Asymmetric aziridine synthesis by aza-Darzens reaction of N-diphenylphosphinylimines with chiral enolates. Part 2: inversion of diastereoselectivity

The aza-Darzens ('ADZ') reactions of N-diphenylphosphinyl ('N-Dpp') imines with chiral enolates derived from N-bromoacetyl 2S-2,10-camphorsultam proceed in generally good yield to give N-diphenylphosphinyl aziridinoyl sultams. However, the stereoselectivity of the reaction is dependent upon the structure of the imine substituent: when the chiral enolate was reacted with arylimines substituted in the ortho-position, mixtures of cis- and trans-2'R,3'R-aziridines were obtained, often with a complete selectivity in favour of the trans-isomer. (c) 2006 Elsevier Ltd. All rights reserved.

Determining the effect of asymmetric data on the variogram. I. Underlying asymmetry

Matheron's usual variogram estimator can result in unreliable variograms when data are strongly asymmetric or skewed. Asymmetry in a distribution can arise from a long tail of values in the underlying process or from outliers that belong to another population that contaminate the primary process. This paper examines the effects of underlying asymmetry on the variogram and on the accuracy of prediction, and the second one examines the effects arising from outliers. Standard geostatistical texts suggest ways of dealing with underlying asymmetry; however, this is based on informed intuition rather than detailed investigation. To determine whether the methods generally used to deal with underlying asymmetry are appropriate, the effects of different coefficients of skewness on the shape of the experimental variogram and on the model parameters were investigated. Simulated annealing was used to create normally distributed random fields of different size from variograms with different nugget:sill ratios. These data were then modified to give different degrees of asymmetry and the experimental variogram was computed in each case. The effects of standard data transformations on the form of the variogram were also investigated. Cross-validation was used to assess quantitatively the performance of the different variogram models for kriging. The results showed that the shape of the variogram was affected by the degree of asymmetry, and that the effect increased as the size of data set decreased. Transformations of the data were more effective in reducing the skewness coefficient in the larger sets of data. Cross-validation confirmed that variogram models from transformed data were more suitable for kriging than were those from the raw asymmetric data. The results of this study have implications for the 'standard best practice' in dealing with asymmetry in data for geostatistical analyses. (C) 2007 Elsevier Ltd. All rights reserved.

Determining the effect of asymmetric data on the variogram. II. Outliers

Asymmetry in a distribution can arise from a long tail of values in the underlying process or from outliers that belong to another population that contaminate the primary process. The first paper of this series examined the effects of the former on the variogram and this paper examines the effects of asymmetry arising from outliers. Simulated annealing was used to create normally distributed random fields of different size that are realizations of known processes described by variograms with different nugget:sill ratios. These primary data sets were then contaminated with randomly located and spatially aggregated outliers from a secondary process to produce different degrees of asymmetry. Experimental variograms were computed from these data by Matheron's estimator and by three robust estimators. The effects of standard data transformations on the coefficient of skewness and on the variogram were also investigated. Cross-validation was used to assess the performance of models fitted to experimental variograms computed from a range of data contaminated by outliers for kriging. The results showed that where skewness was caused by outliers the variograms retained their general shape, but showed an increase in the nugget and sill variances and nugget:sill ratios. This effect was only slightly more for the smallest data set than for the two larger data sets and there was little difference between the results for the latter. Overall, the effect of size of data set was small for all analyses. The nugget:sill ratio showed a consistent decrease after transformation to both square roots and logarithms; the decrease was generally larger for the latter, however. Aggregated outliers had different effects on the variogram shape from those that were randomly located, and this also depended on whether they were aggregated near to the edge or the centre of the field. The results of cross-validation showed that the robust estimators and the removal of outliers were the most effective ways of dealing with outliers for variogram estimation and kriging. (C) 2007 Elsevier Ltd. All rights reserved.

MEASUREMENT AND MODELING OF THE TOXICITY OF BINARY MIXTURES IN THE NEMATODE CAENORHABDITIS ELEGANS-A TEST OF INDEPENDENT ACTION

