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961.
    
Contact aureoles of the anorthositic to granitic plutons of the Mesoproterozoic Nain Plutonic Suite (NPS), Labrador, are particularly well developed in the Palaeoproterozoic granulite facies, metasedimentary, Tasiuyak gneiss. Granulite facies regional metamorphism (MR), c. 1860 Ma, led to biotite dehydration melting of the paragneiss and melt migration, leaving behind biotite‐poor, garnet–sillimanite‐bearing quartzofeldspathic rocks. Subsequently, Tasiuyak gneiss within a c. 1320 Ma contact aureole of the NPS was statically subjected to lower pressure, but higher temperature conditions (MC), leading to a second partial melting event, and the generation of complex mineral assemblages and microstructures, which were controlled to a large extent by the textures of the MR assemblage. This control is clearly seen in scanning electron microscopic images of thin sections and is further supported by phase equilibria modelling. Samples collected within the contact aureole near Anaktalik Brook, west of Nain, Labrador, mainly consist of spinel–cordierite and orthopyroxene–cordierite (or plagioclase) pseudomorphs after MR sillimanite and garnet, respectively, within a quartzofeldspathic matrix. In addition, some samples contain fine‐grained intergrowths of K‐feldspar–quartz–cordierite–orthopyroxene inferred to be pseudomorphs after osumulite. Microstructural evidence of the former melt includes (i) coarse‐grained K‐feldspar–quartz–cordierite–orthopyroxene domains that locally cut the rock fabric and are inferred to represent neosome; (ii) very fine‐ to medium‐grained cordierite–quartz intergrowths interpreted to have formed by a reaction involving dissolution of biotite and feldspar in melt; and (iii) fine‐scale interstitial pools or micro‐cracks filled by feldspar interpreted to have crystallized from melt. Ultrahigh temperature (UHT) conditions during contact metamorphism are supported by (i) solidus temperatures >900 °C estimated for all samples, coupled with extensive textural evidence for contact‐related partial melting; (ii) the inferred (former) presence of osumilite; and (iii) titanium‐in‐quartz thermometry indicating temperatures within error of 900 °C. The UHT environment in which these unusual textures and minerals were developed was likely a consequence of the superposition of more than one contact metamorphic event upon the already relatively anhydrous Tasiuyak gneiss.  相似文献   
962.
In the context of astrophysical dynamos we illustrate that the no-cosines flow, with zero mean helicity, can drive fast dynamo action and we study the dynamo’s mode of operation during both the linear and non-linear saturation regimes. It turns out that in addition to a high growth rate in the linear regime, the dynamo saturates at a level significantly higher than normal turbulent dynamos, namely at exact equipartition when the magnetic Prandtl number Prm∼ 1. Visualization of the magnetic and velocity fields at saturation will help us to understand some of the aspects of the non-linear dynamo problem.  相似文献   
963.
    
Historically, observing snow depth over large areas has been difficult. When snow depth observations are sparse, regression models can be used to infer the snow depth over a given area. Data sparsity has also left many important questions about such inference unexamined. Improved inference, or estimation, of snow depth and its spatial distribution from a given set of observations can benefit a wide range of applications from water resource management, to ecological studies, to validation of satellite estimates of snow pack. The development of Light Detection and Ranging (LiDAR) technology has provided non‐sparse snow depth measurements, which we use in this study, to address fundamental questions about snow depth inference using both sparse and non‐sparse observations. For example, when are more data needed and when are data redundant? Results apply to both traditional and manual snow depth measurements and to LiDAR observations. Through sampling experiments on high‐resolution LiDAR snow depth observations at six separate 1.17‐km2 sites in the Colorado Rocky Mountains, we provide novel perspectives on a variety of issues affecting the regression estimation of snow depth from sparse observations. We measure the effects of observation count, random selection of observations, quality of predictor variables, and cross‐validation procedures using three skill metrics: percent error in total snow volume, root mean squared error (RMSE), and R2. Extremes of predictor quality are used to understand the range of its effect; how do predictors downloaded from internet perform against more accurate predictors measured by LiDAR? Whereas cross validation remains the only option for validating inference from sparse observations, in our experiments, the full set of LiDAR‐measured snow depths can be considered the ‘true’ spatial distribution and used to understand cross‐validation bias at the spatial scale of inference. We model at the 30‐m resolution of readily available predictors, which is a popular spatial resolution in the literature. Three regression models are also compared, and we briefly examine how sampling design affects model skill. Results quantify the primary dependence of each skill metric on observation count that ranges over three orders of magnitude, doubling at each step from 25 up to 3200. Whereas uncertainty (resulting from random selection of observations) in percent error of true total snow volume is typically well constrained by 100–200 observations, there is considerable uncertainty in the inferred spatial distribution (R2) even at medium observation counts (200–800). We show that percent error in total snow volume is not sensitive to predictor quality, although RMSE and R2 (measures of spatial distribution) often depend critically on it. Inaccuracies of downloaded predictors (most often the vegetation predictors) can easily require a quadrupling of observation count to match RMSE and R2 scores obtained by LiDAR‐measured predictors. Under cross validation, the RMSE and R2 skill measures are consistently biased towards poorer results than their true validations. This is primarily a result of greater variance at the spatial scales of point observations used for cross validation than at the 30‐m resolution of the model. The magnitude of this bias depends on individual site characteristics, observation count (for our experimental design), and sampling design. Sampling designs that maximize independent information maximize cross‐validation bias but also maximize true R2. The bagging tree model is found to generally outperform the other regression models in the study on several criteria. Finally, we discuss and recommend use of LiDAR in conjunction with regression modelling to advance understanding of snow depth spatial distribution at spatial scales of thousands of square kilometres. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   
964.
A novel adsorbent for heavy metal remediation in aqueous environments   总被引:1,自引:8,他引:1  
The objective of this study was to investigate the possibility of using maize tassel as an alternative adsorbent for the removal of chromium (VI) and cadmium (II) ions from aqueous solutions. The effect of pH, solution temperature, contact time, initial metal ion concentration and adsorbent dose on the adsorption of chromium (VI) and cadmium (II) by tassel was investigated using batch methods. Adsorption for both chromium (VI) and cadmium (II) was found to be highly pH dependent compared to the other parameters investigated. Obtained results gave an adsorption capacity of 79.1 % for chromium (VI) at pH 2, exposure time of 1h at 25 °C. Maximum capacity of cadmium of 88 % was obtained in the pH range of 5-6 at 25 °C after exposure time of 1 h. The adsorption capacities of tassel for both chromium (VI) and cadmium (II) were found to be comparable to those of other commercial adsorbents currently in use for the removal of heavy metals from aqueous wastes. These results have demonstrated the immense potential of maize tassel as an alternative adsorbent for toxic metal ions remediation in polluted water and wastewater.  相似文献   
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Suitable vineyard soils enhance soil stability and biodiversity which in turn protects roots against erosion and nutrient losses. There is a lack of information related to inexpensive and suitable methods and tools to protect the soil in Mediterranean sloping vineyards(25° of slope inclination). In the vineyards of the Montes de Málaga(southern Spain), a sustainable land management practice that controls soil erosion is actually achieved by tilling rills in the down-slope direction to canalize water and sediments. Because of their design and use, we call them agri-spillways. In this research, we assessed two agri-spillways(between 10 m and 15 m length, and slopes between 25.8° and 35°) by performing runoff experiments under extreme conditions(a motor driven pump that discharged water flows up to 1.33 l s~(-1) for 12 to 15 minutes: ≈1000 l). The final results showed: i) a great capacity by these rills to canalize large amounts of water and sediments; and, ii) higher water flow speeds(between 0.16 m s-1 and 0.28 m s~(-1)) and sediment concentrationrates(up to 1538.6 g l~(-1)) than typically found in other Mediterranean areas and land uses(such as badlands, rangelands or extensive crops of olives and almonds). The speed of water flow and the sediment concentration were much higher in the shorter and steeper rill. We concluded that agri-spillways, given correct planning and maintenance, can be a potential solution as an inexpensive method to protect the soil in sloping Mediterranean vineyards.  相似文献   
970.
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