185 resultados para Markov processes.


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Many different individuals, who have their own expertise and criteria for decision making, are involved in making decisions on construction projects. Decision-making processes are thus significantly affected by communication, in which a dynamic performance of human intentions leads to unpredictable outcomes. In order to theorise the decision making processes including communication, it is argued here that the decision making processes resemble evolutionary dynamics in terms of both selection and mutation, which can be expressed by the replicator-mutator equation. To support this argument, a mathematical model of decision making has been made from an analogy with evolutionary dynamics, in which there are three variables: initial support rate, business hierarchy, and power of persuasion. On the other hand, a survey of patterns in decision making in construction projects has also been performed through self-administered mail questionnaire to construction practitioners. Consequently, comparison between the numerical analysis of mathematical model and the statistical analysis of empirical data has shown a significant potential of the replicator-mutator equation as a tool to study dynamic properties of intentions in communication.

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Asynchronous Optical Sampling (ASOPS) [1,2] and frequency comb spectrometry [3] based on dual Ti:saphire resonators operated in a master/slave mode have the potential to improve signal to noise ratio in THz transient and IR sperctrometry. The multimode Brownian oscillator time-domain response function described by state-space models is a mathematically robust framework that can be used to describe the dispersive phenomena governed by Lorentzian, Debye and Drude responses. In addition, the optical properties of an arbitrary medium can be expressed as a linear combination of simple multimode Brownian oscillator functions. The suitability of a range of signal processing schemes adopted from the Systems Identification and Control Theory community for further processing the recorded THz transients in the time or frequency domain will be outlined [4,5]. Since a femtosecond duration pulse is capable of persistent excitation of the medium within which it propagates, such approach is perfectly justifiable. Several de-noising routines based on system identification will be shown. Furthermore, specifically developed apodization structures will be discussed. These are necessary because due to dispersion issues, the time-domain background and sample interferograms are non-symmetrical [6-8]. These procedures can lead to a more precise estimation of the complex insertion loss function. The algorithms are applicable to femtosecond spectroscopies across the EM spectrum. Finally, a methodology for femtosecond pulse shaping using genetic algorithms aiming to map and control molecular relaxation processes will be mentioned.

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Nonlinear adjustment toward long-run price equilibrium relationships in the sugar-ethanol-oil nexus in Brazil is examined. We develop generalized bivariate error correction models that allow for cointegration between sugar, ethanol, and oil prices, where dynamic adjustments are potentially nonlinear functions of the disequilibrium errors. A range of models are estimated using Bayesian Monte Carlo Markov Chain algorithms and compared using Bayesian model selection methods. The results suggest that the long-run drivers of Brazilian sugar prices are oil prices and that there are nonlinearities in the adjustment processes of sugar and ethanol prices to oil price but linear adjustment between ethanol and sugar prices.

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The impacts of climate change on crop productivity are often assessed using simulations from a numerical climate model as an input to a crop simulation model. The precision of these predictions reflects the uncertainty in both models. We examined how uncertainty in a climate (HadAM3) and crop General Large-Area Model (GLAM) for annual crops model affects the mean and standard deviation of crop yield simulations in present and doubled carbon dioxide (CO2) climates by perturbation of parameters in each model. The climate sensitivity parameter (λ, the equilibrium response of global mean surface temperature to doubled CO2) was used to define the control climate. Observed 1966–1989 mean yields of groundnut (Arachis hypogaea L.) in India were simulated well by the crop model using the control climate and climates with values of λ near the control value. The simulations were used to measure the contribution to uncertainty of key crop and climate model parameters. The standard deviation of yield was more affected by perturbation of climate parameters than crop model parameters in both the present-day and doubled CO2 climates. Climate uncertainty was higher in the doubled CO2 climate than in the present-day climate. Crop transpiration efficiency was key to crop model uncertainty in both present-day and doubled CO2 climates. The response of crop development to mean temperature contributed little uncertainty in the present-day simulations but was among the largest contributors under doubled CO2. The ensemble methods used here to quantify physical and biological uncertainty offer a method to improve model estimates of the impacts of climate change.

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This paper considers the process of Participatory Varietal Selection (PVS) and presents approaches and ideas based on PVS activities conducted on upland rice throughout Ghana between 1997 and 2003. In particular the role of informal seed systems in PVS is investigated and implications for PVS design are identified. PVS programmes were conducted in two main agroecological zones, Forest and Savannah, with 1,578 and 1,143 mm of annual rainfall, respectively, and between 40 and 100 varieties tested at each site. In the Savannah zone IR12979-24-1 was officially released and in the Forest zone IDSA 85 was widely accepted by farmers. Two surveys were conducted in an area of the Forest zone to study mechanisms of spread. Here small amounts (1-2 kg) of seed of selected varieties had been given to 94 farmers. In 2002, 37% of 2,289 farmers in communities surveyed had already grown a PVS variety and had obtained seed via informal mechanisms from other farmers, i.e. through gift, exchange or purchase. A modified approach for PVS is presented which enables important issues identified in the paper to be accommodated. These issues include: utilising existing seed spread mechanisms; facilitating formal release of acceptable varieties; assessing post-harvest traits, and; the need for PVS to be an ongoing and sustainable process.

