842 resultados para Johnson, Will
Resumo:
A large body of research has focused on the observation that second language (L2) learners are limited in their production of temporal and aspectual forms. For example, in L2 English, it has been shown learners use progressive marking with activity verbs and only rarely extend the form to telic verb phrases such as accomplishments or achievements (Bardovi-Harlig and Reynolds, 1995; Bardovi-Harlig, 2000; Robison, 1995). Shirai and Andersen (1995) proposed that activities represent the prototype for the category of progressive aspect and learners generally acquire the prototype first. However, very little research has focused explicitly on advanced learners to see if they eventually extend beyond the prototype. In addition, properties of the native language have not systematically been taken into account. Achievements such as "die" are especially interesting in that they interact differently with markers of progressive aspect across languages. The present study investigated the acquisition of progressive achievements in English by native speakers of Chinese and Korean in order to examine whether there is evidence of universal difficulty, as would be predicted by the prototype account, or whether similarity between the L1 and L2 (as in the case of English and Korean) can facilitate acquisition, as would be predicted by transfer. Our results suggest that the properties of the native language play an important role, supporting the transfer account. However, neither L1 group performs at the level of native speakers. We argue that the acquisition of aspect is influenced by both the properties of the native language and the semantic and pragmatic complexity of the target computation.
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Mankind is facing an unprecedented health challenge in the current pandemic of obesity and diabetes. We propose that this is the inevitable (and predictable) consequence of the evolution of intelligence, which itself could be an expression of life being an information system driven by entropy. Because of its ability to make life more adaptable and robust, intelligence evolved as an efficient adaptive response to the stresses arising from an ever-changing environment. These adaptive responses are encapsulated by the epiphenomena of “hormesis”, a phenomenon we believe to be central to the evolution of intelligence and essential for the maintenance of optimal physiological function and health. Thus, as intelligence evolved, it would eventually reach a cognitive level with the ability to control its environment through technology and have the ability remove all stressors. In effect, it would act to remove the very hormetic factors that had driven its evolution. Mankind may have reached this point, creating an environmental utopia that has reduced the very stimuli necessary for optimal health and the evolution of intelligence – “the intelligence paradox”. One of the hallmarks of this paradox is of course the rising incidence in obesity, diabetes and the metabolic syndrome. This leads to the conclusion that wherever life evolves, here on earth or in another part of the galaxy, the “intelligence paradox’” would be the inevitable side-effect of the evolution of intelligence. ET may not need to just “phone home” but may also need to “phone the local gym”. This suggests another possible reason to explain Fermi’s paradox; Enrico Fermi, the famous physicist, suggested in the 1950s that if extra-terrestrial intelligence was so prevalent, which was a common belief at the time, then where was it? Our suggestion is that if advanced life has got going elsewhere in our galaxy, it can’t afford to explore the galaxy because it has to pay its healthcare costs.
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Arctic sea ice thickness is thought to be an important predictor of Arctic sea ice extent. However, coupled seasonal forecast systems do not generally use sea ice thickness observations in their initialization and are therefore missing a potentially important source of additional skill. To investigate how large this source is, a set of ensemble potential predictability experiments with a global climate model, initialized with and without knowledge of the sea ice thickness initial state, have been run. These experiments show that accurate knowledge of the sea ice thickness field is crucially important for sea ice concentration and extent forecasts up to 8 months ahead, especially in summer. Perturbing sea ice thickness also has a significant impact on the forecast error in Arctic 2 m temperature a few months ahead. These results suggest that advancing capabilities to observe and assimilate sea ice thickness into coupled forecast systems could significantly increase skill.
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Many of the next generation of global climate models will include aerosol schemes which explicitly simulate the microphysical processes that determine the particle size distribution. These models enable aerosol optical properties and cloud condensation nuclei (CCN) concentrations to be determined by fundamental aerosol processes, which should lead to a more physically based simulation of aerosol direct and indirect radiative forcings. This study examines the global variation in particle size distribution simulated by 12 global aerosol microphysics models to quantify model diversity and to identify any common biases against observations. Evaluation against size distribution measurements from a new European network of aerosol supersites shows that the mean model agrees quite well with the observations at many sites on the annual mean, but there are some seasonal biases common to many sites. In particular, at many of these European sites, the accumulation mode number concentration is biased low during winter and Aitken mode concentrations tend to be overestimated in winter and underestimated in summer. At high northern latitudes, the models strongly underpredict Aitken and accumulation particle concentrations compared to the measurements, consistent with previous studies that have highlighted the poor performance of global aerosol models in the Arctic. In the marine boundary layer, the models capture the observed meridional variation in the size distribution, which is dominated by the Aitken mode at high latitudes, with an increasing concentration of accumulation particles with decreasing latitude. Considering vertical profiles, the models reproduce the observed peak in total particle concentrations in the upper troposphere due to new particle formation, although modelled peak concentrations tend to be biased high over Europe. Overall, the multi-model-mean data set simulates the global variation of the particle size distribution with a good degree of skill, suggesting that most of the individual global aerosol microphysics models are performing well, although the large model diversity indicates that some models are in poor agreement with the observations. Further work is required to better constrain size-resolved primary and secondary particle number sources, and an improved understanding of nucleation and growth (e.g. the role of nitrate and secondary organics) will improve the fidelity of simulated particle size distributions.
