Peroxidase-like catalytic activities of ionic metalloporphyrins supported on functionalised polystyrene surface

Metalloderivatives of anionic tetrasulphonated tetraphenylporphyrin (MTPPS, M = Mn(III), Fe(III) and Co(III)) were synthesized and immobilized on cationically functionalised divinylbenzene(DVB)-crosslinked polystyrene(PS). These supported catalysts (PS-MTPPS) were found to exhibit peroxidase-like activity. The co-oxidation of 4-aminoantipyrine and phenol by H₂O₂ was attempted with these catalysts to mimic this enzyme function. The catalytic efficiency of all these immobilized MTPPS was found to be superior to the corresponding unsupported MTPPS in solution. The effect of the central metal ion of the porphyrin, pH of the reaction medium and also the temperature effect are investigated. The ideal pH was seen to be in the 8.0–8.5 range, with maximum effect at 8.2. The efficiency order for the various PS-MTPPS was seen to be Co>Mn>Fe, with CoTPPS showing efficiency comparable to that of horseradish peroxidase. The catalytic efficiency was found to be increasing with temperature for all the catalysts. The re-usability of these PS-MTPPS systems for peroxidase-like activity was also studied and it was found that they exhibited a very high degree of recyclability without much poisoning.     

凸集的一个新概念及其一些特征性质

本文研究了凸集的一些基本性质.给出了集合的边界点的支持方向的新概念.利用支持方向证明了凸集的一些特征性质. 获得了凸集分离定理及其它一些特征性质的新方法和途径.     

基于KMOD核函数的SVM方法在信用评分中的应用

本文介绍了支持向量分类机,并引入具有更好识别能力的KMOD核函数建立了SVM信用卡分类模型.利用澳大利亚和德国的信用卡数据进行了数值实验,结果表明该模型在分类准确率、支持向量方面优于基于RBF的SVM模型.     

基于支持向量机模型的建筑物沉降预测

针对建筑沉降发生的过程,采用支持向量机(SVM)模型对建筑物沉降进行预测.使用前期施工过程中的沉降观测数据作为训练样本集,建立现场动态沉降量预报模型.仿真试验和实践结果表明,模型与BP神经网络预测模型相比能够更准确地反映实际沉降过程,且满足精确性和适用性的要求.     

Characterization of Adulterated Milk by Two-Dimensional Infrared Correlation Spectroscopy

A new approach for discrimination of adulterated milk is reported using two-dimensional infrared (IR) correlation spectroscopy by multiway principal component analysis (MPCA) and least squares support vector machines (LS–SVM). First, the synchronous two-dimensional spectra of pure and adulterated milk were calculated. Then, MPCA was used to reduce the dimensions, extract features of two-dimensional correlation data set, and distinguish adulterated milk and pure milk. Finally, a LS-SVM model was developed using the scores of the first thirteen principal components from synchronous two-dimensional correlation spectra computed by MPCA as the input variables. The ratios of correct classification were 100% and 96.3% for calibration set and prediction set, respectively. The area under the receiver operating characteristic curves (ROC) of 0.991 for prediction set was obtained by LS–SVM. The results indicate that two-dimensional correlation infrared spectra combined with MPCA–LS–SVM may be a rapid screening technique for discrimination of adulterated milk with good accuracy.     

Quality Evaluation of Ephedrae herba by near Infrared Spectroscopy

ABSTRACT

A novel method was developed for the quality control of Ephedrae herba by near-infrared (NIR) spectroscopy. First, qualitative models established by discriminant analysis and support vector machine were used for the preliminary screening of unqualified samples of E. herba. Then quantitative models of ephedrine and the total alkali (ephedrine and pseudoephedrine) were established by partial least squares regression and particle swarm optimization based least square support vector machine. The contents of test samples were predicted by the established NIR quantitative models. As a result, the accuracies of unqualified identification were 98.9% by discriminant analysis and 100% by support vector machine. The performance of the particle swarm optimization based least square support vector machine models were better than the partial least squares regression models. The correlation coefficients were both more than 0.98 and relative standard errors of calibrations were less than 9% in the calibration sets of particle swarm optimization based least square support vector machine models. As for the test sets, the correlation coefficients were both more than 0.93 and the relative standard errors of prediction were less than 13%, indicating satisfactory predicted results. All of these results demonstrated that NIR spectroscopy may be a powerful tool for the quality control of E. herba.     

