931 resultados para model-based reasoning


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Because weed eradication programs commonly take 10 or more years to complete, there is a need to evaluate progress toward the eradication objective. We present a simple model, based on information that is readily obtainable, that assesses conformity to the delimitation and extirpation criteria for eradication. It is applied to the program currently targeting the annual parasitic weed, branched broomrape, in South Australia. The model consists of delimitation and extirpation (E) measures plotted against each other to form an 'eradograph.' Deviations from the 'ideal' eradograph plot can inform tactical responses, e.g., increases in survey and/or control effort. Infestations progress from the active phase to the monitoring phase when no plants have been detected for at least 12 mo. They revert to the active phase upon further detection of plants. We summarize this process for the invasion as a whole in a state-and-transition model. Using this model we demonstrate that the invasion is unlikely to be delimited unless the amount of newly detected infested area decreases, on average, by at least 50% per annum. As a result of control activities implemented, on average approximately 70% (range, 44 to 86%) of active infestations progressed to the monitoring phase in the year following their detection. Simulations suggest that increasing this rate of transition will not increase E to a significant extent. The rate of reversion of infestations from the monitoring phase to the active phase decreased logarithmically with time since last detection, but it is likely that lower rates of reversion would accelerate the trend toward extirpation. Program performance with respect to the delimitation criterion has been variable; performance with respect to the extirpation criterion would be improved considerably by the development and application of cost-effective methods for eliminating branched broomrape soil seed populations.

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In this article we offer a single case study using an action research method for gathering and analysing data offering insights valuable to both design and research supervision practice. We do not attempt to generalise from this single case, but offer it as an instance that can improve our understanding of research supervision practice. We question the conventional ‘dyadic’ models of research supervision and outline a more collaborative model, based on the signature pedagogy of architecture: the design studio. A novel approach to the supervision of creatively oriented post-graduate students is proposed, including new approaches to design methods and participatory supervision that draw on established design studio practices. This model collapses the distance between design and research activities. Our case study involving Research Masters student supervision in the discipline of Architecture, shows how ‘connected learning’ emerges from this approach. This type of learning builds strong elements of creativity and fun, which promote and enhance student engagement. The results of our action research suggests that students learn to research more easily in such an environment and supervisory practices are enhanced when we apply the techniques and characteristics of design studio pedagogy to the more conventional research pedagogies imported from the humanities. We believe that other creative disciplines can apply similar tactics to enrich both the creative practice of research and the supervision of HDR students.

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Tie-lines between the corundum and spinel solid solutions have been determined experimentally at 1823 K. Next, activities of FeCr2O4 and FeAl2O4 in the spinel solid solution were determined by combining the tie-line data with literature values for the activities of Cr2O3 and Al2O3 in the corundum phase. Activities and the Gibbs energy of mixing for the spinel solid solution were also obtained from a model based on cation distribution between nonequivalent crystallographic sites in the oxide lattice. The difference between the Gibbs energy of mixing obtained experimentally and from the model has been attributed to a strain enthalpy term which is relatively unchanged in magnitude from the reported at 1373 K. The integral enthalpy of mixing obtained from experimental data at 1373 and 1823 K using the second law is compared with the model result.

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Parthenium hysterophorus is a weed of global significance causing severe economic, environmental, human and animal health problems in Asia, Africa, Australia and the Pacific. In South Asia, P. hysterophorus occurs in India, Pakistan, Sri Lanka, Bangladesh and Nepal. A host-specific leaf-feeding beetle Zygogramma bicolorata from Mexico was introduced into India in 1984, as a biological control agent for P. hysterophorus. In this study, a GIS-based distribution map of P. hysterophorus and its biological control agent Z. bicolorata in South Asia based on meta-analysis is presented. The map highlights the limited published information on P. hysterophorus incidence in many of the states and territories in India, as well as in neighbouring Bangladesh, Bhutan, Nepal and Pakistan. Incidence of Z. bicolorata was recorded as three distinct clusters, covering many states in India. In Pakistan, Z. bicolorata was recorded in the Punjab region bordering India. A CLIMEX model based on the current distribution of Z. bicolorata in India suggests that the geographic range of this agent in India and Pakistan can extend to other P. hysterophorus-infested areas in the region. The CLIMEX model also suggests that all of Bangladesh and Sri Lanka, and parts of Nepal are climatically suitable for Z. bicolorata.

