Unravelling migratory connectivity in marine turtles using multiple methods

1. Comprehensive knowledge of the fundamental spatial ecology of marine species is critical to allow the identification of key habitats and the likely sources of anthropogenic threats, thus informing effective conservation strategies. 2. Research on migratory marine vertebrates has lagged behind many similar terrestrial animal groups, but studies using electronic tagging systems and molecular techniques offer great insights. 3. Marine turtles have complex life history patterns, spanning wide spatio-temporal scales. As a result of this multidimensional complexity, and despite extensive effort, there are no populations for which a truly holistic understanding of the spatial aspects of the life history has been attained. There is a particular lack of information regarding the distribution and habitats utilized during the first few years of life. 4. We used satellite tracking technology to track individual turtles following nesting at the green turtle Chelonia mydas nesting colony at Poilão Island, Guinea Bissau; the largest breeding aggregation in the eastern Atlantic. 5. We further contextualize these data with pan-Atlantic molecular data and oceanographic current modelling to gain insights into likely dispersal patterns of hatchlings and small pelagic juveniles. 6. All adult turtles remained in the waters of West Africa, with strong connectivity demonstrated with Banc D’Arguin, Mauritania. 7. Despite shortcomings in current molecular markers, we demonstrate evidence for profound sub-structuring of marine turtle stocks across the Atlantic; with a high likelihood based on oceanographic modelling that most turtles from Guinea-Bissau are found in the eastern Atlantic. 8. Synthesis and applications. There is an increased need for a better understanding of spatial distribution of marine vertebrates demonstrating life histories with spatio-temporal complexity. We propose the synergistic use of the technologies and modelling used here as a working framework for the future rapid elucidation of the range and likely key habitats used by the different life stages from such species.

The placebo effect: measurement by multiple methods

This thesis investigated the relationship of explicit (self-report), implicit (IAT) and physiological variables to the placebo effect. The thesis consisted of three main parts. The first collected background data and developed models for two constructs (Optimism and Mindfulness) associated with the placebo effect and implicit attitudes, respectively. The second part of the thesis consisted of the development of an explicit measure of treatment expectancies, and the development of two IATs, one for Optimism and the other for Treatment Credibility. The final portion of the thesis was an experimental study (N=111) which tested these new measures in a sample of healthy volunteers. The primary hypothesis of the thesis, that there would be a relationship between the placebo effect and implicit measures, was not supported. Major findings include an effect of semantic priming on placebo response mediated by condition (Deceptive versus Open Placebo), an unexpected negative relationship between Optimism and self-reported Health, and a physiological relationship between pain ratings and GSR data, which was also mediated by Condition in the experiment. A complete record of the code and data for this thesis can be found at https://github.com/richiemorrisroe/Thesis

Adherence to antiepileptic medicines in children: A multiple-methods assessment involving dried blood spot sampling

Purpose: To evaluate adherence to prescribed antiepileptic drugs (AEDs) in children with epilepsy using a combination of adherence-assessment methods.
Methods: A total of 100 children with epilepsy (=17 years old) were recruited. Medication adherence was determined via parental and child self-reporting (=9 years old), medication refill data from general practitioner (GP) prescribing records, and via AED concentrations in dried blood spot (DBS) samples obtained from children at the clinic and via self- or parental-led sampling in children's own homes. The latter were assessed using population pharmacokinetic modeling. Patients were deemed nonadherent if any of these measures were indicative of nonadherence with the prescribed treatment. In addition, beliefs about medicines, parental confidence in seizure management, and the presence of depressed mood in parents were evaluated to examine their association with nonadherence in the participating children.
Key Findings: The overall rate of nonadherence in children with epilepsy was 33%. Logistic regression analysis indicated that children with generalized epilepsy (vs. focal epilepsy) were more likely (odds ratio [OR] 4.7, 95% confidence interval [CI] 1.37-15.81) to be classified as nonadherent as were children whose parents have depressed mood (OR 3.6, 95% CI 1.16-11.41).
Significance: This is the first study to apply the novel methodology of determining adherence via AED concentrations in clinic and home DBS samples. The present findings show that the latter, with further development, could be a useful approach to adherence assessment when combined with other measures including parent and child self-reporting. Seizure type and parental depressed mood were strongly predictive of nonadherence. © 2013 International League Against Epilepsy.
Key Words: Adherence, Epilepsy, Dried blood spots, MARS, Depressed mood.

Autonomous intelligent cruise control using a novel multiple-controller framework incorporating fuzzy-logic-based switching and tuning

This paper presents a novel intelligent multiple-controller framework incorporating a fuzzy-logic-based switching and tuning supervisor along with a generalised learning model (GLM) for an autonomous cruise control application. The proposed methodology combines the benefits of a conventional proportional-integral-derivative (PID) controller, and a PID structure-based (simultaneous) zero and pole placement controller. The switching decision between the two nonlinear fixed structure controllers is made on the basis of the required performance measure using a fuzzy-logic-based supervisor, operating at the highest level of the system. The supervisor is also employed to adaptively tune the parameters of the multiple controllers in order to achieve the desired closed-loop system performance. The intelligent multiple-controller framework is applied to the autonomous cruise control problem in order to maintain a desired vehicle speed by controlling the throttle plate angle in an electronic throttle control (ETC) system. Sample simulation results using a validated nonlinear vehicle model are used to demonstrate the effectiveness of the multiple-controller with respect to adaptively tracking the desired vehicle speed changes and achieving the desired speed of response, whilst penalising excessive control action. Crown Copyright (C) 2008 Published by Elsevier B.V. All rights reserved.

