912 resultados para Ultrasonic non-destructive testing
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Structured Light Plethysmography (SLP) is a novel non-invasive method that uses structured light to perform pulmonary function testing that does not require physical contact with a patient. The technique produces an estimate of chest wall volume changes over time. A patient is observed continuously by two cameras and a known pattern of light (i.e. structured light) is projected onto the chest using an off-the-shelf projector. Corner features from the projected light pattern are extracted, tracked and brought into correspondence for both camera views over successive frames. A novel self calibration algorithm recovers the intrinsic and extrinsic camera parameters from these point correspondences. This information is used to reconstruct a surface approximation of the chest wall and several novel ideas for 'cleaning up' the reconstruction are used. The resulting volume and derived statistics (e.g. FVC, FEV) agree very well with data taken with a spirometer. © 2010. The copyright of this document resides with its authors.
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Objective: Genetic testing and colonoscopy is recommended for people with a strong history of colorectal cancer (CRC). However, families must communicate so that all members are aware of the risk. The study aimed to explore the factors influencing family communication about genetic risk and colonoscopy among people with a strong family history of CRC who attended a genetic clinic with a view to having a genetic test for hereditary non-polyposis colon cancer (HNPCC).
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BRCA1/2 test decliners/deferrers have received almost no attention in the literature and this is the first study of this population in the United Kingdom. The aim of this multicenter study is to examine the attributes of a group of individuals offered predictive genetic testing for breast/ovarian cancer predisposition who did not wish to proceed with testing at the time of entry into this study. This forms part of a larger study involving 9 U.K. centers investigating the psychosocial impact of predictive genetic testing for BRCA1/2. Cancer worry and reasons for declining or deferring BRCA1/2 predictive genetic testing were evaluated by questionnaire following genetic counseling. A total of 34 individuals declined the offer of predictive genetic testing. Compared to the national cohort of test acceptors, test decliners are significantly younger. Female test decliners have lower levels of cancer worry than female test acceptors. Barriers to testing include apprehension about the result, traveling to the genetics clinic, and taking time away from work/family. Women are more likely than men to worry about receiving less screening if found not to be a carrier. The findings do not indicate that healthy BRCA1/2 test decliners are a more vulnerable group in terms of cancer worry. However, barriers to testing need to be discussed in genetic counseling.
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To compare the rejection rates of non-small cell lung cancer (NSCLC) samples obtained by differing sampling methods for testing by Sanger sequencing for epidermal growth factor receptor (EGFR) mutations. To assess the association between unsatisfactory outcomes and the quantity of DNA extracted from cytological versus histological samples.
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Several randomized phase III studies in advanced stage non-small cell lung cancer (NSCLC) confirmed the superior response rate and progression-free survival of using epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor as first-line therapy compared with chemotherapy in patients with activating EGFR mutations. Despite the need for EGFR mutation tests to guide first-line therapy in East Asian NSCLC, there are no current standard clinical and testing protocols.
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In this paper we propose exact likelihood-based mean-variance efficiency tests of the market portfolio in the context of Capital Asset Pricing Model (CAPM), allowing for a wide class of error distributions which include normality as a special case. These tests are developed in the frame-work of multivariate linear regressions (MLR). It is well known however that despite their simple statistical structure, standard asymptotically justified MLR-based tests are unreliable. In financial econometrics, exact tests have been proposed for a few specific hypotheses [Jobson and Korkie (Journal of Financial Economics, 1982), MacKinlay (Journal of Financial Economics, 1987), Gib-bons, Ross and Shanken (Econometrica, 1989), Zhou (Journal of Finance 1993)], most of which depend on normality. For the gaussian model, our tests correspond to Gibbons, Ross and Shanken’s mean-variance efficiency tests. In non-gaussian contexts, we reconsider mean-variance efficiency tests allowing for multivariate Student-t and gaussian mixture errors. Our framework allows to cast more evidence on whether the normality assumption is too restrictive when testing the CAPM. We also propose exact multivariate diagnostic checks (including tests for multivariate GARCH and mul-tivariate generalization of the well known variance ratio tests) and goodness of fit tests as well as a set estimate for the intervening nuisance parameters. Our results [over five-year subperiods] show the following: (i) multivariate normality is rejected in most subperiods, (ii) residual checks reveal no significant departures from the multivariate i.i.d. assumption, and (iii) mean-variance efficiency tests of the market portfolio is not rejected as frequently once it is allowed for the possibility of non-normal errors.
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Most panel unit root tests are designed to test the joint null hypothesis of a unit root for each individual series in a panel. After a rejection, it will often be of interest to identify which series can be deemed to be stationary and which series can be deemed nonstationary. Researchers will sometimes carry out this classification on the basis of n individual (univariate) unit root tests based on some ad hoc significance level. In this paper, we demonstrate how to use the false discovery rate (FDR) in evaluating I(1)=I(0) classifications based on individual unit root tests when the size of the cross section (n) and time series (T) dimensions are large. We report results from a simulation experiment and illustrate the methods on two data sets.
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