Graviton-photon conversion on spin 0 and 1/2 particles

The differential cross-sections for scattering of gravitons into photons on bosons and fermions are calculated in linearized quantum gravity. They are found to be strongly peaked in the forward direction and become constant at high energies. Numerically, they are very small as expected for such gravitational interactions.Comment: 13 pages, LaTeX with 5 figure

Towards validation of a new computerised test of goal neglect: preliminary evidence from clinical and neuroimaging pilot studies

Objective: Goal neglect is a significant problem following brain injury, and is a target for rehabilitation. It is not yet known how neural activation might change to reflect rehabilitation gains. We developed a computerised multiple elements test (CMET), suitable for use in neuroimaging paradigms. Design: Pilot correlational study and event-related fMRI study. Methods: In Study 1, 18 adults with acquired brain injury were assessed using the CMET, other tests of goal neglect (Hotel Test; Modified Six Elements Test) and tests of reasoning. In Study 2, 12 healthy adults underwent fMRI, during which the CMET was administered under two conditions: self-generated switching and experimenter-prompted switching. Results: Among the clinical sample, CMET performance was positively correlated with both the Hotel Test (r = 0.675, p = 0.003) and the Modified Six Elements Test (r = 0.568, p = 0.014), but not with other clinical or demographic measures. In the healthy sample, fMRI demonstrated significant activation in rostro-lateral prefrontal cortex in the self-generated condition compared with the prompted condition (peak 40, 44, 4; ZE = 4.25, p(FWEcorr) = 0.026). Conclusions: These pilot studies provide preliminary evidence towards the validation of the CMET as a measure of goal neglect. Future studies will aim to further establish its psychometric properties, and determine optimum pre- and post-rehabilitation fMRI paradigms

Chemiluminescence of asbestos-activated macrophages

Chemiluminescence, a measure of reactive oxygen release by phagocytes, was compared in peritoneal exudate macrophages elicited with chrysotile asbestos, Corynebacterium parvum and saline. Chrysotile asbestos- and C. parvum-activated macrophages produced significantly more chemiluminescence than saline-elicited macrophages. In a second series of experiments the ability of opsonized chrysotile asbestos to act as a trigger for the release of chemiluminescence was tested. Opsonized chrysotile asbestos produced a dose-related release of chemiluminescence from activated macrophages except at the highest dose where chemiluminescence was reduced due, possibly, to a toxic effect of chrysotile during the assay. Opsonized latex also triggered a dose-related chemiluminescent response from activated macrophages. The potential role of toxic reactive oxygen species, released from macrophages, in the development of asbestos-related pulmonary inflammation and fibrosis are discussed

The mechanical properties of inconel 718 sheet alloy at 800 deg, 1000 deg, and 1200 deg f

Mechanical properties of Inconel sheet superalloy at very high temperatures for supersonic transpor

Princess and the Pea at the nanoscale: Wrinkling and delamination of graphene on nanoparticles

Thin membranes exhibit complex responses to external forces or geometrical constraints. A familiar example is the wrinkling, exhibited by human skin, plant leaves, and fabrics, resulting from the relative ease of bending versus stretching. Here, we study the wrinkling of graphene, the thinnest and stiffest known membrane, deposited on a silica substrate decorated with silica nanoparticles. At small nanoparticle density monolayer graphene adheres to the substrate, detached only in small regions around the nanoparticles. With increasing nanoparticle density, we observe the formation of wrinkles which connect nanoparticles. Above a critical nanoparticle density, the wrinkles form a percolating network through the sample. As the graphene membrane is made thicker, global delamination from the substrate is observed. The observations can be well understood within a continuum elastic model and have important implications for strain-engineering the electronic properties of graphene.Comment: 11 pages, 8 figures. Accepted for publication in Physical Review

Solid rocket booster internal flow analysis by highly accurate adaptive computational methods

The primary objective of this project was to develop an adaptive finite element flow solver for simulating internal flows in the solid rocket booster. Described here is a unique flow simulator code for analyzing highly complex flow phenomena in the solid rocket booster. New methodologies and features incorporated into this analysis tool are described

Assessing neural network scene classification from degraded images

Scene recognition is an essential component of both machine and biological vision. Recent advances in computer vision using deep convolutional neural networks (CNNs) have demonstrated impressive sophistication in scene recognition, through training on large datasets of labeled scene images (Zhou et al. 2018, 2014). One criticism of CNN-based approaches is that performance may not generalize well beyond the training image set (Torralba and Efros 2011), and may be hampered by minor image modifications, which in some cases are barely perceptible to the human eye (Goodfellow et al. 2015; Szegedy et al. 2013). While these “adversarial examples” may be unlikely in natural contexts, during many real-world visual tasks scene information can be degraded or limited due to defocus blur, camera motion, sensor noise, or occluding objects. Here, we quantify the impact of several image degradations (some common, and some more exotic) on indoor/outdoor scene classification using CNNs. For comparison, we use human observers as a benchmark, and also evaluate performance against classifiers using limited, manually selected descriptors. While the CNNs outperformed the other classifiers and rivaled human accuracy for intact images, our results show that their classification accuracy is more affected by image degradations than human observers. On a practical level, however, accuracy of the CNNs remained well above chance for a wide range of image manipulations that disrupted both local and global image statistics. We also examine the level of image-by-image agreement with human observers, and find that the CNNs' agreement with observers varied as a function of the nature of image manipulation. In many cases, this agreement was not substantially different from the level one would expect to observe for two independent classifiers. Together, these results suggest that CNN-based scene classification techniques are relatively robust to several image degradations. However, the pattern of classifications obtained for ambiguous images does not appear to closely reflect the strategies employed by human observers