阻燃剂MCA的高压法合成工艺研究

以三聚氰胺和氰尿酸为原料,以水为溶剂,考察了高压法合成阻燃剂MCA的工艺。在反应压力为120 KPa、三聚氰胺与氰尿酸的摩尔比约为1∶1.02下,采用改变单一因素的方法探讨了在不同温度、压力、反应时间及不同p H值等情况下对反应结果的影响,得出较优的工艺条件为反应时间为1.5 h、反应的最佳温度为105℃、p H值保持在7左右最佳,在此条件下,产品纯度可达98%以上,产品质量稳定。     

The modified natural power method for principal component computation

A modified version of the natural power method (NP) for fast estimation and tracking of the principal eigenvectors of a vector sequence is Presented. It is an extension of the natural power method because it is a solution to obtain the principal eigenvectors and not only for tracking of the principal subspace. As compared with some power-based methods such as Oja method, the projection approximation subspace tracking (PAST) method, and the novel information criterion (NIC) method, the modified natural power method (MNP) has the fastest convergence rate and can be easily implemented with only O(np) flops of computation at each iteration, where n is the dimension of the vector sequence and p is the dimension of the principal subspace or the number of the principal eigenvectors. Furthermore, it is guaranteed to be globally and exponentially convergent in contrast with some non-power-based methods such as MALASE and OPERA. Selected from Journal of Fudan University (Natural Science), 2004, 43(3): 275–284     

采用形态学分量分析的红外云图插值

提出一种基于形态学分量分析的红外云图插值重建方法. 利用平稳小波变换和轮廓波变换在表示平滑分量和纹理分量时各自的优势, 将得到的低分辨率红外云图通过形态学分量分析方法分解为平滑分量和纹理分量; 并针对小波插值使低频能量损失问题, 采用先插值后变换的方法改进平稳小波插值效果, 分别用平稳小波变换和轮廓波变换对平滑分量和纹理分量进行插值; 最后将插值后的平滑分量和纹理分量重新组合实现红外云图的超分辨率重建. 结果表明, 解决了重建图像中的平滑和伪影问题, 在视觉效果和PSNR等指标上均优于其他插值算法.     

Mapping the inhomogeneity of the U and Th distributions — using sample size concept in the field conditions

Indigenously fabricated portable gamma-ray spectrometer (PGRS) is used for the measurement of gamma activity of ²¹⁴Bi (1.76 MeV) and ²⁰⁸TI (2.62 MeV), under field conditions in Mohar area, Shivpuri Distt. (MP). The energies are discriminated by using a Nal (TI) crystal of size 1.75″ × 2″. PGRS used to map the primordial elemental distributions shows reversals of concentration of thorium and uranium (represented by radium group) in field and lab analysis in many samples, which is attributed to the inhomogenity of distribution of these elements in the area. The concept of difference in the volume of dish shaped field sample and the randomly picked up sample from the field grid point (400 gm in lab analysis) is utilized to interpret the inhomogenity of these elements. However interpretations are based on the assumption that these primordial elements (U, Th) are in secular equilibrium and the terrain has low topographic relief.      

MCA方法在金属材料涂层性能研究中的应用

可移动元胞自动机(MCA)法是继有限元、边界元法之后又一种新的数值方法，它建立在不连续介质力学基础之上，可以直接模拟不均匀材料内部的损伤累积、裂纹扩展、碰撞能的计算等。本文介绍了MCA方法的理论基础及数学模型，通过一个金属基陶瓷涂层材料在冲击载荷作用下的损伤破坏计算实例表明，在同样条件下，双陶瓷涂层试样比单陶瓷涂层试样的抗冲击能力有明显提高，二者断口形貌和本构关系曲线也完全不同，说明涂层结构对涂层材料变形、损伤和破坏形式有重要影响，进而证明MCA方法可用来优化设计涂层结构与材料。     

模拟冲击破碎的MCA方法

可移动元胞自动机法（MCA）是继有限元法和边界单元法之后发展起来的一种新的建立在非连续介质力学基础上的离散数值计算方法。文章介绍了MCA方法的理论基础，并利用MCA模拟软件对冲击载荷作用下脆性块体材料的破坏进行了二维数值模拟，得到了材料的破坏变形过程、温度场、速度场和应力应变关系曲线。数值模拟结果与实际吻合较好，说明该计算方法可以有效地计算和模拟冲击破坏问题。     

