Magnetic characterization and switching of Co nano-rings in current-perpendicular-to-plane configuration

We fabricated Co nano-rings incorporated in the vertical pseudo-spin-valve nanopillar structures with deep submicron lateral sizes. It is shown that the current-perpendicular-to-plane giant magnetoresistance can be used to characterize a very small magnetic nano-ring effectively. Both the onion state and the flux-closure vortex state are observed. The Co nano-rings can be switched between the onion states as well as between onion and vortex states not only by the external field but also by the perpendicularly injected dc current

Aeroelastic analysis of wings using the Euler equations with a deforming mesh

Modifications to the CFL3D three dimensional unsteady Euler/Navier-Stokes code for the aeroelastic analysis of wings are described. The modifications involve including a deforming mesh capability which can move the mesh to continuously conform to the instantaneous shape of the aeroelastically deforming wing, and including the structural equations of motion for their simultaneous time-integration with the governing flow equations. Calculations were performed using the Euler equations to verify the modifications to the code and as a first step toward aeroelastic analysis using the Navier-Stokes equations. Results are presented for the NACA 0012 airfoil and a 45 deg sweptback wing to demonstrate applications of CFL3D for generalized force computations and aeroelastic analysis. Comparisons are made with published Euler results for the NACA 0012 airfoil and with experimental flutter data for the 45 deg sweptback wing to assess the accuracy of the present capability. These comparisons show good agreement and, thus, the CFL3D code may be used with confidence for aeroelastic analysis of wings

Making Rasch decisions: The use of Rasch analysis in the construction of preference based health related quality of life instruments

Objective: To set out the methodological process for using Rasch analysis alongside traditional psychometric methods in the development of a health state classification that is amenable to valuation. Methods: The overactive bladder questionnaire is used to illustrate a four step process for deriving a reduced health state classification from an existing nonpreference based health related quality of life instrument. Step I excludes items that do not meet the initial validation process and step II uses criteria based on Rasch analysis and psychometric testing to select the final items for the health state classification. In step III, item levels are examined and Rasch analysis is used to explore the possibility of reducing the number of item levels. Step IV repeats steps I to III on alternative data sets in order to validate the selection of items for the health state classification. Conclusions: The techniques described enable the construction of a health state classification amenable for valuation exercises that will allow the derivation of preference weights. Thus, the health related quality of life of patients with conditions, like overactive bladder, can be valued and quality adjustment weights such as quality adjusted life years derived

The use of Rasch analysis as a tool in the construction of a preference based measure: the case of AQLQ

The majority of quality of life instruments are not preference-based measures and so cannot be used within cost utility analysis. The Asthma Quality of Life Questionnaire (AQLQ) is one such instrument. The aim of this study was to develop a health state classification that is amenable to valuation from the AQLQ. Rasch models were applied to samples of responders to the AQLQ with the aim of i) selecting a number of items for a preference based utility measure (AQL-5D), ii) reducing the number of levels for each item to a more manageable number of levels for establishing AQL-5D. Selection of items for the evaluation survey was supported with conventional psychometric criteria for item selection (feasibility, internal consistency, floor and ceiling effects, responsiveness and regression against overall health). The role of Rasch analysis in reducing the number of item levels to a preconceived target number of levels proved unsuccessful. However, Rasch analysis proved to be a useful tool in assisting in the initial process of selecting items from an existing HRQL instrument in the construction of AQL-5D. The method is recommended for use alongside conventional psychometric testing to aid in the development of preference-based measures

Making Rasch decisions: The use of Rasch analysis in the construction of preference based health related quality of life instruments

