10 resultados para yuan

em Indian Institute of Science - Bangalore - Índia


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The estimation of the frequency of a sinusoidal signal is a well researched problem. In this work we propose an initialization scheme to the popular dichotomous search of the periodogram peak algorithm(DSPA) that is used to estimate the frequency of a sinusoid in white gaussian noise. Our initialization is computationally low cost and gives the same performance as the DSPA, while reducing the number of iterations needed for the fine search stage. We show that our algorithm remains stable as we reduce the number of iterations in the fine search stage. We also compare the performance of our modification to a previous modification of the DSPA and show that we enhance the performance of the algorithm with our initialization technique.

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In this paper, a novel genetic algorithm is developed by generating artificial chromosomes with probability control to solve the machine scheduling problems. Generating artificial chromosomes for Genetic Algorithm (ACGA) is closely related to Evolutionary Algorithms Based on Probabilistic Models (EAPM). The artificial chromosomes are generated by a probability model that extracts the gene information from current population. ACGA is considered as a hybrid algorithm because both the conventional genetic operators and a probability model are integrated. The ACGA proposed in this paper, further employs the ``evaporation concept'' applied in Ant Colony Optimization (ACO) to solve the permutation flowshop problem. The ``evaporation concept'' is used to reduce the effect of past experience and to explore new alternative solutions. In this paper, we propose three different methods for the probability of evaporation. This probability of evaporation is applied as soon as a job is assigned to a position in the permutation flowshop problem. Experimental results show that our ACGA with the evaporation concept gives better performance than some algorithms in the literature.

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In the present paper, the constitutive model is proposed for cemented soils, in which the cementation component and frictional component are treated separately and then added together to get overall response. The modified Cam clay is used to predict the frictional resistance and an elasto-plastic strain softening model is proposed for the cementation component. The rectangular isotropic yield curve proposed by Vatsala (1995) for the bond component has been modified in order to account for the anisotropy generally observed in the case of natural soft cemented soils. In this paper, the model proposed is used to predict the experimental results of extension tests on the soft cemented soils whereas compression test results are presented elsewhere. The model predictions compare quite satisfactorily with the observed response. A few input parameters are required which are well defined and easily determinable and the model uses associated flow rule.

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A moving magnet linear motor compressor or pressure wave generator (PWG) of 2 cc swept volume with dual opposed piston configuration has been developed to operate miniature pulse tube coolers. Prelimnary experiments yielded only a no-load cold end temperature of 180 K. Auxiliary tests and the interpretation of detailed modeling of a PWG suggest that much of the PV power has been lost in the form of blow-by at piston seals due to large and non-optimum clearance seal gap between piston and cylinder. The results of experimental parameters simulated using Sage provide the optimum seal gap value for maximizing the delivered PV power.

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The knowledge of adsorption characteristics of activated carbon (porous material) in the temperature range from 5 to 20 K is essential when used in cryosorption pumps for nuclear fusion applications. However, such experimental data are very scarce in the literature, especially below 77 K. So, an experimental system is designed and fabricated to measure the adsorption characteristics of porous materials under variable cryogenic temperatures (from 5 K to 100 K). This is based on the commercially available micropore-analyser coupled to a closed helium cycle two-stage Gifford McMahon (GM) Cryocooler, which allows the sample to be cooled to 4.2 K. The sample port is coupled to the Cryocooler through a heat switch, which isolates this port from the cold head of the Cryocooler. By this, the sample temperature can now be varied without affecting the Cryocooler. The setup enables adsorption studies in the pressure range from atmospheric down to 10(-4) Pa. The paper describes the details of the experimental setup and presents the results of adsorption studies at 77 K for activated carbon with nitrogen as adsorbate. The system integration is now completed to enable adsorption studies at 4.2 K.

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Single and two-stage Pulse Tube Cryocoolers (PTC) have been designed, fabricated and experimentally studied. The single stage PTC reaches a no-load temperature of similar to 29 K at its cold end, the two-stage PTC reaches similar to 2.9 K in its second stage cold end and similar to 60 K in its first stage cold end. The two-stage Pulse Tube Cryocooler provides a cooling power of similar to 250 mW at 4.2 K. The single stage system uses stainless steel meshes along with Pb granules as its regenerator materials, while the two-stage PTC uses combinations of Pb along with Er3Ni/HoCu2 as the second stage regenerator materials. Normally, the above systems are insulated by thermal radiation shields and mounted inside a vacuum chamber which is maintained at high vacuum. To evaluate the performance of these systems in the possible conditions of loss of vacuum with and without radiation shields, experimental studies have been performed. The heat-in-leak under such severe conditions has been estimated from the heat load characteristics of the respective stages. The experimental results are analyzed to obtain surface emissivities and effective thermal conductivities as a function of interspace pressure.

