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This paper presents a continuous time surplus maximization bi-objective user equilibrium (C-TSmaxBUE) model, in which the users' variability toward the time and toll trade-off in a tolled road network is explicitly considered. Different users are assigned with different ratios of the time saved per unit of money (RTSMs), the values of which represent the different expectations to trade more money for less travel time. Infinite indifference curves are then generated by considering continuously distributed RTSMs in the population. Accordingly, we extend the definition of the path-based time surplus for the C-TSmaxBUE model, which can be formulated as a Beckmann-type mathematical program operating in the space of RTSM boundaries. To solve the problem, we develop a path-based single-boundary adjustment (SBA) algorithm that fits the non-additive structure of the model. The algorithm involves a Newton-type flow equilibration procedure that simultaneously adjusts RTSM boundaries and path flows, as well as a column generation scheme that firstly enumerates all efficient paths and then identifies the paths that have the potential to reduce generalized travel times. Numerical results on a small network show the feature of the equilibrium flow pattern, whereas instances of practical size confirm that SBA is an efficient tool to obtain high-quality equilibrium solutions. Compared to the original TSmaxBUE problem, we found that a larger set of efficient paths will be used when the users' heterogeneity is considered. • Propose a C-TSmaxBUE model. • Prove C-TSmaxBUE is a generalization of UE, GUE, and TSmaxBUE. • Develop an efficient path-based algorithm for solving the C-TSmaxBUE model. • Demonstrate features of C-TSmaxBUE and applicability of the algorithm. [ABSTRACT FROM AUTHOR]

The equation of state based on the Group Contribution – Polar Perturbed Chain – Statistical Associating Fluid Theory (GC-PPC-SAFT), which is PC-SAFT combined with the group contribution proposed by Tamouza et al., Fluid Phase Equilib. 2004; 222–223:67–76 and a polar term developed by NguyenHuynh et al., Fluid Phase Equilib . 2008; 264 (1–2):62–75, is employed here to model the solubility of hydrogen in oxygenated compounds mixtures such as alcohols, ethers, diols, aldehydes. Our analysis shows that in such systems, the gas solubility may be driven by available volume effects. For this reason, a modified version of this equation of state taking into account non-additive segment diameters, is used in this work. Systematic tests are performed on binary mixtures and a predictive scheme is proposed. A correlation based on the group contribution method is also suggested as a predictive way to determine the non-additive parameter (l ij ). Correlations and predictions are qualitatively and quantitatively satisfactory. The deviations are within the experimental uncertainty (∼10%). [ABSTRACT FROM AUTHOR]

In the quest for greater autonomy, there is an increasing need for solutions that would enable a large set of robots to coalesce and perform complicated multi-robot tasks. This problem, also known as the multi-robot coalition formation problem has been traditionally approached as a single objective optimization problem. However, robots in the real world have to optimize multiple conflicting criteria such as battery life, number of completed tasks, and distance traveled. Researchers have only recently addressed the robot coalition formation problem as a multi-objective optimization problem, however the proposed solutions have computational bottlenecks that make them unsuitable for real time robotic applications. In this paper we address the issue of scalability by proposing parallelized algorithms in the CUDA programming framework. NSGA-II and PAES algorithm have been parallelized due to their suitability to the coalition formation domain as outlined in our previous work. The parallelized versions of these algorithms have been applied to both the additive and non-additive coalition formation environments. Simulations have been performed in the player/stage environment to validate the applicability of our approach to real robot situations. Results establish that the multi-point PAES parallel variant yields significant performance gains in terms of running time and solution quality when the problem is scaled to deal with large inputs. This suggests that the algorithm may be viable for real time robotic applications. Experiments demonstrate significant speedup when the proposed parallel algorithms were compared with the serial solutions proposed earlier. [ABSTRACT FROM AUTHOR]

• An improve heterosis prediction system including dominance and SCA models have been developed and applied to the prediction of heterosis in cucumber. • Genetic distance (GD) is not suitable for the prediction of heterosis in cucumber. • Compared with the GD model, the predictive abilities of the dominance model and the SCA model were improved by 0.15∼0.74 and 0.15∼0.59, respectively. The heterosis prediction has an essential role in hybrid breeding. The prediction of heterosis is highly dependable upon the selection of an efficient method, however, fewer methods have been used till date which lack or unable to explain several important aspects in heterosis prediction. Thus, in our experiment, we tried to explore a new heterosis prediction system based on genomic prediction, in cucumber breeding. Two models, SNP-BLUP and GBLUP were used for genomic prediction model training. The additive, and dominance components were estimated by SNP-BLUP; General combining ability (GCA), and special combining ability (SCA) components were estimated by GBLUP. We explored the correlation of these four model components, the genetics distances with heterosis. The our results show that both the dominance and SCA have stronger correlations with heterosis (r = 0.36∼0.73). While genetic distance, additive model component, and GCA have relatively weak or no significant correlations with heterosis, which may not be suitable for the prediction of heterosis. Therefore, the GD model, Dominance model, and SCA model based on genetic distance, dominance, and SCA predictors were established, respectively. Compared with the GD model, the predictive abilities of the Dominance model and the SCA model were improved by 0.15∼0.74 and 0.15∼0.59, respectively. In conclusion, we have developed an improved heterosis prediction system, which might offer valuable information for cucumber breeding and also provide a reference for the prediction of heterosis in other horticulture crops. [ABSTRACT FROM AUTHOR]

