8 resultados para Positive Matrix Factorization

em eResearch Archive - Queensland Department of Agriculture


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Genetic models partitioning additive and non-additive genetic effects for populations tested in replicated multi-environment trials (METs) in a plant breeding program have recently been presented in the literature. For these data, the variance model involves the direct product of a large numerator relationship matrix A, and a complex structure for the genotype by environment interaction effects, generally of a factor analytic (FA) form. With MET data, we expect a high correlation in genotype rankings between environments, leading to non-positive definite covariance matrices. Estimation methods for reduced rank models have been derived for the FA formulation with independent genotypes, and we employ these estimation methods for the more complex case involving the numerator relationship matrix. We examine the performance of differing genetic models for MET data with an embedded pedigree structure, and consider the magnitude of the non-additive variance. The capacity of existing software packages to fit these complex models is largely due to the use of the sparse matrix methodology and the average information algorithm. Here, we present an extension to the standard formulation necessary for estimation with a factor analytic structure across multiple environments.

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A real-time reverse transcription polymerase chain reaction (qRT-PCR) test for the matrix gene of type A influenza viruses was used during the 2007 Australian equine influenza (EI) outbreak in order to confirm diagnosis and, later, eradication of the virus. During the EI outbreak, horses being exported required vaccination and individual proof of freedom from EI. At the end of the outbreak, positive results were obtained from four horses destined for export, because of contamination of the samples with the vaccine. This report highlights the need for EI testing and vaccination to occur on separate days and with the collection of swabs for testing to precede vaccination.

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Lepidiota contigua Britton is recorded from Windsor Tableland, northern Queensland.

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The current study was undertaken to enumerate Gram-positive bacteria in fresh sub-tropical marine fish and determine the effect of ambient storage (25°C) on the Gram-positive bacterial count. Total and Gram-positive bacteria were enumerated in the muscles, gills and gut of fresh and stored Pseudocaranx dentex, Pagrus auratus and Mugil cephalus on tryptone soya agar (TSA) and TSA with 0.25% phenylethyl alcohol (PEA), respectively. Initial studies indicated that PEA significantly reduced total aerobic bacterial count (TABC) whereas control Gram-positive bacteria were not affected by 0.25% PEA. TABC significantly increased in all fish body parts, whereas Gram-positive aerobic bacterial count (GABC) significantly increased only in the muscles and gills during ambient storage for 15 h. The TABC of the fish species increased from 4.00, 6.13 and 4.58 log cfu g-1, respectively in the muscles, gills, and gut to 6.31, 7.31 and 7.23 log cfu g-1 by the end of storage. GABC increased from 2.00, 3.52 and 2.20 log cfu g-1 to 4.70, 5.85 and 3.36 log cfu g-1. Within each species, TABC were significantly higher in the gills compared to that of muscles and gut; however, no significant differences were found in GABC between muscles and gills. This study demonstrated the potential importance of Gram-positive bacteria in sub-tropical marine fish and their spoilage.

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The intent of this study was to design, document and implement a Quality Management System (QMS) into a laboratory that incorporated both research and development (R&D) and routine analytical activities. In addition, it was necessary for the QMS to be easily and efficiently maintained to: (a) provide documented evidence that would validate the system's compliance with a certifiable standard, (b) fit the purpose of the laboratory, (c) accommodate prevailing government policies and standards, and (d) promote positive outcomes for the laboratory through documentation and verification of the procedures and methodologies implemented. Initially, a matrix was developed that documented the standards' requirements and the necessary steps to be made to meet those requirements. The matrix provided a check mechanism on the progression of the system's development. In addition, it was later utilised in the Quality Manual as a reference tool for the location of full procedures documented elsewhere in the system. The necessary documentation to build and monitor the system consisted of a series of manuals along with forms that provided auditable evidence of the workings of the QMS. Quality Management (QM), in one form or another, has been in existence since the early 1900's. However, the question still remains: is it a good thing or just a bugbear? Many of the older style systems failed because they were designed by non-users, fiercely regulatory, restrictive and generally deemed to be an imposition. It is now considered important to foster a sense of ownership of the system by the people who use the system. The system's design must be tailored to best fit the purpose of the operations of the facility if maximum benefits to the organisation are to be gained.

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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.

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The complexity, variability and vastness of the northern Australian rangelands make it difficult to assess the risks associated with climate change. In this paper we present a methodology to help industry and primary producers assess risks associated with climate change and to assess the effectiveness of adaptation options in managing those risks. Our assessment involved three steps. Initially, the impacts and adaptation responses were documented in matrices by ‘experts’ (rangeland and climate scientists). Then, a modified risk management framework was used to develop risk management matrices that identified important impacts, areas of greatest vulnerability (combination of potential impact and adaptive capacity) and priority areas for action at the industry level. The process was easy to implement and useful for arranging and analysing large amounts of information (both complex and interacting). Lastly, regional extension officers (after minimal ‘climate literacy’ training) could build on existing knowledge provided here and implement the risk management process in workshops with rangeland land managers. Their participation is likely to identify relevant and robust adaptive responses that are most likely to be included in regional and property management decisions. The process developed here for the grazing industry could be modified and used in other industries and sectors. By 2030, some areas of northern Australia will experience more droughts and lower summer rainfall. This poses a serious threat to the rangelands. Although the impacts and adaptive responses will vary between ecological and geographic systems, climate change is expected to have noticeable detrimental effects: reduced pasture growth and surface water availability; increased competition from woody vegetation; decreased production per head (beef and wool) and gross margin; and adverse impacts on biodiversity. Further research and development is needed to identify the most vulnerable regions, and to inform policy in time to facilitate transitional change and enable land managers to implement those changes.

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This study identified Gram-positive bacteria in three sub-tropical marine fish species: Pseudocaranx dentex (silver trevally), Pagrus auratus (snapper) and Mugil cephalus (sea mullet). It further elucidated the role played by fish habitat, fish body part and ambient storage on the composition of the Gram-positive bacteria. A total of 266 isolates of Gram-positive bacteria were identified by conventional biochemical methods, VITEK, PCR using genus- and species-specific primers and/or 16S rRNA gene sequencing. The isolates were found to fall into 13 genera and 30 species. In fresh fish, Staphylococcus epidermidis and Micrococcus luteus were the most frequent isolates. After ambient storage, S. epidermidis, S. xylosus and Bacillus megaterium were no longer present whereas S. warned, B. sphaericus, Brevibacillus borstelensis, Enterococcus faecium and Streptococcus uberis increased in frequency. Micrococcus luteus and S. warned were the most prevalent isolates from P. dentex, while E. faecium and Strep. uberis were the most frequent isolates from P. auratus and M. cephalus. With respect to different parts of the fish body. E. faecium, Strep. uberis and B. sphaericus were the most frequent isolates from the muscles, E. faecium, Strep. uberis from the gills and M. luteus from the gut. This study showed a diversity of Gram-positive bacteria in sub-tropical marine fish; however, their abundance was affected by fish habitat, fish body part and ambient storage.