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A note on Ashbery's metaphorical and intertextual practice.
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Growing criticism of Chinese engagement in Africa centres on the risk to African development posed by China's aggressive export policies and the threat to the Washington Consensus and African governance posed by China's 'non-interference' approach to engagement. This article challenges both these assumptions. The growth of Chinese trade has a wide range of impacts, depending on the sector in question, and the current terms of trade Washington extends to Africa under the auspices of the AGOA do not result in uniformly beneficial effects. With regard to African governance, it is argued that the 'Washington Consensus' has been based on competing and often muddled perceptions of US national interest. This fact tempers the regret felt at Washington's loss of influence over the good governance agenda. Evidence is provided to show that China can work within properly regulated countries and industries, if the African governments in question can provide fair, efficient and transparent environments in which to operate.
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Changes in stratospheric chemistry and circulation associated with ozone recovery may affect the patterns of future climate change.
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Individual-based models (IBMs) can simulate the actions of individual animals as they interact with one another and the landscape in which they live. When used in spatially-explicit landscapes IBMs can show how populations change over time in response to management actions. For instance, IBMs are being used to design strategies of conservation and of the exploitation of fisheries, and for assessing the effects on populations of major construction projects and of novel agricultural chemicals. In such real world contexts, it becomes especially important to build IBMs in a principled fashion, and to approach calibration and evaluation systematically. We argue that insights from physiological and behavioural ecology offer a recipe for building realistic models, and that Approximate Bayesian Computation (ABC) is a promising technique for the calibration and evaluation of IBMs. IBMs are constructed primarily from knowledge about individuals. In ecological applications the relevant knowledge is found in physiological and behavioural ecology, and we approach these from an evolutionary perspective by taking into account how physiological and behavioural processes contribute to life histories, and how those life histories evolve. Evolutionary life history theory shows that, other things being equal, organisms should grow to sexual maturity as fast as possible, and then reproduce as fast as possible, while minimising per capita death rate. Physiological and behavioural ecology are largely built on these principles together with the laws of conservation of matter and energy. To complete construction of an IBM information is also needed on the effects of competitors, conspecifics and food scarcity; the maximum rates of ingestion, growth and reproduction, and life-history parameters. Using this knowledge about physiological and behavioural processes provides a principled way to build IBMs, but model parameters vary between species and are often difficult to measure. A common solution is to manually compare model outputs with observations from real landscapes and so to obtain parameters which produce acceptable fits of model to data. However, this procedure can be convoluted and lead to over-calibrated and thus inflexible models. Many formal statistical techniques are unsuitable for use with IBMs, but we argue that ABC offers a potential way forward. It can be used to calibrate and compare complex stochastic models and to assess the uncertainty in their predictions. We describe methods used to implement ABC in an accessible way and illustrate them with examples and discussion of recent studies. Although much progress has been made, theoretical issues remain, and some of these are outlined and discussed.
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Brazil’s recent cinematic sensation, O som ao redor/Neighboring Sounds (Kleber Mendonça Filho, 2012), displays an effective integration of form and content, as exemplified by its vertical figuration that crystallizes the devastating effects of property development and global capitalism. This chapter will attempt to unravel a two-way drive within this vertical motif: a movement off the ground, resulting in global cosmopolitanism; and another into the ground, in search of the social history and film history at its base. As I hope to demonstrate, despite the characters’ late postmodernist disconnect from local context and history, O som ao redor offers a perspicacious insight into regional and national history that contributes an original and exciting addition to Brazilian and world cinema.
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Regional information on climate change is urgently needed but often deemed unreliable. To achieve credible regional climate projections, it is essential to understand underlying physical processes, reduce model biases and evaluate their impact on projections, and adequately account for internal variability. In the tropics, where atmospheric internal variability is small compared with the forced change, advancing our understanding of the coupling between long-term changes in upper-ocean temperature and the atmospheric circulation will help most to narrow the uncertainty. In the extratropics, relatively large internal variability introduces substantial uncertainty, while exacerbating risks associated with extreme events. Large ensemble simulations are essential to estimate the probabilistic distribution of climate change on regional scales. Regional models inherit atmospheric circulation uncertainty from global models and do not automatically solve the problem of regional climate change. We conclude that the current priority is to understand and reduce uncertainties on scales greater than 100 km to aid assessments at finer scales.