Application of steady state finite element and transient finite difference theory to sound propagation in a variable area duct: A comparison with experiment

Sound propagation without flow in a rectangular duct with a converging-diverging area variation was studied experimentally and theoretically. The area variation was of sufficient magnitude to produce large reflections and induce modal scattering. The rms (root-mean-squared) pressure and phase angle on both the flat and curved surface were measured and tabulated. The steady state finite element theory and the transient finite difference theory are in good agreement with the data. It is concluded that numerical finite difference and finite element theories appear ideally suited for handling duct propagation problems which encounter large area variations

The Presence of the Diphtheria Bacillus on Healthy Surfaces.

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On Resilient Behaviors in Computational Systems and Environments

The present article introduces a reference framework for discussing resilience of computational systems. Rather than a property that may or may not be exhibited by a system, resilience is interpreted here as the emerging result of a dynamic process. Said process represents the dynamic interplay between the behaviors exercised by a system and those of the environment it is set to operate in. As a result of this interpretation, coherent definitions of several aspects of resilience can be derived and proposed, including elasticity, change tolerance, and antifragility. Definitions are also provided for measures of the risk of unresilience as well as for the optimal match of a given resilient design with respect to the current environmental conditions. Finally, a resilience strategy based on our model is exemplified through a simple scenario.Comment: The final publication is available at Springer via http://dx.doi.org/10.1007/s40860-015-0002-6 The paper considerably extends the results of two conference papers that are available at http://ow.ly/KWfkj and http://ow.ly/KWfgO. Text and formalism in those papers has been used or adapted in the herewith submitted pape

A method for exploratory repeated-measures analysis applied to a breast-cancer screening study

When a model may be fitted separately to each individual statistical unit, inspection of the point estimates may help the statistician to understand between-individual variability and to identify possible relationships. However, some information will be lost in such an approach because estimation uncertainty is disregarded. We present a comparative method for exploratory repeated-measures analysis to complement the point estimates that was motivated by and is demonstrated by analysis of data from the CADET II breast-cancer screening study. The approach helped to flag up some unusual reader behavior, to assess differences in performance, and to identify potential random-effects models for further analysis.Comment: Published in at http://dx.doi.org/10.1214/11-AOAS481 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Accuracy of Digital Breast Tomosynthesis for Depicting Breast Cancer Subgroups in a UK Retrospective Reading Study (TOMMY Trial)

Purpose To compare the diagnostic performance of two-dimensional (2D) mammography, 2D mammography plus digital breast tomosynthesis (DBT), and synthetic 2D mammography plus DBT in depicting malignant radiographic features. Materials and Methods In this multicenter, multireader, retrospective reading study (the TOMMY trial), after written informed consent was obtained, 8869 women (age range, 29–85 years; mean, 56 years) were recruited from July 2011 to March 2013 in an ethically approved study. From these women, a reading dataset of 7060 cases was randomly allocated for independent blinded review of (a) 2D mammography images, (b) 2D mammography plus DBT images, and (c) synthetic 2D mammography plus DBT images. Reviewers had no access to results of previous examinations. Overall sensitivities and specificities were calculated for younger women and those with dense breasts. Results Overall sensitivity was 87% for 2D mammography, 89% for 2D mammography plus DBT, and 88% for synthetic 2D mammography plus DBT. The addition of DBT was associated with a 34% increase in the odds of depicting cancer (odds ratio [OR] = 1.34, P = .06); however, this level did not achieve significance. For patients aged 50–59 years old, sensitivity was significantly higher (P = .01) for 2D mammography plus DBT than it was for 2D mammography. For those with breast density of 50% or more, sensitivity was 86% for 2D mammography compared with 93% for 2D mammography plus DBT (P = .03). Specificity was 57% for 2D mammography, 70% for 2D mammography plus DBT, and 72% for synthetic 2D mammography plusmDBT. Specificity was significantly higher than 2D mammography (P < .001in both cases) and was observed for all subgroups (P < .001 for all cases). Conclusion The addition of DBT increased the sensitivity of 2D mammography in patients with dense breasts and the specificity of 2D mammography for all subgroups. The use of synthetic 2D DBT demonstrated performance similar to that of standard 2D mammography with DBT. DBT is of potential benefit to screening programs, particularly in younger women with dense breasts. © RSNA, 2015The TOMMY Trial (a comparison of digital breast tomosynthesis with mammography in the UK Breast Screening Programme) was supported by the NIHR Health Technology Assessment Programme.This is the final published version of the article. It was originally published in Radiology (Gilbert et al., Radiology, 2015, doi:10.1148/radiol.2015142566). The final version is available at http://dx.doi.org/10.1148/radiol.201514256