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Hot spots of endemism are regarded as important global sites for conservation as they are rich in threatened endemic species and currently experiencing extensive habitat loss. Targeting pre-emptive conservation action to sites that are currently relatively intact but which would be vulnerable to particular human activities if they occurred in the future is, however, also valuable but has received less attention. Here, we address this issue by using data on Endemic Bird Areas (EBAs). First, we identify the ecological factors that affect extinction risk in the face of particular human activities, and then use these insights to identify EBAs that should be priorities for pre-emptive conservation action. Threatened endemic species in EBAs are significantly more likely to be habitat specialists or relatively large-bodied than non-threatened species, when compared across avian families. Increasing habitat loss causes a significant increase in extinction risk among habitat specialists, but we found no evidence to suggest that the presence of alien species/human exploitation causes a significant increase in extinction risk among large-bodied species. This suggests that these particular human activities are contributing to high extinction risk among habitat specialists, but not among large-bodied species. Based on these analyses, we identify 39 EBAs containing 570 species (24% of the total in EBAs) that are not currently threatened with severe habitat loss, but would be ecologically vulnerable to future habitat loss should it occur. We show that these sites tend to be poorly represented in existing priority setting exercises involving hot spots, suggesting that vulnerability must be explicitly included within these exercises if such sites are to be adequately protected.

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Four multiparous cows with cannulas in the rumen and proximal duodenum were used in early lactation in a 4 x 4 Latin square experiment to investigate the effect of method of application of a fibrolytic enzyme product on digestive processes and milk production. The cows were given ad libitum a total mixed ration (TMR) composed of 57% (dry matter basis) forage (3:1 corn silage:grass silage) and 43% concentrates. The TMR contained (g/kg dry matter): 274 neutral detergent fiber, 295 starch, 180 crude protein. Treatments were TMR alone or TMR with the enzyme product added (2 kg/1000 kg TMR dry matter) either sprayed on the TMR 1 h before the morning feed (TMR-E), sprayed only on the concentrate the day before feeding (Concs-E), or infused into the rumen for 14 h/d (Rumen-E). There Was no significant effect on either feed intake or milk yield but both were highest on TMR-E. Rumen digestibility of dry matter, organic matter, and starch was unaffected by the enzyme. Digestibility of NDF was lowest on TMR-E in the rumen but highest postruminally. Total Tract digestibility was highest on TMR-E for dry matter, organic matter, and starch but treatment differences were nonsignificant for neutral detergent fiber: Corn silage stover retention time in the rumen was reduced by all enzyme treatments but postruminal transit time vas increased so the decline in total tract retention. time with enzymes was not significant. It is suggested that the tendency for enzymes to reduce particle retention time in the rumen may, by reducing the time available for fibrolysis to occur, at least partly explain the variability in the reported responses to enzyme treatment.

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The rate at which a given site in a gene sequence alignment evolves over time may vary. This phenomenon-known as heterotachy-can bias or distort phylogenetic trees inferred from models of sequence evolution that assume rates of evolution are constant. Here, we describe a phylogenetic mixture model designed to accommodate heterotachy. The method sums the likelihood of the data at each site over more than one set of branch lengths on the same tree topology. A branch-length set that is best for one site may differ from the branch-length set that is best for some other site, thereby allowing different sites to have different rates of change throughout the tree. Because rate variation may not be present in all branches, we use a reversible-jump Markov chain Monte Carlo algorithm to identify those branches in which reliable amounts of heterotachy occur. We implement the method in combination with our 'pattern-heterogeneity' mixture model, applying it to simulated data and five published datasets. We find that complex evolutionary signals of heterotachy are routinely present over and above variation in the rate or pattern of evolution across sites, that the reversible-jump method requires far fewer parameters than conventional mixture models to describe it, and serves to identify the regions of the tree in which heterotachy is most pronounced. The reversible-jump procedure also removes the need for a posteriori tests of 'significance' such as the Akaike or Bayesian information criterion tests, or Bayes factors. Heterotachy has important consequences for the correct reconstruction of phylogenies as well as for tests of hypotheses that rely on accurate branch-length information. These include molecular clocks, analyses of tempo and mode of evolution, comparative studies and ancestral state reconstruction. The model is available from the authors' website, and can be used for the analysis of both nucleotide and morphological data.

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This study begins to redress our lack of knowledge of the interactions between colonial hosts and their parasites by focusing on a novel host-parasite system. Investigations of freshwater bryozoan populations revealed that infection by myxozoan parasites is widespread. Covert infections were detected in all 5 populations studied and were often at high prevalence while overt infections were observed in only 1. Infections were persistent in populations subject to temporal sampling. Negative effects of infection were identified but virulence was low. Infection did not induce mortality in the environmental conditions studied. However, the production of statoblasts (dormant propagules) was greatly reduced in bryozoans with overt infections in comparison to uninfected bryozoans. Overtly-infected bryozoans also grew more slowly and had low fission rates relative to colonies lacking overt infection. Bryozoans with covert infections were smaller than uninfected bryozoans. High levels of vertical transmission were achieved through colony fission and the infection of statoblasts. Increased fission rates may be a strategy for hosts to escape from parasites but the parasite can also exploit the fragmentation of colonial hosts to gain vertical transmission and dispersal. Our study provides evidence that opportunities and constraints for host-parasite co-evolution can be highly dependent on organismal body plans and that low virulence may be associated with exploitation of colonial hosts by endoparasites.

