886 resultados para Design and Analysis of Compute Experiment (DACE)


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The formulation of a new process-based crop model, the general large-area model (GLAM) for annual crops is presented. The model has been designed to operate on spatial scales commensurate with those of global and regional climate models. It aims to simulate the impact of climate on crop yield. Procedures for model parameter determination and optimisation are described, and demonstrated for the prediction of groundnut (i.e. peanut; Arachis hypogaea L.) yields across India for the period 1966-1989. Optimal parameters (e.g. extinction coefficient, transpiration efficiency, rate of change of harvest index) were stable over space and time, provided the estimate of the yield technology trend was based on the full 24-year period. The model has two location-specific parameters, the planting date, and the yield gap parameter. The latter varies spatially and is determined by calibration. The optimal value varies slightly when different input data are used. The model was tested using a historical data set on a 2.5degrees x 2.5degrees grid to simulate yields. Three sites are examined in detail-grid cells from Gujarat in the west, Andhra Pradesh towards the south, and Uttar Pradesh in the north. Agreement between observed and modelled yield was variable, with correlation coefficients of 0.74, 0.42 and 0, respectively. Skill was highest where the climate signal was greatest, and correlations were comparable to or greater than correlations with seasonal mean rainfall. Yields from all 35 cells were aggregated to simulate all-India yield. The correlation coefficient between observed and simulated yields was 0.76, and the root mean square error was 8.4% of the mean yield. The model can be easily extended to any annual crop for the investigation of the impacts of climate variability (or change) on crop yield over large areas. (C) 2004 Elsevier B.V. All rights reserved.

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The aim of phase II single-arm clinical trials of a new drug is to determine whether it has sufficient promising activity to warrant its further development. For the last several years Bayesian statistical methods have been proposed and used. Bayesian approaches are ideal for earlier phase trials as they take into account information that accrues during a trial. Predictive probabilities are then updated and so become more accurate as the trial progresses. Suitable priors can act as pseudo samples, which make small sample clinical trials more informative. Thus patients have better chances to receive better treatments. The goal of this paper is to provide a tutorial for statisticians who use Bayesian methods for the first time or investigators who have some statistical background. In addition, real data from three clinical trials are presented as examples to illustrate how to conduct a Bayesian approach for phase II single-arm clinical trials with binary outcomes.

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We have developed a new simple method for transport, storage, and analysis of genetic material from the corals Agaricia agaricites, Dendrogyra cylindrica, Eusmilia ancora, Meandrina meandrites, Montastrea annularis, Porites astreoides, Porites furcata, Porites porites, and Siderastrea siderea at room temperature. All species yielded sufficient DNA from a single FTA(R) card (19 mug-43 ng) for subsequent PCR amplification of both coral and zooxanthellar DNA. The D1 and D2 variable region of the large Subunit rRNA gene (LSUrDNA) was amplified from the DNA of P. furcata and S. siderea by PCR. Electrophoresis yielded two major DNA bands: an 800-base pair (bp) DNA, which represented the coral ribosomal RNA (rRNA) gene, and a 600-bp DNA, which represented the zooxanthellar srRNA gene. Extraction of DNA from the bands yielded between 290 mug total DNA (S. siderea coral DNA) and 9 mug total DNA (P. furcata zooxanthellar DNA). The ability to transport and store genetic material from scleractinian corals without resort to laboratory facilities in the field allows for the molecular Study of a far wider range and variety of coral sites than have been studied to date. (C) 2003 Elsevier Science B.V. All rights reserved.

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Population subdivision complicates analysis of molecular variation. Even if neutrality is assumed, three evolutionary forces need to be considered: migration, mutation, and drift. Simplification can be achieved by assuming that the process of migration among and drift within subpopulations is occurring fast compared to Mutation and drift in the entire population. This allows a two-step approach in the analysis: (i) analysis of population subdivision and (ii) analysis of molecular variation in the migrant pool. We model population subdivision using an infinite island model, where we allow the migration/drift parameter Theta to vary among populations. Thus, central and peripheral populations can be differentiated. For inference of Theta, we use a coalescence approach, implemented via a Markov chain Monte Carlo (MCMC) integration method that allows estimation of allele frequencies in the migrant pool. The second step of this approach (analysis of molecular variation in the migrant pool) uses the estimated allele frequencies in the migrant pool for the study of molecular variation. We apply this method to a Drosophila ananassae sequence data set. We find little indication of isolation by distance, but large differences in the migration parameter among populations. The population as a whole seems to be expanding. A population from Bogor (Java, Indonesia) shows the highest variation and seems closest to the species center.

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This paper develops a novel method of actuation for robotic hands. The solution employs Bowden cable routed to each joint as the means by which the finger is actuated. The use of Bowden cable is shown to be feasible for this purpose, even with the changing frictional forces associated with it's use. This method greatly simplifies the control of the hand by removing the coupling between joints, and allows for direct and accurate translation between the joints and the motors driving the Bowden wires. The design also allows for two degrees of freedom (with the same centre of rotation) to be realised in the largest knuckle of each finger, meaning biological finger kinematics are more accurately emulated.

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This paper presents the Gentle/G integrated system for reach & grasp therapy retraining following brain injury. The design, control and integration of an experimental grasp assistance unit is described for use in robot assisted stroke rehabilitation. The grasp assist unit is intended to work with the hardware and software of the Gentle/S robot although the hardware could be adapted to other rehabilitation applications. When used with the Gentle/S robot a total of 6 active and 3 passive degrees of freedom are available to provide active, active assist or passive grasp retraining in combination with reaching movements in a reach-grasp-transfer-release sequence.