Manipulation of microenvironment with a built-in electrochemical actuator in proximity of a dissolved oxygen microsensor

Biochemical sensors for continuous monitoring require dependable periodic self diagnosis with acceptable simplicity to check its functionality during operation. An in-situ self-diagnostic technique for a dissolved oxygen microsensor is proposed in an effort to devise an intelligent microsensor system with an integrated electrochemical actuation electrode. With a built-in platinum microelectrode that surrounds the microsensor, two kinds of microenvironments, called the oxygen-saturated or oxygen-depleted phases, can be created by water electrolysis, depending on the polarity. The functionality of the microsensor can be checked during these microenvironment phases. The polarographic oxygen microsensor is fabricated on a flexible polyimide substrate (Kapton) and the feasibility of the proposed concept is demonstrated in a physiological solution. The sensor responds properly during the oxygen-generating and oxygen-depleting phases. The use of these microenvironments for in-situ self-calibration is discussed to achieve functional integration, as well as structural integration, of the microsensor system.     

On-line dead-time compensation method using disturbance observer

A new on-line dead-time compensation method for a permanent magnet (PM) synchronous motor drive is proposed. Using a simple disturbance observer without any additional circuit and off-line experimental measurement, disturbance voltages in the rotor reference dq frame caused by the dead time and nonideal switching characteristics of power devices are estimated in an on-line manner and fed to voltage references in order to compensate the dead-time effects. The proposed method is applied to a PM synchronous motor drive system and implemented by using software of a digital signal processor (DSP) TMS320C31. Simulations and experiments are carried out for this system and the results well demonstrate the effectiveness of the proposed method.     

Deactivation of copper-ion-exchanged hydrogen-mordenite-type zeolite catalyst by SO2 for no reduction by NH3

Deactivation of copper-ion-exchanged hydrogen-mordenite-type zeolite catalyst by SO₂ for NO reduction by NH₃ was examined in a fixed-bed flow reactor. The deactivation of the catalyst was strongly dependent on reaction temperature. At high reaction temperatures over 300°C, the catalyst did not lose its initial activity up to 50 h of operation, regardless of SO₂ feed concentration from 500 to 20,000 ppm. However, at low reaction temperatures near 250°C, apparent deactivation did occur. Changes in the physicochemical properties such as surface area and sulfur content of deactivated catalyst well correlated with catalyst activity, depending upon reaction temperatures. The deactivation was due to pore blocking and/or filling by deactivating agents, which plugged and/or filled the pores of catalyst. The deactivating agents deposited on the catalyst surface were presumed to be (NH₄)₂SO₄ and/or (NH₄)HSO₄ from the results of TGA and ion-chromatography measurement.     

Parathion degradation and toxicity reduction in solar photocatalysis and photolysis.

The solar photocatalytic degradation of methyl parathion was investigated using a circulating TiO2/solar light reactor. Under solar photocatalysis condition, parathion was more effectively degraded than solar photolysis and TiO2-only conditions. With solar photocatalysis, 20 mg/L of parathion was completely degraded within 60 min with a TOC decrease of 63% after 150 min. The main ionic byproducts during photocatalysis recovered from parathion degradation were mainly as NO3-, NO2- and NH4+, 80% of the sulphur as SO4(2-), and 5% of phosphorus as PO4(3-). The organic intermediates 4-nitrophenol and methyl paraoxon were also identified, and these were further degraded in solar photocatalytic condition. Two different bioassays (Vibrio fischeri and Daphnia magna) were used to test the acute toxicity of solutions treated by solar photocatalysis and photolysis. The Microtox test using V. fischeri showed that the toxicity expressed as EC50 (%) value increased from 5.5% to >82% in solar photocatalysis, indicating that the treated solution is non-toxic, but only increased from 4.9 to 20.5% after 150 min in solar photolysis. The acute toxicity test using D. magna showed that EC50 (%) increased from 0.05 to 1.08% under solar photocatalysis, but only increased to 0.12% after 150 min with solar photolysis, indicating the solution is still toxic. The pattern of toxicity reduction parallels the decrease in TOC and the parathion concentrations.     

Hierarchical classifier design in high-dimensional numerous classcases

In applying pattern recognition methods in remote sensing problems, an inherent limitation is that there is almost always only a small number of training samples with which to design the classifier. A hybrid decision tree classifier design procedure that produces efficient and accurate classifiers for this situation is proposed. In doing so, several key questions are addressed, among them the question of the feature extraction techniques to be used and the mathematical relationship between sample size, dimensionality, and risk value. Empirical tests comparing the hybrid design classifier with a conventional single layered one are presented. They suggest that the hybrid design produces higher accuracy with fewer features. The need for fewer features is an important advantage, because it reflects favorably on both the size of the training set needed and the amount of computation time that will be needed in analysis     

Prebiotic synthesis of sequential peptides on the Hadean beach by a molecular engine working with nitrogen oxides as energy sources

Addressing the still open question of the prebiotic origin of sequential macromolecules (peptides, nucleic acids) on the primitive Earth, we describe a molecular engine (the primary pump), which works at ambient temperature and continuously generates, elongates and complexifies sequential peptides. This new scenario is based on a cyclic reaction sequence, whose keystep is the activation of amino acids into their N‐carboxyanhydrides (NCA) through nitrosation by NOx. This process could have taken place on tidal beaches; it requires a buffered ocean, emerged land and a nitrosating atmosphere. With the help of geochemical studies and computer simulations of atmosphere photochemistry, we show that the primitive Earth during the Hadean may have satisfied all these requirements. © 2001 Society of Chemical Industry.     

The influence of NaCl and CO2 on the atmospheric corrosion of magnesium alloy AZ91

The influence of NaCl and CO₂ on the atmospheric corrosion of magnesium alloy AZ91 is studied in the laboratory. Samples were exposed under carefully controlled air and flow conditions; the relative humidity was 95%, the temperature was 22.0°C and the concentration of CO₂ was < 1 ppm or 350 ppm. Different amounts of sodium chloride (0–70 μg/cm²) were added before exposure. The corrosion products were analyzed by gravimetry, ion chromatography, X‐ray diffraction and scanning electron microscopy. Mass gain and metal loss results are reported. The combination of high humidity and NaCl is very corrosive towards AZ91. However, the NaCl‐induced corrosion is inhibited by ambient concentrations of CO₂. Exposure in the absence of CO₂ gives rise to heavy pitting, with brucite, Mg(OH)₂, being the dominant corrosion product. In the presence of CO₂ a layer of hydrated magnesium hydroxy carbonate, Mg₅(CO₃)₄(OH)₂ · 5 H₂O forms. A tentative corrosion mechanism is presented that explains the behavior in the two environments.     

Improved Poisson intensity estimation: denoising application using Poisson data

Recently, Timmermann and Nowak developed algorithms for estimating the means of independent Poisson random variables. The algorithms are based on a multiscale model where certain random variables are assumed to obey a beta-mixture density function. Timmermann and Nowak simplify the density estimation problem by assuming the beta parameters are known and only one mixture parameter is unknown. They use the observed data and the method of moments to estimate the unknown mixture parameter. Taking a different approach, we generate training data from the observed data and compute maximum likelihood estimates of all of the beta-mixture parameters. To assess the improved performance obtained by the proposed modification, we consider a denoising application using Poisson data.