太平洋鳕鱼脑中硫苷脂的分离纯化和分析

以太平洋鳕鱼为原料,从鳕鱼脑中分离硫苷脂,确立了提取及纯化的条件,并对硫苷脂的纯度和分子种进行分析。首先,采用氯仿/甲醇(2∶1,v/v)提取总脂。然后,依次采用氯仿/甲醇/水(7∶3∶0.3,v/v/v)洗脱硅胶柱层析,含0.2mol/L乙酸铵的氯仿/甲醇/水(30∶60∶8,v/v/v)洗脱DEAE Sephadex-A25离子交换柱层析,40%甲醇脱盐和100%甲醇洗脱反相C8柱层析,获得硫苷脂纯品。最后,利用500YMC Diol液相色谱柱(3.0mm×250mm,5μm)分离,以正己烷/异丙醇(70∶30,v/v),异丙醇/水/甲酸/氨水(100∶13∶1∶0.14,v/v/v/v)为流动相梯度洗脱,采用负电喷雾电离(ESI)和母离子扫描模式,用液相色谱-串联质谱(LC-MS/MS)法分析了鳕鱼脑硫苷脂的纯度和分子种组成,并比较了其与哺乳动物脑中硫苷脂分子种组成的异同。结果表明,本实验制得的鳕鱼脑硫苷脂纯度为90.74%,与哺乳动物类似,鳕鱼脑硫苷脂的长链碱基以鞘氨醇为主,主要分子种为d18∶1-C24∶1,但脂肪酸的羟基化程度略低,且含少量独特的分子种,如d18∶1-22∶1和d18∶2-25∶2。     

Measurement of trace nitrate concentrations in seawater by ion chromatography with valve switching

An ion chromatographic method with a valve switching facility was developed to determine trace nitrate concentrations in seawater using two pumps, two different suppressors, and two columns. A carbohydrate membrane desalter was used to reduce the high concentrations of sodium salts in samples. In this method, trace nitrate was eluted from the concentrator column to the analytical columns, while the matrix flowed to waste. Neither chemical pre-treatment nor sample dilution was required. In the optimized separation conditions, the method showed good linearity （R〉0,99） in the 0.05 and 50 mg/L concentration range, and satisfactory repeatability （RSD〈5%, n=6）. The limit of detection for nitrate was 0.02 mg/L. Results showed that the valve switching system was suitable and practical for the determination of trace nitrate in seawater.     

Molecularly imprinted polymers for selective extraction of crystal violet from natural seawater coupled with high-performance liquid chromatographic determination

Molecularly imprinted polymers(MIPs) were prepared by the bulk polymerization using crystal violet as the template molecule, and the methacrylic acid and ethylene glycol dimetheacrylate as functional monomer and cross-linker, respectively. Systematic investigations of synthetic conditions were conducted. The surface morphology and recognition mechanism of the obtained polymers were studied using scanning electron microscope and spectrophotometric analysis. MIPs showed high affinity to template molecule and were successfully applied as special solid-phase extraction sorbent for selective extraction of crystal violet from natural seawater. An off-line molecularly imprinted solid-phase extraction(MISPE) method followed by high-performance liquid chromatography with diodearray detection for the analysis of crystal violet was also established. MISPE columns have good recoveries for crystal violet standard solutions and good linearity was obtained over the concentration range of 0-200 μg L-1(R2 0.99). Finally, two natural seawater samples were investigated. The recoveries of spiked seawater on the MISPE columns were from 44.47% to 62.34%, the relative standard deviation(n=3) being in the range of 2.89%-5.96%.     

