Story patterns in oral narratives: a variationist critique of Labov and Waletzky's model of narrative schemas

Labov and Waletzky's (1967) influential six-schema model of personal narratives has often been considered to make claims regarding a 'universal' narrative structure (Hurst, 1990; Hymes, 1996). This study tests how far variations in personal narratives at a schematic level (that is, which schemas are present and how they combine to structure the narrated experience) correlate with aspects of an individual's culture. Oral narratives produced by members of the Greek Cypriot community in London are analysed, to provide data from an alternative group of informants to Labov and Waletzky's, while still using their model as the central framework for analysis. Frequent appearance in the data of an additional schema, 'post-evaluation', suggests that culture is a variable in relation to narrative structure, as are more specific individual and social factors including age and gender. Story topic is also shown to influence how narratives are structured, with different topics resulting in different structures and the general underlying theme of "Trouble" (Burke, 1945; Bruner, 1991; Bruner, 1997) (in fight, danger of death, argument and embarrassing personal experiences) shown to guarantee the 'crisis' required in a narrative. Such findings have implications as regards claims of a universal model of narrative; and the general view that one narrative-structure model may be suitable for all personal narratives is re-examined. By way of conclusion, the study formulates a 'variationist' model of narrative 'grammar' that combines core, optional and culturally variant features. It is suggested that such a model may begin to capture how an individual's social and cultural background, as well as story topic, can function as decisive factors in determining narrative form.

Supervised learning based multimodal MRI brain tumour segmentation using texture features from supervoxels

BACKGROUND: Accurate segmentation of brain tumour in magnetic resonance images (MRI) is a difficult task due to various tumour types. Using information and features from multimodal MRI including structural MRI and isotropic (p) and anisotropic (q) components derived from the diffusion tensor imaging (DTI) may result in a more accurate analysis of brain images. METHODS: We propose a novel 3D supervoxel based learning method for segmentation of tumour in multimodal MRI brain images (conventional MRI and DTI). Supervoxels are generated using the information across the multimodal MRI dataset. For each supervoxel, a variety of features including histograms of texton descriptor, calculated using a set of Gabor filters with different sizes and orientations, and first order intensity statistical features are extracted. Those features are fed into a random forests (RF) classifier to classify each supervoxel into tumour core, oedema or healthy brain tissue. RESULTS: The method is evaluated on two datasets: 1) Our clinical dataset: 11 multimodal images of patients and 2) BRATS 2013 clinical dataset: 30 multimodal images. For our clinical dataset, the average detection sensitivity of tumour (including tumour core and oedema) using multimodal MRI is 86% with balanced error rate (BER) 7%; while the Dice score for automatic tumour segmentation against ground truth is 0.84. The corresponding results of the BRATS 2013 dataset are 96%, 2% and 0.89, respectively. CONCLUSION: The method demonstrates promising results in the segmentation of brain tumour. Adding features from multimodal MRI images can largely increase the segmentation accuracy. The method provides a close match to expert delineation across all tumour grades, leading to a faster and more reproducible method of brain tumour detection and delineation to aid patient management

Media stylistics

In this chapter we review the concept of ‘media stylistics’. In particular, we disentangle the polysemy of these two terms which, when combined, describe but can also obscure work in this area; and we discuss key themes and concerns which emerge. Through analysis of two short extracts of media discourse in English, we elaborate a distinction between two alternative emphases: study of media language as concerned with the capabilities associated with changing technologies for conveying linguistic messages (e.g. language use in telegraphy, radio, or instant messaging); and study of media language as commentary on modern society’s dominant communication forms, which tend to take an electronic ‘media’ form. In the first emphasis, media discourse is important in understanding the social functions of language and as regards social change. In the second emphasis, media language is more a matter of linguistic resources being used to communicate within an array of contemporary media choices whose availability is simply taken as a social fact. In later stages of the chapter we examine interaction between these different emphases at the level of media ‘genres'. In the formation of media genres, we argue, patterns of linguistic choice are superimposed on a given technical infrastructure and history of media capabilities. Distinctive media styles gradually evolve from each such combination to serve specific and changing expressive and communicative purposes. We conclude with discussion of the implications of this view of media technologies and forms as regards the development of new communicative styles on the Internet

MicroRNA expression profiles in pediatric dysembryoplastic neuroepithelial tumors.

© Springer Science+Business Media New York 2015Among noncoding RNAs, microRNAs (miRNAs) have been most extensively studied, and their biology has repeatedly been proven critical for central nervous system pathological conditions. The diagnostic value of several miRNAs was appraised in pediatric dysembryoplastic neuroepithelial tumors (DNETs) using miRNA microarrays and receiving operating characteristic curves analyses. Overall, five pediatric DNETs were studied. As controls, 17 samples were used: the FirstChoice Human Brain Reference RNA and 16 samples from deceased children who underwent autopsy and were not present with any brain malignancy. The miRNA extraction was carried out using the mirVANA miRNA Isolation Kit, while the experimental approach included miRNA microarrays covering 1211 miRNAs. Quantitative real-time polymerase chain reaction was performed to validate the expression profiles of miR-1909* and miR-3138 in all samples initially screened with miRNA microarrays. Our findings indicated that miR-3138 might act as a tumor suppressor gene when down-regulated and miR-1909* as a putative oncogenic molecule when up-regulated in pediatric DNETs compared to the control cohort. Subsequently, both miRNA signatures might serve as putative diagnostic biomarkers for pediatric DNETs.Peer reviewedFinal Accepted Versio

