Capable Lie algebras with the derived subalgebra of dimension 2 over an arbitrary field

In this paper, we classify all capable nilpotent Lie algebras with the derived subalgebra of dimension 2 over an arbitrary field. Moreover, the explicit structure of such Lie algebras of class 3 is given.     

Fluorescence quantification of tetracycline in the presence of quenching matrix effect by means of a four-way model

In this work, a four-way tensor is used to model the quenching effect in fluorescent measurements. By means of the analysis of excitation-emission matrices obtained in the determination of tetracycline in tea, which acts as quencher, it is shown as the impossibility to use a calibration, or an addition standard based on a three-way model. It is analysed the quencher multiplicative effect made on the tetracycline signal by means of an ANOVA. However, by arranging the experimental data in a four-way tensor, it is viable to perform a calibration based on the parallel factor analysis, PARAFAC, decomposition and a four-way partial least squares, 4-PLS, regression to quantify the tetracycline in the presence of the matrix quencher effect. 4-PLS calibration provides better results. In the range from 40 to 220 μg L⁻¹ gives an average of relative errors in absolute value equal to 8.02% in prediction (3.40% in calibration). The repeatability as standard deviation in this range is 5.08 μg L⁻¹ and the method is accurate, slope and intercept being statistically equal to 1 and 0, respectively when a regression calculated versus true concentration is performed. Moreover, it has a decision limit (CCα) of 13.87 μg L⁻¹ for a probability of false positive, α, equal to 0.05 and a capability of detection (CCβ) of 26.63 μg L⁻¹ (for probabilities of false positive, α, false negative, β, equals to 0.05).     

Robust regression techniques A useful alternative for the detection of outlier data in chemical analysis

The validation of an analytical procedure means the evaluation of some performance criteria such as accuracy, sensitivity, linear range, capability of detection, selectivity, calibration curve, etc. This implies the use of different statistical methodologies, some of them related with statistical regression techniques, which may be robust or not. The presence of outlier data has a significant effect on the determination of sensitivity, linear range or capability of detection amongst others, when these figures of merit are evaluated with non-robust methodologies.In this paper some of the robust methods used for calibration in analytical chemistry are reviewed: the Huber M-estimator; the Andrews, Tukey and Welsh GM-estimators; the fuzzy estimators; the constrained M-estimators, CM; the least trimmed squares, LTS. The paper also shows that the mathematical properties of the least median squares (LMS) regression can be of great interest in the detection of outlier data in chemical analysis. A comparative analysis is made of the results obtained by applying these regression methods to synthetic and real data. There is also a review of some applications where this robust regression works in a suitable and simple way that proves very useful to secure an objective detection of outliers. The use of a robust regression is recommended in ISO 5725-5.     

Tutorial on evaluation of type I and type II errors in chemical analyses: From the analytical detection to authentication of products and process control

Uncertainty is inherent in all experimental determinations. Nevertheless, these measurements are used to make decisions including the performance of the own measurement systems. The link between the decision and the true implicit system that generates the data (measurement system, production process, category of samples, etc.) is a representation of this uncertainty as a probability distribution. This representation leads to the probabilistic formalization of the possibility of making errors. In the context of regulations established by official agencies, it is important to use these statistical decision methods in some cases because the own norm makes them mandatory and, in general, because this is the way of reasonably evaluating whether a working hypothesis is rejected on the basis of the experimental data.The aim of the present tutorial is to introduce some ideas and basic methods for the critical analysis of experimental data. With this goal, the basic elements of the Neyman-Pearson theory of hypothesis testing are formally introduced in connection with the common problems in chemical analysis and, if this is the case, their relation to the norms of regulatory agencies. The notion of decision with ‘enough quality’ is modelled when explicitly considering: (1) the null, H₀, and alternative, H₁, hypotheses. (2) The significance level of the test, which is the probability, α, of rejecting H₀ when it is true, and the power of the test, 1 − β, β being the probability of accepting H₀ when it is false. (3) The difference between H₀ and H₁ that has to be detected with experimental data. (4) The needed sample size. These four concepts should be explicitly defined for each problem and, under the usual assumption of normal distribution of the data, the mathematical relations among these concepts are shown, which allow the analyst to design a decision rule with pre-set values of α and β.To illustrate the unifying character of this inferential methodology, several situations are exposed along the tutorial: the design of a hypothesis test to decide on the performance characteristics of analytical methods, the capability of detection of both quantitative and qualitative analytical methods (including its generalization to the case of multivariate and/or multiway signals), the analytical sensitivity with multivariate signals, the class-modelling and the process control.     

