Parameter uncertainty of a dynamic multispecies size spectrum model

Dynamic size spectrum models have been recognized as an effective way of describing how size-based interactions can give rise to the size structure of aquatic communities. They are intermediate-complexity ecological models that are solutions to partial differential equations driven by the size-dependent processes of predation, growth, mortality, and reproduction in a community of interacting species and sizes. To be useful for quantitative fisheries management these models need to be developed further in a formal statistical framework. Previous work has used time-averaged data to “calibrate” the model using optimization methods with the disadvantage of losing detailed time-series information. Using a published multispecies size spectrum model parameterized for the North Sea comprising 12 interacting fish species and a background resource, we fit the model to time-series data using a Bayesian framework for the first time. We capture the 1967–2010 period using annual estimates of fishing mortality rates as input to the model and time series of fisheries landings data to fit the model to output. We estimate 38 key parameters representing the carrying capacity of each species and background resource, as well as initial inputs of the dynamical system and errors on the model output. We then forecast the model forward to evaluate how uncertainty propagates through to population- and community-level indicators under alternative management strategies

Abundances of the elements in the solar system

A review of the abundances and condensation temperatures of the elements and their nuclides in the solar nebula and in chondritic meteorites. Abundances of the elements in some neighboring stars are also discussed.Comment: 42 pages, 11 tables, 8 figures, chapter, In Landolt- B\"ornstein, New Series, Vol. VI/4B, Chap. 4.4, J.E. Tr\"umper (ed.), Berlin, Heidelberg, New York: Springer-Verlag, p. 560-63

Integrating sequence and array data to create an improved 1000 Genomes Project haplotype reference panel

A major use of the 1000 Genomes Project (1000GP) data is genotype imputation in genome-wide association studies (GWAS). Here we develop a method to estimate haplotypes from low-coverage sequencing data that can take advantage of single-nucleotide polymorphism (SNP) microarray genotypes on the same samples. First the SNP array data are phased to build a backbone (or 'scaffold') of haplotypes across each chromosome. We then phase the sequence data 'onto' this haplotype scaffold. This approach can take advantage of relatedness between sequenced and non-sequenced samples to improve accuracy. We use this method to create a new 1000GP haplotype reference set for use by the human genetic community. Using a set of validation genotypes at SNP and bi-allelic indels we show that these haplotypes have lower genotype discordance and improved imputation performance into downstream GWAS samples, especially at low-frequency variants. © 2014 Macmillan Publishers Limited. All rights reserved

Iterative learning control for improved aerodynamic load performance of wind turbines with smart rotors

Currently there is significant research into the inclusion of smart devices in wind turbine rotor blades, with the aim, in conjunction with collective and individual pitch control, of improving the aerodynamic performance of the rotors. The main objective is to reduce fatigue loads, although mitigating the effects of extreme loads is also of interest. The aerodynamic loads on a wind turbine blade have periodic and non-periodic components, and the nature of these strongly suggests the application of iterative learning control. This paper employs a simple computational fluid dynamics model to represent flow past an airfoil, and uses this to undertake a detailed investigation into the level of control possible by, as in other areas, combining iterative learning control with classical control action with emphasis on how performance can be effectively measure

Iterative learning control applied to a non-linear vortex panel model for improved aerodynamic load performance of wind turbines with smart rotors

The inclusion of smart devices in wind turbine rotor blades could, in conjunction with collective and individual pitch control, improve the aerodynamic performance of the rotors. This is currently an active area of research with the primary objective of reducing the fatigue loads but mitigating the effects of extreme loads is also of interest. The aerodynamic loads on a wind turbine blade contain periodic and non-periodic components and one approach is to consider the application of iterative learning control algorithms. In this paper the control design is based on a simple, in relative terms, computational fluid dynamics model that uses non-linear wake effects to represent flow past an airfoil. In this paper, a representation for the actuator dynamics is included to undertake a detailed investigation into the level of control possible and on how performance can be effectively measured

Iterative learning control of wind turbine smart rotors with pressure sensors

Improving the aerodynamic effectiveness and hence energy production of wind turbines is of critical importance and there is currently research into to the inclusion of smart devices in rotor blades in conjunction with collective and individual pitch control. The main objective is to reduce fatigue loads which have periodic and non-periodic components. This paper gives further results on the use of iterative learning control in this application area based on first constructing a simple but realistic computational fluid dynamics model to represent flow past an airfoil. The new results are based on the use of pressure sensors to estimate the lift

Leading change in higher education

This article considers the situation in the UK higher education system and investigates specifically the leadership practice in a cluster of UK institutions as they changed their status. The research goes further to advocate a form of contextualized leadership that is relevant to higher institutions under change

Control of photosynthesis in barley leaves with reduced activities of glutamine synthetase or glutamate synthase.

Wild-type and mutant plants of barley (Hordeum vulgare L. cv. Maris Mink) lacking activities of chloroplastic glutamine synthetase (GS) and of ferredox-in-dependent glutamate synthase (Fd-GOGAT) were crossed to generate heterozygous plants. Crosses of the F2 generation containing GS activities between 47 and 97 of the wild-type and Fd-GOGAT activities down to 63 of the wild-type have been selected to study the control of both enzymes on photorespiratory carbon and nitrogen metabolism. There were no major pleiotropic effects. Decreased GS had a small impact on leaf protein and the total activity of ribulose-1,5-bisphosphate carboxylase-oxygenase (Rubisco). The activation state of Rubisco was unaffected in air, but a decrease in GS influenced the activation state of Rubisco in low CO2. In illuminated leaves, the amino-acid content decreased with decreasing GS, while the content of ammonium rose, showing that even small reductions in GS limit ammonium re-assimilation and may bring about a loss of nitrogen from the plants, and hence a reduction in protein and Rubisco. Leaf amino-acid contents were restored, and ammonium and nitrate contents decreased, by leaving plants in the dark for 24 h. The ratios of serine to glycine decreased with a decrease in GS when plants were kept at moderate photon flux densities in air, suggesting a possible feedback on glycine decarboxylation. This effect was absent in high light and low CO2. Under these conditions ammonium contents exhibited an optimum and amino-acid contents a minimum at a GS activity of 65 of the wild-type, suggesting an inhibition of ammonium release in mutants with less than 65 GS. The leaf contents of glutamate, glutamine, aspartate, asparagine, and alanine largely followed changes in the total amino-acid contents determined under different environmental conditions. Decreased Fd-GOGAT resulted in a decrease in leaf protein, chlorophyll, Rubisco and nitrate contents. Chlorophyll a/b ratios and specific leaf fresh weight were lower than in the wild-type. Leaf ammonium contents were similar to the wild-type and total leaf amino-acid contents were only affected in low CO2 at high photon flux densities, but mutants with decreased Fd-GOGAT accumulated glutamine and contained less glutamate

A Note On Impossibility Theorems and Seniority Rules

We characterize seniority rules, also known as lexical dictatorships, under weak consistency constraints on the group’s choice function. These constraints are base triple-acyclicity in the case of binary choices and rationalizability (although not rationality) in the case of choices between an arbitrary number of alternatives. Existing results on these weakened constraints remain silent on the treatment of the group’s most junior individuals and therefore do not yield a complete characterization of seniority rules. We also impose a universal domain, binary strict Pareto optimality, binary Pareto indifference, binary independence of irrelevant alternatives, and the newly introduced condition of conflict resolution. The latter condition requires a social choice rules not to remain indecisive between alternatives for which individuals have conflicting preferences. Copyright Kluwer Academic Publishers 2004Consistency, Lexical dictatorship, Rationality, Seniority, Social choice theory,