基于改进MCA的干涉高光谱图像分解

干涉高光谱图像特殊的成像原理,使其帧内存在着大幅值且位置固定的干涉条纹,而帧间存在着水平移位的背景图像,这种特点会严重的破坏原始图像的固有结构,从而导致新兴的压缩感知理论与传统压缩算法的直接应用无法得到理想的效果。由于干涉条纹信息与背景图像信息的特征不同,能够对干涉条纹与背景图像进行稀疏表示的正交基也是不同的。基于这种思想,使用MCA(morphological component analysis)算法对干涉高光谱图像中干涉条纹信息与背景图像信息进行分离处理。由于干涉高光谱图像数据量庞大,传统的MCA算法对干涉高光谱数据的图像分解,迭代收敛速度慢,运算效率较低,故而针对干涉高光谱数据特点对传统MCA算法进行改进,改变其迭代收敛条件,当分离后的图像信号与原始图像信号的误差已经基本保持不变时,即终止迭代;并根据对应正交基能且仅能稀疏表示对应信号的思想,对阈值采用自适应的方式进行更新,在新的阈值更新模式中,图像信号在不同正交基下的映射系数被计算与比较。大量实验结果表明,对于LASIS数据与LAMIS数据,MCA算法都能够较完美的将干涉高光谱图像分解,改进的MCA算法更能在保持完美分解输出结果的同时,相对于传统MCA方法显著的减小迭代次数,更快的达到迭代收敛条件,从而有效的提高了算法的运算效率与实时性需求,也为新兴的压缩感知理论在干涉高光谱图像中的进一步应用提供了一种很好的解决方案。     

The exploratory analysis of qualitative variables by means of three-way analysis of two types of quantification matrices

A comparison is made between a number of techniques for the exploratory analysis of qualitative variables. The paper mainly focuses on a comparison between multiple correspondence analysis (MCA) and Gower's principal co-ordinates analysis (PCO), applied to qualitative variables. The main difference between these methods is in how they deal with infrequent categories. It is demonstrated that MCA solutions can be dominated by infrequent categories, and that, especially in such cases, PCO is a useful alternative to MCA, because it tends to downweight the influence of infrequent categories. Apart from studying the difference between MCA and PCO, other alternatives for the analysis of qualitative variables are discussed, and compared to MCA and PCO.     

Mapping closure approximation for reactive scalars in random flows

The Mapping Closure Approximation (MCA) approach is developed to describe the statistics of both conserved and reactive scalars in random flows. The statistics include Probability Density Function (PDF), Conditional Dissipation Rate (CDR) and Conditional Laplacian (CL). The statistical quantities are calculated using the MCA and compared with the results of the Direct Numerical Simulation (DNS). The results obtained from the MCA are in agreement with those from the DNS. It is shown that the MCA approach can predict the statistics of reactive scalars in random flows. The project supported by the National Committee of Science and Technology, China, under the Special Funds for Major Basic Research Project (G2000077305 and G1999032801), and the National Natural Science Foundation of China (10325211)     

Analysis of Methylcitric Acid by Enantioselective Multidimensional Gas Chromatography-Mass Spectrometry

Methylcitric acid (2-hydroxybutane-1,2,3-tricarboxylic acid–MCA) is a structural analogue of citric acid, but due to an additional methyl group it is a chiral molecule with two stereogenic centers and thus four stereoisomers are conceivable. MCA occurs naturally as prominent metabolite in body fluids of patients with inherited metabolic diseases such as propionic acidemia, methylmalonic aciduria, or holocarboxylase synthetase deficiency. Therefore methylcitric acid is considered to be an important diagnostic marker for these diseases. MCA is most likely produced from accumulated propionyl-CoA in these diseases by the enzyme si-citrate synthase from the citric acid cycle; however, there are other enzymes known which could catalyze the same reaction with different stereoselectivity, such as re-citrate synthase or the more specific enzyme methylcitrate synthase, found in microorganisms. Almost all methods dealing with MCA in the literature are non-enantioselective. For that reason there is no information about occurrence of MCA enantiomers in healthy people, patients with propionic acidemia, methylmalonic aciduria, or holocarboxylase synthetase deficiency and about value of enantiomeric distribution for diagnosis and long-term treatment. The enantioselective analysis of MCA as corresponding trimethyl ester was achieved by enantioselective multidimensional gas chromatography coupled with mass spectrometry using heptakis-(2,3-di-O-methyl-6-O-tert-butyl-dimethylsilyl)-β-cyclodextrin as chiral stationary phase. The described method allows a reliable screening of MCA in complex matrices like urine without time consuming sample preparation and with mass selective detection. During this investigation urine samples from various patients and healthy controls were analyzed. As concluded, MCA is a good diagnostic marker and can be easily measured by the method presented. Only the two stereoisomers (2S,3R) and (2S,3S) were detectable in patients and healthy controls. The varying ratios of these stereoisomers cannot presently be correlated with the health status of patients, although there are some indications that this might be possible. However, the quantitative levels of MCA, determined as the ratio of MCA absolute peak area divided by 1,000 to the creatinine contents of urine samples in this investigation, showed a dependence on the state of health and MCA would thus also be a possible marker for long-term treatment. Such a substance is of major interest nowadays since there are different studies searching for such a long-term marker in propionic acidemia or methylmalonic aciduria.