Idealized model for changes in equilibrium temperature, mixed layer depth, and boundary layer cloud over land in a doubled CO2 climate

An idealized equilibrium model for the undisturbed partly cloudy boundary layer (BL) is used as a framework to explore the coupling of the energy, water, and carbon cycles over land in midlatitudes and show the sensitivity to the clear‐sky shortwave flux, the midtropospheric temperature, moisture, CO2, and subsidence. The changes in the surface fluxes, the BL equilibrium, and cloud cover are shown for a warmer, doubled CO2 climate. Reduced stomatal conductance in a simple vegetation model amplifies the background 2 K ocean temperature rise to an (unrealistically large) 6 K increase in near‐surface temperature over land, with a corresponding drop of near‐surface relative humidity of about 19%, and a rise of cloud base of about 70 hPa. Cloud changes depend strongly on changes of mean subsidence; but evaporative fraction (EF) decreases. EF is almost uniquely related to mixed layer (ML) depth, independent of background forcing climate. This suggests that it might be possible to infer EF for heterogeneous landscapes from ML depth. The asymmetry of increased evaporation over the oceans and reduced transpiration over land increases in a warmer doubled CO2 climate.

Overseas trained teachers: part of a problem or part of a solution?

Overseas trained teachers (OTTs) have grown in numbers during the past decade, particularly in London and the South East of England. In this recruitment explosion many OTTs have experienced difficulties. In professional literature as well as press coverage OTTs often become part of a deficit discourse. A small-scale pilot investigation of OTT experience has begun to suggest why OTTs have been successful as well as the principal challenges they have faced. An important factor in their success was felt to be the quality of support in school from others on the staff. Major challenges included the complexity of the primary curriculum. The argument that globalisation leads to brain-drain may be exaggerated. Suggestions for further research are made, which might indicate the positive benefits OTTs can bring to a school.

Time-dependent orientation coupling in equilibrium polymer melts

The motion in concentrated polymer systems is described by either the Rouse or the reptation model, which both assume that the relaxation of each polymer chain is independent of the surrounding chains. This, however, is in contradiction with several experiments. In this Letter, we propose a universal description of orientation coupling in polymer melts in terms of the time-dependent coupling parameter κ(t). We use molecular dynamics simulations to show that the coupling parameter increases with time, reaching about 50% at long times, independently of the chain length or blend composition. This leads to predictions of component dynamics in mixtures of different molecular weights from the knowledge of monodisperse dynamics for unentangled melts. Finally, we demonstrate that entanglements do not play a significant role in the observed coupling. © 2010 The American Physical Society

Worry and problem-solving skills and beliefs in primary school children

Objective. To examine the association between worry and problem-solving skills and beliefs (confidence and perceived control) in primary school children. Method. Children (8–11 years) were screened using the Penn State Worry Questionnaire for Children. High (N ¼ 27) and low (N ¼ 30) scorers completed measures of anxiety, problem-solving skills (generating alternative solutions to problems, planfulness, and effectiveness of solutions) and problem-solving beliefs(confidence and perceived control). Results. High and low worry groups differed significantly on measures of anxiety and problem-solving beliefs (confidence and control) but not on problem-solving skills. Conclusions. Consistent with findings with adults, worry in children was associated with cognitive distortions, not skills deficits. Interventions for worried children may benefit froma focus on increasing positive problem-solving beliefs.

A model for self-directed problem-based learning for renal therapeutics

Objective To introduce a new approach to problem-based learning (PBL) for self-directed learning in renal therapeutics. Design This 5-week course, designed for large student cohorts using minimal teaching resources, was based on a series of case studies and subsequent pharmaceutical care plans, followed by intensive and regular feedback from the instructor. Assessment Assessment of achievement of the learning outcomes was based on weekly-graded care plans and peer review assessment, allowing each student to judge the contributions of each group member and their own, along with a written case-study based examination. The pharmaceutical care plan template, designed using a “tick-box” system, significantly reduced staff time for feedback and scoring. Conclusion The proposed instructional model achieved the desired learning outcomes with appropriate student feedback, while promoting skills that are essential for the students' future careers as health care professionals.

On the principal eigenvalue of a Robin problem with a large parameter

We study the asymptotic behaviour of the principal eigenvalue of a Robin (or generalised Neumann) problem with a large parameter in the boundary condition for the Laplacian in a piecewise smooth domain. We show that the leading asymptotic term depends only on the singularities of the boundary of the domain, and give either explicit expressions or two-sided estimates for this term in a variety of situations.

