Mechanistic investigations on the efficient catalytic decomposition of peroxynitrite by ebselen analogues

In this study, ebselen and its analogues are shown to be catalysts for the decomposition of peroxynitrite (PN). This study suggests that the PN-scavenging ability of selenenyl amides can be enhanced by a suitable substitution at the phenyl ring in ebselen. Detailed mechanistic studies on the reactivity of ebselen and its analogues towards PN reveal that these compounds react directly with PN to generate highly unstable selenoxides that undergo a rapid hydrolysis to produce the corresponding seleninic acids. The selenoxides interact with nitrite more effectively than the corresponding seleninic acids to produce nitrate with the regeneration of the selenenyl amides. Therefore, the amount of nitrate formed in the reactions mainly depends on the stability of the selenoxides. Interestingly, substitution of an oxazoline moiety on the phenyl ring stabilizes the selenoxide, and therefore, enhances the isomerization of PN to nitrate.

Conflict-Tolerant Real-Time Specifications in Metric Temporal Logic

A framework based on the notion of "conflict-tolerance" was proposed in as a compositional methodology for developing and reasoning about systems that comprise multiple independent controllers. A central notion in this framework is that of a "conflict-tolerant" specification for a controller. In this work we propose a way of defining conflict-tolerant real-time specifications in Metric Interval Temporal Logic (MITL). We call our logic CT-MITL for Conflict-Tolerant MITL. We then give a clock optimal "delay-then-extend" construction for building a timed transition system for monitoring past-MITL formulas. We show how this monitoring transition system can be used to solve the associated verification and synthesis problems for CT-MITL.

On the explicit determination of the polar decomposition in n-dimensional vector spaces

A method for the explicit determination of the polar decomposition (and the related problem of finding tensor square roots) when the underlying vector space dimension n is arbitrary (but finite), is proposed. The method uses the spectral resolution, and avoids the determination of eigenvectors when the tensor is invertible. For any given dimension n, an appropriately constructed van der Monde matrix is shown to play a key role in the construction of each of the component matrices (and their inverses) in the polar decomposition.

Oxidation and decomposition of NH3 over combustion synthesized Al2O3 and CeO2 supported Pt, Pd and Ag catalysts

The catalytic oxidation and decomposition of NH3 have been carried out over combustion synthesized Al2O3 and CeO2 supported Pt, Pd and Ag catalysts using temperature programmed reaction (TPR) technique in a packed bed tubular reactor. Metals are ionically dispersed over CeO2 and fine metal particles are found on Al2O3. NH3 oxidation occurs over 1% Pt/Al2O3, 1% Pd/Al2O3 and 1% Ag/Al2O3 at 175, 270 and 350 C respectively producing N-2, NO, N2O and H2O, whereas 1% Pt/CeO2, 1% Pd/CeO2 and 1% Ag/CeO2 give N-2 along with NO, N2O and H2O at 200, 225 and 250degreesC respectively. N-2 predominates over other nitrogen-containing products during the reaction on all catalysts. At less O-2 concentration, N-2 and H2O are the only products obtained during NH3 Oxidation. NH3 decomposition over all the catalysts occurs above 450degreesC.

A new parallel overlapped domain decomposition method for nonlinear dynamic finite element analysis

In this paper a new parallel algorithm for nonlinear transient dynamic analysis of large structures has been presented. An unconditionally stable Newmark-beta method (constant average acceleration technique) has been employed for time integration. The proposed parallel algorithm has been devised within the broad framework of domain decomposition techniques. However, unlike most of the existing parallel algorithms (devised for structural dynamic applications) which are basically derived using nonoverlapped domains, the proposed algorithm uses overlapped domains. The parallel overlapped domain decomposition algorithm proposed in this paper has been formulated by splitting the mass, damping and stiffness matrices arises out of finite element discretisation of a given structure. A predictor-corrector scheme has been formulated for iteratively improving the solution in each step. A computer program based on the proposed algorithm has been developed and implemented with message passing interface as software development environment. PARAM-10000 MIMD parallel computer has been used to evaluate the performances. Numerical experiments have been conducted to validate as well as to evaluate the performance of the proposed parallel algorithm. Comparisons have been made with the conventional nonoverlapped domain decomposition algorithms. Numerical studies indicate that the proposed algorithm is superior in performance to the conventional domain decomposition algorithms. (C) 2003 Elsevier Ltd. All rights reserved.

