45915 research outputs found
Sort by
Return stroke speed of cloud-to-ground lightning estimated from elve hole radii
No full textWe present the first measurements of the lightning return stroke speed that directly relate to the current return stroke, as opposed to its optical manifestation. The shape of elves is determined by the electromagnetic pulse (EMP) radiation pattern at D region altitudes, which is in turn controlled by the geometry and current propagation properties of the return stroke channel. In particular, numerical simulation of the EMP-ionosphere interaction shows a strong relationship between the elve hole radius and the current return stroke speed. The hole radii are measured from a data set of 55 elves observed with the PIPER photometer. Using these radii observations in conjunction with numerical simulations of the EMP, we perform Bayesian inference to estimate the distribution of return stroke speeds. The results show a maximum a posteriori probability return stroke speed estimate of 0.64c for elve producing lightning
DEMETER observations of ionospheric heating by powerful VLF transmitters
No full textWe report DEMETER spacecraft observations of ionospheric heating produced above powerful VLF transmitters by their intense radiated electromagnetic (EM) signals. We compare the heating effects of signals from the 1 MW NWC transmitter in Australia with those produced by signals from the 885 kW NAA transmitter in Maine. Significant observable effects include perturbations in plasma density and thermal electron temperature, and the production of quasi-electrostatic (QE) VLF plasma wave bands, both over the transmitters, and, in the case of NWC, also in the magnetically conjugate region. In the regions in which the QE wave bands were observed, they were invariably accompanied by a band of ELF turbulence with maximum intensity below 300 Hz. Such turbulence has in the past been associated with the presence of small scale plasma density irregularities. This association suggests that heating effects due to NWC are far-reaching and extend along B(o) into the conjugate hemisphere where they are expressed in part as small scale plasma density fluctuations
A 2D MEMS stage for optical applications
No full textA 2D MEMS platform for a microlens scanner application is reported. The platform is fabricated on an SOI wafer with 50/μm thick device layer. Entire device is defined with a single etching step on the same layer. Through four S-shaped beams, the device is capable of producing nonlinear 2D motion from linear ID translation of two pairs of comb actuator sets. The device has a clear aperture of 2mm by 2mm, which is hallowed from the backside for micro-optics assembly. In this paper, a numerical device model and its validation via experimental characterization results are presented. Integration of the micro-optical components with the stage is also discussed. Additionally, a new driving scheme to minimize the settling time of the device in DC operation is explored
Integrating gene set analysis and nonlinear predictive modeling of disease phenotypes using a Bayesian multitask formulation
No full textIdentifying molecular signatures of disease phenotypes is studied using two mainstream approaches: (i) Predictive modeling methods such as linear classification and regression algorithms are used to find signatures predictive of phenotypes from genomic data, which may not be robust due to limited sample size or highly correlated nature of genomic data. (ii) Gene set analysis methods are used to find gene sets on which phenotypes are linearly dependent by bringing prior biological knowledge into the analysis, which may not capture more complex nonlinear dependencies. Thus, formulating an integrated model of gene set analysis and nonlinear predictive modeling is of great practical importance. In this study, we propose a Bayesian binary classification framework to integrate gene set analysis and nonlinear predictive modeling. We then generalize this formulation to multitask learning setting to model multiple related datasets conjointly. Our main novelty is the probabilistic nonlinear formulation that enables us to robustly capture nonlinear dependencies between genomic data and phenotype even with small sample sizes. We demonstrate the performance of our algorithms using repeated random subsampling validation experiments on two cancer and two tuberculosis datasets by predicting important disease phenotypes from genome-wide gene expression data. We are able to obtain comparable or even better predictive performance than a baseline Bayesian nonlinear algorithm and to identify sparse sets of relevant genes and gene sets on all datasets. We also show that our multitask learning formulation enables us to further improve the generalization performance and to better understand biological processes behind disease phenotypes
Correspondence-free alignment of 3D object models
