Between but not within species variation in the distribution of fitness effects

New mutations provide the raw material for evolution and adaptation. The distribution of fitness effects (DFE) describes the spectrum of effects of new mutations that can occur along a genome, and is therefore of vital interest in evolutionary biology. Recent work has uncovered striking similarities in the DFE between closely related species, prompting us to ask whether there is variation in the DFE among populations of the same species, or among species with different degrees of divergence, i.e., whether there is variation in the DFE at different levels of evolution. Using exome capture data from six tree species sampled across Europe we characterised the DFE for multiple species, and for each species, multiple populations, and investigated the factors potentially influencing the DFE, such as demography, population divergence and genetic background. We find statistical support for there being variation in the DFE at the species level, even among relatively closely related species. However, we find very little difference at the population level, suggesting that differences in the DFE are primarily driven by deep features of species biology, and that evolutionarily recent events, such as demographic changes and local adaptation, have little impact

The GenTree Platform: growth traits and tree-level environmental data in 12 European forest tree species

Background: Progress in the field of evolutionary forest ecology has been hampered by the huge challenge of phenotyping trees across their ranges in their natural environments, and the limitation in high-resolution environmental information. Findings: The GenTree Platform contains phenotypic and environmental data from 4,959 trees from 12 ecologically and economically important European forest tree species: Abies alba Mill. (silver fir), Betula pendula Roth. (silver birch), Fagus sylvatica L. (European beech), Picea abies (L.) H. Karst (Norway spruce), Pinus cembra L. (Swiss stone pine), Pinus halepensis Mill. (Aleppo pine), Pinus nigra Arnold (European black pine), Pinus pinaster Aiton (maritime pine), Pinus sylvestris L. (Scots pine), Populus nigra L. (European black poplar), Taxus baccata L. (English yew), and Quercus petraea (Matt.) Liebl. (sessile oak). Phenotypic (height, diameter at breast height, crown size, bark thickness, biomass, straightness, forking, branch angle, fructification), regeneration, environmental in situ measurements (soil depth, vegetation cover, competition indices), and environmental modeling data extracted by using bilinear interpolation accounting for surrounding conditions of each tree (precipitation, temperature, insolation, drought indices) were obtained from trees in 194 sites covering the species’ geographic ranges and reflecting local environmental gradients. Conclusion: The GenTree Platform is a new resource for investigating ecological and evolutionary processes in forest trees. The coherent phenotyping and environmental characterization across 12 species in their European ranges allow for a wide range of analyses from forest ecologists, conservationists, and macro-ecologists. Also, the data here presented can be linked to the GenTree Dendroecological collection, the GenTree Leaf Trait collection, and the GenTree Genomic collection presented elsewhere, which together build the largest evolutionary forest ecology data collection available

Sensorless force/position control of a single-acting actuator applied to compliant object interaction

International audienceThis paper deals with a sensorless control approach of a lightweight electric actuator. Force and motion control are necessary to perform manipulation tasks with object interaction of different stiffnesses. The controller must ensure stability in a wide range of rigidity, particularly in soft contact cases. The approach proposed here is based on a force/position control scheme. First, a nonlinear position controller is performed through a linear parameter-varying state feedback. A state observer is added to estimate unmeasurable variables coming from an absence of terminal sensors. Subsequently, an output feedback force control is determined using an H∞ framework. The controller is experimentally applied on a single-acting actuator to demonstrate the efficiency of this approach dedicated to compliant object interaction

Combining least-squares and gradient-based algorithms for the identification of a co-current flow heat exchanger

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Fouling Detection in a Parallel Flow Heat Exchanger via a Roesser Model Identification Procedure

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Combining least-squares and gradient-based algorithms for the identification of a co-current flow heat exchanger

<p>Because of the high-dimensional nature of partial differential equations (PDEs), identifying accurate models of processes, the behaviour of which is governed by PDEs, is a challenging problem which still deserves a lot of attention. We address the problem of identifying a grey-box model of a heat exchanger by combining equation-error and output-error-based algorithms. First, in order to estimate rough but reliable values of the sought physical parameters characterising the heat exchanger behaviour, we use the interesting properties of the reinitialised partial moments (RPMs) developed initially for ordinary differential equations to deal with the problem of inaccessible partial derivatives of the PDE. Such an adaptation of the RPM features to PDEs leads to a direct continuous-time system identification problem for which convex least-squares solutions can be found. Second, thanks to a description of the heat exchanger dynamics with a 2D linear time-invariant Roesser model, the aforementioned rough estimates are used as reliable initial guesses for the nonlinear optimisation of a standard non-convex cost function introduced to estimate the state-space matrices of the Roesser model we want to identify. The efficiency of this two-step approach in terms of physical parameter estimation is validated through the simulation of a co-current flow heat exchanger.</p