201,278 research outputs found

    A Multiscale Investigation of Habitat Use and Within-river Distribution of Sympatric Sand Darter Species

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    The western sand darter Ammocrypta clara, and eastern sand darter Ammocrypta pellucida are sand-dwelling fishes of conservation concern. Past research has emphasized the importance of studying individual populations of conservation concern, while recent research has revealed the importance of incorporating landscape scale processes that structure habitat mosaics and local populations. We examined habitat use and distributions of western and eastern sand darters in the lower Elk River of West Virginia. At the sandbar habitat use scale, western sand darters were detected in sandbars with greater area, higher proportions of coarse grain sand and faster bottom current velocity, while the eastern sand darter used a wider range of sandbar habitats. The landscape scale analysis revealed that contributing drainage area was an important predictor for both species, while sinuosity, which presumably represents valley type also contributed to the western sand darter’s habitat suitability. Sandbar quality (area, grain size, and velocity) and fluvial geomorphic variables (drainage area and valley type) are likely key driving factors structuring sand darter distributions in the Elk River. This multiscale study of within-river species distribution and habitat use is unique, given that only a few sympatric populations are known of western and eastern sand darters

    Outcomes of HIV treatment from the private sector in low-income and middle-income countries: a systematic review protocol

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    Introduction: Private sector provision of HIV treatment is increasing in low-income and middle-income countries (LMIC). However, there is limited documentation of its outcomes. This protocol reports a proposed systematic review that will synthesise clinical outcomes of private sector HIV treatment in LMIC. Methods and analysis: This review will be conducted in accordance with the preferred reporting items for systematic review and meta-analyses protocols. Primary outcomes will include: (1) proportion of eligible patients initiating antiretroviral therapy (ART); (2) proportion of those on ART with 90% ART adherence (based on any measure reported); (3) proportion screened for non-communicable diseases (specifically cervical cancer, diabetes, hypertension and mental ill health); (iv) proportion screened for tuberculosis. A search of five electronic bibliographical databases (Embase, Medline, PsychINFO, Web of Science and CINAHL) and reference lists of included articles will be conducted to identify relevant articles reporting HIV clinical outcomes. Searches will be limited to LMIC. No age, publication date, study-design or language limits will be applied. Authors of relevant studies will be contacted for clarification. Two reviewers will independently screen citations and abstracts, identify full text articles for inclusion, extract data and appraise the quality and bias of included studies. Outcome data will be pooled to generate aggregative proportions of primary and secondary outcomes. Descriptive statistics and a narrative synthesis will be presented. Heterogeneity and sensitivity assessments will be conducted to aid interpretation of results. Ethics and dissemination: The results of this review will be disseminated through a peer-reviewed scientific manuscript and at international scientific conferences. Results will inform quality improvement strategies, replication of identified good practices, potential policy changes, and future research

    Semantic Stability in Social Tagging Streams

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    One potential disadvantage of social tagging systems is that due to the lack of a centralized vocabulary, a crowd of users may never manage to reach a consensus on the description of resources (e.g., books, users or songs) on the Web. Yet, previous research has provided interesting evidence that the tag distributions of resources may become semantically stable over time as more and more users tag them. At the same time, previous work has raised an array of new questions such as: (i) How can we assess the semantic stability of social tagging systems in a robust and methodical way? (ii) Does semantic stabilization of tags vary across different social tagging systems and ultimately, (iii) what are the factors that can explain semantic stabilization in such systems? In this work we tackle these questions by (i) presenting a novel and robust method which overcomes a number of limitations in existing methods, (ii) empirically investigating semantic stabilization processes in a wide range of social tagging systems with distinct domains and properties and (iii) detecting potential causes for semantic stabilization, specifically imitation behavior, shared background knowledge and intrinsic properties of natural language. Our results show that tagging streams which are generated by a combination of imitation dynamics and shared background knowledge exhibit faster and higher semantic stability than tagging streams which are generated via imitation dynamics or natural language streams alone

