131 research outputs found

    I Get by With a Little Help From My Bots: Implications of Machine Agents in the Context of Social Support

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    In this manuscript we discuss the increasing use of machine agents as potential sources of support for humans. Continued examination of the use of machine agents, particularly chatbots (or “bots”) for support is crucial as more supportive interactions occur with these technologies. Building off extant research on supportive communication, this manuscript reviews research that has implications for bots as support providers. At the culmination of the literature review, several propositions regarding how factors of technological efficacy, problem severity, perceived stigma, and humanness affect the process of support are proposed. By reviewing relevant studies, we integrate research on human-machine and supportive communication to organize, extend, and provide a foundation for the growing body of work on machine agents for support

    Raman spectroscopy in head and neck cancer

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    In recent years there has been much interest in the use of optical diagnostics in cancer detection. Early diagnosis of cancer affords early intervention and greatest chance of cure. Raman spectroscopy is based on the interaction of photons with the target material producing a highly detailed biochemical 'fingerprint' of the sample. It can be appreciated that such a sensitive biochemical detection system could confer diagnostic benefit in a clinical setting. Raman has been used successfully in key health areas such as cardiovascular diseases, and dental care but there is a paucity of literature on Raman spectroscopy in Head and Neck cancer. Following the introduction of health care targets for cancer, and with an ever-aging population the need for rapid cancer detection has never been greater. Raman spectroscopy could confer great patient benefit with early, rapid and accurate diagnosis. This technique is almost labour free without the need for sample preparation. It could reduce the need for whole pathological specimen examination, in theatre it could help to determine margin status, and finally peripheral blood diagnosis may be an achievable target

    Milky Way Tomography IV: Dissecting Dust

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    We use SDSS photometry of 73 million stars to simultaneously obtain best-fit main-sequence stellar energy distribution (SED) and amount of dust extinction along the line of sight towards each star. Using a subsample of 23 million stars with 2MASS photometry, whose addition enables more robust results, we show that SDSS photometry alone is sufficient to break degeneracies between intrinsic stellar color and dust amount when the shape of extinction curve is fixed. When using both SDSS and 2MASS photometry, the ratio of the total to selective absorption, RVR_V, can be determined with an uncertainty of about 0.1 for most stars in high-extinction regions. These fits enable detailed studies of the dust properties and its spatial distribution, and of the stellar spatial distribution at low Galactic latitudes. Our results are in good agreement with the extinction normalization given by the Schlegel et al. (1998, SFD) dust maps at high northern Galactic latitudes, but indicate that the SFD extinction map appears to be consistently overestimated by about 20% in the southern sky, in agreement with Schlafly et al. (2010). The constraints on the shape of the dust extinction curve across the SDSS and 2MASS bandpasses support the models by Fitzpatrick (1999) and Cardelli et al. (1989). For the latter, we find an RV=3.0±0.1R_V=3.0\pm0.1(random) ±0.1\pm0.1(systematic) over most of the high-latitude sky. At low Galactic latitudes (|b|<5), we demonstrate that the SFD map cannot be reliably used to correct for extinction as most stars are embedded in dust, rather than behind it. We introduce a method for efficient selection of candidate red giant stars in the disk, dubbed "dusty parallax relation", which utilizes a correlation between distance and the extinction along the line of sight. We make these best-fit parameters, as well as all the input SDSS and 2MASS data, publicly available in a user-friendly format.Comment: Submitted to ApJ, 55 pages, 37 figure

    Waist circumference cut-off values for the prediction of cardiovascular risk factors clustering in Chinese school-aged children: a cross-sectional study

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    Background: Waist circumference has been identified as a valuable predictor of cardiovascular risk in children. The development of waist circumference percentiles and cut-offs for various ethnic groups are necessary because of differences in body composition. The purpose of this study was to develop waist circumference percentiles for Chinese children and to explore optimal waist circumference cut-off values for predicting cardiovascular risk factors clustering in this population.----- ----- Methods: Height, weight, and waist circumference were measured in 5529 children (2830 boys and 2699 girls) aged 6-12 years randomly selected from southern and northern China. Blood pressure, fasting triglycerides, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and glucose were obtained in a subsample (n = 1845). Smoothed percentile curves were produced using the LMS method. Receiver-operating characteristic analysis was used to derive the optimal age- and gender-specific waist circumference thresholds for predicting the clustering of cardiovascular risk factors.----- ----- Results: Gender-specific waist circumference percentiles were constructed. The waist circumference thresholds were at the 90th and 84th percentiles for Chinese boys and girls respectively, with sensitivity and specificity ranging from 67% to 83%. The odds ratio of a clustering of cardiovascular risk factors among boys and girls with a higher value than cut-off points was 10.349 (95% confidence interval 4.466 to 23.979) and 8.084 (95% confidence interval 3.147 to 20.767) compared with their counterparts.----- ----- Conclusions: Percentile curves for waist circumference of Chinese children are provided. The cut-off point for waist circumference to predict cardiovascular risk factors clustering is at the 90th and 84th percentiles for Chinese boys and girls, respectively

    A comparison of optimisation algorithms for high-dimensional particle and astrophysics applications

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    Optimisation problems are ubiquitous in particle and astrophysics, and involve locating the optimum of a complicated function of many parameters that may be computationally expensive to evaluate. We describe a number of global optimisation algorithms that are not yet widely used in particle astrophysics, benchmark them against random sampling and existing techniques, and perform a detailed comparison of their performance on a range of test functions. These include four analytic test functions of varying dimensionality, and a realistic example derived from a recent global fit of weak-scale supersymmetry. Although the best algorithm to use depends on the function being investigated, we are able to present general conclusions about the relative merits of random sampling, Differential Evolution, Particle Swarm Optimisation, the Covariance Matrix Adaptation Evolution Strategy, Bayesian Optimisation, Grey Wolf Optimisation, and the PyGMO Artificial Bee Colony, Gaussian Particle Filter and Adaptive Memory Programming for Global Optimisation algorithms

    Adenovirus-Associated Virus Vector-Mediated Gene Transfer in Hemophilia B

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    NIHR (RP-PG-0310-1001), the Medical Research Council, the Katharine Dormandy Trust, the U.K. Department of Health, NHS Blood and Transplant, the NIHR Biomedical Research Centers (to University College London Hospital and University College London), the ASSISI Foundation of Memphis, the American Lebanese Syrian Associated Charities, the Howard Hughes Medical Institute, the National Heart, Lung, and Blood Institute (HL094396), the Royal Free Hospital Charity Special Trustees Fund 35, the Royal Free Hospital NHS Trust, and St. Jude Children’s Research Hospita

    Indirect effects of video chat on outcomes of receiving support: Uniting theorizing about supportive communication and computer-mediated communication

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    This study integrates theorizing about supportive communication and computer-mediated communication to investigate how features of the interactional context, social presence, and evaluations of supportive messages shape recipients’ emotional improvement. Participants (N = 139) reported to the lab with a friend, where they were randomly assigned to experimental conditions that varied the lighting quality of the physical setting and screen size of the device for a video-mediated supportive conversation, which are relevant and impactful features of video chat interactions. Results were consistent with theorizing: Lighting quality exerted a positive serial indirect effect on receivers’ emotional improvement because of its influence on social presence, which in turn influenced evaluations of support. Findings are discussed as they relate to the role of social presence in explaining how contextual features shape video-mediated supportive conversations.</p
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