Which patients with chronic kidney disease have the greatest symptom burden? A comparative study of advanced CKD stage and dialysis modality

Background Chronic kidney disease (CKD) leads to a range of symptoms, which are often under-recognised and little is known about the multidimensional symptom experience in advanced CKD. Objectives To examine (1) symptom burden at CKD stages 4 and 5, and dialysis modalities, and (2) demographic and renal history correlates of symptom burden. Methods Using a cross-sectional design, a convenience sample of 436 people with CKD was recruited from three hospitals. The CKD Symptom Burden Index (CKD-SBI) was used to measure the prevalence, severity, distress and frequency of 32 symptoms. Demographic and renal history data were also collected. Results Of the sample, 75.5 % were receiving dialysis (haemodialysis, n = 287; peritoneal dialysis, n = 42) and 24.5 % were not undergoing dialysis (stage 4, n = 69; stage 5, n = 38). Participants reported an average of 13.01 ± 7.67 symptoms. Fatigue and pain were common and burdensome across all symptom dimensions. While approximately one-third experienced sexual symptoms, when reported these symptoms were frequent, severe and distressing. Haemodialysis, older age and being female were independently associated with greater symptom burden. Conclusions In CKD, symptom burden is better understood when capturing the multidimensional aspects of a range of physical and psychological symptoms. Fatigue, pain and sexual dysfunction are key contributors to symptom burden, and these symptoms are often under-recognised and warrant routine assessment. The CKD-SBI offers a valuable tool for renal clinicians to assess symptom burden, leading to the commencement of timely and appropriate interventions.

Lidar heat map based channel sounding for complex wireless environments

This thesis is a development of a methodology to predict the radio transmitter signal attenuation, via vertical density profiling of digitised objects, through the use of Light Detection and Ranging (LiDaR) measurements. The resulting map of indexed signal attenuation is useful for dynamic radio transmitter placement within the geospatial data set without expensive and tedious radio measurements.

A comparative structural bioinformatics analysis of the insulin receptor family ectodomain based on phylogenetic information

The insulin receptor (IR), the insulin-like growth factor 1 receptor (IGF1R) and the insulin receptor-related receptor (IRR) are covalently-linked homodimers made up of several structural domains. The molecular mechanism of ligand binding to the ectodomain of these receptors and the resulting activation of their tyrosine kinase domain is still not well understood. We have carried out an amino acid residue conservation analysis in order to reconstruct the phylogeny of the IR Family. We have confirmed the location of ligand binding site 1 of the IGF1R and IR. Importantly, we have also predicted the likely location of the insulin binding site 2 on the surface of the fibronectin type III domains of the IR. An evolutionary conserved surface on the second leucine-rich domain that may interact with the ligand could not be detected. We suggest a possible mechanical trigger of the activation of the IR that involves a slight ‘twist’ rotation of the last two fibronectin type III domains in order to face the likely location of insulin. Finally, a strong selective pressure was found amongst the IRR orthologous sequences, suggesting that this orphan receptor has a yet unknown physiological role which may be conserved from amphibians to mammals.

A comparative study of early childhood curriculum documents focused on education for sustainability in South Korea and Australia

This thesis is about a comparative study of early childhood education (ECE) curriculum documents focused on education for sustainability (EfS) in South Korea and Australia. It examined how the national ECE curriculum documents in two culturally different contexts align with contemporary concepts of sustainability and activist early childhood education for sustainability (ECEfS) principles. Drawing on systems theory, Korean and Australian ECE curriculum documents were used as the primary sources for this study within the framework of critical document analysis (CDA). This study offers a step forward in developing culturally inclusive/holistic understandings of sustainability and more contextualised/localised approaches to ECEfS.

Towards a typology of hashtag publics: A large-scale comparative study of user engagement across trending topics

Twitter’s hashtag functionality is now used for a very wide variety of purposes, from covering crises and other breaking news events through gathering an instant community around shared media texts (such as sporting events and TV broadcasts) to signalling emotive states from amusement to despair. These divergent uses of the hashtag are increasingly recognised in the literature, with attention paid especially to the ability for hashtags to facilitate the creation of ad hoc or hashtag publics. A more comprehensive understanding of these different uses of hashtags has yet to be developed, however. Previous research has explored the potential for a systematic analysis of the quantitative metrics that could be generated from processing a series of hashtag datasets. Such research found, for example, that crisis-related hashtags exhibited a significantly larger incidence of retweets and tweets containing URLs than hashtags relating to televised events, and on this basis hypothesised that the information-seeking and -sharing behaviours of Twitter users in such different contexts were substantially divergent. This article updates such study and their methodology by examining the communicative metrics of a considerably larger and more diverse number of hashtag datasets, compiled over the past five years. This provides an opportunity both to confirm earlier findings, as well as to explore whether hashtag use practices may have shifted subsequently as Twitter’s userbase has developed further; it also enables the identification of further hashtag types beyond the “crisis” and “mainstream media event” types outlined to date. The article also explores the presence of such patterns beyond recognised hashtags, by incorporating an analysis of a number of keyword-based datasets. This large-scale, comparative approach contributes towards the establishment of a more comprehensive typology of hashtags and their publics, and the metrics it describes will also be able to be used to classify new hashtags emerging in the future. In turn, this may enable researchers to develop systems for automatically distinguishing newly trending topics into a number of event types, which may be useful for example for the automatic detection of acute crises and other breaking news events.