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Understanding the effects of different types and quality of data on bioclimatic modeling predictions is vital to ascertaining the value of existing models, and to improving future models. Bioclimatic models were constructed using the CLIMEX program, using different data types – seasonal dynamics, geographic (overseas) distribution, and a combination of the two – for two biological control agents for the major weed Lantana camara L. in Australia. The models for one agent, Teleonemia scrupulosa Stål (Hemiptera:Tingidae) were based on a higher quality and quantity of data than the models for the other agent, Octotoma scabripennis Guérin-Méneville (Coleoptera: Chrysomelidae). Predictions of the geographic distribution for Australia showed that T. scrupulosa models exhibited greater accuracy with a progressive improvement from seasonal dynamics data, to the model based on overseas distribution, and finally the model combining the two data types. In contrast, O. scabripennis models were of low accuracy, and showed no clear trends across the various model types. These case studies demonstrate the importance of high quality data for developing models, and of supplementing distributional data with species seasonal dynamics data wherever possible. Seasonal dynamics data allows the modeller to focus on the species response to climatic trends, while distributional data enables easier fitting of stress parameters by restricting the species envelope to the described distribution. It is apparent that CLIMEX models based on low quality seasonal dynamics data, together with a small quantity of distributional data, are of minimal value in predicting the spatial extent of species distribution.

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There are two recognized forms of the disease net blotch of barley: the net form caused by Pyrenophora teres f. teres (PTT) and the spot form caused by P. teres f. maculata (PTM). In this study, amplified fragment length polymorphism analysis was used to investigate the genetic diversity and population structure of 60 PTT and 64 PTM isolates collected across Australia (66 isolates) and in the south-western Cape of South Africa (58 isolates). For comparison, P. tritici-repentis, Exserohilum rostratum and Bipolaris sorokiniana samples were also included in the analyses. Both distance-and model-based cluster analyses separated the PTT and PTM isolates into two strongly divergent genetic groups. Significant variation was observed both among the South African and Australian populations of PTT and PTM and among sampling locations for the PTT samples. Results suggest that sexual reproduction between the two forms is unlikely and that reproduction within the PTT and PTM groups occurs mainly asexually.

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Isothermal-isobaric ensemble Monte Carlo simulation studies of adamantane have been carried out at different temperatures. Thermodynamic properties and radial distribution functions calculated by employing a simple potential model based on sitesite interactions show good agreement with experiment and suggest that the solid is orientationally disordered at high temperatures.

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The oxidative degradation of poly(acrylic acid) (PAA), a water soluble polymer, was studied at various temperatures with different concentrations of persulfates, potassium persulfate (KPS), ammonium persulfate (APS) and sodium persulfate (SPS). The photodegradation of PAA was also examined with APS as oxidizer. The degraded samples were analyzed for the time evolution of molecular weight distribution by gel permeation chromatography. A theoretical model based on the continuous distribution kinetics was developed that accounted for the polymer degradation and the dissociation of persulfate. The rate coefficients for the oxidative and photooxidative degradation of PAA were determined from the parametric fit of the model with experimental data. The rate of degradation increased with increasing amount of persulfate in both oxidative and photooxidative degradation. The rate of degradation also increased with increasing temperature in the case of oxidative degradation.

