Mathematical analysis of a population model with an age–weight structured two-stage life history: asymptotic behavior of solutions

In this paper, we propose a model for the dynamics of a physiologically structured population of individuals whose life cycle is divided into two stages: the first stage is structured by the weight, while the second one is structured by the age, the exit from the first stage occurring when a threshold weight is attained. The model originates in a complex one dealing with a fish population and covers a large class of situations encompassing two-stage life histories with a different structuring variable for each state, one of its key features being that the maturation process is determined in terms of a weight threshold to be reached by individuals in the first stage. Mathematically, the model is based on the classical Lotka–MacKendrick linear model, which is reduced to a delayed renewal equation including a constant delay that can be viewed as the time spent by individuals in the first stage to reach the weight threshold. The influence of the growth rate and the maturation threshold on the long-term behavior of solutions is analyzed using Laplace transform methods.     

DCA based algorithms for multiple sequence alignment (MSA)

In the last years many techniques in bioinformatics have been developed for the central and complex problem of optimally aligning biological sequences. In this paper we propose a new optimization approach based on DC (Difference of Convex functions) programming and DC Algorithm (DCA) for the multiple sequence alignment in its equivalent binary linear program, called “Maximum Weight Trace” problem. This problem is beforehand recast as a polyhedral DC program with the help of exact penalty techniques in DC programming. Our customized DCA, requiring solution of a few linear programs, is original because it converges after finitely many iterations to a binary solution while it works in a continuous domain. To scale-up large-scale (MSA), a constraint generation technique is introduced in DCA. Preliminary computational experiments on benchmark data show the efficiency of the proposed algorithm DCAMSA, which generally outperforms some standard algorithms.     

Global solution with \documentclass{article}\usepackage{amssymb}\begin{document}\pagestyle{empty}$ \mathcal {C}^{k}$\end{document}‐estimates for \documentclass{article}\usepackage{amssymb}\begin{document}\pagestyle{empty}$\bar{\partial }$\end{document}‐equation on q‐convex intersections

We construct a global solution with $\mathcal {C}^{k}$‐estimates for the $\bar{\partial }$‐equation on q‐convex intersections.     

CONTROLLABILITY OF NEUTRAL FUNCTIONAL DIFFERENTIAL EQUATIONS WITH INFINITE DELAY

In this article, we give sufficient conditions for controllability of some partial neutral functional differential equations with infinite delay. We suppose that the linear part is not necessarily densely defined but satisfies the resolvent estimates of the Hille-Yosida theorem. The results are obtained using the integrated semigroups theory. An application is given to illustrate our abstract result.     

Conley index condition for asymptotic stability

In this paper, we use Conley index theory to develop necessary conditions for stability of equilibrium and periodic solutions of nonlinear continuous-time systems. The Conley index is a topological generalization of the Morse theory which has been developed to analyze dynamical systems using topological methods. In particular, the Conley index of an invariant set with respect to a dynamical system is defined as the relative homology of an index pair for the invariant set. The Conley index can then be used to examine the structure of the system invariant set as well as the system dynamics within the invariant set, including system stability properties. Efficient numerical algorithms using homology theory have been developed in the literature to compute the Conley index and can be used to deduce the stability properties of nonlinear dynamical systems.     

Local ordering and magnetism in Ga0.9Fe3.1N

Prior investigations of the ternary nitride series Ga_1-xFe_3+xN (0≤x≤1) have indicated a transition from ferromagnetic γ′-Fe₄N to antiferromagnetic “GaFe₃N”. The ternary nitride “GaFe₃N” has been magnetically and spectroscopically reinvestigated in order to explore the weakening of the ferromagnetic interactions through the gradual incorporation of gallium into γ′-Fe₄N. A hysteretic loop at RT reveals the presence of a minority phase of only 0.1-0.2 at%, in accord with the sound two-step synthesis. The composition of the gallium-richest phase “GaFe₃N” was clarified by Prompt Gamma-ray Activation Analysis and leads to the berthollide formula Ga_0.91(1)Fe_3.09(10)N_1.05(7). Magnetic measurements indicate a transition around 8 K, further supported by Mössbauer spectral data. The weakening of the ferromagnetic coupling through an increasing gallium concentration is explained by a simple Stoner argument. In Ga_0.9Fe_3.1N, the presence of iron on the gallium site affects the magnetism by the formation of 13-atom iron clusters.