Detection capability of tetracyclines analysed by a fluorescence technique: comparison between bilinear and trilinear partial least squares models

According to the committee decision of 12 August 2002 (2002/657/EC) the capability of detection, CCβ, must be set in all analytical methods not only at concentration levels close to zero but also at the maximum permitted limit (PL). In this work we describe a methodology which evaluates the capability of detection of a fluorescence technique with soft calibration models (bilinear and trilinear PLS) to determine tetracyclines (group B1 substances from annex 1 of Directive 96/23/EC). Its estimation is based on the generalisation of the procedure described in International Union of Pure and Applied Chemistry and in the ISO standard 11843 for univariate signals which evaluates the probabilities of false positive (α) and false negative (β). The capability of detection, CCβ, estimated from the second-order signal and the trilinear PLS model is 9.93 μg l⁻¹ of tetracycline, 17.75 μg l⁻¹ of oxytetracycline and 26.31 μg l⁻¹ of chlortetracycline, setting α and β at 0.05. The capability of detection, CCβ, determined around the PL (100 μg kg⁻¹ in milk and muscle) with the second-order signal is 109.4 μg l⁻¹ of tetracycline, 117.0 μg l⁻¹ of oxytetracycline and 124.9 μg l⁻¹ of chlortetracycline, setting α and β at 0.05. The results were compared with those obtained with zero and first-order signals. The effect of the interferences on the capability of detection was also analysed as well as the number of standards used to build the models and their calibration range.When a tetracycline is quantified in presence of uncalibrated ones by means of the trilinear PLS model the errors oscillate between 14.70% for TC and 9.57% for OTC.     

Multivariate analytical sensitivity in the determination of selenium, copper, lead and cadmium by stripping voltammetry when using soft calibration

A new approach to the multivariate sensitivity concept based on the determination of the capability of discrimination of a method of analysis is shown. Thus the analytical sensitivity is defined in this work by the analyte concentration that a analytical method is able to discriminate, which implies the estimation of the ‘false noncompliance’ and ‘false compliance’. In this approach the estimation of the multivariate analytical sensitivity is independent of scale factors and calibration models, and allows one to study the behavior of a analytical method for several concentrations and matrix. The estimation of this parameter in the simultaneous determination of selenium, copper, lead and cadmium by stripping voltammetry when using soft calibration is carried out, showing that different multivariate analytical sensitivities are obtained for each metal.     

Usefulness of capability indices in the framework of analytical methods validation

Analytical methods capability evaluation can be a useful methodology to assess the fitness of purpose of these methods for their future routine application. However, care on how to compute the capability indices have to be made. Indeed, the commonly used formulas to compute capability indices such as Cpk, will highly overestimate the true capability of the methods. Especially during methods validation or transfer, there are only few experiments performed and, using in these situations the commonly applied capability indices to declare a method as valid or as transferable to a receiving laboratory will conduct to inadequate decisions.     

Boosting Fe Cationic Vacancies with Graphdiyne to Enhance Exceptional Pseudocapacitive Lithium Intercalation

Modulating the electronic structure of electrode materials at atomic level is the key to controlling electrodes with outstanding rate capability. On the basis of modulating the iron cationic vacancies (IV) and electronic structure of materials, we proposed the method of preparing graphdiyne/ferroferric oxide heterostructure (IV-GDY-FO) as anode materials. The goal is to motivate lithium-ion batteries (LIBs) toward ultra-high capacity, superior cyclic stability, and excellent rate performance. The graphdiyne is used as carriers to disperse Fe₃O₄ uniformly without agglomeration and induce high valence of Fe with reducing the energy in the system. The presence of Fe vacancy could regulate the charge distribution around vacancies and adjacent atoms, leading to facilitate electronic transportation, enlarge the lithium-ion diffusion, and decrease Li⁺ diffusion barriers, and thus displaying significant pseudocapacitive process and advantageous lithium-ion storage. The optimized electrode IV-GDY-FO reveals a capacity of 2084.1 mAh g⁻¹ at 0.1 C, superior cycle stability and rate performance with a high specific capacity of 1057.4 mAh g⁻¹ even at 10 C.     

Validation of an analytical method to determine sulfamides in kidney by HPLC-DAD and PARAFAC2 with first-order derivative chromatograms

Six sulfamides were extracted from kidney and analysed by high-performance liquid chromatography with diode array detection (HPLC-DAD): sulfadiazine, sulfamethazine, sulfamethoxypyridazine, sulfamethoxazole, sulfadimethoxine and sulfaquinoxaline.Two main difficulties arose in identifying and quantifying the analytes. Firstly, the chromatographic peaks of the matrix interferences overlapped with those of the analytes. The uniqueness property of PARAFAC2 solved this problem. Secondly, the gradient elution caused a baseline drift. The first-order derivative of the chromatograms minimized its effect.The analytical method was validated. As the performance criteria detailed in the European Decision 2002/657/EC are based on specific signals, this paper generalizes those criteria for higher-order and non-specific signals. In this sense the proposed methodology is general and can be applied to any chromatographic method (HPLC or GC) with a detector that provide a multivariate signal (MS, DAD, EC, etc.).     

装备保障能力评估方法综述

装备保障能力评估是提升武器装备战备完好率的重要手段,能有效地促进装备保障能力建设的科学发展和部队战斗力的提升。论文首先介绍了装备保障能力相关理论的发展情况,整理了装备保障能力评估的基本思路,然后从多元统计理论、不确定性理论、多属性评估法、数据挖掘技术、交叉学科理论及组合模型等方面介绍了当前评估方法的发展现状,梳理和总结了各方法的建模基本思想并比较其优缺点,结合研究现状指出了评估理论存在的问题,最后对下一步研究方向进行了归纳。