基于航摄影像的滇池捞鱼河湿地植物类型提取

为了获取滇池湿地的植物类型分布信息,以捞鱼河湿地为示范区,采用分辨率为0.15 m的航摄影像为影像数据源,利用人机交互和面向对象相结合的影像解译方法,实现捞鱼河湿地植物类型分布信息的提取.在植物类型边界提取过程中,发现过高的影像分辨率(≤0.3m)不利于成片具有空间异质性植物类型边界的正常提取,容易出现同一类型过度分割情况.通过邻域降分辨率重采样技术,将影像分辨率降至0.6m时,能有效解决过度分割问题.当分辨率降至更低时,虽然能解决过度分割问题,但会导致地物边界出现不同程度的锯齿而与地物边界不符的后果.研究所应用的基于Feature Extaction模块的植物类型边界提取方法,能有效减少人机交互方法中人工勾绘边界的工作量,在保证分类精度的同时减少人力投入,对航摄影像在大范围湿地植物类型的提取中具有重要借鉴意义.     

Organic geochemistry of marine source rocks and pyrobitumen-containing reservoir rocks of the Sichuan Basin and neighbouring areas,SW China

Three bitumen fractions were obtained and systematically analysed for the terpane and sterane composition from 30 Paleozoic source rocks and 64 bitumen-containing reservoir rocks within the Upper Sinian, Lower Cambrian, Lower Silurian, Middle Carboniferous, Upper Permian and Lower Triassic strata in the Sichuan Basin and neighbouring areas, China. These bitumen fractions include extractable oils (bitumen I), oil-bearing fluid inclusions and/or closely associated components with the kerogen or pyrobitumen/mineral matrix, released during kerogen or pyrobitumen isolation and demineralization (bitumen II), and bound compounds within the kerogen or pyrobitumen released by confined pyrolysis (bitumen III). In addition, atomic H/C and O/C ratios and carbon isotopic compositions of kerogen and pyrobitumen from some of the samples were measured. Geochemical results and geological information suggest that: (1) in the Central Sichuan Basin, hydrocarbon gases in reservoirs within the fourth section of the Upper Sinian Dengying Formation were derived from both the Lower Cambrian and Upper Sinian source rocks; and (2) in the Eastern Sichuan Basin, hydrocarbon gases in Middle Carboniferous Huanglong Formation reservoirs were mainly derived from Lower Silurian source rocks, while those in Upper Permian and Lower Triassic reservoirs were mainly derived from both Upper Permian and Lower Silurian marine source rocks. For both the source and reservoir rocks, bitumen III fractions generally show relatively lower maturity near the peak oil generation stage, while the other two bitumen fractions show very high maturities based on terpane and sterane distributions. Tricyclic terpanes evolved from the distribution pattern C₂₀ < C₂₁ < C₂₃, through C₂₀ < C₂₁ > C₂₃, finally to C₂₀ > C₂₁ > C₂₃ during severe thermal stress. The concentration of C₃₀ diahopane in bitumen III (the bound components released from confined pyrolysis) is substantially lower than in the other two bitumen fractions for four terrigenous Upper Permian source rocks, demonstrating that this compound originated from free hopanoid precursors, rather than hopanoids bound to the kerogen.     

基于特征区域统计的多光谱遥感影像海岛瞬时岸线提取(英文)

本研究采用IKONOS遥感图像,选取波谱特征区,通过区域像元统计并计算各波段权重系数,将影像进行波谱归一化处理,使归一化的影像岛陆与海水特征更明显。在此基础上,采用最大类间方差法确定最佳分割阈值,对归一化的影像进行二值化,从而提取海岛岸线。该方法采用特征曲线法进行水陆分离,得到的二值图像保持了原图的有效边缘,采用二值形态学提取的海岸线连续可靠、信噪比高。结果表明,该方法简单、快速,能有效提取海岸线,具有实用价值。     

An automated approach to vertical road characterisation using mobile LiDAR systems: Longitudinal profiles and cross-sections

The characterisation the vertical profiles and cross-sections of roads is important for the verification of proper construction and road safety assessment. The goal of this paper is the extraction of geometric parameters through the automatic processing of mobile LiDAR system (MLS) point clouds. Massive and complex datasets provided by the MLS are processed using a hierarchical strategy that includes segmentation, principal component analysis (PCA)-based orthogonal regression, filtering and parameter extraction procedures. Best-fit geometric parameters act as a vertical road model for both linear parameters (slope and vertical curves) and cross-sections (superelevations). The proposed automatic processing approach gives satisfactory results for the analysed scenario.     

