Image analysis in the electron microscopy of cellulose protofibrils II. Digital correlation methods

Electron micrographs of parallel arrays of negatively stained ramie cellulose protofibrils were analyzed using the two-dimensional digital autocorrelation function (ACF). The method is based upon the statistical analysis of images in real space. The ACF shows strong parallel streaks of high correlation, and the lateral distance between adjacent streaks allows the mean interfibrillar distance to be estimated as 3.7 nm. The intensity profile along the streaks shows a weak modulation with peaks occurring at integral multiples of 3 or 6 nm. These results provide direct evidence that there is a regular axial texture in the protofibrils, and corroborate the conclusions previously drawn from optical diffraction analysis. Using the difference vectors found in the ACF it has been possible to reduce the picture noise level by linear integration, thereby obtaining an enhanced image. A preliminary result obtained in this way suggests that the projected protofibril morphology associated with the observed axial periodicity is a ribbon-like zigzag structure. Possible applications of the method for future work are discussed.     

马来酸酐与二苄基马来酸酯共存体系的荧光分析法研究

本实验测定了二苄基马来酸酯甲醇溶液的荧光光谱，并发现马来酸酐对该荧光体系有猝灭作用，通过对不同马来酸酐浓度与各种浓度的二苄基马来酸酯甲醇溶液在４００ｎｍ处荧光强度数据的分析，发现马来酸酐的浓度与荧光猝灭程度在一定范围内呈良好的线型关系。据此，提出了用荧光猝灭法对马来酸酐及二苄基马来酸酯的定量分析     

Gas chromatographic system equipped with a mass detector and a selective nitrogen-phosphorous detector operating simulataneously in the analysis of pesticide residues

The possibility to perform gas chromatographic analysis using both a mass detector and a selective nitrogen-phosphorous detector will enable highly sensitive analytical results and an optimal identification reliability. In this work we describe an easily workable technical solution, which has been accomplished in our laboratory and the application of the above system to analytical procedures for the detection and determination of nitrogenous herbicides in drinking water and phosphorylated pesticides in agricultural products is discussed.     

Direct analysis of alkylnaphthalenes in crude oils by two-dimensional capillary gas chromatography

Summary Diaromatics are geochemically significant constituents of crude oils. Their determination is usually achieved by elaborate prefractionation methods, such as medium pressure liquid chromatography and HPLC, prior to capillary gas chromatography. The present contribution describes the quantitative analysis of methylnaphthalenes, ethylnaphthalenes, and dimethylnaphthalenes in selected crude oils by two-dimensional capillary GC. Since the method does not comprise any work-up procedure the determination of geochemical parameters (alkylnaphthalene concentration ratios) is performed on the original, untreated crude oil samples. Accordingly, the analytical results reflect the original composition. The influence by evaporational losses in the laboratory is minimized.     

Nutritional parameters of commercially available milk samples by FTIR and chemometric techniques

A chemometric study on the prediction of the main nutritional aspects of milk has been carried out by using fourier transform infrared spectroscopy (FTIR) attenuated total reflectance (ATR) measurements of commercially available milk samples of different types. Whole, semi and skimmed milks, enriched or not with calcium, vitamins or modified by alteration of lipid or sugar composition were considered. After evaluating different strategies for data acquisition and ATR cleaning between samples, hierarchical cluster analysis (HCA) was carried out for classification of samples in order to choose the calibration set. The prediction capabilities of partial least squares (PLS) data treatment were evaluated in order to obtain information about total fat, total protein, total carbohydrates (CH), calories and calcium. On using the mean square error of cross-validation and prediction as control variables, a critical evaluation were made about the calibration set to be used, the spectral range to be considered and the data treatment (PLS-1 or PLS-2) to be performed. By selecting a calibration set of 33 samples the properties of 48 samples were predicted with relative precision of triplicates of 0.062, 0.040 and 0.039% w/v for total fat, protein and carbohydrates, and 0.66 kcal/100 ml for calories, and 2.1 mg of Ca/100 ml. The mean difference (d_x−y) between predicted and actual values and standard deviation of mean differences (s_x−y), were of 0.06 (0.38), 0.03 (0.18) and −0.15 (0.41), being s_x−y values between brackets, for total fat, proteins and carbohydrates, 0.06 (3.8) kcal/100 ml for calories and −4.5 (9) mg/100 ml for calcium.The sensitivity and selectivity of the methodology developed were evaluated on terms of the net analyte signal. Selectivity factors ranging from 2 to 7.6% have been calculated for the five parameters considered.     

About compensation effect by thermal decomposition of some catalyst precursors

Summary In order to obtain catalysts, the thermal decomposition of the precursors is a compulsory step. However, kinetic analysis of the decomposition data obtained under non-isothermal conditions lead very seldom to the intimate reaction mechanism. There is also a lack of information because in non-isothermal kinetics, the compensation effect, is rather a rule and unfortunately a source of debate. In order to discriminate between these processes, and the influence of conversion, respectively temperature on the reaction rate, the NPK (non-parametric kinetic - Sempere and Nomen) method was used. This method is based on the singular value decomposition algorithm (SVD) applied on the matrix of reaction rate at corresponding conversion and temperature. This method allows a less speculative determination of the conversion functions and of the kinetic parameters.     

Development and validation of methods for the trace determination of phthalates in sludge and vegetables

A routine method which is simple, quick and precise has been set up and validated for phthalate analysis in environmental samples (tomato plants and sewage sludges). Six phthalates have been studied simultaneously: dimethylphthalate, diethylphthalate, di-n-butylphthalate, n-butylbenzylphthalate, di-2-ethyl-hexyl phthalate (DEHP) and di-n-octylphthalate. Optimization of sample, solvent extraction uses a Soxtec apparatus and extract purification with an a solid-phase extraction cartridge allows between 90 and 110% recovery of phthalates. Precise, sensitive and selective identification and quantifying of analytes is by GC-MS in the single ion monitoring mode. This protocol allows analytes with concentrations as low as 10 microg/kg dry matter (DM) to be determined from small (1-2 g DM) samples. This analytical method has been applied to the phthalate transfer study for agricultural recycling of sludges, where phthalate bioavailability has been studied in aquiculture using two types of experiments. Tomatoes have been grown in containers where the trace organics have been directly introduced as pure substances, and in a second experiment under the same growth conditions, sewage sludge has replaced the pure substances. Transfer of these trace organics has been followed into the various parts of the tomato plant and in general only the DEHP is worthy of note although its percentage transfer remains very low even in an experiment designed to maximize this.     

Applications of maximum likelihood principal component analysis: incomplete data sets and calibration transfer

The application of a new method to the multivariate analysis of incomplete data sets is described. The new method, called maximum likelihood principal component analysis (MLPCA), is analogous to conventional principal component analysis (PCA), but incorporates measurement error variance information in the decomposition of multivariate data. Missing measurements can be handled in a reliable and simple manner by assigning large measurement uncertainties to them. The problem of missing data is pervasive in chemistry, and MLPCA is applied to three sets of experimental data to illustrate its utility. For exploratory data analysis, a data set from the analysis of archeological artifacts is used to show that the principal components extracted by MLPCA retain much of the original information even when a significant number of measurements are missing. Maximum likelihood projections of censored data can often preserve original clusters among the samples and can, through the propagation of error, indicate which samples are likely to be projected erroneously. To demonstrate its utility in modeling applications, MLPCA is also applied in the development of a model for chromatographic retention based on a data set which is only 80% complete. MLPCA can predict missing values and assign error estimates to these points. Finally, the problem of calibration transfer between instruments can be regarded as a missing data problem in which entire spectra are missing on the ‘slave’ instrument. Using NIR spectra obtained from two instruments, it is shown that spectra on the slave instrument can be predicted from a small subset of calibration transfer samples even if a different wavelength range is employed. Concentration prediction errors obtained by this approach were comparable to cross-validation errors obtained for the slave instrument when all spectra were available.