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We describe a Bayesian method for investigating correlated evolution of discrete binary traits on phylogenetic trees. The method fits a continuous-time Markov model to a pair of traits, seeking the best fitting models that describe their joint evolution on a phylogeny. We employ the methodology of reversible-jump ( RJ) Markov chain Monte Carlo to search among the large number of possible models, some of which conform to independent evolution of the two traits, others to correlated evolution. The RJ Markov chain visits these models in proportion to their posterior probabilities, thereby directly estimating the support for the hypothesis of correlated evolution. In addition, the RJ Markov chain simultaneously estimates the posterior distributions of the rate parameters of the model of trait evolution. These posterior distributions can be used to test among alternative evolutionary scenarios to explain the observed data. All results are integrated over a sample of phylogenetic trees to account for phylogenetic uncertainty. We implement the method in a program called RJ Discrete and illustrate it by analyzing the question of whether mating system and advertisement of estrus by females have coevolved in the Old World monkeys and great apes.

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Hot spots of endemism are regarded as important global sites for conservation as they are rich in threatened endemic species and currently experiencing extensive habitat loss. Targeting pre-emptive conservation action to sites that are currently relatively intact but which would be vulnerable to particular human activities if they occurred in the future is, however, also valuable but has received less attention. Here, we address this issue by using data on Endemic Bird Areas (EBAs). First, we identify the ecological factors that affect extinction risk in the face of particular human activities, and then use these insights to identify EBAs that should be priorities for pre-emptive conservation action. Threatened endemic species in EBAs are significantly more likely to be habitat specialists or relatively large-bodied than non-threatened species, when compared across avian families. Increasing habitat loss causes a significant increase in extinction risk among habitat specialists, but we found no evidence to suggest that the presence of alien species/human exploitation causes a significant increase in extinction risk among large-bodied species. This suggests that these particular human activities are contributing to high extinction risk among habitat specialists, but not among large-bodied species. Based on these analyses, we identify 39 EBAs containing 570 species (24% of the total in EBAs) that are not currently threatened with severe habitat loss, but would be ecologically vulnerable to future habitat loss should it occur. We show that these sites tend to be poorly represented in existing priority setting exercises involving hot spots, suggesting that vulnerability must be explicitly included within these exercises if such sites are to be adequately protected.

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This article presents a statistical method for detecting recombination in DNA sequence alignments, which is based on combining two probabilistic graphical models: (1) a taxon graph (phylogenetic tree) representing the relationship between the taxa, and (2) a site graph (hidden Markov model) representing interactions between different sites in the DNA sequence alignments. We adopt a Bayesian approach and sample the parameters of the model from the posterior distribution with Markov chain Monte Carlo, using a Metropolis-Hastings and Gibbs-within-Gibbs scheme. The proposed method is tested on various synthetic and real-world DNA sequence alignments, and we compare its performance with the established detection methods RECPARS, PLATO, and TOPAL, as well as with two alternative parameter estimation schemes.

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Homopolymerization of alkylarylcarbenes derived from diazirine monomers that featured benzyl alcohol or phenol residues was found to lead to the production of soluble hyperbranched poly(aryl ether)s. The polymerization process was influenced by the solvents employed, monomer concentration, and the reaction time. An increase in the monomer concentration and reaction time was found to lead to an increase in the molecular weight characteristics of the resulting polymers as determined by gel permeation chromatography (GPC). The composition and architecture of the polyethers were determined by nuclear magnetic resonance (NMR) spectroscopic analysis and were found to be highly complex and dependent on the structure of the monomers used. All of the polymers were found to contain ether linkages formed via carbene insertion into O-H bonds, although polymers derived from phenolic carbenes also contained linkages arising from C-alkylation.

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Quantitative structure activity relationships (QSARs) have been developed to optimise the choice of nitrogen heterocyclic molecules that can be used to separate the minor actinides such as americium(III) from europium(III) in the aqueous PUREX raffinate of nuclear waste. Experimental data on distribution coefficients and separation factors (SFs) for 47 such ligands have been obtained and show SF values ranging from 0.61 to 100. The ligands were divided into a training set of 36 molecules to develop the QSAR and a test set of 11 molecules to validate the QSAR. Over 1500 molecular descriptors were calculated for each heterocycle and the Genetic Algorithm was used to select the most appropriate for use in multiple regression equations. Equations were developed fitting the separation factors to 6-8 molecular descriptors which gave r(2) values of >0.8 for the training set and values of >0.7 for the test set, thus showing good predictive quality. The descriptors used in the equations were primarily electronic and steric. These equations can be used to predict the separation factors of nitrogen heterocycles not yet synthesised and/or tested and hence obtain the most efficient ligands for lanthanide and actinide separation. (C) 2003 Elsevier B.V. All rights reserved.