992 resultados para Rigidity to the shear


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There is an increasing requirement for more astute land resource management through efficiencies in agricultural inputs in a sugar cane production system. A precision agriculture (PA) approach can provide a pathway for a sustainable sugarcane production system. One of the impediments to the adoption of PA practices is access to paddock-scale mapping layers displaying variability in soil properties, crop growth and surface drainage. Variable rate application (VRA) of nutrients is an important component of PA. However, agronomic expertise within PA systems has fallen well behind significant advances in PA technologies. Generally, advisers in the sugar industry have a poor comprehension of the complex interaction of variables that contribute to within-paddock variations in crop growth. This is regarded as a significant impediment to the progression of PA in sugarcane and is one of the reasons for the poor adoption of VRA of nutrients in a PA approach to improved sugar cane production. This project therefore has established a number of key objectives which will contribute to the adoption of PA and the staged progression of VRA supported by relevant and practical agronomic expertise. These objectives include provision of base soils attribute mapping that can be determined using Veris 3100 Electrical Conductivity (EC) and digital elevation datasets using GPS mapping technology for a large sector of the central cane growing region using analysis of archived satellite imagery to determine the location and stability of yield patterns over time and in varying seasonal conditions on selected project study sites. They also include the stablishment of experiments to determine appropriate VRA nitrogen rates on various soil types subjected to extended anaerobic conditions, and the establishment of trials to determine nitrogen rates applicable to a declining yield potential associated with the aging of ratoons in the crop cycle. Preliminary analysis of archived yield estimation data indicates that yield patterns remain relatively stable overtime. Results also indicate the where there is considerable variability in EC values there is also significant variation in yield.

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So far 19 genera of downy mildews have been described, of which seven are parasitic to grasses. Here, we introduce a new genus, Baobabopsis, to accommodate two distinctive downy mildews, B. donbarrettii sp. nov., collected on Perotis rara in northern Australia, and B. enneapogonis sp. nov., collected on Enneapogon spp. in western and central Australia. Baobabopsis donbarrettii produced both oospores and sporangiospores that are morphologically distinct from other downy mildews on grasses. Molecular phylogenetic analyses showed that the two species of Baobabopsis occupied an isolated position among the known genera of graminicolous downy mildews. The importance of the Poaceae for the evolution of downy mildews is highlighted by the observation that more than a third of the known genera of downy mildews occur on grasses, while more than 90 % of the known species of downy mildews infect eudicots.

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Letter: Dr. Leo elected Honorary Secretary of Home for Aged and Infirm. Written in English script.

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Letter regarding the election of Dr. Leo to the Progress Lodge. Written in English script on blue lined white paper.

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Invitation to Opening of New Home for Aged and Infirm Hebrews. Invitation to a reception for new building. Simeon N. Leo, M.D., Hon. Sec.

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Exotic plant pests (EPPs) threaten production, market access and sustainability of Australian plant production systems. For the grains industry there are over 600 identified EPPs of which 54 are considered high priority, posing a significant threat. Despite Australia’s geographical isolation and strong quarantine systems, the threat from EPPs has never been higher with the increasing levels of travel and trade, emphasising the need for improving our efforts in prevention, preparedness and surveillance for EPPs.

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Fisheries management agencies around the world collect age data for the purpose of assessing the status of natural resources in their jurisdiction. Estimates of mortality rates represent a key information to assess the sustainability of fish stocks exploitation. Contrary to medical research or manufacturing where survival analysis is routinely applied to estimate failure rates, survival analysis has seldom been applied in fisheries stock assessment despite similar purposes between these fields of applied statistics. In this paper, we developed hazard functions to model the dynamic of an exploited fish population. These functions were used to estimate all parameters necessary for stock assessment (including natural and fishing mortality rates as well as gear selectivity) by maximum likelihood using age data from a sample of catch. This novel application of survival analysis to fisheries stock assessment was tested by Monte Carlo simulations to assert that it provided unbiased estimations of relevant quantities. The method was applied to the data from the Queensland (Australia) sea mullet (Mugil cephalus) commercial fishery collected between 2007 and 2014. It provided, for the first time, an estimate of natural mortality affecting this stock: 0.22±0.08 year −1 .

