796 research outputs found

    The relation of religion to morals in Christianity

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    Memory Performance Influences Male Reproductive Success in a Wild Bird.

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    Not applicableMarsden Fund (Royal Society of New Zealand

    Perceived Differences in the Management of Mental Health Patients in Remote and Rural Australia and Strategies for Improvement: Findings from a National Qualitative Study of Emergency Clinicians

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    Introduction. We aimed to describe perceptions of Australian emergency clinicians of differences in management of mental health patients in rural and remote Australia compared with metropolitan hospitals, and what could be improved. Methods. Descriptive exploratory study using semi-structured telephone interviews of doctors and nurses in Australian emergency departments (EDs), stratified to represent states and territories and rural or metropolitan location. Content analysis of responses developed themes and sub-themes. Results. Of 39 doctors and 32 nurses responding to email invitation, 20 doctors and 16 nurses were interviewed. Major themes were resources/environment, staff and patient issues. Clinicians noted lack of access in rural areas to psychiatric support services, especially alcohol and drug services, limited referral options, and a lack of knowledge, understanding and acceptance of mental health issues. The clinicians suggested resource, education and guideline improvements, wanting better access to mental health experts in rural areas, better support networks and visiting specialist coverage, and educational courses tailored to the needs of rural clinicians. Conclusion. Clinicians managing mental health patients in rural and remote Australian EDs lack resources, support services and referral capacity, and access to appropriate education and training. Improvements would better enable access to support and referral services, and educational opportunities

    A Design Kit for Mobile Device-Based Interaction Techniques

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    Beside designing the graphical interface of mobile applications, mobile phones and their built-in sensors enable various possibilities to engage with digital content in a physical, device-based manner that move beyond the screen content. So-called mobile device-based interactions are characterized by device movements and positions as well as user actions in real space. So far, there is only little guidance available for novice designers and developers to ideate and design new solutions for specic individual or collaborative use cases. Hence, the potential for designing mobile-based interactions is seldom fully exploited. To address this issue, we propose a design kit for mobile device-based interaction techniques following a morphological approach. Overall, the kit comprises seven dimensions with several elements that can be easily combined with each other to form an interaction technique by selecting at least one entry of each dimension. The design kit can be used to support designers in exploring novel mobile interaction techniques to specic interaction problems in the ideation phase of the design process but also in the analysis of existing device-based interaction solutions

    Does policy uncertainty increase relational risks? Evidence from strategic alliances

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    Prior studies on capital investments, including mergers and acquisitions, point to investment irreversibility as the primary factor behind diminished investments during periods of increased policy uncertainty. We show that increased relational risk, due to the potential for counterparty misbehavior or shirking and higher contracting costs, appears to be the primary driver behind the diminished propensity to undertake strategic alliances during enhanced policy uncertainty regimes. Alliances are even less likely during such times when they (a) involve more than two firms, (b) are in industries with greater counterparty risk, and (c) involve partners that require intense contracts

    Detecting modification of biomedical events using a deep parsing approach

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    <p>Abstract</p> <p>Background</p> <p>This work describes a system for identifying event mentions in bio-molecular research abstracts that are either speculative (e.g. <it>analysis of IkappaBalpha phosphorylation</it>, where it is not specified whether phosphorylation did or did not occur) or negated (e.g. <it>inhibition of IkappaBalpha phosphorylation</it>, where phosphorylation did <it>not </it>occur). The data comes from a standard dataset created for the BioNLP 2009 Shared Task. The system uses a machine-learning approach, where the features used for classification are a combination of shallow features derived from the words of the sentences and more complex features based on the semantic outputs produced by a deep parser.</p> <p>Method</p> <p>To detect event modification, we use a Maximum Entropy learner with features extracted from the data relative to the trigger words of the events. The shallow features are bag-of-words features based on a small sliding context window of 3-4 tokens on either side of the trigger word. The deep parser features are derived from parses produced by the English Resource Grammar and the <it>RASP </it>parser. The outputs of these parsers are converted into the Minimal Recursion Semantics formalism, and from this, we extract features motivated by linguistics and the data itself. All of these features are combined to create training or test data for the machine learning algorithm.</p> <p>Results</p> <p>Over the test data, our methods produce approximately a 4% absolute increase in F-score for detection of event modification compared to a baseline based only on the shallow bag-of-words features.</p> <p>Conclusions</p> <p>Our results indicate that grammar-based techniques can enhance the accuracy of methods for detecting event modification.</p
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