Arsenic speciation patterns in freshwater fish

Muscle of 16 freshwater fish (9 different species belonging to 4 different families) was analysed for arsenic species using HPLC separation (anion and cation exchange) followed by on-line UV-decomposition, hydride generation and AFS detection. The main arsenic compounds found in the extracts were arsenobetaine (AsB), which accounted for 92–100% of extractable arsenic in species of salmonids (Salmo marmoratus, Oncorhynchus mykiss, Salmo trutta m. fario), and dimethylarsinic acid (DMAA), which accounted for 75% of extractable arsenic in burbot (Lota lota). AsB was also found in lower concentrations in almost all other fish species analysed (Silurus glanis, L. lota, Barbus barbus, Rutilus pigus virgo, Chondrostoma nasus). Arsenite (As(III)) and trimethylarsine oxide (TMAO) were detected in low concentrations in some representatives of Cyprinidae only (R. pigus virgo, C. nasus). Except in salmonids, an unknown cationic compound was present in most of the samples in relatively low concentrations. Cluster analysis of the generated data seems to indicate that there is a correlation between fish family and the arsenic speciation pattern. This is especially clear for the salmonids which show a completely separate cluster and thus a very distinct arsenic speciation pattern.     

A Rapid Method for the Determination of Organochlorine, Pyrethroid Pesticides and Polychlorobiphenyls in Fatty Foods Using GC with Electron Capture Detection

A new, single-step extraction and purification method was developed for the separation of 26 organochlorine pesticides (OCPs), three pyrethroid pesticides (PPs) and six polychlorinated biphenyls (PCBs) from fatty foods of either animal or vegetable origin. The method includes homogenisation of extracted fat and diatomaceous earth. Separation was achieved using a mini Pasteur pipette where a matrix solid-phase dispersion extraction was carried out with only 5 mL of dimethyl sulphoxide as an eluting solvent. A Pasteur pipette was joined to a prepacked slurry filled Florisil column, water deactivated to 15% where a liquid–liquid extraction and adsorption chromatography successively took place. The elution of OCPs, PPs and PCBs was performed with n-hexane/diethyl ether. Recoveries for PCBs were from 81 to 86% and for OCPs 68 to 94%, except for β-HCH, which gave lower, more variable recoveries. Excellent recoveries were obtained for pyrethroid pesticides, mostly more than 80%. The method was applied to 509 fatty samples for monitoring of these compounds. GC, with two columns connected to two electron capture detectors (ECD), was used.     

Optimisation of programmable temperature vaporizer-based large volume injection for determination of pesticide residues in fruits and vegetables using gas chromatography-mass spectrometry

The applicability of programmable temperature vaporizer (PTV) solvent vent injection to the gas chromatographic (GC) determination of pesticide residues in fruits and vegetables was evaluated with the aim of miniaturizing the current multiresidue method. For that purpose 24 pesticides representing different chemical classes were initially chosen for optimisation of the large volume injection (LVI) parameters. Various parameters related to the optimum injector performance were tested for several types of packed and empty liners using both fast (at-once) and speed-controlled PTV solvent vent injection of standard solutions in ethyl acetate. In the next step, several packed and empty liners were evaluated for their suitability for pesticide multiresidue analysis. Parameters identified as optimal were then applied for PTV solvent vent injection of sample extracts prepared using the miniaturized multiresidue method to assess the long-term stability of the system. The combined use of large volume injection of 10 microl ethyl acetate extract into an empty multi-baffled or a CarboFrit packed liner using PTV injectors and GC-MS analysis enabled the detection and quantification of 124 pesticides in fruit and vegetable samples at the 0.01 mg/kg level using miniaturized reversed-phase solid-phase extraction (RP-SPE) of diluted acetone extract and clean-up on a small anion-exchange SPE column.     

