铜-5-Br-PAND-TritonX-100体系析相法测定天然水中痕量铜

研究了显色剂 1 - [(5-溴 - 2 -吡啶 )偶氮 ]- 2 ,7-萘二酚 (简称 5- Br- PADN)在 Triton X- 1 0 0存在下 ,用浊点析相分光光度法测定天然水中痕量铜 ( )。在p H8.3～ 9.7的氨水 -氯化铵缓冲溶液中 ,配合物最大吸收波长为 λmax=543nm,相当于 Sandell灵敏度为 0 .0 0 0 1 4μg/cm,铜量在 0～ 2 0μg/2 50 m L范围内符合比尔定律 ,方法已用于测定天然水中的痕量铜。

镍(Ⅱ)-5-Br-PTPF-Triton X-100体系析相法测定天然水中痕量镍(Ⅱ)

非离子表面活性剂应用于"浊点析相法"测定痕量元素已有报道。作者在前文中曾利用本实验室新合成的1-（5-溴-2′-吡啶基）-5-硫代碳酰胺基-3-苯基甲（?）（5-Br-PTPF）试剂,配合非离子表面活性剂,研究了与镍（Ⅱ）的显色反应。发现该试剂对镍的测定有良好的选择性,摩尔吸光率为ε610=3.4×104。为进一步改善灵敏度,以测定ppb数量级的镍,我们在前文试验的基础上,研究了浊点析相分光光度法测定痕量镍的方法。

钴-4-(5-氯-2-吡啶偶氮)-1,3-二氨基苯-Triton X-100体系的析相富集及痕量钴的光度测定

本文研究了TritonX-100在浊点条件下对钴-4-(5-氯-2-吡啶偶氮)-1,3-二氨基苯(5-Cl-PADAB)络合物的析相条件,在pH4.0～6.0介质中,将胶束溶液加热到92±1℃,保持40min,络合物即被TritonX-100相富集。富集液在575nm测定吸光度,钴含量在0～4μg/5ml范围内服从比尔定律,干扰离子可在TritonX-100析相液中加入H_2SO_4消除。拟定的方法灵敏、简捷,已用于不经分离直接测定人发及自来水中痕量钴。

析相光度法测定铁(Ⅲ)的研究

本文研究了铁（Ⅲ）－ＰＥＧ（聚乙二醇－２０００）－铬菁Ｒ－Ｎａ２ＳＯ４体系的析相光度法并应用于测定Ｆｅ（Ⅲ）。最适酸度为４．５～６．５（ＮａＡｃ－ＨＡｃ）缓冲溶液，其络合物的最大吸收位于５６０ｎｍ，表观摩尔吸光系数为５．３６×１０４Ｌｍｏｌ－１ｃｍ－１，Ｆｅ（Ⅲ）浓度在０～４０μｇ范围内服从比尔定律，铁与铬菁Ｒ形式组成为１２的稳定络合物。该方法用于茶叶中铁的测定，获得了满意结果。

析相光度法测定铜（Ⅱ）的研究

本文研究了Ｃｕ（Ⅱ）－ＰＥＧ（聚乙二醇－２０００）－Ｚｉｎｃｏｎ（锌试剂）－（ＮＨ＿４）＿２ＳＯ＿４体系的析相光度法并应用于测定Ｃｕ（Ⅱ）。最宜酸度为ｐＨ５．５～８．５（ＫＨ＿２ＰＯ＿４－Ｋ＿２ＨＰＯ＿４缓冲溶液），其络合物的最大吸收位于６１０ｎｍ，表观摩尔吸光系数为４．０×１０￣４Ｌ·ｍｏｌ￣（－１）·ｃｍ￣（－１），Ｃｕ（Ⅱ）浓度在０～１．５ｍｇ／Ｌ范围内服从比尔定律，铜与Ｚｉｎｃｏｎ形式组成为１：２的稳定的蓝色络合物。该方法用于铝合金中的铜的测定，获得了满意结果。

析相光度法测定铜(Ⅱ)的研究

本文研究了Cu（Ⅱ）－PEG（聚乙二醇-2000）－DDTC（铜试剂）－（NH4）2SO4体系的析相光度法并应用于测定Cu（Ⅱ）。最宜酸度为3．6—9．0（NaAc－HAc，NH4Cl－NH3·H2O）缓冲溶液，其络合物的最大吸收位于450nm，表观摩尔吸光系数为9．05×103L·mol－1·cm-1，Cu（Ⅱ）浓度在0—30μg／L范围内服从比耳定律，铜与DDTC形式组成为1：2的稳定络合物。该方法用于铝合金中铜的测定，获得了满意结果。