A multi-index learning approach for classification of high-resolution remotely sensed images over urban areas

In recent years, it has been widely agreed that spatial features derived from textural, structural, and object-based methods are important information sources to complement spectral properties for accurate urban classification of high-resolution imagery. However, the spatial features always refer to a series of parameters, such as scales, directions, and statistical measures, leading to high-dimensional feature space. The high-dimensional space is almost impractical to deal with considering the huge storage and computational cost while processing high-resolution images. To this aim, we propose a novel multi-index learning (MIL) method, where a set of low-dimensional information indices is used to represent the complex geospatial scenes in high-resolution images. Specifically, two categories of indices are proposed in the study: (1) Primitive indices (PI): High-resolution urban scenes are represented using a group of primitives (e.g., building/shadow/vegetation) that are calculated automatically and rapidly; (2) Variation indices (VI): A couple of spectral and spatial variation indices are proposed based on the 3D wavelet transformation in order to describe the local variation in the joint spectral-spatial domains. In this way, urban landscapes can be decomposed into a set of low-dimensional and semantic indices replacing the high-dimensional but low-level features (e.g., textures). The information indices are then learned via the multi-kernel support vector machines. The proposed MIL method is evaluated using various high-resolution images including GeoEye-1, QuickBird, WorldView-2, and ZY-3, as well as an elaborate comparison to the state-of-the-art image classification algorithms such as object-based analysis, and spectral-spatial approaches based on textural and morphological features. It is revealed that the MIL method is able to achieve promising results with a low-dimensional feature space, and, provide a practical strategy for processing large-scale high-resolution images.     

Novel Folded-PCA for improved feature extraction and data reduction with hyperspectral imaging and SAR in remote sensing

As a widely used approach for feature extraction and data reduction, Principal Components Analysis (PCA) suffers from high computational cost, large memory requirement and low efficacy in dealing with large dimensional datasets such as Hyperspectral Imaging (HSI). Consequently, a novel Folded-PCA is proposed, where the spectral vector is folded into a matrix to allow the covariance matrix to be determined more efficiently. With this matrix-based representation, both global and local structures are extracted to provide additional information for data classification. Moreover, both the computational cost and the memory requirement have been significantly reduced. Using Support Vector Machine (SVM) for classification on two well-known HSI datasets and one Synthetic Aperture Radar (SAR) dataset in remote sensing, quantitative results are generated for objective evaluations. Comprehensive results have indicated that the proposed Folded-PCA approach not only outperforms the conventional PCA but also the baseline approach where the whole feature sets are used.     

Introducing mapping standards in the quality assessment of buildings extracted from very high resolution satellite imagery

Many municipal activities require updated large-scale maps that include both topographic and thematic information. For this purpose, the efficient use of very high spatial resolution (VHR) satellite imagery suggests the development of approaches that enable a timely discrimination, counting and delineation of urban elements according to legal technical specifications and quality standards. Therefore, the nature of this data source and expanding range of applications calls for objective methods and quantitative metrics to assess the quality of the extracted information which go beyond traditional thematic accuracy alone. The present work concerns the development and testing of a new approach for using technical mapping standards in the quality assessment of buildings automatically extracted from VHR satellite imagery. Feature extraction software was employed to map buildings present in a pansharpened QuickBird image of Lisbon. Quality assessment was exhaustive and involved comparisons of extracted features against a reference data set, introducing cartographic constraints from scales 1:1000, 1:5000, and 1:10,000. The spatial data quality elements subject to evaluation were: thematic (attribute) accuracy, completeness, and geometric quality assessed based on planimetric deviation from the reference map. Tests were developed and metrics analyzed considering thresholds and standards for the large mapping scales most frequently used by municipalities. Results show that values for completeness varied with mapping scales and were only slightly superior for scale 1:10,000. Concerning the geometric quality, a large percentage of extracted features met the strict topographic standards of planimetric deviation for scale 1:10,000, while no buildings were compliant with the specification for scale 1:1000.