The interaction of alumina with HCl: An infrared spectroscopy, temperature-programmed desorption and inelastic neutron scattering study

The interaction of HCl with an η-alumina catalyst has been investigated by a combination of diffuse reflectance infrared spectroscopy, temperature-programmed desorption and inelastic neutron scattering (INS) spectroscopy. Infrared spectra provide evidence for dissociative adsorption of HCl and for a process in which hydroxyl groups terminally bound to Al are replaced by chlorine. Temperature-programmed desorption experiments show HCl to desorb over the temperature range 350–>970 K, indicating dissociative HCl adsorption to occur on a wide range of active sites. INS experiments show the residual alumina hydroxyl groups to exhibit an out-of-plane deformation feature, γ(OH), at ca. 200 cm⁻¹, while the in-plane deformation mode, δ(OH), is seen at ca. 1000 cm⁻¹. The formation of new surface hydroxyl groups via the adsorption of hydrogen chloride yields a δ(OH) feature that can be resolved into two bands at 990 and 1050 cm⁻¹. Hydrogen bonding within the alumina/HCl system is responsible for the observation of an Evans transmission window in the infrared spectrum, that occurs via a Fermi resonance interaction between (i) the ν(OH) mode of hydrogen bonded hydroxyl groups and chemisorbed water with (ii) the overtone of the δ(OH) mode of surface hydroxyl groups. The INS technique is able to discriminate among different hydroxyl group bonding geometries on the basis of the local symmetry of the active sites.     

Interactive display of isosurfaces with global illumination

In many applications, volumetric data sets are examined by displaying isosurfaces, surfaces where the data, or some function of the data, takes on a given value. Interactive applications typically use local lighting models to render such surfaces. This work introduces a method to precompute or lazily compute global illumination to improve interactive isosurface renderings. The precompiled illumination resides in a separate volume and includes direct light, shadows, and intersections. Using this volume, interactive globally illuminated renderings of isosurfaces become feasible while still allowing dynamic manipulation of lighting, viewpoint and isovalue.     

Subsecond voltammetric separation between dopamine and serotonin in the presence of ascorbate

Although voltammetry has proved an important tool for unraveling the dynamics of specific neurotransmitter molecules during the past decade, it has been very difficult to monitor more than one neurotransmitter simultaneously. In this work, we present a voltammetric methodology that allows discrimination between dopamine and serotonin, two important neurotransmitter molecules with very similar electrochemical properties, in the presence of high concentrations of ascorbate. We combined the application of a novel large-amplitude/high-frequency voltage excitation with signal processing techniques valid for the analysis of nonstationary and nonlinear phenomena. This allows us to minimize the contribution from capacitance and preserve the faradaic features of the voltammetric response providing us with excellent voltammetric detail. Using appropriate voltage excitation parameters and defining specific regions in the voltage space, so-called voltage windows, we can measure the concentrations of dopamine and serotonin separately or independently in mixed solutions even in the presence of high concentrations of ascorbate. Because of the enhanced voltammetric detail of this new technique, it is also possible to explore effects attributed to interfacial phenomena such as adsorption/desorption and electrode fouling.     

Deconvolution estimation of nerve conduction velocity distribution

A conduction velocity distribution (CVD) estimator that incorporates volume conductor modeling of the nerve-evoked response is introduced in this paper. The CVD estimates are obtained from two compound nerve action potentials (CNAP) recorded at the skin surface. A third channel is introduced in order to assess the estimator performance in the experimental case. The relevance of using an accurate signal model is shown by comparing the performance of the proposed estimator with a previous approach based on a different CNAP model. The performance of the proposed estimator is evaluated for simulated and experimental data. The study assesses signal-to-noise ratio immunity and sensitivity to errors in the model parameters.     

Probabilistic symbolic model checking with PRISM: a hybrid approach

In this paper we present efficient symbolic techniques for probabilistic model checking. These have been implemented in PRISM, a tool for the analysis of probabilistic models such as discrete-time Markov chains, continuous-time Markov chains and Markov decision processes using specifications in the probabilistic temporal logics PCTL and CSL. Motivated by the success of model checkers such as SMV which use BDDs (binary decision diagrams), we have developed an implementation of PCTL and CSL model checking based on MTBDDs (multi-terminal BDDs) and BDDs. Existing work in this direction has been hindered by the generally poor performance of MTBDD-based numerical computation, which is often substantially slower than explicit methods using sparse matrices. The focus of this paper is a novel hybrid technique which combines aspects of symbolic and explicit approaches to overcome these performance problems. For typical examples, we achieve a dramatic improvement over the purely symbolic approach. In addition, thanks to the compact model representation using MTBDDs, we can verify systems an order of magnitude larger than with sparse matrices, while almost matching or even beating them for speed.     

Catalytic mechanism and role of hydroxyl residues in the active site of theta class glutathione S-transferases. Investigation of Ser-9 and Tyr-113 in a glutathione S-transferase from the Australian sheep blowfly, Lucilia cuprina

Spectroscopic and kinetic studies have been performed on the Australian sheep blowfly Lucilia cuprina glutathione S-transferase (Lucilia GST; EC 2.5.1.18) to clarify its catalytic mechanism. Steady state kinetics of Lucilia GST are non-Michaelian, but the quite hyperbolic isothermic binding of GSH suggests that a steady state random sequential Bi Bi mechanism is consistent with the anomalous kinetics observed. The rate-limiting step of the reaction is a viscosity-dependent physical event, and stopped-flow experiments indicate that product release is rate-limiting. Spectroscopic and kinetic data demonstrate that Lucilia GST is able to lower the pKa of the bound GSH from 9.0 to about 6.5. Based on crystallographic suggestions, the role of two hydroxyl residues, Ser-9 and Tyr-113, has been investigated. Removal of the hydroxyl group of Ser-9 by site-directed mutagenesis raises the pKa of bound GSH to about 7.6, and a very low turnover number (about 0.5% of that of wild type) is observed. This inactivation may be explained by a strong contribution of the Ser-9 hydroxyl group to the productive binding of GSH and by an involvement in the stabilization of the ionized GSH. This serine residue is highly conserved in the Theta class GSTs, so the present findings may be applicable to all of the family members. Tyr-113 appears not to be essential for the GSH activation. Stopped-flow data indicate that removal of the hydroxyl group of Tyr-113 does not change the rate-limiting step of reaction but causes an increase of the rate constants of both the formation and release of the GSH conjugate. Tyr-113 resides on alpha-helix 4, and its hydroxyl group hydrogen bonds directly to the hydroxyl of Tyr-105. This would reduce the flexibility of a protein region that contributes to the electrophilic substrate binding site; segmental motion of alpha-helix 4 possibly modulates different aspects of the catalytic mechanism of the Lucilia GST.     

Nonlinear adaptive filtering of stimulus artifact

Noninvasive measurements of somatosensory evoked potentials have both clinical and research applications. The electrical artifact which results from the stimulus is an interference which can distort the evoked signal, and introduce errors in response onset timing estimation. Given that this interference is synchronous with the evoked signal, it cannot be reduced by the conventional technique of ensemble averaging. The technique of adaptive noise cancelling has potential in this regard however, and has been used effectively in other similar problems. An adaptive noise cancelling filter which uses a neural network as the adaptive element is investigated in this application. The filter is implemented and performance determined in the cancelling of artifact for in vivo measurements on the median nerve. A technique of segmented neural network training is proposed in which the network is trained on that segment of the record time window which does not contain the evoked signal. The neural network is found to generalize well from this training to include the segment of the window containing the evoked signal. Both quantitative and qualitative measures show that significant stimulus artifact reduction is achieved.