15 resultados para q-Analysis

em University of Queensland eSpace - Australia


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Let Q be a stable and conservative Q-matrix over a countable state space S consisting of an irreducible class C and a single absorbing state 0 that is accessible from C. Suppose that Q admits a finite mu-subinvariant measure in on C. We derive necessary and sufficient conditions for there to exist a Q-process for which m is mu-invariant on C, as well as a necessary condition for the uniqueness of such a process.

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Maximizing the contribution of endemic natural enemies to integrated pest management (IPM) programs requires a detailed knowledge of their interactions with the target pest. This experimental field study evaluated the impact of the endemic natural enemy complex of Plutella xylostella (L.) (Lepidoptera: Yponomeutidae) on pest populations in commercial cabbage crops in southeastern Queensland, Australia. Management data were used to score pest management practices at experimental sites on independent Brassica farms practicing a range of pest management strategies, and mechanical methods of natural enemy exclusion were used to assess the impact of natural enemies on introduced cohorts of P. xylostella at each site. Natural enemy impact was greatest at sites adopting IPM and least at sites practicing conventional pest management strategies. At IPM sites, the contribution of natural enemies to P. xylostella mortality permitted the cultivation of marketable crops with no yield loss but with a substantial reduction in insecticide inputs. Three species of larval parasitoids (Diadegma semiclausum Hellen [Hymenoptera: Ichneumonidae], Apanteles ippeus Nixon [Hymenoptera: Braconidae], and Oomyzus sokolowskii Kurdjumov [Hymenoptera: Eulophidae]) and one species of pupal parasitoid Diadromus collaris Gravenhorst (Hymenoptera: Ichneumonidae) attacked immature P. xylostella. The most abundant groups of predatory arthropods caught in pitfall traps were Araneae (Lycosidae) > Coleoptera (Carabidae, Coccinelidae, Staphylinidae) > Neuroptera (Chrysopidae) > Formicidae, whereas on crop foliage Araneae (Clubionidae, Oxyopidae) > Coleoptera (Coccinelidae) > Neuroptera (Chrysopidae) were most common. The abundance and diversity of natural enemies was greatest at sites that adopted IPM, correlating greater P. xylostella mortality at these sites. The efficacy of the natural enemy complex to pest mortality under different pest management regimes and appropriate strategies to optimize this important natural resource are discussed.

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A set of varying-thickness Au-films were thermally evaporated onto poly(styrene-co-acrylonitrile) thin film surfaces. The Au/PSA bi-layer targets were then implanted with 50 keV N+ ions to a fluence of 1 × 1016 ions/cm2 to promote metal-to-polymer adhesion and to enhance their mechanical and electrical performance. Electrical conductivity measurements of the implanted Au/PSA thin films showed a sharp percolation behavior versus the pre-implant Au-film thickness with a percolation threshold near the nominal thickness of 44 Å. The electrical conductivity results are discussed along with the film microstructure and the elemental diffusion/mixing within the Au/PSA interface obtained by scanning electron microscopy (SEM) and ion beam analysis techniques (RBS and ERD).

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To be able to determine the grain size obtained from the addition of a grain refining master alloy, the relationship between grain size (d), solute content (defined by the growth restriction factor Q), and the potency and number density of nucleant particles needs to be understood. A study was undertaken on aluminium alloys where additions of TiB2 and Ti were made to eight wrought aluminum alloys covering a range of alloying elements and compositions. It was found from analysis of the data that d = a/(3)root pct TiB2 + b/Q. From consideration of the experimental data and from further analysis of previously published data, it is shown that the coefficients a and b relate to characteristics of the nucleant particles added by a grain refiner. The term a is related to the maximum density of active TiB2 nucleant particles within the melt, while b is related to their potency. By using the analysis methodology presented in this article, the performance characteristics of different master alloys were defined and the effects of Zr and Si on the poisoning of grain refinement were illustrated.

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Despite experimental evidences, the contributions of the concrete slab and composite action to the vertical shear strength of simply supported steel-concrete composite beams are not considered in current design codes, which lead to conservative designs. In this paper, the finite element method is used to investigate the flexural and shear strengths of simply supported composite beams under combined bending and shear. A three-dimensional finite element model has been developed to account for geometric and material nonlinear behavior of composite beams, and verified by experimental results. The verified finite element model is than employed to quantify the contributions of the concrete slab and composite action to the moment and shear capacities of composite beams. The effect of the degree of shear connection on the vertical shear strength of deep composite beams loaded in shear is studied. Design models for vertical shear strength including contributions from the concrete slab and composite action and for the ultimate moment-shear interaction ate proposed for the design of simply supported composite beams in combined bending and shear. The proposed design models provide a consistent and economical design procedure for simply supported composite beams.

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Let S be a countable set and let Q = (q(ij), i, j is an element of S) be a conservative q-matrix over S with a single instantaneous state b. Suppose that we are given a real number mu >= 0 and a strictly positive probability measure m = (m(j), j is an element of S) such that Sigma(i is an element of S) m(i)q(ij) = -mu m(j), j 0 b. We prove that there exists a Q-process P(t) = (p(ij) (t), i, j E S) for which m is a mu-invariant measure, that is Sigma(i is an element of s) m(i)p(ij)(t) = e(-mu t)m(j), j is an element of S. We illustrate our results with reference to the Kolmogorov 'K 1' chain and a birth-death process with catastrophes and instantaneous resurrection.

