Characterization of the Excited States of Indigo Derivatives in their Reduced Forms

A comprehensive characterization of the electronic spectral and photophysical properties of the leuco (reduced) form of several indigo derivatives, including indigo and Tyrian Purple, with di‐, tetra‐, and hexa‐substitution, was obtained in solution. The characterization involves absorption, fluorescence, and triplet–triplet absorption spectra, together with quantitative measurements of quantum yields of fluorescence, ?_F (0.46–0.04), intersystem crossing, ?_T (0.013–0.034), internal conversion, ?_IC, and the corresponding lifetimes. The position and degree of substitution promote differences in the spectral and photophysical properties displayed by the investigated leuco derivatives. The ?_F values are about two orders of magnitude higher than those previously obtained for the corresponding keto forms. Also in contrast with the behavior found for the keto forms, the S₁～～→T₁ intersystem crossing is an efficient route for the excited‐state deactivation channel. These findings strengthen the fact that, in contrast to keto indigo where the internal conversion dominates the deactivation of the excited‐state, with leuco indigo (and derivatives), the excited state deactivation involves competition between internal conversion, triplet state formation, and fluorescence. A time‐resolved investigation of one of the compounds in glycerol showed the presence of a photoisomerization process.     

Quantification of endocrine disruptors and pesticides in water by gas chromatography–tandem mass spectrometry. Method validation using weighted linear regression schemes

A multi-residue methodology based on a solid phase extraction followed by gas chromatography–tandem mass spectrometry was developed for trace analysis of 32 compounds in water matrices, including estrogens and several pesticides from different chemical families, some of them with endocrine disrupting properties. Matrix standard calibration solutions were prepared by adding known amounts of the analytes to a residue-free sample to compensate matrix-induced chromatographic response enhancement observed for certain pesticides. Validation was done mainly according to the International Conference on Harmonisation recommendations, as well as some European and American validation guidelines with specifications for pesticides analysis and/or GC–MS methodology. As the assumption of homoscedasticity was not met for analytical data, weighted least squares linear regression procedure was applied as a simple and effective way to counteract the greater influence of the greater concentrations on the fitted regression line, improving accuracy at the lower end of the calibration curve. The method was considered validated for 31 compounds after consistent evaluation of the key analytical parameters: specificity, linearity, limit of detection and quantification, range, precision, accuracy, extraction efficiency, stability and robustness.     

A heuristic algorithm based on multi-assignment procedures for nurse scheduling

This paper tackles a Nurse Scheduling Problem which consists of generating work schedules for a set of nurses while considering their shift preferences and other requirements. The objective is to maximize the satisfaction of nurses’ preferences and minimize the violation of soft constraints. This paper presents a new deterministic heuristic algorithm, called MAPA (multi-assignment problem-based algorithm), which is based on successive resolutions of the assignment problem. The algorithm has two phases: a constructive phase and an improvement phase. The constructive phase builds a full schedule by solving successive assignment problems, one for each day in the planning period. The improvement phase uses a couple of procedures that re-solve assignment problems to produce a better schedule. Given the deterministic nature of this algorithm, the same schedule is obtained each time that the algorithm is applied to the same problem instance. The performance of MAPA is benchmarked against published results for almost 250,000 instances from the NSPLib dataset. In most cases, particularly on large instances of the problem, the results produced by MAPA are better when compared to best-known solutions from the literature. The experiments reported here also show that the MAPA algorithm finds more feasible solutions compared with other algorithms in the literature, which suggest that this proposed approach is effective and robust.     

An efficient heuristic approach for a multi-period logistics network redesign problem

In this paper, a multi-period logistics network redesign problem arising in the context of strategic supply chain planning is studied. Several aspects of practical relevance are captured, namely, multiple echelons with different types of facilities, product flows between facilities in the same echelon, direct shipments to customers, and facility relocation. A two-phase heuristic approach is proposed to obtain high-quality feasible solutions to the problem, which is initially modeled as a large-scale mixed-integer linear program. In the first phase of the heuristic, a linear programming rounding strategy is applied to find initial values for the binary location variables. The second phase of the heuristic uses local search to correct the initial variable choices when a feasible solution is not identified, or to improve the initial feasible solution when its quality does not meet given criteria. The results of a computational study are reported for randomly generated instances comprising a variety of logistics networks.     

