54 resultados para 18F Labelling


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The microbial mediated production of nitrous oxide (N2O) and its reduction to dinitrogen (N2) via denitrification represents a loss of nitrogen (N) from fertilised agro-ecosystems to the atmosphere. Although denitrification has received great interest by biogeochemists in the last decades, the magnitude of N2lossesand related N2:N2O ratios from soils still are largely unknown due to methodical constraints. We present a novel 15N tracer approach, based on a previous developed tracer method to study denitrification in pure bacterial cultures which was modified for the use on soil incubations in a completely automated laboratory set up. The method uses a background air in the incubation vessels that is replaced with a helium-oxygen gas mixture with a 50-fold reduced N2 background (2 % v/v). This method allows for a direct and sensitive quantification of the N2 and N2O emissions from the soil with isotope-ratio mass spectrometry after 15N labelling of denitrification N substrates and minimises the sensitivity to the intrusion of atmospheric N2 at the same time. The incubation set up was used to determine the influence of different soil moisture levels on N2 and N2O emissions from a sub-tropical pasture soil in Queensland/Australia. The soil was labelled with an equivalent of 50 μg-N per gram dry soil by broadcast application of KNO3solution (4 at.% 15N) and incubated for 3 days at 80% and 100% water filled pore space (WFPS), respectively. The headspace of the incubation vessel was sampled automatically over 12hrs each day and 3 samples (0, 6, and 12 hrs after incubation start) of headspace gas analysed for N2 and N2O with an isotope-ratio mass spectrometer (DELTA V Plus, Thermo Fisher Scientific, Bremen, Germany(. In addition, the soil was analysed for 15N NO3- and NH4+ using the 15N diffusion method, which enabled us to obtain a complete N balance. The method proved to be highly sensitive for N2 and N2O emissions detecting N2O emissions ranging from 20 to 627 μN kg-1soil-1hr-1and N2 emissions ranging from 4.2 to 43 μN kg-1soil-1hr-1for the different treatments. The main end-product of denitrification was N2O for both water contents with N2 accounting for 9% and 13% of the total denitrification losses at 80% and 100%WFPS, respectively. Between 95-100% of the added 15N fertiliser could be recovered. Gross nitrification over the 3 days amounted to 8.6 μN g-1 soil-1 and 4.7 μN g-1 soil-1, denitrification to 4.1 μN g-1 soil-1 and 11.8 μN g-1 soil-1at 80% and 100%WFPS, respectively. The results confirm that the tested method allows for a direct and highly sensitive detection of N2 and N2O fluxes from soils and hence offers a sensitive tool to study denitrification and N turnover in terrestrial agro-ecosystems.

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Product reviews are the foremost source of information for customers and manufacturers to help them make appropriate purchasing and production decisions. Natural language data is typically very sparse; the most common words are those that do not carry a lot of semantic content, and occurrences of any particular content-bearing word are rare, while co-occurrences of these words are rarer. Mining product aspects, along with corresponding opinions, is essential for Aspect-Based Opinion Mining (ABOM) as a result of the e-commerce revolution. Therefore, the need for automatic mining of reviews has reached a peak. In this work, we deal with ABOM as sequence labelling problem and propose a supervised extraction method to identify product aspects and corresponding opinions. We use Conditional Random Fields (CRFs) to solve the extraction problem and propose a feature function to enhance accuracy. The proposed method is evaluated using two different datasets. We also evaluate the effectiveness of feature function and the optimisation through multiple experiments.

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The Rio+20 United Nations Conference on Sustainable Development featured a fractious debate over intellectual property and the environment. Not only was there heated debate about patent law, technology transfer, and sustainable development, there was also a debate about sustainable public procurement, eco-labelling, accountable advertising, and greenwashing.