Multiple perspectives framework to model complex processes

The growing complexity of organisations has resulted in collaboration between multiple stakeholders becoming a challenging and critical issue that organisations must address in order to ensure their practices are sustainable. A multiple-case field study was conducted in order to demonstrate the proposed methodology of analysis and examination for knowledge-based systems in an actual organisational setting. The use of a multiple-perspective framework to improve understanding of the complex relationships in such systems was examined. In particular, the case study focused on the Australian Government’s Nation Building Economic Stimulus Plan (NBESP) which provided $1.9 billion to construct social housing across the State over two years. The results suggest that the use of a multi-perspective framework is appropriate and that there is a need for attention to be paid to the economic perspective.

A multiple account framework for cost-benefit analysis

The paper presents a spreadsheet-based multiple account framework for cost-benefit analysis which incorporates all the usual concerns of cost-benefit analysts such as shadow-pricing to account for market failure. distribution of net benefits. sensitivity and risk analysis, cost of public funds, and environmental effects. The approach is generalizable to a wide range of projects and situations and offers a number of advantages to both analysts and decision-makers, including transparency, a check on internal consistency, and a detailed summary of project net benefits disaggregated by stakeholder group. Of particular importance is the ease with which this framework allows for a project to be evaluated from alternative decision-making perspectives and under alternative policy scenarios where the trade-offs among the project's stakeholders can readily be identified and quantified. (C) 2004 Elsevier Ltd. All rights reserved.

Adherence to antiepileptic medicines in children:a multiple-methods assessment involving dried blood spot sampling

Purpose - To evaluate adherence to prescribed antiepileptic drugs (AEDs) in children with epilepsy using a combination of adherence-assessment methods. Methods - A total of 100 children with epilepsy (≤17 years old) were recruited. Medication adherence was determined via parental and child self-reporting (≥9 years old), medication refill data from general practitioner (GP) prescribing records, and via AED concentrations in dried blood spot (DBS) samples obtained from children at the clinic and via self- or parental-led sampling in children's own homes. The latter were assessed using population pharmacokinetic modeling. Patients were deemed nonadherent if any of these measures were indicative of nonadherence with the prescribed treatment. In addition, beliefs about medicines, parental confidence in seizure management, and the presence of depressed mood in parents were evaluated to examine their association with nonadherence in the participating children. Key Findings - The overall rate of nonadherence in children with epilepsy was 33%. Logistic regression analysis indicated that children with generalized epilepsy (vs. focal epilepsy) were more likely (odds ratio [OR] 4.7, 95% confidence interval [CI] 1.37–15.81) to be classified as nonadherent as were children whose parents have depressed mood (OR 3.6, 95% CI 1.16–11.41). Significance - This is the first study to apply the novel methodology of determining adherence via AED concentrations in clinic and home DBS samples. The present findings show that the latter, with further development, could be a useful approach to adherence assessment when combined with other measures including parent and child self-reporting. Seizure type and parental depressed mood were strongly predictive of nonadherence.

Cluster measurement and benchmarking - A recent Welsh approach

Drawing on extensive academic research and theory on clusters and their analysis, the methodology employed in this pilot study (sponsored by the Welsh Assembly Government’s Economic Research Grants Assessment Board) seeks to create a framework for reviewing and monitoring clusters in Wales on an ongoing basis, and generate the information necessary for successful cluster development policy to occur. The multi-method framework developed and tested in the pilot study is designed to map existing Welsh sectors with cluster characteristics, uncover existing linkages, and better understand areas of strength and weakness. The approach adopted relies on synthesising both quantitative and qualitative evidence. Statistical measures, including the size of potential clusters, are united with other evidence on input-output derived inter-linkages within clusters and to other sectors in Wales and the UK, as well as the export and import intensity of the cluster. Multi Sector Qualitative Analysis is then designed for competencies/capacity, risk factors, markets, types and crucially, the perceived strengths of cluster structures and relationships. The approach outlined above can, with the refinements recommended through the review process, provide policy-makers with a valuable tool for reviewing and monitoring individual sectors and ameliorating problems in sectors likely to decline further.

Online pattern classification with multiple neural network systems: an experimental study

In this paper, an empirical study of the development and application of a committee of neural networks on online pattern classification tasks is presented. A multiple classifier framework is designed by adopting an Adaptive Resonance Theory-based (ART) autonomously learning neural network as the building block. A number of algorithms for combining outputs from multiple neural classifiers are considered, and two benchmark data sets have been used to evaluate the applicability of the proposed system. Different learning strategies coupling offline and online learning approaches, as well as different input pattern representation schemes, including the "ensemble" and "modular" methods, have been examined experimentally. Benefits and shortcomings of each approach are systematically analyzed and discussed. The results are comparable, and in some cases superior, with those from other classification algorithms. The experiments demonstrate the potentials of the proposed multiple neural network systems in offering an alternative to handle online pattern classification tasks in possibly nonstationary environments.

Interest groups in multiple streams:specifying their involvement in the framework

Although interests inhabit a central place in the multiple streams framework (MSF), interest groups have played only a minor role in theoretical and empirical studies until now. In Kingdon’s original conception, organized interests are a key variable in the politics stream. Revisiting Kingdon’s concept with a particular focus on interest groups and their activities—in different streams and at various levels—in the policy process, we take this argument further. In particular, we argue that specifying groups’ roles in other streams adds value to the explanatory power of the framework. To do this, we look at how interest groups affect problems, policies, and politics. The influence of interest groups within the streams is explained by linking the MSF with literature on interest intermediation. We show that depending on the number of conditions and their activity level, interest groups can be involved in all three streams. We illustrate this in case studies reviewing labor market policies in Germany and chemicals regulation at the European level.

Evaluating statistical and machine learning methods to predict risk of in-hospital child mortality in Uganda

Thesis (Master's)--University of Washington, 2016-08