93 resultados para Alternative Formulations
Resumo:
Pseudomonas syringae pv. phaseolicola causes halo blight of the common bean, Phaseolus vulgaris, worldwide and remains difficult to control. Races of the pathogen cause either disease symptoms or a resistant hypersensitive response on a series of differentially reacting bean cultivars. The molecular genetics of the interaction between P. syringae pv. phaseolicola and bean, and the evolution of bacterial virulence, have been investigated in depth and this research has led to important discoveries in the field of plant-microbe interactions. In this review, we discuss several of the areas of study that chart the rise of P. syringae pv. phaseolicola from a common pathogen of bean plants to a molecular plant-pathogen supermodel bacterium. Taxonomy: Bacteria; Proteobacteria, gamma subdivision; order Pseudomonadales; family Pseudomonadaceae; genus Pseudomonas; species Pseudomonas syringae; Genomospecies 2; pathogenic variety phaseolicola. Microbiological properties: Gram-negative, aerobic, motile, rod-shaped, 1.5 µm long, 0.7-1.2 µm in diameter, at least one polar flagellum, optimal temperatures for growth of 25-30 °C, oxidase negative, arginine dihydrolase negative, levan positive and elicits the hypersensitive response on tobacco. Host range: Major bacterial disease of common bean (Phaseolus vulgaris) in temperate regions and above medium altitudes in the tropics. Natural infections have been recorded on several other legume species, including all members of the tribe Phaseoleae with the exception of Desmodium spp. and Pisum sativum. Disease symptoms: Water-soaked lesions on leaves, pods, stems or petioles, that quickly develop greenish-yellow haloes on leaves at temperatures of less than 23 °C. Infected seeds may be symptomless, or have wrinkled or buttery-yellow patches on the seed coat. Seedling infection is recognized by general chlorosis, stunting and distortion of growth. Epidemiology: Seed borne and disseminated from exudation by water-splash and wind occurring during rainfall. Bacteria invade through wounds and natural openings (notably stomata). Weedy and cultivated alternative hosts may also harbour the bacterium. Disease control: Some measure of control is achieved with copper formulations and streptomycin. Pathogen-free seed and resistant cultivars are recommended. Useful websites: Pseudomonas-plant interaction http://www.pseudomonas-syringae.org/; PseudoDB http://xbase.bham.ac.uk/pseudodb/; Plant Associated and Environmental Microbes Database (PAMDB) http://genome.ppws.vt.edu/cgi-bin/MLST/home.pl; PseudoMLSA Database http://www.uib.es/microbiologiaBD/Welcome.html.
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We prove the equivalence of three weak formulations of the steady water waves equations, namely: the velocity formulation, the stream function formulation and the Dubreil-Jacotin formulation, under weak Hölder regularity assumptions on their solutions.
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Proposals have been made for a common currency for East Asia, but the countries preparing to participate need to be in a state of economic convergence. We show that at least six countries of East Asia already satisfy this condition. There also needs to be a mechanism by which the new currency relates to other reserve currencies. We demonstrate that a numéraire could be defined solely from the actual worldwide consumption of food and energy per capita, linked to fiat currencies via world market prices. We show that real resource prices are stable in real terms, and likely to remain so. Furthermore, the link from energy prices to food commodity prices is permanent, arising from energy inputs in agriculture, food processing and distribu-tion. Calibration of currency value using a yardstick such as our SI numéraire offers an unbiased measure of the con-sistently stable cost of subsistence in the face of volatile currency exchange rates. This has the advantage that the par-ticipating countries need only agree to currency governance based on a common standards institution, a much less on-erous form of agreement than would be required in the creation of a common central bank.
Resumo:
This invention relates to solid formulations for the oral delivery of live microbial cells which comprise dried viable cells and small amounts of a bile acid binding agent, for example, an anion exchange resin such as cholestyramine. The presence of bile acid binding agents in the formulation significantly increases the survival of the cells in the intestinal tract and facilitates delivery of the viable cells to the intestine.