The Solubilization of Rock Phosphate by Organic Acids

Bases of the production of phosphoric fertilizers are classical methods involving acid dissolution of rock phosphates. The development of new methods applicable both to high-quality and low-quality phosphates is important for solving technological and ecological problems and to increase the economical effectiveness of phosphorus fertilizer technologies. In this respect, the bioconversion of rock phosphates in order to obtain phosphorus fertilizers is very promising. The basic principle of the biotechnological processing of natural phosphates is the production of organic acids, mainly citric, oxalic, and gluconic acid, that attack and dissolve the phosphates, converting the phosphorus to a form utilizable for the plants. The aim of this research is to optimize the process of Tunisian phosphorite solubilization with citric, oxalic, and gluconic acids in relation to the following main factors: the acid concentration, reaction time, solid/liquid phases ratio, and natural phosphate fraction. Two objective functions have been investigated: the quantity of the available acid in the system and the extent of phosphate dissolution. The research data has been processed according to the standard statistical tests. A mathematical model describing the phosphate decomposition process by organic acids has been obtained. A multicriteria optimization has been performed to determine the optimum levels of the examined factors. It was established that the different factors have a different effect on the goal parameters. A maximum degree of 91.89% of phosphorus extraction has been reached at phosphate solubilization by citric acid.     

Optimization with multivariate stochastic dominance constraints

We consider stochastic optimization problems where risk-aversion is expressed by a stochastic ordering constraint. The constraint requires that a random vector depending on our decisions stochastically dominates a given benchmark random vector. We identify a suitable multivariate stochastic order and describe its generator in terms of von Neumann–Morgenstern utility functions. We develop necessary and sufficient conditions of optimality and duality relations for optimization problems with this constraint. Assuming convexity we show that the Lagrange multipliers corresponding to dominance constraints are elements of the generator of this order, thus refining and generalizing earlier results for optimization under univariate stochastic dominance constraints. Furthermore, we obtain necessary conditions of optimality for non-convex problems under additional smoothness assumptions.     

Optimality and duality theory for stochastic optimization problems with nonlinear dominance constraints

We consider a new class of optimization problems involving stochastic dominance constraints of second order. We develop a new splitting approach to these models, optimality conditions and duality theory. These results are used to construct special decomposition methods.This research was supported by the NSF awards DMS-0303545 and DMS-0303728.Key words.Stochastic programming – stochastic ordering – semi-infinite optimized – decomposition     

Concavity and efficient points of discrete distributions in probabilistic programming

We consider stochastic programming problems with probabilistic constraints involving integer-valued random variables. The concept of a p-efficient point of a probability distribution is used to derive various equivalent problem formulations. Next we introduce the concept of r-concave discrete probability distributions and analyse its relevance for problems under consideration. These notions are used to derive lower and upper bounds for the optimal value of probabilistically constrained stochastic programming problems with discrete random variables. The results are illustrated with numerical examples. Received: October 1998 / Accepted: June 2000?Published online October 18, 2000     

Hydro­gen bonding in N,N′‐bis­[(1S)‐2‐azido‐1‐(2‐methyl­propyl)­ethyl]­oxal­amide: twofold symmetry of R(10) hydrogen‐bonded dimers connected into an α‐network

The title compound, C₁₄H₂₆N₈O₂, belongs to a class of retropeptides with an oxal­amide unit (–NH–CO–CO–NH–), and is a precursor for the synthesis of an amine‐terminal gelator. The compound is a good synthon for one‐dimensional hydrogen bonding. The crystal structure reveals a hydrogen‐bonded cyclic dimer with unusual twofold rotation symmetry.     

Innovative approach to treating waste waters by a membrane capacitive deionisation system

The application of membrane capacitive deionisation was investigated for treating model water samples and real waste waters from the textile industry. For the pre-treatment of waste waters, nanofiltration was integrated in order to prevent scaling and fouling of membranes and electrodes during membrane capacitive deionisation. Different conditions were applied when treating water samples with membrane capacitive deionisation with the aim of optimising conditions for high desalination efficiency and, consequently, for conductivity reduction. The conductivity of waste waters with high salt concentrations was reduced to the required value, below 1.5 mS cm^?1. The desalination rates achieved as much as 95 %, depending on the initial conductivity and the different ions present in the water samples. In addition, chemometric characterisation of the samples was performed in order to determine the existence of significant correlations between the monitored parameters: the presence of various ions (Na⁺, K⁺, Ca²⁺, Mg²⁺, Cl^?, Br^?, F^?, SO₄^2?, NO₃^?, desalination and water recovery, the duration of each phase and the flow of the solution during each phase. A model for desalination rate prediction was designed using multiple linear regression. It was established that the model values accorded well with the experimental values — the differences between model and experimental values were less than 1 %.