The Onset of Chaos in Pulsating Variable Stars

Random changes in pulsation period occur in cool pulsating Mira variables, Type A, B, and C semiregular variables, RV Tauri variables, and in most classical Cepheids. The physical processes responsible for such fluctuations are uncertain, but presumably originate in temporal modifications of the envelope convection in such stars. Such fluctuations are seemingly random over a few pulsation cycles of the stars, but are dominated by the regularity of the primary pulsation over the long term. The magnitude of stochasticity in pulsating stars appears to be linked directly to their dimensions, although not in simple fashion. It is relatively larger in M supergiants, for example, than in short-period Cepheids, but is common enough that it can be detected in visual observations for many types of pulsating stars. Although chaos was discovered in such stars 80 years ago, detection of its general presence in the group has only been possible in recent studies.Comment: To appear in the proceedings of the Odessa Variable Stars 2010 Conference (see http://uavso.org.ua/?page=vs2010&lang=en), edited by I. Andronov and V. Kovtyuk

The electrophilic fluorination of enol esters using SelectFluor : a polar two-electron process

The reaction of enol esters with SelectFluor is facile and leads to the corresponding α-fluoroketones under mild conditions and, as a result, this route is commonly employed for the synthesis of medicinally important compounds such as fluorinated steroids. However, despite the use of this methodology in synthesis, the mechanism of this reaction and the influence of structure on reactivity are unclear. We present a rigorous mechanistic study of the fluorination of these substrates, informed primarily by detailed and robust kinetic experiments. The results of this study implicate a polar two-electron process via an oxygen-stabilised carbenium species, rather than a single-electron process involving radical intermediates. The structure/reactivity relationships revealed here will assist synthetic chemists in deploying this type of methodology in the syntheses of α-fluoroketone

Developing the Saegusa-Ito cyclisation for the synthesis of difluorinated cyclohexenones

Palladium(II)-catalysed cycloalkenylation (Saegusa-Ito cyclisation) has been used for the first time to transform difluorinated silylenol ethers to difluorinated cycloalkenones under mild conditions. The silylenol ether precursors were prepared in two high-yielding steps from trifluoroethanol, and cyclised in moderate to good yields. A combination of air and copper(I) chloride in acetonitrile achieved the turnover of the initial palladium(II) salt, while the provision of an oxygen atmosphere ensured more rapid reaction. Annulations required a minimum level of substitution on the chain, but failed when the alkene was substituted. Annelations allowed a range of n,6-bicyclic systems to be prepared and afforded three products in which heterocycles were fused to the new cyclohexenone. The least substituted system explored underwent cyclisation followed by terminal oxidation to a cyclic enal, which corresponded to a Wacker product of unusual regiochemistry

Application of a single-objective, hybrid genetic algorithm approach to pharmacokinetic model building.

A limitation in traditional stepwise population pharmacokinetic model building is the difficulty in handling interactions between model components. To address this issue, a method was previously introduced which couples NONMEM parameter estimation and model fitness evaluation to a single-objective, hybrid genetic algorithm for global optimization of the model structure. In this study, the generalizability of this approach for pharmacokinetic model building is evaluated by comparing (1) correct and spurious covariate relationships in a simulated dataset resulting from automated stepwise covariate modeling, Lasso methods, and single-objective hybrid genetic algorithm approaches to covariate identification and (2) information criteria values, model structures, convergence, and model parameter values resulting from manual stepwise versus single-objective, hybrid genetic algorithm approaches to model building for seven compounds. Both manual stepwise and single-objective, hybrid genetic algorithm approaches to model building were applied, blinded to the results of the other approach, for selection of the compartment structure as well as inclusion and model form of inter-individual and inter-occasion variability, residual error, and covariates from a common set of model options. For the simulated dataset, stepwise covariate modeling identified three of four true covariates and two spurious covariates; Lasso identified two of four true and 0 spurious covariates; and the single-objective, hybrid genetic algorithm identified three of four true covariates and one spurious covariate. For the clinical datasets, the Akaike information criterion was a median of 22.3 points lower (range of 470.5 point decrease to 0.1 point decrease) for the best single-objective hybrid genetic-algorithm candidate model versus the final manual stepwise model: the Akaike information criterion was lower by greater than 10 points for four compounds and differed by less than 10 points for three compounds. The root mean squared error and absolute mean prediction error of the best single-objective hybrid genetic algorithm candidates were a median of 0.2 points higher (range of 38.9 point decrease to 27.3 point increase) and 0.02 points lower (range of 0.98 point decrease to 0.74 point increase), respectively, than that of the final stepwise models. In addition, the best single-objective, hybrid genetic algorithm candidate models had successful convergence and covariance steps for each compound, used the same compartment structure as the manual stepwise approach for 6 of 7 (86 %) compounds, and identified 54 % (7 of 13) of covariates included by the manual stepwise approach and 16 covariate relationships not included by manual stepwise models. The model parameter values between the final manual stepwise and best single-objective, hybrid genetic algorithm models differed by a median of 26.7 % (q₁ = 4.9 % and q₃ = 57.1 %). Finally, the single-objective, hybrid genetic algorithm approach was able to identify models capable of estimating absorption rate parameters for four compounds that the manual stepwise approach did not identify. The single-objective, hybrid genetic algorithm represents a general pharmacokinetic model building methodology whose ability to rapidly search the feasible solution space leads to nearly equivalent or superior model fits to pharmacokinetic data

