Multi-objective Estimation of Distribution Algorithm Based on Joint Modeling of Objectives and Variables

This paper proposes a new multi-objective estimation of distribution algorithm (EDA) based on joint modeling of objectives and variables. This EDA uses the multi-dimensional Bayesian network as its probabilistic model. In this way it can capture the dependencies between objectives, variables and objectives, as well as the dependencies learnt between variables in other Bayesian network-based EDAs. This model leads to a problem decomposition that helps the proposed algorithm to find better trade-off solutions to the multi-objective problem. In addition to Pareto set approximation, the algorithm is also able to estimate the structure of the multi-objective problem. To apply the algorithm to many-objective problems, the algorithm includes four different ranking methods proposed in the literature for this purpose. The algorithm is applied to the set of walking fish group (WFG) problems, and its optimization performance is compared with an evolutionary algorithm and another multi-objective EDA. The experimental results show that the proposed algorithm performs significantly better on many of the problems and for different objective space dimensions, and achieves comparable results on some compared with the other algorithms.

Distribution of the coal flow in the mill-duct system of the As Pontes Power Plant using CFD modeling

The efficiency of a Power Plant is affected by the distribution of the pulverized coal within the furnace. The coal, which is pulverized in the mills, is transported and distributed by the primary gas through the mill-ducts to the interior of the furnace. This is done with a double function: dry and enter the coal by different levels for optimizing the combustion in the sense that a complete combustion occurs with homogeneous heat fluxes to the walls. The mill-duct systems of a real Power Plant are very complex and they are not yet well understood. In particular, experimental data concerning the mass flows of coal to the different levels are very difficult to measure. CFD modeling can help to determine them. An Eulerian/Lagrangian approach is used due to the low solid–gas volume ratio.

Environmental niche variation and evolutionary diversification of the Brachypodium distachyon grass complex species in their native circum-Mediterranean range

PREMISE OF THE STUDY: We conducted environmental niche modeling (ENM) of the Brachypodium distachyon s.l. complex, a model group of two diploid annual grasses ( B. distachyon , B. stacei ) and their derived allotetraploid ( B. hybridum) , native to the circum-Mediterranean region. We (1) investigated the ENMs of the three species in their native range based on present and past climate data; (2) identifi ed potential overlapping niches of the diploids and their hybrid across four Quaternary windows; (3) tested whether speciation was associated with niche divergence/conservatism in the complex species; and (4) tested for the potential of the polyploid outperforming the diploids in the native range. M ETHODS: Geo-referenced data, altitude, and 19 climatic variables were used to construct the ENMs. We used paleoclimate niche models to trace the potential existence of ancestral gene fl ow among the hybridizing species of the complex. KEY RESULTS: Brachypodium distachyon grows in higher, cooler, and wetter places, B. stacei in lower, warmer, and drier places, and B. hybridum in places with intermediate climatic features. Brachypodium hybridum had the largest niche overlap with its parent niches, but a similar distribution range and niche breadth. C ONCLUSIONS: Each species had a unique environmental niche though there were multiple niche overlapping areas for the diploids across time, suggesting the potential existence of several hybrid zones during the Pleistocene and the Holocene. No evidence of niche divergence was found, suggesting that species diversifi cation was not driven by ecological speciation but by evolutionary history, though it could be associated to distinct environmental adaptations.

Fluorescence-intensity distribution analysis and its application in biomolecular detection technology

A methodology, fluorescence-intensity distribution analysis, has been developed for confocal microscopy studies in which the fluorescence intensity of a sample with a heterogeneous brightness profile is monitored. An adjustable formula, modeling the spatial brightness distribution, and the technique of generating functions for calculation of theoretical photon count number distributions serve as the two cornerstones of the methodology. The method permits the simultaneous determination of concentrations and specific brightness values of a number of individual fluorescent species in solution. Accordingly, we present an extremely sensitive tool to monitor the interaction of fluorescently labeled molecules or other microparticles with their respective biological counterparts that should find a wide application in life sciences, medicine, and drug discovery. Its potential is demonstrated by studying the hybridization of 5′-(6-carboxytetramethylrhodamine)-labeled and nonlabeled complementary oligonucleotides and the subsequent cleavage of the DNA hybrids by restriction enzymes.

Overcoming performance and convergence issues of discrete transform based modeling of crosslinking classical and reversible deactivated radical polymerizations

Population balances of polymer species in terms 'of discrete transforms with respect to counts of groups lead to tractable first order partial differential equations when ali rate constants are independent of chain length and loop formation is negligible [l]. Average molecular weights in the absence ofgelation are long known to be readily found through integration of an initial value problem. The extension to size distribution prediction is also feasible, but its performance is often lower to the one provided by methods based upon real chain length domain [2]. Moreover, the absence ofagood starting procedure and a higher numerical sensitivity hás decisively impaired its application to non-linear reversibly deactivated polymerizations, namely NMRP [3].

Distribution of halacarid species in sediment surface samples of Josephine Bank and Great Meteor Bank, Northeast Atlantic (Table 4)

In 22 samples, 6 from Josephine Bank and 16 from the Great Meteor Bank, 14 halacarid species were found and described. Halacarus spiniger n. sp., Copidognathus magniporus n. sp., Arhodeoporus lineatus n. sp., A. brevocularis n. sp., Coloboceras karamani n. sp., Scaptognathus minutus n. sp., and Atelopsalis newelli were hithero unknown. Acaromantis squilla Trouessart & Neumann and Atelopsalis tricuspis Trouessart were redescribed. Four larvae, probably belonging to Copidognathus longips Bartsch, C. tricorneata (Lohmann), Lohmannella falcata (Hodge), and Atelopsalis newelli n. sp. were described, two Scaptognathus larvae could not be identifird. To date only three species, Copidognathus tricorneata, Lohmannella falcata, and Scaptognathus minutus, have been found on both seamounts.