Otimização da concentração de misturas de herbicidas considerando a resistência de plantas daninhas.

I CMAC Sudeste

Otimização dinâmica multiobjetivo da aplicação de herbicida considerando a resistência de plantas daninhas.

Neste trabalho apresenta-se um modelo de otimização dinâmica multaiobjetivo da aplicação de herbicida. A densidade de sementes no início do plantio e a frequência dos alelos são tomadas como variáveis de estado. A variável de controle ?e a dose de herbicida aplicada em cada período de plantio. O modelo de otimização considera a diminuição da eficiência do herbicida ao longo do tempo, em função da evolução da resistência da planta daninha. Os objetivos são: 1) maximizar o lucro do produtor e 2) minimizar o acréscimo na resistência da planta daninha, promovido pelo uso do herbicida. Assim, o problema de otimização dinâmica multi objetivo formulado ?e resolvido utilizando-se a abordagem E - restrito. Os problemas resultantes desta abordagem são resolvidos via programação não-linear, utilizando o método ASA-CG. Resultados de simulações numéricas descrevem o conjunto de Pareto-ótimo da aplicação do herbicida nicosulfuron visando o controle da infestação da planta daninha Bidens subalternans em períodos de 5 e 10 anos, respectivamente

Network Archaeology: Uncovering Ancient Networks from Present-day Interactions

Often questions arise about old or extinct networks. What proteins interacted in a long-extinct ancestor species of yeast? Who were the central players in the Last.fm social network 3 years ago? Our ability to answer such questions has been limited by the unavailability of past versions of networks. To overcome these limitations, we propose several algorithms for reconstructing a network's history of growth given only the network as it exists today and a generative model by which the network is believed to have evolved. Our likelihood-based method finds a probable previous state of the network by reversing the forward growth model. This approach retains node identities so that the history of individual nodes can be tracked. We apply these algorithms to uncover older, non-extant biological and social networks believed to have grown via several models, including duplication-mutation with complementarity, forest fire, and preferential attachment. Through experiments on both synthetic and real-world data, we find that our algorithms can estimate node arrival times, identify anchor nodes from which new nodes copy links, and can reveal significant features of networks that have long since disappeared.Comment: 16 pages, 10 figure

Heterologous reporter expression in the planarian Schmidtea mediterranea through somatic mRNA transfection

Planarians have long been studied for their regenerative abilities. Moving forward, tools for ectopic expression of non-native proteins will be of substantial value. Using a luminescent reporter to overcome the strong autofluorescence of planarian tissues, we demonstrate heterologous protein expression in planarian cells and live animals. Our approach is based on the introduction of mRNA through several nanotechnological and chemical transfection methods. We improve reporter expression by altering untranslated region (UTR) sequences and codon bias, facilitating the measurement of expression kinetics in both isolated cells and whole planarians using luminescence imaging. We also examine protein expression as a function of variations in the UTRs of delivered mRNA, demonstrating a framework to investigate gene regulation at the post-transcriptional level. Together, these advances expand the toolbox for the mechanistic analysis of planarian biology and establish a foundation for the development and expansion of transgenic techniques in this unique model system

Searching for network modules

When analyzing complex networks a key target is to uncover their modular structure, which means searching for a family of modules, namely node subsets spanning each a subnetwork more densely connected than the average. This work proposes a novel type of objective function for graph clustering, in the form of a multilinear polynomial whose coefficients are determined by network topology. It may be thought of as a potential function, to be maximized, taking its values on fuzzy clusterings or families of fuzzy subsets of nodes over which every node distributes a unit membership. When suitably parametrized, this potential is shown to attain its maximum when every node concentrates its all unit membership on some module. The output thus is a partition, while the original discrete optimization problem is turned into a continuous version allowing to conceive alternative search strategies. The instance of the problem being a pseudo-Boolean function assigning real-valued cluster scores to node subsets, modularity maximization is employed to exemplify a so-called quadratic form, in that the scores of singletons and pairs also fully determine the scores of larger clusters, while the resulting multilinear polynomial potential function has degree 2. After considering further quadratic instances, different from modularity and obtained by interpreting network topology in alternative manners, a greedy local-search strategy for the continuous framework is analytically compared with an existing greedy agglomerative procedure for the discrete case. Overlapping is finally discussed in terms of multiple runs, i.e. several local searches with different initializations.Comment: 10 page

Geometric Mixing, Peristalsis, and the Geometric Phase of the Stomach

Mixing fluid in a container at low Reynolds number - in an inertialess environment - is not a trivial task. Reciprocating motions merely lead to cycles of mixing and unmixing, so continuous rotation, as used in many technological applications, would appear to be necessary. However, there is another solution: movement of the walls in a cyclical fashion to introduce a geometric phase. We show using journal-bearing flow as a model that such geometric mixing is a general tool for using deformable boundaries that return to the same position to mix fluid at low Reynolds number. We then simulate a biological example: we show that mixing in the stomach functions because of the "belly phase": peristaltic movement of the walls in a cyclical fashion introduces a geometric phase that avoids unmixing.Comment: Revised, published versio

Equation for the potential of an electron system with slowly varying density in the energy-functional formalism

A second-order differential equation is derived for the electric potential of an electron system with slowly varying density. It includes consistently the first-gradient corrections to both the kinetic energy and the exchange energy. In the regime of high density, the equation reduces to the one derived by Schwinger Phys. Rev. A 24 2353 (1981