931 resultados para Two-Level Optimization


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Potatoes of a number of varieties of contrasting levels of resistance were planted in pure or mixed stands in four experiments over 3 years. Three experiments compared the late blight severity and progress in mixtures with that in pure stands. Disease on susceptible or moderately resistant varieties typical of those in commercial use was similar in mixtures and pure stands. In 2 of 3 years, there were slight reductions on cv. Sante, which is moderately susceptible, in mixture with cv. Cara, which is moderately resistant. Cara was unaffected by this mixture. Mixtures of an immune or near-immune partner with Cara or Sante substantially reduced disease on the latter. The effect of the size of plots of individual varieties or mixtures on blight severity was compared in two experiments. Larger plots had a greater area under the disease progress curve, but the average rate of disease progress was greater in smaller plots; this may be because most disease progress took place later, under more favourable conditions, in the smaller plots. In one experiment, two planting densities were used. Density had no effect on disease and did not interact with mixture effects. The overall conclusion is that, while mixtures of potato varieties may be desirable for other reasons, they do not offer any improvement on the average of the disease resistance of the components.

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It is generally acknowledged that population-level assessments provide,I better measure of response to toxicants than assessments of individual-level effects. population-level assessments generally require the use of models to integrate potentially complex data about the effects of toxicants on life-history traits, and to provide a relevant measure of ecological impact. Building on excellent earlier reviews we here briefly outline the modelling options in population-level risk assessment. Modelling is used to calculate population endpoints from available data, which is often about Individual life histories, the ways that individuals interact with each other, the environment and other species, and the ways individuals are affected by pesticides. As population endpoints, we recommend the use of population abundance, population growth rate, and the chance of population persistence. We recommend two types of model: simple life-history models distinguishing two life-history stages, juveniles and adults; and spatially-explicit individual-based landscape models. Life-history models are very quick to set up and run, and they provide a great deal or insight. At the other extreme, individual-based landscape models provide the greatest verisimilitude, albeit at the cost of greatly increased complexity. We conclude with a discussion of the cations of the severe problems of parameterising models.

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Objectives: To assess the potential source of variation that surgeon may add to patient outcome in a clinical trial of surgical procedures. Methods: Two large (n = 1380) parallel multicentre randomized surgical trials were undertaken to compare laparoscopically assisted hysterectomy with conventional methods of abdominal and vaginal hysterectomy; involving 43 surgeons. The primary end point of the trial was the occurrence of at least one major complication. Patients were nested within surgeons giving the data set a hierarchical structure. A total of 10% of patients had at least one major complication, that is, a sparse binary outcome variable. A linear mixed logistic regression model (with logit link function) was used to model the probability of a major complication, with surgeon fitted as a random effect. Models were fitted using the method of maximum likelihood in SAS((R)). Results: There were many convergence problems. These were resolved using a variety of approaches including; treating all effects as fixed for the initial model building; modelling the variance of a parameter on a logarithmic scale and centring of continuous covariates. The initial model building process indicated no significant 'type of operation' across surgeon interaction effect in either trial, the 'type of operation' term was highly significant in the abdominal trial, and the 'surgeon' term was not significant in either trial. Conclusions: The analysis did not find a surgeon effect but it is difficult to conclude that there was not a difference between surgeons. The statistical test may have lacked sufficient power, the variance estimates were small with large standard errors, indicating that the precision of the variance estimates may be questionable.

