A multicommutated flow system for determination of bismuth in milk shakes by hydride generation atomic fluorescence spectrometry incorporating on-line neutralization of waste effluent

A highly sensitive method was developed for determination of bismuth in milk shakes by multicommutation hydride generation atomic fluorescence spectrometry (HG-AFS) based on off-line sonication for 10 min with aqua regia 8% (v/v) and on-line waste treatment. The instrumentation and chemistry variables were studied in order to provide the best performance. The limit of detection in the original samples, established for a probability level of 99.6% (k = 3), was 1.67 ng/g Bi. The method provides a fast alternative in control analysis with a sampling throughput of 72 h as compared with 31 h obtained by the classical continuous measurement. Additionally, multicommutation reduces waste generation by a factor of 2.6. The consumption of sample, reductant, and blank, as compared with continuous mode HG-AFS, was reduced 9.6, 4.5, and 13.3 times, respectively. To confirm the accuracy of the method, recovery studies were performed, and excellent agreement between multicommutation and continuous measurement-based values was obtained. Application of the developed methodology for bismuth determination in milk shake samples from the Spanish market provided concentrations ranging from 4.2 to 15.0 ng/mL, and good comparability with data obtained by continuous measurements after microwave-assisted total digestion of samples for a 95% probability level and 12 degrees of freedom was found.     

Nonstochastic behavior of atomic surface diffusion on Cu(111) down to low temperatures

Atomic diffusion is usually understood as a succession of random, independent displacements of an adatom over the surface's potential energy landscape. Nevertheless, an analysis of molecular dynamics simulations of self-diffusion on Cu(111) demonstrates the existence of different types of correlations in the atomic jumps at all temperatures. Thus, the atomic displacements cannot be correctly described in terms of a random walk model. This fact has a profound impact on the determination and interpretation of diffusion coefficients and activation barriers.     

Comparative analysis of the conformational profile of substance P using simulated annealing and molecular dynamics

The present study describes an extensive conformational search of substance P using two different computational methods. On the one hand, the peptide was studied using the iterative simulated annealing, and on the other, molecular dynamics simulations at 300 and 400 K. With the former method, the peptide was studied in vacuo with a dielectric constant of 80, whereas using the latter study the peptide was studied in a box of TIP3P water molecules. Analysis of the results obtained using both methodologies was carried out using an in-house methodology using a cluster analysis method based on information theory. Comparison of the two sampling methodologies and the different environment used in the calculations is also analyzed. Finally, the conformational motifs that are characteristic of substance P in a hydrophilic environment are presented and compared with the experimental results available in the literature.     

Geometrical-numerical approach to diffraction phenomena

The calculation of diffracted fields is considered by means of a geometrical analysis of the incoming wave into semiperiodic zones in the aperture plane, followed by a numerical process for addition of the contributions corresponding to the semiperiodic zones. This general approach constitutes a novel interpretation of diffraction phenomena that permits exact evaluation of the mathematical expressions of diffraction theory and overcomes the limitations of any approximation. The method is illustrated by analysis of two important configuration in optics: the pinhole camera, for which we deduce the optimum radius for imaging, and the diffraction of a spherical converging wave through a circular aperture, from which we determine the limit of the validity of the Fraunhofer approximation (i.e., of the Airy pattern) and the influence of the obliquity factor.     

Downside Risk analysis applied to the Hedge Funds universe

Hedge Funds are considered as one of the portfolio management sectors which shows a fastest growing for the past decade. An optimal Hedge Fund management requires an appropriate risk metrics. The classic CAPM theory and its Ratio Sharpe fail to capture some crucial aspects due to the strong non-Gaussian character of Hedge Funds statistics. A possible way out to this problem while keeping the CAPM simplicity is the so-called Downside Risk analysis. One important benefit lies in distinguishing between good and bad returns, that is: returns greater or lower than investor's goal. We revisit most popular Downside Risk indicators and provide new analytical results on them. We compute these measures by taking the Credit Suisse/Tremont Investable Hedge Fund Index Data and with the Gaussian case as a benchmark. In this way, an unusual transversal lecture of the existing Downside Risk measures is provided.     

Classification of Dansgaard–Oeschger climatic cycles by the application of similitude signal processing

In this work we have performed a detailed analysis, using signal processing tools, to study time series of data (temperature proxy) extracted from the GRIP ice-core records and we relate it with the evolution of atmospheric CO₂ within the last glacial period. Our method is based in considering the warm periods known as Dansgaard–Oeschger (D/O) events and posterior returns to the cold stage as a climatic cycle. After the warming phase, D/O events relax to the initial cold state in three different ways, what gives rise to three classes of cycles. Also, the Younger/Dryas–Bolling/Allerod (Y/D–B/A) cycle corresponds to one of the classes obtained. We have found that all cycles start with identical warming phases which seem completely unrelated to variations in CO₂ concentration. We discuss on the consequences for global climatology of such steady pattern of cycles.     

Ion binding to polyelectrolytes: Monte Carlo simulations versus classical mean field theories

The influence of ion size and surface charge model in titrations of ionizable polyelectrolytes is studied by means of the Semi Grand Canonical Monte Carlo simulation method in the context of the primitive model. Three models describing a discrete distribution of charged functional groups on the polyelectrolyte and different values for the radius of the background electrolyte spanning from ionic to hydrated radii values were analyzed. The polyelectrolyte titrations were simulated by calculating the degree of ionization versus pH curves at two ionic strengths. The results allow us to quantify the impact of the sizes of the background salt ions and surface functional groups of the polyelectrolyte on the dissociation degree. This influence is explained in terms of the effectiveness of the screening of the charged surface sites. Finally, by comparison with the Non-Linear Poisson–Boltzmann model, the influence of ionic correlations and finite size of the solution ions is assessed.