Two phase detonation studies

An experimental study of the passage of a shock wave over a burning fuel drop is described. This includes high speed framing photographs of the interaction taken at 500,000 frames per second. A theoretical prediction of the ignition of a fuel drop by a shock wave is presented and the results compared with earlier experimental work. Experimental attempts to generate a detonation in a liquid fuel drop (kerosene)-liquid oxidizer drop (hydrogen peroxide)-inert gas-environment are described. An appendix is included which gives the analytical prediction of power requirements for the drop generator to produce certain size drops at a certain mass rate. A bibliography is also included which lists all of the publications resulting from this research grant

Preliminary evaluation of radar imagery of Yellowstone Park, Wyoming

Evaluation of radar imagery of Yellowstone Park, Wyomin

Acoustic characterization of Hofstadter butterfly with resonant scatterers

We are interested in the experimental characterization of the Hofstadter butterfly by means of acoustical waves. The transmission of an acoustic pulse through an array of 60 variable and resonant scatterers periodically distribued along a waveguide is studied. An arbitrary scattering arrangement is realized by using the variable length of each resonator cavity. For a periodic modulation, the structures of forbidden bands of the transmission reproduce the Hofstadter butterfly. We compare experimental, analytical, and computational realizations of the Hofstadter butterfly and we show the influence of the resonances of the scatterers on the structure of the butterfly

CASTNet: Community-Attentive Spatio-Temporal Networks for Opioid Overdose Forecasting

Opioid overdose is a growing public health crisis in the United States. This crisis, recognized as "opioid epidemic," has widespread societal consequences including the degradation of health, and the increase in crime rates and family problems. To improve the overdose surveillance and to identify the areas in need of prevention effort, in this work, we focus on forecasting opioid overdose using real-time crime dynamics. Previous work identified various types of links between opioid use and criminal activities, such as financial motives and common causes. Motivated by these observations, we propose a novel spatio-temporal predictive model for opioid overdose forecasting by leveraging the spatio-temporal patterns of crime incidents. Our proposed model incorporates multi-head attentional networks to learn different representation subspaces of features. Such deep learning architecture, called "community-attentive" networks, allows the prediction of a given location to be optimized by a mixture of groups (i.e., communities) of regions. In addition, our proposed model allows for interpreting what features, from what communities, have more contributions to predicting local incidents as well as how these communities are captured through forecasting. Our results on two real-world overdose datasets indicate that our model achieves superior forecasting performance and provides meaningful interpretations in terms of spatio-temporal relationships between the dynamics of crime and that of opioid overdose.Comment: Accepted as conference paper at ECML-PKDD 201

A High Throughput Workflow Environment for Cosmological Simulations

The next generation of wide-area sky surveys offer the power to place extremely precise constraints on cosmological parameters and to test the source of cosmic acceleration. These observational programs will employ multiple techniques based on a variety of statistical signatures of galaxies and large-scale structure. These techniques have sources of systematic error that need to be understood at the percent-level in order to fully leverage the power of next-generation catalogs. Simulations of large-scale structure provide the means to characterize these uncertainties. We are using XSEDE resources to produce multiple synthetic sky surveys of galaxies and large-scale structure in support of science analysis for the Dark Energy Survey. In order to scale up our production to the level of fifty 10^10-particle simulations, we are working to embed production control within the Apache Airavata workflow environment. We explain our methods and report how the workflow has reduced production time by 40% compared to manual management.Comment: 8 pages, 5 figures. V2 corrects an error in figure

Predictions for Higgs and SUSY spectra from SO(10) Yukawa Unification with mu > 0

We use $t, b, \tau$ Yukawa unification to constrain SUSY parameter space. We find a narrow region survives for $\mu > 0$ (suggested by \bsgam and the anomalous magnetic moment of the muon) with $A_0 \sim - 1.9 m_{16}$, $m_{10} \sim 1.4 m_{16}$, $m_{16} \sim 1200 -3000$ \gev and $\mu, M_{1/2} \sim 100 - 500$ \gev. Demanding Yukawa unification thus makes definite predictions for Higgs and sparticle masses.Comment: 10 pages, 3 figures, revised version to be published in PR