266 research outputs found

    Assumptions behind grammatical approaches to code-switching: when the blueprint is a red herring

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    Many of the so-called ‘grammars’ of code-switching are based on various underlying assumptions, e.g. that informal speech can be adequately or appropriately described in terms of ‘‘grammar’’; that deep, rather than surface, structures are involved in code-switching; that one ‘language’ is the ‘base’ or ‘matrix’; and that constraints derived from existing data are universal and predictive. We question these assumptions on several grounds. First, ‘grammar’ is arguably distinct from the processes driving speech production. Second, the role of grammar is mediated by the variable, poly-idiolectal repertoires of bilingual speakers. Third, in many instances of CS the notion of a ‘base’ system is either irrelevant, or fails to explain the facts. Fourth, sociolinguistic factors frequently override ‘grammatical’ factors, as evidence from the same language pairs in different settings has shown. No principles proposed to date account for all the facts, and it seems unlikely that ‘grammar’, as conventionally conceived, can provide definitive answers. We conclude that rather than seeking universal, predictive grammatical rules, research on CS should focus on the variability of bilingual grammars

    In Support of the Matrix Language Frame Model: Evidence from Igbo-English Intrasentential Codeswitching

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    This paper explores the morphosyntactic features of mixed nominal expressions in a sample of empirical Igbo-English intrasentential codeswitching data (i.e. codeswitching within a bilingual clause) in terms of the Matrix Language Frame (MLF) model. Since both Igbo and English differ in the relative order of head and complement within the nominal argument phrase, the analysed data seem appropriate for testing the veracity of the principal assumption underpinning the MLF model: the notion that the two languages (in our case Igbo and English) participating in codeswitching do not both contribute equally to the morphosyntactic frame of a mixed constituent. As it turns out, the findings provide both empirical and quantitative support for the basic theoretical view that there is a Matrix Language (ML) versus Embedded Language (EL) hierarchy in classic codeswitching as predicted by the MLF model because both Igbo and English do not simultaneously satisfy the roles of the ML in Igbo-English codeswitching

    Mammography Facility Characteristics Associated With Interpretive Accuracy of Screening Mammography

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    BackgroundAlthough interpretive performance varies substantially among radiologists, such variation has not been examined among mammography facilities. Understanding sources of facility variation could become a foundation for improving interpretive performance.MethodsIn this cross-sectional study conducted between 1996 and 2002, we surveyed 53 facilities to evaluate associations between facility structure, interpretive process characteristics, and interpretive performance of screening mammography (ie, sensitivity, specificity, positive predictive value [PPV1], and the likelihood of cancer among women who were referred for biopsy [PPV2]). Measures of interpretive performance were ascertained prospectively from mammography interpretations and cancer data collected by the Breast Cancer Surveillance Consortium. Logistic regression and receiver operating characteristic (ROC) curve analyses estimated the association between facility characteristics and mammography interpretive performance or accuracy (area under the ROC curve [AUC]). All P values were two-sided.ResultsOf the 53 eligible facilities, data on 44 could be analyzed. These 44 facilities accounted for 484 463 screening mammograms performed on 237 669 women, of whom 2686 were diagnosed with breast cancer during follow-up. Among the 44 facilities, mean sensitivity was 79.6% (95% confidence interval [CI] = 74.3% to 84.9%), mean specificity was 90.2% (95% CI = 88.3% to 92.0%), mean PPV1 was 4.1% (95% CI = 3.5% to 4.7%), and mean PPV2 was 38.8% (95% CI = 32.6% to 45.0%). The facilities varied statistically significantly in specificity (P < .001), PPV1 (P < .001), and PPV2 (P = .002) but not in sensitivity (P = .99). AUC was higher among facilities that offered screening mammograms alone vs those that offered screening and diagnostic mammograms (0.943 vs 0.911, P = .006), had a breast imaging specialist interpreting mammograms vs not (0.932 vs 0.905, P = .004), did not perform double reading vs independent double reading vs consensus double reading (0.925 vs 0.915 vs 0.887, P = .034), or conducted audit reviews two or more times per year vs annually vs at an unknown frequency (0.929 vs 0.904 vs 0.900, P = .018).ConclusionMammography interpretive performance varies statistically significantly by facility

    Microwave Imaging for Neoadjuvant Chemotherapy Monitoring: Initial Clinical Experience

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    Introduction: Microwave tomography recovers images of tissue dielectric properties, which appear to be specific for breast cancer, with low-cost technology that does not present an exposure risk, suggesting the modality may be a good candidate for monitoring neoadjuvant chemotherapy. Methods: Eight patients undergoing neoadjuvant chemotherapy for locally advanced breast cancer were imaged longitudinally five to eight times during the course of treatment. At the start of therapy, regions of interest (ROIs) were identified from contrast-enhanced magnetic resonance imaging studies. During subsequent microwave examinations, subjects were positioned with their breasts pendant in a coupling fluid and surrounded by an immersed antenna array. Microwave property values were extracted from the ROIs through an automated procedure and statistical analyses were performed to assess short term (30 days) and longer term (four to six months) dielectric property changes. Results: Two patient cases (one complete and one partial response) are presented in detail and demonstrate changes in microwave properties commensurate with the degree of treatment response observed pathologically. Normalized mean conductivity in ROIs from patients with complete pathological responses was significantly different from that of partial responders (P value = 0.004). In addition, the normalized conductivity measure also correlated well with complete pathological response at 30 days (P value = 0.002). Conclusions: These preliminary findings suggest that both early and late conductivity property changes correlate well with overall treatment response to neoadjuvant therapy in locally advanced breast cancer. This result is consistent with earlier clinical outcomes that lesion conductivity is specific to differentiating breast cancer from benign lesions and normal tissue

    Neutral evolution: A null model for language dynamics

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    We review the task of aligning simple models for language dynamics with relevant empirical data, motivated by the fact that this is rarely attempted in practice despite an abundance of abstract models. We propose that one way to meet this challenge is through the careful construction of null models. We argue in particular that rejection of a null model must have important consequences for theories about language dynamics if modelling is truly to be worthwhile. Our main claim is that the stochastic process of neutral evolution (also known as genetic drift or random copying) is a viable null model for language dynamics. We survey empirical evidence in favour and against neutral evolution as a mechanism behind historical language changes, highlighting the theoretical implications in each case.Comment: 20 pages, 2 figures. To appear in a special issue of ACS - Advances in Complex Systems on language dynamic

    Image reconstruction techniques; (170.3880) Medical and biological imaging

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    Abstract: Diffuse optical tomography (DOT) reconstructs the images of internal optical parameter distribution using noninvasive boundary measurements. The image reconstruction procedure is known to be an ill-posed problem. In order to solve such a problem, a regularization technique is needed to constrain the solution space. In this study, a projection-error-based adaptive regularization (PAR) technique is proposed to improve the reconstructed image quality. Simulations are performed using a diffusion approximation model and the simulated results demonstrate that the PAR technique can improve reconstruction precision of object more effectively. The method is demonstrated to have low sensitivity to noise at various noise levels. Moreover, with the PAR method, the detectability of an object located both at the center and near the peripheral regions has been increased largely
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