Gas sensing properties of catalytically modified WO3 with copper and vanadium for NH3 detection

Ammonia gas detection by pure and catalytically modified WO3 based gas sensor was analysed. The sensor response of pure WO3 to NH3 was not only rather low but also presented an abnormal behaviour, probably due to the unselective oxidation of ammonia to NOx. Copper and vanadium were introduced in different concentrations and the resulting material was annealed at different temperatures in order to improve the sensing properties for NH3 detection. The introduction of copper and vanadium as catalytic additives improved the response to NH3 and also eliminated the abnormal behaviour. Possible mechanisms of NH3 reaction over these materials are discussed. Sensor responses to other gases like NO2 or CO and the interference of humidity on ammonia detection were also analysed so as to choose the best sensing element.

A reusable smart interface for gas sensor resistance measurement

The advances of the semiconductor industry enable microelectromechanical systems sensors, signal conditioning logic and network access to be integrated into a smart sensor node. In this framework, a mixed-mode interface circuit for monolithically integrated gas sensor arrays was developed with high-level design techniques. This interface system includes analog electronics for inspection of up to four sensor arrays and digital logic for smart control and data communication. Although different design methodologies were used in the conception of the complete circuit, high-level synthesis tools and methodologies were crucial in speeding up the whole design cycle, enhancing reusability for future applications and producing a flexible and robust component.

On-line event detection by recursive dynamic principal component analysis and gas sensor arrays under drift conditions

Leakage detection is an important issue in many chemical sensing applications. Leakage detection hy thresholds suffers from important drawbacks when sensors have serious drifts or they are affected by cross-sensitivities. Here we present an adaptive method based in a Dynamic Principal Component Analysis that models the relationships between the sensors in the may. In normal conditions a certain variance distribution characterizes sensor signals. However, in the presence of a new source of variance the PCA decomposition changes drastically. In order to prevent the influence of sensor drifts the model is adaptive and it is calculated in a recursive manner with minimum computational effort. The behavior of this technique is studied with synthetic signals and with real signals arising by oil vapor leakages in an air compressor. Results clearly demonstrate the efficiency of the proposed method.

The effects of electron-hole separation on the photoconductivity of individual metal oxide nanowires

The responses of individual ZnO nanowires to UV light demonstrate that the persistent photoconductivity (PPC) state is directly related to the electron¿hole separation near the surface. Our results demonstrate that the electrical transport in these nanomaterials is influenced by the surface in two different ways. On the one hand, the effective mobility and the density of free carriers are determined by recombination mechanisms assisted by the oxidizing molecules in air. This phenomenon can also be blocked by surface passivation. On the other hand, the surface built-in potential separates the photogenerated electron¿hole pairs and accumulates holes at the surface. After illumination, the charge separation makes the electron¿hole recombination difficult and originates PPC. This effect is quickly reverted after increasing either the probing current (self-heating by Joule dissipation) or the oxygen content in air (favouring the surface recombination mechanisms). The model for PPC in individual nanowires presented here illustrates the intrinsic potential of metal oxide nanowires to develop optoelectronic devices or optochemical sensors with better and new performances.

Gas identification with tin oxide sensor array and self-organizing maps: adaptive correction of sensor drifts

Low-cost tin oxide gas sensors are inherently nonspecific. In addition, they have several undesirable characteristics such as slow response, nonlinearities, and long-term drifts. This paper shows that the combination of a gas-sensor array together with self-organizing maps (SOM's) permit success in gas classification problems. The system is able to determine the gas present in an atmosphere with error rates lower than 3%. Correction of the sensor's drift with an adaptive SOM has also been investigated

Drift compensation of gas sensor array data by Orthogonal Signal Correction

Drift is an important issue that impairs the reliability of gas sensing systems. Sensor aging, memory effects and environmental disturbances produce shifts in sensor responses that make initial statistical models for gas or odor recognition useless after a relatively short period (typically few weeks). Frequent recalibrations are needed to preserve system accuracy. However, when recalibrations involve numerous samples they become expensive and laborious. An interesting and lower cost alternative is drift counteraction by signal processing techniques. Orthogonal Signal Correction (OSC) is proposed for drift compensation in chemical sensor arrays. The performance of OSC is also compared with Component Correction (CC). A simple classification algorithm has been employed for assessing the performance of the algorithms on a dataset composed by measurements of three analytes using an array of seventeen conductive polymer gas sensors over a ten month period.

