Coadsorption of carbofuran and lead at the water/silica interface. Possible impact on environment

Despite its extremely weak adsorption at the water/silica interface, carbofuran can, however, induce the coadsorption of metallic salts, like, for example, lead nitrate, and thus enhance its adsorption. We quantitatively studied this phenomenon with a depletion method and under concentration conditions close to the environmental ones. Heavy metal salt was found to positively adsorb, whereas carbofuran relative adsorption is generally slightly negative. This study provides evidence that considering these facts is of paramount importance in environmental prospects. To cite this article: G. Elmanfe et al., C. R. Chimie 9 (2006).     

Carboxylate-bridged copper(II)-lanthanide(III) complexes [(Cu(3)Ln(2)(oda)(6)(H(2)O)(6)).12H(2)O](n)(Ln = Dy,Ho, Er,Y; oda = oxydiacetate)

The hydrothermal reaction of Ln(2)O(3) (Ln = Dy and Ho), Cu(OAc)(2).2H(2)O, and oxydiacetic acid in the approximate mole ratio of 1:3:8 resulted in the formation of two new members of the isostructural series of polymers formulated as [(Cu(3)Ln(2)(oda)(6)(H(2)O)(6)).12H(2)O](n), crystallizing in the hexagonal crystal system, space group P6/mcc (No. 192). Temperature-dependent magnetic susceptibilities and EPR spectra are reported for the heterometallic compounds Cu-Dy 1, Cu-Ho 2, Cu-Er 3, and Cu-Y 4. The results are discussed in terms of the structure of the compounds, the electronic properties of the lanthanide ions, and the exchange interactions between the magnetic ions.     

ICP-MS multi-element analysis of wine samples - a comparative study of the methodologies used in two laboratories

A comparison of the performance of the methodologies used in two distinct laboratories (Lab A and Lab B) for multi-element analysis in different wines was carried out. ICP-MS apparatus (quadrupole mass analyzers) of different brands as well as different wine pre-treatments were used. At Lab A, a pre-treatment by UV-irradiation was performed. At Lab B, a micro-concentric nebulizer was used for direct analysis of the wine. Twenty-six elements (Li, V, Co, Ni, Cu, Zn, Ga, As, Rb, Sr, Ba, La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, Lu, and Pb) were measured in common at the two labs in three different wine samples (red and white Bordeaux table wines and Port wine) and the results were compared. The two methodologies provided similar LODs and similar precisions, with RSDs of 0.5-5%, for most of the elements. The recovery percentages were 85-120% at Lab A for the three wines, and 78-119% at Lab B for the Bordeaux wines, validating the accuracy of the methods used. Comparable results were obtained at both labs for ten elements (Li, V, Co, Ni, Cu, Zn, Rb, Sr, Ba, and Pb) in the three selected wines; the differences were lower than 10% in most cases. For REEs, the differences observed were slightly higher, but still in the acceptable range due to the sub-ppb levels involved. The results obtained for As and Ga were not comparable, due to methodological influence. A comparison through linear least-squares adjustment indicated that the results obtained by the two labs were linearly correlated (correlation coefficient =0.997) but statistically different as the slope was slightly, but significantly different from one, for a confidence level of 95% (the intercept was statistically identical to zero in any case). In the future, strictly more identical results can be achieved by using a reference wine sample.     

Mapping potential energy surfaces

A recently proposed dynamical method [A. Laio and M. Parrinello, Proc. Natl. Acad. Sci. U.S.A. 99, 12562 (2002)] allows us to globally sample the free energy surface. This approach uses a coarse-grained non-Markovian dynamics to bias microscopic atomic trajectories. After a sufficiently long simulation time, the global free energy surface can be reconstructed from the non-Markovian dynamics. Here we apply this scheme to study the T=0 free energy surface, i.e., the potential energy surface in coarse-grained space. We show that the accuracy of the reconstructed potential energy surface can be dramatically improved by a simple postprocessing procedure with only minor computational overhead. We illustrate this approach by conducting conformational analysis on a small organic molecule, demonstrating its superiority over traditional unbiased approaches in sampling potential energy surfaces in coarse-grained space.     

Ultrathin-layer sodium dodecyl sulfate disc electrophoresis of proteins in the range from 10 to 220 kDa in homogeneous,low-concentrated polyacrylamide gels

This study describes an ultrathin-layer sodium dodecyl sulfate (SDS) disc electrophoresis in polyacrylamide gels of a thickness of only 150 microm. By use of 2-amino-2-methyl-1,3-propanediol/glycine instead of traditional Tris/HCl buffer in the resolving phase of the gel, proteins with a wide range of molecular sizes (10 kDa to over 220 kDa) are separated in unusually low-concentrated gels (4%T, 3.3%C). 2-Amino-2-methyl-1,3-propanediol in the resolving part of the gel contributes to stabilization of the pH value at 8.8, while glycine improves destacking as well as separation of small proteins from the bulk of stacked SDS. This method combines both the advantages of conventional slab-gel electrophoresis and capillary gel electrophoresis. It is easy to apply and well suited for all further miniaturization attempts.     

Factor probabilistic distance clustering (FPDC): a new clustering method

Factor clustering methods have been developed in recent years thanks to improvements in computational power. These methods perform a linear transformation of data and a clustering of the transformed data, optimizing a common criterion. Probabilistic distance (PD)-clustering is an iterative, distribution free, probabilistic clustering method. Factor PD-clustering (FPDC) is based on PD-clustering and involves a linear transformation of the original variables into a reduced number of orthogonal ones using a common criterion with PD-clustering. This paper demonstrates that Tucker3 decomposition can be used to accomplish this transformation. Factor PD-clustering alternatingly exploits Tucker3 decomposition and PD-clustering on transformed data until convergence is achieved. This method can significantly improve the PD-clustering algorithm performance; large data sets can thus be partitioned into clusters with increasing stability and robustness of the results. Real and simulated data sets are used to compare FPDC with its main competitors, where it performs equally well when clusters are elliptically shaped but outperforms its competitors with non-Gaussian shaped clusters or noisy data.     

Robust energy planning in buildings with energy and comfort costs

Energy management in buildings is addressed in this paper. The energetic impact of buildings in the current energetic context is first depicted. Then the studied optimization problem is defined as the optimal management of production and consumption activities in houses. A scheduling problem is identified to adjust the energy consumption to both the energy cost and the inhabitant’s comfort. The available flexibilities of the services provided by domestic appliances are used to compute optimal energy plans. These flexibilities are associated to time windows or heating storage abilities. A constraints formulation of the energy allocation problem is given. A derived mixed linear program is used to solve this problem. The energy consumption in houses is very dependent to uncertain data such as weather forecasts and inhabitants’ activities. Parametric uncertainties are introduced in the home energy management problem in order to provide robust energy allocation. Robust linear programming is implemented. Event related uncertainties are also addressed through stochastic programming in order to take into account the inhabitant’s activities. A scenario based approach is implemented to face this robust optimization problem.