PSO-LSSVM对LIBS定量分析精度的提高

针对土壤定量分析受基体效应影响大，LIBS定量分析精度不佳等问题，采用粒子群算法对LSSVM进行优化，提高模型的精确度。选取Pb Ⅰ 405.78 nm和Cr Ⅰ 425.44 nm作为分析谱线进行分析。采集十二个不同浓度样品的特征光谱，每个浓度样品在不同点采集20组数据，将其中17组数据设为训练集，3组数据设为预测集，用LSSVM和PSO-LSSVM两种方法建立定标模型。对比两种模型的拟合相关系数（R2）、训练集均方根误差（RMSEC）和预测集均方根误差(RMSEP)。由于自吸收效应的影响，随着浓度的增加，预测值逐渐低于实际值，LSSVM定标模型的拟合程度较低，无法达到实验要求，模型性能有待提高。利用粒子群算法对LSSVM的模型参数惩罚系数和核函数参数进行优化，得到最佳的参数组合，Pb元素为(8 096.8, 138.865 7)，Cr元素为(4 908.6, 393.563 5)，用最佳的参数组合构建LSSVM的定标模型。相比于LSSVM，PSO-LSSVM定标模型的精确度更高，Pb和Cr元素的R2提高到了0.982 8和0.985 0，拟合效果明显提升。Pb和Cr元素的训练集均方根误差由0.026 0 Wt%和0.027 2 Wt%下降到0.022 4 Wt%和0.019 1 Wt%，预测集均方根误差由0.101 8 Wt%和0.078 8 Wt% 下降到0.045 8 Wt%和0.042 0 Wt%，模型的稳定性进一步提高。说明PSO-LSSVM算法能够更好地降低土壤基体效应和自吸收效应带来的影响，提高分析结果的精确度与稳定性。     

A Robust Near-Infrared Calibration Model for the Determination of Chlorophyll Concentration in Tree Leaves with a Calibration Transfer Method

A method based on piecewise direct standardization was developed to directly predict leaf chlorophyll concentrations by correction of near-infrared spectra to construct a robust calibration model. Chinar, camphor, and gingko leaves collected from two growth intervals were evaluated. Spectral pretreatment methods and wavelength selection were investigated. The first derivative combined with stability competitive adaptive reweighted sampling before piecewise direct standardization provided the best performance. Under the optimized parameters, the root mean square error of prediction was significantly reduced by using piecewise direct standardization. This study demonstrates that the calibration model may be used to rapidly characterize chlorophyll concentrations across species and growth intervals.     

2型糖尿病患者尿液的代谢组学研究

目的 从代谢组学角度分析并寻找2型糖尿病（T2DM）患者可能的代谢标记物。方法 选取30例初诊、或有糖尿病史经药物治疗控制不理想且无并发症的T2DM 患者,另选取30例性别、年龄匹配的健康者为正常对照。收集清晨空腹中段尿,以气相色谱- 质谱联用（GC-MS）技术对尿液样本进行代谢图谱分析,正交偏最小二乘法判别研究尿液内源性化合物在两组间的差异。结果 T2DM 组和正常对照组尿液代谢谱明显分离。与正常对照组比较,T2DM 组尿液2,3,4- 三羟基丁酸、肌醇、D- 葡萄糖、D- 葡萄糖酸及尿素含量升高（P＜0.05 或0.01）,马尿酸含量减少（P＜0.01）。结论 代谢组学检查提示T2DM 患者尿液中代谢标志物为2,3,4- 三羟基丁酸、肌醇、马尿酸、D-葡萄糖、D- 葡萄糖酸及尿素,观察这些标志物含量的变化有助于T2DM 的临床诊断及发病机制研究。     

Comparison of two-dimensional integration methods for shape reconstruction from gradient data

As a requisite and key step in some gradient-based measurement techniques, the reconstruction of the shape, more generally the scalar potential, from the measured gradient data has been studied for many years. In this work, three types of two-dimensional integration methods are compared under various conditions. The merits and drawbacks of each integration method are consequently revealed to provide suggestions in selection of a proper integration method for a particular application.     

An improved ensemble learning machine for biological activity prediction of tyrosine kinase inhibitors

Boosting is one of the most important strategies in ensemble learning because of its ability to improve the stability and performance of weak learners. It is nonparametric, multivariate, fast and interpretable but is not robust against outliers. To enhance its prediction accuracy as well as immunize it against outliers, a modified version of a boosting algorithm (AdaBoost R2) was developed and called AdaBoost R3. In the sampling step, extremum samples were added to the boosting set. In the robustness step, a modified Huber loss function was applied to overcome the outlier problem. In the output step, a deterministic threshold was used to guarantee that bad predictions do not participate in the final output. The performance of the modified algorithm was investigated with two anticancer data sets of tyrosine kinase inhibitors, and the mechanism of inhibition was studied using the relative weighted variable importance procedure. Investigating the effect of base learner's strength reveals that boosting is only successful using the classification and regression tree method (a weak to moderate learner) and does not have a significant effect using the radial basis functions partial least square method (a strong base learners). Copyright © 2015 John Wiley & Sons, Ltd.     