Areas of normal pulmonary parenchyma on HRCT exhibit increased FDG PET signal in IPF patients

Purpose: Patients with idiopathic pulmonary fibrosis (IPF) show increased PET signal at sites of morphological abnormality on high-resolution computed tomography (HRCT). The purpose of this investigation was to investigate the PET signal at sites of normal-appearing lung on HRCT in IPF. Methods: Consecutive IPF patients (22 men, 3 women) were prospectively recruited. The patients underwent 18F-FDG PET/HRCT. The pulmonary imaging findings in the IPF patients were compared to the findings in a control population. Pulmonary uptake of 18F-FDG (mean SUV) was quantified at sites of morphologically normal parenchyma on HRCT. SUVs were also corrected for tissue fraction (TF). The mean SUV in IPF patients was compared with that in 25 controls (patients with lymphoma in remission or suspected paraneoplastic syndrome with normal PET/CT appearances). Results: The pulmonary SUV (mean ± SD) uncorrected for TF in the controls was 0.48 ± 0.14 and 0.78 ± 0.24 taken from normal lung regions in IPF patients (p < 0.001). The TF-corrected mean SUV in the controls was 2.24 ± 0.29 and 3.24 ± 0.84 in IPF patients (p < 0.001). Conclusion: IPF patients have increased pulmonary uptake of 18F-FDG on PET in areas of lung with a normal morphological appearance on HRCT. This may have implications for determining disease mechanisms and treatment monitoring. © 2013 The Author(s)

Weakly supervised pre-training for brain tumor segmentation using principal axis measurements of tumor burden

Peer reviewe

Automated brain tumour detection and segmentation using superpixel-based extremely randomized trees in FLAIR MRI

PURPOSE: We propose a fully automated method for detection and segmentation of the abnormal tissue associated with brain tumour (tumour core and oedema) from Fluid- Attenuated Inversion Recovery (FLAIR) Magnetic Resonance Imaging (MRI). METHODS: The method is based on superpixel technique and classification of each superpixel. A number of novel image features including intensity-based, Gabor textons, fractal analysis and curvatures are calculated from each superpixel within the entire brain area in FLAIR MRI to ensure a robust classification. Extremely randomized trees (ERT) classifier is compared with support vector machine (SVM) to classify each superpixel into tumour and non-tumour. RESULTS: The proposed method is evaluated on two datasets: (1) Our own clinical dataset: 19 MRI FLAIR images of patients with gliomas of grade II to IV, and (2) BRATS 2012 dataset: 30 FLAIR images with 10 low-grade and 20 high-grade gliomas. The experimental results demonstrate the high detection and segmentation performance of the proposed method using ERT classifier. For our own cohort, the average detection sensitivity, balanced error rate and the Dice overlap measure for the segmented tumour against the ground truth are 89.48 %, 6 % and 0.91, respectively, while, for the BRATS dataset, the corresponding evaluation results are 88.09 %, 6 % and 0.88, respectively. CONCLUSIONS: This provides a close match to expert delineation across all grades of glioma, leading to a faster and more reproducible method of brain tumour detection and delineation to aid patient management

Effect of thermomechanical processing defects on fatigue and fracture behaviour of forged magnesium

The microstructural origins of premature fatigue failures were investigated on a variety of forged components manufactured from AZ80 and ZK60 magnesium, both at the test specimen level and the full-scale component level. Both stress and strain-controlled approaches were used to characterize the macroscopically defect-free forged material behaviour as well as with varying levels of defect intensities. The effect of thermomechanical processing defects due to forging of a industrially relevant full-scale component were characterized and quantified using a variety of techniques. The fracture initiation and early crack growth behaviour was deterministically traced back to a combination of various effects having both geometric and microstructural origins, including poor fusion during forging, entrainment of contaminants sub-surface, as well as other inhomogeneities in the thermomechanical processing history. &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; At the test specimen level, the fracture behaviour under both stress and strain controlled uniaxial loading was characterized for forged AZ80 Mg and a structure-property relationship was developed. The fracture surface morphology was quantitatively assessed revealing key features which characterize the presence and severity of intrinsic forging defects.&nbsp; A significant degradation in fatigue performance was observed as a result of forging defects accelerating fracture initiation and early crack growth, up to 6 times reduction in life (relative to the defect free material) under constant amplitude fully reversed fatigue loading. &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; At the full-scale component level, the fatigue and fracture behaviour under combined structural loading was also characterized for a number of ZK60 forged components with varying levels of intrinsic thermomechanical processing defects. A novel in-situ non-contact approach (utilizing Digital-Image Correlation) was used as a screening test to establish the presence of these intrinsic defects and reliably predict their effect on the final fracture behaviour in an accelerated manner compared to conventional methods