Ru(4+) ion in CeO(2) (Ce(0.95)Ru(0.05)O(2-delta)): A non-deactivating, non-platinum catalyst for water gas shift reaction

Hydrogen is a clean energy carrier and highest energy density fuel. Water gas shift (WGS) reaction is an important reaction to generate hydrogen from steam reforming of CO. A new WGS catalyst, Ce(1-x)Ru(x)O(2-delta) (0 <= x <= 0.1) was prepared by hydrothermal method using melamine as a complexing agent. The Catalyst does not require any pre-treatment. Among the several compositions prepared and tested, Ce(0.95)Ru(0.05)O(2-delta) (5% Ru(4+) ion substituted in CeO(2)) showed very high WGS activity in terms of high conversion rate (20.5 mu mol.g(-1).s(-1) at 275 degrees C) and low activation energy (12.1 kcal/mol). Over 99% conversion of CO to CO(2) by H(2)O is observed with 100% H(2) selectivity at >= 275 degrees C. In presence of externally fed CO(2) and H(2) also, complete conversion of CO to CO(2) was observed with 100% H(2) selectivity in the temperature range of 305-385 degrees C. Catalyst does not deactivate in long duration on/off WGS reaction cycle due to absence of surface carbon and carbonate formation and sintering of Ru. Due to highly acidic nature of Ru(4+) ion, surface carbonate formation is also inhibited. Sintering of noble metal (Ru) is avoided in this catalyst because Ru remains in Ru(4+) ionic state in the Ce(1-x)Ru(x)O(2-delta) catalyst.

A comparison of three methods for downscaling daily precipitation in the Punjab region

Many downscaling techniques have been developed in the past few years for projection of station-scale hydrological variables from large-scale atmospheric variables simulated by general circulation models (GCMs) to assess the hydrological impacts of climate change. This article compares the performances of three downscaling methods, viz. conditional random field (CRF), K-nearest neighbour (KNN) and support vector machine (SVM) methods in downscaling precipitation in the Punjab region of India, belonging to the monsoon regime. The CRF model is a recently developed method for downscaling hydrological variables in a probabilistic framework, while the SVM model is a popular machine learning tool useful in terms of its ability to generalize and capture nonlinear relationships between predictors and predictand. The KNN model is an analogue-type method that queries days similar to a given feature vector from the training data and classifies future days by random sampling from a weighted set of K closest training examples. The models are applied for downscaling monsoon (June to September) daily precipitation at six locations in Punjab. Model performances with respect to reproduction of various statistics such as dry and wet spell length distributions, daily rainfall distribution, and intersite correlations are examined. It is found that the CRF and KNN models perform slightly better than the SVM model in reproducing most daily rainfall statistics. These models are then used to project future precipitation at the six locations. Output from the Canadian global climate model (CGCM3) GCM for three scenarios, viz. A1B, A2, and B1 is used for projection of future precipitation. The projections show a change in probability density functions of daily rainfall amount and changes in the wet and dry spell distributions of daily precipitation. Copyright (C) 2011 John Wiley & Sons, Ltd.

An oxidative cross-dehydrogenative-coupling reaction in water using molecular oxygen as the oxidant: vanadium catalyzed indolation of tetrahydroisoquinolines

An aerobic oxidative cross-dehydrogenative coupling reaction between sp(3) C-H and sp(2) C-H bonds is developed by employing a vanadium catalyst (10 mol%) in an aqueous medium using molecular oxygen as the oxidant. This environmentally benign strategy exhibits larger substrate scope and shows high regioselectivity.

Support Vector Machine Approach to Downscale Precipitation in Climate Change Scenarios

