2,577 research outputs found

    Derivatives at Agricultural Banks

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    Using data between 1995 and 2010, we find that agricultural banks are benefiting from the derivatives activities by reducing total risk without hurting their profit. In nonagricultural banks, both profitability and total risk are adversely affected, possibly due to speculative derivatives positions.Agricultural Banks, Financial Derivatives, Profitability, Risk Management, Agricultural Finance, Risk and Uncertainty,

    A Study of Chinese-English Code-switching in Chinese Sports News Reports

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    This paper reports a study of Chinese-English code-switching in Chinese sports news reports with an aim to provide a better understanding of the linguistic features of Chinese-English code-switching. Based on the data collected from Titan Sports–the most influential comprehensive sports newspaper in China, the study finds that the switched constituents vary from singly occurring letters and lexemes to embedded phrases and sentences, with each carrying its own features. Adopting Myers-Scotton’s Markedness Model to the discussion of code-switching occurrences, this study relates the linguistic features observed to the sense of markedness which can account for the features found in the study. Key words: Chinese-English code-switching; Matrix language; Embedded constituent; Markedness Resumé: Cet article présente une étude sur l'alternance de codes du chinois en anglais dans les nouvelles sportives chinoises dans le but de fournir une meilleure compréhension des caractéristiques linguistiques de l'alternance de codes du chinois en anglais. Basée sur des données recueillies auprès de Titan Sports, le plus influent journal de sport en Chine, l'étude constate que les constituants alternés varient des lettres et des lexèmes qui apparaissent seul à des phrases intégrées, et que chacun porte ses propres caractéristiques. En adoptant le modèle de caractère marqué de Myers-Scotton, cette étude relie les caractéristiques linguistiques observés au sens du marquage, qui peut expliquer les caractéristiques trouvées dans l'étude.Mots-clés: alternance de codes du chinois en anglais; matrice de langue; constituants intégrés; caractère marqu

    Reconstruction of three-dimensional turbulent flow structures using surface measurements for free-surface flows based on a convolutional neural network

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    A model based on a convolutional neural network (CNN) is designed to reconstruct the three-dimensional turbulent flows beneath a free surface using surface measurements, including the surface elevation and surface velocity. Trained on datasets obtained from the direct numerical simulation (DNS) of turbulent open-channel flows with a deformable free surface, the proposed model can accurately reconstruct the near-surface flow field and capture the characteristic large-scale flow structures away from the surface. The reconstruction performance of the model, measured by metrics such as the normalised mean squared reconstruction errors and scale-specific errors, is considerably better than that of the traditional linear stochastic estimation (LSE) method. We further analyse the saliency maps of the CNN model and the kernels of the LSE model and obtain insights into how the two models utilise surface features to reconstruct subsurface flows. The importance of different surface variables is analysed based on the saliency map of the CNN, which reveals knowledge about the surface-subsurface relations. The CNN is also shown to have a good generalization capability with respect to the Froude number if a model trained for a flow with a high Froude number is applied to predict flows with lower Froude numbers. The results presented in this work indicate that the CNN is effective regarding the detection of subsurface flow structures and by interpreting the surface-subsurface relations underlying the reconstruction model, the CNN can be a promising tool for assisting with the physical understanding of free-surface turbulence

    Crop Production Simulation and Analysis of Climate Scenarios Based on the APSIM Model for the Long Term Run of the Western Loess Plateau

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    The APSIM model is an effective tool for making decisions on agricultural management. The model can simulate the biophysical process in farming systems, particularly economic and ecological features of the systems under climatic risk (Keating et al. 1998). The APSIM model has previously been used in the Loess Plateau (Tan, 2007; Chen et al. 2008). Based on climate data from the Loess Plateau from 1961-2010, we simulated three commonly grown crops, wheat, maize and lucerne. Additionally, by applying three climate change scenarios, we attempted to determine the production risk in the future, and gain an understanding of the impact of climate change on crop yield in the western Loess Plateau
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