Objective: To set out the methodological process for using Rasch analysis alongside traditional psychometric methods in the development of a health state classification that is amenable to valuation. Methods: The overactive bladder questionnaire is used to illustrate a four step process for deriving a reduced health state classification from an existing nonpreference based health related quality of life instrument. Step I excludes items that do not meet the initial validation process and step II uses criteria based on Rasch analysis and psychometric testing to select the final items for the health state classification. In step III, item levels are examined and Rasch analysis is used to explore the possibility of reducing the number of item levels. Step IV repeats steps I to III on alternative data sets in order to validate the selection of items for the health state classification. Conclusions: The techniques described enable the construction of a health state classification amenable for valuation exercises that will allow the derivation of preference weights. Thus, the health related quality of life of patients with conditions, like overactive bladder, can be valued and quality adjustment weights such as quality adjusted life years derived

Growth control of GaAs nanowires using pulsed laser deposition with arsenic over pressure

Using pulsed laser ablation with arsenic over pressure, the growth conditions for GaAs nanowires have been systematically investigated and optimized. Arsenic over pressure with As$_2$ molecules was introduced to the system by thermal decomposition of polycrystalline GaAs to control the stoichiometry and shape of the nanowires during growth. GaAs nanowires exhibit a variety of geometries under varying arsenic over pressure, which can be understood by different growth processes via vapor-liquid-solid mechanism. Single-crystal GaAs nanowires with uniform diameter, lengths over 20 $\mu$m, and thin surface oxide layer were obtained and can potentially be used for further electronic characterization

Twist Symmetry and Classical Solutions in Open String Field Theory

We construct classical solutions of open string field theory which are not invariant under ordinary twist operation. From detailed analysis of the moduli space of the solutions, it turns out that our solutions become nontrivial at boundaries of the moduli space. The cohomology of the modified BRST operator and the CSFT potential evaluated by the level truncation method strongly support the fact that our nontrivial solutions correspond to the closed string vacuum. We show that the nontrivial solutions are equivalent to the twist even solution which was found by Takahashi and Tanimoto, and twist invariance of open string field theory remains after the shift of the classical backgrounds.Comment: 19 pages, 2 figures; v2: errors fixe

Predicting Future Instance Segmentation by Forecasting Convolutional Features

Anticipating future events is an important prerequisite towards intelligent behavior. Video forecasting has been studied as a proxy task towards this goal. Recent work has shown that to predict semantic segmentation of future frames, forecasting at the semantic level is more effective than forecasting RGB frames and then segmenting these. In this paper we consider the more challenging problem of future instance segmentation, which additionally segments out individual objects. To deal with a varying number of output labels per image, we develop a predictive model in the space of fixed-sized convolutional features of the Mask R-CNN instance segmentation model. We apply the "detection head'" of Mask R-CNN on the predicted features to produce the instance segmentation of future frames. Experiments show that this approach significantly improves over strong baselines based on optical flow and repurposed instance segmentation architectures

The Changing AGN Population

We investigate how the fraction of broad-line sources in the AGN population changes with X-ray luminosity and redshift. We first construct the rest-frame hard-energy (2-8 keV) X-ray luminosity function (HXLF) at z=0.1-1 using Chandra Lockman Hole-Northwest wide-area data, Chandra Deep Field-North 2 Ms data, other Chandra deep field data, and the ASCA Large Sky Survey data. We find that broad-line AGNs dominate above 3e43 ergs/s and have a mean luminosity of 1.3e44 ergs/s. Type II AGNs can only become an important component of the X-ray population at Seyfert-like X-ray luminosities. We then construct z=0.1-0.5 and z=0.5-1 HXLFs and compare them with both the local HXLF measured from HEAO-1 A2 survey data and the z=1.5-3 HXLF measured from soft-energy (0.5-2 keV) Chandra and ROSAT data. We find that the number density of >1e44 ergs/s sources (quasars) steadily declines with decreasing redshift, while the number density of 1e43-1e44 ergs/s sources peaks at z=0.5-1. Strikingly, however, the number density of broad-line AGNs remains roughly constant with redshift while their average luminosities decline at the lower redshifts, showing another example of cosmic downsizing.Comment: Accepted by The Astrophysical Journal Letters, 5 page