25 resultados para Binary vectors

em University of Queensland eSpace - Australia


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We have evaluated the transformation efficiency of two lettuce ( Lactuca sativa L.) cultivars, LE126 and Seagreen, using Agrobacterium tumefaciens- mediated gene transfer. Six- day- old cotyledons were co- cultivated with Agrobacterium cultures carrying binary vectors with two different genetic constructs. The first construct contained the beta- glucuronidase gene ( GUS) under the control of the cauliflower mosaic virus 35S promoter ( CaMV 35S), while the second construct contained the ethylene mutant receptor etr1- 1, which confers ethylene insensitivity, under the control of a leaf senescence- specific promoter ( sag12). Tissues co- cultivated with the GUS construct showed strong regeneration potential with over 90% of explants developing callus masses and 85% of the calli developing shoots. Histochemical GUS assays showed that 85.7% of the plants recovered were transgenic. Very different results were observed when cotyledon explants were co- cultivated with Agrobacteria carrying the etr1- 1 gene. There was a dramatic effect on the regeneration properties of the cultured explants with root formation taking place directly from the cotyledon tissue in 34% of the explants and no callus or shoots observed initially. Eventually callus formed in 10% of cotyledons and some organogenic shoots were obtained ( 2.86%). These results indicate that the ethylene insensitivity conferred by the etr1- 1 gene alters the normal pattern of regeneration in lettuce cotyledons, inhibiting the formation of shoots and stimulating root formation during regeneration.

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Adsorption of p-cresol, nitrobenzene and p-nitrophenol on treated and untreated carbons is investigated systematically. The effects of carbon surface chemistry and solution pH are studied and discussed. All adsorption experiments were carried out in pH-controlled solutions to examine the adsorption properties of the adsorption systems where the solutes are in molecular as well as ionic forms. Using the homogeneous Langmuir equation, the single solute parameters are determined. These parameters are then used to predict the binary solute adsorption isotherms and gain further insights into the adsorption process. (C) 2002 Elsevier Science Ltd. All rights reserved.

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High-quality nanometer thick ultramicroporous membranes were prepared from silica sol-gel processes and tested for the permeation of binary gas mixtures of He, H-2, CO2, and CH4 across different temperature and partial pressure regimens. Pore size distribution by molecular probing showed that the majority of pore sizes had dimensions below 2.9 Angstrom. In 50:50 binary mixtures, the fluxes of gases increased as a function of temperature, indicating an activated transport mechanism. The ultramicroporous membranes showed high selectivities at 150 degreesC for He/CO2 (30), He/CH4 (93), H-2/CO2 (10), and H-2/CH4 (9) with lower selectivities for CO2/CH4 (5). High activation energies (E-a) were observed for the permeance of 50:50 binary mixtures containing He and H-2 of 22.1-27.5 and 17.6-23.1 kJ.mol(-1), respectively. The E-a for the permeance of the total mixture approached the E-a for the permeance of the molecule with the smaller kinetic diameter (He or H-2).

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The use of a fully parametric Bayesian method for analysing single patient trials based on the notion of treatment 'preference' is described. This Bayesian hierarchical modelling approach allows for full parameter uncertainty, use of prior information and the modelling of individual and patient sub-group structures. It provides updated probabilistic results for individual patients, and groups of patients with the same medical condition, as they are sequentially enrolled into individualized trials using the same medication alternatives. Two clinically interpretable criteria for determining a patient's response are detailed and illustrated using data from a previously published paper under two different prior information scenarios. Copyright (C) 2005 John Wiley & Sons, Ltd.

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Complementary field and laboratory tests confirmed and quantified the pollination abilities of Tranes sp. weevils and Cycadothrips chadwicki thrips, specialist insects of their respective cycad hosts, Macrozamia machinii and M. lucida. No agamospermous seeds were produced when both wind and insects were excluded from female cones; and the exclusion of wind-vectored pollen alone did not eliminate seed set, because insects were able to reach the cone. Based on enclosure pollination tests, each weevil pollinates an average 26.2 ovules per cone and each thrips 2.4 ovules per cone. These pollinators visited similar numbers of ovules per cone in fluorescent dye tests that traced insect movement through cones. Fluorescent dye granules deposited by Cycadothrips were concentrated around the micropyle of each visited ovule, the site of pollen droplet release, where pollen must be deposited to achieve pollination. In contrast, Tranes weevils left dye scattered on different areas of each visited ovule, indicating that chance plays a greater role in this system. Each weevil and 25 thrips delivered 6.2 and 5.2 pollen grains, respectively, on average, to each visited ovule per cone, based on examination of dissected pollen canals. In sum, the pollination potential of 25 Cycadothrips approximates that of one Tranes weevil.

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This paper investigates the relationship between mechanical properties and microstructure in high pressure die cast binary Mg-Al alloys. As-cast test bars produced using high pressure die casting have been tested in tension in order to determine the properties for castings produced using this technique. It has been shown that increasing aluminium levels results in increases in yield strength and a decrease in ductility for these alloys. Higher aluminium levels also result in a decrease in creep rate at 150 degrees C. It has also been shown that an increase in aluminium levels results in an increase in the volume fraction of eutectic Mg17Al12 in the microstructure.

