181 resultados para graphical factor models


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Exponential and sigmoidal functions have been suggested to describe the bulk density profiles of crusts. The present work aims to evaluate these conceptual models using high resolution X-radiography. Repacked seedbeds from two soil materials, air-dried or prewetted by capillary rise, were subjected to simulated rain, which resulted in three types of structural crusts, namely, slaking, infilling, and coalescing. Bulk density distributions with depth were generated using high-resolution (70 mum), calibrated X-ray images of slices from the resin-impregnated crusted seedbeds. The bulk density decreased progressively with depth, which supports the suggestion that a crust should be considered as a nonuniform layer. For the slaking and the coalescing crusts, the exponential function underestimated the strong change in bulk density across the morphologically defined transition between the crust and the underlying material; the sigmoidal function provided a better description. Neither of these crust models effectively described the shape of the bulk density profiles through the whole seedbed. Below the infilling and slaking crusts, bulk density increased linearly with depth as a result of slumping. In the coalescing crusted seedbed, the whole seedbed uniformly collapsed and most of the bulk density change within the crust could be ascribed to slumping (0.33 g cm(-3)) rather than to crusting (0.12 g cm(-3)). Finally, (i) X-radiography appears as a unique tool to generate high resolution bulk density profiles and (ii) in structural crusts, bulk density profiles could be modeled using the existing exponential and sigmoidal crusting models, provided a slumping model would be coupled.

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A generalised ladder operator is used to construct the conserved operators for any one-dimensional lattice model derived from the Yang-Baxter equation. As an example, the low order conserved operators for the XYh model are calculated explicitly.

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Perianth development is specifically disrupted in mutants of the PETAL LOSS (PTL) gene, particularly petal initiation and orientation. We have cloned PTL and show that it encodes a plant-specific trihelix transcription factor, one of a family previously known only as regulators of light-controlled genes. PTL transcripts were detected in the early-developing flower, in four zones between the initiating sepals and in their developing margins. Strong misexpression of PTL in a range of tissues universally results in inhibition of growth, indicating that its normal role is to suppress growth between initiating sepals, ensuring that they remain separate. Consistent with this, sepals are sometimes fused in ptl single mutants, but much more frequently in double mutants with either of the organ boundary genes cup-shaped cotyledon1 or 2. Expression of PTL within the newly arising sepals is apparently prevented by the PINOID auxin-response gene. Surprisingly, PTL expression could not be detected in petals during the early stages of their development, so petal defects associated with PTL loss of function may be indirect, perhaps involving disruption to signalling processes caused by overgrowth in the region. PTL-driven reporter gene expression was also detected at later stages in the margins of expanding sepals, petals and stamens, and in the leaf margins; thus, PTL may redundantly dampen lateral outgrowth of these organs, helping define their final shape.

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One of the primary personality dimensions or traits that has consistently been linked to substance abuse is impulsivity. However, impulsivity is not a homogenous construct and although many of the measures of impulsivity are correlated, the most recent review of published factor analytic studies has proposed two independent dimensions of impulsivity: reward sensitivity, reflecting one of the primary dimension of J. A. Gray's personality theory, and rash impulsiveness. These two facets of impulsivity derived from the field of personality research parallel recent developments in the neurosciences where changes in the incentive value of rewarding substances has been linked to alterations in neural substrates involved in reward seeking and with a diminished capacity to inhibit behavior due to chronic drug exposure. In this paper, we propose a model that integrates the findings from research into individual differences with recent models of neural substrates implicated in the development of substance misuse. (C) 2004 Elsevier Ltd. All rights reserved.

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Models of population dynamics are commonly used to predict risks in ecology, particularly risks of population decline. There is often considerable uncertainty associated with these predictions. However, alternatives to predictions based on population models have not been assessed. We used simulation models of hypothetical species to generate the kinds of data that might typically be available to ecologists and then invited other researchers to predict risks of population declines using these data. The accuracy of the predictions was assessed by comparison with the forecasts of the original model. The researchers used either population models or subjective judgement to make their predictions. Predictions made using models were only slightly more accurate than subjective judgements of risk. However, predictions using models tended to be unbiased, while subjective judgements were biased towards over-estimation. Psychology literature suggests that the bias of subjective judgements is likely to vary somewhat unpredictably among people, depending on their stake in the outcome. This will make subjective predictions more uncertain and less transparent than those based on models. (C) 2004 Elsevier SAS. All rights reserved.

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Antigen recognition by cytotoxic CD8 T cells is dependent upon a number of critical steps in MHC class I antigen processing including proteosomal cleavage, TAP transport into the endoplasmic reticulum, and MHC class 1 binding. Based on extensive experimental data relating to each of these steps there is now the capacity to model individual antigen processing steps with a high degree of accuracy. This paper demonstrates the potential to bring together models of individual antigen processing steps, for example proteosome cleavage, TAP transport, and MHC binding, to build highly informative models of functional pathways. In particular, we demonstrate how an artificial neural network model of TAP transport was used to mine a HLA-binding database so as to identify H LA-binding peptides transported by TAP. This integrated model of antigen processing provided the unique insight that HLA class I alleles apparently constitute two separate classes: those that are TAP-efficient for peptide loading (HLA-B27, -A3, and -A24) and those that are TAP-inefficient (HLA-A2, -B7, and -B8). Hence, using this integrated model we were able to generate novel hypotheses regarding antigen processing, and these hypotheses are now capable of being tested experimentally. This model confirms the feasibility of constructing a virtual immune system, whereby each additional step in antigen processing is incorporated into a single modular model. Accurate models of antigen processing have implications for the study of basic immunology as well as for the design of peptide-based vaccines and other immunotherapies. (C) 2004 Elsevier Inc. All rights reserved.