Resumo:
[1] Remotely sensed, multiannual data sets of shortwave radiative surface fluxes are now available for assimilation into land surface schemes (LSSs) of climate and/or numerical weather prediction models. The RAMI4PILPS suite of virtual experiments assesses the accuracy and consistency of the radiative transfer formulations that provide the magnitudes of absorbed, reflected, and transmitted shortwave radiative fluxes in LSSs. RAMI4PILPS evaluates models under perfectly controlled experimental conditions in order to eliminate uncertainties arising from an incomplete or erroneous knowledge of the structural, spectral and illumination related canopy characteristics typical for model comparison with in situ observations. More specifically, the shortwave radiation is separated into a visible and near-infrared spectral region, and the quality of the simulated radiative fluxes is evaluated by direct comparison with a 3-D Monte Carlo reference model identified during the third phase of the Radiation transfer Model Intercomparison (RAMI) exercise. The RAMI4PILPS setup thus allows to focus in particular on the numerical accuracy of shortwave radiative transfer formulations and to pinpoint to areas where future model improvements should concentrate. The impact of increasing degrees of structural and spectral subgrid variability on the simulated fluxes is documented and the relevance of any thus emerging biases with respect to gross primary production estimates and shortwave radiative forcings due to snow and fire events are investigated.
Resumo:
This dissertation deals with aspects of sequential data assimilation (in particular ensemble Kalman filtering) and numerical weather forecasting. In the first part, the recently formulated Ensemble Kalman-Bucy (EnKBF) filter is revisited. It is shown that the previously used numerical integration scheme fails when the magnitude of the background error covariance grows beyond that of the observational error covariance in the forecast window. Therefore, we present a suitable integration scheme that handles the stiffening of the differential equations involved and doesn’t represent further computational expense. Moreover, a transform-based alternative to the EnKBF is developed: under this scheme, the operations are performed in the ensemble space instead of in the state space. Advantages of this formulation are explained. For the first time, the EnKBF is implemented in an atmospheric model. The second part of this work deals with ensemble clustering, a phenomenon that arises when performing data assimilation using of deterministic ensemble square root filters in highly nonlinear forecast models. Namely, an M-member ensemble detaches into an outlier and a cluster of M-1 members. Previous works may suggest that this issue represents a failure of EnSRFs; this work dispels that notion. It is shown that ensemble clustering can be reverted also due to nonlinear processes, in particular the alternation between nonlinear expansion and compression of the ensemble for different regions of the attractor. Some EnSRFs that use random rotations have been developed to overcome this issue; these formulations are analyzed and their advantages and disadvantages with respect to common EnSRFs are discussed. The third and last part contains the implementation of the Robert-Asselin-Williams (RAW) filter in an atmospheric model. The RAW filter is an improvement to the widely popular Robert-Asselin filter that successfully suppresses spurious computational waves while avoiding any distortion in the mean value of the function. Using statistical significance tests both at the local and field level, it is shown that the climatology of the SPEEDY model is not modified by the changed time stepping scheme; hence, no retuning of the parameterizations is required. It is found the accuracy of the medium-term forecasts is increased by using the RAW filter.
Resumo:
Lorenz’s theory of available p otential energy (APE) remains the main framework for studying the atmospheric and oceanic energy cycles. Because the APE generation rate is the volume integral of a thermodynamic efficiency times the local diabatic heating/cooling rate, APE theory is often regarded as an extension of the theory of heat engines. Available energetics in classical thermodynamics, however, usually relies on the concept of exergy, and is usually measured relative to a reference state maximising entropy at constant energy, whereas APE’s reference state minimises p otential energy at constant entropy. This review seeks to shed light on the two concepts; it covers local formulations of available energetics, alternative views of the dynamics/thermodynamics coupling, APE theory and the second law, APE production/dissipation, extensions to binary fluids, mean/eddy decomp ositions, APE in incompressible fluids, APE and irreversible turbulent mixing, and the role of mechanical forcing on APE production.
Resumo:
Ensemble learning techniques generate multiple classifiers, so called base classifiers, whose combined classification results are used in order to increase the overall classification accuracy. In most ensemble classifiers the base classifiers are based on the Top Down Induction of Decision Trees (TDIDT) approach. However, an alternative approach for the induction of rule based classifiers is the Prism family of algorithms. Prism algorithms produce modular classification rules that do not necessarily fit into a decision tree structure. Prism classification rulesets achieve a comparable and sometimes higher classification accuracy compared with decision tree classifiers, if the data is noisy and large. Yet Prism still suffers from overfitting on noisy and large datasets. In practice ensemble techniques tend to reduce the overfitting, however there exists no ensemble learner for modular classification rule inducers such as the Prism family of algorithms. This article describes the first development of an ensemble learner based on the Prism family of algorithms in order to enhance Prism’s classification accuracy by reducing overfitting.