157 resultados para Todd, Doug


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Aleks Sierz in his important survey of mid 1990s drama has identified the plays of Sarah Kane as exemplars of what he terms ‘In-Yer Face’ theatre. Sierz argues that Kane and her contemporaries such as Mark Ravenhill and Judy Upton represent a break with the ideological concerns of the previous generation of playwrights such as Doug Lucie and Stephen Lowe, whose work was shaped through recognizable political concerns, often in direct opposition to Thatcherism. In contrast Sarah Kane and her generation have frequently been seen as literary embodiments of ‘Thatcher’s Children’, whereby following the fall of the Berlin Wall and the inertia of the Major years, their drama eschews a recognizable political position, and seems more preoccupied with the plight of individuals cut adrift from society. In the case of Sarah Kane her frequently quoted statement, ‘I have no responsibility as a woman writer because I don’t believe there’s such a thing’, has compounded this perception. Moreover, its dogmatism also echoes the infamous comments attributed to Mrs Thatcher regarding the role of the individual to society. However, this article seeks to reassess Kane’s position as a woman writer and will argue that her drama is positioned somewhere between the female playwrights who emerged after 1979 such as Sarah Daniels, Timberlake Wertenbaker and Clare McIntyre, whose drama was distinguished by overtly feminist concerns, and its subsequent breakdown, best exemplified by the brief cultural moment associated with the newly elected Blair government known as ‘Cool Britannia’. Drawing on a variety of sources, including Kane’s unpublished monologues, written while she was a student just after Mrs Thatcher left office, this paper will argue that far from being an exponent of post-feminism, Kane’s drama frequently revisits and is influenced by the generation of dramatists whose work was forged out the sharp ideological positions that characterized the 1980s and a direct consequence of Thatcherism.

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This paper provides an update on research in the relatively new and fast-moving field of decadal climate prediction, and addresses the use of decadal climate predictions not only for potential users of such information but also for improving our understanding of processes in the climate system. External forcing influences the predictions throughout, but their contributions to predictive skill become dominant after most of the improved skill from initialization with observations vanishes after about six to nine years. Recent multi-model results suggest that there is relatively more decadal predictive skill in the North Atlantic, western Pacific, and Indian Oceans than in other regions of the world oceans. Aspects of decadal variability of SSTs, like the mid-1970s shift in the Pacific, the mid-1990s shift in the northern North Atlantic and western Pacific, and the early-2000s hiatus, are better represented in initialized hindcasts compared to uninitialized simulations. There is evidence of higher skill in initialized multi-model ensemble decadal hindcasts than in single model results, with multi-model initialized predictions for near term climate showing somewhat less global warming than uninitialized simulations. Some decadal hindcasts have shown statistically reliable predictions of surface temperature over various land and ocean regions for lead times of up to 6-9 years, but this needs to be investigated in a wider set of models. As in the early days of El Niño-Southern Oscillation (ENSO) prediction, improvements to models will reduce the need for bias adjustment, and increase the reliability, and thus usefulness, of decadal climate predictions in the future.

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A procedure is described in which patients are randomized between two experimental treatments and a control. At a series of interim analyses, each experimental treatment is compared with control. One of the experimental treatments might then be found sufficiently superior to the control for it to be declared the best treatment, and the trial stopped. Alternatively, experimental treatments might be eliminated from further consideration at any stage. It is shown how the procedure can be conducted while controlling overall error probabilities. Data concerning evaluation of different doses of riluzole in the treatment of motor neurone disease are used for illustration.

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During the 1990s there was a major change in the state of the world's oceans. In particular, the North Atlantic underwent a rapid warming, with sea surface temperatures (SSTs) in the subpolar gyre region increasing by 1°C in just a few years. Associated with the changes in SST patterns were changes in the surface climate, in particular, a tendency for warm and dry conditions over areas of North America in all seasons, and warm springs and wet summers over areas of Europe. Here, the extent to which a climate prediction system initialized using observations of the ocean state is able to capture the observed changes in seasonal mean surface climate is investigated. Rather than examining predictions of the mid-1990s North Atlantic warming event itself, this study compares hindcasts started before and after the warming, relative to hindcasts that do not assimilate information. It is demonstrated that the hindcasts capture many aspects of the observed changes in seasonal mean surface climate, especially in North, South, and Central America and in Europe. Furthermore, the prediction system retains skill beyond the first year. Finally, it is shown that, in addition to memory of Atlantic SSTs, successfully predicting Pacific SSTs was likely important for the hindcasts to predict surface climate over North America.

