57 resultados para Drought strategies


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As computational Grids are increasingly used for executing long running multi-phase parallel applications, it is important to develop efficient rescheduling frameworks that adapt application execution in response to resource and application dynamics. In this paper, three strategies or algorithms have been developed for deciding when and where to reschedule parallel applications that execute on multi-cluster Grids. The algorithms derive rescheduling plans that consist of potential points in application execution for rescheduling and schedules of resources for application execution between two consecutive rescheduling points. Using large number of simulations, it is shown that the rescheduling plans developed by the algorithms can lead to large decrease in application execution times when compared to executions without rescheduling on dynamic Grid resources. The rescheduling plans generated by the algorithms are also shown to be competitive when compared to the near-optimal plans generated by brute-force methods. Of the algorithms, genetic algorithm yielded the most efficient rescheduling plans with 9-12% smaller average execution times than the other algorithms.

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Development of new multifunctional nanostructures relies on the ability to make new materials at the nanoscale with control over size, shape and composition. While this control is extremely important to tune several properties, an alternative strategy is to create active interfaces between two or more nanostructures to form nanoscale heterostructures. In these heterostructures, the interfaces play a key role in stabilizing and enhancing the efficiency of the individual components for various applications. In this article, we discuss synthesis methods of different types of nanoscale heterostructures and the role of interfaces in various applications. We present the current state-of-the-art in designing heterostructures and possible upcoming synthetic strategies with their advantages and disadvantages. We present how such heterostructures are highly efficient for catalytic, photovoltaic and nanoelectronic applications drawing several examples from our own studies and from the literature.

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When an Indian prime minister publicly admits that India has fallen behind China, it is news. Manmohan Singh's statement last January at the Indian Science Congress in Bhubaneswar that this is so with respect to scientific research, and that “India's relative position in the world of science has been declining”, has rung alarm bells. Singh was not springing anything new on Indian scientists; many of us will admit that things are not well1. Recognizing the problem is the first step towards reversing this slide.

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Comparison of multiple protein structures has a broad range of applications in the analysis of protein structure, function and evolution. Multiple structure alignment tools (MSTAs) are necessary to obtain a simultaneous comparison of a family of related folds. In this study, we have developed a method for multiple structure comparison largely based on sequence alignment techniques. A widely used Structural Alphabet named Protein Blocks (PBs) was used to transform the information on 3D protein backbone conformation as a ID sequence string. A progressive alignment strategy similar to CLUSTALW was adopted for multiple PB sequence alignment (mulPBA). Highly similar stretches identified by the pairwise alignments are given higher weights during the alignment. The residue equivalences from PB based alignments are used to obtain a three dimensional fit of the structures followed by an iterative refinement of the structural superposition. Systematic comparisons using benchmark datasets of MSTAs underlines that the alignment quality is better than MULTIPROT, MUSTANG and the alignments in HOMSTRAD, in more than 85% of the cases. Comparison with other rigid-body and flexible MSTAs also indicate that mulPBA alignments are superior to most of the rigid-body MSTAs and highly comparable to the flexible alignment methods. (C) 2012 Elsevier Masson SAS. All rights reserved.

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Carbon footprint (CF) refers to the total amount of carbon dioxide and its equivalents emitted due to various anthropogenic activities. Carbon emission and sequestration inventories have been reviewed sector-wise for all federal states in India to identify the sectors and regions responsible for carbon imbalances. This would help in implementing appropriate climate change mitigation and management strategies at disaggregated levels. Major sectors of carbon emissions in India are through electricity generation, transport, domestic energy consumption, industries and agriculture. A majority of carbon storage occurs in forest biomass and soil. This paper focuses on the statewise carbon emissions (CO2. CO and CH4), using region specific emission factors and statewise carbon sequestration capacity. The estimate shows that CO2, CO and CH4 emissions from India are 965.9, 22.5 and 16.9 Tg per year, respectively. Electricity generation contributes 35.5% of total CO2 emission, which is followed by the contribution from transport. Vehicular transport exclusively contributes 25.5% of total emission. The analysis shows that Maharashtra emits higher CO2, followed by Andhra Pradesh, Uttar Pradesh, Gujarat, Tamil Nadu and West Bengal. The carbon status, which is the ratio of annual carbon storage against carbon emission, for each federal state is computed. This shows that small states and union territories (UT) like Arunachal Pradesh, Mizoram and Andaman and Nicobar Islands, where carbon sequestration is higher due to good vegetation cover, have carbon status > 1. Annually, 7.35% of total carbon emissions get stored either in forest biomass or soil, out of which 34% is in Arunachal Pradesh, Madhya Pradesh, Chhattisgarh and Orissa. (C) 2012 Elsevier Ltd. All rights reserved.

