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Nachman K.E.,Future Health
Journal of Water and Health | Year: 2010

Confined food-animal operations in the United States produce more than 40 times the amount of waste than human biosolids generated from US wastewater treatment plants. Unlike biosolids, which must meet regulatory standards for pathogen levels, vector attraction reduction and metal content, no treatment is required of waste from animal agriculture. This omission is of concern based on dramatic changes in livestock production over the past 50 years, which have resulted in large increases in animal waste and a high degree of geographic concentration of waste associated with the regional growth of industrial food-animal production. Regulatory measures have not kept pace with these changes. The purpose of this paper is to: 1) review trends that affect food-animal waste production in the United States, 2) assess risks associated with food-animal wastes, 3) contrast food-animal waste management practices to management practices for biosolids and 4) make recommendations based on existing and potential policy options to improve management of food-animal waste. © IWA Publishing 2010. Source


Kaijser J.,Catholic University of Leuven | Sayasneh A.,Imperial College London | Van hoorde K.,Future Health | Ghaem-maghami S.,Imperial College London | And 4 more authors.
Human Reproduction Update | Year: 2014

Background: Characterizing ovarian pathology is fundamental to optimizing management in both pre- and post-menopausal women. Inappropriate referral to oncology services can lead to unnecessary surgery or overly radical interventions compromising fertility in young women, whilst the consequences of failing to recognize cancer significantly impact on prognosis. By reflecting on recent developments of new diagnostic tests for preoperative identification of malignant disease in women with adnexal masses, we aimed to update a previous systematic review and meta-analysis. Methods: An extended search was performed in MEDLINE (PubMed) and EMBASE (OvidSp) from March 2008 to October 2013. Eligible studies provided information on diagnostic test performance of models, designed to predict ovarian cancer in a preoperative setting, that contained at least two variables. Study selection and extraction of study characteristics, types of bias, and test performance was performed independently by two reviewers. Quality was assessed using a modified version of the QUADAS assessment tool. A bivariate hierarchical random effects model was used to produce summary estimates of sensitivity and specificity with 95% confidence intervals or plot summary ROC curves for all models considered. Results: Our extended search identified a total of 1542 new primary articles. In total, 195 studies were eligible for qualitative data synthesis, and 96 validation studies reporting on 19 different prediction models met the predefined criteria for quantitative data synthesis. These models were tested on 26 438 adnexal masses, including 7199 (27%) malignant and 19 239 (73%) benign masses. The Risk of Malignancy Index (RMI) was the most frequently validated model. The logistic regression model LR2 with a risk cut-offof 10% and Simple Rules (SR), both developed by the International Ovarian Tumor Analysis (IOTA) study, performed better than all other included models with a pooled sensitivity and specificity, respectively, of 0.92 [95% CI 0.88-0.95] and 0.83 [95% CI 0.77-0.88] for LR2 and 0.93 [95% CI 0.89-0.95] and 0.81 [95% CI 0.76-0.85] for SR. A meta-analysis of centre-specific results stratified for menopausal status of two multicentre cohorts comparing LR2, SR and RMI-1 (using a cut-offof 200) showed a pooled sensitivity and specificity in premenopausal women for LR2 of 0.85 [95% CI 0.75-0.91] and 0.91 [95% CI 0.83-0.96] compared with 0.93 [95% CI 0.84-0.97] and 0.83 [95% CI 0.73-0.90] for SR and 0.44 [95% CI 0.28-0.62] and 0.95 [95% CI 0.90-0.97] for RMI-1. In post-menopausal women, sensitivity and specificity of LR2, SR and RMI-1 were 0.94 [95% CI 0.89-0.97] and 0.70 [95% CI 0.62-0.77], 0.93 [95% CI 0.88-0.96] and 0.76 [95% CI 0.69-0.82], and 0.79 [95% CI 0.72-0.85] and 0.90 [95% CI 0.84-0.94], respectively. Conclusions: An evidence-based approach to the preoperative characterization of any adnexal mass should incorporate the use of IOTA Simple Rules or the LR2 model, particularly for women of reproductive age. © The Author 2013. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. Source


De Brabanter K.,Iowa State University | Suykens J.A.K.,Catholic University of Leuven | De Moor B.,Future Health
Journal of Statistical Software | Year: 2013

We present a new MATLAB toolbox under Windows and Linux for nonparametric regression estimation based on the statistical library for least squares support vector machines (StatLSSVM). The StatLSSVM toolbox is written so that only a few lines of code are necessary in order to perform standard nonparametric regression, regression with correlated errors and robust regression. In addition, construction of additive models and pointwise or uniform confidence intervals are also supported. A number of tuning criteria such as classical cross-validation, robust cross-validation and cross-validation for correlated errors are available. Also, minimization of the previous criteria is available without any user interaction. Source


Varon C.,Future Health
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference | Year: 2012

Artefacts can pose a big problem in the analysis of electrocardiogram (ECG) signals. Even though methods exist to reduce the influence of these contaminants, they are not always robust. In this work a new algorithm based on easy-to-implement tools such as autocorrelation functions, graph theory and percentile analysis is proposed. This new methodology successfully detects corrupted segments in the signal, and it can be applied to real-life problems such as for example to sleep apnea classification. Source


Bertrand A.,Catholic University of Leuven | Bertrand A.,Future Health | Moonen M.,Catholic University of Leuven | Moonen M.,Future Health
IEEE Transactions on Signal Processing | Year: 2012

Total least squares (TLS) estimation is a popular solution technique for overdetermined systems of linear equations with a noisy data matrix. In this paper, we revisit the distributed total least squares (D-TLS) algorithm, which operates in an ad hoc network, where each node has access to a subset of the linear equations. The D-TLS algorithm computes the TLS solution of the full system of equations in a fully distributed fashion (without fusion center). To reduce the large computational complexity due to an eigenvalue decomposition (EVD) at every node and in each iteration, we modify the D-TLS algorithm based on inverse power iterations (IPIs). In each step of the modified algorithm, a single IPI is performed, which significantly reduces the computational complexity. We show that this IPI-based D-TLS algorithm still converges to the network-wide TLS solution under certain assumptions, which are often satisfied in practice. We provide simulation results to demonstrate the convergence of the algorithm, even when some of these assumptions are not satisfied. © 2012 IEEE. Source

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