Rachid Senoussi

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Plant viruses are submitted to narrow population bottlenecks both during infection of their hosts and during horizontal transmission between host individuals. The size of bottlenecks exerted on virus populations during plant invasion has been estimated in a few pathosystems but is not addressed yet for horizontal transmission. Using competition for aphid(More)
The computation of the implicit equation of a rational parametric surface is in many applications the first step to deal with. The different methods of implicitization belong to two main classes. The first class of methods relies on classical elimination theory. Iterated resultants in one variable or resultants in several variables are used to compute the(More)
The effective size of populations (Ne) determines whether selection or genetic drift is the predominant force shaping their genetic structure and evolution. Populations having high Ne adapt faster, as selection acts more intensely, than populations having low Ne, where random effects of genetic drift dominate. Estimating Ne for various steps of plant virus(More)
Methods for spatial cluster detection dealing with diseases quantified by continuous variables are few, whereas several diseases are better approached by continuous indicators. For example, subclinical mastitis of the dairy cow is evaluated using a continuous marker of udder inflammation, the somatic cell score (SCS). Consequently, this study proposed to(More)
Frankliniella occidentalis (Pergande) is a key pest of various crops worldwide. In this study, we analyse the dependence of the infestation of this pest on spatially distributed micro climatic factors in a rose greenhouse. Despite the importance of this subject, the few existing studies have been realized in laboratory rather than in greenhouse conditions.(More)
In the rst part, we establish an upper bound of an iterated logarithm law for a sequence of processes Mn(:) ∈ C(R;R) endowed with the uniform convergence on compacts, where Mn(x) is a square integrable martingale for each x in R. In the second part we present an iterative kernel estimator of the driving function f of the regression model: Xn+1 = f(Xn) +(More)
The analysis of animal movement within different landscapes may increase our understanding of how landscape features affect the perceptual range of animals. Perceptual range is linked to movement probability of an animal via a dispersal kernel, the latter being generally considered as spatially invariant but could be spatially affected. We hypothesize that(More)