Debating standard language ideology in the classroom:Using the speak good English movement to raise awareness of Global Englishes

In this article, we describe and evaluate an innovative pedagogical task designed to raise awareness of Global Englishes and to challenge standard language ideology in an English language classroom. The task encouraged the learning and debate of the controversial Speak Good English Movement, which campaigns for Singaporeans to use a ‘standard’ form of English rather than the local variety, ‘Singlish’. The debate was introduced as a Global Englishes-inspired multi-lesson task at a Japanese university with 108 students in four classes. Data were collected in the form of written reflections, in which learners stated their own positions and beliefs. Data indicated that the majority sided against the Speak Good English Movement, viewing Singlish as a legitimate variety of English with important cultural attributes, which contributed to a national identity. Results showed that the debate achieved the aim of encouraging students to critically reflect on standard language ideology in both English and Japanese, their mother tongue. Overall, the activity was successful in raising awareness of the diversity of English, and encouraging critical reflection on the complexities surrounding standard language beliefs. This was seen to be essential given the dominance of the ‘native’ speaker episteme in Japanese language curricula

Climate Model Quality Assurance Through Consistency Testing and Error Source Identification

The Community Earth System Model (CESMTM) is a global climate model whose simulations have significant impact on social policy. The CESM is large and complex, consisting of about 1.5 million lines of code and several coupled component models. Quality assurance is necessary for the continued development and improvement of the CESM. To address this need, the CESM Ensemble Consistency Test (CESM-ECT) was developed as a statistical test for consistency between experimental outputs and an accepted ensemble. The CESM-ECT provides rapid feedback to model developers, scientists, and end users without expert knowledge of climate science. In this work, we investigate the properties and composition of the CESM-ECT ensemble, resulting in an improved test. We expand the CESM-ECT by creating an "ultra-fast" test at the ninth CESM time step and demonstrate that the test can detect statistical inconsistency in multiple CESM component models. Equipped with refined tests, we focus on locating sources of statistical inconsistency. Our approach uses graph analysis to find relevant segments of CESM code, and we propose an iterative instrumentation method for converging on the sources of inconsistency. We discuss the modification and performance optimization of a central atmospheric microphysics package with the assistance of our newly developed tools. We conclude by advancing a strategy to realize our iterative instrumentation process, which will identify specific code lines leading to statistical inconsistency. The framework created in this thesis will enable full-featured quality assurance for the CESM through consistency testing and error source identification.</p

Why Compact Tori For Fusion?

A compact torus (CT) has a toroidal magnetic and plasma geometry, but is contained within a simply-connected vacuum vessel such as a cylinder. Spheromaks and field-reversed configurations fall into this category. Compact tori are translatable and have a high engineering beta. The primary benefit of CTs for fusion is the absence of toroidal field and Ohmic Heating coils and the many problems brought on by them. Studying fusion-relevant plasma in simply-connected geometries affords the world fusion program both physics and technology opportunities not found in other configurations. This paper outlines the technology and physics opportunities of compact tori, and presents a cost model based on geometry for comparison with less compact configurations

Quality of life in lung cancer patients: does socioeconomic status matter?

BACKGROUND: As part of a prospective study on quality of life in newly diagnosed lung cancer patients an investigation was carried out to examine whether there were differences among patients' quality of life scores and their socioeconomic status. METHODS: Quality of life was measured at two points in time (baseline and three months after initial treatment) using three standard instruments; the Nottingham Health Profile (NHP), the European Organization for Research and Cancer Treatment Quality of Life Questionnaire (EORTC QLQ-C30) and its lung cancer supplement (QLQ-LC13). Socioeconomic status for each individual patient was derived using Carstairs and Morris Deprivation Category ranging from 1 (least deprived) to 7 (most deprived) on the basis of the postcode sector of their address. RESULTS: In all, 129 lung cancer patients entered into the study. Of these data for 82 patients were complete (at baseline and follow-up). 57% of patients were of lower socioeconomic status and they had more health problems, less functioning, and more symptoms as compared to affluent patients. Of these, physical mobility (P = 0.05), energy (P = 0.01), role functioning (P = 0.04), physical functioning (P = 0.03), and breathlessness (P = 0.02) were significant at baseline. However, at follow-up assessment there was no significant difference between patient groups nor did any consistent pattern emerge. CONCLUSION: At baseline assessment patients of lower socioeconomic status showed lower health related quality of life. Since there was no clear trend at follow-up assessment this suggests that patients from different socioeconomic status responded to treatment similarly. In general, the findings suggest that quality of life is not only the outcome of the disease and its treatment, but is also highly dependent on each patients' socioeconomic characteristics

Development of a compact air-regulated siphon for use in storm sewage overflows.

