The fate of 14C-radiolabelled diclofenac and 4'-hydroxydiclofenac in membrane bioreactor treatment of wastewater

This study aimed at enhancing knowledge on the fate of diclofenac (DF), together with its main human metabolite 4'-hydroxydiclofenac (4'OHDF), during wastewater treatment by using a laboratory-scale membrane bioreactor (MBR). The reactor was fed continuously with non-radiolabelled diclofenac for a one month period prior to a single pulse of a 14C-radiolabelled solution of DF and 4'OHDF. The solution spike contained approximately 25% 4'OHDF and 65% DF, which corresponds to the ratio observed in municipal sewage, as well as traces of two other metabolites. The radioactivity was monitored for a total of twelve days in the various output streams. The calculation of the complete mass balance in the system demonstrated that the major part of the radioactivity left the reactor with the permeate (88.7%), while 2.1% was recovered in the excess sludge. Negligible amounts were recovered in the off-gas traps and on the membranes. Chromatographic analyses of effluent samples, by means of HPLC-MS coupled in parallel to a radiodetector, displayed a different pattern than the one of the spiked solution. It showed the occurrence of three additional metabolites.     

ProDA: An End-to-End Wavelet-Based OLAP System for Massive Datasets

ProDA employs wavelets to support exact, approximate, and progressive OLAP queries on large multidimensional datasets, while keeping update costs relatively low. ProDA not only supports online execution of ad hoc analytical queries on massive datasets, but also extends the set of supported analytical queries to include the entire family of polynomial aggregate queries as well as the new class of plot queries.     

The MAC method

In this article recent advances in the Marker and Cell (MAC) method will be reviewed. The MAC technique dates back to the early 1960s at the Los Alamos Laboratories and this article starts with a historical review, and then a brief discussion of related techniques. Improvements since the early days of MAC (and the Simplified MAC - SMAC) include automatic time-stepping, the use of the conjugate gradient method to solve the Poisson equation for the corrected velocity potential, greater efficiency through stripping out the virtual particles (markers) other than those near the free surface, and more accurate approximations of the free surface boundary conditions, the addition of bounded high accuracy upwinding for the convected terms (thereby being able to solve higher Reynolds number flows), and a (dynamics) flow visualization facility. More recently, effective techniques for surface and interfacial flows and, in particular, for accurately tracking the associated surface(s)/interface(s) including moving contact angles have been developed. This article will concentrate principally on a three-dimensional version of the SMAC method. It will eschew both code verification and model validation; instead it will emphasize the applications that the MAC method can solve, from multiphase flows to rheology.     

Retrieving ocean surface current by 4-D variational assimilation of sea surface temperature images

In this article we propose a new method to estimate ocean mesoscale structures of the surface current velocity by processing sea surface satellite images. Assuming that the intensity level can be described by a transport-diffusion equation, the proposed approach is based on variational assimilation of image observations within a simple transport-diffusion model. This approach permits to retrieve the current velocity field from a sequence of satellite images. Results of processing synthetic data and real NOAA-AVHRR satellite images are presented and commented.     

Interannual vegetation phenology estimates from global AVHRR measurements: Comparison with in situ data and applications

In a previous paper, we described a procedure to correct the directional effects in AVHRR reflectance time series. The corrected measurements show much less high frequency variability than their original counterparts, which makes them suitable to study vegetation dynamics. The time series are used here to estimate the start and ending dates of the growing season for 18 years from 1982 to 1999. We focus on the interannual variations of these phenological parameters.A database of in situ phenology observations is used to quantify the accuracy of the satellite-based estimates. Although based on a limited sampling of the Northern mid and high latitudes, the comparison indicates that i) the satellite phenological product contains meaningful information on interannual onset anomalies; ii) there is a higher degree of consistency over regions covered by Broadleaf Forests, Grasses and cereal Crops than over those covered by Needleleaf Forests or Savannas; and iii) the satellite phenological product is of lower quality in regions with mountainous terrain. In favorable conditions, interannual variations of the onset are captured with an accuracy of a few days.As this satellite-derived product captures the interannual onset variability at ground-truth sites, we confidently use it to larger scales studies. Mapped at a continental scale, the onset anomalies show coherent patterns at the regional (≈ 1000 km) scale for the mid and high latitudes of the Northern hemisphere, which is consistent with a meteorological forcing. In the tropics, there is larger spatial heterogeneity, which suggests more complex controls of the phenology. The relation between vegetation phenology and climate is further investigated over Europe by comparing the variability of the satellite-derived vegetation onset and that of the winter North Atlantic Oscillation index, at a fine spatial scale. The strong correlations observed confirm that this climate forcing parameter explains most of the onset variability over a large fraction of Northern Europe (earlier onsets for positive winter NAO), with lower impact towards the south and opposite effects around the Mediterranean basin. The NAO has a predictive character as the January-February NAO index is strongly correlated with the vegetation onset that occurs around April in Northern Europe.     

Nonlinear stability,excitation and soliton solutions in electrified dispersive systems

A weakly nonlinear theory of wave propagation in two superposed dielectric fluids in the presence of a horizontal electric field is investigated in (2+1)-dimensions. The equation governing the evolution of the amplitude of the progressive waves is obtained in the form of a two-dimensional nonlinear Schrödinger equation. A three-wave resonant interaction for nonlinear excitations created from electrohydrodynamic capillary-gravity waves is observed to be possible in a dispersive medium with a self-focusing cubic nonlinearity. Under suitable conditions, the nonlinear envelope equations for the resonant interaction are derived by using multiple scales and inverse scattering methods, and an explicit three-wave soliton solution is discussed. Both the dynamic properties and the modulational instability of finite amplitude electrohydrodynamic wave are studied for the cubic nonlinear Schrödinger equation by means of linearized stability analysis and the nonlinear interaction coefficient. We show that the trajectories in phase space exhibit different behavior with the increase of nonlinear perturbations, and we determine the electric field and wavenumber ranges at which the original point is elliptic or hyperbolic, respectively. It is found also that the presence of the electric field in the equation modifies the nature of wave stability and soliton structures, and that the amplitude and width of the soliton are decreased and increased, respectively, when the electric field value increases.     

Evaluation of tile–wall bonding integrity based on impact acoustics and support vector machine

It is well recognized that the impact-acoustic emissions contain information that can indicate the presence of the adhesive defects in the bonding structures. In our previous papers, artificial neural network (ANN) was adopted to assess the bonding integrity of the tile–walls with the feature extracted from the power spectral density (PSD) of the impact-acoustic signals acting as the input of classifier. However, in addition to the inconvenience posed by the general drawbacks such as long training time and large number of training samples needed, the performance of the classic ANN classifier is deteriorated by the similar spectral characteristics between different bonding status caused by abnormal impacts. In this paper our previous works was developed by the employment of the least-squares support vector machine (LS-SVM) classifier instead of the ANN to derive a bonding integrity recognition approach with better reliability and enhanced immunity to surface roughness. With the help of the specially designed artificial sample slabs, experiments results obtained with the proposed method are provided and compared with that using the ANN classifier, demonstrating the effectiveness of the present strategy.     

A Multiobjective Evolutionary Approach to Concurrently Learn Rule and Data Bases of Linguistic Fuzzy-Rule-Based Systems

In this paper, we propose the use of a multiobjective evolutionary approach to generate a set of linguistic fuzzy-rule-based systems with different tradeoffs between accuracy and interpretability in regression problems. Accuracy and interpretability are measured in terms of approximation error and rule base (RB) complexity, respectively. The proposed approach is based on concurrently learning RBs and parameters of the membership functions of the associated linguistic labels. To manage the size of the search space, we have integrated the linguistic two-tuple representation model, which allows the symbolic translation of a label by only considering one parameter, with an efficient modification of the well known (2 + 2) Pareto archived evolution strategy (PAES). We tested our approach on nine real world datasets of different sizes and with different numbers of variables. Besides the (2 + 2)PAES, we have also used the well known nondominated sorting genetic algorithm (NSGA-II) and an accuracy-driven single-objective evolutionary algorithm (EA). We employed these optimization techniques both to concurrently learn rules and parameters and to learn only rules. We compared the different approaches by applying a nonparametric statistical test for pairwise comparisons, thus taking into consideration three representative points from the obtained Pareto fronts in the case of the multiobjective EAs. Finally, a data complexity measure, which is typically used in pattern recognition to evaluate the data density in terms of average number of patterns per variable, has been introduced to characterize regression problems. Results confirm the effectiveness of our approach, particularly for (possibly high dimensional) datasets with high values of the complexity metric.     

Sharing Context-Aware Road and Safety Information

We present an integrated vehicular system for the collection, management, and provision of context-aware information on traffic and driver location. This system uses an integrated vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication paradigm enriched with an information management system. The infrastructure manages vehicle-detected safety hazards and other relevant information, adapting them to the vehicle's context and driver's preferences. This vehicular integrated system resembles the concept of a smart road.     

Optimum design of long-span suspension bridges considering aeroelastic and kinematic constraints

Cable supported bridges are wind prone structures. Therefore, their aerodynamic behaviour must be studied in depth in order to guarantee their safe performance. In the last decades important achievements have been reached in the study of bridges under wind-induced actions. On the other hand, non-conventional design techniques such as sensitivity analysis or optimum design have not been applied although they have proved their feasibility in the automobile or aeronautic industries. The aim of this research work is to demonstrate how non-conventional design techniques can help designers when dealing with long span bridges considering their aeroelastic behaviour. In that respect, the comprehensive analytical optimum design problem formulation is presented. In the application example the optimum design of the challenging Messina Strait Bridge is carried out. The chosen initial design has been the year 2002 design proposal. Up to a 33% deck material saving has been obtained after finishing the optimization process.