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Dynamic binary translation is the process of translating, modifying and rewriting executable (binary) code from one machine to another at run-time. This process of low-level re-engineering consists of a reverse engineering phase followed by a forward engineering phase. UQDBT, the University of Queensland Dynamic Binary Translator, is a machine-adaptable translator. Adaptability is provided through the specification of properties of machines and their instruction sets, allowing the support of different pairs of source and target machines. Most binary translators are closely bound to a pair of machines, making analyses and code hard to reuse. Like most virtual machines, UQDBT performs generic optimizations that apply to a variety of machines. Frequently executed code is translated to native code by the use of edge weight instrumentation, which makes UQDBT converge more quickly than systems based on instruction speculation. In this paper, we describe the architecture and run-time feedback optimizations performed by the UQDBT system, and provide results obtained in the x86 and SPARC® platforms.

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Computer modelling promises to. be an important tool for analysing and predicting interactions between trees within mixed species forest plantations. This study explored the use of an individual-based mechanistic model as a predictive tool for designing mixed species plantations of Australian tropical trees. The 'spatially explicit individually based-forest simulator' (SeXI-FS) modelling system was used to describe the spatial interaction of individual tree crowns within a binary mixed-species experiment. The three-dimensional model was developed and verified with field data from three forest tree species grown in tropical Australia. The model predicted the interactions within monocultures and binary mixtures of Flindersia brayleyana, Eucalyptus pellita and Elaeocarpus grandis, accounting for an average of 42% of the growth variation exhibited by species in different treatments. The model requires only structural dimensions and shade tolerance as species parameters. By modelling interactions in existing tree mixtures, the model predicted both increases and reductions in the growth of mixtures (up to +/- 50% of stem volume at 7 years) compared to monocultures. This modelling approach may be useful for designing mixed tree plantations. (c) 2006 Published by Elsevier B.V.

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Knowledge of the adsorption behavior of coal-bed gases, mainly under supercritical high-pressure conditions, is important for optimum design of production processes to recover coal-bed methane and to sequester CO2 in coal-beds. Here, we compare the two most rigorous adsorption methods based on the statistical mechanics approach, which are Density Functional Theory (DFT) and Grand Canonical Monte Carlo (GCMC) simulation, for single and binary mixtures of methane and carbon dioxide in slit-shaped pores ranging from around 0.75 to 7.5 nm in width, for pressure up to 300 bar, and temperature range of 308-348 K, as a preliminary study for the CO2 sequestration problem. For single component adsorption, the isotherms generated by DFT, especially for CO2, do not match well with GCMC calculation, and simulation is subsequently pursued here to investigate the binary mixture adsorption. For binary adsorption, upon increase of pressure, the selectivity of carbon dioxide relative to methane in a binary mixture initially increases to a maximum value, and subsequently drops before attaining a constant value at pressures higher than 300 bar. While the selectivity increases with temperature in the initial pressure-sensitive region, the constant high-pressure value is also temperature independent. Optimum selectivity at any temperature is attained at a pressure of 90-100 bar at low bulk mole fraction of CO2, decreasing to approximately 35 bar at high bulk mole fractions. (c) 2005 American Institute of Chemical Engineers.

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Quantitatively predicting mass transport rates for chemical mixtures in porous materials is important in applications of materials such as adsorbents, membranes, and catalysts. Because directly assessing mixture transport experimentally is challenging, theoretical models that can predict mixture diffusion coefficients using Only single-component information would have many uses. One such model was proposed by Skoulidas, Sholl, and Krishna (Langmuir, 2003, 19, 7977), and applications of this model to a variety of chemical mixtures in nanoporous materials have yielded promising results. In this paper, the accuracy of this model for predicting mixture diffusion coefficients in materials that exhibit a heterogeneous distribution of local binding energies is examined. To examine this issue, single-component and binary mixture diffusion coefficients are computed using kinetic Monte Carlo for a two-dimensional lattice model over a wide range of lattice occupancies and compositions. The approach suggested by Skoulidas, Sholl, and Krishna is found to be accurate in situations where the spatial distribution of binding site energies is relatively homogeneous, but is considerably less accurate for strongly heterogeneous energy distributions.

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Hannenhalli and Pevzner developed the first polynomial-time algorithm for the combinatorial problem of sorting of signed genomic data. Their algorithm solves the minimum number of reversals required for rearranging a genome to another when gene duplication is nonexisting. In this paper, we show how to extend the Hannenhalli-Pevzner approach to genomes with multigene families. We propose a new heuristic algorithm to compute the reversal distance between two genomes with multigene families via the concept of binary integer programming without removing gene duplicates. The experimental results on simulated and real biological data demonstrate that the proposed algorithm is able to find the reversal distance accurately. ©2005 IEEE

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In this paper we present an efficient k-Means clustering algorithm for two dimensional data. The proposed algorithm re-organizes dataset into a form of nested binary tree*. Data items are compared at each node with only two nearest means with respect to each dimension and assigned to the one that has the closer mean. The main intuition of our research is as follows: We build the nested binary tree. Then we scan the data in raster order by in-order traversal of the tree. Lastly we compare data item at each node to the only two nearest means to assign the value to the intendant cluster. In this way we are able to save the computational cost significantly by reducing the number of comparisons with means and also by the least use to Euclidian distance formula. Our results showed that our method can perform clustering operation much faster than the classical ones. © Springer-Verlag Berlin Heidelberg 2005

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