953 resultados para ARRAY-BASED TECHNOLOGY
Resumo:
The geospace environment is controlled largely by events on the Sun, such as solar flares and coronal mass ejections, which generate significant geomagnetic and upper atmospheric disturbances. The study of this Sun-Earth system, which has become known as space weather, has both intrinsic scientific interest and practical applications. Adverse conditions in space can damage satellites and disrupt communications, navigation, and electric power grids, as well as endanger astronauts. The Center for Integrated Space Weather Modeling (CISM), a Science and Technology Center (STC) funded by the U.S. National Science Foundation (see http://www.bu.edu/cism/), is developing a suite of integrated physics-based computer models that describe the space environment from the Sun to the Earth for use in both research and operations [Hughes and Hudson, 2004, p. 1241]. To further this mission, advanced education and training programs sponsored by CISM encourage students to view space weather as a system that encompasses the Sun, the solar wind, the magnetosphere, and the ionosphere/thermosphere. This holds especially true for participants in the CISM space weather summer school [Simpson, 2004].
Resumo:
We advocate the use of systolic design techniques to create custom hardware for Custom Computing Machines. We have developed a hardware genetic algorithm based on systolic arrays to illustrate the feasibility of the approach. The architecture is independent of the lengths of chromosomes used and can be scaled in size to accommodate different population sizes. An FPGA prototype design can process 16 million genes per second.
Resumo:
Substituting grass silage with maize silage in forage mixtures may result in one forage influencing the nutritive value of another in terms of whole tract nutrient digestibility and N utilisation. This experiment investigated effects of four forage combinations being, grass silage (G); 67 g/100 g grass silage + 33 g/100 g maize silage (GGM); 67 g/100 g maize silage + 33 g/100 g grass silage (MMG); maize silage (M). All diets were formulated to be isonitrogenous (22.4 g N/kg dry matter [DM]) using a concentrate mixture. Ration digestibility and N balance was determined using 7 Holstein Friesian steers (mean body weight 411.0 +/- 120.9 kg) in a cross-over design. Inclusion of maize silage in the diet had a positive linear effect on forage and total DM intake (P = 0.001), and on apparent DM and organic matter digestibility (both P = 0.048). Regardless of the silage ratio used, the metabolisable energy concentration of maize silage was calculated to be higher than that of grass silage (P = 0.058), and linearly related to the relative proportions of the two silages in the forage mixture. Inclusion of maize silage in the diet resulted in a linear decline in the apparent digestibility of starch (P = 0.022), neutral detergent fibre (P < 0.001) and acid detergent fibre (P = 0.003). Nitrogen retention, expressed as amount retained per day or in terms of body weight (g/100 kg) increased linearly with maize inclusion (P = 0.047 and 0.046, respectively). Replacing grass silage with maize silage caused linear responses according to the proportions of each forage in the diet, and that there were no associative effects of combining forages. (C) 2004 Elsevier B.V. All rights reserved.
Resumo:
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.
Resumo:
Grass-based diets are of increasing social-economic importance in dairy cattle farming, but their low supply of glucogenic nutrients may limit the production of milk. Current evaluation systems that assess the energy supply and requirements are based on metabolisable energy (ME) or net energy (NE). These systems do not consider the characteristics of the energy delivering nutrients. In contrast, mechanistic models take into account the site of digestion, the type of nutrient absorbed and the type of nutrient required for production of milk constituents, and may therefore give a better prediction of supply and requirement of nutrients. The objective of the present study is to compare the ability of three energy evaluation systems, viz. the Dutch NE system, the agricultural and food research council (AFRC) ME system, and the feed into milk (FIM) ME system, and of a mechanistic model based on Dijkstra et al. [Simulation of digestion in cattle fed sugar cane: prediction of nutrient supply for milk production with locally available supplements. J. Agric. Sci., Cambridge 127, 247-60] and Mills et al. [A mechanistic model of whole-tract digestion and methanogenesis in the lactating dairy cow: model development, evaluation and application. J. Anim. Sci. 79, 1584-97] to predict the feed value of grass-based diets for milk production. The dataset for evaluation consists of 41 treatments of grass-based diets (at least 0.75 g ryegrass/g diet on DM basis). For each model, the predicted energy or nutrient supply, based on observed intake, was compared with predicted requirement based on observed performance. Assessment of the error of energy or nutrient supply relative to requirement is made by calculation of mean square prediction error (MSPE) and by concordance correlation coefficient (CCC). All energy evaluation systems predicted energy requirement to be lower (6-11%) than energy supply. The root MSPE (expressed as a proportion of the supply) was lowest for the mechanistic model (0.061), followed by the Dutch NE system (0.082), FIM ME system (0.097) and AFRCME system(0.118). For the energy evaluation systems, the error due to overall bias of prediction dominated the MSPE, whereas for the mechanistic model, proportionally 0.76 of MSPE was due to random variation. CCC analysis confirmed the higher accuracy and precision of the mechanistic model compared with energy evaluation systems. The error of prediction was positively related to grass protein content for the Dutch NE system, and was also positively related to grass DMI level for all models. In conclusion, current energy evaluation systems overestimate energy supply relative to energy requirement on grass-based diets for dairy cattle. The mechanistic model predicted glucogenic nutrients to limit performance of dairy cattle on grass-based diets, and proved to be more accurate and precise than the energy systems. The mechanistic model could be improved by allowing glucose maintenance and utilization requirements parameters to be variable. (C) 2007 Elsevier B.V. All rights reserved.
Resumo:
This paper considers the various complex changes that occur to nitrogen (N) containing compounds in forages through the processes of ensiling, rumen degradation and microbial synthesis, post-ruminal digestion and absorption and synthesis into milk protein. Particular emphasis is placed on reviewing recent data on the efficiency of utilisation of N-containing compounds in silages by rumen microbes, since low efficiency here is believed to be a major cause of large N losses to the environment on some silage-based diets. Data are reviewed which show that although rumen degradation of N compounds in silage is rapid and extensive, up to 10% of the soluble N can escape the rumen by being associated with the liquid phase. There is now firm evidence that the composition of the amino acids (AAs) absorbed is heavily dependent on the process of ensiling and that witting or use of certain silage additives conserve the initial amino acid profile of the forage. This provides an opportunity to manipulate the amino acid supply to better match demand thus potentially enhancing utilisation. This review confirms that utilisation of the N fractions in grass and legume silages in particular, is poor and the efficiency of microbial protein synthesis (EMPS) is consistently higher on maize silage-based diets. It is concluded that the way in which grass and legume silages in particular are produced and used in the future needs a radical rethink. New research needs to be aimed at enhancing the utilisation of N in the rumen through a better understanding of N/carbohydrate relationships and the ability of forages to supply degraded carbohydrate. Also more emphasis is needed on understanding of the potentially different role of the different N fractions that exist in silages. (C) 2004 Elsevier B.V. All rights reserved.
Resumo:
In recent years there has been a resurgence of interest in the biological roles of carbohydrates and as a result it is now known that carbohydrates are involved in a vast array of disease processes. This review summarises progress in the development of carbohydrate-based therapeutics that involve: inhibition of carbohydrate-lectin interactions; immunisation, using monoclonal antibodies for carbohydrate antigens; inhibition of enzymes that synthesise disease-associated carbohydrates; replacement of carbohydrate-processing enzymes; targeting of drugs to specific disease cells via carbohydrate-lectin interactions; carbohydrate based anti-thrombotic agents.