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A RAPD-PCR assay was developed and used to test For competitive variability in growth of the nematode biological control fungus Pochonia chlamydosporia. Saprophytic competence in soil with or without tomato plants was examined in three isolates of the fungus: RES 280 (J), originally isolated from potato cyst nematode (PCN) cysts; RES 200 (1) and RES 279 (S), both originally isolated from root knot nematode (RKN) eggs. Viable counts taken at 70 d indicated that I was the best saprophyte followed by S, with J the poorest. RAPD-PCR analysis of colonies from mixed treatments revealed that there was a cumulative effect of adding isolates to the system. This Suggested that the isolates did not interact and that they may occupy separate niches in soil and the rhizosphere. To investigate parasitic ability, soils were seeded with two isolates of the fungus: J and S, singly or in combination. Tomato or potato plants were grown in these soils; free of nematodes, or inoculated with PCN or RKN, and incubated for 77 d. The abundance of the PCN isolate J in PCN cysts was significantly greater than that of the RKN isolate S but in RKN egg masses, S was significantly more abundant than J. RAPD-PCR analysis of colonies from mixed treatments confirmed that J was more abundant than S ill PCN cysts whereas the converse was observed on RKN egg masses. This substantiates the phenomenon of nematode host preference at the infraspecific level of P. chlamydosporia and highlights its relevance for biological control of plant parasitic nematodes.

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The influence, was investigated, of abiotic parameters on the isolation of protoplasts from in vitro seedling cotyledons of white lupin. The protoplasts were found to be competent in withstanding a wide range of osmotic potentials of the enzyme medium, however, −2.25 MPa (0.5 M mannitol), resulted in the highest yield of protoplasts. The pH of the isolation medium also had a profound effect on protoplast production. Vacuum infiltration of the enzyme solution into the cotyledon tissue resulted in a progressive drop in the yield of protoplasts. The speed and duration of orbital agitation of the cotyledon tissue played a significant role in the release of protoplasts and a two step (stationary-gyratory) regime was found to be better than the gyratory-only system.

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The vinylogous aldol reaction between appropriate aldehydes and furan-based silyloxy diene synthon generated from 3-benzyl-5H-furan-2-one (3) afforded two truncated lactone analogues [compounds (4) and (5)] of nostoclides (2). The compounds were fully characterized by IR, NMR (H-1 and C-13), 2D NMR spectroscopy experiments (HMBC, HSQC and NOESY), MS spectrometry and X-ray crystallography. Compounds (4) and (5) crystallized in the space group P2(1)2(1)2(1) and P2(1)/c, respectively. Although expected correlations between hydrogen atoms in spatial close proximity were not observed for compound (5) using NMR, the stereochemistry of the exocyclic double bond of both (4) and (5) was unambiguously determined to be Z and E, respectively, using X-ray crystallography. The packing of both compounds within the crystal are stabilized by non-classical inter-molecular hydrogen bonds. DFT calculations (B3LYP/6-31+G* level) confirmed that the crystal structures possessed the lowest energies in the gas phase when compared to their geometric isomers. (c) 2006 Elsevier B.V. All rights reserved.

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Recent research along the coastal cliffs and embayments of Jersey has revealed new aspects of the geomorphology of the rocky shore platform and its relationship with the steep slopes that link it to the island plateau above. Specifically, a rockhead platform meets a 10-30 m high, near vertical cliff at approximately 8-10 m above Jersey Datum (J.D.= ±0 m Ordnance Datum; likewise Guernsey Datum: G.D.), slopes down-towards mid-tide levels becoming ever more deeply dissected. Generalised contours of this platform show it to be distinct from a lower tidal rockhead platform which is comparatively smooth over large areas as it undergoes continuing contemporary abrasion. This lower platform is generally separated from the higher one by low cliffs, less than a metre high at mid-tidal levels, but two to three metres at the base of the backing cliffs. Both of these platforms are shown to antedate the Last Cold Stage (Devensian) head at a number of localities and this relationship is taken to represent the general situation, not only in Jersey, but throughout the other Channel Islands and adjacent coasts of Armorica. Whether either, or both, of these two platforms are older than Marine Oxygen Isotope Substage (MOIS) 5e (Ipswichian) as well is not known. However the considerable age of the numerous and wide intertidal shore platforms of the Channel Islands and adjacent coasts of Amorica makes a greater age quite possible.

