Transient Stochastic Analysis of Biodegradable Contaminant Transport: First-Order Decay

A stochastic methodology was used to analyze the field-scale transport of solutes in heterogeneous aquifers with first-order biodegradation. Spectral methods and perturbation techniques were utilized to develop expressions for the field-scale effective parameters in the mean transport model. Expressions were obtained for the longitudinal and transverse macrodispersivity coefficients, and effective velocity and an effective decay parameter for statistically anisotropic, and isotropic, heterogeneous porous medium, respectively. The behavior of these parameters was described as function of time and log K correlation scale. The expressions for asymptotic values of the dispersivity coefficients and effective velocity and decay parameters were also derived for the isotropic case.     

Variability in UVB tolerances of melanized and nonmelanized cells of Cryptococcus neoformans and C. laurentii

Solar radiation is one of the major factors responsible for the control of fungus populations in the environment. Inactivation by UVA and UVB radiation is especially important for the control of fungi that disperse infective units through the air, including fungi such as Cryptococcus spp. that infect their vertebrate hosts by inhalation. Cryptococcus neoformans produces melanin in the presence of certain exogenous substrates such as l-3,4 dihydroxyphenylalanine and melanization may protect the fungus against biotic and abiotic environmental factors. In the present study, we investigated the effect of exposure to an UVB irradiance of 1000 mW m(-2) (biologically effective weighted irradiance) on the survival of melanized and nonmelanized cells of four strains of C. neoformans and four strains of C. laurentii. The relative survival (survival of cells exposed to radiation in relation to cells not exposed) of cells grown 2, 4, 6 or 8 days on medium with or without L-dopa was determined after exposure to UVB doses of 1.8 and 3.6 kJ m(-2). Both the irradiance spectrum and the intensities of those doses are environmentally realistic, and, in fact, occur routinely during summer months in temperate regions. Differences in tolerance to UVB radiation were observed between the C. neoformans and C. laurentii strains. The C. neoformans strains were more susceptible to UVB radiation than the C. laurentii strains. In C. neoformans, differences in tolerance to radiation were observed during development of both melanized and nonmelanized cells. For most treatments (strain, time of growth and UVB dose), there were virtually no differences in tolerances between melanized and nonmelanized cells, but when differences occurred they were smaller than those previously observed with UVC. In tests with two strains of C. laurentii, there was no difference in tolerance to UVB radiation between melanized and nonmelanized cells during 8 days of culture; and in tests with four strains for less culture time (4 days) there were no significant differences in tolerance between melanized and nonmelanized cells of any strain of this species.     

Qualitative operators for reasoning maps: Evaluating multi-criteria options with networks of reasons

Cognitive/causal maps have been widely used as a powerful way of capturing decision-makers’ views about a problem, representing it as a cause–effect discourse. Several ways of making causal inferences from this type of model have been proposed in the Operational Research and Artificial Intelligence literatures, but none, as far as we are aware, has attempted to use a causal map structure to perform a multi-criteria evaluation of decision alternatives. Recently, we have proposed a new multi-criteria method, denominated as a Reasoning Map, which permits the use of decision-makers’ reasoning, structured as a network of means-and-ends (a particular type of causal map) to perform such an evaluation. In this manner, the model resembles the way that people talk and think about decisions in practice. The method also pays explicit attention to the cognitive limitations of decision-makers in providing preference information. Thus it employs qualitative assessment of preferences, utilises aggregation operators for qualitative data and provides also qualitative outputs. In this paper we discuss and evaluate possible ways of aggregating qualitative performance information in Reasoning Maps.     

Likelihood stabilization for ill-conditioned vector GARCH models

The likelihood of vector GARCH models is ill-conditioned because of two facts. First, when the series display high correlations, as often happens with financial data, some eigenvalues of the conditional covariance matrix are close to zero. Second, the likelihood function is very flat in the neighborhood of the optimum due to the functional form of the GARCH process. These facts explain the instability of multivariate GARCH estimation procedures. Building on this analysis, we suggest a data transformation which moves the critical eigenvalues far from zero and, therefore, improves the stability of iterative optimization methods. The transformed values are re-scaled principal components, so their interpretation is straightforward. The application of this technique is illustrated by modeling the short-run conditional correlations of four nominal exchange rates.      

Piecewise finite series solutions of seasonal diseases models using multistage Adomian method

The aim of this paper is to apply the multistage Adomian Decomposition Method MADM to solve systems of nonautonomous nonlinear differential equations that describe several epidemic models with periodic behavior. Here the concept of the MADM is introduced and then it is employed to obtain a piecewise finite series solution. The MADM is used here as a hybrid analytical–numerical technique for approximating the solutions of the epidemic models. In order to show the efficiency of the method, the obtained numerical results are compared with the fourth-order Runge–Kutta method solutions. Numerical comparisons show that the MADM is accurate, easy to apply and the calculated solutions preserve the periodic behavior of the continuous models. Moreover, the method has the advantage of giving a functional form of the solution for any time interval. Furthermore, it is shown that if the truncation order and the time step size are not properly chosen large computational work is required and inaccurate solutions may be obtained.     