Reforming technology company incentive programs for achieving knowledge-based economic development:a Brazil-Australia comparative study

This doctoral thesis aims to demonstrate the importance of incentives to technology-based firms as a strategy to promote knowledge-based economic development (KBED). To remain competitive, technology-based firms must innovate and seek new markets; therefore, this study aims to propose an incentive model to technology-based firms as a strategy to promote knowledge-based urban development, according to framework described by Yigitcanlar (2011). This is an exploratory and descriptive research with a qualitative approach. Surveys were carried out with national trade associations that represented technology-based firms both in Brazil and Australia. After analysing the surveys, structured interviews were conducted with government representatives, trade associations and businessmen who had used financial support by the federal government. When comparing both countries, the study found the importance of direct incentives through tax incentives, for it is a less bureaucratic, quicker and more direct process for firms. We suggest to include the terms incentives in the framework of knowledge-based urban development, as one of the pillars that contribute to knowledge-based economic development.

Revisiting Coptotermes (Isoptera: Rhinotermitidae): a global taxonomic road map for species validity and distribution of an economically important subterranean termite genus

Coptotermes Wasmann (Isoptera: Rhinotermitidae) is one of the most economically important subterranean termite genera and some species are successful invaders. However, despite its important pest status, the taxonomic validity of many named Coptotermes species remains unclear. In this study, we reviewed all named species within the genus and investigated evidence supporting the validity of each named species. Species were systematically scrutinized according to the region of their original description: Southeast Asia, India, China, Africa, the Neotropics, and Australia. We estimate that of the currently 69 named species described by accepted nomenclatural rules, only 21 taxa have solid evidence for validity, 44 names have uncertain status, and the remaining species names should be synonymized or were made unavailable. Species with high degrees of invasiveness may be known under additional junior synonyms due to independent parochial descriptions. Molecular data for a vast majority of species are scarce and significant effort is needed to complete the taxonomic and phylogenetic revision of the genus. Because of the wide distribution of Coptotermes, we advocate for an integrative taxonomic effort to establish the distribution of each putative species, provide specimens and corresponding molecular data, check original descriptions and type specimens (if available), and provide evidence for a more robust phylogenetic position of each species. This study embodies both consensus and contention of those studying Coptotermes and thus pinpoints the current uncertainty of many species. This project is intended to be a roadmap for identifying those Coptotermes species names that need to be more thoroughly investigated, as an incentive to complete a necessary revision process.

Mixed pixel analysis and assessment for flood mapping

The most difficult operation in flood inundation mapping using optical flood images is to map the ‘wet’ areas where trees and houses are partly covered by water. This can be referred to as a typical problem of the presence of mixed pixels in the images. A number of automatic information extracting image classification algorithms have been developed over the years for flood mapping using optical remote sensing images, with most labelling a pixel as a particular class. However, they often fail to generate reliable flood inundation mapping because of the presence of mixed pixels in the images. To solve this problem, spectral unmixing methods have been developed. In this thesis, methods for selecting endmembers and the method to model the primary classes for unmixing, the two most important issues in spectral unmixing, are investigated. We conduct comparative studies of three typical spectral unmixing algorithms, Partial Constrained Linear Spectral unmixing, Multiple Endmember Selection Mixture Analysis and spectral unmixing using the Extended Support Vector Machine method. They are analysed and assessed by error analysis in flood mapping using MODIS, Landsat and World View-2 images. The Conventional Root Mean Square Error Assessment is applied to obtain errors for estimated fractions of each primary class. Moreover, a newly developed Fuzzy Error Matrix is used to obtain a clear picture of error distributions at the pixel level. This thesis shows that the Extended Support Vector Machine method is able to provide a more reliable estimation of fractional abundances and allows the use of a complete set of training samples to model a defined pure class. Furthermore, it can be applied to analysis of both pure and mixed pixels to provide integrated hard-soft classification results. Our research also identifies and explores a serious drawback in relation to endmember selections in current spectral unmixing methods which apply fixed sets of endmember classes or pure classes for mixture analysis of every pixel in an entire image. However, as it is not accurate to assume that every pixel in an image must contain all endmember classes, these methods usually cause an over-estimation of the fractional abundances in a particular pixel. In this thesis, a subset of adaptive endmembers in every pixel is derived using the proposed methods to form an endmember index matrix. The experimental results show that using the pixel-dependent endmembers in unmixing significantly improves performance.