Stereochemistry of 2'-5' linked nucleic acids: crystal and molecular structure of ammonium adenylyl-2',5'-adenosine tetrahydrate: a core fragment of 2'-5' oligo A's produced by interferon induced adenylate synthetase

The preponderance of 3'-5' phosphodiester links in nucleic acids is well known. Albeit less prevalent, the 2'-5' links are specifically utilised in the formation of 'lariat' in group II introns and in the msDNA-RNA junction in myxobacterium. As a sequel to our earlier study on cytidylyl-2',5'-adenosine we have now obtained the crystal structure of adenylyl-2',5'-adenosine (A2'p5'A) at atomic resolution. This dinucleoside monophosphate crystallizes in the orthorhombic space group P2(1)2(1)2(1) with a = 7.956(3) A, b = 12.212(3) A and c = 36.654(3) A. CuK alpha intensity data were collected on a diffractometer. The structure was sloved by direct methods and refined by full matrix least squares methods to R = 10.8%. The 2' terminal adenine is in the commonly observed anti (chi 2 = 161 degrees) conformation and the 5' terminal base has a syn (chi 1 = 55 degrees) conformation more often seen in purine nucleotides. A noteworthy feature of A2'p5'A is the intranucleotide hydrogen bond between N3 and O5' atoms of the 5' adenine base. The two furanose rings in A2'p5'A show different conformations - C2' endo, C3' endo puckering for the 5' and 2' ends respectively. In this structure too there is a stacking of the purine base on the ribose O4' just as in other 2'-5' dinucleoside structures, a feature characteristically seen in the left handed Z DNA. In having syn, anti conformation about the glycosyl bonds, C2' endo, C3' endo mixed sugar puckering and N3-O5' intramolecular hydrogen bond A2'p5'A resembles its 3'-5' analogue and several other 2'-5' dinucleoside monophosphate structures solved so far. Striking similarities between the 2'-5' dinucleoside monophosphate structures suggest that the conformation of the 5'-end nucleoside dictates the conformation of the 2' end nucleoside. Also, the 2'-5' dimers do not favour formation of miniature classical double helical structures like the 3'-5' dimers. It is conceivable, 2-5(A) could be using the stereochemical features of A2'p5'A which accounts for its higher activity.

Impact of climate change on Indian forests: a dynamic vegetation modeling approach

We make an assessment of the impact of projected climate change on forest ecosystems in India. This assessment is based on climate projections of the Regional Climate Model of the Hadley Centre (HadRM3) and the dynamic global vegetation model IBIS for A2 and B2 scenarios. According to the model projections, 39% of forest grids are likely to undergo vegetation type change under the A2 scenario and 34% under the B2 scenario by the end of this century. However, in many forest dominant states such as Chattisgarh, Karnataka and Andhra Pradesh up to 73%, 67% and 62% of forested grids are projected to undergo change. Net Primary Productivity (NPP) is projected to increase by 68.8% and 51.2% under the A2 and B2 scenarios, respectively, and soil organic carbon (SOC) by 37.5% for A2 and 30.2% for B2 scenario. Based on the dynamic global vegetation modeling, we present a forest vulnerability index for India which is based on the observed datasets of forest density, forest biodiversity as well as model predicted vegetation type shift estimates for forested grids. The vulnerability index suggests that upper Himalayas, northern and central parts of Western Ghats and parts of central India are most vulnerable to projected impacts of climate change, while Northeastern forests are more resilient. Thus our study points to the need for developing and implementing adaptation strategies to reduce vulnerability of forests to projected climate change.

CO2-fertilization and potential future terrestrial carbon uptake in India

There is huge knowledge gap in our understanding of many terrestrial carbon cycle processes. In this paper, we investigate the bounds on terrestrial carbon uptake over India that arises solely due to CO (2) -fertilization. For this purpose, we use a terrestrial carbon cycle model and consider two extreme scenarios: unlimited CO2-fertilization is allowed for the terrestrial vegetation with CO2 concentration level at 735 ppm in one case, and CO2-fertilization is capped at year 1975 levels for another simulation. Our simulations show that, under equilibrium conditions, modeled carbon stocks in natural potential vegetation increase by 17 Gt-C with unlimited fertilization for CO2 levels and climate change corresponding to the end of 21st century but they decline by 5.5 Gt-C if fertilization is limited at 1975 levels of CO2 concentration. The carbon stock changes are dominated by forests. The area covered by natural potential forests increases by about 36% in the unlimited fertilization case but decreases by 15% in the fertilization-capped case. Thus, the assumption regarding CO2-fertilization has the potential to alter the sign of terrestrial carbon uptake over India. Our model simulations also imply that the maximum potential terrestrial sequestration over India, under equilibrium conditions and best case scenario of unlimited CO2-fertilization, is only 18% of the 21st century SRES A2 scenarios emissions from India. The limited uptake potential of the natural potential vegetation suggests that reduction of CO2 emissions and afforestation programs should be top priorities.