Hydrolysis kinetics of silane coupling agents studied by near-infrared spectroscopy plus partial least squares model

Abstract

A method of Fourier transform near-infrared (FT-NIR) spectroscopy combined with partial least squares (PLS) model was successfully applied to investigate the hydrolysis kinetics of four kinds of silane coupling agents (phenyltriethoxysilane, vinyltriethoxysilane, 3-mercaptopropyltriethoxysilane, 3-chloropropyltriethoxysilane) in an acid-catalyzed EtOH system. The fast scanning speed and high sensitivity of the FT-NIR spectroscopy, and the powerful data processing ability of the PLS, enabled the method to quantitatively and accurately catch the fast changing H₂O concentration during the hydrolysis processes without delay, realizing the study of the fast-paced hydrolysis reactions of the silane coupling agents. The results showed that electrophilic substitution occurred in the hydrolysis reactions, which followed second-order reactions and greatly depend on the catalyst concentration and reaction temperature. The hydrolysis rate constants, activation energy, and Arrhenius Frequency factors were gained. In conclusion, the FT-NIR PLS model is a powerful tool for hydrolysis kinetics researching of the silane coupling agents.     

LIQUID CRYSTALLINE POLYMERS. IV. THERMOTROPIC LIQUID CRYSTALLINE POLY(ARYLIDENE-ETHER)S AND COPOLYMERS CONTAINING N-METHYLPIPERIDONE LINKED TO THE MAIN CHAIN THROUGH SPACERS OF VARIOUS LENGTHS

Two novel series of poly(arylidene-ether)s and copoly(arylidene-ether)s were synthesized from N-methylpiperidone and/or cyclohexanone respectively. The first series (homopolymers) was derived from 4,4′-diformyl-α,ω-diphenoxyalkane or 4,4′-diformyl-2,2′ dimethoxy-α,ω-diphenoxyalkane with N-methylpiperidone. The second series (copolymers) was derived from the diphenoxyalkanes (I–VIII) with N-methylpiperidone and cyclohexanone. The inherent viscosities of the polymers thus prepared were in the range of 0.37–0.98 dI/g. The majority of the polymers and copolymers are soluble in chlorinated hydrocarbons. DSC measurements and microscope observation under polarized light demonstrate that this type of poly(arylidene-ether)s form nematic mesophase over a wide temperature range in contrast to the corresponding copoly(arylidene-ether)s. All of the polymers and copolymers exhibited thermotropic liquid crystalline properties. In most cases, the mesophase extends up to 315°C, where thermal decomposition prevents further observation. The morphology of polymer IXb and copolymer XIb as a selected example was examined by scanning electronic microscope.     

Simultaneous Anodic Stripping Voltammetric Determination of Pb and Cd,Using a Vibrating Gold Microwire Electrode,Assisted by Chemometric Techniques

Simultaneous anodic stripping voltammetric determination of Pb and Cd is restricted on gold electrodes as a result of the overlapping of these two peaks. This work describes the quantitative determination of a binary mixture system of Pb and Cd, at low concentration levels (up to 15.0 and 10.0 µg L^?1 for Pb and Cd, respectively) by differential pulse anodic stripping voltammetry (DPASV; deposition time of 30 s), using a green electrode (vibrating gold microwire electrode) without purging in a chloride medium (0.5 M NaCl) under moderate acidic conditions (HCl 1.0 mM), assisted by chemometric tools. The application of multivariate curve resolution alternating least squares (MCR‐ALS) for the resolution and quantification of both metals is shown. The optimized MCR‐ALS models showed good prediction ability with concentration prediction errors of 12.4 and 11.4 % for Pb and Cd, respectively. The quantitative results obtained by MCR‐ALS were compared to those obtained with partial least squares (PLS) and classical least squares (CLS) regression methods. For both metals, PLS and MCR‐ALS results are comparable and superior to CLS. For Cd, as a result of the peak shift problem, the application of CLS was unsuitable. MCR‐ALS provides additional advantage compared to PLS since it estimates the pure response of the analytes signal. Finally, the built up multivariate calibration models, based either in MCR‐ALS or PLS regression, allowed to quantify concentrations of Pb and Cd in surface river water samples, with satisfactory results.