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Microsatellite markers were used to examine spatio-temporal genetic variation in the endangered eastern freshwater cod Maccullochella ikei in the Clarence River system, eastern Australia. High levels of population structure were detected. A model-based clustering analysis of multilocus genotypes identified four populations that were highly differentiated by F-statistics (FST = 0· 09 − 0· 49; P < 0· 05), suggesting fragmentation and restricted dispersal particularly among upstream sites. Hatchery breeding programmes were used to re-establish locally extirpated populations and to supplement remnant populations. Bayesian and frequency-based analyses of hatchery fingerling samples provided evidence for population admixture in the hatchery, with the majority of parental stock sourced from distinct upstream sites. Comparison between historical and contemporary wild-caught samples showed a significant loss of heterozygosity (21%) and allelic richness (24%) in the Mann and Nymboida Rivers since the commencement of stocking. Fragmentation may have been a causative factor; however, temporal shifts in allele frequencies suggest swamping with hatchery-produced M. ikei has contributed to the genetic decline in the largest wild population. This study demonstrates the importance of using information on genetic variation and population structure in the management of breeding and stocking programmes, particularly for threatened species.

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The quality of species distribution models (SDMs) relies to a large degree on the quality of the input data, from bioclimatic indices to environmental and habitat descriptors (Austin, 2002). Recent reviews of SDM techniques, have sought to optimize predictive performance e.g. Elith et al., 2006. In general SDMs employ one of three approaches to variable selection. The simplest approach relies on the expert to select the variables, as in environmental niche models Nix, 1986 or a generalized linear model without variable selection (Miller and Franklin, 2002). A second approach explicitly incorporates variable selection into model fitting, which allows examination of particular combinations of variables. Examples include generalized linear or additive models with variable selection (Hastie et al. 2002); or classification trees with complexity or model based pruning (Breiman et al., 1984, Zeileis, 2008). A third approach uses model averaging, to summarize the overall contribution of a variable, without considering particular combinations. Examples include neural networks, boosted or bagged regression trees and Maximum Entropy as compared in Elith et al. 2006. Typically, users of SDMs will either consider a small number of variable sets, via the first approach, or else supply all of the candidate variables (often numbering more than a hundred) to the second or third approaches. Bayesian SDMs exist, with several methods for eliciting and encoding priors on model parameters (see review in Low Choy et al. 2010). However few methods have been published for informative variable selection; one example is Bayesian trees (O’Leary 2008). Here we report an elicitation protocol that helps makes explicit a priori expert judgements on the quality of candidate variables. This protocol can be flexibly applied to any of the three approaches to variable selection, described above, Bayesian or otherwise. We demonstrate how this information can be obtained then used to guide variable selection in classical or machine learning SDMs, or to define priors within Bayesian SDMs.

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Analytical models of IEEE 802.11-based WLANs are invariably based on approximations, such as the well-known mean-field approximations proposed by Bianchi for saturated nodes. In this paper, we provide a new approach for modeling the situation when the nodes are not saturated. We study a State Dependent Attempt Rate (SDAR) approximation to model M queues (one queue per node) served by the CSMA/CA protocol as standardized in the IEEE 802.11 DCF. The approximation is that, when n of the M queues are non-empty, the attempt probability of the n non-empty nodes is given by the long-term attempt probability of n saturated nodes as provided by Bianchi's model. This yields a coupled queue system. When packets arrive to the M queues according to independent Poisson processes, we provide an exact model for the coupled queue system with SDAR service. The main contribution of this paper is to provide an analysis of the coupled queue process by studying a lower dimensional process and by introducing a certain conditional independence approximation. We show that the numerical results obtained from our finite buffer analysis are in excellent agreement with the corresponding results obtained from ns-2 simulations. We replace the CSMA/CA protocol as implemented in the ns-2 simulator with the SDAR service model to show that the SDAR approximation provides an accurate model for the CSMA/CA protocol. We also report the simulation speed-ups thus obtained by our model-based simulation.

