Circuits and circuit testing for spaceborne redundant digital systems Special technical report no. 3

Design and testing of majority logic redundancy for spaceborne and GSE digital system

Thermal annealing of GaAs concentrator solar cells

Isochronal and isothermal annealing tests were performed on GaAs concentrator cells which were irradiated with electrons of various energies to fluences up to 1 x 10(exp 16) e/sq cm. The results include: (1) For cells irradiated with electrons from 0.7 to 2.3 MeV, recovery decreases with increasing electron energy. (2) As determined by the un-annealed fractions, isothermal and isochronal annealing produce the same recovery. Also, cells irradiated to 3 x 10(exp 15) or 1 x 10(exp 16) e/sq cm recover to similar un-annealed fractions. (3) Some significant annealing is being seen at 150 C although very long times are required

Research on failure free systems Final report

Development and testing of integrated circuits and redundant systems for circuit reliability and failure free system

Effect of dislocations on properties of heteroepitaxial InP solar cells

The apparently unrelated phenomena of temperature dependency, carrier removal and photoluminescence are shown to be affected by the high dislocation densities present in heteroepitaxial InP solar cells. Using homoepitaxial InP cells as a baseline, it is found that the relatively high dislocation densities present in heteroepitaxial InP/GaAs cells lead to increased volumes of dVoc/dt and carrier removal rate and substantial decreases in photoluminescence spectral intensities. With respect to dVoc/dt, the observed effect is attributed to the tendency of dislocations to reduce Voc. Although the basic cause for the observed increase in carrier removal rate is unclear, it is speculated that the decreased photoluminescence intensity is attributable to defect levels introduced by dislocations in the heteroepitaxial cells

Continuous cough monitoring using ambient sound recording during convalescence from a COPD exacerbation

Purpose Cough is common in chronic obstructive pulmonary disease (COPD) and is associated with frequent exacerbations and increased mortality. Cough increases during acute exacerbations (AE-COPD), representing a possible metric of clinical deterioration. Conventional cough monitors accurately report cough counts over short time periods. We describe a novel monitoring system which we used to record cough continuously for up to 45 days during AE-COPD convalescence. Methods This is a longitudinal, observational study of cough monitoring in AE-COPD patients discharged from a single teaching-hospital. Ambient sound was recorded from two sites in the domestic environment and analysed using novel cough classifier software. For comparison, the validated hybrid HACC/LCM cough monitoring system was used on days 1, 5, 20 and 45. Patients were asked to record symptoms daily using diaries. Results Cough monitoring data were available for 16 subjects with a total of 568 monitored days. Daily cough count fell significantly from mean±SEM 272.7±54.5 on day 1 to 110.9±26.3 on day 9 (p<0.01) before plateauing. The absolute cough count detected by the continuous monitoring system was significantly lower than detected by the hybrid HACC/LCM system but normalised counts strongly correlated (r=0.88, p<0.01) demonstrating an ability to detect trends. Objective cough count and subjective cough scores modestly correlated (r=0.46). Conclusions Cough frequency declines significantly following AE-COPD and the reducing trend can be detected using continuous ambient sound recording and novel cough classifier software. Objective measurement of cough frequency has the potential to enhance our ability to monitor the clinical state in patients with COPD

A Hamiltonian approach for explosive percolation

We introduce a cluster growth process that provides a clear connection between equilibrium statistical mechanics and an explosive percolation model similar to the one recently proposed by Achlioptas et al. [Science 323, 1453 (2009)]. We show that the following two ingredients are essential for obtaining an abrupt (first-order) transition in the fraction of the system occupied by the largest cluster: (i) the size of all growing clusters should be kept approximately the same, and (ii) the inclusion of merging bonds (i.e., bonds connecting vertices in different clusters) should dominate with respect to the redundant bonds (i.e., bonds connecting vertices in the same cluster). Moreover, in the extreme limit where only merging bonds are present, a complete enumeration scheme based on tree-like graphs can be used to obtain an exact solution of our model that displays a first-order transition. Finally, the proposed mechanism can be viewed as a generalization of standard percolation that discloses an entirely new family of models with potential application in growth and fragmentation processes of real network systems.Comment: 4 pages, 4 figure