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Vicine and convicine are anti-nutritional compounds that accumulate in the cotyledons of faba beans. When humans consume beans with high levels of these compounds, it can cause a condition called favism in individuals harbouring a deficiency in the activity of their glucose-6-phosphate dehydrogenase. When faba beans are used in animal feeds, there can be effects on performance. These concerns have resulted in increasing interest within plant breeding in developing low vicine and convicine faba bean germplasm. In order to facilitate this objective, we developed a rapid and robust screening method for vicine and convicine, capable of distinguishing between faba beans that are either high (wild type) or low in vicine and convicine. In the absence of reliable commercial reference materials, we report an adaptation of a previously published method where a biochemical assay and spectral data were used to confirm the identity of our analytes, vicine and convicine. This method could be readily adopted in other facilities and open the way to the efficient exploitation of diverse germplasm in regions where faba beans play a significant role in human nutrition. We screened a collection of germplasm of interest to a collaborative plant breeding programme developing between the National Institute for Agricultural Botany in the UK and L'Institut Nationale d'Agronomie de Tunisie in Tunisia. We report the results obtained and discuss the prospects for developing molecular markers for the low vicine and convicine trait.

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In this paper we consider the structure of dynamically evolving networks modelling information and activity moving across a large set of vertices. We adopt the communicability concept that generalizes that of centrality which is defined for static networks. We define the primary network structure within the whole as comprising of the most influential vertices (both as senders and receivers of dynamically sequenced activity). We present a methodology based on successive vertex knockouts, up to a very small fraction of the whole primary network,that can characterize the nature of the primary network as being either relatively robust and lattice-like (with redundancies built in) or relatively fragile and tree-like (with sensitivities and few redundancies). We apply these ideas to the analysis of evolving networks derived from fMRI scans of resting human brains. We show that the estimation of performance parameters via the structure tests of the corresponding primary networks is subject to less variability than that observed across a very large population of such scans. Hence the differences within the population are significant.

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In June 2009 the Sarychev volcano located in the Kuril Islands to the northeast of Japan erupted explosively, injecting ash and an estimated 1.2 ± 0.2 Tg of sulfur dioxide into the upper troposphere and lower stratosphere, making it arguably one of the 10 largest stratospheric injections in the last 50 years. During the period immediately after the eruption, we show that the sulfur dioxide (SO2) cloud was clearly detected by retrievals developed for the Infrared Atmospheric Sounding Interferometer (IASI) satellite instrument and that the resultant stratospheric sulfate aerosol was detected by the Optical Spectrograph and Infrared Imaging System (OSIRIS) limb sounder and CALIPSO lidar. Additional surface‐based instrumentation allows assessment of the impact of the eruption on the stratospheric aerosol optical depth. We use a nudged version of the HadGEM2 climate model to investigate how well this state‐of‐the‐science climate model can replicate the distributions of SO2 and sulfate aerosol. The model simulations and OSIRIS measurements suggest that in the Northern Hemisphere the stratospheric aerosol optical depth was enhanced by around a factor of 3 (0.01 at 550 nm), with resultant impacts upon the radiation budget. The simulations indicate that, in the Northern Hemisphere for July 2009, the magnitude of the mean radiative impact from the volcanic aerosols is more than 60% of the direct radiative forcing of all anthropogenic aerosols put together. While the cooling induced by the eruption will likely not be detectable in the observational record, the combination of modeling and measurements would provide an ideal framework for simulating future larger volcanic eruptions.

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Useful probabilistic climate forecasts on decadal timescales should be reliable (i.e. forecast probabilities match the observed relative frequencies) but this is seldom examined. This paper assesses a necessary condition for reliability, that the ratio of ensemble spread to forecast error being close to one, for seasonal to decadal sea surface temperature retrospective forecasts from the Met Office Decadal Prediction System (DePreSys). Factors which may affect reliability are diagnosed by comparing this spread-error ratio for an initial condition ensemble and two perturbed physics ensembles for initialized and uninitialized predictions. At lead times less than 2 years, the initialized ensembles tend to be under-dispersed, and hence produce overconfident and hence unreliable forecasts. For longer lead times, all three ensembles are predominantly over-dispersed. Such over-dispersion is primarily related to excessive inter-annual variability in the climate model. These findings highlight the need to carefully evaluate simulated variability in seasonal and decadal prediction systems.Useful probabilistic climate forecasts on decadal timescales should be reliable (i.e. forecast probabilities match the observed relative frequencies) but this is seldom examined. This paper assesses a necessary condition for reliability, that the ratio of ensemble spread to forecast error being close to one, for seasonal to decadal sea surface temperature retrospective forecasts from the Met Office Decadal Prediction System (DePreSys). Factors which may affect reliability are diagnosed by comparing this spread-error ratio for an initial condition ensemble and two perturbed physics ensembles for initialized and uninitialized predictions. At lead times less than 2 years, the initialized ensembles tend to be under-dispersed, and hence produce overconfident and hence unreliable forecasts. For longer lead times, all three ensembles are predominantly over-dispersed. Such over-dispersion is primarily related to excessive inter-annual variability in the climate model. These findings highlight the need to carefully evaluate simulated variability in seasonal and decadal prediction systems.

