TinyGP 151 B.1 Overview of TinyGP 151 B.2 Input Data Files for TinyGP 153 B.3 Source Code 154 B.4 Compiling and Running TinyGP 162 Bibliography 167 Inde

Visual information and knowledge representation in organisations

The construction industry’s environment is continually changing. Employees are now more geographically widespread and diverse, both culturally and educationally, than ever before. A great deal of research has been carried out on knowledge acquisition and storage, but there is still a distinct lack of research into knowledge presentation and communication. Information and knowledge presentation play a significant role in daily decision-making processes, when inappropriate decisions may result from inaccurate or poorly communicated information. The simplified, filtered coherent presentation of explicit knowledge can be instrumental to a successful, profitable and safety conscious business. Wates Construction is a major construction company and employs around 1300 people directly, as well as various subcontractors on different projects. Their current turn over is around £1billion, they are based in the UK and have branches in Ireland and Abu Dhabi. Wates realised their existing information system was inefficiently conveying information to its employees and the need to provide a simplified system, to assist staff’s decision-making processes. Earlier IT professionals’ attempts to make the system more usable had made no significant difference to its performance

Interactive analysis of time intervals in a two-dimensional space

Time intervals are conventionally represented as linear segments in a one-dimensional space. An alternative representation of time intervals is the triangular model (TM), which represents time intervals as points in a two-dimensional space. In this paper, the use of TM in visualising and analysing time intervals is investigated. Not only does this model offer a compact visualisation of the distribution of intervals, it also supports an innovative temporal query mechanism that relies on geometries in the two-dimensional space. This query mechanism has the potential to simplify queries that are difficult to specify using traditional linear temporal query devices. Moreover, a software prototype that implements TM in a geographical information system (GIS) is introduced. This prototype has been applied in a real scenario to analyse time intervals that were detected by a Bluetooth tracking system. This application shows that TM has the potential to support a traditional GIS to analyse interval-based geographical data

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio