1,320 research outputs found

    Linear stability analysis of capillary instabilities for concentric cylindrical shells

    Full text link
    Motivated by complex multi-fluid geometries currently being explored in fibre-device manufacturing, we study capillary instabilities in concentric cylindrical flows of NN fluids with arbitrary viscosities, thicknesses, densities, and surface tensions in both the Stokes regime and for the full Navier--Stokes problem. Generalizing previous work by Tomotika (N=2), Stone & Brenner (N=3, equal viscosities) and others, we present a full linear stability analysis of the growth modes and rates, reducing the system to a linear generalized eigenproblem in the Stokes case. Furthermore, we demonstrate by Plateau-style geometrical arguments that only axisymmetric instabilities need be considered. We show that the N=3 case is already sufficient to obtain several interesting phenomena: limiting cases of thin shells or low shell viscosity that reduce to N=2 problems, and a system with competing breakup processes at very different length scales. The latter is demonstrated with full 3-dimensional Stokes-flow simulations. Many N>3N > 3 cases remain to be explored, and as a first step we discuss two illustrative NN \to \infty cases, an alternating-layer structure and a geometry with a continuously varying viscosity

    Iowan Drift Problem, Northeastern Iowa

    Get PDF
    https://ir.uiowa.edu/igs_ri/1006/thumbnail.jp

    Monitoring of somatic parameters at outpatient departments for mood and anxiety disorders

    Get PDF
    INTRODUCTION: Somatic complications account for the majority of the 13-30 years shortened life expectancy in psychiatric patients compared to the general population. The study aim was to assess to which extent patients visiting outpatient departments for mood and anxiety disorders were monitored for relevant somatic comorbidities and (adverse) effects of psychotropic drugs-more specifically a) metabolic parameters, b) lithium safety and c) ECGs-during their treatment. METHODS: We performed a retrospective clinical records review and cross-sectional analysis to assess the extent of somatic monitoring at four outpatient departments for mood and anxiety disorders in The Netherlands. We consecutively recruited adult patients visiting a participating outpatient department between March and November 2014. The primary outcome was percentage of patients without monitoring measurements. Secondary outcomes were number of measurements per parameter per patient per year and time from start of treatment to first measurement. RESULTS: We included 324 outpatients, of whom 60.2% were female. Most patients were treated for depressive disorders (39.8%), anxiety disorders (16.7%) or bipolar or related disorders (11.7%) and 198 patients (61.1%) used at least one psychotropic drug. For 186 patients (57.4%), no monitoring records were recorded (median treatment period 7.3 months, range 0-55.6). The median number of measurements per parameter per year since the start of outpatient treatment for patients with monitoring measurements was 0.31 (range 0.0-12.9). The median time to first monitoring measurement per parameter for patients with monitoring measurements was 3.8 months (range 0.0-50.7). DISCUSSION: Somatic monitoring in outpatients with mood and anxiety disorders is not routine clinical practice. Monitoring practices need to be improved to prevent psychiatric outpatients from undetected somatic complications

    Pain relief is associated with decreasing postural sway in patients with non-specific low back pain

    Get PDF
    Background Increased postural sway is well documented in patients suffering from non-specific low back pain, whereby a linear relationship between higher pain intensities and increasing postural sway has been described. No investigation has been conducted to evaluate whether this relationship is maintained if pain levels change in adults with non-specific low back pain. Methods Thirty-eight patients with non-specific low back pain and a matching number of healthy controls were enrolled. Postural sway was measured by three identical static bipedal standing tasks of 90 sec duration with eyes closed in narrow stance on a firm surface. The perceived pain intensity was assessed by a numeric rating scale (NRS-11). The patients received three manual interventions (e.g. manipulation, mobilization or soft tissue techniques) at 3-4 day intervals, postural sway measures were obtained at each occasion. Results A clinically relevant decrease of four NRS scores in associated with manual interventions correlated with a significant decrease in postural sway. In contrast, if no clinically relevant change in intensity occurred ([less than or equal to]1 level), postural sway remained similar compared to baseline. The postural sway measures obtained at follow-up sessions 2 and 3 associated with specific NRS level showed no significant differences compared to reference values for the same pain score. Conclusions Alterations in self-reported pain intensities are closely related to changes in postural sway. The previously reported linear relationship between the two variables is maintained as pain levels change. Pain interference appears responsible for the altered sway in pain sufferers. This underlines the clinical use of sway measures as an objective monitoring tool during treatment or rehabilitation