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The authors examined avoidance personal goals as concurrent (Study 1) and longitudinal (Study 2) predictors of multiple aspects of well-being in the United States and Japan. In both studies, participants adopted more avoidance personal goals in Japan relative to the United States. Both studies also demonstrated that avoidance personal goals were significant negative predictors of the most relevant aspects of well-being in each culture. Specifically, avoidance personal goals were negative predictors of intrapersonal and eudaimonic well-being in the United States and were negative predictors of interpersonal and eudaimonic well-being in Japan. The findings clarify and extend puzzling findings from prior empirical work in this area, and raise provocative possibilities about the nature of avoidance goal pursuit.

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We conducted 2 longitudinal meditational studies to test an integrative model of goals, stress and coping, and well‐being. Study 1 documented avoidance personal goals as an antecedent of life stressors and life stressors as a partial mediator of the relation between avoidance goals and longitudinal change in subjective well‐being (SWB). Study 2 fully replicated Study 1 and likewise validated avoidance goals as an antecedent of avoidance coping and avoidance coping as a partial mediator of the relation between avoidance goals and longitudinal change in SWB. It also showed that avoidance coping partially mediates the link between avoidance goals and life stressors and validated a sequential meditational model involving both avoidance coping and life stressors. The aforementioned results held when controlling for social desirability, basic traits, and general motivational dispositions. The findings are discussed with regard to the integration of various strands of research on self‐regulation. (PsycINFO Database Record (c) 2012 APA, all rights reserved)(journal abstract)

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Useful probabilistic climate forecasts on decadal timescales should be reliable (i.e. forecast probabilities match the observed relative frequencies) but this is seldom examined. This paper assesses a necessary condition for reliability, that the ratio of ensemble spread to forecast error being close to one, for seasonal to decadal sea surface temperature retrospective forecasts from the Met Office Decadal Prediction System (DePreSys). Factors which may affect reliability are diagnosed by comparing this spread-error ratio for an initial condition ensemble and two perturbed physics ensembles for initialized and uninitialized predictions. At lead times less than 2 years, the initialized ensembles tend to be under-dispersed, and hence produce overconfident and hence unreliable forecasts. For longer lead times, all three ensembles are predominantly over-dispersed. Such over-dispersion is primarily related to excessive inter-annual variability in the climate model. These findings highlight the need to carefully evaluate simulated variability in seasonal and decadal prediction systems.Useful probabilistic climate forecasts on decadal timescales should be reliable (i.e. forecast probabilities match the observed relative frequencies) but this is seldom examined. This paper assesses a necessary condition for reliability, that the ratio of ensemble spread to forecast error being close to one, for seasonal to decadal sea surface temperature retrospective forecasts from the Met Office Decadal Prediction System (DePreSys). Factors which may affect reliability are diagnosed by comparing this spread-error ratio for an initial condition ensemble and two perturbed physics ensembles for initialized and uninitialized predictions. At lead times less than 2 years, the initialized ensembles tend to be under-dispersed, and hence produce overconfident and hence unreliable forecasts. For longer lead times, all three ensembles are predominantly over-dispersed. Such over-dispersion is primarily related to excessive inter-annual variability in the climate model. These findings highlight the need to carefully evaluate simulated variability in seasonal and decadal prediction systems.

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In the 1960s North Atlantic sea surface temperatures (SST) cooled rapidly. The magnitude of the cooling was largest in the North Atlantic subpolar gyre (SPG), and was coincident with a rapid freshening of the SPG. Here we analyze hindcasts of the 1960s North Atlantic cooling made with the UK Met Office’s decadal prediction system (DePreSys), which is initialised using observations. It is shown that DePreSys captures—with a lead time of several years—the observed cooling and freshening of the North Atlantic SPG. DePreSys also captures changes in SST over the wider North Atlantic and surface climate impacts over the wider region, such as changes in atmospheric circulation in winter and sea ice extent. We show that initialisation of an anomalously weak Atlantic Meridional Overturning Circulation (AMOC), and hence weak northward heat transport, is crucial for DePreSys to predict the magnitude of the observed cooling. Such an anomalously weak AMOC is not captured when ocean observations are not assimilated (i.e. it is not a forced response in this model). The freshening of the SPG is also dominated by ocean salt transport changes in DePreSys; in particular, the simulation of advective freshwater anomalies analogous to the Great Salinity Anomaly were key. Therefore, DePreSys suggests that ocean dynamics played an important role in the cooling of the North Atlantic in the 1960s, and that this event was predictable.