多元小波变换及L^2（R^p）框架

提出了一般形式不可分离变量的多元小波变换,通常的小汉变换只是本的特例,进而相应地构造了多元小波框架以及多元函数小波框架展开式。     

Environmetrical Treatment of Water Quality Survey Data from Yantra River, Bulgaria

 The environmetrical analysis carried out has indicated that the short-term water quality survey may give a very important information on the latent factors influencing the water quality of Yantra river basin. The principal components analysis carried out reveals that at least four principal components are necessary for multivariate statistical modeling of the water quality – combination of natural and anthropogenic influences (“mixed” factor) reflecting parameters such as water hardness, marine influence, organic pollution; typical anthropogenic influences (“anthropogenic” factor) explaining the metal contamination of the river water; everyday wastes, usually N-containing pollutants such as nitrates, nitrites or ammonia, form the “N-containing wastes” factor and a “temperature” factor formed by typical physical parameters such as water and air temperature. The formation of these special features of the river waters from Yantra basin is also confirmed by the results of cluster analysis (variable clustering) where the content of the significant clusters of the variables is the same as the content of the principal components modeling over 75% of the total variance of the system. Additionally, the cluster analysis of the objects has proved that the water quality during both sampling traverses is very stable and reproducible. Few exceptions are observed due to momentary local pollution in an industrial area along the river stream. Comparison with standard requirements for water quality has indicated that the Yantra river waters are of high quality and could be used after minor pretreatment as potable water sources. The environmetrical approaches applied reveal a specific information concerning the river water quality. In this way the ecological problem treated has not a local importance but suggests a strategy for estimation of similar ecosystems in global sense. Received July 30, 1998. Revision June 1, 1999.     

On some aspects of multivariate polynomial interpolation

The purpose of this paper is to present some aspects of multivariate Hermite polynomial interpolation. We do not focus on algebraic considerations, combinatoric and geometric aspects, but on explicitation of formulas for uniform and non-uniform bivariate interpolation and some higher dimensional problems. The concepts of similar and equivalent interpolation schemes are introduced and some differential aspects related to them are also investigated. This revised version was published online in June 2006 with corrections to the Cover Date.     

Profiles of Essential Oils and Correlations with Phenolic Acids and Primary Metabolites in Flower Buds of Magnolia heptapeta and Magnolia denudata var. purpurascens

Magnolia flower buds are a source of herbal medicines with various active compounds. In this study, differences in the distribution and abundance of major essential oils, phenolic acids, and primary metabolites between white flower buds of Magnolia heptapeta and violet flower buds of Magnolia denudata var. purpurascens were characterised. A multivariate analysis revealed clear separation between the white and violet flower buds with respect to primary and secondary metabolites closely related to metabolic systems. White flower buds contained large amounts of monoterpene hydrocarbons (MH), phenolic acids, aromatic amino acids, and monosaccharides, related to the production of isoprenes, as MH precursors, and the activity of MH synthase. However, concentrations of β-myrcene, a major MH compound, were higher in violet flower buds than in white flower buds, possibly due to higher threonine levels and low acidic conditions induced by comparatively low levels of some organic acids. Moreover, levels of stress-related metabolites, such as oxygenated monoterpenes, proline, and glutamic acid, were higher in violet flower buds than in white flower buds. Our results support the feasibility of metabolic profiling for the identification of phytochemical differences and improve our understanding of the correlated biological pathways for primary and secondary metabolites.     

Analysis of Individual High-Frequency Traders’ Buy–Sell Order Strategy Based on Multivariate Hawkes Process

Traders who instantly react to changes in the financial market and place orders in milliseconds are called high-frequency traders (HFTs). HFTs have recently become more prevalent and attracting attention in the study of market microstructures. In this study, we used data to track the order history of individual HFTs in the USD/JPY forex market to reveal how individual HFTs interact with the order book and what strategies they use to place their limit orders. Specifically, we introduced an 8-dimensional multivariate Hawkes process that included the excitations due to the occurrence of limit orders, cancel orders, and executions in the order book change, and performed maximum likelihood estimations of the limit order processes for 134 HFTs. As a result, we found that the limit order generation processes of 104 of the 134 HFTs were modeled by a multivariate Hawkes process. In this analysis of the EBS market, the HFTs whose strategies were modeled by the Hawkes process were categorized into three groups according to their excitation mechanisms: (1) those excited by executions; (2) those that were excited by the occurrences or cancellations of limit orders; and (3) those that were excited by their own orders.     