Decomposition temperatures of Cu2Ln2O5 (Ln = Tb, Dy, Ho, Er, Tm, Yb, and Lu) compounds

The equilibrium decomposition temperatures of Cu2Ln2O5 (Ln = Tb, Dy, Ho, Er, Tm, Yb, and Lu) compounds have been measured using a combined DTA-TGA apparatus under a flowing Ar + O2 gas mixture, in which the partial pressure of oxygen was controlled at 5.0 × 103 Pa. The Cu2Ln2O5 compounds yield Ln2O3 and Cu2O on decomposition. The decomposition temperature increases monotonically with the atomic number of the lanthanide element. This suggests that the stability of the Cu2Ln2O5 compounds with respect to the component binary oxides increases with decreasing radius of the Ln3+ ion.

Kinetic decomposition of Ni2SiO4 in oxygen potential gradients

Nickel orthosilicate (Ni2SiO4) has been found to decompose into its component binary oxides in oxygen potential gradients at 1373 K. Nickel oxide was formed at the high oxygen potential boundary, while silica was detected at the low oxygen potential side. Significant porosity and fissures were observed near the Ni2SiO4/SiO2 interface and the SiO2 layer. The critical oxygen partial pressure ratio required for decomposition varied from 1.63 to 2.15 as the oxygen pressures were altered from 1.01 ⊠ 105 to 2.7X 10−4 Pa, well above the dissociation pressure of Ni2SiO4. Platinum markers placed at the boundaries of the Ni2SiO4 sample indicated growth of NiO at the higher oxygen potential boundary, without any apparent transport of material to the low oxygen potential side. However, significant movement of the bulk Ni2SiO4 crystal with respect to the marker was not observed. The decomposition of the silicate occurs due to the unequal rates of transport of Ni and Si. The critical oxygen partial pressure ratio required for decomposition is related both to the thermodynamic stability of Ni2SiO4 with respect to component oxides and the ratio of diffusivities of nickel and silicon. Kinetic decomposition of multicomponent oxides, first discovered by Schmalzried, Laqua, and co-workers [H. Schmalzried, W. Laqua, and P. L. Lin, Z. Natur Forsch. Teil A 34, 192 (1979); H. Schmalzried and W. Laqua, Oxid. Met. 15, 339 (1981); W. Laqua and H. Schmalzried, Chemical Metallurgy—A Tribute to Carl Wagner (Metallurgical Society of the AIME, New York, 1981), p. 29] has important consequences for their use at high temperatures and in geochemistry.

Expression pattern of Cubitus interruptus from the mulberry silkworm Bombyx mori in late developmental stages

A partial genomic clone of Bombyx mori homologue of the segment polarity gene Cubitus interruptus (BmCi), encoding the conserved zinc finger domain and harbouring two introns, has been characterized. BmCi was expressed in the silkglands of B. mori from embryonic to the late larval stages(3rd, 4th and 5th intermoults). The expression was confined to the anterior region of the middle silkglands, overlapping with the domain of sericin-2 expression and excluding the domains of Bm invected expression, namely the middle and posterior regions of the middle silkglands. In the wing discs, the expression was restricted to the anterior compartment, which increased from 4th to 5th larval intermoults and declined later in the pupal wing buds. In gonadal tissues (both ovaries and testes) BmCi was expressed from the larval to pupal stages. The transcripts were localized to the sperm tubes containing spermatogonia in the testis of Bombyx larvae. BmCi expression, however, was not detected in any of these tissues during the moulting stages. Expression of Ci in the wing discs and gonads is evolutionarily conserved, while the silkgland represents a novel domain. Our results imply that BmCi is involved in the specification and maintenance of micro-compartment identity within the middle silkglands.

