title: Chinese Public Attitudes Toward Epilepsy (PATE) scale: translation and psychometric evaluation

authors: Lim, Kheng Seang

subjects: Public Attitudes Toward Epilepsy

abstract: None of the quantitative scale for public attitudes toward epilepsy was translated to Chinese language. This study aimed to translate and test the validity and reliability of a Chinese version of the Public Attitudes Toward Epilepsy (PATE) scale. Methods: The translation was performed according to standard principles and tested in 140 Chinese-speaking adults aged more than 18 years for psychometric validation. Results: The items in each domain had similar standard deviations (equal item variance), ranged from 0.85-0.95 in personal domain and 0.75-1.04 in general domain. The correlation between an item and its domain was 0.4 and above for all, and higher than the correlation with the other domain. Multitrait analysis showed the Chinese PATE had a similar variance, floor and ceiling effects, and relative relationship between the domains, as the original PATE. The Chinese PATE scale showed a similar correlation with almost all demographic variable except age. Item means were generally clustered in the factor analysis as hypothesized. The Cronbach’s α values was within acceptable range (0.773) in the personal domain and satisfactory range (0.693) in the general domain. Conclusion: The Chinese PATE scale is a validated and reliable translated version in measuring the public attitudes toward epilepsy.

text: Chinese Public Attitudes Toward Epilepsy (PATE) scale: translation and psychometric evaluation None of the quantitative scale for public attitudes toward epilepsy was translated to Chinese language. This study aimed to translate and test the validity and reliability of a Chinese version of the Public Attitudes Toward Epilepsy (PATE) scale. Methods: The translation was performed according to standard principles and tested in 140 Chinese-speaking adults aged more than 18 years for psychometric validation. Results: The items in each domain had similar standard deviations (equal item variance), ranged from 0.85-0.95 in personal domain and 0.75-1.04 in general domain. The correlation between an item and its domain was 0.4 and above for all, and higher than the correlation with the other domain. Multitrait analysis showed the Chinese PATE had a similar variance, floor and ceiling effects, and relative relationship between the domains, as the original PATE. The Chinese PATE scale showed a similar correlation with almost all demographic variable except age. Item means were generally clustered in the factor analysis as hypothesized. The Cronbach’s α values was within acceptable range (0.773) in the personal domain and satisfactory range (0.693) in the general domain. Conclusion: The Chinese PATE scale is a validated and reliable translated version in measuring the public attitudes toward epilepsy.

year: 2013

title: Holocene volcanic soils in the Mt. Gambier region, South Australia

authors: Takesako, Hiroshi

subjects: Andic properties

abstract: Volcanic soils derived from mid-Holocene basaltic tephra in the Mt. Gambier region of South Australia have developed in a xeric moisture regime. We studied two soils, one at Mt Gambier (MTG) and the other at nearby Mt Schank (MTS). Both volcanoes were active ca. 6000 cal. years ago. The MTG soil has a high content of CaCO₃ (incorporated during eruption through limestone) and other exotic materials intermixed with basaltic tephra containing low amounts of glass. The MTS soil is derived mainly from basaltic tephra with high glass content and much less CaCO₃ than at MTG. These parent mineralogies have led to markedly different clay compositions and chemical properties: the MTS soil contains abundant allophane (mainly) and ferrihydrite with few layer silicate clays, whereas the MTG soil is dominated by layer silicate clays and low allophane or ferrihydrite. Both soils are near neutral or alkaline. The MTS soil has a melanic horizon and andic properties and is classed as a Melanoxerand. The MTG soil has weak andic properties with insufficient glass to enable it to be classed in the Andisols, and is instead a Calcixeroll.

text: Holocene volcanic soils in the Mt. Gambier region, South Australia Volcanic soils derived from mid-Holocene basaltic tephra in the Mt. Gambier region of South Australia have developed in a xeric moisture regime. We studied two soils, one at Mt Gambier (MTG) and the other at nearby Mt Schank (MTS). Both volcanoes were active ca. 6000 cal. years ago. The MTG soil has a high content of CaCO₃ (incorporated during eruption through limestone) and other exotic materials intermixed with basaltic tephra containing low amounts of glass. The MTS soil is derived mainly from basaltic tephra with high glass content and much less CaCO₃ than at MTG. These parent mineralogies have led to markedly different clay compositions and chemical properties: the MTS soil contains abundant allophane (mainly) and ferrihydrite with few layer silicate clays, whereas the MTG soil is dominated by layer silicate clays and low allophane or ferrihydrite. Both soils are near neutral or alkaline. The MTS soil has a melanic horizon and andic properties and is classed as a Melanoxerand. The MTG soil has weak andic properties with insufficient glass to enable it to be classed in the Andisols, and is instead a Calcixeroll.

year: 2010

title: Visualising categorical data: Linguistic case studies from te Reo Māori and New Zealand English

authors: Trye, David

subjects: visualisation

abstract: Categorical variables are prevalent in real-world datasets across numerous domains, yet few visualisation techniques accommodate them effectively. This is especially true of datasets comprising three or more categorical variables, termed multivariate categorical data. Visualising such data is challenging due to the lack of inherent ordering of nominal categories, the so-called ‘curse of dimensionality’, and the potential variability in the number of categories per variable. Corpus linguistics, which involves the study of large digital collections of naturally occurring language, serves as the primary application domain in this thesis. This domain was chosen because it is rich in multivariate categorical data and, at the same time, is often visualised using only basic techniques.