Analysis of Vicinal Water in Soft Contact Lenses Using a Combination of Infrared Absorption Spectroscopy and Multivariate Curve Resolution

In this paper, we propose a new spectroscopic method to explore the behavior of molecules near polymeric molecular networks of water-containing soft materials such as hydrogels. We demonstrate the analysis of hydrogen bonding states of water in the vicinity of hydrogels (soft contact lenses). In this method, we apply force to hydrated contact lenses to deform them and to modulate the ratio between the signals from bulk and vicinal regions. We then collect spectra at different forces. Finally, we extracted the spectra of the vicinal region using the multivariate curve resolution-alternating least square (MCR-ALS) method. We report the hydration states depending on the chemical structures of hydrogels constituting the contact lenses.     

组合生成算法与多元线性回归相结合用于近红外光谱波长的优选

分立波长型近红外光谱分析仪是光谱分析仪器中较为普及的一种快速成份定量分析仪。如滤光片型、发光二极管型等。该类分析仪器研发的一个主要问题是如何针对于待测物质主要成份进行近红外光谱解析。找到最优定标波长组合用于建立稳健的定标模型。常用的波长选择方法为相关光谱结合逐步多元线性回归方法,该方法依据各参与定标波长所对应的t检验值进行最优定标波长的判别,但在实际应用中定标模型的定标精度和预测精度相差较大,具有很大的不准确性。为了实现定标波长的优选引入了组合数学中的组合生成算法。可以在较短的时间内完成最优波长组合的选取,结果是令人满意的。     

钙调蛋白抑制剂预测模型研究

选用30个结构多样的caM抑制剂分子作为数据集,采用多元线性回归(MLR)方法及主成分回归分析(PCA)方法对每个化合物的194个分子参数进行回归分析,分别建立了各自的最优预测模型.结果表明:多元线性回归分析方法所建模型与主成分回归所建模型相对比,发现逐步筛选法为最优建模方法?该方法所建模型统计结果良好(R2=0.952,SEE为0.289),应用于检验集时结果也比较令人满意(R2=0.941,SEP为0.295),模型表现出较强的可靠性和预测性.     

Metabolite profiling of Huaiyang Medicago polymorpha with different mowing crops

Abstract

The main purpose of our study was to identify and compare secondary metabolites due to different mowing in order to make better use of Huaiyang Medicago polymorpha. The metabolite profiling of Huaiyang Medicago polymorpha with two mowing crops was performed using a rapid resolution liquid chromatography system with quadrupole time-of-flight mass spectrometer (RRLC-QTOFMS) followed by multivariate statistical analyses. Principal Component Analysis (PCA) results showed a clear distinction between two mowing crops. The major metabolites that contributed to mowing discrimination were identified. The results also showed that the content of major active compounds in Medicago polymorpha from the second crop are higher significantly than the first crop. This study suggests that the strategy is a reliable and simple method for the rapid discrimination of subtle variations due to different mowing crops.     

Quality consistency evaluation of commercial transfer factor injections by chromatographic fingerprint combined with multivariate statistical analysis

The current quality control methods relying mainly on chromogenic reaction can hardly ensure the quality and safety of the biochemical drug with complex chemical composition. Therefore, a chromatographic fingerprint method was developed for the quality evaluation of a multicomponent biochemical drug, transfer factor injection. High‐performance liquid chromatography fingerprint was measured by using a C₁₈ column (250 × 4.6 mm, 5 µm) with a mobile phase composed of 0.1% trifluoroacetic acid–water and 0.085% trifluoroacetic acid–acetonitrile under gradient elution. The developed method was validated and was subsequently applied to 57 batches of commercial products which were sampled by National Drug Assessment Program. High‐resolution mass spectrometry analysis was performed on characteristic peaks of fingerprints, and a series of amino acids, nucleosides, and deoxynucleosides were identified. In the fingerprint assessments, principal component analysis and Hotelling T² analysis yielded the best results. The results generally indicated that there was a significant difference among products of batch‐to‐batch or from different manufacturers. Abnormal samples and its discriminatory components were also explored. In summary, the established fingerprinting method with multivariate statistical analysis could offer an efficient, reliable, and practical approach for quality consistency evaluation of transfer factor injection, providing a reference for the quality control of other multicomponent biochemical drugs.