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Background Despite its global recognition as a ruminant pathogen, cases of Chlamydia pecorum infection in Australian livestock are poorly documented. In this report, a C. pecorum specific Multi Locus Sequence Analysis scheme was used to characterise the C. pecorum strains implicated in two cases of sporadic bovine encephalomyelitis confirmed by necropsy, histopathology and immunohistochemistry. This report provides the first molecular evidence for the presence of mixed infections of C. pecorum strains in Australian cattle. Case presentation Affected animals were two markedly depressed, dehydrated and blind calves, 12 and 16 weeks old. The calves were euthanized and necropsied. In one calf, a severe fibrinous polyserositis was noted with excess joint fluid in all joints whereas in the other, no significant lesions were seen. No gross abnormalities were noted in the brain of either calf. Histopathological lesions seen in both calves included: multifocal, severe, subacute meningoencephalitis with vasculitis, fibrinocellular thrombosis and malacia; diffuse, mild, acute interstitial pneumonia; and diffuse, subacute epicarditis, severe in the calf with gross serositis. Immunohistochemical labelling of chlamydial antigen in brain, spleen and lung from the two affected calves and brain from two archived cases, localised the antigen to the cytoplasm of endothelium, mesothelium and macrophages. C. pecorum specific qPCR, showed dissemination of the pathogen to multiple organs. Phylogenetic comparisons with other C. pecorum bovine strains from Australia, Europe and the USA revealed the presence of two genetically distinct sequence types (ST). The predominant ST detected in the brain, heart, lung and liver of both calves was identical to the C. pecorum ST previously described in cases of SBE. A second ST detected in an ileal tissue sample from one of the calves, clustered with previously typed faecal bovine isolates. Conclusion This report provides the first data to suggest that identical C. pecorum STs may be associated with SBE in geographically separated countries and that these may be distinct from those found in the gastrointestinal tract. This report provides a platform for further investigations into SBE and for understanding the genetic relationships that exist between C. pecorum strains detected in association with other infectious diseases in livestock.

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Animal and human studies have demonstrated that early pain experiences can produce alterations in the nociceptive systems later in life including increased sensitivity to mechanical, thermal, and chemical stimuli. However, less is known about the impact of neonatal immune challenge on future responses to noxious stimuli and the reactivity of neural substrates involved in analgesia. Here we demonstrate that rats exposed to Lipopolysaccharide (LPS; 0.05 mg/kg IP, Salmonella enteritidis) during postnatal day (PND) 3 and 5 displayed enhanced formalin-induced flinching but not licking following formalin injection at PND 22. This LPS-induced hyperalgesia was accompanied by distinct recruitment of supra-spinal regions involved in analgesia as indicated by significantly attenuated Fos-protein induction in the rostral dorsal periaqueductal grey (DPAG) as well as rostral and caudal axes of the ventrolateral PAG (VLPAG). Formalin injections were associated with increased Fos-protein labelling in lateral habenula (LHb) as compared to medial habenula (MHb), however the intensity of this labelling did not differ as a result of neonatal immune challenge. These data highlight the importance of neonatal immune priming in programming inflammatory pain sensitivity later in development and highlight the PAG as a possible mediator of this process

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Background Optimal infant nutrition comprises exclusive breastfeeding, with complementary foods introduced from six months of age. How parents make decisions regarding this is poorly studied. This study begins to address the dearth of research into the decision-making processes used by first-time mothers relating to the introduction of complementary foods. Methods This qualitative explorative study was conducted using interviews (13) and focus groups (3). A semi-structured interview guide based on the Theory of Planned Behaviour (TPB). The TPB, a well-validated decision-making model, identifies the key determinants of a behaviour through behavioural beliefs, subjective norms, and perceived behavioural control over the behaviour. It is purported that these beliefs predict behavioural intention to perform the behaviour, and performing the behaviour. A purposive, convenience, sample of 21 metropolitan parents recruited through advertising at local playgroups and childcare centres, and electronically through the University community email list self-selected to participate. Data were analysed thematically within the theoretical constructs: behavioural beliefs, subjective norms and perceived behavioural control. Data relating to sources of information about the introduction of complementary foods were also collected. Results Overall, first-time mothers found that waiting until six months was challenging despite knowledge of the WHO recommendations and an initial desire to comply with this guideline. Beliefs that complementary foods would assist the infants' weight gain, sleeping patterns and enjoyment at meal times were identified. Barriers preventing parents complying with the recommendations included subjective and group norms, peer influences, infant cues indicating early readiness and food labelling inconsistencies. The most valued information source was from peers who had recently introduced complementary foods. Conclusions First-time mothers in this study did not demonstrate a good understanding of the rationale behind the WHO recommendations, nor did they understand fully the signs of readiness of infants to commence solid foods. Factors that assisted waiting until six months were a trusting relationship with a health professional whose practice and advice was consistent with the recommendations and/or when their infant was developmentally ready for complementary foods at six months and accepted them with ease and enthusiasm. Barriers preventing parents complying with the recommendations included subjective and group norms, peer influences, infant cues indicating early readiness and food labelling inconsistencies.

