一个用于气候描述的新载荷相关模式

用原变量正交分解作为建立一个新载荷相关模式的基础 ,以所有第一载荷相关为正显著相关作为气候分类的判据 ,对分类结果进行气候描述 ,即描述气候时空变化的特性。可将此方法运用于其它含有时空观测数据的领域。

Regression Relationship between WI and FMC at Different Growth Periods of Sawtooth Oaks Leaf

[Objective] The aim was to study the regression relationship between water index （WI） and fuel moisture content （FMC） of different growth periods of sawtooth oaks leaf.[Method] Taking sawtooth oaks in Huaguo Mountain,Lianyungang City as research object,the sensitivity of WI to leaf FMC was studied at leaf level,and statistical characteristics were analyzed.[Result] The WI of sawtooth oaks leaves was sensitive to the changes of FMC,and the line regression level between them was significant.A fitting curve between leaf FMC and WI was obtained.[Conclusion] The research provides reference for acquisition methods of vegetation water remote sensing within the range of study area.

Efficient Separation of Ar and Kr from Environmental Samples for Trace Radioactive Noble Gas Detection

Radioactive noble-gas isotopes, SSKr （half-life tl/2=10.8 y）, 39Ar （tl/2=269 y）, and SlKr （t1/2-229,000 y）, are ideal tracers and can be detected by atom trap trace analysis （ATTA）, a laser-based technique, from environmental samples like air and groundwater. Prior to ATTA measurements, it is necessary to efficiently extract krypton and argon gases from samples. Using a combination of cryogenic distillation, titanium chemical reaction and gas chromatography, we demonstrate that we can recover both krypton and argon gases from 1-10 L ＂air-like＂ samples with yields in excess of 90% and 98%, respectively, which meet well the requirements for ATTA measurements. A group of testing samples are analyzed to verify the performance of the system, including two groundwater samples obtained from north China plain.

Qualitative and Quantitative Analysis of Linoleic Acid in Polygonati Rhizoma

Objective To explore the major compound in Polygonati Rhizoma(Huang Jing,黄精)for quality control.Methods The major compound was isolated and analyzed by liquid chromatography-mass spectrometry(LC-MS),and subsequently further identified by nuclear magnetic resonance(NMR).Thin layer chromatography(TLC)was optimized based on the previous methods reported in the Chinese Pharmacopeia(2015 edition).Results The major compound was isolated from the natural material and identified as linoleic acid.A high performance liquid chromatography(HPLC)method with robust linearity(R2=0.9997),specificity,precision,stability,repeatability and recovery was developed for linoleic acid determination.TLC chromatogram was improved significantly after optimization for qualitative analysis.Conclusions The optimized TLC method is practical and can be adopted for quality control of Polygonati Rhizoma(Huang Jing,黄精).The levels of linoleic acid vary between species of Polygonati Rhizoma(Huang Jing,黄精),with Polygonatum cyrtonema Hua(Jiang Xing Huang Jing,姜型黄精)showing the highest contents.This study provides valuable information for quality control of Polygonati Rhizoma(Huang Jing,黄精).

Abundance quantification by independent component analysis of hyperspectral imagery for oil spill coverage calculation

The estimation of oil spill coverage is an important part of monitoring of oil spills at sea.The spatial resolution of images collected by airborne hyper-spectral remote sensing limits both the detection of oil spills and the accuracy of estimates of their size.We consider at-sea oil spills with zonal distribution in this paper and improve the traditional independent component analysis algorithm.For each independent component we added two constraint conditions:non-negativity and constant sum.We use priority weighting by higher-order statistics,and then the spectral angle match method to overcome the order nondeterminacy.By these steps,endmembers can be extracted and abundance quantified simultaneously.To examine the coverage of a real oil spill and correct our estimate,a simulation experiment and a real experiment were designed using the algorithm described above.The result indicated that,for the simulation data,the abundance estimation error is 2.52% and minimum root mean square error of the reconstructed image is 0.030 6.We estimated the oil spill rate and area based on eight hyper-spectral remote sensing images collected by an airborne survey of Shandong Changdao in 2011.The total oil spill area was 0.224 km^2,and the oil spill rate was 22.89%.The method we demonstrate in this paper can be used for the automatic monitoring of oil spill coverage rates.It also allows the accurate estimation of the oil spill area.

DIMENSIONALITY REDUCTION FOR HYPERSPECTRAL IMAGERY BASED ON FASTICA

The high dimensions of hyperspectral imagery have caused burden for further processing. A new Fast Independent Component Analysis (FastICA) approach to dimensionality reduction for hyperspectral imagery is presented. The virtual dimensionality is introduced to determine the number of dimensions needed to be preserved. Since there is no prioritization among independent components generated by the FastICA,the mixing matrix of FastICA is initialized by endmembers,which were extracted by using unsupervised maximum distance method. Minimum Noise Fraction (MNF) is used for preprocessing of original data,which can reduce the computational complexity of FastICA significantly. Finally,FastICA is performed on the selected principal components acquired by MNF to generate the expected independent components in accordance with the order of endmembers. Experimental results demonstrate that the proposed method outperforms second-order statistics-based transforms such as principle components analysis.

