244 research outputs found

    Tommy, lad!: song

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    https://digitalcommons.ithaca.edu/sheetmusic/1136/thumbnail.jp

    Tommy, lad!

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    https://digitalcommons.library.umaine.edu/mmb-vp/6047/thumbnail.jp

    Sonic immersion: reaching new audiences through sound

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    This PhD thesis is a practice-based effort to respond to the homogenisation of acousmatic audiences to niche cliques of practitioners. It consists of a portfolio of nine acousmatic compositions in stereophonic and multichannel formats and a written commentary. Two of the compositions form part of a larger collaborative work/project (Sound Sculptures (section 4.4) and Ancestor 1 (section 4.5)). The commentary discusses the creative and compositional processes behind the acousmatic works, building upon a variety of approaches to engaging wider audiences with the medium of sound. Through exploring various approaches to audience engagement, audience development and collaboration (with other artists, art forms and organisations), this practice-based research explores how an electroacoustic composer may reach new and existing audiences. This has led to a variety of dissemination outcomes including performances, site-specific works, installations and workshops. All compositions have been composed in the electroacoustic studios at the University of Birmingham using Reaper, GRM Tools, Ableton Live, The Ambisonic Toolkit, IEM Plug-in Suite, O3A Core (Blue Ripple Sound), SoundMagic Spectral (Michael Norris), SoundHack and RX 8 (Izotope). The multichannel works (8 and 16 channels) have been decoded using ATK plugins for binaural listening purposes

    Impact of food, alcohol and pH on modified-release hydrocortisone developed to treat congenital adrenal hyperplasia.

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    BACKGROUND: We developed a modified-release hydrocortisone, Chronocort®, to replace the cortisol rhythm in patients with congenital adrenal hyperplasia. Food, alcohol and pH affect drug absorption and it is important to assess their impact when replicating a physiological rhythm. SUBJECTS AND METHODS: In vitro dissolution to study impact of alcohol and pH on Chronocort®. A Phase 1, three-period, cross over study in 18 volunteers to assess the impact of food on Chronocort® and to compare bioavailability to immediate-release hydrocortisone. RESULTS: In vitro dissolution of Chronocort® was not affected by gastrointestinal pH up to 6.0 nor by an alcohol content up to 20 % v/v. Food delayed and reduced the rate of absorption of Chronocort® as reflected by a longer Tmax (fed vs fasted: 6.75 hrs vs 4.5 hrs, p=0005) and lower Cmax (549.49 vs 708.46, nmol/L, ratio 77% with CI 71 - 85). Cortisol exposure was similar in fed and fasted state: Geo LSmean ratio (CI) AUC0 t for fed/fasted was 108.33% (102.30 - 114.72%). Cortisol exposure was higher for Chronocort® compared to immediate-release hydrocortisone: Geo LSmean ratios (CI) 118.83% (111.58 - 126.54%); however, derived free cortisol showed cortisol exposure CIs were within 80.0 125.0 %: Geo LSmean ratio (CI) for AUC0 t 112.73% (105.33 - 120.65%). CONCLUSIONS: Gastric pH ≤ 6.0 and alcohol do not effect hydrocortisone release from Chronocort®. Food delays Chronocort® absorption but cortisol exposure is similar in the fasted and fed state and exposure as assessed by free cortisol is similar between Chronocort® and immediate-release hydrocortisone

    Measure Transformer Semantics for Bayesian Machine Learning

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    The Bayesian approach to machine learning amounts to computing posterior distributions of random variables from a probabilistic model of how the variables are related (that is, a prior distribution) and a set of observations of variables. There is a trend in machine learning towards expressing Bayesian models as probabilistic programs. As a foundation for this kind of programming, we propose a core functional calculus with primitives for sampling prior distributions and observing variables. We define measure-transformer combinators inspired by theorems in measure theory, and use these to give a rigorous semantics to our core calculus. The original features of our semantics include its support for discrete, continuous, and hybrid measures, and, in particular, for observations of zero-probability events. We compile our core language to a small imperative language that is processed by an existing inference engine for factor graphs, which are data structures that enable many efficient inference algorithms. This allows efficient approximate inference of posterior marginal distributions, treating thousands of observations per second for large instances of realistic models.Comment: An abridged version of this paper appears in the proceedings of the 20th European Symposium on Programming (ESOP'11), part of ETAPS 201

    1000 Families Study, a UK multiwave cohort investigating the well-being of families of children with intellectual disabilities : cohort profile

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    Purpose: The 1000 Families Study is a large, UK-based, cohort of families of children with intellectual disability (ID). The main use of the cohort data will be to describe and explore correlates of the well-being of families of children with ID, including parents and siblings, using cross-sectional and (eventually) longitudinal analyses. The present cohort profile intends to describe the achieved cohort. Participants: Over 1000 families of UK children with ID aged between 4 and 15 years 11 months (total n=1184) have been recruited. The mean age of the cohort was 9.01 years old. The cohort includes more boys (61.8%) than girls (27.0%; missing 11.1%). Parents reported that 45.5% (n=539) of the children have autism. Most respondents were a female primary caregiver (84.9%), and 78.0% were the biological mother of the cohort child with ID. The largest ethnic group for primary caregivers was White British (78.5%), over half were married and living with their partner (53.3%) and 39.3% were educated to degree level. Findings: to date Data were collected on family, parental and child well-being, as well as demographic information. Wave 1 data collection took place between November 2015 and January 2017, primarily through online questionnaires. Telephone interviews were also completed by 644 primary caregivers. Future plans: Wave 2 data collection is ongoing and the research team will continue following up these families in subsequent waves, subject to funding availability. Results will be used to inform policy and practice on family and child well-being in families of children with ID. As this cohort profile aims to describe the cohort, future publications will explore relevant research questions and report key findings related to family well-being
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