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Objective: To determine whether the use of verbal descriptors suggested by the European Union (EU) such as "common" (1-10% frequency) and "rare" (0.01-0.1%) effectively conveys the level of risk of side effects to people taking a medicine. Design: Randomised controlled study with unconcealed allocation. Participants: 120 adults taking simvastatin or atorvastatin after cardiac surgery or myocardial infarction. Setting: Cardiac rehabilitation clinics at two hospitals in Leeds, UK. Intervention: A written statement about one of the side effects of the medicine (either constipation or pancreatitis). Within each side effect condition half the patients were given the information in verbal form and half in numerical form (for constipation, "common" or 2.5%; for pancreatitis, "rare" or 0.04%). Main outcome measure: The estimated likelihood of the side effect occurring. Other outcome measures related to the perceived severity of the side effect, its risk to health, and its effect on decisions about whether to take the medicine. Results: The mean likelihood estimate given for the constipation side effect was 34.2% in the verbal group and 8.1% in the numerical group; for pancreatitis it was 18% in the verbal group and 2.1% in the numerical group. The verbal descriptors were associated with more negative perceptions of the medicine than their equivalent numerical descriptors. Conclusions: Patients want and need understandable information about medicines and their risks and benefits. This is essential if they are to become partners in medicine taking. The use of verbal descriptors to improve the level of information about side effect risk leads to overestimation of the level of harm and may lead patients to make inappropriate decisions about whether or not they take the medicine.

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Whereas several clinical endpoints in monitoring the response to treatment in patients with Huntington's disease (HD) have been explored, there has been a paucity of research in the quality of life in such patients. The aim of this study was to validate the use of two generic health-related quality of life instruments (the Short Form 36 health survey questionnaire [SF-36] and the Sickness Impact Profile [SIP]) and to evaluate their psychometric properties. We found that both instruments demonstrated acceptable convergent validity and reliability for patients and carers. However, there was an advantage in using the SF-36 because of its more robust construct validity and test-retest reliability; furthermore, motor symptoms appeared to influence some strictly nonmotor dimensions of the SIP. On a pragmatic level, the SF-36 is shorter and quicker to administer and, therefore, easier for patients at various stages of the disease to complete. Thus, the SF-36 would appear to be the recommended instrument of choice for patients with HD and their carers, although further work needs to be done to investigate the sensitivity of this instrument longitudinally. (C) 2004 Movement Disorder Society.

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This paper deals with the design of optimal multiple gravity assist trajectories with deep space manoeuvres. A pruning method which considers the sequential nature of the problem is presented. The method locates feasible vectors using local optimization and applies a clustering algorithm to find reduced bounding boxes which can be used in a subsequent optimization step. Since multiple local minima remain within the pruned search space, the use of a global optimization method, such as Differential Evolution, is suggested for finding solutions which are likely to be close to the global optimum. Two case studies are presented.

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We propose a unified data modeling approach that is equally applicable to supervised regression and classification applications, as well as to unsupervised probability density function estimation. A particle swarm optimization (PSO) aided orthogonal forward regression (OFR) algorithm based on leave-one-out (LOO) criteria is developed to construct parsimonious radial basis function (RBF) networks with tunable nodes. Each stage of the construction process determines the center vector and diagonal covariance matrix of one RBF node by minimizing the LOO statistics. For regression applications, the LOO criterion is chosen to be the LOO mean square error, while the LOO misclassification rate is adopted in two-class classification applications. By adopting the Parzen window estimate as the desired response, the unsupervised density estimation problem is transformed into a constrained regression problem. This PSO aided OFR algorithm for tunable-node RBF networks is capable of constructing very parsimonious RBF models that generalize well, and our analysis and experimental results demonstrate that the algorithm is computationally even simpler than the efficient regularization assisted orthogonal least square algorithm based on LOO criteria for selecting fixed-node RBF models. Another significant advantage of the proposed learning procedure is that it does not have learning hyperparameters that have to be tuned using costly cross validation. The effectiveness of the proposed PSO aided OFR construction procedure is illustrated using several examples taken from regression and classification, as well as density estimation applications.