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In Australia, bankruptcy retains a social stigma, as is often seen as a personal failing, and an indication that the individual cannot be trusted to meet their obligations. Official labelling and informal labelling reinforce this stigmatisation of bankruptcy in employment and business contexts. This occurs through legislation and policy that imposes restrictions on participation in some occupations on the grounds of bankruptcy, and imposes obligations on persons to disclose their bankruptcy to their employer. These restrictions and obligations that are varying in length and extent, both within industries and professions and across industries and professions, and appear to lack a coherent policy justification. Further, informal labelling is facilitated by the law providing for a permanent, publicly accessible record of bankruptcy, and failing to restrict the use of bankruptcy information in employment and business decision-making. This stigmatisation of bankruptcy inhibits the fresh start objective of bankruptcy, and is not supported by a strong correlation between bankruptcy and negative personal or other attributes. This article therefore argues that a review is needed to determine the circumstances in which there is a genuine policy justification for employment restrictions, and the appropriate length and scope of such restrictions. Reform of the Bankruptcy Act should also be considered. Possible areas for law reform including reducing the minimum period of bankruptcy; removing the permanency and/or public accessibility of the bankruptcy record; revising the language used in the Bankruptcy Act; and introducing a prohibition or restriction on the ability of employers to use bankruptcy status in employment decision making. Such changes would promote the fresh start objective of Australia’s bankruptcy system, and increase the likelihood that bankruptcy does not unfairly inhibit an individual’s ability to engage as an economic actor in Australian society and thereby improve their financial well-being.

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This study extends important insights into the motivation behind the Fairtrade impact disclosures the Fairtrade licensors, Fairtrade Labelling Organization International (FLO), and some of its major licensees. Reflecting on Bourdieu's institutional sociology and using thematic analysis method, this study reveals that Fairtrade impact disclosures are used to mediate the tension, challenges, and contradictions persist in the field. The findings provide important insights about the legitimizing strategy of the dominant Fairtrade organizations. Such insights are imperative for the regulatory bodies, social activists and academics working for the development of the accountability practices within the Fairtrade field.

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The most difficult operation in flood inundation mapping using optical flood images is to map the ‘wet’ areas where trees and houses are partly covered by water. This can be referred to as a typical problem of the presence of mixed pixels in the images. A number of automatic information extracting image classification algorithms have been developed over the years for flood mapping using optical remote sensing images, with most labelling a pixel as a particular class. However, they often fail to generate reliable flood inundation mapping because of the presence of mixed pixels in the images. To solve this problem, spectral unmixing methods have been developed. In this thesis, methods for selecting endmembers and the method to model the primary classes for unmixing, the two most important issues in spectral unmixing, are investigated. We conduct comparative studies of three typical spectral unmixing algorithms, Partial Constrained Linear Spectral unmixing, Multiple Endmember Selection Mixture Analysis and spectral unmixing using the Extended Support Vector Machine method. They are analysed and assessed by error analysis in flood mapping using MODIS, Landsat and World View-2 images. The Conventional Root Mean Square Error Assessment is applied to obtain errors for estimated fractions of each primary class. Moreover, a newly developed Fuzzy Error Matrix is used to obtain a clear picture of error distributions at the pixel level. This thesis shows that the Extended Support Vector Machine method is able to provide a more reliable estimation of fractional abundances and allows the use of a complete set of training samples to model a defined pure class. Furthermore, it can be applied to analysis of both pure and mixed pixels to provide integrated hard-soft classification results. Our research also identifies and explores a serious drawback in relation to endmember selections in current spectral unmixing methods which apply fixed sets of endmember classes or pure classes for mixture analysis of every pixel in an entire image. However, as it is not accurate to assume that every pixel in an image must contain all endmember classes, these methods usually cause an over-estimation of the fractional abundances in a particular pixel. In this thesis, a subset of adaptive endmembers in every pixel is derived using the proposed methods to form an endmember index matrix. The experimental results show that using the pixel-dependent endmembers in unmixing significantly improves performance.