The effects of properties, microstructure and phase transformation on the erosion of hard materials

BaBibliography: pages 88-92.A variety of ceramic and ultrahard materials have been subjected to both solid particle and cavitation erosion. The materials tested include three grain sizes of alumina, stabilised zirconias, sialon, cubic boron nitride and polycrystalline diamond, and these have a range of microstructural, physical and mechanical properties. The damage modes are described for the two types of erosion and the results are critically discussed. It has been shown that different properties and microstructural features control the respective types of erosion. Hardness is the critical property which controls material loss during solid particle erosion. Cavitation erosion in contrast is less sensitive to hardness, but is extremely defect sensitive and preferentially attacks weak or damaged regions on the target. Grain size and shape, and th.e properties of the grain boundary or intergranular phase exert a strong influence on both types of erosion. It has in addition been concluded, that a propensity for a stress induced phase transformation, such as that exhibited by stabilised zirconia, will benefit the resistance of a ceramic to erosion. Ultrahard materials generally outperform the structural ceramics that were tested. While it was not possible to ascertain the effects of grain size conclusively, a large extent of intergrowth between the crystallites during manufacture appears to be beneficial to erosion resistance

Developing the Quantitative Histopathology Image Ontology : A case study using the hot spot detection problem

Interoperability across data sets is a key challenge for quantitative histopathological imaging. There is a need for an ontology that can support effective merging of pathological image data with associated clinical and demographic data. To foster organized, cross-disciplinary, information-driven collaborations in the pathological imaging field, we propose to develop an ontology to represent imaging data and methods used in pathological imaging and analysis, and call it Quantitative Histopathological Imaging Ontology – QHIO. We apply QHIO to breast cancer hot-spot detection with the goal of enhancing reliability of detection by promoting the sharing of data between image analysts

A 4'-Phosphopantetheinyl Transferase Mediates Non-Ribosomal Peptide Synthetase Activation in Aspergillus fumigatus

Aspergillus fumigatus is a significant human pathogen. Non-ribosomal peptide (NRP) synthesis is thought to be responsible for a significant proportion of toxin and siderophore production in the organism. Furthermore, it has been shown that 4'-phosphopantetheinylation is required for the activation of key enzymes involved in non-ribosomal peptide synthesis in other species. Here we report the cloning, recombinant expression and functional characterisation of a 4'-phosphopantetheinyl transferase from A. fumigatus and the identification of an atypical NRP synthetase (Afpes1), spanning 14.3 kb. Phylogenetic analysis has shown that the NRP synthetase exhibits greatest identity to NRP synthetases from Metarhizium anisolpiae (PesA) and Alternaria brassicae (AbrePsy1). Northern hybridisation and RT-PCR analysis have confirmed that both genes are expressed in A. fumigatus. A 120 kDa fragment of the A. fumigatus NRP synthetase, containing a putative thiolation domain, was cloned and expressed in the baculovirus expression system. Detection of a 4'- phosphopantetheinylated peptide (SFSAMK) from this protein, by MALDI-TOF mass spectrometric analysis after coincubation of the 4'-phosphopantetheinyl transferase with the recombinant NRP synthetase fragment and acetyl CoA, confirms that it is competent to play a role in NRP synthetase activation in A. fumigatus. The 4'-phosphopantetheinyl transferase also activates, by 4'-phosphopantetheinylation, recombinant a-aminoadipate reductase (Lys2p) from Candida albicans, a key enzyme involved in lysine biosynthesis

Cross-sectional analysis of adverse outcomes in 1,029 pregnancies of Afro-Caribbean women in Trinidad with and without systemic lupus erythematosus