Dynamics in the O(2 × 1) adlayer on Ru(0001): bridging timescales from milliseconds to minutes by scanning tunneling microscopy

The dynamics within an O(2 × 1) adlayer on Ru(0001) is studied by density functional theory and high-speed scanning tunneling microscopy. Transition state theory proposes dynamic oxygen species in the reduced O(2 × 1) layer at room temperature. Collective diffusion processes can result in structural reorientations of characteristic stripe patterns. Spiral high-speed scanning tunneling microscopy measurements reveal this reorientation as a function of time in real space. Measurements, ranging over several minutes with constantly high frame rates of 20 Hz resolved the gradual reorientation. Moreover, reversible fast flipping events of stripe patterns are observed. These measurements relate the observations of long-term atomic rearrangements and their underlying fast processes captured within several tens of milliseconds

Resolving atomic diffusion in Ru(0001)-O(2×2) with spiral high-speed scanning tunneling microscopy

An intermediate state in atomic diffusion processes in the O(2×2) layer on Ru(0001) is resolved with spiral high-speed scanning tunneling microscopy (STM). The diffusion of atomic oxygen in the adlayer has been studied by density functional theory and STM. Transition state theory proposes a migration pathway for the diffusion in the oxygen adlayer. With spiral scan geometries—a new approach to high-speed STM—the oxygen vacancy mobility on the highly covered Ru(0001) surface is determined to be in the range of 0.1 to 1 Hz. Experimental evidence for the intermediate state along the oxygen diffusion pathway is provided in real space and real time

Spiral high-speed scanning tunneling microscopy: Tracking atomic diffusion on the millisecond timescale

Scanning tunneling microscopy (STM) is one of the most prominent techniques to resolve atomic structures of flat surfaces and thin films. With the scope to answer fundamental questions in physics and chemistry, it was used to elucidate numerous sample systems at the atomic scale. However, dynamic sample systems are difficult to resolve with STM due to the long acquisition times of typically more than 100 s per image. Slow electronic feedback loops, slow data acquisition, and the conventional raster scan limit the scan speed. Raster scans introduce mechanical noise to the image and acquire data discontinuously. Due to the backward and upward scan or the flyback movement of the tip, image acquisition times are doubled or even quadrupled. By applying the quasi-constant height mode and by using a combination of high-speed electronics for data acquisition and innovative spiral scan patterns, we could increase the frame rate in STM significantly. In the present study, we illustrate the implementation of spiral scan geometries and focus on the scanner input signal and the image visualization. Constant linear and constant angular velocity spirals were tested on the Ru(0001) surface to resolve chemisorbed atomic oxygen. The spatial resolution of the spiral scans is comparable to slow raster scans, while the imaging time was reduced from ~100 s to ~8 ms. Within 8 ms, oxygen diffusion processes were atomically resolved

Deep neural network or dermatologist?

Deep learning techniques have proven high accuracy for identifying melanoma in digitised dermoscopic images. A strength is that these methods are not constrained by features that are pre-defined by human semantics. A down-side is that it is difficult to understand the rationale of the model predictions and to identify potential failure modes. This is a major barrier to adoption of deep learning in clinical practice. In this paper we ask if two existing local interpretability methods, Grad-CAM and Kernel SHAP, can shed light on convolutional neural networks trained in the context of melanoma detection. Our contributions are (i) we first explore the domain space via a reproducible, end-to-end learning framework that creates a suite of 30 models, all trained on a publicly available data set (HAM10000), (ii) we next explore the reliability of GradCAM and Kernel SHAP in this context via some basic sanity check experiments (iii) finally, we investigate a random selection of models from our suite using GradCAM and Kernel SHAP. We show that despite high accuracy, the models will occasionally assign importance to features that are not relevant to the diagnostic task. We also show that models of similar accuracy will produce different explanations as measured by these methods. This work represents first steps in bridging the gap between model accuracy and interpretability in the domain of skin cancer classification