Computing and Information Systems - Research Publications
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ItemEvaluating untimed and timed abridged versions of Raven's Advanced Progressive Matrices(TAYLOR & FRANCIS INC, 2022-01-02)INTRODUCTION: Raven's Advanced Progressive Matrices (APM) are frequently utilized in clinical and experimental settings to index intellectual capacity. As the APM is a relatively long assessment, abridged versions of the test have been proposed. The psychometric properties of an untimed 12-item APM have received some consideration in the literature, but validity explorations have been limited. Moreover, both reliability and validity of a timed 12-item APM have not previously been examined. METHOD: We considered the psychometric properties of untimed (Study 1; N = 608; Mage = 27.89, SD = 11.68) and timed (Study 2; N = 479; Mage = 20.93, SD = 3.12) versions of a brief online 12-item form of the APM. RESULTS: Confirmatory factor analyses established both versions of the tests are unidimensional. Item response theory analyses revealed that, in each case, the 12 items are characterized by distinct differences in difficulty, discrimination, and guessing. Differential item functioning showed few male/female or native English/non-native English performance differences. Test-retest reliability was .65 (Study 1) to .69 (Study 2). Both tests had medium-to-large correlations with the Wechsler Abbreviated Scale of Intelligence (2nd ed.) Perceptual Reasoning Index (r = .50, Study 1; r = .56, Study 2) and Full-Scale IQ (r = .34, Study 1; r = .41, Study 2). CONCLUSION: In sum, results suggest both untimed and timed online versions of the brief APM are psychometrically sound. As test duration was found to be highly variable for the untimed version, the timed form might be a more suitable choice when it is likely to form part of a longer battery of tests. Nonetheless, classical test and item response theory analyses, plus validity considerations, suggest the untimed version might be the superior abridged form.
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ItemMAPPING THE CHATTER: SPATIAL METAPHORS FOR DYNAMIC TOPIC MODELLING OF SOCIAL MEDIA(Copernicus GmbH, 2022-08-05)Abstract. Topic modelling is a branch of Natural Language Processing (NLP) that deals with the discovery of conversation topics in a given document corpus. In social media, this translates into aggregating social media posts, e.g. tweets, into topics of conversation and observing how these topics evolve over time (hence the “dynamic” adjective). Conveying the results of topic modelling can be challenging since the topics often do not lend themselves naturally to meaningful labelling. The volume of real world (global) social media also means that millions of topics can be ongoing at any given time and the relationships between them can involve hundreds of dimensions and relationships that continually emerge. The popularity of topics is itself subject to change over time and reflect the pulse of what is happening in society at large. In this paper, we propose a spatialization technique based on open-source software that reduces the intrinsic complexity of dynamic topic modelling results to familiar topographic objects, namely: ridges, valleys, and peaks. This offers new possibilities for understanding complex relationships that change over time whilst overcoming issues with traditional topic modelling visualisation approaches such as network graphs.
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ItemNo Preview AvailableAttribute-BasedKeyword Search over the Encrypted Blockchain(TECH SCIENCE PRESS, 2021)
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ItemWomen with type 1 diabetes exhibit a progressive increase in gut Saccharomyces cerevisiae in pregnancy associated with evidence of gut inflammation(ELSEVIER IRELAND LTD, 2022-02)AIMS: Studies of the gut microbiome have focused on its bacterial composition. We aimed to characterize the gut fungal microbiome (mycobiome) across pregnancy in women with and without type 1 diabetes. METHODS: Faecal samples (n = 162) were collected from 70 pregnant women (45 with and 25 without type 1 diabetes) across all trimesters. Fungi were analysed by internal transcribed spacer 1 amplicon sequencing. Markers of intestinal inflammation (faecal calprotectin) and intestinal epithelial integrity (serum intestinal fatty acid binding protein; I-FABP), and serum antibodies to Saccharomyces cerevisiae (ASCA) were measured. RESULTS: Women with type 1 diabetes had decreased fungal alpha diversity by the third trimester, associated with an increased abundance of Saccharomyces cerevisiae that was inversely related to the abundance of the anti-inflammatory butyrate-producing bacterium Faecalibacterium prausnitzii. Women with type 1 diabetes had higher concentrations of calprotectin, I-FABP and ASCA. CONCLUSIONS: Women with type 1 diabetes exhibit a shift in the gut mycobiome across pregnancy associated with evidence of gut inflammation and impaired intestinal barrier function. The relevance of these findings to the higher rate of pregnancy complications in type 1 diabetes warrants further study.
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ItemRun or Pat: Using Deep Learning to Classify the Species Type and Emotion of Pets(EEE, 2021-01-01)Deep learning has been applied in many contexts. In this paper we present a novel application area: to detect the species type and emotion of pets with focus on a diverse set of dog and cat collections comprising 52 dog and 23 cat species. Building on an extensive collection of labelled images with over 300 images per species type, we explore a range of deep learning models to develop a classifier for species type and their associated emotion. We outline the realization of the technical solution delivered through a mobile application (iPhone/Android) and present results based on feedback based on real world adoption and utilisation by the broader mobile application community.
