823 resultados para heterogeneous habitat
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In the presence of a catalytic amount of water, 1,5-dienes undergo novel and unusual oxidation with potassium permanganate�copper sulfate in dichloromethane to give substituted butanolides in good yields under very mild conditions.
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Homoallyl alcohols 4a-b and 5a-b undergo smooth oxidative cyclisation to give the corresponding ring enlarged keto-lactones under heterogeneous permanganate oxidation conditions.
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A high-throughput screening was employed to identify new compounds in Cu(CH3COO)(2)center dot H2O-NIPA-heterocyclic ligand systems. Of the compounds identified, three compounds, Cu-3{(NO2)-C6H3-(COO)(2)}(3)(C3N6H6)] (1), Cu-2(mu(3)-OH)(H2O){(NO2)-C6H3-(COO)(2)}(CN4H)]center dot-(H2O) (II), and Cu-2(mu(3)-OH)(H2O){(NO2)-C6H3-(COO)(2}-)(CN5H2)]center dot 2(H2O) (III), have been isolated as good quality single crystals by employing conventional hydrothermal methods. Three other compounds, Cu-2{(NO2)-C6H3-(COO)(2)}-(CN4H)(H2O) (IIa), Cu-2{(NO2)-C6H3-(COO)(2)}(CN5H2) (IIIa), and Cu-2{(NO2)-C6H3-(COO)(2)}{(CN5H2)(2)}2H(2)O (IIIb), were identified by a combination of elemental analysis, thermogravimetric analysis (TGA), and IR spectroscopic studies, although their structures are yet to be determined. The single crystalline compounds were also characterized by elemental analysis, TGA, IR, UV vis, magnetic, and catalytic studies. The structures of the compounds have paddle wheel (I) and infinite Cu 0(H) Cu chains (II and HI) connected with NLPA and heterocyclic ligands forming two-(II) and three-dimensional (I and III) structures. The bound and lattice water molecules in 11 and 111 could be reversibly removed/inserted without affecting the structure. In the case of II, the removal of water gives rise to a structural transition, but the dehydrated phase reverts back to the original phase on prolonged exposure to atmospheric conditions. Magnetic studies indicate an overall antiferromagnetism in all of the compounds. Lewis acid catalytic studies indicate that compounds II and HI are active for cyanosilylation of imines.
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1. Habitat fragmentation, anthropogenic disturbance and the introduction of invasive species are factors thought to structure ant assemblages. To understand responses of the ant community to changes in the environment, ants are commonly categorised into functional groups, a scheme developed and based on Australian ants. 2. Behaviourally dominant and aggressive ants of the dominant dolichoderinae functional group have been suggested to structure the ant assemblages in arid and semi-arid habitats of these regions. Given the limited geographical distribution of dominant dolichoderinae, it is crucial to determine the responses of the ant community to changes in the environment in their absence. 3. This study addresses this less studied aspect by considering the associations of ants of Western Ghats, India, with habitat, anthropogenic disturbance and introduced ants. We determined how ant functional groups respond to these factors in this region, where dominant dolichoderines are naturally absent, and whether responses are consistent with predictions derived from the ant functional group scheme. 4. This study provides new information on ant assemblages in a little-studied region. As in other parts of the world, ant assemblages in Western Ghats were strongly influenced by habitat and disturbance, with different functional groups associated with different habitats and levels of disturbance. 5. No functional group showed evidence of being influenced by the abundance of introduced species. In addition, predictions of negative interactions between functional groups were not supported. Our findings suggest that abiotic factors are universal determinants of ant assemblage structure, but that competitive interactions may not be.
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It is argued that the nanometric dispersion of Bi in a Zn matrix is an ideal model system for heterogeneous nucleation experiments. The classical theory of heterogeneous nucleation with a hemispherical cap model is applied to analyse the nucleation data. It is shown that, unlike the results of earlier experiments, the derived site density for catalytic nucleation and contact angle are realistic and strongly suggest the validity of the classical theory. The surface energy between the 0001 plane of Zn and the <10(1)over bar 2> plane of Bi, which constitute the epitaxial nucleation interface, is estimated to be 39 mJ m(-2).
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Aqueous phase oxidation of sulphur dioxide at low concentrations catalysed by a PVP-Cu complex in the solid phase and dissolved Cu(II) in the liquid phase is studied in a rotating catalyst basket reactor (RCBR). The equilibrium adsorption of Cu(II) and S(VI) on PVP particles is found to be of the Langmuir-type. The diffusional effects of S(IV) species in PVP-Cu resin are found to be insignificant whereas that of product S(VI) are found to be significant. The intraparticle diffusivity of S(VI) is obtained from independent tracer experiments. In the oxidation reaction HSO3- is the reactive species. Both the S(IV) species in the solution, namely SO2(aq) and HSO3- get adsorbed onto the active PVP-Cu sites of the catalyst, but only HSO3- undergoes oxidation. A kinetic mechanism is proposed based on this feature which shows that SO2(aq) has a deactivating effect on the catalyst. A rate model is developed for the three-phase reaction system incorporating these factors along with the effect of concentration of H2SO4 on the solubility of SO2 in the dilute aqueous solutions of Cu(II). Transient oxidation experiments are conducted at different conditions of concentration of SO2 and O-2 in the gas phase and catalyst concentration, and the rate parameters are estimated from the data. The observed and calculated profiles are in very good agreement. This confirms the deactivating effect of nonreactive SO2(aq) on the heterogeneous catalysis.
