On the shape of the mass-function of dense clumps in the Hi-GAL fields. II. Using Bayesian inference to study the clump mass function

Context. Stars form in dense, dusty clumps of molecular clouds, but little is known about their origin, their evolution and their detailed physical properties. In particular, the relationship between the mass distribution of these clumps (also known as the "clump mass function", or CMF) and the stellar initial mass function (IMF), is still poorly understood. Aims. In order to better understand how the CMF evolve toward the IMF, and to discern the "true" shape of the CMF, large samples of bona-fide pre- and proto-stellar clumps are required. Two such datasets obtained from the Herschel infrared GALactic Plane Survey (Hi-GAL) have been described in paper I. Robust statistical methods are needed in order to infer the parameters describing the models used to fit the CMF, and to compare the competing models themselves. Methods. In this paper we apply Bayesian inference to the analysis of the CMF of the two regions discussed in Paper I. First, we determine the Bayesian posterior probability distribution for each of the fitted parameters. Then, we carry out a quantitative comparison of the models used to fit the CMF. Results. We have compared the results from several methods implementing Bayesian inference, and we have also analyzed the impact of the choice of priors and the influence of various constraints on the statistical conclusions for the preferred values of the parameters. We find that both parameter estimation and model comparison depend on the choice of parameter priors. Conclusions. Our results confirm our earlier conclusion that the CMFs of the two Hi-GAL regions studied here have very similar shapes but different mass scales. Furthermore, the lognormal model appears to better describe the CMF measured in the two Hi-GAL regions studied here. However, this preliminary conclusion is dependent on the choice of parameters priors.Comment: Submitted for publication to A&A on November 12, 2013. This paper contains 11 pages and 7 figure

Assessment of cyst content using mean gray value for discriminating endometrioma from other unilocular cysts in premenopausal women

Objective To assess whether the analysis of cyst content using mean gray value (MGV) can discriminate ovarian endometriomas from other unilocular ovarian cysts in premenopausal women. Methods Stored three-dimensional (3D) volumes from 54 unilocular ovarian cysts diagnosed in 50 premenopausal women (mean age, 37 (range, 22–50) years) were analyzed to calculate the MGV from cyst content. Cysts with solid components or septations were excluded. MGV was calculated in all cases with the Virtual Organ Computer-aided AnaLysisTM technique. The Bmode presumptive diagnosis based on the examiner’s subjective impression was also recorded. Results Sixteen of the cysts resolved spontaneously and were given a final clinical diagnosis of hemorrhagic functional cyst, while 38 cysts were removed surgically (diagnosed histologically as seven simple cysts, three hemorrhagic cysts, 20 endometriomas, five mucinous cysts and three paraovarian cysts). B-mode diagnoses were as follows: seven simple cysts, 18 hemorrhagic cysts, 24 endometriomas, three mucinous cysts and two paraovarian cysts. MGV was significantly higher in ovarian endometrioma when compared with all other kinds of cyst. The receiver–operating characteristics curve showed that using an MGV cut-off ≥15.560 had a sensitivity of 85% and a specificity of 76.5% for diagnosing ovarian endometrioma (area under the curve, 0.831; 95% CI, 0.718–0.944). These figures were similar to those for B-mode diagnosis (sensitivity, 90%; specificity, 82%) (McNemar test, P = 1.000). Combining B-mode and MGV gave a sensitivity of 80% and a specificity of 91%. Conclusion Cyst content MGV is higher in ovarian endometrioma than it is in other unilocular ovarian cysts. The diagnostic performance of MGV is similar to that of the examiner’s subjective impression. The combination of both criteria achieves the highest specificit

Equivalent layered models for functionally graded plates

Functionally graded plates whose material properties vary continuously through the thickness are modelled as exactly equivalent plates composed of up to four isotropic layers. Separate models are derived for analysis using classical plate theory, first-order and higher-order shear deformation theory. For cases where Poisson’s ratio varies through the thickness, the integrations required to obtain the membrane, coupling and out-of-plane stiffness matrices are performed accurately using a series solution. The model is verified by comparison with well converged solutions from approximate models in which the plate is divided into many isotropic layers. Critical buckling loads and undamped natural frequencies are found for a range of illustrative examples

Diagnostic accuracy of transvaginal sonography for detecting parametrial involvement in women with deep endometriosis: systematic review and meta-analysis

Objective: To evaluate the accuracy of transvaginal sonography (TVS) for detecting parametrial deep endometriosis, using laparoscopy as the reference standard. Methods: A search was performed in PubMed/MEDLINE and Web of Science for studies evaluating TVS for detecting parametrial involvement in women with suspected deep endometriosis, as compared with laparoscopy, from January 2000 to December 2020. The Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool was used to evaluate the quality of the studies. Pooled sensitivity, specificity and positive and negative likelihood ratios for TVS in the detection of parametrial deep endometriosis were calculated, and the post-test probability of parametrial deep endometriosis following a positive or negative test was determined. Results: The search identified 134 citations. Four studies, comprising 560 patients, were included in the analysis. The mean prevalence of parametrial deep endometriosis at surgery was 18%. Overall, the pooled estimated sensitivity, specificity and positive and negative likelihood ratios of TVS in the detection of parametrial deep endometriosis were 31% (95% CI, 10–64%), 98% (95% CI, 95–99%), 18.5 (95% CI, 8.8–38.9) and 0.70 (95% CI, 0.46–1.06), respectively. The diagnostic odds ratio was 26 (95% CI, 10–68). Heterogeneity was high. Visualization of a lesion suspected to be parametrial deep endometriosis on TVS increased significantly the post-test probability of parametrial deep endometriosis. Conclusion: TVS has high specificity but low sensitivity for the detection of parametrial deep endometriosis. © 2021 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology