Screening and selective quantification of illicit drugs in wastewater by mixed-mode solid-phase extraction and quadrupole-time-of-flight liquid chromatography-mass spectrometry

For the first time, a mixed-mode solid-phase extraction with fractionation of basic analytes from neutral and acidic species during cartridge elution and liquid chromatography-quadrupole-time-of-flight mass spectrometry (LC-QTOF-MS) was combined for the quantitative determination of 24 illicit drugs and metabolites in urban sewage samples. The effects of several sample preparation and instrumental parameters in the sensitivity and selectivity of the quantitative method are thoroughly discussed. Under final working conditions, recoveries above 63% and 82% were attained for all species in raw and treated sewage, respectively; whereas, the limits of quantification of the method, defined for a signal-to-noise of 10 (S/N = 10), ranged from 2 to 50 ng L(-1). Sequential elution of mixed-mode cartridges allowed a significant reduction of matrix effects observed during electrospray ionization of basic drugs versus those measured for hydrophilic balance reversed-phase sorbents and the same mixed-mode polymer without fractionated elution. Analysis of raw wastewater samples confirmed the ubiquity of cocaine (COC), benzoylecgonine (BE), and 11-nor-9-carboxy-Δ(9)-tetrahydrocannabinol (THCCOOH) in this matrix. The capability of the above methodology to identify new illicit drugs and/or metabolites in sewage samples is also discussed. With this aim, a two step strategy is proposed. First, high-resolution MS chromatograms, acquired throughout each chromatographic run, are automatically searched against an in-house built database, a reduced list of candidate drugs is generated, and the corresponding extracted ion chromatograms are obtained. In a further LC run, the tandem mass spectrometry (MS/MS) spectra of unknown peaks are acquired using different collision energies and compared with those existing in public libraries, or interpreted, to assign the unknown peak to one of the previously selected candidates.     

Tailoring fiber grating sensors for assessment of highly refractive fuels

Three approaches that allow the tailoring of long period gratings based refractometric sensors for concentration measurement in fuel blends are employed to assess the fuel quality in biodiesel and biodiesel-petrodiesel blend. To allow the analysis of fuel samples with refractive index higher than fiber cladding one, the samples refractive indices were changed by thermo-optic effect and by dilution in a standard substance with low refractive index. The obtained results show the sensor can detect oil concentration in biodiesel samples with resolution as better as 0.07% and biodiesel concentration in biodiesel-petrodiesel samples with average resolution of 0.09%.     

1/f Noise in human color vision: the role of S-cone signals

We examine the functional role of S-cone signals on reaction time (RT) variability in human color vision. Stimuli were selected along red-green and blue-yellow cardinal directions and at random directions in the isoluminant plane of the color space. Trial-to-trial RT variability was not statistically independent but correlated across experimental conditions and exhibited 1/f noise spectra with an exponent close to unity in most of the cases. Regarding contrast coding, 1/f noise for random chromatic stimuli at isoluminance was similar to that for achromatic stimuli, thus suggesting that S-cone signals reduce variability of higher order color mechanisms. If we regard spatial coding, the effect of S-cone density in the retina on RT variability was investigated. The magnitude of 1/f noise at 16 min of arc (S-cone free zone) was higher than at 90 min of arc in the blue-yellow channel, and it was similar for the red-green channel. The results suggest that S-cone signals are beneficial and they modulate 1/f noise spectra at postreceptoral stages. The implications related to random multiplicative processes as a possible source of 1/f noise and the optimal information processing in color vision are discussed.     