析相液—液萃取法

析相液—液萃取法是基于胶束水溶液中的析相(Phase Separation)法,国内外已有不少研究报告发表,本文就此题作论述,以了解其发展的概貌及趋向。 析相液—液萃取法有形成凝聚体的析相法和“浊点”析相法两种。 1 形成凝聚体的析相法 形成凝聚体的作用,发生于某些物质的离子在带电荷的表面活性剂(如季铵盐阳离子)或其它物质的水溶液。开始时,这种物质的离子与胶束聚合成业微观的晶簇,接着聚合成显微滴,再进一步凝聚。这些显微滴能以富含表面活性剂的连续相析出,因此,形成两个明显的相。当再加入适当电解质时,富含表面活性剂的相能沉淀或絮凝析出。除了阳离子和阴离子表面活性剂外,蛋白质、高聚物和微乳液也有形成凝聚体的行为。Dubin等根据表面电荷的不同,用来分离血红蛋白质。

聚乙二醇-钍试剂-硫酸钠体系中非有机溶剂萃取光度法测定铁

本文研究了铁（Ⅲ）－ＰＥＧ（聚乙二醇－２０００）－钍试剂－Ｎａ２ＳＯ４体系的析相光度法并应用于测定Ｆｅ（Ⅲ），最适酸度为４．６（ＮａＡｃ－ＨＡｃ）缓冲溶液，其络合物的最大吸收位于５６６ｎｍ，表观摩尔吸光系数为８．０６×１０３Ｌ·ｍｏｌ－１·ｃｍ－１。Ｆｅ（Ⅲ）浓度在０—３０μｇ·ｍＬ－１范围内服从比耳定律，该方法用于发样中铁的测定。

Clustering analysis algorithm for security supervising data based on semantic description in coal mines

In order to mine production and security information from security supervising data and to ensure security and safety involved in production and decision-making,a clustering analysis algorithm for security supervising data based on a semantic description in coal mines is studied.First,the semantic and numerical-based hybrid description method of security supervising data in coal mines is described.Secondly,the similarity measurement method of semantic and numerical data are separately given and a weight-based hybrid similarity measurement method for the security supervising data based on a semantic description in coal mines is presented.Thirdly,taking the hybrid similarity measurement method as the distance criteria and using a grid methodology for reference,an improved CURE clustering algorithm based on the grid is presented.Finally,the simulation results of a security supervising data set in coal mines validate the efficiency of the algorithm.

Application of Integration of Spatial Statistical Analysis with GIS to Regional Economic Analysis

This paper summarizes a few spatial statistical analysis methods for to measuring spatial autocorrelation and spatial association, discusses the criteria for the identification of spatial association by the use of global Moran Coefficient, Local Moran and Local Geary. Furthermore, a user-friendly statistical module, combining spatial statistical analysis methods with GIS visual techniques, is developed in Arcview using Avenue. An example is also given to show the usefulness of this module in identifying and quantifying the underlying spatial association patterns between economic units.

RELATIVE PRINCIPLE COMPONENT AND RELATIVE PRINCIPLE COMPONENT ANALYSIS ALGORITHM

In this letter,the new concept of Relative Principle Component (RPC) and method of RPC Analysis (RPCA) are put forward. Meanwhile,the concepts such as Relative Transform (RT),Ro-tundity Scatter (RS) and so on are introduced. This new method can overcome some disadvantages of the classical Principle Component Analysis (PCA) when data are rotundity scatter. The RPC selected by RPCA are more representative,and their significance of geometry is more notable,so that the application of the new algorithm will be very extensive. The performance and effectiveness are simply demonstrated by the geometrical interpretation proposed.

Determination of constituents of essential oil from Angelica sinensis by gas chromatographymass spectrometry

Gas chromatographymass spectrometry (GC-MS) coupled with chemometric resolution upon two- dimensional data was employed to analyze the constituents of essential oils of Angelica sinensis. Constituents in essential oils of Angelica sinensis root were identified by GC-MS with the help of subwindow factor analysis (SFA) method resolving two-dimensional original data into mass spectra and chromatograms. 76 of 97 separated constituents in essential oil of Angelica sinensis root were identified and quantified, and they account for about 91.36% of the total content. The results show that ligustilide, butylene phthalide, 2-methoxy-4-vinylphenol, carvacrol, allo-ocimene,2,6,6-trimethylbicyclo-[3,1,1]hept-2-ene are the main constituents in essential oil of Angelica sinensis root.

Predicting Arabidopsis thaliana Gene Function by Transitiving Co-expression in Shortest-path

The present paper predicted the function of unknow genes by analyzing the co-expression data of Arabidopsis thaliana from biological pathway based on the shortest-path algorithm. This paper proposed that transitive co-expression among genes can be used as an important attribute to link genes of the same biological pathway. The genes from the same biological pathway with similar functions are strongly correlated in expression. Moreover,the function of unknown genes can be predicted by the known genes where they are strongly correlated in expression lying on the same shortest-path from the biological pathway. Analyzing the Arabidopsis thaliana from the biological pathway,this study showed that this method can reliably reveal function of the unknown Arabidopsis thaliana genes and the approach of predicting gene function by transitiving co-expression in shortest-path is feasible and effective.

Recovery of Dyestuffs from Dilute Solution with Two-phase Electrophoresis

Two-phase electrophoresis was used to separate the dyestuffs from their dilute solutions. Several dyestuffs (naphthol green B, acid-chrome blue K, methyl blue and direct fast torquoise blue GL, and n-butanol) were treated in a self-designed experimental setup and the mass transfer characteristics in this process were studied. The results confirm the potential of this technique for recovering dyestuffs from their dilute solutions.