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Selection of machine learning techniques requires a certain sensitivity to the requirements of the problem. In particular, the problem can be made more tractable by deliberately using algorithms that are biased toward solutions of the requisite kind. In this paper, we argue that recurrent neural networks have a natural bias toward a problem domain of which biological sequence analysis tasks are a subset. We use experiments with synthetic data to illustrate this bias. We then demonstrate that this bias can be exploitable using a data set of protein sequences containing several classes of subcellular localization targeting peptides. The results show that, compared with feed forward, recurrent neural networks will generally perform better on sequence analysis tasks. Furthermore, as the patterns within the sequence become more ambiguous, the choice of specific recurrent architecture becomes more critical.

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The X-ray structure of human phenylethanolamine N-methyltransferase (hPNMT) complexed. with its product, S-adenoSyl-L-homocysteine (4), and the most potent inhibitor reported to date, SK&F 64139 (7), was used to identify the residues involved in inhibitor binding. Four of these residues, Va153, Lys57, Glu219 and Asp267, were replaced, in turn, with alanine. All variants had increased K-m values for phenylethanolamine (10), but only D267A showed a noteworthy (20-fold) decrease in its k(cat) value. Both WT hPNMT and D267A had similar k(cat) values for a rigid analogue, anti-9-amino-6-(trifluoromethyl)benzonorbornene (12), suggesting that Asp267 plays an important role in positioning the substrate but does not participate directly in catalysis. The K-i values for the binding of inhibitors such as 7 to the E219A and D267A variants increased by 2-3 orders of magnitude. Further, the inhibitors were shown to bind up to 50-fold more tightly in the presence of S-adenoSyl-(L)-methionine (3), suggesting that the binding of the latter brings about a conformational change in the enzyme.

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This paper presents a finite-difference time-domain (FDTD) simulator for electromagnetic analysis and design applications in MRI. It is intended to be a complete FDTD model of an MRI system including all RF and low-frequency field generating units and electrical models of the patient. The pro-ram has been constructed in an object-oriented framework. The design procedure is detailed and the numerical solver has been verified against analytical solutions for simple cases and also applied to various field calculation problems. In particular, the simulator is demonstrated for inverse RF coil design, optimized source profile generation, and parallel imaging in high-frequency situations. The examples show new developments enabled by the simulator and demonstrate that the proposed FDTD framework can be used to analyze large-scale computational electromagnetic problems in modern MRI engineering. (C) 2004 Elsevier Inc. All rights reserved.

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Loading of the femoral neck (FN) is dominated by bending and compressive stresses. We hypothesize that adaptation of the FN to physical activity would be manifested in the cross-sectional area (CSA) and section modulus (Z) of bone, indices of axial and bending strength, respectively. We investigated the influence of physical activity on bone strength during adolescence using 7 years of longitudinal data from 109 boys and 121 girls from the Saskatchewan Paediatric Bone and Mineral Accrual Study (PBMAS). Physical activity data (PAC-Q physical activity inventory) and anthropometric measurements were taken every 6 months and DXA bone scans were measured annually (Hologic QDR2000, array mode). We applied hip structural analysis to derive strength and geometric indices of the femoral neck using DXA scans. To control for maturation, we determined a biological maturity age defined as years from age at peak height velocity (APHV). To account for the repeated measures within individual nature of longitudinal data, multilevel random effects regression analyses were used to analyze the data. When biological maturity age and body size (height and weight) were controlled, in both boys and girls, physical activity was a significant positive independent predictor of CSA and Z of the narrow region of the femoral neck (P < 0.05). There was no independent effect of physical activity on the subperiosteal width of the femoral neck. When leg length and leg lean mass were introduced into the random effects models to control for size and muscle mass of the leg (instead of height and weight), all significant effects of physical activity disappeared. Even among adolescents engaged in normal levels of physical activity, the statistically significant relationship between physical activity and indices of bone strength demonstrate that modifiable lifestyle factors like exercise play an important role in optimizing bone strength during the growing years. Physical activity differences were explained by the interdependence between activity and lean mass considerations. Physical activity is important for optimal development of bone strength. (c) 2005 Elsevier Inc. All rights reserved.

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Web transaction data between Web visitors and Web functionalities usually convey user task-oriented behavior pattern. Mining such type of click-stream data will lead to capture usage pattern information. Nowadays Web usage mining technique has become one of most widely used methods for Web recommendation, which customizes Web content to user-preferred style. Traditional techniques of Web usage mining, such as Web user session or Web page clustering, association rule and frequent navigational path mining can only discover usage pattern explicitly. They, however, cannot reveal the underlying navigational activities and identify the latent relationships that are associated with the patterns among Web users as well as Web pages. In this work, we propose a Web recommendation framework incorporating Web usage mining technique based on Probabilistic Latent Semantic Analysis (PLSA) model. The main advantages of this method are, not only to discover usage-based access pattern, but also to reveal the underlying latent factor as well. With the discovered user access pattern, we then present user more interested content via collaborative recommendation. To validate the effectiveness of proposed approach, we conduct experiments on real world datasets and make comparisons with some existing traditional techniques. The preliminary experimental results demonstrate the usability of the proposed approach.