999 resultados para Leaf structure


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The foliage of a plant performs vital functions. As such, leaf models are required to be developed for modelling the plant architecture from a set of scattered data captured using a scanning device. The leaf model can be used for purely visual purposes or as part of a further model, such as a fluid movement model or biological process. For these reasons, an accurate mathematical representation of the surface and boundary is required. This paper compares three approaches for fitting a continuously differentiable surface through a set of scanned data points from a leaf surface, with a technique already used for reconstructing leaf surfaces. The techniques which will be considered are discrete smoothing D2-splines [R. Arcangeli, M. C. Lopez de Silanes, and J. J. Torrens, Multidimensional Minimising Splines, Springer, 2004.], the thin plate spline finite element smoother [S. Roberts, M. Hegland, and I. Altas, Approximation of a Thin Plate Spline Smoother using Continuous Piecewise Polynomial Functions, SIAM, 1 (2003), pp. 208--234] and the radial basis function Clough-Tocher method [M. Oqielat, I. Turner, and J. Belward, A hybrid Clough-Tocher method for surface fitting with application to leaf data., Appl. Math. Modelling, 33 (2009), pp. 2582-2595]. Numerical results show that discrete smoothing D2-splines produce reconstructed leaf surfaces which better represent the original physical leaf.

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We investigate the blend morphology and performance of bulk heterojunction organic photovoltaic devices comprising the donor polymer, pDPP-TNT (poly{3,6-dithiophene-2-yl-2,5-di(2-octyldodecyl)-pyrrolo[3,4-c]pyrrole-1, 4-dione-alt-naphthalene}) and the fullerene acceptor, [70]PCBM ([6,6]-phenyl C71-butyric acid methyl ester). The blend morphology is heavily dependent upon the solvent system used in the fabrication of thin films. Thin films spin-coated from chloroform possess a cobblestone-like morphology, consisting of thick, round-shaped [70]PCBM-rich mounds separated by thin polymer-rich valleys. The size of the [70]PCBM domains is found to depend on the overall film thickness. Thin films spin-coated from a chloroform:dichlorobenzene mixed solvent system are smooth and consist of a network of pDPP-TNT nanofibers embedded in a [70]PCBM-rich matrix. Rinsing the films in hexane selectively removes [70]PCBM and allows for analysis of domain size and purity. It also provides a means for investigating exciton dissociation efficiency through relative photoluminescence yield measurements. Devices fabricated from chloroform solutions show much poorer performance than the devices fabricated from the mixed solvent system; this disparity in performance is seen to be more pronounced with increasing film thickness. The primary cause for the improved performance of devices fabricated from mixed solvents is attributed to the greater donor-acceptor interfacial area and resulting greater capacity for charge carrier generation.

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In recent years, the beauty leaf plant (Calophyllum Inophyllum) is being considered as a potential 2nd generation biodiesel source due to high seed oil content, high fruit production rate, simple cultivation and ability to grow in a wide range of climate conditions. However, however, due to the high free fatty acid (FFA) content in this oil, the potential of this biodiesel feedstock is still unrealized, and little research has been undertaken on it. In this study, transesterification of beauty leaf oil to produce biodiesel has been investigated. A two-step biodiesel conversion method consisting of acid catalysed pre-esterification and alkali catalysed transesterification has been utilized. The three main factors that drive the biodiesel (fatty acid methyl ester (FAME)) conversion from vegetable oil (triglycerides) were studied using response surface methodology (RSM) based on a Box-Behnken experimental design. The factors considered in this study were catalyst concentration, methanol to oil molar ratio and reaction temperature. Linear and full quadratic regression models were developed to predict FFA and FAME concentration and to optimize the reaction conditions. The significance of these factors and their interaction in both stages was determined using analysis of variance (ANOVA). The reaction conditions for the largest reduction in FFA concentration for acid catalysed pre-esterification was 30:1 methanol to oil molar ratio, 10% (w/w) sulfuric acid catalyst loading and 75 °C reaction temperature. In the alkali catalysed transesterification process 7.5:1 methanol to oil molar ratio, 1% (w/w) sodium methoxide catalyst loading and 55 °C reaction temperature were found to result in the highest FAME conversion. The good agreement between model outputs and experimental results demonstrated that this methodology may be useful for industrial process optimization for biodiesel production from beauty leaf oil and possibly other industrial processes as well.