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ItemNo Preview Available
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ItemCogTale: an online platform for the evaluation, synthesis, and dissemination of evidence from cognitive interventions studies(BMC, 2021-08-24)Systematic reviews and meta-analyses are critical in health-related decision-making, and are considered the gold standard in research synthesis methods. However, with new trials being regularly published and with the development of increasingly rigorous standards of data synthesis, systematic reviews often require much expertise and long periods of time to be completed. Automation of some of the steps of evidence synthesis productions is a promising improvement in the field, capable of reducing the time and costs associated with the process.This article describes the development and main characteristics of a novel online repository of cognitive intervention studies entitled Cognitive Treatments Article Library and Evaluation (CogTale). The platform is currently in a Beta Release phase, as it is still under development. However, it already contains over 70 studies, and the CogTale team is continuously coding and uploading new studies into the repository. Key features include advanced search options, the capability to generate meta-analyses, and an up-to-date display of relevant published studies.
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ItemType 1 diabetes in pregnancy is associated with distinct changes in the composition and function of the gut microbiome(BMC, 2021-08-06)BACKGROUND: The gut microbiome changes in response to a range of environmental conditions, life events and disease states. Pregnancy is a natural life event that involves major physiological adaptation yet studies of the microbiome in pregnancy are limited and their findings inconsistent. Pregnancy with type 1 diabetes (T1D) is associated with increased maternal and fetal risks but the gut microbiome in this context has not been characterized. By whole metagenome sequencing (WMS), we defined the taxonomic composition and function of the gut bacterial microbiome across 70 pregnancies, 36 in women with T1D. RESULTS: Women with and without T1D exhibited compositional and functional changes in the gut microbiome across pregnancy. Profiles in women with T1D were distinct, with an increase in bacteria that produce lipopolysaccharides and a decrease in those that produce short-chain fatty acids, especially in the third trimester. In addition, women with T1D had elevated concentrations of fecal calprotectin, a marker of intestinal inflammation, and serum intestinal fatty acid-binding protein (I-FABP), a marker of intestinal epithelial damage. CONCLUSIONS: Women with T1D exhibit a shift towards a more pro-inflammatory gut microbiome during pregnancy, associated with evidence of intestinal inflammation. These changes could contribute to the increased risk of pregnancy complications in women with T1D and are potentially modifiable by dietary means. Video abstract.
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ItemHigher frequency of vertebrate-infecting viruses in the gut of infants born to mothers with type 1 diabetes(WILEY, 2020-02-05)Background: Microbial exposures in utero and early life shape the infant microbiome, which can profoundly impact on health. Compared to the bacterial microbiome, very little is known about the virome. We set out to characterize longitudinal changes in the gut virome of healthy infants born to mothers with or without type 1 diabetes using comprehensive virome capture sequencing. Methods: Healthy infants were selected from Environmental Determinants of Islet Autoimmunity (ENDIA), a prospective cohort of Australian children with a first‐degree relative with type 1 diabetes, followed from pregnancy. Fecal specimens were collected three‐monthly in the first year of life. Results: Among 25 infants (44% born to mothers with type 1 diabetes) at least one virus was detected in 65% (65/100) of samples and 96% (24/25) of infants during the first year of life. In total, 26 genera of viruses were identified and >150 viruses were differentially abundant between the gut of infants with a mother with type 1 diabetes vs without. Positivity for any virus was associated with maternal type 1 diabetes and older infant age. Enterovirus was associated with older infant age and maternal smoking. Conclusions: We demonstrate a distinct gut virome profile in infants of mothers with type 1 diabetes, which may influence health outcomes later in life. Higher prevalence and greater number of viruses observed compared to previous studies suggests significant underrepresentation in existing virome datasets, arising most likely from less sensitive techniques used in data acquisition.
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ItemEliciting group judgements about replicability: A technical implementation of the IDEA Protocol(Hawaii International Conference on System Sciences, 2021-01-01)In recent years there has been increased interest in replicating prior research. One of the biggest challenges to assessing replicability is the cost in resources and time that it takes to repeat studies. Thus there is an impetus to develop rapid elicitation protocols that can, in a practical manner, estimate the likelihood that research findings will successfully replicate. We employ a novel implementation of the IDEA ('Investigate', 'Discuss', 'Estimate' and 'Aggregate) protocol, realised through the repliCATS platform. The repliCATS platform is designed to scalably elicit expert opinion about replicability of social and behavioural science research. The IDEA protocol provides a structured methodology for eliciting judgements and reasoning from groups. This paper describes the repliCATS platform as a multi-user cloud-based software platform featuring (1) a technical implementation of the IDEA protocol for eliciting expert opinion on research replicability, (2) capture of consent and demographic data, (3) on-line training on replication concepts, and (4) exporting of completed judgements. The platform has, to date, evaluated 3432 social and behavioural science research claims from 637 participants.