Accuracy of Digital Breast Tomosynthesis for Depicting Breast Cancer Subgroups in a UK Retrospective Reading Study (TOMMY Trial).

PURPOSE: To compare the diagnostic performance of two-dimensional (2D) mammography, 2D mammography plus digital breast tomosynthesis (DBT), and synthetic 2D mammography plus DBT in depicting malignant radiographic features. MATERIALS AND METHODS: In this multicenter, multireader, retrospective reading study (the TOMMY trial), after written informed consent was obtained, 8869 women (age range, 29-85 years; mean, 56 years) were recruited from July 2011 to March 2013 in an ethically approved study. From these women, a reading dataset of 7060 cases was randomly allocated for independent blinded review of (a) 2D mammography images, (b) 2D mammography plus DBT images, and (c) synthetic 2D mammography plus DBT images. Reviewers had no access to results of previous examinations. Overall sensitivities and specificities were calculated for younger women and those with dense breasts. RESULTS: Overall sensitivity was 87% for 2D mammography, 89% for 2D mammography plus DBT, and 88% for synthetic 2D mammography plus DBT. The addition of DBT was associated with a 34% increase in the odds of depicting cancer (odds ratio [OR] = 1.34, P = .06); however, this level did not achieve significance. For patients aged 50-59 years old, sensitivity was significantly higher (P = .01) for 2D mammography plus DBT than it was for 2D mammography. For those with breast density of 50% or more, sensitivity was 86% for 2D mammography compared with 93% for 2D mammography plus DBT (P = .03). Specificity was 57% for 2D mammography, 70% for 2D mammography plus DBT, and 72% for synthetic 2D mammography plusmDBT. Specificity was significantly higher than 2D mammography (P < .001in both cases) and was observed for all subgroups (P < .001 for all cases). CONCLUSION: The addition of DBT increased the sensitivity of 2D mammography in patients with dense breasts and the specificity of 2D mammography for all subgroups. The use of synthetic 2D DBT demonstrated performance similar to that of standard 2D mammography with DBT. DBT is of potential benefit to screening programs, particularly in younger women with dense breasts. (©) RSNA, 2015.The TOMMY Trial (a comparison of digital breast tomosynthesis with mammography in the UK Breast Screening Programme) was supported by the NIHR Health Technology Assessment Programme.This is the final published version of the article. It was originally published in Radiology (Gilbert et al., Radiology, 2015, doi:10.1148/radiol.2015142566). The final version is available at http://dx.doi.org/10.1148/radiol.201514256

Symptoms and syndromes associated with SARS-CoV-2 infection and severity in pregnant women from two community cohorts

We tested whether pregnant and non-pregnant women differ in COVID-19 symptom profile and severity, and we extended previous investigations on hospitalized pregnant women to those who did not require hospitalization. Two female community-based cohorts (18-44 years) provided longitudinal (smartphone application, N = 1,170,315, n = 79 pregnant tested positive) and cross-sectional (web-based survey, N = 1,344,966, n = 134 pregnant tested positive) data, prospectively collected through self-participatory citizen surveillance in UK, Sweden and USA. Pregnant and non-pregnant were compared for frequencies of events, including SARS-CoV-2 testing, symptoms and hospitalization rates. Multivariable regression was used to investigate symptoms severity and comorbidity effects. Pregnant and non-pregnant women positive for SARS-CoV-2 infection were not different in syndromic severity, except for gastrointestinal symptoms. Pregnant were more likely to have received testing, despite reporting fewer symptoms. Pre-existing lung disease was most closely associated with syndromic severity in pregnant hospitalized. Heart and kidney diseases and diabetes increased risk. The most frequent symptoms among non-hospitalized women were anosmia [63% pregnant, 92% non-pregnant] and headache [72%, 62%]. Cardiopulmonary symptoms, including persistent cough [80%] and chest pain [73%], were more frequent among pregnant who were hospitalized. Consistent with observations in non-pregnant populations, lung disease and diabetes were associated with increased risk of more severe SARS-CoV-2 infection during pregnancy