Increasing biomass in Amazonian forest plots

A previous study by Phillips et al. of changes in the biomass of permanent sample plots in Amazonian forests was used to infer the presence of a regional carbon sink. However, these results generated a vigorous debate about sampling and methodological issues. Therefore we present a new analysis of biomass change in old-growth Amazonian forest plots using updated inventory data. We find that across 59 sites, the above-ground dry biomass in trees that are more than 10 cm in diameter (AGB) has increased since plot establishment by 1.22 ± 0.43 Mg per hectare per year (ha-1 yr-1), where 1 ha = 104 m2), or 0.98 ± 0.38 Mg ha-1 yr-1 if individual plot values are weighted by the number of hectare years of monitoring. This significant increase is neither confounded by spatial or temporal variation in wood specific gravity, nor dependent on the allometric equation used to estimate AGB. The conclusion is also robust to uncertainty about diameter measurements for problematic trees: for 34 plots in western Amazon forests a significant increase in AGB is found even with a conservative assumption of zero growth for all trees where diameter measurements were made using optical methods and/or growth rates needed to be estimated following fieldwork. Overall, our results suggest a slightly greater rate of net stand-level change than was reported by Phillips et al. Considering the spatial and temporal scale of sampling and associated studies showing increases in forest growth and stem turnover, the results presented here suggest that the total biomass of these plots has on average increased and that there has been a regional-scale carbon sink in old-growth Amazonian forests during the previous two decades

Variables associated with nest survival of Golden-winged Warblers (Vermivora chrysoptera) among vegetation communities commonly used for nesting

Among shrubland- and young forest-nesting bird species in North America, Golden-winged Warblers (Vermivora chrysoptera) are one of the most rapidly declining partly because of limited nesting habitat. Creation and management of high quality vegetation communities used for nesting are needed to reduce declines. Thus, we examined whether common characteristics could be managed across much of the Golden-winged Warbler’s breeding range to increase daily survival rate (DSR) of nests. We monitored 388 nests on 62 sites throughout Minnesota, Wisconsin, New York, North Carolina, Pennsylvania, Tennessee, and West Virginia. We evaluated competing DSR models in spatial-temporal (dominant vegetation type, population segment, state, and year), intraseasonal (nest stage and time-within-season), and vegetation model suites. The best-supported DSR models among the three model suites suggested potential associations between daily survival rate of nests and state, time-within-season, percent grass and Rubus cover within 1 m of the nest, and distance to later successional forest edge. Overall, grass cover (negative association with DSR above 50%) and Rubus cover (DSR lowest at about 30%) within 1 m of the nest and distance to later successional forest edge (negative association with DSR) may represent common management targets across our states for increasing Golden-winged Warbler DSR, particularly in the Appalachian Mountains population segment. Context-specific adjustments to management strategies, such as in wetlands or areas of overlap with Blue-winged Warblers (Vermivora cyanoptera), may be necessary to increase DSR for Golden-winged Warblers