Testing the Random Walk Hypothesis: Power versus Frequency of Observation

Power functions of tests of the random walk hypothesis versus stationary first order autoregressive alternatives are tabulated for samples of fixed span but various frequencies of observation.

Pouvons-nous réduire la dose d’azote après un retour de prairie?

Affiche présentée dans le cadre du Colloque de l'ARC, «Des racines et des ailes pour la recherche collégiale», dans le cadre du 85e Congrès de l’Acfas, Université McGill, Montréal, les 8 et 9 mai 2017.Au Québec, les émissions de gaz à effet de serre (GES) d’origine agricole représentent près de 8 % des émissions totales. Environ 40 % des émissions agricoles découle de l’usage des engrais minéraux et des engrais de ferme. Tout apport excédentaire d’engrais azoté dans les cultures se traduit par des émissions supplémentaires d’oxyde nitreux (N2O), un puissant gaz à effet de serre qui contribue aux émissions de GES. Plusieurs études ont démontré que la culture de maïs n’avait pas besoin d’apports importants d’azote en postlevée, après des retours de prairie. En collaboration avec des producteurs agricoles, 16 sites d’essais de fertilisation azotée ont été implantés sur des retours de prairie ayant reçu des engrais de ferme. Les traitements consistaient à apporter 4 doses d’azote minéral (0, 40, 80 et 120 kg N/ha). La teneur en nitrates du sol ainsi que les rendements à la récolte ont été évalués. La teneur en nitrates a confirmé l’effet significatif de la prairie et des engrais de ferme sur la teneur en azote disponible pour le maïs. L’apport d’azote minéral n’a pas eu d’effet significatif sur les rendements en azote, à l’exception d’un site. Le maïs cultivé sur un retour de prairie ne nécessite pas un ajout d’engrais minéral. Éliminer l’apport d’azote réduit tant les émissions de GES que les dépenses en engrais pour les producteurs

Machine Translation and Automated Analysis of Cuneiform Languages (MTAAC)

Project Abstract: Ancient Mesopotamia, birthplace of writing, has produced vast numbers of cuneiform tablets that only a handful of highly specialized scholars are able to read. The task of studying them is so labor intensive that the vast majority have not yet been translated, with the result that their contents are not accessible either to historians in other fields or to the wider public. This project will develop and apply new computerised methods to translate and analyse the contents of some 67,000 highly standardised administrative documents from southern Mesopotamia from the 21st century BC. By automating these basic but labor-intensive processes, we will free up scholars’ time. The tools that we will develop, combining machine learning, statistical and neural machine translation technologies, may then be applied to other ancient languages. Similarly, the translations themselves, and the historical, social and economic data extracted from them, will be made publicly available on the web

Testing the Random Walk Hypothesis: Power versus Frequency of Observation

Power functions of tests of the random walk hypothesis versus stationary first order autoregressive alternatives are tabulated for samples of fixed span but various frequencies of observation. For a t -test and normalized test, power is found to depend, for a substantial range of parameter values, more on the span of the data in time than on the number of observations. For a runs test, power rapidly declines as the number of observations is increased beyond a certain point

Pyrogenic iron: The missing link to high iron solubility in aerosols

Atmospheric deposition is a source of potentially bioavailable iron (Fe) and thus can partially control biological productivity in large parts of the ocean. However, the explanation of observed high aerosol Fe solubility compared to that in soil particles is still controversial, as several hypotheses have been proposed to explain this observation. Here, a statistical analysis of aerosol Fe solubility estimated from four models and observations compiled from multiple field campaigns suggests that pyrogenic aerosols are the main sources of aerosols with high Fe solubility at low concentration. Additionally, we find that field data over the Southern Ocean display a much wider range in aerosol Fe solubility compared to the models, which indicate an underestimation of labile Fe concentrations by a factor of 15. These findings suggest that pyrogenic Fe-containing aerosols are important sources of atmospheric bioavailable Fe to the open ocean and crucial for predicting anthropogenic perturbations to marine productivity

Testing the Random Walk Hypothesis: Power Versus Frequency of Observation

Power functions of tests of the random walk hypothesis versus stationary first order autoregressive alternatives are tabulated for samples of fixed span but various frequencies of observation. For a t-test and normalized test, power is found to depend, for a substantial range of parameter values, more on the span of the data in time than on the number of observations. For a runs test, power rapidly declines as the number of observations is increased beyond a certain point.Random walk, unit roots, power function, efficient markets hypothesis