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The level set method is commonly used to address image noise removal. Existing studies concentrate mainly on determining the speed function of the evolution equation. Based on the idea of a Canny operator, this letter introduces a new method of controlling the level set evolution, in which the edge strength is taken into account in choosing curvature flows for the speed function and the normal to edge direction is used to orient the diffusion of the moving interface. The addition of an energy term to penalize the irregularity allows for better preservation of local edge information. In contrast with previous Canny-based level set methods that usually adopt a two-stage framework, the proposed algorithm can execute all the above operations in one process during noise removal.

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The combination of the synthetic minority oversampling technique (SMOTE) and the radial basis function (RBF) classifier is proposed to deal with classification for imbalanced two-class data. In order to enhance the significance of the small and specific region belonging to the positive class in the decision region, the SMOTE is applied to generate synthetic instances for the positive class to balance the training data set. Based on the over-sampled training data, the RBF classifier is constructed by applying the orthogonal forward selection procedure, in which the classifier structure and the parameters of RBF kernels are determined using a particle swarm optimization algorithm based on the criterion of minimizing the leave-one-out misclassification rate. The experimental results on both simulated and real imbalanced data sets are presented to demonstrate the effectiveness of our proposed algorithm.

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In this contribution we aim at anchoring Agent-Based Modeling (ABM) simulations in actual models of human psychology. More specifically, we apply unidirectional ABM to social psychological models using low level agents (i.e., intra-individual) to examine whether they generate better predictions, in comparison to standard statistical approaches, concerning the intentions of performing a behavior and the behavior. Moreover, this contribution tests to what extent the predictive validity of models of attitude such as the Theory of Planned Behavior (TPB) or Model of Goal-directed Behavior (MGB) depends on the assumption that peoples’ decisions and actions are purely rational. Simulations were therefore run by considering different deviations from rationality of the agents with a trembling hand method. Two data sets concerning respectively the consumption of soft drinks and physical activity were used. Three key findings emerged from the simulations. First, compared to standard statistical approach the agent-based simulation generally improves the prediction of behavior from intention. Second, the improvement in prediction is inversely proportional to the complexity of the underlying theoretical model. Finally, the introduction of varying degrees of deviation from rationality in agents’ behavior can lead to an improvement in the goodness of fit of the simulations. By demonstrating the potential of ABM as a complementary perspective to evaluating social psychological models, this contribution underlines the necessity of better defining agents in terms of psychological processes before examining higher levels such as the interactions between individuals.

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A poplar short rotation coppice (SRC) grown for the production of bioenergy can combine carbon (C) storage with fossil fuel substitution. Here, we summarize the responses of a poplar (Populus) plantation to 6 yr of free air CO2 enrichment (POP/EUROFACE consisting of two rotation cycles). We show that a poplar plantation growing in nonlimiting light, nutrient and water conditions will significantly increase its productivity in elevated CO2 concentrations ([CO2]). Increased biomass yield resulted from an early growth enhancement and photosynthesis did not acclimate to elevated [CO2]. Sufficient nutrient availability, increased nitrogen use efficiency (NUE) and the large sink capacity of poplars contributed to the sustained increase in C uptake over 6 yr. Additional C taken up in high [CO2] was mainly invested into woody biomass pools. Coppicing increased yield by 66% and partly shifted the extra C uptake in elevated [CO2] to above-ground pools, as fine root biomass declined and its [CO2] stimulation disappeared. Mineral soil C increased equally in ambient and elevated [CO2] during the 6 yr experiment. However, elevated [CO2] increased the stabilization of C in the mineral soil. Increased productivity of a poplar SRC in elevated [CO2] may allow shorter rotation cycles, enhancing the viability of SRC for biofuel production.