932 resultados para Evolutionary particle swarm optimization
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Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2015
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Magdeburg, Univ., Fak. für Informatik, Diss., 2015
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Otto-von-Guericke-Universität Magdeburg, Fakultät für Mathematik, Univ., Dissertation, 2015
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n.s. no.91(1999)
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v.22:no.3(1938)
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We are interested in coupled microscopic/macroscopic models describing the evolution of particles dispersed in a fluid. The system consists in a Vlasov-Fokker-Planck equation to describe the microscopic motion of the particles coupled to the Euler equations for a compressible fluid. We investigate dissipative quantities, equilibria and their stability properties and the role of external forces. We also study some asymptotic problems, their equilibria and stability and the derivation of macroscopic two-phase models.
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The paper documents MINTOOLKIT for GNU Octave. MINTOOLKIT provides functions for minimization and numeric differentiation. The main algorithms are BFGS, LBFGS, and simulated annealing. Examples are given.
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Restriction site-associated DNA sequencing (RADseq) provides researchers with the ability to record genetic polymorphism across thousands of loci for nonmodel organisms, potentially revolutionizing the field of molecular ecology. However, as with other genotyping methods, RADseq is prone to a number of sources of error that may have consequential effects for population genetic inferences, and these have received only limited attention in terms of the estimation and reporting of genotyping error rates. Here we use individual sample replicates, under the expectation of identical genotypes, to quantify genotyping error in the absence of a reference genome. We then use sample replicates to (i) optimize de novo assembly parameters within the program Stacks, by minimizing error and maximizing the retrieval of informative loci; and (ii) quantify error rates for loci, alleles and single-nucleotide polymorphisms. As an empirical example, we use a double-digest RAD data set of a nonmodel plant species, Berberis alpina, collected from high-altitude mountains in Mexico.
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BACKGROUND: Highway maintenance workers are constantly and simultaneously exposed to traffic-related particle and noise emissions, and both have been linked to increased cardiovascular morbidity and mortality in population-based epidemiology studies. OBJECTIVES: We aimed to investigate short-term health effects related to particle and noise exposure. METHODS: We monitored 18 maintenance workers, during as many as five 24-hour periods from a total of 50 observation days. We measured their exposure to fine particulate matter (PM2.5), ultrafine particles, noise, and the cardiopulmonary health endpoints: blood pressure, pro-inflammatory and pro-thrombotic markers in the blood, lung function and fractional exhaled nitric oxide (FeNO) measured approximately 15 hours post-work. Heart rate variability was assessed during a sleep period approximately 10 hours post-work. RESULTS: PM2.5 exposure was significantly associated with C-reactive protein and serum amyloid A, and negatively associated with tumor necrosis factor α. None of the particle metrics were significantly associated with von Willebrand factor or tissue factor expression. PM2.5 and work noise were associated with markers of increased heart rate variability, and with increased HF and LF power. Systolic and diastolic blood pressure on the following morning were significantly associated with noise exposure after work, and non-significantly associated with PM2.5. We observed no significant associations between any of the exposures and lung function or FeNO. CONCLUSIONS: Our findings suggest that exposure to particles and noise during highway maintenance work might pose a cardiovascular health risk. Actions to reduce these exposures could lead to better health for this population of workers.
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Rubisco is responsible for the fixation of CO2 into organic compounds through photosynthesis and thus has a great agronomic importance. It is well established that this enzyme suffers from a slow catalysis, and its low specificity results into photorespiration, which is considered as an energy waste for the plant. However, natural variations exist, and some Rubisco lineages, such as in C4 plants, exhibit higher catalytic efficiencies coupled to lower specificities. These C4 kinetics could have evolved as an adaptation to the higher CO2 concentration present in C4 photosynthetic cells. In this study, using phylogenetic analyses on a large data set of C3 and C4 monocots, we showed that the rbcL gene, which encodes the large subunit of Rubisco, evolved under positive selection in independent C4 lineages. This confirms that selective pressures on Rubisco have been switched in C4 plants by the high CO2 environment prevailing in their photosynthetic cells. Eight rbcL codons evolving under positive selection in C4 clades were involved in parallel changes among the 23 independent monocot C4 lineages included in this study. These amino acids are potentially responsible for the C4 kinetics, and their identification opens new roads for human-directed Rubisco engineering. The introgression of C4-like high-efficiency Rubisco would strongly enhance C3 crop yields in the future CO2-enriched atmosphere.
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We study the properties of the well known Replicator Dynamics when applied to a finitely repeated version of the Prisoners' Dilemma game. We characterize the behavior of such dynamics under strongly simplifying assumptions (i.e. only 3 strategies are available) and show that the basin of attraction of defection shrinks as the number of repetitions increases. After discussing the difficulties involved in trying to relax the 'strongly simplifying assumptions' above, we approach the same model by means of simulations based on genetic algorithms. The resulting simulations describe a behavior of the system very close to the one predicted by the replicator dynamics without imposing any of the assumptions of the analytical model. Our main conclusion is that analytical and computational models are good complements for research in social sciences. Indeed, while on the one hand computational models are extremely useful to extend the scope of the analysis to complex scenar
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The goal of the present work was assess the feasibility of using a pseudo-inverse and null-space optimization approach in the modeling of the shoulder biomechanics. The method was applied to a simplified musculoskeletal shoulder model. The mechanical system consisted in the arm, and the external forces were the arm weight, 6 scapulo-humeral muscles and the reaction at the glenohumeral joint, which was considered as a spherical joint. The muscle wrapping was considered around the humeral head assumed spherical. The dynamical equations were solved in a Lagrangian approach. The mathematical redundancy of the mechanical system was solved in two steps: a pseudo-inverse optimization to minimize the square of the muscle stress and a null-space optimization to restrict the muscle force to physiological limits. Several movements were simulated. The mathematical and numerical aspects of the constrained redundancy problem were efficiently solved by the proposed method. The prediction of muscle moment arms was consistent with cadaveric measurements and the joint reaction force was consistent with in vivo measurements. This preliminary work demonstrated that the developed algorithm has a great potential for more complex musculoskeletal modeling of the shoulder joint. In particular it could be further applied to a non-spherical joint model, allowing for the natural translation of the humeral head in the glenoid fossa.