Nonlinear inverse dynamic models of gas sensing systems based on chemical sensor arrays for quantitative measurements

Gas sensing systems based on low-cost chemical sensor arrays are gaining interest for the analysis of multicomponent gas mixtures. These sensors show different problems, e.g., nonlinearities and slow time-response, which can be partially solved by digital signal processing. Our approach is based on building a nonlinear inverse dynamic system. Results for different identification techniques, including artificial neural networks and Wiener series, are compared in terms of measurement accuracy.

Drift compensation of gas sensor array data by common principal component analysis

A new drift compensation method based on Common Principal Component Analysis (CPCA) is proposed. The drift variance in data is found as the principal components computed by CPCA. This method finds components that are common for all gasses in feature space. The method is compared in classification task with respect to the other approaches published where the drift direction is estimated through a Principal Component Analysis (PCA) of a reference gas. The proposed new method ¿ employing no specific reference gas, but information from all gases ¿has shown the same performance as the traditional approach with the best-fitted reference gas. Results are shown with data lasting 7-months including three gases at different concentrations for an array of 17 polymeric sensors.

Atomic diffusion induced by stress relaxation in InGaAs/GaAs epitaxial layers

The origin of the microscopic inhomogeneities in InxGa12xAs layers grown on GaAs by molecular beam epitaxy is analyzed through the optical absorption spectra near the band gap. It is seen that, for relaxed thick layers of about 2.8 mm, composition inhomogeneities are responsible for the band edge smoothing into the whole compositional range (0.05,x,0.8). On the other hand, in thin enough layers strain inhomogeneities are dominant. This evolution in line with layer thickness is due to the atomic diffusion at the surface during growth, induced by the strain inhomogeneities that arise from stress relaxation. In consequence, the strain variations present in the layer are converted into composition variations during growth. This process is energetically favorable as it diminishes elastic energy. An additional support to this hypothesis is given by a clear proportionality between the magnitude of the composition variations and the mean strain.

Double-tagged fluorescent bacterial bioreporter for the study of polycyclic aromatic hydrocarbon diffusion and bioavailability.

Bacterial degradation of polycyclic aromatic hydrocarbons (PAHs), ubiquitous contaminants from oil and coal, is typically limited by poor accessibility of the contaminant to the bacteria. In order to measure PAH availability in complex systems, we designed a number of diffusion-based assays with a double-tagged bacterial reporter strain Burkholderia sartisoli RP037-mChe. The reporter strain is capable of mineralizing phenanthrene (PHE) and induces the expression of enhanced green fluorescent protein (eGFP) as a function of the PAH flux to the cell. At the same time, it produces a second autofluorescent protein (mCherry) in constitutive manner. Quantitative epifluorescence imaging was deployed in order to record reporter signals as a function of PAH availability. The reporter strain expressed eGFP proportionally to dosages of naphthalene or PHE in batch liquid cultures. To detect PAH diffusion from solid materials the reporter cells were embedded in 2 cm-sized agarose gel patches, and fluorescence was recorded over time for both markers as a function of distance to the PAH source. eGFP fluorescence gradients measured on known amounts of naphthalene or PHE served as calibration for quantifying PAH availability from contaminated soils. To detect reporter gene expression at even smaller diffusion distances, we mixed and immobilized cells with contaminated soils in an agarose gel. eGFP fluorescence measurements confirmed gel patch diffusion results that exposure to 2-3 mg lampblack soil gave four times higher expression than to material contaminated with 10 or 1 (mg PHE) g(-1).

Le problème de l'interdépendance dans la comparaison des politiques publiques infranationales : une méta-analyse des mécanismes de diffusion

Un des problèmes majeurs de la méthode comparative, et notamment de la comparaison entre politiques publiques infranationales, est le fait que les phénomènes à comparer, au lieu de consister en unités analytiques indépendantes les unes des autres, sont au contraire susceptibles de s'influencer mutuellement. Cette contribution aborde la problématique de l'interdépendance, avec une attention particulière aux différences entre politiques publiques internationales et infranationales. Elle synthétisera et discutera les apports des travaux empiriques sur la diffusion, à travers une métaanalyse des « conditions nécessaires » pour les différents mécanismes de diffusion des politiques publiques. Dans ce but, elle analysera, un échantillon de la littérature scientifique avec la technique des ensembles flous, et illustré à l'aide d'exemples concrets.

