Testing the assumptions of linear prediction analysis in normal vowels

This paper develops an improved surrogate data test to show experimental evidence, for all the simple vowels of US English, for both male and female speakers, that Gaussian linear prediction analysis, a ubiquitous technique in current speech technologies, cannot be used to extract all the dynamical structure of real speech time series. The test provides robust evidence undermining the validity of these linear techniques, supporting the assumptions of either dynamical nonlinearity and/or non-Gaussianity common to more recent, complex, efforts at dynamical modelling speech time series. However, an additional finding is that the classical assumptions cannot be ruled out entirely, and plausible evidence is given to explain the success of the linear Gaussian theory as a weak approximation to the true, nonlinear/non-Gaussian dynamics. This supports the use of appropriate hybrid linear/nonlinear/non-Gaussian modelling. With a calibrated calculation of statistic and particular choice of experimental protocol, some of the known systematic problems of the method of surrogate data testing are circumvented to obtain results to support the conclusions to a high level of significance

A Comparative Study of the Magnitude, Frequency and Distribution of Intense Rainfall in the United Kingdom

During the 1960s, a study was made of the magnitude, frequency and distribution of intense rainfall over the UK, employing data from more than 120 daily-read rain gauges covering the period 1911 to 1960. Using the same methodology, that study was recently updated utilizing data for the period 1961 to 2006 for the same gauges, or from those nearby. This paper describes the techniques applied to ensure consistency of data and statistical modelling. It presents a comparison of patterns of extreme rainfalls for the two periods and discusses the changes that have taken place. Most noticeably, increases up to 20% have occurred in the north west of the country and in parts of East Anglia. There have also been changes in other areas, including decreases of the same magnitude over central England. The implications of these changes are considered

Feedback control architecture & the bacterial chemotaxis network

Bacteria move towards favourable and away from toxic environments by changing their swimming pattern. This response is regulated by the chemotaxis signalling pathway, which has an important feature: it uses feedback to ‘reset’ (adapt) the bacterial sensing ability, which allows the bacteria to sense a range of background environmental changes. The role of this feedback has been studied extensively in the simple chemotaxis pathway of Escherichia coli. However it has been recently found that the majority of bacteria have multiple chemotaxis homologues of the E. coli proteins, resulting in more complex pathways. In this paper we investigate the configuration and role of feedback in Rhodobacter sphaeroides, a bacterium containing multiple homologues of the chemotaxis proteins found in E. coli. Multiple proteins could produce different possible feedback configurations, each having different chemotactic performance qualities and levels of robustness to variations and uncertainties in biological parameters and to intracellular noise. We develop four models corresponding to different feedback configurations. Using a series of carefully designed experiments we discriminate between these models and invalidate three of them. When these models are examined in terms of robustness to noise and parametric uncertainties, we find that the non-invalidated model is superior to the others. Moreover, it has a ‘cascade control’ feedback architecture which is used extensively in engineering to improve system performance, including robustness. Given that the majority of bacteria are known to have multiple chemotaxis pathways, in this paper we show that some feedback architectures allow them to have better performance than others. In particular, cascade control may be an important feature in achieving robust functionality in more complex signalling pathways and in improving their performance

Translating a walking intervention for health professional delivery within primary care: A mixed‐methods treatment fidelity assessment

Objectives: Existing fidelity studies of physical activity interventions are limited in methodological quality and rigour, particularly those delivered by health care providers in clinical settings. The present study aimed to enhance and assess the fidelity of a walking intervention delivered by health care providers within general practice in line with the NIH Behavior Change Consortium treatment fidelity framework. / Design: Two practice nurses and six health care assistants delivered a theory‐based walking intervention to 63 patients in their own practices. A cross‐sectional mixed‐methods study assessed fidelity related to treatment delivery and treatment receipt, from the perspectives of health care providers and patients. / Methods: All providers received training and demonstrated delivery competence prior to the trial. Delivery of intervention content was coded from audio‐recordings using a standardized checklist. Qualitative interviews with 12 patients were conducted to assess patient perspectives of treatment receipt and analysed using framework analysis. / Results: Overall, 78% of intervention components were delivered as per the protocol (range 36–91%), with greater fidelity for components requiring active engagement from patients (e.g., completion of worksheets). The qualitative data highlighted differences in patients’ comprehension of specific intervention components. Understanding of, and engagement with, motivational components aimed at improving self‐efficacy was poorer than for volitional planning components. / Conclusions: High levels of fidelity of delivery were demonstrated. However, patient‐, provider‐, and component‐level factors impacted on treatment delivery and receipt. We recommend that methods for the enhancement and assessment of treatment fidelity are consistently implemented to enhance the rigour of physical activity intervention research

An investigation into the synthesis, structural characterisation, thermal and polymorphic behaviour of organic crystalline materials

