87 research outputs found

    Assay of aminoglycosides is influenced by tissue homogenization technique

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    Recovery of neomycin from tissue homogenates was lower when glass/glass homogenizers were used due to the abrasion of glass which will bind to the drug. Glass homogenizers should be avoided for the determination of aminoglycoside levels in tissues.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/42733/1/18_2005_Article_BF01948411.pd

    Thermodynamic Properties of the Dimerised and Frustrated S=1/2 Chain

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    By high temperature series expansion, exact diagonalisation and temperature density-matrix renormalisation the magnetic susceptibility χ(T)\chi(T) and the specific heat C(T)C(T) of dimerised and frustrated S=1/2S=1/2 chains are computed. All three methods yield reliable results, in particular for not too small temperatures or not too small gaps. The series expansion results are provided in the form of polynomials allowing very fast and convenient fits in data analysis using algebraic programmes. We discuss the difficulty to extract more than two coupling constants from the temperature dependence of χ(T)\chi(T).Comment: 14 pages, 13 figures, 4 table

    Customer emotions in service failure and recovery encounters

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    Emotions play a significant role in the workplace, and considerable attention has been given to the study of employee emotions. Customers also play a central function in organizations, but much less is known about customer emotions. This chapter reviews the growing literature on customer emotions in employee–customer interfaces with a focus on service failure and recovery encounters, where emotions are heightened. It highlights emerging themes and key findings, addresses the measurement, modeling, and management of customer emotions, and identifies future research streams. Attention is given to emotional contagion, relationships between affective and cognitive processes, customer anger, customer rage, and individual differences

    The Anorexia Nervosa Genetics Initiative (ANGI): Overview and methods

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    Background: Genetic factors contribute to anorexia nervosa (AN); and the first genome-wide significant locus has been identified. We describe methods and procedures for the Anorexia Nervosa Genetics Initiative (ANGI), an international collaboration designed to rapidly recruit 13,000 individuals with AN and ancestrally matched controls. We present sample characteristics and the utility of an online eating disorder diagnostic questionnaire suitable for large-scale genetic and population research. Methods: ANGI recruited from the United States (US), Australia/New Zealand (ANZ), Sweden (SE), and Denmark (DK). Recruitment was via national registers (SE, DK); treatment centers (US, ANZ, SE, DK); and social and traditional media (US, ANZ, SE). All cases had a lifetime AN diagnosis based on DSM-IV or ICD-10 criteria (excluding amenorrhea). Recruited controls had no lifetime history of disordered eating behaviors. To assess the positive and negative predictive validity of the online eating disorder questionnaire (ED100K-v1), 109 women also completed the Structured Clinical Interview for DSM-IV (SCID), Module H. Results: Blood samples and clinical information were collected from 13,363 individuals with lifetime AN and from controls. Online diagnostic phenotyping was effective and efficient; the validity of the questionnaire was acceptable. Conclusions: Our multi-pronged recruitment approach was highly effective for rapid recruitment and can be used as a model for efforts by other groups. High online presence of individuals with AN rendered the Internet/social media a remarkably effective recruitment tool in some countries. ANGI has substantially augmented Psychiatric Genomics Consortium AN sample collection. ANGI is a registered clinical trial: clinicaltrials.govNCT01916538; https://clinicaltrials.gov/ct2/show/NCT01916538?cond=Anorexia+Nervosa&draw=1&rank=3

    Overview of the JET results in support to ITER

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    Multifactor B-spline mixed models in designed experiments for the engine mapping problem

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    Polynomial spline regression models using B-spline basis functions are shown to provide greater flexibility and lead to more accurate predictions than traditional polynomial models. Use of multifactor B-spline regression models is described in a case study from the automotive industry in engine mapping using a two-stage hierarchical model. The accuracy and effectiveness of the approach is demonstrated with validation runs
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