The objective of the study was to examine pregnancy outcomes in women with systemic lupus erythematosus (SLE) and population controls in Trinidad. We performed a cross-sectional analysis of adverse outcomes in pregnancies of Afro-Caribbean women with SLE and without SLE. One hundred and twenty-two female adult cases of SLE and 203 neighbourhood age-matched women without SLE were interviewed concerning details of their reproductive history, and the anticardiolipin antibody (ACL) status was established for women with SLE. A total of 1,029 pregnancies were reported (356 by women with SLE, 673 by women without SLE). In women with ≥ 1 pregnancy the total number of pregnancies was similar in women with a diagnosis of SLE and women without; however, a lower proportion of women with SLE had ever been pregnant compared with women without SLE (80% versus 91%, P = 0.002). In multivariate logistic regression analyses adjusted for maternal age, district of residence, pregnancy order and smoking, SLE pregnancies were more than twice as likely to end in foetal death than non-SLE pregnancies (odds ratio (OR), 2.4; 95% confidence interval (CI), 1.2–4.7). This effect was driven by a large increase in the odds of stillbirth (OR, 8.5; 95% CI, 2.5–28.8). The odds of early miscarriage (OR, 1.4; 95% CI, 0.6–3.1) and of mid-trimester miscarriage (OR, 1.9; 95% CI, 0.4–9.5) were higher, but were not statistically significantly different, in SLE pregnancies than in non-SLE pregnancies. The odds of ectopic pregnancy (OR, 7.5; 95% CI, 0.9–62.5) and of preterm birth (OR, 3.4; 95% CI, 1.2–10.0) were higher in SLE pregnancies conceived after diagnosis than in non-SLE pregnancies. There was no evidence of raised levels of IgG or IgM ACL among the majority (93/97 women, 96%) of SLE cases who reported sporadic mid-trimester miscarriage or stillbirth, although there was evidence of high levels of IgM and IgG ACL among women reporting three or more miscarriages and three consecutive miscarriages, and of raised IgG ACL among those experiencing ectopic pregnancy. In conclusion, we found evidence for a large increase in risk of stillbirth in the pregnancies of Afro-Caribbean Trinidadian women with SLE (not accounted for by high ACL status). There was some evidence of an increased risk of preterm delivery and ectopic pregnancy in pregnancies conceived after a diagnosis of maternal SLE

Optical Flow Background Estimation for Real-time Pan/tilt Camera Object Tracking

As Computer Vision (CV) techniques develop, pan/tilt camera systems are able to enhance data capture capabilities over static camera systems. In order for these systems to be effective for metrology purposes, they will need to respond to the test article in real-time with a minimum of additional uncertainty. A methodology is presented here for obtaining high-resolution, high frame-rate images, of objects traveling at speeds ⩾1.2 m/s at 1 m from the camera by tracking the moving texture of an object. Strong corners are determined and used as flow points using implementations on a graphic processing unit (GPU), resulting in significant speed-up over central processing units (CPU). Based on directed pan/tilt motion, a pixel-to-pixel relationship is used to estimate whether optical flow points fit background motion, dynamic motion or noise. To smooth variation, a two-dimensional position and velocity vector is used with a Kalman filter to predict the next required position of the camera so the object stays centered in the image. High resolution images can be stored by a parallel process resulting in a high frame rate procession of images for post-processing. The results provide real-time tracking on a portable system using a pan/tilt unit for generic moving targets where no training is required and camera motion is observed from high accuracy encoders opposed to image correlation

Creating Isolated Liquid Compartments Using Photopatterned Obstacles in Microfluidics

We propose a method to trap liquid (both oil and water) in a microchannel by sequentially injecting oil and water (or vice versa) over photopatterned obstacles with controlled wetting properties. We present a simple geometrical model to understand the liquid-entrapment process and predict the evolution of the water/oil interface over an obstacle. Our analysis provides an analytic solution that can successfully predict useful properties such as angular position of pinch-off and the amount of captured liquid. We show that we are able to obtain a liquid bridge over two circular obstacles, and we are also able to predict the condition for the formation of a bridge. We further demonstrate the effect of the obstacle shape and how a sudden change in gradient results in larger liquid entrapment. We also demonstrate the ability to entrap isolated liquid chambers for parallel experimentation

Beyond Voxel Prediction Uncertainty: Identifying brain lesions you can trust

Deep neural networks have become the gold-standard approach for the automated segmentation of 3D medical images. Their full acceptance by clinicians remains however hampered by the lack of intelligible uncertainty assessment of the provided results. Most approaches to quantify their uncertainty, such as the popular Monte Carlo dropout, restrict to some measure of uncertainty in prediction at the voxel level. In addition not to be clearly related to genuine medical uncertainty, this is not clinically satisfying as most objects of interest (e.g. brain lesions) are made of groups of voxels whose overall relevance may not simply reduce to the sum or mean of their individual uncertainties. In this work, we propose to go beyond voxel-wise assessment using an innovative Graph Neural Network approach, trained from the outputs of a Monte Carlo dropout model. This network allows the fusion of three estimators of voxel uncertainty: entropy, variance, and model's confidence; and can be applied to any lesion, regardless of its shape or size. We demonstrate the superiority of our approach for uncertainty estimate on a task of Multiple Sclerosis lesions segmentation.Comment: Accepted for presentation at the Workshop on Interpretability of Machine Intelligence in Medical Image Computing (iMIMIC) at MICCAI 202