The organic solid state appears in a complex number of forms. The design, synthesis and application of solid state organic materials have a big impact upon society, e.g. pharmaceuticals. Traditionally, the process of selecting active pharmaceutical ingredients (APIs) was limited to free drug or accepted salt formulations. The cocrystallisation of APIs with a former molecule significantly increases the developmental options for APIs. Many pharmaceutical solids are prepared as polycrystalline materials in order to deliver favourable physical properties, i.e. solubility, bioavailability and stability. In such cases, the development and application of structure solution techniques via powder X-ray diffraction (pxrd) has played an ever increasing pivotal role. In this thesis a number of new multi-component materials; oxamic acid:nicotinamide, oxamic acid:isonicotinamide, fumaric acid:nicotinamide, maleic acid:nicotinamide and maleic acid:isonicotinamide, will be synthesised, via a number of synthetic methods, and fully structurally characterised. A direct comparison of structures solved by powder and single crystal diffraction, have been made in order to evaluate the reliability of structure solution from pxrd in these types of materials. The thermal behaviour of molecular materials will be presented as significant structural information can be extracted from the anisotropic expansion of molecular materials. In conjunction with the research into new multi-component materials, the structure solution of oxamic acid via pxrd, single X-ray diffraction and neutron diffraction will be investigated. Small organic molecular materials like oxamic acid provide a challenge to the crystallographer due to the similarities in the electron density surrounding each functional group in the molecule

Communique: Reponse de la Haute Autorite a la question ecrite No. 51 de Mme Erisia Gennai Tonietti et M. Pedini. European Coal and Steel Community High Authority Information Service. 24 July 1962

Experience curves are widely used to predict the cost benefits of increasing the deployment of a technology. But how good are such forecasts? Can one predict their accuracy a priori? In this paper we answer these questions by developing a method to make distributional forecasts for experience curves. We test our method using a dataset with proxies for cost and experience for 51 products and technologies and show that it works reasonably well. The framework that we develop helps clarify why the experience curve method often gives similar results to simply assuming that costs decrease exponentially. To illustrate our method we make a distributional forecast for prices of solar photovoltaic modules

Why do some asthma patients respond poorly to glucocorticoid therapy?

Glucocorticosteroids are the first-line therapy for controlling airway inflammation in asthma. They bind intracellular glucocorticoid receptors to trigger increased expression of anti-inflammatory genes and suppression of pro-inflammatory gene activation in asthmatic airways. In the majority of asthma patients, inhaled glucocorticoids are clinically efficacious, improving lung function and preventing exacerbations. However, 5–10 % of the asthmatic population respond poorly to high dose inhaled and then systemic glucocorticoids. These patients form a category of severe asthma associated with poor quality of life, increased morbidity and mortality, and constitutes a major societal and health care burden. Inadequate therapeutic responses to glucocorticoid treatment is also reported in other inflammatory conditions such as rheumatoid arthritis and inflammatory bowel disease; however, asthma represents the most studied steroid-refractory disease. Several cellular and molecular events underlying glucocorticoid resistance in asthma have been identified involving abnormalities of glucocorticoid receptor signaling pathways. These events have been strongly related to immunological dysregulation, genetic, and environmental factors such as cigarette smoking or respiratory infections. A better understanding of the multiple mechanisms associated with glucocorticoid insensitivity in asthma phenotypes could improve quality of life for people with asthma but would also provide transferrable knowledge for other inflammatory diseases. In this review, we provide an update on the molecular mechanisms behind steroid-refractory asthma. Additionally, we discuss some therapeutic options for treating those asthmatic patients who respond poorly to glucocorticoid therapy

Exploiting Nonlinear Recurrence and Fractal Scaling Properties for Voice Disorder Detection

Background: Voice disorders affect patients profoundly, and acoustic tools can potentially measure voice function objectively. Disordered sustained vowels exhibit wide-ranging phenomena, from nearly periodic to highly complex, aperiodic vibrations, and increased "breathiness". Modelling and surrogate data studies have shown significant nonlinear and non-Gaussian random properties in these sounds. Nonetheless, existing tools are limited to analysing voices displaying near periodicity, and do not account for this inherent biophysical nonlinearity and non-Gaussian randomness, often using linear signal processing methods insensitive to these properties. They do not directly measure the two main biophysical symptoms of disorder: complex nonlinear aperiodicity, and turbulent, aeroacoustic, non-Gaussian randomness. Often these tools cannot be applied to more severe disordered voices, limiting their clinical usefulness.

Methods: This paper introduces two new tools to speech analysis: recurrence and fractal scaling, which overcome the range limitations of existing tools by addressing directly these two symptoms of disorder, together reproducing a "hoarseness" diagram. A simple bootstrapped classifier then uses these two features to distinguish normal from disordered voices.

Results: On a large database of subjects with a wide variety of voice disorders, these new techniques can distinguish normal from disordered cases, using quadratic discriminant analysis, to overall correct classification performance of 91.8% plus or minus 2.0%. The true positive classification performance is 95.4% plus or minus 3.2%, and the true negative performance is 91.5% plus or minus 2.3% (95% confidence). This is shown to outperform all combinations of the most popular classical tools.

Conclusions: Given the very large number of arbitrary parameters and computational complexity of existing techniques, these new techniques are far simpler and yet achieve clinically useful classification performance using only a basic classification technique. They do so by exploiting the inherent nonlinearity and turbulent randomness in disordered voice signals. They are widely applicable to the whole range of disordered voice phenomena by design. These new measures could therefore be used for a variety of practical clinical purposes.
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