No full textIn this work, we present a pose-invariant shape matching methodology for complete 3D object models. Our approach is based on first describing the objects with shape descriptors and then minimizing the distance between descriptors over an appropriate set of geometric transformations. Our chosen shape description methodology is the density-based framework (DBF), which is experimentally shown to be very effective in 3D object retrieval [1]. In our earlier work, we showed that density-based descriptors exhibit a permutation property that greatly reduces the equivocation of the eigenvalue-based axis labeling and moments-based polarity assignment in a computationally very efficient manner. In the present work, we show that this interesting permutation property is a consequence of the symmetry properties of regular polyhedra. Furthermore, we extend the invariance scheme to arbitrary 3D rotations by a discretization of the infinite space of 3D rotations followed by a nearest neighbor based approximate procedure employed to generate the necessary permutations
Immersive haptic interaction with media
No full textNew 3D video representations enable new modalities of interaction, such as haptic interaction, with 2D and 3D video for truly immersive media applications. Haptic interaction with video includes haptic structure and haptic motion for new immersive experiences. It is possible to compute haptic structure signals from 3D scene geometry or depth information. This paper introduces the concept of haptic motion, as well as new methods to compute haptic structure and motion signals for 2D video-plus-depth representation. The resulting haptic signals can be rendered using a haptic cursor attached to a 2D or 3D video display
Crack growth behavior of low-alloy bainitic 51CrV4 steel
No full textThe crack growth behavior of low-alloy bainitic 51CrV4 steel was investigated. The current results indicate that the stress state present during the isothermal bainitic transformation has a strong influence on the crack propagation behavior in the near threshold regime, when the crack growth direction is perpendicular to the loading axis of the original sample undergoing phase transformation. However, the influence of stresses superimposed during the bainitic transformation on the crack growth behavior vanishes when the stress ratio is reduced from R=0.5 to R=0.1. Microstructural investigations revealed a locally pinned crack, indicating that the crack growth behavior in the near threshold regime is also strongly dependent on the local microstructure. Overall, the current results constitute the first step towards establishing a database for understanding and modeling the crack growth behavior in final work pieces exhibiting functionally-graded microstructures
Bronze Age goddess frontal view
No full textOne of photographs captured by Ara Güler during his visits at Anatolian archaeological sites and museumsBlack & white photograph
Spectroscopic properties of Tm3+:TeO2-PbF 2 glasses in the near infrared
No full textTm3+-doped glasses have two emission bands that peak around 1470 nm and 1800 nm in the near infrared, making them potentially important in the development of fiber-optic amplifiers and fiber lasers. The relative strength and the quantum efficiency of these bands depend on the glass composition as well as the active ion concentration. In this study, we have investigated the variation of the luminescence strengths as a function of glass composition and Tm3+ ion concentration in a new type of Tm 3+-doped tellurite glass. In the experiments, two sets of samples with the host composition (1-x)TeO2-(x)PbF2 were prepared. In the first set, the active ion concentration was constant (1 mol. % Tm 3+) and x=10, 15, 17, 20, 22 and 25 mol. %. The second set had samples with x=10 mol. % and the active ion concentration varied from 0.2 to 1 mol. %. In the experiments, absorption measurements were first made to determine the spontaneous emission probabilities of the 4f-4f transitions of the Tm3+ ions. The calculations were made by using the Judd-Ofelt theory. The samples were then excited with a 785-nm diode to measure the relative emission strengths of the 1470-nm and 1800-nm bands. Our results show that as the Tm3+ ion concentration increases from 0.2 mol. % to 1 mol. %, the ratio of the 1470-nm intensity decreases from 0.98 to 0.18 relative to that of the 1800-nm band
Foliations of hyperbolic space by constant mean curvature hypersurfaces
No full textWe show that the constant mean curvature hypersurfaces in Hn+1 spanning the boundary of a star-shaped C1,1 domain in Sn∞ (Hn+1) give a foliation of Hn+1. We also show that if is a closed codimension-1 C2,α submanifold in Sn∞ (Hn+1) bounding a unique constant mean curvature hypersurface H in Hn+1 with ∂∞ H = for any H ∈ (−1, 1), then the constant mean curvature hypersurfaces { H} foliate Hn+1