灰铸铁石墨形态的自动分类

在所提取的纹理特征的基础上,使用误差后向传播神经网络构建了一种优化的人工神经网络人顺。实现了灰铸铁石墨态的自动分类。用于描述石墨形态特征由分形维,粗细参数和二维自回归系数共同组成。该法成功地将人工神经网络引入了对灰铸铁石墨形态的分类,相对于传统人工目测法是一种很大的进步,而神经网络分类器的优化方法对其它神经网络模型的构也具有一定参考价值。     

ESI-MS quantitation of iron as its 4-(2-pyridylazo)resorcinol (PAR) complex: application to pharmaceutical tablets containing iron oxide pigment

Quantitation of iron oxide (Fe(2)O(3)) in pharmaceutical formulations using electrospray ionization mass spectrometry (ESI-MS) following iron complexation with 4-(2-pyridylazo)resorcinol (PAR) was evaluated. Complexation of Fe(III) with PAR was found to produce an intense mass spectral signal at low pH compared to the free ligand. Using the selected-ion-monitoring mode of a triple-quadrupole mass spectrometer, the signal at m/z 484 arising from the singly charged [Fe(III)(PAR)(2)](+) complex gave a limit of detection of ~2 μM for total iron. The linear range of the calibration curve was found to be 2-43 μM total iron. Trace iron interference was decreased to submicromolar levels by performing an optimized labware cleaning protocol and instrument replumbing using Polyetheretherketone (PEEK) tubing. The validation parameters of this ESI-MS total iron analysis (specificity, linearity, precision, accuracy, robustness and stability) are within the acceptance criteria listed in the validation guidelines developed by the Food and Drug Administration for industry. Recovery of 93% of the added iron indicated a satisfactory extraction procedure for tablets containing Fe(2)O(3) pigment. There was no statistical difference between the results obtained by ESI-MS and the common elemental method, inductively coupled plasma-optical emission spectroscopy. Since the proposed ESI-MS method can be performed on a mass spectrometer equipped with an ESI source, which is standard instrumentation in the pharmaceutical industry, the method validated here provides an alternate method for metal ion analysis by ESI-MS.     

Initial Validation of a New Procedure for Determining Aromatics in Petroleum Distillates

Abstract

The analytical data from an initial validation of a new method developed for determining aromatics in distillate fuels is reported. The method applies supercritical fluid chromatography (SFC) for the liquid chromatographic separation of total saturates and total aromatics, followed by flame ionization detection. A study was conducted to determine the validity of a SFC procedure after it was proposed to the Canadian national standard writing body for its adoption as a new standard method for determining aromatics. Inter-laboratory results suggest that SFC provides reproducible data among different laboratories and these SFC data correlate well with those obtained from other methods such as fluorescent indicator adsorption (FIA), nuclear magnetic resonance (NMR), and mass spectrometry (MS).     

Determination of molybdenum in steels by flow-injection spectrophometry

A flow-injection procedure is proposed for the determination of molybdenum in steels based on the thiocyanate method. Effects of iron(III), acidity, reagent concentration and interfering species were investigated by using flow-injection systems with the merging zones approach which reduced drastically the number of standard solutions to be prepared. Full details of system design are given. The procedure can be applied to several types of steel samples of industrial relevance. After dissolution of the steels in aqua regia, molybdenum can be determined in the range 0.10–4.00% (w/w) at a rate of up to 270 samples per hour with relative standard deviations less than 2%. The results agree with those obtained by atomic absorption spectrometry with the standard addition method and by plasma atomic emission spectrometry, and with certified values of standard reference samples.     

Determination of the content and identity of lidocaine solutions with UV-visible spectroscopy and multivariate calibration

A method is proposed for the determination of the content and identity of the active compound in pharmaceutical solutions by means of ultraviolet-visible (UV-Vis) spectroscopy, orthogonal signal correction (OSC) and multivariate calibration with soft independent modelling of class analogy (SIMCA) classification and partial least squares (PLS) regression. The content was determined with PLS regression and the identity with PLS regression and SIMCA classification. The method was tested on the local anaesthetic compound lidocaine. For the validation, external test sets of both manufactured sample solutions and samples from a stability study were used. For comparison with this new method, liquid chromatography was used as a reference method. The results show that in respect of accuracy, precision and repeatability, the new method is comparable to the reference method. The main advantage over liquid chromatography is the much shorter time of analysis and the simpler analytical procedure. An estimate of the analysis time saved with the proposed method compared with using liquid chromatography, together with practical considerations, is given.     

