A quantitative mesoscale characterization of the mechanical behaviour of Ceramic Matrix Composites

An experimental micro-macro kinematic description of matrix cracking in unidirectionnal ceramic matrix composites is proposed. It has been enlighten by observations performed during an in situ tensile test in a Scanning Electron Microscope. The characterization of matrix crack nucleation, propagation and coalescence has been done with new parameters and related to the macroscopic behaviour

First Results of the Phase II SIMPLE Dark Matter Search

We report results of a 14.1 kgd measurement with 15 superheated droplet detectors of total active mass 0.208 kg, comprising the first stage of a 30 kgd Phase II experiment. In combination with the results of the neutron-spin sensitive XENON10 experiment, these results yield a limit of |a_p| < 0.32 for M_W = 50 GeV/c2 on the spin-dependent sector of weakly interacting massive particle-nucleus interactions with a 50% reduction in the previously allowed region of the phase space formerly defined by XENON, KIMS and PICASSO. In the spin-independent sector, a limit of 2.3x10-5 pb at M_W = 45 GeV/c2 is obtained.Comment: 4 pages, 4 figures; PRL-accepted version with corrected SI contour (Fig. 4

Automatic Extraction of Hiatal Dimensions in 3-D Transperineal Pelvic Ultrasound Recordings

The aims of this work were to create a robust automatic software tool for measurement of the levator hiatal area on transperineal ultrasound (TPUS) volumes and to measure the potential reduction in variability and time taken for analysis in a clinical setting. The proposed tool automatically detects the C-plane (i.e., the plane of minimal hiatal dimensions) from a 3-D TPUS volume and subsequently uses the extracted plane to automatically segment the levator hiatus, using a convolutional neural network. The automatic pipeline was tested using 73 representative TPUS volumes. Reference hiatal outlines were obtained manually by two experts and compared with the pipeline's automated outlines. The Hausdorff distance, area, a clinical quality score, C-plane angle and C-plane Euclidean distance were used to evaluate C-plane detection and quantify levator hiatus segmentation accuracy. A visual Turing test was created to compare the performance of the software with that of the expert, based on the visual assessment of C-plane and hiatal segmentation quality. The overall time taken to extract the hiatal area with both measurement methods (i.e., manual and automatic) was measured. Each metric was calculated both for computer–observer differences and for inter-and intra-observer differences. The automatic method gave results similar to those of the expert when determining the hiatal outline from a TPUS volume. Indeed, the hiatal area measured by the algorithm and by an expert were within the intra-observer variability. Similarly, the method identified the C-plane with an accuracy of 5.76 ± 5.06° and 6.46 ± 5.18 mm in comparison to the inter-observer variability of 9.39 ± 6.21° and 8.48 ± 6.62 mm. The visual Turing test suggested that the automatic method identified the C-plane position within the TPUS volume visually as well as the expert. The average time taken to identify the C-plane and segment the hiatal area manually was 2 min and 35 ± 17 s, compared with 35 ± 4 s for the automatic result. This study presents a method for automatically measuring the levator hiatal area using artificial intelligence-based methodologies whereby the C-plane within a TPUS volume is detected and subsequently traced for the levator hiatal outline. The proposed solution was determined to be accurate, relatively quick, robust and reliable and, importantly, to reduce time and expertise required for pelvic floor disorder assessment

The SIMPLE Phase II Dark Matter Search

Phase II of SIMPLE (Superheated Instrument for Massive ParticLe Experiments) searched for astroparticle dark matter using superheated liquid C$_{2}$ClF$_{5}$ droplet detectors. Each droplet generally requires an energy deposition with linear energy transfer (LET) $\gtrsim$ 150 keV/$\mu$m for a liquid-to-gas phase transition, providing an intrinsic rejection against minimum ionizing particles of order 10$^{-10}$, and reducing the backgrounds to primarily $\alpha$ and neutron-induced recoil events. The droplet phase transition generates a millimetric-sized gas bubble which is recorded by acoustic means. We describe the SIMPLE detectors, their acoustic instrumentation, and the characterizations, signal analysis and data selection which yield a particle-induced, "true nucleation" event detection efficiency of better than 97% at a 95% C.L. The recoil-$\alpha$ event discrimination, determined using detectors first irradiated with neutrons and then doped with alpha emitters, provides a recoil identification of better than 99%; it differs from those of COUPP and PICASSO primarily as a result of their different liquids with lower critical LETs. The science measurements, comprising two shielded arrays of fifteen detectors each and a total exposure of 27.77 kgd, are detailed. Removal of the 1.94 kgd Stage 1 installation period data, which had previously been mistakenly included in the data, reduces the science exposure from 20.18 to 18.24 kgd and provides new contour minima of $\sigma_{p}$ = 4.3 $\times$ 10$^{-3}$ pb at 35 GeV/c$^{2}$ in the spin-dependent sector of WIMP-proton interactions and $\sigma_{N}$ = 3.6 $\times$ 10$^{-6}$ pb at 35 GeV/c$^{2}$ in the spin-independent sector. These results are examined with respect to the fluorine spin and halo parameters used in the previous data analysis.Comment: 20 pages, 19 figures; accepted Physical Review