An air regulated siphon has been developed to operate as a storm water overflow. One of the main requirements has been that a siphon of compact design can accommodate high discharges for relatively small increases in upstream level thereby preventing the possibility of surcharges in the sewer upstream of the overflow.The s-shaped siphon was chosen for development as it has, by virtue of its natural shape, an efficient priming system. The downstream leg of the s-shaped siphon is returned beneath the crest so that a vertical wall of water formed shortly after first spill thereby effecting a seal which ensures priming.A sectional perspex model was used to determine the effects of inlet lip length, inlet lip elevation, tailwater level, siphon width, upstream channel width, vortices at inlet and revised outlet configurations.Results were compared using a dimensionless plot of the ratio of priming head and throat depth (hi/d) against co-efficient of discharge (CD). The curves obtained for all the differenct configurations are useful as design aids for the design of a compact air regulated siphon for use in storm sewage overflows

Carborane–β-cyclodextrin complexes as a supramolecular connector for bioactive surfaces

Supramolecular chemistry provides an attractive entry to generate dynamic and well-controlled bioactive surfaces. Novel host–guest systems are urgently needed to provide a broader affinity and applicability portfolio. A synthetic strategy to carborane–peptide bioconjugates was therefore developed to provide an entry to monovalent supramolecular functionalization of β-cyclodextrin coated surfaces. The β-cyclodextrin·carborane–cRGD surfaces are formed efficiently and with high affinity as demonstrated by IR-RAS, WCA, and QCM-D, compare favourable to existing bio-active host–guest surface assemblies, and display an efficient bioactivity, as illustrated by a strong functional effect of the supramolecular system on the cell adhesion and spreading properties. Cells seeded on the supramolecular surface displaying bioactive peptide epitopes exhibited a more elongated morphology, focal adhesions, and stronger cell adhesion compared to control surfaces. This highlights the macroscopic functionality of the novel supramolecular immobilization strategy

Improving temperature‐based predictions of the timing of flowering in cotton

Key management recommendations for cotton (Gossypium hirsutum L.) management require estimates of the timing of crop phenology. Most commonly growing day degree (DD) (thermal time) approaches are used. Currently, across many cotton production regions, there is no consistent approach to predicting first square and flower timing. Day degree approaches vary considerably, with base thresholds different (12.0–15.6 °C) with no consistency using an optimum temperature threshold (i.e., temperature where development ceases to increase). As cotton is grown in variable and changing climates, and cultivars change, there is a need to ensure the accuracy of this approach for predicting timing of flowering for assisting cotton management. In this study new functions to predict first square and first flower were developed and validated using data collected in multiple seasons and regions (Australia and the United States). Earlier controlled environment studies that monitored crop development were used to assess in more detail how temperatures were affecting early cotton development. New DD functions developed predicted first square and first flower better than the existing Australian and U.S. approaches. The best performing functions had base temperatures like those of existing U.S. functions (15.6 °C) and an optimum threshold temperature of 32.0 °C. New universal DD targets for first square (343 DD [°C]) and first flower (584 DD) were developed. Controlled environment studies supported this base temperature outcome; however, it was less clear that 32.0 °C was the optimum threshold temperature from these data. Precise predictions of cotton development will facilitate accurate growth stage assessments and hence better cotton management decisions

Chemotherapy versus supportive care in advanced non-small cell lung cancer: improved survival without detriment to quality of life

BACKGROUND: In 1995 a meta-analysis of randomised trials investigating the value of adding chemotherapy to primary treatment for non-small cell lung cancer (NSCLC) suggested a small survival benefit for cisplatin-based chemotherapy in each of the primary treatment settings. However, the metaanalysis included many small trials and trials with differing eligibility criteria and chemotherapy regimens. METHODS: The aim of the Big Lung Trial was to confirm the survival benefits seen in the meta-analysis and to assess quality of life and cost in the supportive care setting. A total of 725 patients were randomised to receive supportive care alone (n = 361) or supportive care plus cisplatin-based chemotherapy (n = 364). RESULTS: 65% of patients allocated chemotherapy (C) received all three cycles of treatment and a further 27% received one or two cycles. 74% of patients allocated no chemotherapy (NoC) received thoracic radiotherapy compared with 47% of the C group. Patients allocated C had a significantly better survival than those allocated NoC: HR 0.77 (95% CI 0.66 to 0.89, p = 0.0006), median survival 8.0 months for the C group v 5.7 months for the NoC group, a difference of 9 weeks. There were 19 (5%) treatment related deaths in the C group. There was no evidence that any subgroup benefited more or less fromchemotherapy. No significant differences were observed between the two groups in terms of the pre-defined primary and secondary quality of life end points, although large negative effects of chemotherapy were ruled out. The regimens used proved to be cost effective, the extra cost of chemotherapy being offset by longer survival. CONCLUSIONS: The survival benefit seen in this trial was entirely consistent with the NSCLC meta-analysis and subsequent similarly designed large trials. The information on quality of life and cost should enablepatients and their clinicians to make more informed treatment choices

#Bieber + #Blast = #BieberBlast: Early Prediction of Popular Hashtag Compounds

Compounding of natural language units is a very common phenomena. In this paper, we show, for the first time, that Twitter hashtags which, could be considered as correlates of such linguistic units, undergo compounding. We identify reasons for this compounding and propose a prediction model that can identify with 77.07% accuracy if a pair of hashtags compounding in the near future (i.e., 2 months after compounding) shall become popular. At longer times T = 6, 10 months the accuracies are 77.52% and 79.13% respectively. This technique has strong implications to trending hashtag recommendation since newly formed hashtag compounds can be recommended early, even before the compounding has taken place. Further, humans can predict compounds with an overall accuracy of only 48.7% (treated as baseline). Notably, while humans can discriminate the relatively easier cases, the automatic framework is successful in classifying the relatively harder cases.Comment: 14 pages, 4 figures, 9 tables, published in CSCW (Computer-Supported Cooperative Work and Social Computing) 2016. in Proceedings of 19th ACM conference on Computer-Supported Cooperative Work and Social Computing (CSCW 2016