9 resultados para Box-Cox

em Aston University Research Archive


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Automatically generating maps of a measured variable of interest can be problematic. In this work we focus on the monitoring network context where observations are collected and reported by a network of sensors, and are then transformed into interpolated maps for use in decision making. Using traditional geostatistical methods, estimating the covariance structure of data collected in an emergency situation can be difficult. Variogram determination, whether by method-of-moment estimators or by maximum likelihood, is very sensitive to extreme values. Even when a monitoring network is in a routine mode of operation, sensors can sporadically malfunction and report extreme values. If this extreme data destabilises the model, causing the covariance structure of the observed data to be incorrectly estimated, the generated maps will be of little value, and the uncertainty estimates in particular will be misleading. Marchant and Lark [2007] propose a REML estimator for the covariance, which is shown to work on small data sets with a manual selection of the damping parameter in the robust likelihood. We show how this can be extended to allow treatment of large data sets together with an automated approach to all parameter estimation. The projected process kriging framework of Ingram et al. [2007] is extended to allow the use of robust likelihood functions, including the two component Gaussian and the Huber function. We show how our algorithm is further refined to reduce the computational complexity while at the same time minimising any loss of information. To show the benefits of this method, we use data collected from radiation monitoring networks across Europe. We compare our results to those obtained from traditional kriging methodologies and include comparisons with Box-Cox transformations of the data. We discuss the issue of whether to treat or ignore extreme values, making the distinction between the robust methods which ignore outliers and transformation methods which treat them as part of the (transformed) process. Using a case study, based on an extreme radiological events over a large area, we show how radiation data collected from monitoring networks can be analysed automatically and then used to generate reliable maps to inform decision making. We show the limitations of the methods and discuss potential extensions to remedy these.

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Factors associated with duration of dementia in a consecutive series of 103 Alzheimer's disease (AD) cases were studied using the Kaplan-Meier estimator and Cox regression analysis (proportional hazard model). Mean disease duration was 7.1 years (range: 6 weeks-30 years, standard deviation = 5.18); 25% of cases died within four years, 50% within 6.9 years, and 75% within 10 years. Familial AD cases (FAD) had a longer duration than sporadic cases (SAD), especially cases linked to presenilin (PSEN) genes. No significant differences in duration were associated with age, sex, or apolipoprotein E (Apo E) genotype. Duration was reduced in cases with arterial hypertension. Cox regression analysis suggested longer duration was associated with an earlier disease onset and increased senile plaque (SP) and neurofibrillary tangle (NFT) pathology in the orbital gyrus (OrG), CA1 sector of the hippocampus, and nucleus basalis of Meynert (NBM). The data suggest shorter disease duration in SAD and in cases with hypertensive comorbidity. In addition, degree of neuropathology did not influence survival, but spread of SP/NFT pathology into the frontal lobe, hippocampus, and basal forebrain was associated with longer disease duration. © 2014 R. A. Armstrong.

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Background/Aim: Heparanase (HPA) contributes to breast cancer metastasis by facilitating the breakdown of the basement membrane and extracellular matrix. High expression of HPA is thought to be associated with increased nodal involvement and poor survival in patients with breast cancer. Overexpression of cyclooxygenase-2 (COX-2) in breast cancer is associated with indicators of poor prognosis such as lymph node metastasis, poor differentiation, and large tumor size. The underlying mechanism by which HPA and COX-2 overexpression increases the metastatic potential of breast cancer is not fully-understood. To enhance our understanding over these mechanisms, we aimed to investigate the relationship between the size of the tumor and HPA expression, tumor grade as well as lymph node status in patients with breast cancer. Materials and Methods: Immunohistochemical analysis of HPA and COX-2 expression was performed on 246 breast tumor samples. The expression of HPA was correlated with COX-2 expression, tumor grade, lymph node status, oestrogen receptor status. Results: The overexpression of HPA and COX-2 was associated with increased likelihood of lymph node positivity in large, high-grade tumors. High-grade tumors with size greater than 20 mm, that overexpressed HPA, were 4-times more likely to be associated with lymph node involvement (OR 4.71, CI 1.21-18.25). Whereas, tumors greater than 20 mm in size were 5-times more likely to metastasize to the regional lymph nodes, if associated with overexpression of COX-2 (OR 5.5, CI 1.2-24.8). Conclusion: Expression of HPA appears to be a key mechanism by which large, highgrade breast tumors metastasize to regional lymph nodes, while COX-2 overexpression may be an independent predictor of lymph node positivity.

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A simplified (without phase modulator) scheme of a black box optical regenerator is proposed, where an appropriate nonlinear propagation is used to enhance regeneration. Applying semi-theoretical models the authors optimise and demonstrate feasibility of error-free long distance transmission at 40 Gbit/s.

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Editorinal on the Special Issue: The JCMS Annual Review of the European Union in 2013