Robust pair‐copula based forecasts of realized volatility

A useful application for copula functions is modeling the dynamics in the conditional moments of a time series. Using copulas, one can go beyond the traditional linear ARMA (p,q) modeling, which is solely based on the behavior of the autocorrelation function, and capture the entire dependence structure linking consecutive observations. This type of serial dependence is best represented by a canonical vine decomposition, and we illustrate this idea in the context of emerging stock markets, modeling linear and nonlinear temporal dependences of Brazilian series of realized volatilities. However, the analysis of intraday data collected from e‐markets poses some specific challenges. The large amount of real‐time information calls for heavy data manipulation, which may result in gross errors. Atypical points in high‐frequency intraday transaction prices may contaminate the series of daily realized volatilities, thus affecting classical statistical inference and leading to poor predictions. Therefore, in this paper, we propose to robustly estimate pair‐copula models using the weighted minimum distance and the weighted maximum likelihood estimates (WMLE). The excellent performance of these robust estimates for pair‐copula models are assessed through a comprehensive set of simulations, from which the WMLE emerged as the best option for members of the elliptical copula family. We evaluate and compare alternative volatility forecasts and show that the robustly estimated canonical vine‐based forecasts outperform the competitors. Copyright © 2013 John Wiley & Sons, Ltd.     

Integrating nonlinear branch-and-bound and outer approximation for convex Mixed Integer Nonlinear Programming

In this paper, we present a new hybrid algorithm for convex Mixed Integer Nonlinear Programming (MINLP). The proposed hybrid algorithm is an improved version of the classical nonlinear branch-and-bound (BB) procedure, where the enhancements are obtained with the application of the outer approximation algorithm on some nodes of the enumeration tree. The two methods are combined in such a way that each one collaborates to the convergence of the other. Computational experiments with benchmark instances of the MINLP problem show the good performance of the proposed algorithm, which is compared to the outer approximation algorithm, the nonlinear BB algorithm and the hybrid algorithm implemented in the solver Bonmin.     

Electronic and magnetic properties of double perovskites (, Ca)

We have studied the magnetic and electronic properties of double perovskites A₂FeReO₆ with A=Ba and Ca using ab initio methods based on density functional theory. It has been shown that when changing Ba by Ca the system undergoes a metal–insulator transition coincidentally to a structural phase transition, even if conduction band fillings are not significantly changed. Our results suggest that only considering a quite large correlation term on the Re site could explain an insulating character for Ca₂FeReO₆. Instead, we found that small correlations could induce a bad metallic behavior as suggested in more recent experiments.     

Pt-Cu / ZSM-5 for removal of nitrates from drinking water

Removal of nitrates from drinking water by catalytic hydrogenation over ZSM-5 supported Pt-Cu catalysts was studied. Bimetallics Pt-Cu were prepared by ion exchange of copper on a parent monometallic platinum catalyst. Monometallic platinum catalysts are inactive for nitrate reduction, while Pt-Cu bimetallic catalysts are active for nitrate removal. In the bimetallic catalyst, the role of copper is probably to reduce nitrate according to a redox reaction. The addition of copper to Pt catalysts decreases the production of ammonium ions     

Low temperature magnetic properties of NdCu2

μSR experiments on NdCu₂ give evidence for short range order below 25\ K above T_N=6.5\ K. No signal was detected between 16\ K and 1.2\ K where neutron scattering reveals an incommensurate spin structure. Below 1.2\ K the μSR signal is recovered and shows a rotation with 22 MHz. This is interpreted with a squaring up of Nd spins accompanied by a decrease of magnon excitations which is reflected in a decrease of damping of the muon signal. This revised version was published online in July 2006 with corrections to the Cover Date.