不同载体负载Cu催化剂上甘油氢解制1,2-丙二醇催化性能的研究

采用等体积浸渍法合成了一系列不同载体负载的Cu基催化剂,并研究了其在甘油氢解反应中的催化性能。借助X射线衍射(XRD)、程序升温还原(H₂-TPR)和氨气程序升温脱附(NH₃-TPD)等手段对催化剂进行了表征,同时考察了反应温度、反应压力、反应时间和催化剂重复使用次数对其催化性能的影响。结果表明,载体对催化剂反应性能影响较大,且甘油氢解反应需要适当的酸性;当在催化剂8Cu/γ-Al₂O₃用量为反应原料质量的2.5%、反应温度513 K、反应压力6 MPa、反应时间6 h、反应原料为质量分数为10%的甘油水溶液的条件下,其催化效果最优,甘油转化率最高为88.4%,1,2-丙二醇的选择性可达到86.2%,且催化剂显示了良好的稳定性。     

BaTiO3-BaAl2O4-Al2O3复合载体的制备、表征及其Ni基催化剂催化CH4/CO2重整反应性能

以十六烷基三甲基溴化胺为结构导向剂,采用溶胶-凝胶法制备了BaTiO3-BaAl2O4-Al2O3复合载体,采用X射线衍射、红外光谱、N2吸附-脱附、透射电子显微镜和H2程序升温还原等技术对复合载体进行了表征,并以CH4/CO2重整制合成气为探针反应,考察了不同Ni/BaTiO3-BaAl2O4-Al2O3催化剂的性能.结果表明,BaTiO3-BaAl2O4-Al2O3复合载体具有多孔织构特性和较高的比表面积,BaTiO3和BaAl2O4以晶粒状态分布在复合载体的内外表面,晶粒尺寸在20～50nm的范围,复合载体孔径为10～20nm.复合载体上BaTiO3和BaAl2O4的引入,适度削弱了Ni/BaTiO3-BaAl2O4-Al2O3催化剂中Ni物种与γ-Al2O3间的强相互作用,抑止了NiAl2O4尖晶石的生成;当载体中Ba(Ti)含量为17.33%时,其负载的Ni催化剂上CH4/CO2重整制合成气反应的活性和稳定性最高.     

Support vector machine classification of suspect powders using laser‐induced breakdown spectroscopy (LIBS) spectral data

Classification of suspect powders, by using laser‐induced breakdown spectroscopy (LIBS) spectra, to determine if they could contain Bacillus anthracis spores is difficult because of the variability in their composition and the variability typically associated with LIBS analysis. A method that builds a support vector machine classification model for such spectra relying on the known elemental composition of the Bacillus spores was developed. A wavelet transformation was incorporated in this method to allow for possible thresholding or standardization, then a linear model technique using the known elemental structure of the spores was incorporated for dimension reduction, and a support vector machine approach was employed for the final classification of the substance. The method was applied to real data produced from an LIBS device. Several methods used to test the predictive performance of the classification model revealed promising results. Published 2012. This article is a US Government work and is in the public domain in the USA.     

新型大孔有机膦酸锆的合成及其表征

论文以草甘膦锆(ZrGP)为原料、乙二醇和乙醇混合物为共撑物,介绍了一种新型孔材料的合成方法。利用乙醇将草甘膦锆层板撑开后,乙二醇两端的羟基与草甘膦锆内不同层板上的羧基发生脱水成酯反应,进而生成窗口型孔材料。扫描电镜和XRD分析表明,合成得到的材料内部孔径大约为55 nm左右,是典型的大孔。由于所形成的孔壁由无机骨架和有机链共同组成,该孔材料具有较大的比表面积,达到260 m2.g-1。此外,该孔材料孔内存在大量的可配位基团,因而该材料在吸附、催化等领域会有广阔的应用前景。