71,043 research outputs found

    Flexible protein folding by ant colony optimization

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    Protein structure prediction is one of the most challenging topics in bioinformatics. As the protein structure is found to be closely related to its functions, predicting the folding structure of a protein to judge its functions is meaningful to the humanity. This chapter proposes a flexible ant colony (FAC) algorithm for solving protein folding problems (PFPs) based on the hydrophobic-polar (HP) square lattice model. Different from the previous ant algorithms for PFPs, the pheromones in the proposed algorithm are placed on the arcs connecting adjacent squares in the lattice. Such pheromone placement model is similar to the one used in the traveling salesmen problems (TSPs), where pheromones are released on the arcs connecting the cities. Moreover, the collaboration of effective heuristic and pheromone strategies greatly enhances the performance of the algorithm so that the algorithm can achieve good results without local search methods. By testing some benchmark two-dimensional hydrophobic-polar (2D-HP) protein sequences, the performance shows that the proposed algorithm is quite competitive compared with some other well-known methods for solving the same protein folding problems

    Protein folding in hydrophobic-polar lattice model: a flexible ant colony optimization approach

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    This paper proposes a flexible ant colony (FAC) algorithm for solving protein folding problems based on the hydrophobic-polar square lattice model. Collaborations of novel pheromone and heuristic strategies in the proposed algorithm make it more effective in predicting structures of proteins compared with other state-of-the-art algorithms

    The state of the market and the contrarian strategy: Evidence from China’s stock market

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    This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2012 The Chinese Economic Association.Using the most comprehensive weekly dataset of ‘A’ shares listed on the Chinese stock market, this paper examines short-term contrarian strategies under different market states from 1995–2010. We find statistically significant profits from contrarian strategies, especially during the period after 2007, when China (along with other countries) experienced an economic downturn following the worldwide financial crisis. Our empirical evidence suggests that: (1) no significant profit is generated from either momentum or contrarian strategies in the intermediate horizon; (2) after microstructure effects are adjusted for, contrarian strategies with only four to eight weeks holding periods based on the stocks’ previous four to eight week's performance generate statistically significant profits of around 0.2% per week; (3) the contrarian strategy following a ‘down’ market generates higher profit than those following an ‘up’ market, suggesting that a contrarian strategy could be used as a shelter when the market is in decline. The profits following a ‘down’ market are robust after risk adjustment

    Relativistic description of magnetic moments in nuclei with doubly closed shells plus or minus one nucleon

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    Using the relativistic point-coupling model with density functional PC-PK1, the magnetic moments of the nuclei 207^{207}Pb, 209^{209}Pb, 207^{207}Tl and 209^{209}Bi with a jjjj closed-shell core 208^{208}Pb are studied on the basis of relativistic mean field (RMF) theory. The corresponding time-odd fields, the one-pion exchange currents, and the first- and second-order corrections are taken into account. The present relativistic results reproduce the data well. The relative deviation between theory and experiment for these four nuclei is 6.1% for the relativistic calculations and somewhat smaller than the value of 13.2% found in earlier non-relativistic investigations. It turns out that the π\pi meson is important for the description of magnetic moments, first by means of one-pion exchange currents and second by the residual interaction provided by the π\pi exchange.Comment: 11 pages, 7 figure

    Birational cobordism invariance of uniruled symplectic manifolds

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    A symplectic manifold (M,ω)(M,\omega) is called {\em (symplectically) uniruled} if there is a nonzero genus zero GW invariant involving a point constraint. We prove that symplectic uniruledness is invariant under symplectic blow-up and blow-down. This theorem follows from a general Relative/Absolute correspondence for a symplectic manifold together with a symplectic submanifold. A direct consequence is that symplectic uniruledness is a symplectic birational invariant. Here we use Guillemin and Sternberg's notion of cobordism as the symplectic analogue of the birational equivalence.Comment: To appear in Invent. Mat

    SamACO: variable sampling ant colony optimization algorithm for continuous optimization

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    An ant colony optimization (ACO) algorithm offers algorithmic techniques for optimization by simulating the foraging behavior of a group of ants to perform incremental solution constructions and to realize a pheromone laying-and-following mechanism. Although ACO is first designed for solving discrete (combinatorial) optimization problems, the ACO procedure is also applicable to continuous optimization. This paper presents a new way of extending ACO to solving continuous optimization problems by focusing on continuous variable sampling as a key to transforming ACO from discrete optimization to continuous optimization. The proposed SamACO algorithm consists of three major steps, i.e., the generation of candidate variable values for selection, the ants’ solution construction, and the pheromone update process. The distinct characteristics of SamACO are the cooperation of a novel sampling method for discretizing the continuous search space and an efficient incremental solution construction method based on the sampled values. The performance of SamACO is tested using continuous numerical functions with unimodal and multimodal features. Compared with some state-of-the-art algorithms, including traditional ant-based algorithms and representative computational intelligence algorithms for continuous optimization, the performance of SamACO is seen competitive and promising
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