An investigation of carbon nanotubes obtained from the decomposition of methane over reduced Mg1− xM xAl2O4 spinel catalysts

Carbon nanotubes produced by the treatment of Mg1−xMxAl2O4 (M = Fe, Co, or Ni; x = 0.1, 0.2, 0.3, or 0.4) spinels with an H2–CH4 mixture at 1070 °C have been investigated systematically. The grains of the oxide-metal composite particles are uniformly covered by a weblike network of carbon nanotube bundles, several tens of micrometers long, made up of single-wall nanotubes with a diameter close to 4 nm. Only the smallest metal particles (<5 nm) are involved in the formation of the nanotubes. A macroscopic characterization method involving surface area measurements and chemical analysis has been developed in order to compare the different nanotube specimens. An increase in the transition metal content of the catalyst yields more carbon nanotubes (up to a metal content of 10.0 wt% or x = 0.3), but causes a decrease in carbon quality. The best compromise is to use 6.7 wt% of metal (x = 0.2) in the catalyst. Co gives superior results with respect to both the quantity and quality of the nanotubes. In the case of Fe, the quality is notably hampered by the formation of Fe3C particles.

NETGEM: Network Embedded Temporal GEnerative Model for gene expression data

Background: Temporal analysis of gene expression data has been limited to identifying genes whose expression varies with time and/or correlation between genes that have similar temporal profiles. Often, the methods do not consider the underlying network constraints that connect the genes. It is becoming increasingly evident that interactions change substantially with time. Thus far, there is no systematic method to relate the temporal changes in gene expression to the dynamics of interactions between them. Information on interaction dynamics would open up possibilities for discovering new mechanisms of regulation by providing valuable insight into identifying time-sensitive interactions as well as permit studies on the effect of a genetic perturbation. Results: We present NETGEM, a tractable model rooted in Markov dynamics, for analyzing the dynamics of the interactions between proteins based on the dynamics of the expression changes of the genes that encode them. The model treats the interaction strengths as random variables which are modulated by suitable priors. This approach is necessitated by the extremely small sample size of the datasets, relative to the number of interactions. The model is amenable to a linear time algorithm for efficient inference. Using temporal gene expression data, NETGEM was successful in identifying (i) temporal interactions and determining their strength, (ii) functional categories of the actively interacting partners and (iii) dynamics of interactions in perturbed networks. Conclusions: NETGEM represents an optimal trade-off between model complexity and data requirement. It was able to deduce actively interacting genes and functional categories from temporal gene expression data. It permits inference by incorporating the information available in perturbed networks. Given that the inputs to NETGEM are only the network and the temporal variation of the nodes, this algorithm promises to have widespread applications, beyond biological systems. The source code for NETGEM is available from https://github.com/vjethava/NETGEM

Hardware implementation of 4x4 DCT/Quantization block using multiplication and error-free algorithm

The 4ÃÂ4 discrete cosine transform is one of the most important building blocks for the emerging video coding standard, viz. H.264. The conventional implementation does some approximation to the transform matrix elements to facilitate integer arithmetic, for which hardware is suitably prepared. Though the transform coding does not involve any multiplications, quantization process requires sixteen 16-bit multiplications. The algorithm used here eliminates the process of approximation in transform coding and multiplication in the quantization process, by usage of algebraic integer coding. We propose an area-efficient implementation of the transform and quantization blocks based on the algebraic integer coding. The designs were synthesized with 90 nm TSMC CMOS technology and were also implemented on a Xilinx FPGA. The gate counts and throughput achievable in this case are 7000 and 125 Msamples/sec.

A Real-time clustering system for spatio-temporal signals from network of neurons

Over past few years, the studies of cultured neuronal networks have opened up avenues for understanding the ion channels, receptor molecules, and synaptic plasticity that may form the basis of learning and memory. The hippocampal neurons from rats are dissociated and cultured on a surface containing a grid of 64 electrodes. The signals from these 64 electrodes are acquired using a fast data acquisition system MED64 (Alpha MED Sciences, Japan) at a sampling rate of 20 K samples with a precision of 16-bits per sample. A few minutes of acquired data runs in to a few hundreds of Mega Bytes. The data processing for the neural analysis is highly compute-intensive because the volume of data is huge. The major processing requirements are noise removal, pattern recovery, pattern matching, clustering and so on. In order to interface a neuronal colony to a physical world, these computations need to be performed in real-time. A single processor such as a desk top computer may not be adequate to meet this computational requirements. Parallel computing is a method used to satisfy the real-time computational requirements of a neuronal system that interacts with an external world while increasing the flexibility and scalability of the application. In this work, we developed a parallel neuronal system using a multi-node Digital Signal processing system. With 8 processors, the system is able to compute and map incoming signals segmented over a period of 200 ms in to an action in a trained cluster system in real time.