Multi-resolution graph-based clustering analysis for lithofacies identifi cation from well log data: Case study of intraplatform bank gas fi elds, Amu Darya Basin

In this study, we used the multi-resolution graph-based clustering （MRGC） method for determining the electrofacies （EF） and lithofacies （LF） from well log data obtained from the intraplatform bank gas fields located in the Amu Darya Basin. The MRGC could automatically determine the optimal number of clusters without prior knowledge about the structure or cluster numbers of the analyzed data set and allowed the users to control the level of detail actually needed to define the EF. Based on the LF identification and successful EF calibration using core data, an MRGC EF partition model including five clusters and a quantitative LF interpretation chart were constructed. The EF clusters 1 to 5 were interpreted as lagoon, anhydrite flat, interbank, low-energy bank, and high-energy bank, and the coincidence rate in the cored interval could reach 85%. We concluded that the MRGC could be accurately applied to predict the LF in non-cored but logged wells. Therefore, continuous EF clusters were partitioned and corresponding LF were characteristics ＆different LF were analyzed interpreted, and the distribution and petrophysical in the framework of sequence stratigraphy.

Flame retardancy and its mechanism of polymers flame retarded by DBDPE/Sb_2O_3

The flammability characterization and thermal composition of polymers flame retarded by decabromodiphenylethane (DBDPE) and antimony trioxide (Sb2O3) were studied by cone calorimeter and thermogravimetry (TG). The results show that ABS/DBDPE/Sb2O3 has the similar flammability parameters and thermal composition curves to ABS/DBDPO/Sb2O3. It suggests that DBDPE/Sb2O3 has the similar flame retardant behavior to DBDPO/Sb2O3. The heat release rate (HRR) and the effect heat combustion (EHC) curves of polymers flame retarded by DBDPE/Sb2O3 all decrease, but the mass loss rate (MLR) curve slightly increase. It shows that the decrease of HRR is not due to the increase of char formation ratio but the generation of incombustible gases. The major flame retardant mechanism of DBDPE/Sb2O3 is gas phase flame retardant mechanism. Increasing content of Sb2O3 in DBDPE/Sb2O3 can improve the flame retardant property and thermal stability of acrylonitrile butadiene styrene. Sb2O3 has a good synergistic effect with DBDPE.

Multi-attributed decision making for mining methods based on grey system and interval numbers

In the case of unknown weights, theories of multi-attributed decision making based on interval numbers and grey related analysis were used to optimize mining methods. As the representative of independence for the indicator, the smaller the correlation of indicators is, the greater the weight is. Hence, the weights of interval numbers of indicators were determined by using correlation coefficient. Relative closeness based on positive and negative ideal methods was calculated by introducing distance between interval numbers, which made decision making more rational and comprehensive. A new method of ranking interval numbers based on normal distribution was proposed for the optimization of mining methods, whose basic properties were discussed. Finally, the feasibility and effectiveness of this method were verified by theories and practice.

Component Analysis of Volatile Oil of Garlic from Different Districts and Assay of Allicin Content

[ Objective] The aim was to study the chemical component of volatile oil of garlic in different districts. [ Method] GC-MS was used to an- alyze the composition of the garlic volatile oil in Guiyang, Guizhou Majiang, Shandong, Yunnan and Chongqing and the HPLC method was used to assay the content of gadicin. [ Result]Gadicin in different essential oil had the highest content but varied a lot. The sampling amount of garlicin be- tween 0.562 and 2.810 μg was in a good linear relation （R =0.999 2, n = 5 ） with peak area, the average recovery rate was 99.39, RSD = 1.76%. [ Conclusion] GC-MS can be used to analysis the composition of essential oil quickly and effectively. The liquid chromatographic analysis of garlicin was simple, reliable and reproducible. The study provided the theoretical basis for selecting garlic in gadic flavor oil production and improving quality of gadicin oil.

Temporal-spatial cross-correlation analysis of non-stationary near-surface wind speed time series

Temporal-spatial cross-correlation analysis of non-stationary wind speed time series plays a crucial role in wind field reconstruction as well as in wind pattern recognition.Firstly,the near-surface wind speed time series recorded at different locations are studied using the detrended fluctuation analysis(DFA),and the corresponding scaling exponents are larger than 1.This indicates that all these wind speed time series have non-stationary characteristics.Secondly,concerning this special feature( i.e.,non-stationarity)of wind signals,a cross-correlation analysis method,namely detrended cross-correlation analysis(DCCA) coefficient,is employed to evaluate the temporal-spatial cross-correlations between non-stationary time series of different anemometer pairs.Finally,experiments on ten wind speed data synchronously collected by the ten anemometers with equidistant arrangement illustrate that the method of DCCA cross-correlation coefficient can accurately analyze full-scale temporal-spatial cross-correlation between non-stationary time series and also can easily identify the seasonal component,while three traditional cross-correlation techniques(i.e.,Pearson coefficient,cross-correlation function,and DCCA method) cannot give us these information directly.