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Realistic virtual models of leaf surfaces are important for a number of applications in the plant sciences, such as modelling agrichemical spray droplet movement and spreading on the surface. In this context, the virtual surfaces are required to be sufficiently smooth to facilitate the use of the mathematical equations that govern the motion of the droplet. While an effective approach is to apply discrete smoothing D2-spline algorithms to reconstruct the leaf surfaces from three-dimensional scanned data, difficulties arise when dealing with wheat leaves that tend to twist and bend. To overcome this topological difficulty, we develop a parameterisation technique that rotates and translates the original data, allowing the surface to be fitted using the discrete smoothing D2-spline methods in the new parameter space. Our algorithm uses finite element methods to represent the surface as a linear combination of compactly supported shape functions. Numerical results confirm that the parameterisation, along with the use of discrete smoothing D2-spline techniques, produces realistic virtual representations of wheat leaves.

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Mass-guided fractionation of the MeOH extract from a specimen of the Australian marine sponge Hyrtios sp. resulted in the isolation of two new tryptophan alkaloids, 6-oxofascaplysin (2), and secofascaplysic acid (3), in addition to the known metabolites fascaplysin (1) and reticulatate (4). The structures of all molecules were determined following NMR and MS data analysis. Structural ambiguities in 2 were addressed through comparison of experimental and DFT-generated theoretical NMR spectral values. Compounds 1–4 were evaluated for their cytotoxicity against a prostate cancer cell line (LNCaP) and were shown to display IC50 values ranging from 0.54 to 44.9 μM.

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This thesis is a study in narratology that examines the pre-theoretical ideas that underlie the study of narrative and time. The thesis explores how the lemniscate can be transported from geometry to narrative in order to structure a non-linear story that breaks the rules of causality and chronology by coupling physical movement through space with the backward pull of memory. The findings offer new possibilities for understanding the nexus between shape and story and for recording non-linear narratives that are marked by simultaneity, counterpoint, and reversal.

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Aggregation and biofilm formation are critical mechanisms for bacterial resistance to host immune factors and antibiotics. Autotransporter (AT) proteins, which represent the largest group of outer-membrane and secreted proteins in Gram-negative bacteria, contribute significantly to these phenotypes. Despite their abundance and role in bacterial pathogenesis, most AT proteins have not been structurally characterized, and there is a paucity of detailed information with regard to their mode of action. Here we report the structure–function relationships of Antigen 43 (Ag43a), a prototypic self-associating AT protein from uropathogenic Escherichia coli. The functional domain of Ag43a displays a twisted L-shaped β-helical structure firmly stabilized by a 3D hydrogen-bonded scaffold. Notably, the distinctive Ag43a L shape facilitates self-association and cell aggregation. Combining all our data, we define a molecular “Velcro-like” mechanism of AT-mediated bacterial clumping, which can be tailored to fit different bacterial lifestyles such as the formation of biofilms.

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Since its discovery in 1991, the bacterial periplasmic oxidative folding catalyst DsbA has been the focus of intense research. Early studies addressed why it is so oxidizing and how it is maintained in its less stable oxidized state. The crystal structure of Escherichia coli DsbA (EcDsbA) revealed that the oxidizing periplasmic enzyme is a distant evolutionary cousin of the reducing cytoplasmic enzyme thioredoxin. Recent significant developments have deepened our understanding of DsbA function, mechanism, and interactions: the structure of the partner membrane protein EcDsbB, including its complex with EcDsbA, proved a landmark in the field. Studies of DsbA machineries from bacteria other than E. coli K-12 have highlighted dramatic differences from the model organism, including a striking divergence in redox parameters and surface features. Several DsbA structures have provided the first clues to its interaction with substrates, and finally, evidence for a central role of DsbA in bacterial virulence has been demonstrated in a range of organisms. Here, we review current knowledge on DsbA, a bacterial periplasmic protein that introduces disulfide bonds into diverse substrate proteins and which may one day be the target of a new class of anti-virulence drugs to treat bacterial infection. Antioxid. Redox Signal. 14, 1729–1760.