Ecological risk assessments must increasingly consider the effects of chemical mixtures on the environment as anthropogenic pollution continues to grow in complexity. Yet testing every possible mixture combination is impractical and unfeasible; thus, there is an urgent need for models that can accurately predict mixture toxicity from single-compound data. Currently, two models are frequently used to predict mixture toxicity from single-compound data: Concentration addition and independent action (IA). The accuracy of the predictions generated by these models is currently debated and needs to be resolved before their use in risk assessments can be fully justified. The present study addresses this issue by determining whether the IA model adequately described the toxicity of binary mixtures of five pesticides and other environmental contaminants (cadmium, chlorpyrifos, diuron, nickel, and prochloraz) each with dissimilar modes of action on the reproduction of the nematode Caenorhabditis elegans. In three out of 10 cases, the IA model failed to describe mixture toxicity adequately with significant or antagonism being observed. In a further three cases, there was an indication of synergy, antagonism, and effect-level-dependent deviations, respectively, but these were not statistically significant. The extent of the significant deviations that were found varied, but all were such that the predicted percentage effect seen on reproductive output would have been wrong by 18 to 35% (i.e., the effect concentration expected to cause a 50% effect led to an 85% effect). The presence of such a high number and variety of deviations has important implications for the use of existing mixture toxicity models for risk assessments, especially where all or part of the deviation is synergistic.

The synthesis of chiral N-heterocyclic carbene–borane and –diorganoborane complexes and their use in the asymmetric reduction of ketones

Chiral N-heterocyclic carbene–borane complexes have been synthesised, and have been shown to reduce ketones with Lewis acid promotion. Chiral N-heterocyclic carbene–borane and –diorganoborane complexes can reduce ketones with enantioselectivities up to 75% and 85% ee, respectively.

Olfactory attractiveness of mixtures of some host plant and conspecific semiochemicals to the banana weevil Cosmopolites sordidus (Germar, 1824)

A simple "Y" shaped olfactometer was used in laboratory studies on the olfactory attractiveness of mixtures in various proportions of industrial analogues of some host plant and conspecific-based semiochemicals, or their combinations with banana rhizome, to the banana weevil. The aim was to identify factors that influence their attractiveness to the weevil, and consider the possibility for their use as lures for trapping the weevil in the field. Cosmopolites sordidus was attracted to the mixtures at specific concentrations and proportions of constituent chemicals. 6-methylhept-5-en-2-one was only attractive on its own at 1 µl/100 ml and in mixture with 4- mercaptophenol, but not at 10 µl, 0.01 µl, or in combination with banana rhizome. 4-mercaptohpenol and 2-n-butylfuran, which were compatible with most host plant-based chemicals and were attractive as a mixture, were perceived to be key elements in the composition of attractants to the weevil. It was concluded that in addition to the composition, other factors that may determine the attractiveness or otherwise of a mixture to C. sordidus are the proportions and concentrations of the constituent chemicals.

A field experiment to recreate species rich hay meadows using regional seed mixtures

Species rich semi-natural grasslands are an important but threatened habitat throughout Europe and much of the former area has been lost since the 1950s. However, in some countries large areas have been preserved and the demand for meadow recreation by sowing seed mixtures is increasing. In the White Carpathians Protected Landscape Area (Czech Republic) the use of commercial seed mixtures is undesirable and the use of regional mixtures has been investigated. The costs for seeding large areas are high and lower cost techniques are needed. In 1999 a field experiment was set up to investigate the establishment of hay meadow vegetation comparing sowing a regional mixture all over a plot with sowing narrow 2.5 In strips of regional seed mixtures into a matrix of a commercial grass mixture or into natural regeneration. The results after five seasons showed good establishment of the sown species in the meadow treatment. Spread of sown species from the sown strips into the surrounding matrix occurred but the cover of species was lower in the commercial grass matrix compared with the natural regeneration matrix. Colonisation of some plots by unsown desirable grassland species from adjacent grassland habitats also occurred, but more species colonised the natural regeneration matrix than the commercial grasses or the sown meadow matrix itself. Overall, the results indicate that, in appropriate situations, sown strips can provide a lower cost but slower and longer-term alternative to field scale sowing of regional seed mixtures for recreation of hay meadow vegetation. (C) 2007 Elsevier Ltd. All rights reserved.

Long-term effectiveness of sowing high and low diversity seed mixtures to enhance plant community development on ex-arable fields

Questions: How is succession on ex-arable land affected by sowing high and low diversity mixtures of grassland species as compared to natural succession? How long do effects persist? Location: Experimental plots installed in the Czech Republic, The Netherlands, Spain, Sweden and the United Kingdom. Methods: The experiment was established on ex-arable land, with five blocks, each containing three 10 m x 10 m experiment tal plots: natural colonization, a low- (four species) and high-diversity (15 species) seed mixture. Species composition and biomass was followed for eight years. Results: The sown plants considerably affected the whole successional pathway and the effects persisted during the whole eight year period. Whilst the proportion of sown species (characterized by their cover) increased during the study period, the number of sown species started to decrease from the third season onwards. Sowing caused suppression of natural colonizing species, and the sown plots had more biomass. These effects were on average larger in the high diversity mixtures. However, the low diversity replicate sown with the mixture that produced the largest biomass or largest suppression of natural colonizers fell within the range recorded at the five replicates of the high diversity plots. The natural colonization plots usually had the highest total species richness and lowest productivity at the end of the observation period. Conclusions: The effect of sowing demonstrated dispersal limitation as a factor controlling the rate of early secondary succession. Diversity was important primarily for its 'insurance effect': the high diversity mixtures were always able to compensate for the failure of some species.