Preparation of a soluble solid sample by a continuous ultrasound assisted dissolution system for the flow-injection atomic absorption spectrometric determination of iron in milk powder and infant formula

A simple and new flow-injection manifold (CUDS) for the continuous ultrasound assisted dissolution of a soluble solid sample coupled to a flow-injection flame atomic absorption spectrometric manifold for the continuous iron determination is described. An experimental design was used for the evaluation of factors involving the CUDS. The method was applied to a certified reference material (CRM-151, skim milk powder) for quality assurance/validation and to real samples (milk powder and infant formulas). The total sampling frequency achieved was 80 samples per hour with a relative standard deviation for the complete procedure of 1.1%. The detection limit was 0.60 μg g⁻¹ for a sample amount of 30 mg. The results demonstrated that the CUDS is an innovative and efficient tool as compared to the manual-traditional sample preparation methods, but with drastic increase of both sample throughput and precision.     

A method for calibration and validation subset partitioning

This paper proposes a new method to divide a pool of samples into calibration and validation subsets for multivariate modelling. The proposed method is of value for analytical applications involving complex matrices, in which the composition variability of real samples cannot be easily reproduced by optimized experimental designs. A stepwise procedure is employed to select samples according to their differences in both x (instrumental responses) and y (predicted parameter) spaces. The proposed technique is illustrated in a case study involving the prediction of three quality parameters (specific mass and distillation temperatures at which 10 and 90% of the sample has evaporated) of diesel by NIR spectrometry and PLS modelling. For comparison, PLS models are also constructed by full cross-validation, as well as by using the Kennard-Stone and random sampling methods for calibration and validation subset partitioning. The obtained models are compared in terms of prediction performance by employing an independent set of samples not used for calibration or validation. The results of F-tests at 95% confidence level reveal that the proposed technique may be an advantageous alternative to the other three strategies.     

Improved fluorimetric determination of dissolved aluminium by micelle-enhanced lumogallion complex in natural waters

A modification of the aluminium-lumogallion fluorescence measurement in the presence of the non-ionic surfactant Triton X-100 is presented. The detection limit for dissolved Al is 0.7 nM, with a relative standard deviation of 3.6% at an Al level of 5.0 nM. Compared with previously reported methods in the literature, the method described here is free from matrix effects and can be used for the determination of aluminium in fresh, estuarine and saline waters. The interferences from iron and fluoride were minimized by the addition of o-phenanthroline and Be2+, respectively. The analysis of NIST SRM 1643C and PRC standard 2430101 by the proposed method provides results consistent with the certified values. A successful inter-laboratory calibration exercise also demonstrates the merit of the proposed method for the determination of Al in environmental and marine sciences.     

辉光放电原子发射光谱法快速分析生铸铁

通过对辉光光源参数-放电电流、放电电压、预溅射时间和分析时间对生铸铁标样放电强度和稳定性影响的研究,优化光源参数,建立了辉光放电原子发射光谱法同时测定生铸铁中碳、硅、锰、磷、硫等12个元素的快速分析方法。分析生铸铁试样时发现了不同灰口铸铁在碳分析结果方面存在偏差,对碳的偏差进行了讨论并通过制样条件和光源参数的调整可以有效地减小偏差。通过对不同生铸铁样品进行准确度和精密度试验,结果表明:分析结果与标准值或化学法结果一致。分析一件试样的时间仅需2~5 min。     