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There are p heterogeneous objects to be assigned to n competing agents (n > p) each with unit demand. It is required to design a Groves mechanism for this assignment problem satisfying weak budget balance, individual rationality, and minimizing the budget imbalance. This calls for designing an appropriate rebate function. When the objects are identical, this problem has been solved which we refer as WCO mechanism. We measure the performance of such mechanisms by the redistribution index. We first prove an impossibility theorem which rules out linear rebate functions with non-zero redistribution index in heterogeneous object assignment. Motivated by this theorem,we explore two approaches to get around this impossibility. In the first approach, we show that linear rebate functions with non-zero redistribution index are possible when the valuations for the objects have a certain type of relationship and we design a mechanism with linear rebate function that is worst case optimal. In the second approach, we show that rebate functions with non-zero efficiency are possible if linearity is relaxed. We extend the rebate functions of the WCO mechanism to heterogeneous objects assignment and conjecture them to be worst case optimal.
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Small mammals were sampled in two natural habitats (montane stunted evergreen forests and montane grassland) and four anthropogenic habitats (tea, wattle, bluegum and pine plantation) in the Upper Nilgiris in southern India. Of the species trapped, eight were in montane evergreen forests and three were in other habitats. Habitat discrimination was studied in the rodents Rattus rattus and Mus famulus and the shrew Suncus montanus in the montane forest habitat. Multivariate tests on five variables (canopy cover, midstorey density, ground cover, tree density, canopy height) showed that R. rattus uses areas of higher tree density and lower canopy cover. Suncus montanus and M. famulus use habitat with higher tree density and ground cover and lower canopy height. Multivariate tests did not discriminate habitat use between the species. Univariate tests, however, showed that M. famulus uses areas of higher tree density than R. rattus and S. montanus. Rattus rattus was the dominant species in the montane forest, comprising 60.9% of total density, while the rodent Millardia meltada was the dominant species in the grassland. Studies of spatial interaction between these two species in habitats where they coexisted showed neither overlap nor avoidance between the species. Rattus rattus, however, did use areas of lower ground cover than did M. meltada. The analysis of spatial interactions between the species, habitat discrimination and use, and the removal experiments suggest that interspecific competition may not be a strong force in structuring these small mammal communities. There are distinct patterns in the use of different habitats by some species, but microhabitat selection and segregation is weak. Other factors such as intraspecific competition may play a more important role in these communities.
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MATLAB is an array language, initially popular for rapid prototyping, but is now being increasingly used to develop production code for numerical and scientific applications. Typical MATLAB programs have abundant data parallelism. These programs also have control flow dominated scalar regions that have an impact on the program's execution time. Today's computer systems have tremendous computing power in the form of traditional CPU cores and throughput oriented accelerators such as graphics processing units(GPUs). Thus, an approach that maps the control flow dominated regions to the CPU and the data parallel regions to the GPU can significantly improve program performance. In this paper, we present the design and implementation of MEGHA, a compiler that automatically compiles MATLAB programs to enable synergistic execution on heterogeneous processors. Our solution is fully automated and does not require programmer input for identifying data parallel regions. We propose a set of compiler optimizations tailored for MATLAB. Our compiler identifies data parallel regions of the program and composes them into kernels. The problem of combining statements into kernels is formulated as a constrained graph clustering problem. Heuristics are presented to map identified kernels to either the CPU or GPU so that kernel execution on the CPU and the GPU happens synergistically and the amount of data transfer needed is minimized. In order to ensure required data movement for dependencies across basic blocks, we propose a data flow analysis and edge splitting strategy. Thus our compiler automatically handles composition of kernels, mapping of kernels to CPU and GPU, scheduling and insertion of required data transfer. The proposed compiler was implemented and experimental evaluation using a set of MATLAB benchmarks shows that our approach achieves a geometric mean speedup of 19.8X for data parallel benchmarks over native execution of MATLAB.
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In this thesis we address the problem of multi-agent search. We formulate two deploy and search strategies based on optimal deployment of agents in search space so as to maximize the search effectiveness in a single step. We show that a variation of centroidal Voronoi configuration is the optimal deployment. When the agents have sensors with different capabilities, the problem will be heterogeneous in nature. We introduce a new concept namely, generalized Voronoi partition in order to formulate and solve the heterogeneous multi-agent search problem. We address a few theoretical issues such as optimality of deployment, convergence and spatial distributedness of the control law and the search strategies. Simulation experiments are carried out to compare performances of the proposed strategies with a few simple search strategies.
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Microwave-based methods are widely employed to synthesize metal nanoparticles on various substrates. However, the detailed mechanism of formation of such hybrids has not been addressed. In this paper, we describe the thermodynamic and kinetic aspects of reduction of metal salts by ethylene glycol under microwave heating conditions. On the basis of this analysis, we identify the temperatures above which the reduction of the metal salt is thermodynamically favorable and temperatures above which the rates of homogeneous nucleation of the metal and the heterogeneous nucleation of the metal on supports are favored. We delineate different conditions which favor the heterogeneous nucleation of the metal on the supports over homogeneous nucleation in the solvent medium based on the dielectric loss parameters of the solvent and the support and the metal/solvent and metal/support interfacial energies. Contrary to current understanding, we show that metal particles can be selectively formed on the substrate even under situations where the temperature of the substrate Is lower than that of the surrounding medium. The catalytic activity of the Pt/CeO(2) and Pt/TiO(2) hybrids synthesized by this method for H(2) combustion reaction shows that complete conversion is achieved at temperatures as low as 100 degrees C with Pt-CeO(2) catalyst and at 50 degrees C with Pt-TiO(2) catalyst. Our method thus opens up possibilities for rational synthesis of high-activity supported catalysts using a fast microwave-based reduction method.
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Practical usage of machine learning is gaining strategic importance in enterprises looking for business intelligence. However, most enterprise data is distributed in multiple relational databases with expert-designed schema. Using traditional single-table machine learning techniques over such data not only incur a computational penalty for converting to a flat form (mega-join), even the human-specified semantic information present in the relations is lost. In this paper, we present a practical, two-phase hierarchical meta-classification algorithm for relational databases with a semantic divide and conquer approach. We propose a recursive, prediction aggregation technique over heterogeneous classifiers applied on individual database tables. The proposed algorithm was evaluated on three diverse datasets. namely TPCH, PKDD and UCI benchmarks and showed considerable reduction in classification time without any loss of prediction accuracy. (C) 2012 Elsevier Ltd. All rights reserved.
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Native species' response to the presence of invasive species is context specific. This response cannot be studied in isolation from the prevailing environmental stresses in invaded habitats such as seasonal drought. We investigated the combined effects of an invasive shrub Lantana camara L. (lantana), seasonal rainfall and species' microsite preferences on the growth and survival of 1,105 naturally established seedlings of native trees and shrubs in a seasonally dry tropical forest. Individuals were followed from April 2008 to February 2010, and growth and survival measured in relation to lantana density, seasonality of rainfall and species characteristics in a 50-ha permanent forest plot located in Mudumalai, southern India. We used a mixed effects modelling approach to examine seedling growth and generalized linear models to examine seedling survival. The overall relative height growth rate of established seedlings was found to be very low irrespective of the presence or absence of dense lantana. 22-month growth rate of dry forest species was lower under dense lantana while moist forest species were not affected by the presence of lantana thickets. 4-month growth rates of all species increased with increasing inter-census rainfall. Community results may be influenced by responses of the most abundant species, Catunaregam spinosa, whose growth rates were always lower under dense lantana. Overall seedling survival was high, increased with increasing rainfall and was higher for species with dry forest preference than for species with moist forest preference. The high survival rates of naturally established seedlings combined with their basal sprouting ability in this forest could enable the persistence of woody species in the face of invasive species.
Resumo:
MATLAB is an array language, initially popular for rapid prototyping, but is now being increasingly used to develop production code for numerical and scientific applications. Typical MATLAB programs have abundant data parallelism. These programs also have control flow dominated scalar regions that have an impact on the program's execution time. Today's computer systems have tremendous computing power in the form of traditional CPU cores and throughput oriented accelerators such as graphics processing units(GPUs). Thus, an approach that maps the control flow dominated regions to the CPU and the data parallel regions to the GPU can significantly improve program performance. In this paper, we present the design and implementation of MEGHA, a compiler that automatically compiles MATLAB programs to enable synergistic execution on heterogeneous processors. Our solution is fully automated and does not require programmer input for identifying data parallel regions. We propose a set of compiler optimizations tailored for MATLAB. Our compiler identifies data parallel regions of the program and composes them into kernels. The problem of combining statements into kernels is formulated as a constrained graph clustering problem. Heuristics are presented to map identified kernels to either the CPU or GPU so that kernel execution on the CPU and the GPU happens synergistically and the amount of data transfer needed is minimized. In order to ensure required data movement for dependencies across basic blocks, we propose a data flow analysis and edge splitting strategy. Thus our compiler automatically handles composition of kernels, mapping of kernels to CPU and GPU, scheduling and insertion of required data transfer. The proposed compiler was implemented and experimental evaluation using a set of MATLAB benchmarks shows that our approach achieves a geometric mean speedup of 19.8X for data parallel benchmarks over native execution of MATLAB.