Climate change and forests in India: adaptation opportunities and challenges

Climate change is projected to lead to shift of forest types leading to irreversible damage to forests by rendering several species extinct and potentially affecting the livelihoods of local communities and the economy. Approximately 47% and 42% of tropical dry deciduous grids are projected to undergo shifts under A2 and B2 SRES scenarios respectively, as opposed to less than 16% grids comprising of tropical wet evergreen forests. Similarly, the tropical thorny scrub forest is projected to undergo shifts in majority of forested grids under A2 (more than 80%) as well as B2 scenarios (50% of grids). Thus the forest managers and policymakers need to adapt to the ecological as well as the socio-economic impacts of climate change. This requires formulation of effective forest management policies and practices, incorporating climate concerns into long-term forest policy and management plans. India has formulated a large number of innovative and progressive forest policies but a mechanism to ensure effective implementation of these policies is needed. Additional policies and practices may be needed to address the impacts of climate change. This paper discusses an approach and steps involved in the development of an adaptation framework as well as policies, strategies and practices needed for mainstreaming adaptation to cope with projected climate change. Further, the existing barriers which may affect proactive adaptation planning given the scale, accuracy and uncertainty associated with assessing climate change impacts are presented.

Impact of climate change at species level: a case study of teak in India

In this study, we model the long-term effect of climate change on commercially important teak (Tectona grandis) and its productivity in India. This modelling assessment is based on climate projections of the regional climate model of the Hadley Center (HadRM3) and the dynamic vegetation model, IBIS. According to the model projections, 30% of teak grids in India are vulnerable to climate change under both A2 and B2 SRES scenarios because the future climate may not be optimal for teak at these grids. However, the net primary productivity and biomass are expected to increase because of elevated levels of CO2. Given these directions of likely impacts, it is crucial to further investigate the climate change impacts on teak and incorporate such findings into long-term teak plantation programs. This study also demonstrates the feasibility and limitations of assessing the impact of projected climate change at the species level in the tropics.

Implications of climate change on mitigation potential estimates for forest sector in India

Climate change is projected to impact forest ecosystems, including biodiversity and Net Primary Productivity (NPP). National level carbon forest sector mitigation potential estimates are available for India; however impacts of projected climate change are not included in the mitigation potential estimates. Change in NPP (in gC/m(2)/yr) is taken to represent the impacts of climate change. Long term impacts of climate change (2085) on the NPP of Indian forests are available; however no such regional estimates are available for short and medium terms. The present study based on GCM climatology scenarios projects the short, medium and long term impacts of climate change on forest ecosystems especially on NPP using BIOME4 vegetation model. We estimate that under A2 scenario by the year 2030 the NPP changes by (-5) to 40% across different agro-ecological zones (AEZ). By 2050 it increases by 15% to 59% and by 2070 it increases by 34 to 84%. However, under B2 scenario it increases only by 3 to 25%, 3.5 to 34% and (-2.5) to 38% respectively, in the same time periods. The cumulative mitigation potential is estimated to increase by up to 21% (by nearly 1 GtC) under A2 scenario between the years 2008 and 2108, whereas, under B2 the mitigation potential increases only by 14% (646 MtC). However, cumulative mitigation potential estimates obtained from IBIS-a dynamic global vegetation model suggest much smaller gains, where mitigation potential increases by only 6% and 5% during the period 2008 to 2108.

A macroeconomic analysis of adaptation to climate change impacts on forests in India

We examine the potential for adaptation to climate change in Indian forests, and derive the macroeconomic implications of forest impacts and adaptation in India. The study is conducted by integrating results from the dynamic global vegetation model IBIS and the computable general equilibrium model GRACE-IN, which estimates macroeconomic implications for six zones of India. By comparing a reference scenario without climate change with a climate impact scenario based on the IPCC A2-scenario, we find major variations in the pattern of change across zones. Biomass stock increases in all zones but the Central zone. The increase in biomass growth is smaller, and declines in one more zone, South zone, despite higher stock. In the four zones with increases in biomass growth, harvest increases by only approximately 1/3 of the change in biomass growth. This is due to two market effects of increased biomass growth. One is that an increase in biomass growth encourages more harvest given other things being equal. The other is that more harvest leads to higher supply of timber, which lowers market prices. As a result, also the rent on forested land decreases. The lower prices and rent discourage more harvest even though they may induce higher demand, which increases the pressure on harvest. In a less perfect world than the model describes these two effects may contribute to an increase in the risk of deforestation because of higher biomass growth. Furthermore, higher harvest demands more labor and capital input in the forestry sector. Given total supply of labor and capital, this increases the cost of production in all the other sectors, although very little indeed. Forestry dependent communities with declining biomass growth may, however, experience local unemployment as a result.

Design and development of a self-supported polymer electrolyte fuel cell system with anodic dead-end operation

Design and operational details for a self-supported polymer electrolyte fuel cell (PEFC) system with anodic dead-end fuel supply and internally humidified cathodic oxidant flow are described. During the PEFC operation, nitrogen and water back diffuse across the Nafion membrane from the cathode to the anode and accumulate in the anode flow channels affecting stack performance. The accumulated inert species are flushed from the stack by purging the fuel cell stack with a timer-activated purge valve to address the aforesaid problem. To minimize the system complexity, stack is designed in such a way that all the inert species accumulate in only one cell called the purge cell. A pulsed purge sequence comprises opening the valve for purge duration followed by purge-valve closing for the hold period and repeating the sequence in cycles. Since self-humidification is inadequate to keep the membrane wet, the anodic dead-end-operated PEFC stack with composite membrane comprising perflourosulphonic acid (Nafion) and silica is employed for keeping the membrane humidified even while operating the stack with dry hydrogen and internally humidified air.

Wet chemical formation of nanoparticles of binary perovskites through isothermal gel to crystallite conversion

Coarse BO2·xH2O (2 < x < 80) gels, free of anion contaminants react with A(OH)2 under refluxing conditions at 70�100°C giving rise to crystallites of single phased, nanometer size powders of ABO3 perovskites (A = Ba, Sr, Ca, Mg, Pb; B = Zr, Ti, Sn). Solid solutions of perovskites could be prepared from compositionally modified gels or mixtures of A(OH)2. Donor doped perovskites could also be prepared from the same method so that the products after processing are often semiconducting. Faster interfacial diffusion of A2+ ions into the gel generates the crystalline regions whose composition is controllable by the A/B ratio as well as the A(OH)2 concentration.

Studies on n=2 Aurivillius phases: structure of the series Bi3-xLaxTiNbO9 (0 <= x <= 1)

The crystal structures of the solid solutions of Bi3-xLaxTiNbO9 (0 less than or equal to x less than or equal to 1) have been analyzed by powder X-ray diffraction with supporting evidence from selected area electron diffraction (SAD). The structure of the starting member (x = 0) is verified to be in the orthorhombic space group A2(1) am while the end member (x = 1) is determined to crystallize in the centrosymmetric orthorhombic space group Pmcb. The structure of x = 1 phase is solved by ab initio powder diffraction. The intermediate compositions belong to the space group A2(1) am as confirmed by Rietveld refinements. Rietveld refinements on all the compositions reveal that the La3+ ion is disordered only in the A site and not in the [Bi2O2](2+) layer. The tilt in the Ti/NbO6 octahedra decreases with increasing x. (C) 2003 Elsevier B.V. All rights reserved.

Multigroup-Decodable STBCs from Clifford Algebras

A Space-Time Block Code (STBC) in K symbols (variables) is called g-group decodable STBC if its maximum-likelihood decoding metric can be written as a sum of g terms such that each term is a function of a subset of the K variables and each variable appears in only one term. In this paper we provide a general structure of the weight matrices of multi-group decodable codes using Clifford algebras. Without assuming that the number of variables in each group to be the same, a method of explicitly constructing the weight matrices of full-diversity, delay-optimal g-group decodable codes is presented for arbitrary number of antennas. For the special case of Nt=2a we construct two subclass of codes: (i) A class of 2a-group decodable codes with rate a2(a−1), which is, equivalently, a class of Single-Symbol Decodable codes, (ii) A class of (2a−2)-group decodable with rate (a−1)2(a−2), i.e., a class of Double-Symbol Decodable codes. Simulation results show that the DSD codes of this paper perform better than previously known Quasi-Orthogonal Designs.

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.

Daily relative humidity projections in an Indian river basin for IPCC SRES scenarios

A two-stage methodology is developed to obtain future projections of daily relative humidity in a river basin for climate change scenarios. In the first stage, Support Vector Machine (SVM) models are developed to downscale nine sets of predictor variables (large-scale atmospheric variables) for Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (SRES) (A1B, A2, B1, and COMMIT) to R (H) in a river basin at monthly scale. Uncertainty in the future projections of R (H) is studied for combinations of SRES scenarios, and predictors selected. Subsequently, in the second stage, the monthly sequences of R (H) are disaggregated to daily scale using k-nearest neighbor method. The effectiveness of the developed methodology is demonstrated through application to the catchment of Malaprabha reservoir in India. For downscaling, the probable predictor variables are extracted from the (1) National Centers for Environmental Prediction reanalysis data set for the period 1978-2000 and (2) simulations of the third-generation Canadian Coupled Global Climate Model for the period 1978-2100. The performance of the downscaling and disaggregation models is evaluated by split sample validation. Results show that among the SVM models, the model developed using predictors pertaining to only land location performed better. The R (H) is projected to increase in the future for A1B and A2 scenarios, while no trend is discerned for B1 and COMMIT.