Assessing the statistical validity of proteomics based biomarkers

A strategy is presented for the statistical validation of discrimination models in proteomics studies. Several existing tools are combined to form a solid statistical basis for biomarker discovery that should precede a biochemical validation of any biomarker. These tools consist of permutation tests, single and double cross-validation. The cross-validation steps can simply be combined with a new variable selection method, called rank products. The strategy is especially suited for the low-samples-to-variables-ratio (undersampling) case, as is often encountered in proteomics and metabolomics studies. As a classification method, principal component discriminant analysis is used; however, the methodology can be used with any classifier. A dataset containing serum samples from Gaucher patients and healthy controls serves as a test case. Double cross-validation shows that the sensitivity of the model is 89% and the specificity 90%. Potential putative biomarkers are identified using the novel variable selection method. Results from permutation tests support the choice of double cross-validation as the tool for determining error rates when the modelling procedure involves a tuneable parameter. This shows that even cross-validation does not guarantee unbiased results. The validation of discrimination models with a combination of permutation tests and double cross-validation helps to avoid erroneous results which may result from the undersampling.     

Molybdenum determination in iron matrices by ICP-AES after separation and preconcentration using polyurethane foam

A procedure is proposed for the separation and determination of molybdenum in iron matrices by a batch process. It is based on the solid-phase extraction of the molybdenum(V) ion as thiocyanate complex on polyurethane (PU) foam. The extraction parameters were optimized. Using 0.20 mol L-1 hydrochloric acid, a thiocyanate concentration of 0.10 mol L-1, 100 mg of polyurethane foam and shaking time of 10 min, molybdenum (5-400 micrograms) can be separated and preconcentrated from large amounts of iron (10 mg). Desorption was carried out instantaneously by conc. nitric acid or acetone. Distribution coefficients, sorption capacity of the PU foam and coefficients of variation were also evaluated. The effect of some ions on the separation procedure was assessed. Iron(III) should be reduced to iron(II). The proposed procedure was used to determine molybdenum in standard iron matrices such as steel and pure iron. The achieved results did not show significant differences with certified values.     

Sandwich techniques in flow-injection analysis : Part 2. Simultaneous Determination of Iron(II) and Total Iron

Samples (1500 μl) are inserted between zones of water and ascorbic acid solution with subsequent addition of 1,10-phenanthroline at pH 5.0. The signal provides a plateau region corresponding to Fe(Il) followed by a peak corresponding to total iron. The proposed system allows up to 90 injections per hour. Linear working ranges are 0.1–9 and 0.3–12 mg l^?1 Fe(II) and total iron, with relative standard deviations of < 0.6 and 1.2%, respectively. Results obtained for various ground waters agree well with those obtained by a standard method.     

Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) for spatially resolved trace analysis of early-medieval archaeological iron finds

The suitability of laser ablation ICP-MS for minor and trace analysis of archaeological iron finds, produced by a direct reduction process in a ‘bloomery’ furnace, is reported. The analysis of elemental impurities in the iron can provide useful archaeometallurgical information on the production process and the provenance of the iron. Since, even after refinement, the iron resulting from this process may contain many inclusions (slag, charcoal, holes, etc.), a method should be used with sufficient spatial resolution to preclude the inclusions from the analysis. The ablation parameters are selected such that ablation craters of approx. 100 μm in diameter are obtained. The method is validated with low alloy steel and cast iron standard reference materials and by a comparative analysis with electron probe microanalysis (EPMA). The precision is limited mainly by the homogeneity of the iron, rather than by instrumental reproducibility. The advantages and drawbacks of the method are briefly compared with EPMA. Preliminary results from the analysis of archaeological iron samples from excavations at Develier-Courtételle (Canton Jura, CH), Neftenbach (Canton Zurich, CH), Wartau (Canton St Gallen, CH) and Mont Chemin (Canton Valais, CH) are given.     

Determination of silicon in cast iron by 14 MeV neutron activation

Silicon in cast iron was analyzed by 14 MeV neutron activation—high-resolution γ-ray spectrometry. Silicon was detected as²⁸Al, the product of the²⁸Si(n, p)²⁸Al reaction. Interference of⁵⁶Mn was separated using a Ge(Li) detector and a biased amplifying system. The 1. 81 MeV gamma-radiation of⁵⁶Mn, which is the product of the⁵⁶Fe(n, p)⁵⁶Mn reaction of the matrix of cast iron, was used as an internal standard and for correction of the self-absorption of the 1. 78 MeV gamma-radiation of²⁸Al by the sample. The interferences of aluminum, phosphorus and manganese could be neglected according to the results calculated from their nuclear properties and contents in the cast iron of this experiment. The results of this method agreed well with the results of the usual chemical method, with errors less than 5% of the results, and the precision of the method was satisfactory with a C. V. of less than almost 6% for rapid analysis of silicon in cast iron. The analytical line through the origin with a slope of the mean value of the repetition experiments could be used as the analytical line with almost the same precision and accuracy of the results as for the analytical line calculated by the least squares method.     

Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) for spatially resolved trace analysis of early-medieval archaeological iron finds

The suitability of laser ablation ICP-MS for minor and trace analysis of archaeological iron finds, produced by a direct reduction process in a 'bloomery' furnace, is reported. The analysis of elemental impurities in the iron can provide useful archaeometallurgical information on the production process and the provenance of the iron. Since, even after refinement, the iron resulting from this process may contain many inclusions (slag, charcoal, holes, etc.), a method should be used with sufficient spatial resolution to preclude the inclusions from the analysis. The ablation parameters are selected such that ablation craters of approx. 100 microm in diameter are obtained. The method is validated with low alloy steel and cast iron standard reference materials and by a comparative analysis with electron probe microanalysis (EPMA). The precision is limited mainly by the homogeneity of the iron, rather than by instrumental reproducibility. The advantages and drawbacks of the method are briefly compared with EPMA. Preliminary results from the analysis of archaeological iron samples from excavations at Develier-Courtetelle (Canton Jura, CH), Neftenbach (Canton Zurich, CH), Wartau (Canton St Gallen, CH) and Mont Chemin (Canton Valais, CH) are given.     

Spectrophotometric determination of iron(III) and total iron by sequential injection analysis technique

A procedure for determination of concentrations of iron(III) and total iron by sequential injection analysis is described. The method is based on the strong blue-colored complexes formed between iron(III) and tiron. The absorbance of the complexes is measured spectrophotometrically at 635 nm. Oxidation of iron(II) and masking of interfering fluoride is simultaneously done by injecting one zone of hydrogen peroxide and one of thorium(IV) between the sample and reagent zones. Concentration of iron(III) and total iron, in the range 0.002–0.026 M, in diluted samples from a pickle bath were determined. The relative standard deviation was 0.4% (n=7). The method was also used in a pilot plant of a zinc process for determination of iron(III) in the range 0.2–3.0 g l⁻¹. The sample throughput is approximately 17 samples per hour, including three repetitive determinations of each sample.     

Correction parameters in X-ray fluorescence analysis applying the limit dilution method (LDM)

Summary Some corrective parameters: H, M, Y and Y/H are defined from the mathematical development justifying the Limit Dilution Method (LDM) in XRF analysis. These corrective parameters, for a given diluent and dilution, are characteristic of the analyte in each sample. The influence of these parameters on important phenomena such as the diluent effect is evaluated by a theoretical model. Using parameters Y, an algorithm is proposed which corrects the diluent effect and establishes linear functions of fluorescence intensity vs. analyte concentration. This paper also proposes a selection procedure for the optimum standard for a given problem using the Y/H parameter. The method is applied to the XRF analysis of mixtures of iron and zirconium oxides and these results show the corrective action of the suggested parameters and the appropriateness of the selection of the standards.     

Functional nonparametric classification of wood species from thermal data

In this study, thermogravimetric (TG) and differential scanning calorimetry (DSC) curves, obtained by means of a simultaneous TG/DSC analyzer, and statistical functional nonparametric methods are used to classify different wood species. The temperature ranges, where the highest probability of correct classification is reached, are also computed. As each observation is a curve, a nonparametric functional discriminant technique based on the Bayes rule and the Nadaraya–Watson regression estimator is used. It assigns a future observation to the highest probability predefined class (supervised classification). The smoothing parameter needed in this nonparametric method is selected according to the cross-validation technique. The method proposed is applied to a sample of 49 wood items (7 per wood class) and also to classify between hardwoods and softwoods. In all the cases, the samples have been successfully classified, obtaining better results with the TG curves. The results are compared with those obtained with other nonparametric methods based on boosting algorithm. A discussion about the relation of the obtained results with the referenced wood component degradation temperature ranks is presented.