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Section 95AT of the Competition and Consumer Act 2010 (Cth) (CCA) provides that the Tribunal may grant an authorisation to acquire shares or assets that would otherwise contravene s 50. Section 95AT was inserted by the Trade Practices Legislation Amendment Act 2006 (Cth) and commenced on 1 January 2007. In Application for Authorisation of Macquarie Generation by AGL Energy Limited, (AGL Energy) the Tribunal has for the first time granted AGL Energy Limited (AGL) a conditional authorisation to acquire the assets of Macquarie Generation from the NSW Government.

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Priceite is a calcium borate mineral and occurs as white crystals in the monoclinic pyramidal crystal system. We have used a combination of Raman spectroscopy with complimentary infrared spectroscopy and scanning electron microscopy with Energy-dispersive X-ray Spectroscopy (EDS) to study the mineral priceite. Chemical analysis shows a pure phase consisting of B and Ca only. Raman bands at 956, 974, 991, and 1019 cm−1 are assigned to the BO stretching vibration of the B10O19 units. Raman bands at 1071, 1100, 1127, 1169, and 1211 cm−1 are attributed to the BOH in-plane bending modes. The intense infrared band at 805 cm−1 is assigned to the trigonal borate stretching modes. The Raman band at 674 cm−1 together with bands at 689, 697, 736, and 602 cm−1 are assigned to the trigonal and tetrahedral borate bending modes. Raman spectroscopy in the hydroxyl stretching region shows a series of bands with intense Raman band at 3555 cm−1 with a distinct shoulder at 3568 cm−1. Other bands in this spectral region are found at 3221, 3385, 3404, 3496, and 3510 cm−1. All of these bands are assigned to water stretching vibrations. The observation of multiple bands supports the concept of water being in different molecular environments in the structure of priceite. The molecular structure of a natural priceite has been assessed using vibrational spectroscopy.

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Premise of the study: Plant invasiveness can be promoted by higher values of adaptive traits (e.g., photosynthetic capacity, biomass accumulation), greater plasticity and coordination of these traits, and by higher and positive relative influence of these functionalities on fitness, such as increasing reproductive output. However, the dataset for this premise rarely include linkages between epidermal-stomatal traits, leaf internal anatomy, and physiological performance. Methods: Three ecological pairs of invasive vs non-invasive (native) woody vine species of South-East Queensland, Australia were investigated for trait differences in leaf morphology and anatomy under varying light intensity. The linkages of these traits with physiological performance (e.g. water use efficiency, photosynthesis, and leaf construction cost) and plant adaptive traits of specific leaf area, biomass, and relative growth rates were also explored. Key results: Mean leaf anatomical trait differed significantly between the two groups, except for stomatal size. Plasticity of traits, and to a very limited extent, their phenotypic integration were higher in the invasive relative to the native species. ANOVA, ordination, and analysis of similarity suggest that for leaf morphology and anatomy, the three functional strategies contribute to the differences between the two groups in the order phenotypic plasticity > trait means > phenotypic integration. Conclusions: The linkages demonstrated in the study between stomatal complex/gross anatomy and physiology are scarce in the ecological literature of plant invasiveness, but the findings suggest that leaf anatomical traits need to be considered routinely as part of weed species assessment and in the worldwide leaf economic spectrum.

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This research project investigated the influence of family transitions on children's adjustment and school achievement across the primary school years, in single-parent, re-partnered and two-parent families. The quality of children's relationships with parents, teachers and peers were predictive of more positive outcomes, regardless of family structure. The research analysed data from the Kindergarten Cohort participating in Growing Up in Australia: The Longitudinal Study of Australian Children. Across the age span of the children studied, cumulative effects of any residential or school changes, or decreased family income, associated with family transitions, were more likely to predict poorer child outcomes in behaviour adjustment and school achievement.

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Fine-grained leaf classification has concentrated on the use of traditional shape and statistical features to classify ideal images. In this paper we evaluate the effectiveness of traditional hand-crafted features and propose the use of deep convolutional neural network (ConvNet) features. We introduce a range of condition variations to explore the robustness of these features, including: translation, scaling, rotation, shading and occlusion. Evaluations on the Flavia dataset demonstrate that in ideal imaging conditions, combining traditional and ConvNet features yields state-of-theart performance with an average accuracy of 97:3%�0:6% compared to traditional features which obtain an average accuracy of 91:2%�1:6%. Further experiments show that this combined classification approach consistently outperforms the best set of traditional features by an average of 5:7% for all of the evaluated condition variations.