Functional MRI BOLD response to Tower of London performance of first-episode schizophrenia patients using cortical pattern matching

Due to its three-dimensional folding pattern, the human neocortex; poses a challenge for accurate co-registration of grouped functional; brain imaging data. The present study addressed this problem by; employing three-dimensional continuum-mechanical image-warping; techniques to derive average anatomical representations for coregistration; of functional magnetic resonance brain imaging data; obtained from 10 male first-episode schizophrenia patients and 10 age-matched; male healthy volunteers while they performed a version of the; Tower of London task. This novel technique produced an equivalent; representation of blood oxygenation level dependent (BOLD) response; across hemispheres, cortical regions, and groups, respectively, when; compared to intensity average co-registration, using a deformable; Brodmann area atlas as anatomical reference. Somewhat closer; association of Brodmann area boundaries with primary visual and; auditory areas was evident using the gyral pattern average model.; Statistically-thresholded BOLD cluster data confirmed predominantly; bilateral prefrontal and parietal, right frontal and dorsolateral; prefrontal, and left occipital activation in healthy subjects, while; patients’ hemispheric dominance pattern was diminished or reversed,; particularly decreasing cortical BOLD response with increasing task; difficulty in the right superior temporal gyrus. Reduced regional gray; matter thickness correlated with reduced left-hemispheric prefrontal/; frontal and bilateral parietal BOLD activation in patients. This is the; first study demonstrating that reduction of regional gray matter in; first-episode schizophrenia patients is associated with impaired brain; function when performing the Tower of London task, and supports; previous findings of impaired executive attention and working memory; in schizophrenia.

Name-calling by a child diagnosed with asperger’s syndrome

Rendle-Short, Wilkinson, and Danby show how social interaction is directly relevant to maintaining friendships, mental health and well-being, and supportive peer relations. Using conversation analysis, the chapter focuses on conversational participants’ pursuit of affiliation and intimacy from a language as action perspective. It focuses on the use of derogatory naming practices by a 10-year-old girl diagnosed with Asperger’s Syndrome. The analysis shows how derogatory address terms, part of a wider pattern of behaviour evident in this child’s interaction, result in behaviour that might be thought of as impolite or lacking in restraint. It also illustrates how a single case study can draw attention to the context-specific nature of interaction when working with children with Asperger’s Syndrome. The chapter contributes to our understanding of the difficulty in pinpointing, with precision and with clear evidence, what counts as a ‘social interaction difficulty’ due to the context specific nature of interaction.

The Cairns abortion trial: Language, deviance, and the ‘spoiled identity’

In 2009 a couple in Cairns were charged, and later found not guilty, of illegally obtaining a medical abortion through the use of medication imported from overseas. The court case reignited the discussions surrounding the illegality and social acceptance of abortion in Queensland, Australia. Based on a discourse analysis of 150 online news media articles covering the Cairns trial, this article critically examines the language and key words relied upon by media when covering the Cairns trial. It argues that, despite popular support for the decriminalisation of abortion, emotive language that aligns with a pro-life ideology is still being employed which has the power to shape perceptions of deviance and stigma surrounding abortion. This is useful to demonstrate how media discourse surrounding abortion needs to further align with a pro-choice ideology for women to be empowered for their choices.

Topical pattern based document modelling and relevance ranking

For traditional information filtering (IF) models, it is often assumed that the documents in one collection are only related to one topic. However, in reality users’ interests can be diverse and the documents in the collection often involve multiple topics. Topic modelling was proposed to generate statistical models to represent multiple topics in a collection of documents, but in a topic model, topics are represented by distributions over words which are limited to distinctively represent the semantics of topics. Patterns are always thought to be more discriminative than single terms and are able to reveal the inner relations between words. This paper proposes a novel information filtering model, Significant matched Pattern-based Topic Model (SPBTM). The SPBTM represents user information needs in terms of multiple topics and each topic is represented by patterns. More importantly, the patterns are organized into groups based on their statistical and taxonomic features, from which the more representative patterns, called Significant Matched Patterns, can be identified and used to estimate the document relevance. Experiments on benchmark data sets demonstrate that the SPBTM significantly outperforms the state-of-the-art models.

Towards a potential model to enhance language learner autonomy in the Vietnamese higher education context

This constructivist theory-led case study explored how the term language learner autonomy (LLA) is interpreted and the appropriate pedagogy to foster LLA in the Vietnamese higher education context. Evidence through the exploration of the government policies and the cases of three EFL classes confirms the interpretation that learner autonomy and language acquisition are mutually supported. The study has proposed project work as a potential model while demonstrating the role of the teacher and the use of target language as mediators to enhance LLA in the local context. Findings of the study contribute a theoretical and pedagogical justification for encouraging LLA in Vietnam and other similar contexts.

A modified Density-Based Scanning Algorithm with Noise for spatial travel pattern analysis from Smart Card AFC data

Smart Card Automated Fare Collection (AFC) data has been extensively exploited to understand passenger behavior, passenger segment, trip purpose and improve transit planning through spatial travel pattern analysis. The literature has been evolving from simple to more sophisticated methods such as from aggregated to individual travel pattern analysis, and from stop-to-stop to flexible stop aggregation. However, the issue of high computing complexity has limited these methods in practical applications. This paper proposes a new algorithm named Weighted Stop Density Based Scanning Algorithm with Noise (WS-DBSCAN) based on the classical Density Based Scanning Algorithm with Noise (DBSCAN) algorithm to detect and update the daily changes in travel pattern. WS-DBSCAN converts the classical quadratic computation complexity DBSCAN to a problem of sub-quadratic complexity. The numerical experiment using the real AFC data in South East Queensland, Australia shows that the algorithm costs only 0.45% in computation time compared to the classical DBSCAN, but provides the same clustering results.

The Arab Spring on Twitter: Language Communities in #egypt and #libya

Building on hashtag datasets gathered since January 2011, this paper will compare patterns of Twitter usage during the popular revolution in Egypt and the civil war in Libya. Using custom-made tools for processing ‘big data’ (boyd & Crawford, 2011), we will examine the volume of tweets sent by English-, Arabic-, and mixed-language Twitter users over time, and examine the networks of interaction (variously through @replying, retweeting, or both) between these groups as they developed and shifted over the course of these uprisings. Examining @reply and retweet traffic, we will identify general patterns of information flow between the English- and Arabic-speaking sides of the Twittersphere, and highlight the roles played by key boundary riders connecting both language spheres. Further, we will examine the URLs shared in these hashtags by Twitter participants, to identify the most prominent overall information sources, examine differences in the information diet experienced by English- and Arabic-language users, and investigate whether there are any online sources whose URLs are transcending language boundaries more frequently than others.