Petróleo y gas en África: viejas realidades, nuevos escenarios

[cat] En els últims temps es parla molt del nou paper dels hidrocarburs d'Àfrica, fins i tot s'al·ludeix a un oil rush o a un african oil scramble , que inevitablement desembocarà en una confrontació bipolar entre la Xina i els Estats Units, pel control de les reserves de petroli del subsòl del continent africà. Així, el propòsit d'aquest text és, en primer lloc, realitzar una anàlisi descriptiva que ajudi a valorar la hipòtesi d'aquest african oil scramble. A continuación, amb les dades obtingudes, es discutirà sobre la possibilitat de que aquest fenomen desemboqui en un escenari de confrontació xinoamericana. Aquesta especulació ens durà a concloure que hi ha suficients indicis per a argumentar que el joc petrolífer africà podria desenvolupar-se en un escenari marcat per la multilateralitat.

Nutrient supply by mass flow and diffusion to maize plants in response to soil aggregate size and water potential

Nutrients are basically transported to the roots by mass flow and diffusion. The aim of this study was to quantify the contribution of these two mechanisms to the acquisition of macronutrients (N, P, K, Ca, Mg, and S) and cationic micronutrients (Fe, Mn, Zn, and Cu) by maize plants as well as xylem exudate volume and composition in response to soil aggregate size and water availability. The experiment was conducted in a greenhouse with samples of an Oxisol, from under two management systems: a region of natural savanna-like vegetation (Cerradão, CER) and continuous maize under conventional management for over 30 years (CCM). The treatments were arranged in a factorial [2 x (1 + 2) x 2] design, with two management systems (CER and CCM), (1 + 2) soil sifted through a 4 mm sieve and two aggregate classes (< 0.5 mm and 0.5 - 4.0 mm) and two soil matric potentials (-40 and -10 kPa). These were evaluated in a randomized block design with four replications. The experiment was conducted for 70 days after sowing. The influence of soil aggregate size and water potential on the nutrient transport mechanisms was highest in soil samples with higher nutrient concentrations in solution, in the CER system; diffusion became more relevant when water availability was higher and in aggregates < 0.5 mm. The volume of xylem exudate collected from maize plants increased with the decrease in aggregate size and the increased availability of soil water in the CER system. The highest Ca and Mg concentrations in the xylem exudate of plants grown on samples from the CER system were related to the high concentrations of these nutrients in the soil solution of this management system.

Inter-firm labor mobility and knowledge diffusion: a theoretical approach

[cat] Analitzem una economia amb dues característiques principals: la mobilitat dels treballadors implica transferència de coneixement i la productivitat de l’empresa augmenta amb l’intercanvi de coneixement. Cada empresa desenvolupa un tipus de coneixement que serà trasmès a la resta de la indústria mitjançant la mobilitat de treballadors. Estudiem dues estructures de mercat laboral i utilitzant un anàlisi comparatiu derivem les implicacions del model. Els resultats revelen com la mobilitat de treballadors depèn en la varietat i nivell del coneixement, la presència de costos de mobilitat, les institucions, la capacitat d’absorvir coneixement per part de les empreses i la mida de la indústria. Els resultats no depenen de l’estructura del mercat laboral.

High b-value diffusion-weighted imaging: A sensitive method to reveal white matter differences in schizophrenia.

Over the last 10 years, diffusion-weighted imaging (DWI) has become an important tool to investigate white matter (WM) anomalies in schizophrenia. Despite technological improvement and the exponential use of this technique, discrepancies remain and little is known about optimal parameters to apply for diffusion weighting during image acquisition. Specifically, high b-value diffusion-weighted imaging known to be more sensitive to slow diffusion is not widely used, even though subtle myelin alterations as thought to happen in schizophrenia are likely to affect slow-diffusing protons. Schizophrenia patients and healthy controls were scanned with a high b-value (4000s/mm(2)) protocol. Apparent diffusion coefficient (ADC) measures turned out to be very sensitive in detecting differences between schizophrenia patients and healthy volunteers even in a relatively small sample. We speculate that this is related to the sensitivity of high b-value imaging to the slow-diffusing compartment believed to reflect mainly the intra-axonal and myelin bound water pool. We also compared these results to a low b-value imaging experiment performed on the same population in the same scanning session. Even though the acquisition protocols are not strictly comparable, we noticed important differences in sensitivities in the favor of high b-value imaging, warranting further exploration.