Synthesis, characterization and photocatalytic evaluation of visible light activated C-doped TiO2 nanoparticles

We have demonstrated heterogeneous photocatalytic degradation of microcystin-LR (MC-LR) by visible light activated carbon doped TiO(2) (C-TiO(2)) nanoparticles, synthesized by a modified sol-gel route based on the self-assembly technique exploiting oleic acid as a pore directing agent and carbon source. The C-TiO(2) nanoparticles crystallize in anatase phase despite the low calcination temperature of 350 °C and exhibit a highly porous structure that can be optimized by tuning the concentration of the oleic acid surfactant. The carbon modified nanomaterials exhibited enhanced absorption in the broad visible light region together with an apparent red shift in the optical absorption edge by 0.5 eV (2.69 eV), compared to the 3.18 eV of reference anatase TiO(2). Carbon species were identified by x-ray photoelectron spectroscopy analysis through the formation of both Ti-C and C-O bonds, indicative of substitution of carbon for oxygen atoms and the formation of carbonates, respectively. Electron paramagnetic resonance spectroscopy revealed the formation of two carbon related paramagnetic centers in C-TiO(2), whose intensity was markedly enhanced under visible light illumination, pointing to the formation of localized states within the anatase band gap, following carbon doping. The photocatalytic activity of C-TiO(2) nanomaterials was evaluated for the degradation of MC-LR at pH 3.0 under visible light (λ > 420 nm) irradiation. The doped materials showed a higher MC-LR degradation rate than reference TiO(2), behavior that is attributed to the incorporation of carbon into the titania lattice.     

Adaptively preconditioned Krylov spaces to identify irrelevant predictors

Linear regression methods have problems in estimation when the predictor variables are highly correlated and when their number exceeds the number of available observations. PLS is one well known method for handling such ill-conditioned regression problems. It does so by approximating the regression solution in a low dimensional subspace. While it copes with collinearity and singularity problems, PLS does not have a variable selection procedure intrinsic to the method. However, it is often the case that one needs to decide which predictors, among the numerous and correlated ones, are the more relevant. The PLS coefficient is a good starting point for the identification of relevant variables in ill-conditioned regression settings. We propose to adaptively precondition the space generated by PLS in order to determine the most relevant predictors. The relevant subset is determined by a multiple testing procedure, and preconditioning stops when this set no longer changes. The principal objective is to do regression modelling and to recover solutions that are easy to interpret in the high dimensional regression setting. We use dimension reduction in a PLS fashion, using information on the response to guide the variable selection procedure. A variety of examples is studied with good results.     

Wave log‐domain filters using lattice sections

In this paper, the design of log‐domain filters with uncommon transfer functions is considered, using the wave log‐domain design method. To this end, the concept of log‐domain wave equivalent of a lattice section is introduced, as a new building block, in order to enable the design of filters with transfer functions dealing with amplitude and phase response at the same time. This building block is very useful when the phase and the group delay response of the filter is significant. The functionality of this design approach is verified through a design example and simulation results. Copyright © 2010 John Wiley & Sons, Ltd.     

Potato: a comparative study of the effect of cultivars and cultivation conditions and genetic modification on the physico-chemical properties of potato tubers in conjunction with multivariate analysis towards authenticity

Potato (Solanum tuberosum L.) is a highly nutritious, mild flavored, easy to blend food that has many possibilities for "building in" desired nutrients. Varietal and environmental differences are known to exist in the shape, size, and nutritional content of potatoes. Different populations opt for varying sensory properties in relation to their diets. Potatoes are a low energy food in comparison to cereals and legumes. The aim of this review was to present an update of the currently conducted studies both on the characterization of several potato varieties (physical, chemical, and sensory analysis) and by means of genetic modification. Towards this target, five comprehensive tables were compiled where all recent data (physicochemical properties) and GM varieties were presented in conjunction with multivariate analysis (chemometrics). The latter was shown to be effectively used towards authenticity purposes (identification of geographical origin, variety, GM).     

Optimizing bus services with variable directional and temporal demand using genetic algorithm

As a major mode choice of commuters for daily travel, bus transit plays an important role in many urban and metropolitan areas. This work proposes a mathematical model to optimize bus service by minimizing total cost and considering a temporally and directionally variable demand. An integrated bus service, consisting of all-stop and stop-skipping services is proposed and optimized subject to directional frequency conservation, capacity and operable fleet size constraints. Since the research problem is a combinatorial optimization problem, a genetic algorithm is developed to search for the optimal result in a large solution space. The model was successfully implemented on a bus transit route in the City of Chengdu, China, and the optimal solution was proved to be better than the original operation in terms of total cost. The sensitivity of model parameters to some key attributes/variables is analyzed and discussed to explore further the potential of accruing additional benefits or avoiding some of the drawbacks of stop-skipping services.     

A metaheuristic approach for the sequencing by hybridization problem with positive and negative errors

This work introduces a metaheuristic method for the reconstruction of the DNA string from its l-mer content in the presence of large amounts of positive and negative errors. The procedure consists of three parts: the formulation of the problem as an asymmetric traveling salesman problem (ATSP), a technique for handling the positive errors and an optimization algorithm that solves the formulated problem. The optimization algorithm is a variation of the threshold accepting method with intense local search and its function is controlled by a size diminishing shell. The optimization algorithm is used consecutively on ATSPs of continuously decreasing sizes till it reaches a final solution. The proposed method provides solutions of better quality compared to algorithms in the recent bibliography.     

Nanostructured titania films sensitized by quantum dot chalcogenides

The optical and structural properties of cadmium and lead sulfide nanocrystals deposited on mesoporous TiO₂ substrates via the successive ionic layer adsorption and reaction method were comparatively investigated by reflectance, transmittance, micro-Raman and photoluminescence measurements. Enhanced interfacial electron transfer is evidenced upon direct growth of both CdS and PbS on TiO₂ through the marked quenching of their excitonic emission. The optical absorbance of CdS/TiO₂ can be tuned over a narrow spectral range. On the other side PbS/TiO₂ exhibits a remarkable band gap tunability extending from the visible to the near infrared range, due to the distinct quantum size effects of PbS quantum dots. However, PbS/TiO₂ suffers from severe degradation upon air exposure. Degradation effects are much less pronounced for CdS/TiO₂ that is appreciably more stable, though it degrades readily upon visible light illumination.