Concern over changes in global climate has increased in recent years with improvement in understanding of atmospheric dynamics and growth in evidence of climate link to long‐term variability in hydrologic records. Climate impact studies rely on climate change information at fine spatial resolution. Towards this, the past decade has witnessed significant progress in development of downscaling models to cascade the climate information provided by General Circulation Models (GCMs) at coarse spatial resolution to the scale relevant for hydrologic studies. While a plethora of downscaling models have been applied successfully to mid‐latitude regions, a few studies are available on tropical regions where the atmosphere is known to have more complex behavior. In this paper, a support vector machine (SVM) approach is proposed for statistical downscaling to interpret climate change signals provided by GCMs over tropical regions of India. Climate variables affecting spatio‐temporal variation of precipitation at each meteorological sub‐division of India are identified. Following this, cluster analysis is applied on climate data to identify the wet and dry seasons in each year. The data pertaining to climate variables and precipitation of each meteorological sub‐division is then used to develop SVM based downscaling model for each season. Subsequently, the SVM based downscaling model is applied to future climate predictions from the second generation Coupled Global Climate Model (CGCM2) to assess the impact of climate change on hydrological inputs to the meteorological sub‐divisions. The results obtained from the SVM downscaling model are then analyzed to assess the impact of climate change on precipitation over India.

Production of niobium powder by electronically mediated reaction (EMR) using calcium as a reductant

Explored in this study is an electronically mediated reaction (EMR) route for the production of niobium powder using calcium as a reductant for niobium oxide (Nb2O5). Feed material, Nb2O5, and reductant calcium alloy containing aluminum and nickel were charged into electronically isolated locations in a molten salt (e.g. CaCl2) at 1173 K. The current flow through an external path between the feed and reductant locations was monitored. A current approximately 0.4 A was measured during the reaction in the external circuit connecting cathode and anode location. Niobium powder with low aluminum and nickel content was obtained although liquid Ca–Al–Ni alloy was used as the reductant. This clearly demonstrates that niobium metal powder can be produced by an electronically mediated reaction (EMR), without direct physical contact between feed (Nb2O5) and reductant (calcium). Mechanism of calciothermic reduction of Nb2O5 in the molten salt is discussed using an isothermal chemical potential diagram.

Passive vibration isolation of reaction wheel disturbances using a low frequency flexible space platform

Reaction wheel assemblies (RWAs) are momentum exchange devices used in fine pointing control of spacecrafts. Even though the spinning rotor of the reaction wheel is precisely balanced to minimize emitted vibration due to static and dynamic imbalances, precision instrument payloads placed in the neighborhood can always be severely impacted by residual vibration forces emitted by reaction wheel assemblies. The reduction of the vibration level at sensitive payloads can be achieved by placing the RWA on appropriate mountings. A low frequency flexible space platform consisting of folded continuous beams has been designed to serve as a mount for isolating a disturbance source in precision payloads equipped spacecrafts. Analytical and experimental investigations have been carried out to test the usefulness of the low frequency flexible platform as a vibration isolator for RWAs. Measurements and tests have been conducted at varying wheel speeds, to quantify and characterize the amount of isolation obtained from the reaction wheel generated vibration. These tests are further extended to other variants of similar design in order to bring out the best isolation for given disturbance loads. Both time and frequency domain analysis of test data show that the flexible beam platform as a mount for reaction wheels is quite effective and can be used in spacecrafts for passive vibration control. (C) 2011 Elsevier Ltd. All rights reserved.

Differential Reaction Kinetics, Cleavage Complex Formation, and Nonamer Binding Domain Dependence Dictate the Structure-Specific and Sequence-Specific Nuclease Activity of RAGs

During V(D)J recombination, RAG (recombination-activating gene) complex cleaves DNA based on sequence specificity. Besides its physiological function, RAG has been shown to act as a structure-specific nuclease. Recently, we showed that the presence of cytosine within the single-stranded region of heteroduplex DNA is important when RAGs cleave on DNA structures. In the present study, we report that heteroduplex DNA containing a bubble region can be cleaved efficiently when present along with a recombination signal sequence (RSS) in cis or trans configuration. The sequence of the bubble region influences RAG cleavage at RSS when present in cis. We also find that the kinetics of RAG cleavage differs between RSS and bubble, wherein RSS cleavage reaches maximum efficiency faster than bubble cleavage. In addition, unlike RSS, RAG cleavage at bubbles does not lead to cleavage complex formation. Finally, we show that the ``nonamer binding region,'' which regulates RAG cleavage on RSS, is not important during RAG activity in non-B DNA structures. Therefore, in the current study, we identify the possible mechanism by which RAG cleavage is regulated when it acts as a structure-specific nuclease. (C) 2011 Elsevier Ltd. All rights reserved.