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Project evaluation is a process of measuring costs, benefits, risks and uncertainties for the purpose of decision-making by estimating and assessing impacts of the project to the community. The effects of impacts of toll roads are similar but different from the general non-tolled roads. Project evaluation methodologies are extensively studied and applied to various transport infrastructure projects. However, there is no definitive methodology to evaluate toll roads. This review discusses the impacts of toll roads then reviews the limitations of existing project evaluation methodologies when evaluating toll road impacts. The review identified gaps of knowledge of toll evaluations. First, the treatment of toll in project evaluation, particularly in Cost-Benefit Analysis requires further study to explore the appropriate methodology. Secondly, the project evaluation methodology needs to place strong emphasis on empirically based risk and uncertainty assessment. Addressing the limitations of the existing project evaluation methodologies leads to improvements of the methodology in practical level as well as fills the gap of knowledge of project evaluation for toll roads with respect to net impacts to the community.

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Many problems in analysis have been solved using the theory of Hodge structures. P. Deligne started to treat these structures in a categorical way. Following him, we introduce the categories of mixed real and complex Hodge structures. Category of mixed Hodge structures over the field of real or complex numbers is a rigid abelian tensor category, and in fact, a neutral Tannakian category. Therefore it is equivalent to the category of representations of an affine group scheme. The direct sums of pure Hodge structures of different weights over real or complex numbers can be realized as a representation of the torus group, whose complex points is the Cartesian product of two punctured complex planes. Mixed Hodge structures turn out to consist of information of a direct sum of pure Hodge structures of different weights and a nilpotent automorphism. Therefore mixed Hodge structures correspond to the representations of certain semidirect product of a nilpotent group and the torus group acting on it.

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What can the statistical structure of natural images teach us about the human brain? Even though the visual cortex is one of the most studied parts of the brain, surprisingly little is known about how exactly images are processed to leave us with a coherent percept of the world around us, so we can recognize a friend or drive on a crowded street without any effort. By constructing probabilistic models of natural images, the goal of this thesis is to understand the structure of the stimulus that is the raison d etre for the visual system. Following the hypothesis that the optimal processing has to be matched to the structure of that stimulus, we attempt to derive computational principles, features that the visual system should compute, and properties that cells in the visual system should have. Starting from machine learning techniques such as principal component analysis and independent component analysis we construct a variety of sta- tistical models to discover structure in natural images that can be linked to receptive field properties of neurons in primary visual cortex such as simple and complex cells. We show that by representing images with phase invariant, complex cell-like units, a better statistical description of the vi- sual environment is obtained than with linear simple cell units, and that complex cell pooling can be learned by estimating both layers of a two-layer model of natural images. We investigate how a simplified model of the processing in the retina, where adaptation and contrast normalization take place, is connected to the nat- ural stimulus statistics. Analyzing the effect that retinal gain control has on later cortical processing, we propose a novel method to perform gain control in a data-driven way. Finally we show how models like those pre- sented here can be extended to capture whole visual scenes rather than just small image patches. By using a Markov random field approach we can model images of arbitrary size, while still being able to estimate the model parameters from the data.

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Digital image

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Digital image

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Bovine Viral Diarrhoea Virus (BVDV) is one of the most serious pathogen, which causes tremendous economic loss to the cattle industry worldwide, meriting the development of improved subunit vaccines. Structural glycoprotein E2 is reported to be a major immunogenic determinant of BVDV virion. We have developed a novel hollow silica vesicles (SV) based platform to administer BVDV-1 Escherichia coli-expressed optimised E2 (oE2) antigen as a nanovaccine formulation. The SV-140 vesicles (diameter 50 nm, wall thickness 6 nm, perforated by pores of entrance size 16 nm and total pore volume of 0.934 cm(3)g(-1)) have proven to be ideal candidates to load oE2 antigen and generate immune response. The current study for the first time demonstrates the ability of freeze-dried (FD) as well as non-FD oE2/SV140 nanovaccine formulation to induce long-term balanced antibody and cell mediated memory responses for at least 6 months with a shortened dosing regimen of two doses in small animal model. The in vivo ability of oE2 (100 mu g)/SV-140 (500 mu g) and FD oE2 (100 mu g)/SV-140 (500 mu g) to induce long-term immunity was compared to immunisation with oE2 (100 mu g) together with the conventional adjuvant Quil-A from the Quillaja saponira (10 mu g) in mice. The oE2/SV-140 as well as the FD oE2/SV-140 nanovaccine generated oE2-specific antibody and cell mediated responses for up to six months post the final second immunisation. Significantly, the cell-mediated responses were consistently high in mice immunised with oE2/SV-140 (1,500 SFU/million cells) at the six-month time point. Histopathology studies showed no morphological changes at the site of injection or in the different organs harvested from the mice immunised with 500 mu g SV-140 nanovaccine compared to the unimmunised control. The platform has the potential for developing single dose vaccines without the requirement of cold chain storage for veterinary and human applications.