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Tensile experiments on a fine-grained single-phase Mg–Zn–Al alloy (AZ31) at 673 K revealed superplastic behavior with an elongation to failure of 475% at 1 × 10−4 s−1 and non-superplastic behavior with an elongation to failure of 160% at 1 × 10−2 s−1; the corresponding strain rate sensitivities under these conditions were 0.5 and 0.2, respectively. Measurements indicated that the grain boundary sliding (GBS) contribution to strain ξ was 30% under non-superplastic conditions; there was also a significant sharpening in texture during such deformation. Under superplastic conditions, ξ was 50% at both low and high elongations of 20% and 120%; the initial texture became more random under such conditions. In non-superplastic conditions, deformation occurred under steady-state conditions without grain growth before significant flow localization whereas, under superplastic conditions, there was grain growth during the early stages of deformation, leading to strain hardening. The grains retained equiaxed shapes under all experimental conditions. Superplastic deformation is attributed to GBS, while non-superplastic deformation is attributed to intragranular dislocation creep with some contribution from GBS. The retention of equiaxed grain shapes during dislocation creep is consistent with a model based on local recovery related to the disturbance of triple junctions.

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Time series, from a narrow point of view, is a sequence of observations on a stochastic process made at discrete and equally spaced time intervals. Its future behavior can be predicted by identifying, fitting, and confirming a mathematical model. In this paper, time series analysis is applied to problems concerning runwayinduced vibrations of an aircraft. A simple mathematical model based on this technique is fitted to obtain the impulse response coefficients of an aircraft system considered as a whole for a particular type of operation. Using this model, the output which is the aircraft response can be obtained with lesser computation time for any runway profile as the input.

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A recent theoretical model developed by Imparato et al. Phys of the experimentally measured heat and work effects produced by the thermal fluctuations of single micron-sized polystyrene beads in stationary and moving optical traps has proved to be quite successful in rationalizing the observed experimental data. The model, based on the overdamped Brownian dynamics of a particle in a harmonic potential that moves at a constant speed under a time-dependent force, is used to obtain an approximate expression for the distribution of the heat dissipated by the particle at long times. In this paper, we generalize the above model to consider particle dynamics in the presence of colored noise, without passing to the overdamped limit, as a way of modeling experimental situations in which the fluctuations of the medium exhibit long-lived temporal correlations, of the kind characteristic of polymeric solutions, for instance, or of similar viscoelastic fluids. Although we have not been able to find an expression for the heat distribution itself, we do obtain exact expressions for its mean and variance, both for the static and for the moving trap cases. These moments are valid for arbitrary times and they also hold in the inertial regime, but they reduce exactly to the results of Imparato et al. in appropriate limits. DOI: 10.1103/PhysRevE.80.011118 PACS.

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Parthenium (Parthenium hysterophorus L.), a major weed causing economic, environmental, and human and animal health problems in Australia and several countries in Asia, Africa, and the Pacific, has been a target for biological control in Australia since the mid-1970s. Nine species of insects and two rust fungi have been introduced as biological control agents into Australia. These include Carmenta sp. nr ithacae, a root feeding agent from Mexico. The larvae of C. sp. nr ithacae bore through the stem-base into the root where they feed on the cortical tissue of the taproot. During 1998-2002, 2,816 larval-infested plants and 387 adults were released at 31 sites across Queensland, Australia. Evidence of field establishment was first observed in two of the release sites in central Queensland in 2004. Annual surveys at these sites and nonrelease sites during 2006-2011 showed wide variations in the incidence and abundance of C. sp. nr ithacae between years and sites. Surveys at three of the nine release sites in northern Queensland and 16 of the 22 release sites in central Queensland confirmed the field establishment of C. sp. nr ithacae in four release sites and four nonrelease sites, all in central Queensland. No field establishment was evident in the inland region or in northern Queensland. A CLIMEX model based on the native range distribution of C. sp. nr ithacae predicts that areas east of the dividing range along the coast are more suitable for field establishment than inland areas. Future efforts to redistribute this agent should be restricted to areas identified as climatically favorable by the CLIMEX model.