2,826 research outputs found

    Australia\u27s solution to disability discrimination enforcement

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    [Excerpt] Until recently, Australian disability discrimination law was similar to that of the United States and much of the rest of the world: it defined disability relatively narrowly, its penalties for noncompliance were relatively paltry, and it depended on enforcement of lawsuits brought by aggrieved private citizens. In 2009, however, Australia adopted the Fair Work Act 2009 (FW Act). The FW Act defined disability much more broadly, increased substantially the penalties for noncompliance, and created a state institution to enforce disability rights. This article analyses the FW Act, compares it to the workplace disability law in the United States, and argues that the FW Act is a transformational development in the struggle to achieve workplace equality and is an approach that should attract significant international interest

    Surf

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    Pages 72-7

    Characterisation of dairy soiled water in a survey of 60 Irish dairy farms

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    peer-reviewedDairy farming in Ireland generates an effluent known as dairy soiled water (DSW), which consists of a relatively dilute mixture of cow faeces, urine, spilt milk and detergents that is typically applied to grassland. However, relatively little is known about the volumes generated, nutrient content and management factors that influence volume and concentration. Sixty dairy farms that had a separate storage tank for storing DSW were selected for this study. The spatial distribution of the farms reflected the spatial distribution of dairy cows across the 26 counties of the Republic of Ireland, with each farm representing between 10,000 and 20,000 dairy cows. Samples were analysed for biochemical oxygen demand (BOD), ammonium N (NH4-N), total nitrogen (TN), potassium (K), phosphorus (molybdate-reactive and total) (MRP and TP) and dry matter (DM) content. Management characteristics and parlour properties were quantified. Factors influencing volume and concentration of DSW were determined using mixed model multiple regression analysis. On average, 9784 l (standard error 209 l) of DSW, including rainfall, was produced cow−1 year−1 and this contained significant quantities of total N, P and K (587, 80 and 568 mg l−1, respectively). A typical Irish dairy farm stocked at 1.9 cows ha−1 could therefore supply approximately 13, 2 and 12 kg ha−1 of total N, P and K, respectively, across the farm, annually to meet some of the nutrient requirements for herbage production and potentially replace some of the synthetic fertilizer use. Seventy one percent of samples were within the regulated concentration limits of soiled water for BOD (<2500 mg l−1), rising to 87% during the closed period for slurry spreading (mid October to mid-late January), while 81% were within the concentration limits for DM (<1% DM), rising to 94% during the closed period. The efficiency of a milking parlour (cows per unit, time taken) plays a key role in determining the volume of DSW generated. This, in turn, also influences the concentration of nutrients and other chemicals. Large variability was found in nutrient concentrations and this presents a challenge for effective nutrient management to maximise the fertilizer replacement value of DSW

    Estimating the relative rate of recombination to mutation in bacteria from single-locus variants using composite likelihood methods

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    A number of studies have suggested using comparisons between DNA sequences of closely related bacterial isolates to estimate the relative rate of recombination to mutation for that bacterial species. We consider such an approach which uses single-locus variants: pairs of isolates whose DNA differ at a single gene locus. One way of deriving point estimates for the relative rate of recombination to mutation from such data is to use composite likelihood methods. We extend recent work in this area so as to be able to construct confidence intervals for our estimates, without needing to resort to computationally-intensive bootstrap procedures, and to develop a test for whether the relative rate varies across loci. Both our test and method for constructing confidence intervals are obtained by modeling the dependence structure in the data, and then applying asymptotic theory regarding the distribution of estimators obtained using a composite likelihood. We applied these methods to multi-locus sequence typing (MLST) data from eight bacteria, finding strong evidence for considerable rate variation in three of these: Bacillus cereus, Enterococcus faecium and Klebsiella pneumoniae.Comment: Published at http://dx.doi.org/10.1214/14-AOAS795 in the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

    The relationship between participation in a recreational program and self-concept of delinquent males

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    Automated Recognition of Brain Region Mentions in Neuroscience Literature

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    The ability to computationally extract mentions of neuroanatomical regions from the literature would assist linking to other entities within and outside of an article. Examples include extracting reports of connectivity or region-specific gene expression. To facilitate text mining of neuroscience literature we have created a corpus of manually annotated brain region mentions. The corpus contains 1,377 abstracts with 18,242 brain region annotations. Interannotator agreement was evaluated for a subset of the documents, and was 90.7% and 96.7% for strict and lenient matching respectively. We observed a large vocabulary of over 6,000 unique brain region terms and 17,000 words. For automatic extraction of brain region mentions we evaluated simple dictionary methods and complex natural language processing techniques. The dictionary methods based on neuroanatomical lexicons recalled 36% of the mentions with 57% precision. The best performance was achieved using a conditional random field (CRF) with a rich feature set. Features were based on morphological, lexical, syntactic and contextual information. The CRF recalled 76% of mentions at 81% precision, by counting partial matches recall and precision increase to 86% and 92% respectively. We suspect a large amount of error is due to coordinating conjunctions, previously unseen words and brain regions of less commonly studied organisms. We found context windows, lemmatization and abbreviation expansion to be the most informative techniques. The corpus is freely available at http://www.chibi.ubc.ca/WhiteText/

    Student Recital

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