This thesis contributes to the area of categorical data visualisation in several ways. First, we propose a taxonomy of techniques for visualising categorical data, highlight limitations of existing solutions, and identify relevant analysis tasks. Building on this foundation, the thesis introduces novel techniques and enhancements for visualising datasets involving multiple categorical variables. We focus on adapting the layout and interactive capabilities of an existing technique that uses a matrix of heatmaps to represent pairwise category intersections. These modifications show that directly visualising statistical test results for categorical data can be beneficial for exploring bivariate patterns and associations. Furthermore, we contribute the design, implementation and evaluation of a novel technique called MultiCat, which is not restricted to pairwise intersections but rather facilitates analysis of relationships among multiple variables simultaneously. Both these techniques are interactive and offer greater scalability than existing alternatives, thereby affording new possibilities for analysing multivariate categorical data. However, since categorical variables can occur within more complex data structures, we also consider their presence in networks and hypergraphs, which require specialised methods.

To demonstrate the application of these techniques, we draw on two linguistic case studies that focus on languages of special significance in Aotearoa New Zealand. Addressing the low-resource status of Māori, the country’s Indigenous language, we first contribute two related Twitter datasets—a monolingual Māori corpus and a mixed–language Māori–English corpus—together with an architecture for differentiating Māori and English words. Our initial case study uses the monolingual Māori corpus and proposed visualisation techniques to investigate grammatical possession in Māori, offering fresh insights into the linguistic practices of contemporary speakers. The second case study uses networks and hypergraphs with categorical attributes to explore Māori loanword co-occurrence in New Zealand English newspaper articles. We find that loanwords tend not to occur in isolation and that New Zealanders are still importing new (unlisted) borrowings from Māori.

Ultimately, the techniques developed in this thesis have broad applications both within and beyond the corpus linguistics community. By enabling more effective visualisation and analysis of multivariate categorical data, this research has the potential to facilitate deeper insights into domains as diverse as education, healthcare, business and science.

text: Visualising categorical data: Linguistic case studies from te Reo Māori and New Zealand English Categorical variables are prevalent in real-world datasets across numerous domains, yet few visualisation techniques accommodate them effectively. This is especially true of datasets comprising three or more categorical variables, termed multivariate categorical data. Visualising such data is challenging due to the lack of inherent ordering of nominal categories, the so-called ‘curse of dimensionality’, and the potential variability in the number of categories per variable. Corpus linguistics, which involves the study of large digital collections of naturally occurring language, serves as the primary application domain in this thesis. This domain was chosen because it is rich in multivariate categorical data and, at the same time, is often visualised using only basic techniques.

This thesis contributes to the area of categorical data visualisation in several ways. First, we propose a taxonomy of techniques for visualising categorical data, highlight limitations of existing solutions, and identify relevant analysis tasks. Building on this foundation, the thesis introduces novel techniques and enhancements for visualising datasets involving multiple categorical variables. We focus on adapting the layout and interactive capabilities of an existing technique that uses a matrix of heatmaps to represent pairwise category intersections. These modifications show that directly visualising statistical test results for categorical data can be beneficial for exploring bivariate patterns and associations. Furthermore, we contribute the design, implementation and evaluation of a novel technique called MultiCat, which is not restricted to pairwise intersections but rather facilitates analysis of relationships among multiple variables simultaneously. Both these techniques are interactive and offer greater scalability than existing alternatives, thereby affording new possibilities for analysing multivariate categorical data. However, since categorical variables can occur within more complex data structures, we also consider their presence in networks and hypergraphs, which require specialised methods.

To demonstrate the application of these techniques, we draw on two linguistic case studies that focus on languages of special significance in Aotearoa New Zealand. Addressing the low-resource status of Māori, the country’s Indigenous language, we first contribute two related Twitter datasets—a monolingual Māori corpus and a mixed–language Māori–English corpus—together with an architecture for differentiating Māori and English words. Our initial case study uses the monolingual Māori corpus and proposed visualisation techniques to investigate grammatical possession in Māori, offering fresh insights into the linguistic practices of contemporary speakers. The second case study uses networks and hypergraphs with categorical attributes to explore Māori loanword co-occurrence in New Zealand English newspaper articles. We find that loanwords tend not to occur in isolation and that New Zealanders are still importing new (unlisted) borrowings from Māori.

Ultimately, the techniques developed in this thesis have broad applications both within and beyond the corpus linguistics community. By enabling more effective visualisation and analysis of multivariate categorical data, this research has the potential to facilitate deeper insights into domains as diverse as education, healthcare, business and science.

year: 2024