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.     

主成分计算的改进自然幂迭代方法

提供快速估计与跟踪一个向量序列的主特征向量的改进自然幂迭代方法．它是自然幂迭代方法的一个延伸,不仅跟踪主子空间,而且得到了主特征向量．与一些基于幂迭代的方法(例如Oja,PAST与NIC)相比,改进自然幂迭代方法具有最快的收敛速度,且能容易地以每步迭代O(np)的计算量加以实现,这里n为所考虑向量序列的维数,p为所要跟踪的主子空间的维数(或主特征向量的个数)．与某些非幂迭代的方法(例如MALASE与OPERA)相比,改进自然幂迭代方法保证了全局指数收敛．     

阻燃润滑剂MCA在聚酰胺中的应用

介绍了MCA与其它阻燃助剂对聚酰胺阻燃性能的影响,实验结果表明:应用MCA阻燃 聚酰胺效果明显,减少了环境污染,同时KNO3的加入使燃烧残留物成炭,取得了更好的阻燃效果。     

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。     

一种基于次元分析技术的鲁棒波束形成算法

针对实际应用中先验知识存在偏差的问题,基于权向量长度恒定的常规线性约束波束形成算法,提出一种权向量长度恒定的最差情况性能优化波束形成算法.分析了神经次元分析(MCA)学习规则与该波束形成优化问题在数学描述上的相似性,利用神经MCA学习规则实现鲁棒自适应波束形成.仿真结果表明,与基于线性约束的波束形成算法相比,该算法具有更强的信号跟踪能力和干扰抑制能力,并且对信号方向向量的偏差具有更强的鲁棒性.     

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。