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Ozone is a major air pollutant with adverse health effects which exhibit marked inter-individual variability. In mice, regions of genetic linkage with ozone-induced lung injury include the tumor necrosis factor-alpha (TNF), lymphotoxin-alpha (LTA), Toll-like receptor 4 (TLR4), superoxide dismutase (SOD2), and glutathione peroxidase (GPX1) genes. We genotyped polymorphisms in these genes in 51 individuals who had undergone ozone challenge. Mean change in FEV1 with ozone challenge, as a percentage of baseline, was -3% in TNF -308G/A or A/A individuals, compared with -9% in G/G individuals (p = 0.024). When considering TNF haplotypes, the smallest change in FEV1 with ozone exposure was associated with the TNF haplotype comprising LTA +252G/TNF -1031T/TNF -308A/TNF -238G. This association remained statistically significant after correction for age, sex, disease, and ozone concentration (p = 0.047). SOD2 or GPX1 genotypes were not associated with lung function, and the TLR4 polymorphism was too infrequent to analyze. The results of this study support TNF as a genetic factor for susceptibility to ozone-induced changes in lung function in humans, and has potential implications for stratifying health risks of air pollution.

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In primates, the observation of meaningful, goaldirected actions engages a network of cortical areas located within the premotor and inferior parietal lobules. Current models suggest that activity within these regions arises relatively automatically during passive action observation without the need for topdown control. Here we used functional magnetic resonance imaging to determine whether cortical activit)' associated with action observation is modulated by the strategic allocation of selective attention. Normal observers viewed movie clips of reach-to-grasp actions while performing an easy or difficult visual discrimination at the fovea. A wholebrain analysis was performed to determine the effects of attentional load on neural responses to observed hand actions. Our results suggest that cortical areas involved in action observation are significantiy modulated by attentional load. These findings have important implications for recent attempts to link the human action-observation system to response properties of "mirror neurons" in monkeys.

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We construct the Drinfeld twists ( factorizing F-matrices) of the gl(m-n)-invariant fermion model. Completely symmetric representation of the pseudo-particle creation operators of the model are obtained in the basis provided by the F-matrix ( the F-basis). We resolve the hierarchy of the nested Bethe vectors in the F-basis for the gl(m-n) supersymmetric model.

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Myb is a key transcription factor that can regulate proliferation, differentiation, and apoptosis, predominantly in the haemopoietic system. Abnormal expression of Myb is associated with a number of cancers, both haemopoietic and non-haemopoietic. In order to better understand the role of Myb in normal and tumorigenic processes, we undertook a cDNA array screen to identify genes that are regulated by this factor. In this way, we identified the gene encoding vascular endothelial growth factor (VEGF) as being potentially regulated by the Myb oncoprotein in myeloid cells. To determine whether this was a direct effect on VEGF gene transcription, we examined the activity of the murine VEGF promoter in the presence of either wild-type (WT) or mutant forms of Myb. It was found that WT Myb was able to activate the VEGF promoter and that a minimal promoter region of 120 bp was sufficient to confer Myb responsiveness. Surprisingly, activation of the VEGF promoter was independent of DNA binding by Myb. This was shown by the use of DNA binding-defective Myb mutants and by mutagenesis of a potential Myb-binding site in the minimal promoter. Mutation of Sp1 sites within this region abolished Myb-mediated regulation of a reporter construct, suggesting that Myb DNA binding-independent activation of VEGF expression occurs via these Sp1 binding elements. Regulation of VEGF production by Myb has implications for the potential role of Myb in myeloid leukaemias and in solid tumours where VEGF may be functioning as an autocrine growth factor. (c) 2006 Elsevier Inc. All rights reserved.

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An important consideration in the development of mathematical models for dynamic simulation, is the identification of the appropriate mathematical structure. By building models with an efficient structure which is devoid of redundancy, it is possible to create simple, accurate and functional models. This leads not only to efficient simulation, but to a deeper understanding of the important dynamic relationships within the process. In this paper, a method is proposed for systematic model development for startup and shutdown simulation which is based on the identification of the essential process structure. The key tool in this analysis is the method of nonlinear perturbations for structural identification and model reduction. Starting from a detailed mathematical process description both singular and regular structural perturbations are detected. These techniques are then used to give insight into the system structure and where appropriate to eliminate superfluous model equations or reduce them to other forms. This process retains the ability to interpret the reduced order model in terms of the physico-chemical phenomena. Using this model reduction technique it is possible to attribute observable dynamics to particular unit operations within the process. This relationship then highlights the unit operations which must be accurately modelled in order to develop a robust plant model. The technique generates detailed insight into the dynamic structure of the models providing a basis for system re-design and dynamic analysis. The technique is illustrated on the modelling for an evaporator startup. Copyright (C) 1996 Elsevier Science Ltd