921 resultados para indicator kriging


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Experimental charge density analysis combined with the quantum crystallographic technique of X-ray wavefunction refinement (XWR) provides quantitative insights into the intra-and intermolecular interactions formed by acetazolamide, a diuretic drug. Firstly, the analysis of charge density topology at the intermolecular level shows the presence of exceptionally strong interaction motifs such as a DDAA-AADD (D-donor, A-acceptor) type quadruple hydrogen bond motif and a sulfonamide dimer synthon. The nature and strength of intra-molecular S center dot center dot center dot O chalcogen bonding have been characterized using descriptors from the multipole model (MM) and XWR. Although pure geometrical criteria suggest the possibility of two intra-molecular S center dot center dot center dot O chalcogen bonded ring motifs, only one of them satisfies the ``orbital geometry'' so as to exhibit an interaction in terms of an electron density bond path and a bond critical point. The presence of `s-holes' on the sulfur atom leading to the S center dot center dot center dot O chalcogen bond has been visualized on the electrostatic potential surface and Laplacian isosurfaces close to the `reactive surface'. The electron localizability indicator (ELI) and Roby bond orders derived from the `experimental wave function' provide insights into the nature of S center dot center dot center dot O chalcogen bonding.

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Identification of homogeneous hydrometeorological regions (HMRs) is necessary for various applications. Such regions are delineated by various approaches considering rainfall and temperature as two key variables. In conventional approaches, formation of regions is based on principal components (PCs)/statistics/indices determined from time series of the key variables at monthly and seasonal scales. An issue with use of PCs for regionalization is that they have to be extracted from contemporaneous records of hydrometeorological variables. Therefore, delineated regions may not be effective when the available records are limited over contemporaneous time period. A drawback associated with the use of statistics/indices is that they do not provide effective representation of the key variables when the records exhibit non-stationarity. Consequently, the resulting regions may not be effective for the desired purpose. To address these issues, a new approach is proposed in this article. The approach considers information extracted from wavelet transformations of the observed multivariate hydrometeorological time series as the basis for regionalization by global fuzzy c-means clustering procedure. The approach can account for dynamic variability in the time series and its non-stationarity (if any). Effectiveness of the proposed approach in forming HMRs is demonstrated by application to India, as there are no prior attempts to form such regions over the country. Drought severity-area-frequency (SAF) curves are constructed corresponding to each of the newly formed regions for the use in regional drought analysis, by considering standardized precipitation evapotranspiration index (SPEI) as the drought indicator.

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We have estimated a metallicity map of the Large Magellanic Cloud (LMC) using the Magellanic Cloud Photometric Survey (MCPS) and Optical Gravitational Lensing Experiment (OGLE III) photometric data. This is a first of its kind map of metallicity up to a radius of 4 degrees-5 degrees, derived using photometric data and calibrated using spectroscopic data of Red Giant Branch (RGB) stars. We identify the RGB in the V, (V - I) colour-magnitude diagrams of small subregions of varying sizes in both data sets. We use the slope of the RGB as an indicator of the average metallicity of a subregion, and calibrate the RGB slope to metallicity using spectroscopic data for field and cluster red giants in selected subregions. The average metallicity of the LMC is found to be Fe/H] = -0.37 dex (sigmaFe/H] = 0.12) from MCPS data, and Fe/H] = -0.39 dex (sigmaFe/H] = 0.10) from OGLE III data. The bar is found to be the most metal-rich region of the LMC. Both the data sets suggest a shallow radial metallicity gradient up to a radius of 4 kpc (-0.049 +/- 0.002 dex kpc(-1) to -0.066 +/- 0.006 dex kpc(-1)). Subregions in which the mean metallicity differs from the surrounding areas do not appear to correlate with previously known features; spectroscopic studies are required in order to assess their physical significance.

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Displacement estimation is a key step in the evaluation of tissue elasticity by quasistatic strain imaging. An efficient approach may incorporate a tracking strategy whereby each estimate is initially obtained from its neighbours' displacements and then refined through a localized search. This increases the accuracy and reduces the computational expense compared with exhaustive search. However, simple tracking strategies fail when the target displacement map exhibits complex structure. For example, there may be discontinuities and regions of indeterminate displacement caused by decorrelation between the pre- and post-deformation radio frequency (RF) echo signals. This paper introduces a novel displacement tracking algorithm, with a search strategy guided by a data quality indicator. Comparisons with existing methods show that the proposed algorithm is more robust when the displacement distribution is challenging.

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用地质统计学中有代表性的普通Kriging法和对数正态Kriging法对某油田P油层的渗透率、孔隙度和有效厚度等特征参数进行了分析。通过比较两种计算方法的特征参数结果,发现这两种地质统计学方法在描述油藏多孔介质的非均质性方面各有各的适用范围。普通Kriging法更适合于特征参数呈正态分布关系的情况,对数正态Kriging法更适合于特征参数呈非正态分布关系的情况。这为非均质油藏的油藏描述方法提供了合理的判据,为非均质多孔介质中流体流动规律的研究提供了有力基础。

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The water content distribution in the surface layer of Maoping slope has been studied by testing the water content at 31 control sites. The water content profiles at these sites have also been determined. The water content distributions at different segments have been obtained by using the Kriging method of geostatistics. By comparing the water content distributions with the landform of the slope, it was shown that the water content is closely dependent on the landform of the slope. The water content distribution in the surface layer provided a fundamental basis for landslide predication and treatment.