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Akira Shimojuku Asmaa Boujibar Daisuke Yamazaki Takashi Yoshino Naotaka Tomioka Junshan Xu 《Physics and Chemistry of Minerals》2014,41(7):555-567
The growth rate of ringwoodite reaction rims between MgSiO3 perovskite and periclase was investigated at 22.5 GPa and 1,800 °C for 1–24 h using the Kawai-type high-pressure apparatus. The reaction was likely to proceed by a diffusion-controlled mechanism in which the dominant diffusion mechanism was grain-boundary diffusion. The reaction constant (the width of the ringwoodite reaction rim squared divided by time) determined from these experiments was between 1.3 × 10?15 and 5.6 × 10?15 m2/s. A Pt inert marker experiment indicated that the MgO component migrated faster than the SiO2 component in ringwoodite. Thus, either Mg or O having the slower diffusion rate controlled the reaction. Because previous diffusion studies have shown that diffusion rates of O are slower than those of Mg, O would be a rate-controlling element for ringwoodite formation from MgSiO3 perovskite and periclase. The growth rate appeared to be too fast to explain the observed topographic rise (~10 km) inside mantle plumes at the 660-km discontinuity. 相似文献
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ABSTRACTThis paper presents a neural network model capable of catchment-wide simultaneous prediction of river stages at multiple gauging stations. Thirteen meteorological parameters are considered in the input, which includes rainfall, temperature, mean relative humidity and evaporation. The NARX model is trained with a representative set of hourly data, with optimal time delay for both the input and output. The network trained using 120-day data is able to produce simulations that are in excellent agreement with field observations. We show that for application with one-step-ahead predictions, the loss in network performance is marginal. Inclusion of additional tidal observations does not improve predictions, suggesting that the river stage stations under consideration are not sensitive to tidal backwater effects despite the claim commonly made.
EDITOR D. Koutsoyiannis ASSOCIATE EDITOR F. Pappenberger 相似文献
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Bijendra Kumar Asmaa Naaz Kriti Shukla Chandravir Narayan Govind Singh Alok Kumar AL Ramanathan Anshumali 《Journal of the Geological Society of India》2016,87(2):227-235
The systematic and comprehensive geochemical analysis of fluoride (F) in twenty agricultural soil samples was carried out to understand spatial variability, mechanism of retention and release, and the areas of potential risk due to high concentrations of F in soil around Sidhi District, Central India. The spatial variations in physico-chemical parameters revealed significant difference in the methods of cultivation due to geomorphological constraints, availability of surface water and ground water etc., in the study area. The north and small pocket in central Sidhi were rich in fertile soils due to availability of surface and ground water. The southern and eastern Sidhi were rainfed areas, hence, the monocropping system by traditional methods showed less impact on the soil physico-chemical parameters. The soil F varied from 366.94 to 1178 mg/kg and 2-4 times greater than the background soil value (320 mg/kg) of the world. The pollution indexes were > 1 indicating prevalence of elevated soil fluorine. 相似文献
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Since 2003, the permanent failure of the scan line corrector (SLC) of the Landsat Enhanced Thematic Mapper Plus (ETM+) sensor has seriously limited the scientific applications and usability of ETM+ data. While a number of methods have been conducted to fill the regular un-scanned locations in ETM+ SLC-off images, only a few researches have been developed to recover the large gap areas in such images. In this study, an innovative gap filling method has been introduced to reconstruct the large gap locations in SLC-off images via multi-temporal auxiliary fill images. A correlation is established between the corresponding pixels in the target SLC-off image and two auxiliary fill images in parallel using the multiple linear regression (MLR) model in two successive steps. In the first step, almost half the gap locations have been recovered using the MLR model, then in the second step a weighted multiple linear regression (WMLR) algorithm is proposed to recover the remaining missing values. The simulated and actual case studies show that the proposed approach may provide a powerful tool for recovering the large gaps in SLC-off images, especially when there is a long time interval between the auxiliary fill images and the target SLC-off image. 相似文献
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