Genetic Algorithm for the determination of binodal curves in ternary systems Polymer / Liquid(1) / Liquid(2) and Polymer(1) / Polymer(2) / Solvent

A simple genetic algorithm for the numerical evaluation of binodal curves in ternary systems polymer-liquid (1)-liquid (2) and polymer (1)-polymer (2)-solvent is presented. The technique exploits a specifically developed restarting technique based on a combined elitist and zooming strategy on the last population at each iteration. The objective function (fitness) is represented by the weighted sum of the squared differences of chemical potentials of the two phases of each component, obtained evaluating first derivatives of Gibbs free energy of the mixture with respect to the number of moles of the components. The method proposed (a) is numerically stable since it does not require the evaluation of first derivatives of the objective function and (b) can be applied in a wide range of cases changing the equation of state. Several comparisons with simplified iterative procedures presented in the past in the technical literature both for mixtures of two polymers with identical characteristics in a solvent and for mixtures of solvent-nonsolvent-polymer with solvent-polymer interaction parameter equal to zero are reported. Finally, a comparison between present results and the alternating tangent approach is reported for two technically meaningful binary systems, when a simplified PC-SAFT equation of state is adopted. The comparisons show that reliable results can be obtained by means of the algorithm proposed and suggest that the procedure presented can be used for practical purpose

A two-step process in the emergence of neurogenesis

Cnidarians belong to the first phylum differentiating a nervous system, thus providing suitable model systems to trace the origins of neurogenesis. Indeed corals, sea anemones, jellyfish and hydra contract, swim and catch their food thanks to sophisticated nervous systems that share with bilaterians common neurophysiological mechanisms. However, cnidarian neuroanatomies are quite diverse, and reconstructing the urcnidarian nervous system is ambiguous. At least a series of characters recognized in all classes appear plesiomorphic: (1) the three cell types that build cnidarian nervous systems (sensory-motor cells, ganglionic neurons and mechanosensory cells called nematocytes or cnidocytes); (2) an organization of nerve nets and nerve rings [those working as annular central nervous system (CNS)]; (3) a neuronal conduction via neurotransmitters; (4) a larval anterior sensory organ required for metamorphosis; (5) a persisting neurogenesis in adulthood. By contrast, the origin of the larval and adult neural stem cells differs between hydrozoans and other cnidarians; the sensory organs (ocelli, lens-eyes, statocysts) are present in medusae but absent in anthozoans; the electrical neuroid conduction is restricted to hydrozoans. Evo-devo approaches might help reconstruct the neurogenic status of the last common cnidarian ancestor. In fact, recent genomic analyses show that if most components of the postsynaptic density predate metazoan origin, the bilaterian neurogenic gene families originated later, in basal metazoans or as eumetazoan novelties. Striking examples are the ParaHox Gsx, Pax, Six, COUP-TF and Twist-type regulators, which seemingly exert neurogenic functions in cnidarians, including eye differentiation, and support the view of a two-step process in the emergence of neurogenesis