Bayesian clustering of farm types using the mixtures model

A Bayesian method of classifying observations that are assumed to come from a number of distinct subpopulations is outlined. The method is illustrated with simulated data and applied to the classification of farms according to their level and variability of income. The resultant classification shows a greater diversity of technical charactersitics within farm types than is conventionally the case. The range of mean farm income between groups in the new classification is wider than that of the conventional method and the variability of income within groups is narrower. Results show that the highest income group in 2000 included large specialist dairy farmers and pig and poultry producers, whilst in 2001 it included large and small specialist dairy farms and large mixed dairy and arable farms. In both years the lowest income group is dominated by non-milk producing livestock farms.

Asymptotic normality in mixtures of power series distributions

The problem of estimating the individual probabilities of a discrete distribution is considered. The true distribution of the independent observations is a mixture of a family of power series distributions. First, we ensure identifiability of the mixing distribution assuming mild conditions. Next, the mixing distribution is estimated by non-parametric maximum likelihood and an estimator for individual probabilities is obtained from the corresponding marginal mixture density. We establish asymptotic normality for the estimator of individual probabilities by showing that, under certain conditions, the difference between this estimator and the empirical proportions is asymptotically negligible. Our framework includes Poisson, negative binomial and logarithmic series as well as binomial mixture models. Simulations highlight the benefit in achieving normality when using the proposed marginal mixture density approach instead of the empirical one, especially for small sample sizes and/or when interest is in the tail areas. A real data example is given to illustrate the use of the methodology.

Equivalence of truncated count mixture distributions and mixtures of truncated count distributions

This article is about modeling count data with zero truncation. A parametric count density family is considered. The truncated mixture of densities from this family is different from the mixture of truncated densities from the same family. Whereas the former model is more natural to formulate and to interpret, the latter model is theoretically easier to treat. It is shown that for any mixing distribution leading to a truncated mixture, a (usually different) mixing distribution can be found so. that the associated mixture of truncated densities equals the truncated mixture, and vice versa. This implies that the likelihood surfaces for both situations agree, and in this sense both models are equivalent. Zero-truncated count data models are used frequently in the capture-recapture setting to estimate population size, and it can be shown that the two Horvitz-Thompson estimators, associated with the two models, agree. In particular, it is possible to achieve strong results for mixtures of truncated Poisson densities, including reliable, global construction of the unique NPMLE (nonparametric maximum likelihood estimator) of the mixing distribution, implying a unique estimator for the population size. The benefit of these results lies in the fact that it is valid to work with the mixture of truncated count densities, which is less appealing for the practitioner but theoretically easier. Mixtures of truncated count densities form a convex linear model, for which a developed theory exists, including global maximum likelihood theory as well as algorithmic approaches. Once the problem has been solved in this class, it might readily be transformed back to the original problem by means of an explicitly given mapping. Applications of these ideas are given, particularly in the case of the truncated Poisson family.

Effects of fungicide dose and mixtures on selection for triazole resistance in Mycosphaerella graminicola under field conditions

The effects of varying doses of fungicides, alone or in mixtures, on selection for triazole resistance were examined under field conditions. Two experiments were conducted using the triazole fungicide fluquinconazole with the strobilurin fungicide azoxystrobin as a mixture partner. Inoculated wheat plots with a known ratio of more sensitive to less sensitive isolates of the leaf blotch fungus Mycosphaerella graminicola were sprayed with fungicide and sampled once symptoms had appeared. Selection for fluquinconazole resistance increased in proportion to the dose, up to one-half of the full dose (the maximum tested) in both experiments. At the higher doses of fluquinconazole, the addition of azoxystrobin was associated with a decrease in selection (nonsignificant in the first experiment) for triazole resistance. Control by low doses of fluquinconazole was increased by mixture with azoxystrobin, but at higher doses mixture with azoxystrobin sometimes decreased control, so that reduced selection was obtained at the cost of some reduction in control. The effects on resistance are not necessarily general consequences of mixing fungicides, and suggest that the properties of any specific mixture may need to be demonstrated experimentally. Selection was inversely related to control in the unmixed treatments in both experiments, but the relationship was weaker in the mixtures with azoxystrobin.