System for measuring transients in fluid flow

When test valve is actuated, piston is moved by pressurized fluid, and displacement is monitored by electro-optical tracking system and recorded by oscilloscope camera. Electro-optical monitor produces output voltage proportional to displacement of piston

Risk measurement: an introduction to value at risk

This paper is a self-contained introduction to the concept and methodology of "value at risk," which is a new tool for measuring an entity's exposure to market risk. We explain the concept of value at risk, and then describe in detail the three methods for computing it: historical simulation; the variance-covariance method; and Monte Carlo or stochastic simulation. We then discuss the advantages and disadvantages of the three methods for computing value at risk. Finally, we briefly describe some alternative measures of market risk.Risk and Uncertainty,

Research on the structural performance of large rocket booster subjected to longitudinal excitations

Dynamic structural behavior of large booster rocket subjected to longitudinal excitations - analysis of theoretical mode

Individual differences in human annoyance response to noise

Individual variations in annoyance and in susceptibility to noise were studied to establish a finer definition of the ingredients of the human annoyance response. The study involved interactions among a heterogeneous sample of human subjects, various noise stimuli, and different physical environments of exposure. Significant differences in annoyance ratings among the six noise stimuli, all equated for peak sound pressure level, were found

Extracting quantum dynamics from genetic learning algorithms through principal control analysis

Genetic learning algorithms are widely used to control ultrafast optical pulse shapes for photo-induced quantum control of atoms and molecules. An unresolved issue is how to use the solutions found by these algorithms to learn about the system's quantum dynamics. We propose a simple method based on covariance analysis of the control space, which can reveal the degrees of freedom in the effective control Hamiltonian. We have applied this technique to stimulated Raman scattering in liquid methanol. A simple model of two-mode stimulated Raman scattering is consistent with the results.Comment: 4 pages, 5 figures. Presented at coherent control Ringberg conference 200

Suppression of spin-pumping by a MgO tunnel-barrier

Spin-pumping generates pure spin currents in normal metals at the ferromagnet (F)/normal metal (N) interface. The efficiency of spin-pumping is given by the spin mixing conductance, which depends on N and the F/N interface. We directly study the spin-pumping through an MgO tunnel-barrier using the inverse spin Hall effect, which couples spin and charge currents and provides a direct electrical detection of spin currents in the normal metal. We find that spin-pumping is suppressed by the tunnel-barrier, which is contrary to recent studies that suggest that the spin mixing conductance can be enhanced by a tunnel-barrier inserted at the interface

De-blending Deep Herschel Surveys: A Multi-wavelength Approach

Cosmological surveys in the far infrared are known to suffer from confusion. The Bayesian de-blending tool, XID+, currently provides one of the best ways to de-confuse deep Herschel SPIRE images, using a flat flux density prior. This work is to demonstrate that existing multi-wavelength data sets can be exploited to improve XID+ by providing an informed prior, resulting in more accurate and precise extracted flux densities. Photometric data for galaxies in the COSMOS field were used to constrain spectral energy distributions (SEDs) using the fitting tool CIGALE. These SEDs were used to create Gaussian prior estimates in the SPIRE bands for XID+. The multi-wavelength photometry and the extracted SPIRE flux densities were run through CIGALE again to allow us to compare the performance of the two priors. Inferred ALMA flux densities (F$^i$), at 870$\mu$m and 1250$\mu$m, from the best fitting SEDs from the second CIGALE run were compared with measured ALMA flux densities (F$^m$) as an independent performance validation. Similar validations were conducted with the SED modelling and fitting tool MAGPHYS and modified black body functions to test for model dependency. We demonstrate a clear improvement in agreement between the flux densities extracted with XID+ and existing data at other wavelengths when using the new informed Gaussian prior over the original uninformed prior. The residuals between F$^m$ and F$^i$ were calculated. For the Gaussian prior, these residuals, expressed as a multiple of the ALMA error ($\sigma$), have a smaller standard deviation, 7.95$\sigma$ for the Gaussian prior compared to 12.21$\sigma$ for the flat prior, reduced mean, 1.83$\sigma$ compared to 3.44$\sigma$, and have reduced skew to positive values, 7.97 compared to 11.50. These results were determined to not be significantly model dependent. This results in statistically more reliable SPIRE flux densities.Comment: 8 pages, 7 figures, 3 tables. Accepted for publication in A&