Characterization and quantitation of mixtures of alkyl ether sulfates and carboxylic acids by capillary electrophoresis with indirect photometric detection

The separation, characterization, and determination of mixtures of alkyl ether sulfates (AES) and fatty acids (C10-C16) in background electrolytes (BGEs) containing acetonitrile (ACN)-water mixtures is addressed. Due to inhibition of the ionization of the carboxylate groups, the migration time and the resolution between the fatty acids decreased when the water content of the BGE was reduced, but efficiency and resolution between the AES oligomers improved. The migration times increased and resolution improved by substituting 5% ACN by an equivalent amount of dioxane. A complete separation of the two surfactant classes, up to the AES oligomers with 8 ethylene oxide units (EOs) with respect to C10, with excellent resolution between the AES oligomers, while preserving a satisfactory resolution between the fatty acids, was achieved with a BGE containing 5 mM trimethoxybenzoic acid, 7 mM dipentylamine, 85% ACN, 5% dioxane, and 10% water. The two surfactant classes were increasingly resolved by further reducing the water content of the BGE. Thus, C2 (acetate) was resolved from the AES oligomers up to 7 EOs using 90% ACN and 5% dioxane, but the resolution between the heavier fatty acids was poor with this BGE. Identification of the AES oligomers was eased by the excellent regularity of the successive migration times; thus, within each AES subclass or series of oligomers with the same number of carbon atoms in the alkyl chain, the migration times decreased following a mild curve as the number of EOs increased. The way how the data obtained by indirect photometry (corrected peak areas that are proportional to the molar concentrations) should be managed to avoid systematic error when the calibration curve is constructed using an AES standard with an oligomer distribution different from that of the samples is discussed and equations are given. Decyl sulfate was successfully used as internal standard. The detection limits (S/N = 3) were of ca. 2 microM for individual AES oligomers.     

Estimating household purchase rates for consumer nondurable goods

Understanding the purchase rates of households for frequently purchased packaged goods is an important element in developing effective marketing strategies. Previous researchers have attempted to estimate these rates by assuming that the time between purchases is a random variable that follows some common parametric probability distribution such as the exponential or Weibull distribution. Recent research has shown that for many frequently purchased packaged goods, the interpurchase times cannot be adequately described by these commonly used probability distributions. In this study we demonstrate how household purchase rates can be estimated in a robust manner using a generalized semiparametric approach that obviates the need for specifying a parametric form for the distribution of interpurchase times. The motivation being that often there is no theory of household purchase behaviour that specifies a priori the probability distribution underlying the interpurchase times. Our empirical results indicate that, for the data analysed, the household purchase rates exhibit a regular pattern that cannot be recovered by probability distributions often used in previous research. Further, marketing actions taken by sellers do indeed influence household purchase behaviour.     

Producing valuable products from industrial and household wastes using autoclave thermovaporous treatment

Abstract

The autoclave thermo vaporous treatment in water-vapour media allows to obtain useful products from different industrial and household wastes: the silica and hexafluorosilicium acid - collateral product by manufacture of mineral fertilizers; aluminium hydroxide - by-product of aluminium designs and of electrolytical condensers manufacture; household wastes, containing cellulose; product and film from plastic.     

Analytic hierarchy based policy design method (AHPo) for solving societal problems that require a multifaceted approach

This paper proposes an AHP based statistical method for the design of a comprehensive policy alternative, AHPo, for solving societal problems that require a multifaceted approach. In the proposed method, criteria relevant to the goal or focus are structured in the same way as in the conventional AHP. However, these two methods are quite different in regard to the method of quantification. The new method predicts or analyses the impact of the policy alternatives on the overall goal. In other words, it predicts or rationalizes the way people appreciate the situation in which an alternative is adopted and implemented. It will serve as a tool for supporting (especially political) decision making.     

Household consumption, investment and life insurance

This paper develops a continuous-time Markov model for utility optimization of households. The household optimizes expected future utility from consumption by controlling consumption, investments and purchase of life insurance for each person in the household. The optimal controls are investigated in the special case of a two-person household, and we present graphics illustrating how differences between the two persons affect the controls.     

An integer programming dynamic farm-household model to evaluate the impact of agricultural policy reforms on farm investment behaviour

We develop a multi-objective farm-household dynamic integer programming model to simulate investment behaviour in different policy and price scenarios, with a particular focus on the decoupling of the Common Agricultural Policy (CAP). The model takes into account the characteristics of individual assets, including ageing and fixity through the explicit consideration of transaction costs. A case study application in the context of arable farming in Northern Italy is provided as an example. The results emphasise different patterns of reaction of different farm-household types over time, as an effect of the varying opportunity costs of resources and initial asset endowments. Overall, this application highlights the potentialities and limits of the methodology. In particular, the approach proved to be effective in providing a variety of results depending on the individual features of each farm-household, such as the differences between: (a) a ‘no reaction’ attitude; (b) an adaptation of farm activity and assets; and (c) a radical reaction pattern guided by high-income alternatives to farming. This highlights the potential of this tool as a generator of ideas and working hypotheses. We argue that, in view of the further developments of the CAP, the use of instruments able to account for multiple objectives, dynamics and investment choices will become even more relevant in the analysis of EU agricultural policy.     

