898 resultados para Choruses, Secular (Mixed voices) with orchestra--Vocal scores with piano


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Bipolar mixed states combine depressive and manic features, presenting diagnostic and treatment challenges and reflecting a severe form of the illness. DSM-IV criteria for a mixed state require combined depressive and manic syndromes, but a range of mixed states has been described clinically. A unified definition of mixed states would be valuable in understanding their diagnosis, mechanism and treatment implications. We investigated the manner in which depressive and manic features combine to produce a continuum of mixed states. In 88 subjects with bipolar disorder (DSM-IV), we evaluated symptoms and clinical characteristics, and compared depression-based, mania-based, and other published definitions of mixed states. We developed an index of the extent to which symptoms were mixed (Mixed State Index, MSI) and characterized its relationship to clinical state. Predominately manic and depressive mixed states using criteria from recent literature, as well as Kraepelinian mixed states, had similar symptoms and MSI scores. Anxiety correlated significantly with depression scores in manic subjects and with mania scores in depressed subjects. Discriminant function analysis associated mixed states with symptoms of hyperactivity and negative cognitions, but not subjective depressive or elevated mood. High MSI scores were associated with severe course of illness. For depressive or manic episodes, characteristics of mixed states emerged with two symptoms of the opposite polarity. This was a cross-sectional study. Mixed states appear to be a continuum. An index of the degree to which depressive and manic symptoms combine appears useful in identifying and characterizing mixed states. We propose a depressive or manic episode with three or more symptoms of the opposite polarity as a parsimonious definition of a mixed state.

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Contains 83 glees and madrigals for various combinations of voices, with optional piano accompaniment.

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Mode of access: Internet.

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In portfolio.

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Duration: 20:00.

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For mixed voices (SATB) and piano.

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Mode of access: Internet.

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Thesis (Ph.D.)--University of Washington, 2016-06

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Accurate knowledge of species’ habitat associations is important for conservation planning and policy. Assessing habitat associations is a vital precursor to selecting appropriate indicator species for prioritising sites for conservation or assessing trends in habitat quality. However, much existing knowledge is based on qualitative expert opinion or local scale studies, and may not remain accurate across different spatial scales or geographic locations. Data from biological recording schemes have the potential to provide objective measures of habitat association, with the ability to account for spatial variation. We used data on 50 British butterfly species as a test case to investigate the correspondence of data-derived measures of habitat association with expert opinion, from two different butterfly recording schemes. One scheme collected large quantities of occurrence data (c. 3 million records) and the other, lower quantities of standardised monitoring data (c. 1400 sites). We used general linear mixed effects models to derive scores of association with broad-leaf woodland for both datasets and compared them with scores canvassed from experts. Scores derived from occurrence and abundance data both showed strongly positive correlations with expert opinion. However, only for occurrence data did these fell within the range of correlations between experts. Data-derived scores showed regional spatial variation in the strength of butterfly associations with broad-leaf woodland, with a significant latitudinal trend in 26% of species. Sub-sampling of the data suggested a mean sample size of 5000 occurrence records per species to gain an accurate estimation of habitat association, although habitat specialists are likely to be readily detected using several hundred records. Occurrence data from recording schemes can thus provide easily obtained, objective, quantitative measures of habitat association.

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Purpose: The aim of the present paper was to determine the effect of different types of ionizing radiation on the bond strength of three different dentin adhesive systems. Materials and Methods: One hundred twenty specimens of 60 human teeth (protocol number: 032/2007) sectioned mesiodistally were divided into 3 groups according to the adhesives systems used: SB (Adper Single Bond Plus), CB (Clearfil SE Bond) and AP (Adper Prompt Self-Etch). The adhesives were applied on dentin and photo-activated using LED (Lec 1000, MMoptics, 1000 mW/cm(2)). Customized elastomer molds (0.5 mm thickness) with three orifices of 1.2 mm diameter were placed onto the bonding areas and filled with composite resin (Filtek Z-250), which was photo-activated for 20 s. Each group was subdivided into 4 Subgroups for application of the different types of ionizing radiation: ultraviolet radiation (UV), diagnostic x-ray radiation (DX), therapeutic x-ray radiation (TX) and without irradiation (control group, CG). Microshear tests were carried out (Instron, model 4411), and afterwards the modes of failure were evaluated by optical and scanning electron microscope and classified using 5 scores: adhesive failure, mixed failures with 3 significance levels, and cohesive failure. The results of the shear bond strength test were submitted to ANOVA with Tukey`s test and Dunnett`s test, and the data from the failure pattern evaluation were analyzed with the Mann Whitney test (p = 0.05). Results: No change in bond strength of CB and AP was observed after application of the different radiation types, only SB showed increase in bond strength after UV (p = 0.0267) irradiation. The UV also changed the failure patterns of SB (p = 0.0001). Conclusion: The radio-induced changes did not cause degradation of the restorations, which means that they can be exposed to these types of ionizing radiation without weakening the bond strength.

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This paper presents a two-step pseudo likelihood estimation technique for generalized linear mixed models with the random effects being correlated between groups. The core idea is to deal with the intractable integrals in the likelihood function by multivariate Taylor's approximation. The accuracy of the estimation technique is assessed in a Monte-Carlo study. An application of it with a binary response variable is presented using a real data set on credit defaults from two Swedish banks. Thanks to the use of two-step estimation technique, the proposed algorithm outperforms conventional pseudo likelihood algorithms in terms of computational time.