Multivariate analysis of non-homogeneous peaks in liquid chromatography

Summary The effects of concentration, separation and spectral similarity as factors influencing the accuracy of iterative target testing factor analysis (ITT-FA) are investigated for three component systems by the application of analysis of variance (ANOVAR). ANOVAR is applied over a range of peak separations to map the changing effects of the three factors with increasing overlap. Two error responses were measured and analysed, (a) Relative cluster error (RCE) a measure of the error over all peaks in a cluster and (b) Relative peak error (RPE) the error of an individual peak. Multicomponent analysis (MCA) a method requiringa priori spectral information, is used as a referee method for ITT-FA.     

Embedded design based virtual instrument program for positron beam automation

Automation of positron beam experiment with a single chip embedded design using a programmable system on chip (PSoC) which provides easy interfacing of the high-voltage DC power supply is reported. Virtual Instrument (VI) control program written in Visual Basic 6.0 ensures the following functions (i) adjusting of sample high voltage by interacting with the programmed PSoC hardware, (ii) control of personal computer (PC) based multi channel analyzer (MCA) card for energy spectroscopy, (iii) analysis of the obtained spectrum to extract the relevant line shape parameters, (iv) plotting of relevant parameters and (v) saving the file in the appropriate format. The present study highlights the hardware features of the PSoC hardware module as well as the control of MCA and other units through programming in Visual Basic.     

LC/ESI-MS n and 1H HR-MAS NMR analytical methods as useful taxonomical tools within the genus Cystoseira C. Agardh (Fucales; Phaeophyceae)

Species of the genus Cystoseira are particularly hard to discriminate, due to the complexity of their morphology, which can be influenced by their phenological state and ecological parameters. Our study emphasized on the relevance of two kinds of analytical tools, (1) LC/ESI-MSⁿ and (2) ¹H HR-MAS NMR, also called in vivo NMR, to identify Cystoseira specimens at the specific level and discuss their taxonomy. For these analyses, samples were collected at several locations in Brittany (France), where Cystoseira baccata, C. foeniculacea, C. humilis, C. nodicaulis and C. tamariscifolia were previously reported. To validate our chemical procedure, the sequence of the ITS2 has been obtained for each species to investigate their phylogenetic relationships at a molecular level. Our study highlighted the consistency of the two physico-chemical methods, compared to “classical” molecular approach, in studying taxonomy within the genus Cystoseira. Especially, LC/ESI-MSⁿ and phylogenetic analyses converged into the discrimination of two taxonomical groups among the 5 species. The occurrence of some specific signals in the ¹H HR-MAS NMR spectra and/or some characteristic chemical compounds during LC/ESI-MSⁿ analysis could be regarded as discriminating factors. LC/ESI-MSⁿ and ¹H HR-MAS NMR turned out to be two relevant and innovative techniques to discriminate taxonomically this complex genus.     

An Algorithm Framework for Drug-Induced Liver Injury Prediction Based on Genetic Algorithm and Ensemble Learning

In the process of drug discovery, drug-induced liver injury (DILI) is still an active research field and is one of the most common and important issues in toxicity evaluation research. It directly leads to the high wear attrition of the drug. At present, there are a variety of computer algorithms based on molecular representations to predict DILI. It is found that a single molecular representation method is insufficient to complete the task of toxicity prediction, and multiple molecular fingerprint fusion methods have been used as model input. In order to solve the problem of high dimensional and unbalanced DILI prediction data, this paper integrates existing datasets and designs a new algorithm framework, Rotation-Ensemble-GA (R-E-GA). The main idea is to find a feature subset with better predictive performance after rotating the fusion vector of high-dimensional molecular representation in the feature space. Then, an Adaboost-type ensemble learning method is integrated into R-E-GA to improve the prediction accuracy. The experimental results show that the performance of R-E-GA is better than other state-of-art algorithms including ensemble learning-based and graph neural network-based methods. Through five-fold cross-validation, the R-E-GA obtains an ACC of 0.77, an F1 score of 0.769, and an AUC of 0.842.     

Distribution of the inter and intra inertia in conditional MCA

Conditional Multiple Correspondence Analysis (MCA), where a control variable plays the role of a partition model, allows us to decompose global inertia into between inertia and within inertia. The problem is to assess when the conditioning variable gives different results with respect to the unconditional analysis. In this paper, we study the asymptotic distribution function of these inertias, which can allow us to determine whether conditioning is significant. Some simulations were performed to corroborate the established results.     

特征向量计算的神经网络方法

矩阵特征向量计算在实际问题中有着广泛应用，本文采用神经网络计算方法来研究主元分析（ＰＣＡ）和次元分析（ＭＣＡ）问题．我们首先考虑神经元的情况（ｐ＝１），给出了求矩阵最大特征元和最小特征元的算法。然后对多神经元性形（ｐ〉１），给出了抽取矩阵主元和次元的算法．和目前许多元知的算法不一样，在我们ＰＣＡ的算法中发迹矩阵的负号就能够得到ＭＣＡ问题的解。     

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.