Diamond/porous titanium three-dimensional hybrid electrodes

Hybrid three-dimensional electrodes produced from microcrystalline boron-doped diamond (BDD) and/or nanocrystalline diamond films were grown on porous titanium (Ti) substrate by hot filament chemical vapor deposition (HFCVD) technique. Powder metallurgy technique was used to obtain the Ti substrates provided by interconnected and open pores among its volume. Diamond growth parameters were optimized in order to provide the entire substrate surface covering including the deeper surfaces, pore bottoms, and walls. The morphology and structure of these electrodes were studied by scanning electron microscopy (SEM) and visible Raman spectroscopy techniques, respectively. Electrochemical response was characterized by cyclic voltammetry measurements. Results showed a wide working potential window and low background current characteristic of the diamond electrodes. The kinetic parameters also pointed out to a quasi-reversible behavior for these hybrid three-dimensional diamond/Ti electrodes.     

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.     

Nonlinear spectrum effect on the coherent control of molecular systems

This work demonstrates that the detuning of the fs-laser spectrum from the two-photon absorption band of organic materials can be used to reach further control of the two-photon absorption by pulse spectral phase manipulation. We investigate the coherent control of the two-photon absorption in imidazole-thiophene core compounds presenting distinct two-photon absorption spectra. The coherent control, performed using pulse phase shaping and genetic algorithm, exhibited different growth rates for each sample. Such distinct trends were explained by calculating the two-photon absorption probability considering the intrapulse interference mechanism, taking into account the two-photon absorption spectrum of the samples. Our results indicate that tuning the relative position between the nonlinear absorption and the pulse spectrum can be used as a novel strategy to optimize the two-photon absorption in broadband molecular systems.     

Electronics with and on paper

Today there is a strong interest in the scientific and industrial community concerning the use of biopolymers for electronic applications, driven mainly by low‐cost and disposable applications. Adding to this interest, we must recognise the importance of the dream of wireless auto‐sustained and low‐energy‐consumption electronics. This dream can be fulfilled by cellulose paper, the lightest and the cheapest known substrate material, as well as the Earth's major biopolymer and of tremendous global economic importance. Most of the paper used up to now is optimised in terms of the required mechanical and physical properties to be used as the support of inks of different origins. In the future, specific electronic heterogeneous paper sheets should be fabricated aiming to get paper fibers with required bulk and surface functionalities, proper water/vapour barrier, size and diameter/thickness of the fibrils and full paper thickness. This will be the function of components/devices to be incorporated/integrated such as thin‐film transistors, complementary metal oxide semiconductor devices, passive electronic components (resistances, inductors and capacitors), memory transistors, electrochromics and thin‐film paper batteries. (© 2011 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

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.     

Nonlinear perturbations of a ‐Laplacian equation with critical growth in

We prove the existence of solution for a class of ‐Laplacian equations where the nonlinearity has a critical growth. Here, we consider two cases: the first case involves the situation where the variable exponents are periodic functions. The second one involves the case where the variable exponents are nonperiodic perturbations.     

Self-similar solutions for active scalar equations in Fourier–Besov–Morrey spaces

We are concerned with a family of dissipative active scalar equation with velocity fields coupled via multiplier operators that can be of positive-order. We consider sub-critical values for the fractional diffusion and prove global well-posedness of solutions with small initial data belonging to a framework based on Fourier transform, namely Fourier–Besov–Morrey spaces. Since the smallness condition is with respect to the weak norm of this space, some initial data with large \(L^{2}\) -norm can be considered. Self-similar solutions are obtained depending on the homogeneity of the initial data and couplings. Also, we show that solutions are asymptotically self-similar at infinity. Our results can be applied in a unified way for a number of active scalar PDEs like 1D models on dislocation dynamics in crystals, Burgers’ equation, 2D vorticity equation, 2D generalized SQG, 3D magneto-geostrophic equations, among others.     

A genetic algorithm with neural network fitness function evaluation for IMRT beam angle optimization

Intensity Modulated Radiotherapy Treatment (IMRT) is a technique used in the treatment of cancer, where the radiation beams are modulated by a multileaf collimator allowing the irradiation of the patient using non-uniform radiation fields from selected angles. Beam angle optimization consists in trying to find the best set of angles that should be used in IMRT planning. The choice of this set of angles is patient and pathology dependent and, in clinical practice, most of the times it is made using a trial and error procedure or simply using equidistantly distributed angles. In this paper we propose a genetic algorithm that aims at calculating good sets of angles in an automated way, given a predetermined number of angles. We consider the discretization of all possible angles in the interval [0 \(^{\circ }\) , 360 \(^{\circ }\) ], and each individual is represented by a chromosome with 360 binary genes. As the calculation of a given individual’s fitness is very expensive in terms of computational time, the genetic algorithm uses a neural network as a surrogate model to calculate the fitness of most of the individuals in the population. To explicitly consider the estimation error that can result from the use of this surrogate model, the fitness of each individual is represented by an interval of values and not by a single crisp value. The genetic algorithm is capable of finding improved solutions, when compared to the usual equidistant solution applied in clinical practice. The genetic algorithm will be described and computational results will be shown.     

Confined modified realizability

We present a refinement ofthe bounded modified realizability which provides both upper and lower bounds for witnesses. Our interpretation is based on a generalisation of Howard/Bezem's notion of strong majorizability. We show how the bounded modified realizability coincides with (a weak version of) our interpretation in the case when least elements exist (e.g. natural numbers). The new interpretation, however, permits the extraction of more accurate bounds, and provides an ideal setting for dealing directly with data types whose natural ordering is not well‐founded (© 2010 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)