Convergence analysis of stochastic diffusion search

In this paper we present a connectionist searching technique - the Stochastic Diffusion Search (SDS), capable of rapidly locating a specified pattern in a noisy search space. In operation SDS finds the position of the pre-specified pattern or if it does not exist - its best instantiation in the search space. This is achieved via parallel exploration of the whole search space by an ensemble of agents searching in a competitive cooperative manner. We prove mathematically the convergence of stochastic diffusion search. SDS converges to a statistical equilibrium when it locates the best instantiation of the object in the search space. Experiments presented in this paper indicate the high robustness of SDS and show good scalability with problem size. The convergence characteristic of SDS makes it a fully adaptive algorithm and suggests applications in dynamically changing environments.

Measuring departures from Hardy-Weinberg: a Markov chain Monte Carlo method for estimating the inbreeding coefficient

Many well-established statistical methods in genetics were developed in a climate of severe constraints on computational power. Recent advances in simulation methodology now bring modern, flexible statistical methods within the reach of scientists having access to a desktop workstation. We illustrate the potential advantages now available by considering the problem of assessing departures from Hardy-Weinberg (HW) equilibrium. Several hypothesis tests of HW have been established, as well as a variety of point estimation methods for the parameter which measures departures from HW under the inbreeding model. We propose a computational, Bayesian method for assessing departures from HW, which has a number of important advantages over existing approaches. The method incorporates the effects-of uncertainty about the nuisance parameters--the allele frequencies--as well as the boundary constraints on f (which are functions of the nuisance parameters). Results are naturally presented visually, exploiting the graphics capabilities of modern computer environments to allow straightforward interpretation. Perhaps most importantly, the method is founded on a flexible, likelihood-based modelling framework, which can incorporate the inbreeding model if appropriate, but also allows the assumptions of the model to he investigated and, if necessary, relaxed. Under appropriate conditions, information can be shared across loci and, possibly, across populations, leading to more precise estimation. The advantages of the method are illustrated by application both to simulated data and to data analysed by alternative methods in the recent literature.

A two-locus forensic match probability for subdivided populations

A two-locus match probability is presented that incorporates the effects of within-subpopulation inbreeding (consanguinity) in addition to population subdivision. The usual practice of calculating multi-locus match probabilities as the product of single-locus probabilities assumes independence between loci. There are a number of population genetics phenomena that can violate this assumption: in addition to consanguinity, which increases homozygosity at all loci simultaneously, gametic disequilibrium will introduce dependence into DNA profiles. However, in forensics the latter problem is usually addressed in part by the careful choice of unlinked loci. Hence, as is conventional, we assume gametic equilibrium here, and focus instead on between-locus dependence due to consanguinity. The resulting match probability formulae are an extension of existing methods in the literature, and are shown to be more conservative than these methods in the case of double homozygote matches. For two-locus profiles involving one or more heterozygous genotypes, results are similar to, or smaller than, the existing approaches.

The Prony fitting method for digital deconvolution problem

The Prony fitting theory is applied in this paper to solve the deconvolution problem. There are two cases in deconvolution in which unstable solution is easy to appear. They are: (1)the frequency band of known kernel is more narraw than that of the unknown kernel; (2) there exists noise. These two cases are studied thoroughly and the effectiveness of Prony fitting method is showed. Finally, this method is simulated in computer. The simulation results are compared with those obtained by using FFT method directly.

A new approach for the solution of the optimal set-point tracking problem for nonlinear systems

In this paper, a discrete time dynamic integrated system optimisation and parameter estimation algorithm is applied to the solution of the nonlinear tracking optimal control problem. A version of the algorithm with a linear-quadratic model-based problem is developed and implemented in software. The algorithm implemented is tested with simulation examples.

German open ended funds: was there a valuation problem?

In late 2005, a number of German open ended funds suffered significant withdrawals by unit holders. The crisis was precipitated by a long term bear market in German property investment and the fact that these funds offered short term liquidity to unit holders but had low levels of liquidity in the fund. A more controversial suggestion was that the crisis was exacerbated by a perception that the valuations of the fund were too infrequent and inaccurate. As units are priced by reference to these valuations with no secondary market, the valuation process is central to the process. There is no direct evidence that these funds were over-valued but there is circumstantial evidence and this paper examines the indirect evidence of the process to see whether the hypothesis that valuation is an issue for the German funds holds any credibility. It also discusses whether there is a wider issue for other funds of this nature or whether it is a parochial problem confined to Germany. The conclusions are that there is reason to believe that German valuation processes make over-valuation in a recession more likely than in other countries and that more direct research into the German valuation system is required to identify the issues which need to be addressed to make the valuation system more trusted.