Montmorillonite as an adsorbent for extraction and concentration of atrazine, propazine, deethylatrazine, deisopropylatrazine and hydroxyatrazine

Adsorption properties of the clay mineral montmorillonite in the potassium homoionic form (KMT) was investigated to achieve the extraction and concentration of the herbicides atrazine (AT) and propazine (PROP), as well as the main degradation products of atrazine, namely deethylatrazine (DEA), deisopropylatrazine (DIA) and hydroxyatrazine (ATOH). A batch approach was proposed, with recovery percentages for AT, PROP and DIA higher than 90% at concentrations of 0.50 and 2.50 μg L⁻¹. For DEA and ATOH, however, low recoveries were obtained. For DEA, this fact can be explained by its low K_d with KMT, contrary to ATOH, which interacts strongly with the mineral surface, hindering the complete desorption and hence, generating low recovery percentages. The influence of pH, ionic strength and humic acid was studied, and a comparison with the C₁₈ phase as SPE cartridges was carried out. Montmorillonite showed a similar performance to commercial cartridge for concentrations of AT, DEA and PROP, but better recoveries for DIA was obtained using the clay mineral. For ATOH the recovery was also higher on the clay mineral, although for this compound the most suitable SPE cartridge is constituted by cation exchange resin. After the concentration and elution steps, the 0.50 and 2.50 μg L⁻¹ gave chromatographic peak areas that could be easily quantified with an analytical curve obtained in the concentration range between 7.5 and 100 μg L⁻¹. The obtained concentration factors are suitable to allow the application of the method to the monitoring of triazine residues in drinking water.     

Analytical methods for determination of new fluoroquinolones in biological matrices and pharmaceutical formulations by liquid chromatography: a review

Fluoroquinolones are one of the most promising and intensively studied drugs of contemporary anti-infective chemotherapy. New fluoroquinolone antibacterials with improved pharmacokinetic properties and a broad spectrum of activity have been developed, opening new windows of opportunity for clinical use. To our knowledge, no comprehensive and critical review of the analytical methods for the determination of these agents, which correspond to the third- and fourth-generation quinolones, has yet been published. This work summarizes for the first time most of the liquid chromatographic methods reported in the literature for the separation and quantification of the new fluoroquinolones in biological matrices and pharmaceutical formulations. A systematic and detailed survey of physicochemical properties, sample preparation procedures, and chromatographic and detection conditions is presented herein. In the course of this review several liquid chromatographic methods are discussed: reversed-phase high-performance liquid chromatography (RP-HPLC), ion-exchange high-performance liquid chromatography (IEX-HPLC), hydrophilic interaction liquid chromatography (HILIC), high-performance thin-layer chromatography (HPTLC) and other chiral chromatographic methods. Their advantages, applicability and limitations are also examined.     

Quantitative analysis of structure and bandgap changes in graphene oxide nanoribbons during thermal annealing

Graphene oxide nanoribbons (GONRs) are wide bandgap semiconductors that can be reduced to metallic graphene nanoribbons. The transformation of GONRs from their semiconductive to the metallic state by annealing has attracted significant interest due to its simplicity. However, the detailed process by which GONRs transform from wide-bandgap semiconductors to semimetals with a near zero bandgap is unclear. As a result, precise control of the bandgap between these two states is not currently achievable. Here, we quantitatively examine the removal of oxygen-containing groups and changes in the bandgap during thermal annealing of GONRs. X-ray photoelectron spectroscopy measurements show the progressive removal of oxygen-containing functional groups. Aberration-corrected scanning transmission electron microscopy reveals that initially small graphene regions in GONRs become large stacked graphitic layers during thermal annealing. These structural and chemical changes are correlated with progressive changes in the electrochemical bandgap, monitored by cyclic voltammetry. These results show that small changes in the thermal annealing temperature result in significant changes to the bandgap and chemical composition of GONRs and provide a straightforward method for tuning the bandgap in oxidized graphene structures.     

Ecological interaction and phylogeny, studying functionality on composed networks

We study a class of composed networks that are formed by two tree networks, T_P and T_A, whose end points touch each other through a bipartite network B_PA. We explore this network using a functional approach. We are interested in how much the topology, or the structure, of T_X (X=A or P) determines the links of B_PA. This composed structure is a useful model in evolutionary biology, where T_P and T_A are the phylogenetic trees of plants and animals that interact in an ecological community. We make use of ecological networks of dispersion of fruits, which are formed by frugivorous animals and plants with fruits; the animals, usually birds, eat fruits and disperse their seeds. We analyse how the phylogeny of T_X determines or is correlated with B_PA using a Monte Carlo approach. We use the phylogenetic distance among elements that interact with a given species to construct an index κ that quantifies the influence of T_X over B_PA. The algorithm is based on the assumption that interaction matrices that follows a phylogeny of T_X have a total phylogenetic distance smaller than the average distance of an ensemble of Monte Carlo realisations. We find that the effect of phylogeny of animal species is more pronounced in the ecological matrix than plant phylogeny.