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1. The relationship between species richness and ecosystem function, as measured by productivity or biomass, is of long-standing theoretical and practical interest in ecology. This is especially true for forests, which represent a majority of global biomass, productivity and biodiversity. 2. Here, we conduct an analysis of relationships between tree species richness, biomass and productivity in 25 forest plots of area 8-50ha from across the world. The data were collected using standardized protocols, obviating the need to correct for methodological differences that plague many studies on this topic. 3. We found that at very small spatial grains (0.04ha) species richness was generally positively related to productivity and biomass within plots, with a doubling of species richness corresponding to an average 48% increase in productivity and 53% increase in biomass. At larger spatial grains (0.25ha, 1ha), results were mixed, with negative relationships becoming more common. The results were qualitatively similar but much weaker when we controlled for stem density: at the 0.04ha spatial grain, a doubling of species richness corresponded to a 5% increase in productivity and 7% increase in biomass. Productivity and biomass were themselves almost always positively related at all spatial grains. 4. Synthesis. This is the first cross-site study of the effect of tree species richness on forest biomass and productivity that systematically varies spatial grain within a controlled methodology. The scale-dependent results are consistent with theoretical models in which sampling effects and niche complementarity dominate at small scales, while environmental gradients drive patterns at large scales. Our study shows that the relationship of tree species richness with biomass and productivity changes qualitatively when moving from scales typical of forest surveys (0.04ha) to slightly larger scales (0.25 and 1ha). This needs to be recognized in forest conservation policy and management.

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Cryptococcus neoformans is a pathogenic basidiomycetous yeast responsible for more than 600,000 deaths each year. It occurs as two serotypes (A and D) representing two varieties (i.e. grubii and neoformans, respectively). Here, we sequenced the genome and performed an RNA-Seq-based analysis of the C. neoformans var. grubii transcriptome structure. We determined the chromosomal locations, analyzed the sequence/structural features of the centromeres, and identified origins of replication. The genome was annotated based on automated and manual curation. More than 40,000 introns populating more than 99% of the expressed genes were identified. Although most of these introns are located in the coding DNA sequences (CDS), over 2,000 introns in the untranslated regions (UTRs) were also identified. Poly(A)-containing reads were employed to locate the polyadenylation sites of more than 80% of the genes. Examination of the sequences around these sites revealed a new poly(A)-site-associated motif (AUGHAH). In addition, 1,197 miscRNAs were identified. These miscRNAs can be spliced and/or polyadenylated, but do not appear to have obvious coding capacities. Finally, this genome sequence enabled a comparative analysis of strain H99 variants obtained after laboratory passage. The spectrum of mutations identified provides insights into the genetics underlying the micro-evolution of a laboratory strain, and identifies mutations involved in stress responses, mating efficiency, and virulence.

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Advances in forest carbon mapping have the potential to greatly reduce uncertainties in the global carbon budget and to facilitate effective emissions mitigation strategies such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation). Though broad-scale mapping is based primarily on remote sensing data, the accuracy of resulting forest carbon stock estimates depends critically on the quality of field measurements and calibration procedures. The mismatch in spatial scales between field inventory plots and larger pixels of current and planned remote sensing products for forest biomass mapping is of particular concern, as it has the potential to introduce errors, especially if forest biomass shows strong local spatial variation. Here, we used 30 large (8-50 ha) globally distributed permanent forest plots to quantify the spatial variability in aboveground biomass density (AGBD in Mgha(-1)) at spatial scales ranging from 5 to 250m (0.025-6.25 ha), and to evaluate the implications of this variability for calibrating remote sensing products using simulated remote sensing footprints. We found that local spatial variability in AGBD is large for standard plot sizes, averaging 46.3% for replicate 0.1 ha subplots within a single large plot, and 16.6% for 1 ha subplots. AGBD showed weak spatial autocorrelation at distances of 20-400 m, with autocorrelation higher in sites with higher topographic variability and statistically significant in half of the sites. We further show that when field calibration plots are smaller than the remote sensing pixels, the high local spatial variability in AGBD leads to a substantial ``dilution'' bias in calibration parameters, a bias that cannot be removed with standard statistical methods. Our results suggest that topography should be explicitly accounted for in future sampling strategies and that much care must be taken in designing calibration schemes if remote sensing of forest carbon is to achieve its promise.