Final Analysis and Results of the Phase II SIMPLE Dark Matter Search

We report the final results of the Phase II SIMPLE measurements, comprising two run stages of 15 superheated droplet detectors each, the second stage including an improved neutron shielding. The analyses includes a refined signal analysis, and revised nucleation efficiency based on reanalysis of previously-reported monochromatic neutron irradiations. The combined results yield a contour minimum of \sigma_{p} = 4.2 x 10^-3 pb at 35 GeV/c^2 on the spin-dependent sector of WIMP-proton interactions, the most restrictive to date from a direct search experiment and overlapping for the first time results previously obtained only indirectly. In the spin-independent sector, a minimum of 3.6 x 10^-6 pb at 35 GeV/c^2 is achieved, with the exclusion contour challenging the recent CoGeNT region of current interest.Comment: revised, PRL-accepted version with slightly weakened limit contour

Reducing tuberculosis incidence by tuberculin skin testing, preventive treatment, and antiretroviral therapy in an area of low tuberculosis transmission

BACKGROUND: Tuberculin skin testing (TST) and preventive treatment of tuberculosis (TB) are recommended for all persons with human immunodeficiency virus (HIV) infection. We aimed to assess the effect of TST and preventive treatment of TB on the incidence of TB in the era of combination antiretroviral therapy in an area with low rates of TB transmission. METHODS: We calculated the incidence of TB among participants who entered the Swiss HIV Cohort Study after 1995, and we studied the associations of TST results, epidemiological and laboratory markers, preventive TB treatment, and combination antiretroviral therapy with TB incidence. RESULTS: Of 6160 participants, 142 (2.3%) had a history of TB at study entry, and 56 (0.91%) developed TB during a total follow-up period of 25,462 person-years, corresponding to an incidence of 0.22 cases per 100 person-years. TST was performed for 69% of patients; 9.4% of patients tested had positive results (induration &gt; or = 5 mm in diameter). Among patients with positive TST results, TB incidence was 1.6 cases per 100 person-years if preventive treatment was withheld, but none of the 193 patients who received preventive treatment developed TB. Positive TST results (adjusted hazard ratio [HR], 25; 95% confidence interval [CI], 11-57), missing TST results (HR, 12; 95% CI, 4.8-20), origin from sub-Saharan Africa (HR, 5.8; 95% CI, 2.7-12.5), low CD4+ cell counts, and high plasma HIV RNA levels were associated with an increased risk of TB, whereas the risk was reduced among persons receiving combination antiretroviral therapy (HR, 0.44; 95% CI, 0.2-0.8). CONCLUSION: Screening for latent TB using TST and administering preventive treatment for patients with positive TST results is an efficacious strategy to reduce TB incidence in areas with low rates of TB transmission. Combination antiretroviral therapy reduces the incidence of TB

Assessment of Microvascular Disease in Heart and Brain by MRI: Application in Heart Failure with Preserved Ejection Fraction and Cerebral Small Vessel Disease

The objective of this review is to investigate the commonalities of microvascular (small vessel) disease in heart failure with preserved ejection fraction (HFpEF) and cerebral small vessel disease (CSVD). Furthermore, the review aims to evaluate the current magnetic resonance imaging (MRI) diagnostic techniques for both conditions. By comparing the two conditions, this review seeks to identify potential opportunities to improve the understanding of both HFpEF and CSVD

Let's Agree to Disagree: Learning Highly Debatable Multirater Labelling

Classification and differentiation of small pathological objects may greatly vary among human raters due to differences in training, expertise and their consistency over time. In a radiological setting, objects commonly have high within-class appearance variability whilst sharing certain characteristics across different classes, making their distinction even more difficult. As an example, markers of cerebral small vessel disease, such as enlarged perivascular spaces (EPVS) and lacunes, can be very varied in their appearance while exhibiting high inter-class similarity, making this task highly challenging for human raters. In this work, we investigate joint models of individual rater behaviour and multi-rater consensus in a deep learning setting, and apply it to a brain lesion object-detection task. Results show that jointly modelling both individual and consensus estimates leads to significant improvements in performance when compared to directly predicting consensus labels, while also allowing the characterization of human-rater consistency