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Drought is the most crucial environmental factor that limits productivity of many crop plants. Exploring novel genes and gene combinations is of primary importance in plant drought tolerance research. Stress tolerant genotypes/species are known to express novel stress responsive genes with unique functional significance. Hence, identification and characterization of stress responsive genes from these tolerant species might be a reliable option to engineer the drought tolerance. Safflower has been found to be a relatively drought tolerant crop and thus, it has been the choice of study to characterize the genes expressed under drought stress. In the present study, we have evaluated differential drought tolerance of two cultivars of safflower namely, A1 and Nira using selective physiological marker traits and we have identified cultivar A1 as relatively drought tolerant. To identify the drought responsive genes, we have constructed a stress subtracted cDNA library from cultivar A1 following subtractive hybridization. Analysis of similar to 1,300 cDNA clones resulted in the identification of 667 unique drought responsive ESTs. Protein homology search revealed that 521 (78 %) out of 667 ESTs showed significant similarity to known sequences in the database and majority of them previously identified as drought stress-related genes and were found to be involved in a variety of cellular functions ranging from stress perception to cellular protection. Remaining 146 (22 %) ESTs were not homologous to known sequences in the database and therefore, they were considered to be unique and novel drought responsive genes of safflower. Since safflower is a stress-adapted oil-seed crop this observation has great relevance. In addition, to validate the differential expression of the identified genes, expression profiles of selected clones were analyzed using dot blot (reverse northern), and northern blot analysis. We showed that these clones were differentially expressed under different abiotic stress conditions. The implications of the analyzed genes in abiotic stress tolerance are discussed in our study.

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Single-layer graphene (SLG), the 3.4 angstrom thick two-dimensional sheet of sp(2) carbon atoms, was first prepared in 2004 by mechanical exfoliation of graphite crystals using the scotch tape technique. Since then, SLG has been prepared by other physical methods such as laser irradiation or ultrasonication of graphite in liquid media. Chemical methods of synthesis of SLG are more commonly used; the most popular involves preparation of single-layer graphene oxide followed by reduction with a stable reagent, often assisted by microwave heating. This method yields single-layer reduced graphene oxide. Other methods for preparing SLG include chemical vapour deposition over surfaces of transition metals such as Ni and Cu. Large-area SLG has also been prepared by epitaxial growth over SIC. Few-layer graphene (FLG) is prepared by several methods; arc discharge of graphite in hydrogen atmosphere being the most convenient. Several other methods for preparing FLG include exfoliation of graphite oxide by rapid heating, ultrasonication or laser irradiation of graphite in liquid media, reduction of few-layer graphene oxide, alkali metal intercalation followed by exfoliation. Graphene nanoribbons, which are rectangular strips of graphene, are best prepared by the unzipping of carbon nanotubes by chemical oxidation or laser irradiation. Many graphene analogues of inorganic materials such as MoS2, MoSe2 and BN have been prepared by mechanical exfoliation, ultrasonication and by chemical methods involving high-temperature or hydrothermal reactions and intercalation of alkali metals followed by exfoliation. Scrolls of graphene are prepared by potassium intercalation in graphite or by microwave irradiation of graphite immersed in liquid nitrogen.

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This article considers a class of deploy and search strategies for multi-robot systems and evaluates their performance. The application framework used is deployment of a system of autonomous mobile robots equipped with required sensors in a search space to gather information. The lack of information about the search space is modelled as an uncertainty density distribution. The agents are deployed to maximise single-step search effectiveness. The centroidal Voronoi configuration, which achieves a locally optimal deployment, forms the basis for sequential deploy and search (SDS) and combined deploy and search (CDS) strategies. Completeness results are provided for both search strategies. The deployment strategy is analysed in the presence of constraints on robot speed and limit on sensor range for the convergence of trajectories with corresponding control laws responsible for the motion of robots. SDS and CDS strategies are compared with standard greedy and random search strategies on the basis of time taken to achieve reduction in the uncertainty density below a desired level. The simulation experiments reveal several important issues related to the dependence of the relative performances of the search strategies on parameters such as the number of robots, speed of robots and their sensor range limits.