13,991 research outputs found

    Adaptive particle swarm optimization

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    An adaptive particle swarm optimization (APSO) that features better search efficiency than classical particle swarm optimization (PSO) is presented. More importantly, it can perform a global search over the entire search space with faster convergence speed. The APSO consists of two main steps. First, by evaluating the population distribution and particle fitness, a real-time evolutionary state estimation procedure is performed to identify one of the following four defined evolutionary states, including exploration, exploitation, convergence, and jumping out in each generation. It enables the automatic control of inertia weight, acceleration coefficients, and other algorithmic parameters at run time to improve the search efficiency and convergence speed. Then, an elitist learning strategy is performed when the evolutionary state is classified as convergence state. The strategy will act on the globally best particle to jump out of the likely local optima. The APSO has comprehensively been evaluated on 12 unimodal and multimodal benchmark functions. The effects of parameter adaptation and elitist learning will be studied. Results show that APSO substantially enhances the performance of the PSO paradigm in terms of convergence speed, global optimality, solution accuracy, and algorithm reliability. As APSO introduces two new parameters to the PSO paradigm only, it does not introduce an additional design or implementation complexity

    Integrating Horizontal Gene Transfer and Common Descent to Depict Evolution and Contrast It with ‘‘Common Design

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    Horizontal gene transfer (HGT) and common descent interact in space and time. Because events of HGT co-occur with phylogenetic evolution, it is difficult to depict evolutionary patterns graphically. Tree-like representations of life’s diversification are useful, but they ignore the significance of HGT in evolutionary history, particularly of unicellular organisms, ancestors of multicellular life. Here we integrate the reticulated-tree model, ring of life, symbiogenesis whole-organism model, and eliminative pattern pluralism to represent evolution. Using Entamoeba histolytica alcohol dehydrogenase 2 (EhADH2), a bifunctional enzyme in the glycolytic pathway of amoeba, we illustrate how EhADH2 could be the product of both horizontally acquired features from ancestral prokaryotes (i.e. aldehyde dehydrogenase [ALDH] and alcohol dehydrogenase [ADH]), and subsequent functional integration of these enzymes into EhADH2, which is now inherited by amoeba via common descent. Natural selection has driven the evolution of EhADH2 active sites, which require specific amino acids (cysteine 252 in the ALDH domain; histidine 754 in the ADH domain), iron- and NAD1 as cofactors, and the substrates acetyl-CoA for ALDH and acetaldehyde for ADH. Alternative views invoking ‘‘common design’’ (i.e. the non-naturalistic emergence of major taxa independent from ancestry) to explain the interaction between horizontal and vertical evolution are unfounded

    Influence of expertise on the visual control strategies of athletes during competitive long jumping

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    Understanding performance of athletes in competition is required for enhancing the quality of how athletes co-adapt to the specific, changing constraints of those environments. In long jumping, for example, an athlete must co-adapt with these constraints while also meeting the challenging accuracy demands of the sport. Examining then how long jumpers with different levels of expertise navigate the competition environment is important. This analysis is necessary, given evidence from motor learning research showing that individuals with higher levels of expertise use different sources of information to guide their performance behaviors. In this study, key gait variables during the long jump run-up were recorded during performance at 8 competitions in the 2015 and 2016 Australian track and field seasons to examine the visual control strategies of athletes differing in expertise levels, when performing legal and foul jumps. No statistically significant differences were observed between jumpers differing in levels of expertise when comparing gait patterns in foul and legal jumps. However, different footfall variability curves did emerge that can advance current understanding of long jump run-ups. International-level athletes exhibited higher levels of functional variability during the initial phases of the run-up of legal jumps, with step adjustments spread across the whole of the run-up, compared to National-level athletes. Since athletes of lower levels of expertise exhibited a more stereotyped run-up profile, it is suggested that coaches and practitioners encourage more exploration in training of this group by incorporating increased levels of representative variability during practice. From a practical perspective, increasing variability in practice contexts could encourage National-level athletes to explore different movement solutions and (re)calibrate actions to changing environmental demands, providing more representative simulations of the competition environment
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