Abstract: Mixtures of two redox-active compounds with dissimilar diffusion coefficients produce non-additive mass-transfer limited currents. Similarly, in the potential range where three redox-active species, decamethylferrocene (dMeFc), ferrocene (Fc) and N-methylphenothiazine (MePTZ), are oxidized simultaneously with rates controlled by linear diffusion, electrogenerated radicals diffusing outwards from the electrode react with original species diffusing towards the electrode from the bulk; thus, Fc + reacts with dMeFc producing Fc and dMeFc +, while MePTZ + reacts with both Fc and dMeFc producing MePTZ together with Fc + and dMeFc +. These processes replace the flux of dMeFc with Fc at the second current plateau (referring to normal pulse voltammetry), and the fluxes of both dMeFc and Fc with MePTZ at the third plateau. Analogous results have been obtained and analyzed with two other multicomponent systems undergoing multiple sequential electron transfers, namely dMeFc/Fc/TPTA and dMeFc/TTF (TPTA: tri-N-p-tolylamine; TTF: tetrathiafulvalene). Since the diffusion coefficients of the three species are different, the mass-transfer limited currents of the second and third oxidation waves are not equal to the sum of the currents that each component would have produced if it were in the solution alone. Numerical simulations of the experimental voltammograms using diffusion coefficients measured independently support this mechanism. Multicomponent systems are encountered frequently in practice and our results identify one significant (∼10%) source of error in quantitative voltammetric analysis. Ways around the problem are summarized in the conclusions section. [Copyright &y& Elsevier]

• Novel mesocosm design employed to study litter decomposition. • Litter mixing with invasive species caused non-additive decomposition. • Non-additive decomposition varied between native species. • Decomposition rate was strongly correlated with initial litter chemical properties. • Leaching of phenolics from invasive litter suppressed microbial respiration. Invasive alien plants are a worldwide problem, causing substantial damage to biodiversity as well as economies. Recent studies suggest invasive plants may also alter fundamental ecosystem processes such as nutrient and carbon cycling in soil by depositing chemically distinct leaf litter. Here, we used laboratory microcosms to test whether the chemical properties of Rhododendron ponticum litter, an invasive shrub in Britain, lead to slower decomposition than that of native (or naturalised) species with labile litter (Acer pseudoplatanus and Fraxinus excelsior), but not relative to the recalcitrant litter of Quercus petraea. Leading from this, we hypothesised that the labile native litter decomposition rate is reduced when mixed with R. ponticum litter in non-additive responses, with the strength of these responses increasing with the proportion of R. ponticum in litter mixes (25%, 50% and 75% R. ponticum). Over the incubation period, the decomposition (measured as the microbial respiration rate) of unmixed R. ponticum litter was significantly lower than that of A. pseudoplatanus and F. excelsior , but not Q. petraea. When mixed with R. ponticum (50%), F. excelsior litter decomposition was slowed, whilst no effect was seen for Q. petraea. However, A. pseudoplatanus litter decomposition was enhanced, contrary to expectation. The strength of the non-additive decomposition responses did not vary with different proportions of R. ponticum to the other species, with only the 50% mixtures showing significant non-additive respiration rates. Litter chemical properties were highly associated with decomposition rates, with both phenolic content and C:N ratio negatively correlated with microbial respiration. To test the influence of phenolics on litter decomposition, leachates of R. ponticum litter with phenolics present or removed (via activated carbon) were added to microcosms containing the native species litter. Microbial respiration in F. excelsior microcosms was lower when R. ponticum leachate contained phenolics. For A. pseudoplatanus and Q. petraea litter, no effect of leachate treatment was observed. Our results show that invasive litter chemistry can alter the decomposition of native litter, with the impact varying between species. Altered decomposition rates could cause plant-soil feedbacks, leading to altered soil nutrient concentrations. The novel soil conditions may favour the invader, increasing its dominance, whilst negatively influencing native species possessing greater nutrient demands. [ABSTRACT FROM AUTHOR]