On the segmentation and classification of hand radiographs

This research is part of a wider project to build predictive models of bone age using hand radiograph images. We examine ways of finding the outline of a hand from an X-ray as the first stage in segmenting the image into constituent bones. We assess a variety of algorithms including contouring, which has not previously been used in this context. We introduce a novel ensemble algorithm for combining outlines using two voting schemes, a likelihood ratio test and dynamic time warping (DTW). Our goal is to minimize the human intervention required, hence we investigate alternative ways of training a classifier to determine whether an outline is in fact correct or not. We evaluate outlining and classification on a set of 1370 images. We conclude that ensembling with DTW improves performance of all outlining algorithms, that the contouring algorithm used with the DTW ensemble performs the best of those assessed, and that the most effective classifier of hand outlines assessed is a random forest applied to outlines transformed into principal components

Microdissection of human chromosomes by a laser microbeam

A laser microbeam apparatus, based on an excimer laser pumped dye laser is used to microdissect human chromosomes and to isolate a single chromosome slice

Domain-invariant icing detection on wind turbine rotor blades with generative artificial intelligence for deep transfer learning

Wind energy’s ability to liberate the world from conventional sources of energy relies on lowering the significant costs associated with the maintenance of wind turbines. Since icing events on turbine rotor blades are a leading cause of operational failures, identifying icing in advance is critical. Some recent studies have utilized deep learning (DL) techniques to predict icing events with high accuracy by leveraging rotor blade images, but these studies only focus on specific wind parks and fail to generalize to unseen scenarios (e.g., new rotor blade designs). In this paper, we aim to facilitate ice prediction on the face of lack of ice images in new wind parks. We propose the utilization of synthetic data augmentation via a generative artificial intelligence technique—the neural style transfer algorithm to improve the generalization of existing ice prediction models. We also compare the proposed technique with the CycleGAN as a baseline. We show that training standalone DL models with augmented data that captures domain-invariant icing characteristics can help improve predictive performance across multiple wind parks. Through efficient identification of icing, this study can support preventive maintenance of wind energy sources by making them more reliable toward tackling climate change

Structure of the silicon vacancy in 6H-SiC after annealing identified as the carbon vacancy–carbon antisite pair

We investigated radiation-induced defects in neutron-irradiated and subsequently annealed 6H-silicon carbide (SiC) with electron paramagnetic resonance (EPR), the magnetic circular dichroism of the absorption (MCDA), and MCDA-detected EPR (MCDA-EPR). In samples annealed beyond the annealing temperature of the isolated silicon vacancy we observed photoinduced EPR spectra of spin S=1 centers that occur in orientations expected for nearest neighbor pair defects. EPR spectra of the defect on the three inequivalent lattice sites were resolved and attributed to optical transitions between photon energies of 999 and 1075 meV by MCDA-EPR. The resolved hyperfine structure indicates the presence of one single carbon nucleus and several silicon ligand nuclei. These experimental findings are interpreted with help of total energy and spin density data obtained from the standard local-spin density approximation of the density-functional theory, using relaxed defect geometries obtained from the self-consistent charge density-functional theory based tight binding scheme. We have checked several defect models of which only the photoexcited spin triplet state of the carbon antisite–carbon vacancy pair (CSi-VC) in the doubly positive charge state can explain all experimental findings. We propose that the (CSi-VC) defect is formed from the isolated silicon vacancy as an annealing product by the movement of a carbon neighbor into the vacancy

Mean field treatment of exclusion processes with random-force disorder

The asymmetric simple exclusion process with random-force disorder is studied within the mean field approximation. The stationary current through a domain with reversed bias is analyzed and the results are found to be in accordance with earlier intuitive assumptions. On the grounds of these results, a phenomenological random barrier model is applied in order to describe quantitatively the coarsening phenomena. Predictions of the theory are compared with numerical results obtained by integrating the mean field evolution equations.Comment: 21 pages, 14 figure

Presenting features and long-term effects of growth hormone treatment of children with optic nerve hypoplasia/septo-optic dysplasia

<p>Abstract</p> <p>Background</p> <p>Optic nerve hypoplasia (ONH) with/or without septo-optic dysplasia (SOD) is a known concomitant of congenital growth hormone deficiency (CGHD).</p> <p>Methods</p> <p>Demographic and longitudinal data from KIGS, the Pfizer International Growth Database, were compared between 395 subjects with ONH/SOD and CGHD and 158 controls with CGHD without midline pathology.</p> <p>Results</p> <p>ONH/SOD subjects had higher birth length/weight, and mid-parental height SDS. At GH start, height, weight, and BMI SDS were higher in the ONH/SOD group. After 1 year of GH, both groups showed similar changes in height SDS, while weight and BMI SDS remained higher in the ONH/SOD group. The initial height responses of the two groups were similar to those predicted using the KIGS-derived prediction model for children with idiopathic GHD. At near-adult height, ONH/SOD and controls had similar height, weight, and BMI SDS.</p> <p>Conclusions</p> <p>Compared to children with CGHD without midline defects, those with ONH/SOD presented with greater height, weight, and BMI SDS. These differences persisted at 1 year of GH therapy, but appeared to be overcome by long-term GH treatment.</p