Lethal effect of electric fields on isolated ventricular myocytes

Defibrillator-type shocks may cause electric and contractile dysfunction. In this study, we determined the relationship between probability of lethal injury and electric field intensity ($E$ ) in isolated rat ventricular myocytes, with emphasis on field orientation and stimulus waveform. This relationship was sigmoidal with irreversible injury for $E ≫ hbox{50 V/cm}$ . During both threshold and lethal stimulation, cells were twofold more sensitive to the field when it was applied longitudinally (versus transversally) to the cell major axis. For a given $E$, the estimated maximum variation of transmembrane potential ( $Delta V_{max }$) was greater for longitudinal stimuli, which might account for the greater sensitivity to the field. Cell death, however, occurred at lower maximum $Delta V_{max }$ values for transversal shocks. This might be explained by a less steep spatial decay of transmembrane potential predicted for transversal stimulation, which would possibly result in occurrence of electroporation in a larger membrane area. For the same stimulus duration, cells were less sensitive to field-induced injury when shocks were biphasic (versus monophasic). Ours results indicate that, although significant myocyte death may occur in the $E$ range expected during clinical defibrillation, biphasic shocks are less likely to produce irreversible cell injury.      

Variational optical flow computation in real time.

This paper investigates the usefulness of bidirectional multigrid methods for variational optical flow computations. Although these numerical schemes are among the fastest methods for solving equation systems, they are rarely applied in the field of computer vision. We demonstrate how to employ those numerical methods for the treatment of variational optical flow formulations and show that the efficiency of this approach even allows for real-time performance on standard PCs. As a representative for variational optic flow methods, we consider the recently introduced combined local-global method. It can be considered as a noise-robust generalization of the Horn and Schunck technique. We present a decoupled, as well as a coupled, version of the classical Gauss-Seidel solver, and we develop several multgrid implementations based on a discretization coarse grid approximation. In contrast, with standard bidirectional multigrid algorithms, we take advantage of intergrid transfer operators that allow for nondyadic grid hierarchies. As a consequence, no restrictions concerning the image size or the number of traversed levels have to be imposed. In the experimental section, we juxtapose the developed multigrid schemes and demonstrate their superior performance when compared to unidirectional multgrid methods and nonhierachical solvers. For the well-known 316 x 252 Yosemite sequence, we succeeded in computing the complete set of dense flow fields in three quarters of a second on a 3.06-GHz Pentium4 PC. This corresponds to a frame rate of 18 flow fields per second which outperforms the widely-used Gauss-Seidel method by almost three orders of magnitude.     

An autocorrelation-based time domain analysis technique for monitoring perfusion and oxygenation in transplanted organs

In designing an implantable sensor for perfusion monitoring of transplant organs the ability of the sensor to gather perfusion information with limited power consumption and in near real time is paramount. The following work was performed to provide a processing method that is able to predict perfusion and oxygenation change within the blood flowing through a transplanted organ. For this application, an autocorrelation-based algorithm was used to reduce the acquisition time required for fast Fourier transform (FFT) analysis while retaining the accuracy inherent to FFT analysis. In order to provide data proving that the developed method is able to predict perfusion as accurately as FFT two experiments were developed isolating both periodic and quasi-periodic cardiac frequencies. It was shown that the autocorrelation-based method was able to perform comparably with FFT (limited to a sampling frequency of 300 Hz) and maintain accuracy down to acquisition times as low as 4 s in length.     

Autogestion de Réseaux de Capteurs Sans Fil : Services, Fonctions, Modèles et Étude de Cas

The wireless sensor networks (Wsn) are a novel technology that has appeared after great advancements in the development of intelligent sensors, powerful microprocessors, and communication protocols, their basic components. This kind of network is composed by hundreds to thousands of elements and has the objective of data collecting, processing, and disseminating to a point of interest. The network elements, named sensors nodes, have small dimensions and resource restrictions, especially the energy, the processing, and the communication capacities. It is expected that theWsn are intelligent, autonomic, and context aware. To reach such an objective, they are supposed to perform the management of themselves, i.e., be self-managed. In this article, we propose a management solution for such a sort of network, based on the autonomic computing paradigm. In order to show that self-management can improve the productivity of the network and control the quality of the provided services, we present a case study of a heterogeneous and hierarchicWsn that collects and disseminates data continuously.