France: genetics education for non-genetics health care providers

OBJECTIVE: This paper explores the treatment of medical genetics in undergraduate medical education, specialists' training and continuing medical education (CME) for general practitioners, specialists, nurses and midwives. METHODS: We conducted a qualitative survey of websites, published or unpublished documents, telephone interviews and mailed questionnaires. RESULTS: Genetics is a medical specialty in France, and the small number of university professors in genetics are in charge of the genetic component of medical training of all future practitioners. The study was complicated by the ongoing waves of reforms in the French health and educational systems and by the autonomy of the faculties. Specialist training and CME in genetics is heterogeneous and not organised as a priority. CONCLUSIONS: Specialist education and CME in genetics of non-geneticist health care providers needs to be adapted to the fast ongoing developments of this field of knowledge.     

On solving integral equations using Markov chain Monte Carlo methods

In this paper, we propose an original approach to the solution of Fredholm equations of the second kind. We interpret the standard Von Neumann expansion of the solution as an expectation with respect to a probability distribution defined on a union of subspaces of variable dimension. Based on this representation, it is possible to use trans-dimensional Markov chain Monte Carlo (MCMC) methods such as Reversible Jump MCMC to approximate the solution numerically. This can be an attractive alternative to standard Sequential Importance Sampling (SIS) methods routinely used in this context. To motivate our approach, we sketch an application to value function estimation for a Markov decision process. Two computational examples are also provided.     

Shear response of Fe-bearing MgSiO3 post-perovskite at lower mantle pressures

We investigate the shear response of possible slip systems activated in pure and Fe-bearing MgSiO₃ post-perovskite (PPv) through ab initio generalized stacking fault (GSF) energy calculations. Here we show that the [100](001) slip system has the easiest response to plastic shear among ten possible slip systems investigated. Incorporation of Fe²⁺ decreases the strength of all slip systems but does not change the plastic anisotropy style. Therefore, pure and Fe-bearing MgSiO₃ PPv should demonstrate similar LPO patterns with a strong signature of the [100](001) slip system. An aggregate with this deformation texture is expected to produce a V_SH > V_SV type polarization anisotropy, being consistent with seismological observations.     

Efficient Bayesian Inference for Multivariate Probit Models With Sparse Inverse Correlation Matrices

We propose a Bayesian approach for inference in the multivariate probit model, taking into account the association structure between binary observations. We model the association through the correlation matrix of the latent Gaussian variables. Conditional independence is imposed by setting some off-diagonal elements of the inverse correlation matrix to zero and this sparsity structure is modeled using a decomposable graphical model. We propose an efficient Markov chain Monte Carlo algorithm relying on a parameter expansion scheme to sample from the resulting posterior distribution. This algorithm updates the correlation matrix within a simple Gibbs sampling framework and allows us to infer the correlation structure from the data, generalizing methods used for inference in decomposable Gaussian graphical models to multivariate binary observations. We demonstrate the performance of this model and of the Markov chain Monte Carlo algorithm on simulated and real datasets. This article has online supplementary materials.     

A normalised residence time transport equation for the numerical simulation of combustion with high-temperature air

This study concerns the numerical simulation of turbulent non-premixed combustion in highly preheated air streams. One of the objectives is to settle an efficient computational procedure to proceed with the numerical simulation of large-scale industrial devices. It is also expected that the availability of such a computational framework may facilitate comprehensive sensitivity analyses as well as the development of mathematical models able to represent turbulence-chemistry interactions (TCI) in such conditions. Based on the salient physical ingredients that characterise scalar mixing, propagation, and self-ignition processes, a turbulent combustion modelling framework is thus introduced and applied to the numerical simulation of well-documented laboratory flames. In the corresponding geometries, the bulk flow velocities of the reactants streams can reach rather large values, which lead the flame to lift from the burner rim. Partially premixed flame edges thus stabilise the whole flame structure and the temperature of the oxidising stream can be increased by vitiation with burned gases so as to promote the corresponding flame-stabilisation processes. For sufficiently large values of the vitiated airstream temperature, self-ignition mechanisms may be triggered thus leading to a competition between mixing, propagation, and ignition processes. In this context, the ratio of the residence time to the self-ignition delay is thought to be a relevant variable to delineate the possible influence of ignition phenomena. Therefore, a modelled transport equation for this normalised residence time is considered. The performance of the corresponding modelling proposal is analysed with special emphasis placed on its ability to reproduce ‘memory’ or ‘lagrangian’ effects related to thermal aging processes. In this respect, it is noteworthy that the present set of computations makes use of tabulated quantities associated to (i) steady laminar one-dimensional diffusion flamelets, so as to describe the composition of combustion products, (ii) steady laminar one-dimensional premixed flamelets, to describe the flame brush propagation, and (iii) temporal evolution of zero-dimensional homogeneous mixtures to account for the possible occurrence of self-ignition phenomena. In particular, the tabulated self-ignition time value is used to evaluate the increase in the normalised residence time. Finally, two modelling parameters are put into evidence and studied through a detailed sensitivity analysis.     

Extrinsic Magnetoelectricity in Barium Titanate/Nickel Nanocomposites: Effect of Compaction Pressure on Interfacial Anisotropy

The dynamic control of the dielectric response in magnetoelectric (ME) nanocomposites (NCs) renders an entire additional degree of freedom to the functionality of miniaturized magnetoelectronics and spintronics devices. In composite materials, the ME effect is realized by using the concept of product properties. Through the investigation of the microwave properties of a series of BaTiO₃/Ni NCs fabricated by compaction of nanopowders, we present experimental evidence that the compaction (uniaxial) pressure in the range of 33–230 MPa significantly affects the ME features. We report here data for only one composition (17.1 vol.% of Ni in the BaTiO₃/Ni NC sample). Our findings revealed that the ME coupling coefficient exhibits a large enhancement for specific values of the Ni volume fraction and compaction pressure. Overall, these observations are considered to be evidence of stress-induced microstructural changes under pressure that strongly affect the elastic interaction between the magnetostrictive and piezoelectric phases in these NCs. These results have a potential technological impact for designing precise tunable ME NCs for microwave devices such as tunable phase shifters, resonators, and delay lines.     

On the structure of multiobjective combinatorial search space: MNK-landscapes with correlated objectives

The structure of the search space explains the behavior of multiobjective search algorithms, and helps to design well-performing approaches. In this work, we analyze the properties of multiobjective combinatorial search spaces, and we pay a particular attention to the correlation between the objective functions. To do so, we extend the multiobjective NK-landscapes in order to take the objective correlation into account. We study the co-influence of the problem dimension, the degree of non-linearity, the number of objectives, and the objective correlation on the structure of the Pareto optimal set, in terms of cardinality and number of supported solutions, as well as on the number of Pareto local optima. This work concludes with guidelines for the design of multiobjective local search algorithms, based on the main fitness landscape features.     

On the theta number of powers of cycle graphs

We give a closed formula for Lovász’s theta number of the powers of cycle graphs C _k ^d?1 and of their complements, the circular complete graphs K _k/d . As a consequence, we establish that the circular chromatic number of a circular perfect graph is computable in polynomial time. We also derive an asymptotic estimate for the theta number of C _k ^d .