Effect of a Novel Nucleating Agent on Isothermal Crystallization of Poly（L-lactic acid）

The effect of a novel active nucleating agent(TBC8-eb) on the isothermal crystallization of poly(L-lactic acid) (PLLA) was studied by differential scanning calorimetry(DSC) and Fourier transform infrared spectroscopy(FTIR) . The analysis on kinetics demonstrates that TBC8-eb can not only accelerate the crystallization rate but also transform most of the original spherulite crystals of PLLA into sheaf-like crystals. Furthermore,the free energy of folding(σe) of PLLA and PLLA with TBC8-eb is 0.15 and 0.06 J·m-2,respectively,which suggests that the addition of TBC8-eb favors the regular folding of molecule chains in the crystallization of PLLA,improv-ing its crystallization rate. The FTIR results show that TBC8-eb can accelerate the conformational ordering of PLLA in the isothermal crystallization. The conformational ordering of PLLA nucleated with TBC8-eb begins with the interchain interaction of CH3,and then a short helix emerges where a couple of CH3 groups interact.

Spectroscopic Multicomponent Analysis Using Multi-objective Optimization for Variable Selection

The multiple determination tasks of chemical properties are a classical problem in analytical chemistry. The major problem is concerned in to find the best subset of variables that better represents the compounds. These variables are obtained by a spectrophotometer device. This device measures hundreds of correlated variables related with physicocbemical properties and that can be used to estimate the component of interest. The problem is the selection of a subset of informative and uncorrelated variables that help the minimization of prediction error. Classical algorithms select a subset of variables for each compound considered. In this work we propose the use of the SPEA-II （strength Pareto evolutionary algorithm II）. We would like to show that the variable selection algorithm can selected just one subset used for multiple determinations using multiple linear regressions. For the case study is used wheat data obtained by NIR （near-infrared spectroscopy） spectrometry where the objective is the determination of a variable subgroup with information about E protein content （%）, test weight （Kg/HI）, WKT （wheat kernel texture） （%） and farinograph water absorption （%）. The results of traditional techniques of multivariate calibration as the SPA （successive projections algorithm）, PLS （partial least square） and mono-objective genetic algorithm are presents for comparisons. For NIR spectral analysis of protein concentration on wheat, the number of variables selected from 775 spectral variables was reduced for just 10 in the SPEA-II algorithm. The prediction error decreased from 0.2 in the classical methods to 0.09 in proposed approach, a reduction of 37%. The model using variables selected by SPEA-II had better prediction performance than classical algorithms and full-spectrum partial least-squares.

Quantitative Analysis Using Fourier Transform Ion Cyclotron Resonance Mass Spectrometry and Correlation between Mass Spectrometry Data and Sulfur Content of Crude Oils

Fourier transform ion cyclotron resonance mass spectrometry(FT-ICR MS) has become a powerful tool for analyzing the detailed composition of petroleum samples. However, the correlation between the numerous peaks obtained by FT-ICR MS and bulk properties of petroleum samples is still a challenge. In this study, the internal standard method was applied for the quantitative analysis of four straight-run vacuum gas oils(VGO) by atmospheric pressure photoionization(APPI) FT-ICR MS. The heteroatom class distribution of these VGO samples turned to be different when the concentration changed. Linear relationship between the normalized abundance and the concentration of VGO samples was identified for the total aromatic compounds, aromatic hydrocarbons, S1 and N1 species. The differences of the response factors were also discussed. The sulfur contents of a series of crude oils were proved to be linear with the FT-ICR MS data calibrated by the response factor of S1 species. This study demonstrated the feasibility of the internal standard method in quantitative analysis with APPI FT-ICR MS, and the bulk properties of petroleum samples could be correlated directly with the FT-ICR MS data.

Analysis of Nitrosamines in Organic Foods

Nitrosamines are classified by IARC as Group 2B carcinogens. Usually they might be present in organic foods as products of reaction between secondary amines and nitrosation system. The aim of the study was to test the concentration of nitrosamines in Bulgarian products. High performance liquid chromatography with UV detector was used for identification and quantitation. A standard solution of N-nitrosodiethanolamine was used as a reference substance and in the validation procedure of samples. The limit of detection of the method was determined to 14× 10^-9 g/mL. The results of the testing showed that analyzed organic foods produced in Bulgaria did not contain nitrosamines above the limit of detection of the method.

Discrimination of rice panicles by hyperspectral reflectance data based on principal component analysis and support vector classification

Detection of crop health conditions plays an important role in making control strategies of crop disease and insect damage and gaining high-quality production at late growth stages. In this study, hyperspectral reflectance of rice panicles was measured at the visible and near-infrared regions. The panicles were divided into three groups according to health conditions： healthy panicles, empty panicles caused by Nilaparvata lugens St^l, and panicles infected with Ustilaginoidea virens. Low order derivative spectra, namely, the first and second orders, were obtained using different techniques. Principal component analysis （PCA） was performed to obtain the principal component spectra （PCS） of the foregoing derivative and raw spectra to reduce the reflectance spectral dimension. Support vector classification （SVC） was employed to discriminate the healthy, empty, and infected panicles, with the front three PCS as the in- dependent variables. The overall accuracy and kappa coefficient were used to assess the classification accuracy of SVC. The overall accuracies of SVC with PCS derived from the raw, first, and second reflectance spectra for the testing dataset were 96.55%, 99.14%, and 96.55%, and the kappa coefficients were 94.81%, 98.71%, and 94.82%, respectively. Our results demonstrated that it is feasible to use visible and near-infrared spectroscopy to discriminate health conditions of rice panicles.