    Scalable Tensor Factorizations for Incomplete Data

    Full text link
    The problem of incomplete data - i.e., data with missing or unknown values - in multi-way arrays is ubiquitous in biomedical signal processing, network traffic analysis, bibliometrics, social network analysis, chemometrics, computer vision, communication networks, etc. We consider the problem of how to factorize data sets with missing values with the goal of capturing the underlying latent structure of the data and possibly reconstructing missing values (i.e., tensor completion). We focus on one of the most well-known tensor factorizations that captures multi-linear structure, CANDECOMP/PARAFAC (CP). In the presence of missing data, CP can be formulated as a weighted least squares problem that models only the known entries. We develop an algorithm called CP-WOPT (CP Weighted OPTimization) that uses a first-order optimization approach to solve the weighted least squares problem. Based on extensive numerical experiments, our algorithm is shown to successfully factorize tensors with noise and up to 99% missing data. A unique aspect of our approach is that it scales to sparse large-scale data, e.g., 1000 x 1000 x 1000 with five million known entries (0.5% dense). We further demonstrate the usefulness of CP-WOPT on two real-world applications: a novel EEG (electroencephalogram) application where missing data is frequently encountered due to disconnections of electrodes and the problem of modeling computer network traffic where data may be absent due to the expense of the data collection process

    Design of a health-economic Markov model to assess cost-effectiveness and budget impact of the prevention and treatment of depressive disorder

    Get PDF
    Contains fulltext : 225612.pdf (Publisher’s version ) (Open Access)Background/objective: To describe the design of 'DepMod', a health-economic Markov model for assessing cost-effectiveness and budget impact of user-defined preventive interventions and treatments in depressive disorders. Methods: DepMod has an epidemiological layer describing how a cohort of people can transition between health states (sub-threshold depression, first episode of mild, moderate or severe depression, (partial) remission, recurrence, death). Superimposed on the epidemiological layer, DepMod has an intervention layer consisting of a reference scenario and alternative scenario comparing the effectiveness and cost-effectiveness of a user-defined package of preventive interventions and psychological and pharmacological treatments of depression. Results are presented in terms of quality-adjusted life years (QALYs) gained and healthcare expenditure. Costs and effects can be modelled over five years and are subjected to probabilistic sensitivity analysis. Results: DepMod was used to assess the cost-effectiveness of scaling up preventive interventions for treating people with subclinical depression, which showed that there is an 82% probability that scaling up prevention is cost-effective given a willingness-to-pay threshold of €20,000 per QALY. Conclusion: DepMod is a Markov model that assesses the cost-utility and budget impact of different healthcare packages aimed at preventing and treating depression and is freely available for academic purposes upon request at the authors.12 p

    Search based software engineering: Trends, techniques and applications

    Get PDF
    © ACM, 2012. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version is available from the link below.In the past five years there has been a dramatic increase in work on Search-Based Software Engineering (SBSE), an approach to Software Engineering (SE) in which Search-Based Optimization (SBO) algorithms are used to address problems in SE. SBSE has been applied to problems throughout the SE lifecycle, from requirements and project planning to maintenance and reengineering. The approach is attractive because it offers a suite of adaptive automated and semiautomated solutions in situations typified by large complex problem spaces with multiple competing and conflicting objectives. This article provides a review and classification of literature on SBSE. The work identifies research trends and relationships between the techniques applied and the applications to which they have been applied and highlights gaps in the literature and avenues for further research.EPSRC and E

    Beyond data mining; towards "idea engineering"

    Full text link
    Abstract—SE data mining tools can be reconfigured to define and explore the space of decisions made by a community. Index Terms—Data mining, software engineering, artificial intelligenc
    corecore