    Inspecting post-16 art and design : with guidance on self-evaluation

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    Managing change in North Shore’s Residential 3 Built Heritage zone: An evaluation of resource consent outcomes

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    The goal of the study presented in this report has been to determine the extent to which resource consent outcomes in North Shore City’s Residential 3 Built Heritage zone comply with the District Plan. To this end, a sample of 250 properties was selected representing a sample size of 6.5%. The records for each of these properties was checked to identify those that have had a consent granted for additions and alterations to buildings, new and relocated buildings, and the demolition or removal of houses in the Residential 3 zone. This revealed that 100 properties in the sample (or 40%) have been granted a total of 126 resource consents for one or more of these activities. Each of the 100 properties was visited and the outcomes of the consents were compared against the District Plan assessment criteria

    A Neural Network Method for Mixture Estimation for Vegetation Mapping

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    While most forest maps identify only the dominant vegetation class in delineated stands, individual stands are often better characterized by a mix of vegetation types. Many land management applications, including wildlife habitat studies, can benefit from knowledge of mixes. This paper examines various algorithms that use data from the Landsat Thematic Mapper (TM) satellite to estimate mixtures of vegetation types within forest stands. Included in the study are maximum likelihood classification and linear mixture models as well as a new methodology based on the ARTMAP neural network. Two paradigms are considered: classification methods, which describe stand-level vegetation mixtures as mosaics of pixels, each identified with its primary vegetation class; and mixture methods, which treat samples as blends of vegetation, even at the pixel level. Comparative analysis of these mixture estimation methods, tested on data from the Plumas National Forest, yields the following conclusions: (1) accurate estimates of proportions of hardwood and conifer cover within stands can be obtained, particularly when brush is not present in the understory; (2) ARTMAP outperforms statistical methods and linear mixture models in both the classification and the mixture paradigms; (3) topographic correction fails to improve mapping accuracy; and (4) the new ARTMAP mixture system produces the most accurate overall results. The Plumas data set has been made available to other researchers for further development of new mapping methods and comparison with the quantitative studies presented here, which establish initial benchmark standards.National Science Foundation (IRI 94-0165, SBR 95-13889); Office of Naval Research (N00014-95-1-0409, N00014-95-0657); Region 5 Remote Sensing Laboratory of the U.S. Forest Servic

    Correction for founder effects in host-viral association studies via principal components

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    Viruses such as HIV and Hepatitis C (HCV) replicate rapidly and with high transcription error rates, which may facilitate their escape from immune detection through the encoding of mutations at key positions within human leukocyte antigen (HLA)-specific peptides, thus impeding T-cell recognition. Large-scale population-based host-viral association studies are conducted as hypothesis-generating analyses which aim to determine the positions within the viral sequence at which host HLA immune pressure may have led to these viral escape mutations. When transmission of the virus to the host is HLA-associated, however, standard tests of association can be confounded by the viral relatedness of contemporarily circulating viral sequences, as viral sequences descended from a common ancestor may share inherited patterns of polymorphisms, termed 'founder effects'. Recognizing the correspondence between this problem and the confounding of case-control genome-wide association studies by population stratification, we adapt methods taken from that field to the analysis of host-viral associations. In particular, we consider methods based on principal components analysis within a logistic regression framework motivated by alternative formulations in the Frisch-Waugh-Lovell Theorem. We demonstrate via simulation their utility in detecting true host-viral associations whilst minimizing confounding by associations generated by founder effects. The proposed methods incorporate relatively robust, standard statistical procedures which can be easily implemented using widely available software, and provide alternatives to the more complex computer intensive methods often implemented in this area

    Higher education provision in the United Kingdom: an analysis of HE workforce data

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    "This report is an analysis of Higher Education (HE) provision in the United Kingdom. It brings together information about the HE workforce from diverse sources, and provides an authoritative and comprehensive set of facts, figures and insights relating to the UK higher education sector." - Page 3
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