SARS-CoV-2 (COVID-19) infection in pregnant women: characterization of symptoms and syndromes predictive of disease and severity through real-time, remote participatory epidemiology

Objective: To test whether pregnant and non-pregnant women differ in COVID-19 symptom profile and severity. To extend previous investigations on hospitalized pregnant women to those who did not require hospitalization. Design: Observational study prospectively collecting longitudinal (smartphone application interface) and cross-sectional (web-based survey) data. Setting:Community-based self-participatory citizen surveillance in the United Kingdom, Sweden and the United States of America. Population: Two female community-based cohorts aged 18-44 years. The discovery cohort was drawn from 1,170,315 UK, Sweden and USA women (79 pregnant tested positive) who self-reported status and symptoms longitudinally via smartphone. The replication cohort included 1,344,966 USA women (134 pregnant tested positive) who provided cross-sectional self-reports. Methods: Pregnant and non-pregnant were compared for frequencies of symptoms and events, including SARS-CoV-2 testing and hospitalization rates. Multivariable regression was used to investigate symptoms severity and comorbidity effects. Results: Pregnant and non-pregnant women positive for SARS-CoV-2 infection were not different in syndromic severity. Pregnant were more likely to have received testing than non-pregnant, despite reporting fewer symptoms. Pre-existing lung disease was most closely associated with the syndromic severity in pregnant hospitalized women. Heart and kidney diseases and diabetes increased risk. The most frequent symptoms among all non-hospitalized women were anosmia [63% pregnant, 92% non-pregnant] and headache [72%, 62%]. Cardiopulmonary symptoms, including persistent cough [80%] and chest pain [73%], were more frequent among pregnant women who were hospitalized. Conclusions: Symptom characteristics and severity were comparable among pregnant and non-pregnant women, except for gastrointestinal symptoms. Consistent with observations in non-pregnant populations, lung disease and diabetes were associated with increased risk of more severe SARS-CoV-2 infection during pregnancy. Tweetable abstract: Pregnancy with SARS-CoV-2 has no higher risk of severe symptoms. Underlying lung disease or cardiac condition can increase risk. Competing Interest Statement: ATC previously served as an investigator on a clinical trial of diet and lifestyle using a separate mobile application that was supported by Zoe Global Ltd. Clinical Trial -- Funding Statement: This work was supported by Zoe Global. The Department of Twin Research receives grants from the Wellcome Trust (212904/Z/18/Z) and Medical Research Council/British Heart Foundation Ancestry and Biological Informative Markers for Stratification of Hypertension (AIMHY; MR/M016560/1), and support from the European Union, the Chronic Disease Research Foundation, Zoe Global, the NIHR Clinical Research Facility and the Biomedical Research Centre (based at Guys and St Thomas NHS Foundation Trust in partnership with Kings College London). The School of Biomedical Engineering & Imaging Science and Center for Medical Engineering at Kings College London receive grants from the Wellcome/EPSRC Centre for Medical Engineering [WT 203148/Z/16/Z]. E.M. is funded by the Skills Development Scheme of the Medical Research Council UK. C.M.A. is funded by NIDDK K23 DK120899 and the Boston Childrens Hospital Office of Faculty Development Career Development Award. CHS is supported by an Alzheimers Society Junior fellowship (AS-JF-17-011). W.M., J.S.B. and A.T.C. are supported by the Massachusetts Consortium on Pathogen Readiness (MassCPR) and Mark and Lisa Schwartz