Capillary electrophoresis enhanced by automatic two-way background correction using cubic smoothing splines and multivariate data analysis applied to the characterisation of mixtures of surfactants

Mixtures of the surfactant classes coconut diethanolamide, cocamido propyl betaine and alkylbenzene sulfonate were separated by capillary electrophoresis in several media containing organic solvents and anionic solvophobic agents. Good resolution between both the surfactant classes and the homologues within the classes was achieved in a BGE containing 80 mM borate buffer of pH 8.5, 20% n-propanol and 40 mM sodium deoxycholate. Full resolution, assistance in peak assignment to the classes (including the recognition of solutes not belonging to the classes), and improvement of the signal-to-noise ratio was achieved by multivariate data analysis of the time-wavelength electropherograms. Cubic smoothing splines were used to develop an algorithm capable of automatically modelling the two-way background, which increased the sensitivity and reliability of the multivariate analysis of the corrected signal. The exclusion of significant signals from the background model was guaranteed by the conservativeness of the criteria used and the safeguards adopted all along the point selection process, where the CSS algorithm supported the addition of new points to the initially reduced background sample. Efficient background modelling made the application of multivariate deconvolution within extensive time windows possible. This increased the probability of finding quality spectra for each solute class by orthogonal projection approach. The concentration profiles of the classes were improved by subsequent application of alternating least squares. The two-way electropherograms were automatically processed, with minimal supervision by the user, in less than 2 min. The procedure was successfully applied to the identification and quantification of the surfactants in household cleaners.     

Enzyme class identification in cleaning products by hydrolysis followed by derivatization with o-phthaldialdehyde, HPLC and linear discriminant analysis

The enzymes present in raw materials of the cleaning industry (enzyme industrial concentrates) and in household cleaners were isolated by precipitation with acetone and hydrolyzed with HCl. The resulting amino acids were derivatized with o-phthaldialdehyde, and the derivatives were separated by HPLC. The peaks of 14 amino acids were observed using a C18 column and a multi-segmented gradient of acetonitrile-water in the presence of a 5 mM citric/citrate buffer of pH 6.5. Using either normalized peak areas (divided by the sum of the peak areas of the chromatogram) or ratios of pairs of peak areas as predictor variables, linear discriminant analysis models, capable of predicting the enzyme class, including proteases, lipases, amylases and cellulases, were constructed. For this purpose, both enzyme industrial concentrates and detergent bases spiked with them were included in the training set. In all cases, the enzymes of the evaluation set, including industrial concentrates, spiked detergent bases and commercial cleaners were correctly classified with assignment probabilities higher than 99%.     

Use of hop cone extract obtained under supercritical CO2 conditions for producing antibacterial all-purpose cleaners

This paper attempts to demonstrate empirically the possibility of using a hydrophobic extract of hop cone obtained under the conditions of supercritical carbon dioxide to produce all-purpose cleaner with antimicrobial activity and low irritant potential. A series of prototypes of products varied by the extract concentration was developed. The formulations were assessed for physicochemical properties: particle size, turbidity, and color. The results indicate that the hydrophobic extracts of hop cone can be a valuable component of chemical products intended for washing, having a broad spectrum of action and contributing to improvement of the product’s safety.     

Evaluation of matrix solid‐phase dispersion extraction for the determination of polycyclic aromatic hydrocarbons in household dust with the aid of experimental design and response surface methodology

A simple, fast, and inexpensive procedure for sample preparation based on matrix solid‐phase dispersion was developed for the determination of Environmental Protection Agency 16 priority polycyclic aromatic hydrocarbons in indoor dust samples. Parameters that affect the extraction efficiency such as type of dispersant, elution solvent, and solvent volume were evaluated and optimized with the aid of experimental design and response surface methodology. Analysis was performed by HPLC coupled with UV‐Vis diode array detector (UV‐DAD). For verification, a GC coupled with a mass spectrometer in SIM mode was also applied. Recoveries obtained were from 53 to 120% for all target analytes with detection limits ranging from 0.2 to 10 ng/g and 0.2 to 2 ng/g for LC‐UV‐DAD and GC‐MS, respectively. The optimized method was used for the analysis of 11 household dust samples collected from private houses.