22 resultados para WALK


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We report numerical results from a study of balance dynamics using a simple model of atmospheric motion that is designed to help address the question of why balance dynamics is so stable. The non-autonomous Hamiltonian model has a chaotic slow degree of freedom (representing vortical modes) coupled to one or two linear fast oscillators (representing inertia-gravity waves). The system is said to be balanced when the fast and slow degrees of freedom are separated. We find adiabatic invariants that drift slowly in time. This drift is consistent with a random-walk behaviour at a speed which qualitatively scales, even for modest time scale separations, as the upper bound given by Neishtadt’s and Nekhoroshev’s theorems. Moreover, a similar type of scaling is observed for solutions obtained using a singular perturbation (‘slaving’) technique in resonant cases where Nekhoroshev’s theorem does not apply. We present evidence that the smaller Lyapunov exponents of the system scale exponentially as well. The results suggest that the observed stability of nearly-slow motion is a consequence of the approximate adiabatic invariance of the fast motion.

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We consider the forecasting performance of two SETAR exchange rate models proposed by Kräger and Kugler [J. Int. Money Fin. 12 (1993) 195]. Assuming that the models are good approximations to the data generating process, we show that whether the non-linearities inherent in the data can be exploited to forecast better than a random walk depends on both how forecast accuracy is assessed and on the ‘state of nature’. Evaluation based on traditional measures, such as (root) mean squared forecast errors, may mask the superiority of the non-linear models. Generalized impulse response functions are also calculated as a means of portraying the asymmetric response to shocks implied by such models.

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This paper forecasts Daily Sterling exchange rate returns using various naive, linear and non-linear univariate time-series models. The accuracy of the forecasts is evaluated using mean squared error and sign prediction criteria. These show only a very modest improvement over forecasts generated by a random walk model. The Pesaran–Timmerman test and a comparison with forecasts generated artificially shows that even the best models have no evidence of market timing ability.

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The encoding of goal-oriented motion events varies across different languages. Speakers of languages without grammatical aspect (e.g., Swedish) tend to mention motion endpoints when describing events, e.g., “two nuns walk to a house,”, and attach importance to event endpoints when matching scenes from memory. Speakers of aspect languages (e.g., English), on the other hand, are more prone to direct attention to the ongoingness of motion events, which is reflected both in their event descriptions, e.g., “two nuns are walking.”, and in their non-verbal similarity judgements. This study examines to what extent native speakers of Swedish (n = 82) with English as a foreign language (FL) restructure their categorisation of goal-oriented motion as a function of their English proficiency and experience with the English language (e.g., exposure, learning). Seventeen monolingual native English speakers from the United Kingdom (UK) were engaged for comparison purposes. Data on motion event cognition were collected through a memory-based triads matching task, in which a target scene with an intermediate degree of endpoint orientation was matched with two alternative scenes with low and high degrees of endpoint orientation, respectively. Results showed that the preference among the Swedish speakers of L2 English to base their similarity judgements on ongoingness rather than event endpoints was correlated with their use of English in their everyday lives, such that those who often watched television in English approximated the ongoingness preference of the English native speakers. These findings suggest that event cognition patterns may be restructured through the exposure to FL audio-visual media. The results thus add to the emerging picture that learning a new language entails learning new ways of observing and reasoning about reality.

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Effective public policy to mitigate climate change footprints should build on data-driven analysis of firm-level strategies. This article’s conceptual approach augments the resource-based view (RBV) of the firm and identifies investments in four firm-level resource domains (Governance, Information management, Systems, and Technology [GISTe]) to develop capabilities in climate change impact mitigation. The authors denote the resulting framework as the GISTe model, which frames their analysis and public policy recommendations. This research uses the 2008 Carbon Disclosure Project (CDP) database, with high-quality information on firm-level climate change strategies for 552 companies from North America and Europe. In contrast to the widely accepted myth that European firms are performing better than North American ones, the authors find a different result. Many firms, whether European or North American, do not just “talk” about climate change impact mitigation, but actually do “walk the talk.” European firms appear to be better than their North American counterparts in “walk I,” denoting attention to governance, information management, and systems. But when it comes down to “walk II,” meaning actual Technology-related investments, North American firms’ performance is equal or superior to that of the European companies. The authors formulate public policy recommendations to accelerate firm-level, sector-level, and cluster-level implementation of climate change strategies.

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Unlike most other biological species, humans can use cultural innovations to occupy a range of environments, raising the intriguing question of whether human migrations move relatively independently of habitat or show preferences for familiar ones. The Bantu expansion that swept out of West Central Africa beginning ∼5,000 y ago is one of the most influential cultural events of its kind, eventually spreading over a vast geographical area a new way of life in which farming played an increasingly important role. We use a new dated phylogeny of ∼400 Bantu languages to show that migrating Bantu-speaking populations did not expand from their ancestral homeland in a “random walk” but, rather, followed emerging savannah corridors, with rainforest habitats repeatedly imposing temporal barriers to movement. When populations did move from savannah into rainforest, rates of migration were slowed, delaying the occupation of the rainforest by on average 300 y, compared with similar migratory movements exclusively within savannah or within rainforest by established rainforest populations. Despite unmatched abilities to produce innovations culturally, unfamiliar habitats significantly alter the route and pace of human dispersals.

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For the last few years, I have been working on an extensive digital model of ancient Rome as it appeared in the early 4th Century AD. This sort of visualisation lends itself to many applications in diverse fields: I am currently using it for research work into illumination and sightlines in the ancient city, have licensed it for broadcast in TV documentaries and publication in magazines, and am working with a computer games studio to turn it into an online game where players will be able to walk round the streets and buildings of the entire city (when not engaged in trading with or assassinating one another). Later this year I will be making a free online course, or MOOC, about the architecture of ancient Rome, which will largely be illustrated by this model.