An interactive graphics system to facilitate finite element structural analysis

The characteristics of an interactive graphics systems to facilitate the finite element method of structural analysis are described. The finite element model analysis consists of three phases: (1) preprocessing (model generation), (2) problem solution, and (3) postprocessing (interpretation of results). The advantages of interactive graphics to finite element structural analysis are defined

Predicting the On-Study Relapse Rate for Multiple Sclerosis Patients in Clinical Trials

Background: The annual relapse rate has been commonly used as a primary efficacy endpoint in phase III multiple sclerosis (MS) clinical trials. The aim of this study was to determine the relative contribution of different possible prognostic factors available at baseline to the on-study relapse rate in MS. Methods: A total of 821 patients from the placebo arms of the Sylvia Lawry Centre for Multiple Sclerosis Research (SLCMSR) database were available for this analysis. The univariate relationships between on-study relapse rate and the baseline demographic, clinical, and MRI-based predictors were assessed. The multiple relationships were then examined using a Poisson regression model. Two predictor subsets were selected. Subset 1 included age at disease onset, disease duration, gender, Expanded Disability Status Scale (EDSS) at baseline, number of relapses in the last 24 months prior to baseline, and the disease course (RR and SP). Subset 2 consisted of Subset 1 plus gadolinium enhancement status in MRI. The number of patients for developing the models with no missing values was 727 for Subset 1 and 306 for Subset 2. Results:The univariate relationships show that the on-study relapse rate was higher for younger and for female patients, for RR patients than for SP patients, and for patients with positive enhancement status at entry (Wilcoxon test, p<0.05). A higher on-study relapse rate was associated with a shorter disease duration, lower entry EDSS, more pre-study relapses and more enhancing lesions in T1 at entry. The fitted Poisson model shows that disease duration (estimate=-0.02) and previous relapse number (estimate=0.59 for 1, 0.91 for 2 and 1.45 for 3 or more relapses vs 0 relapse) remain. We were able to confirm these findings in a second, independent dataset. Conclusions: The relapse number prior to entry into clinical trials together with disease duration are the best predictors for the on-study relapse rate. Disease course and gadolinium enhancement status, given the other covariates, have no significant influence on the on-study relapse rate

Kinks: Fingerprints of strong electronic correlations

The textbook knowledge of solid state physics is that the electronic specific heat shows a linear temperature dependence with the leading corrections being a cubic term due to phonons and a cubic-logarithmic term due to the interaction of electrons with bosons. We have shown that this longstanding conception needs to be supplemented since the generic behavior of the low-temperature electronic specific heat includes a kink if the electrons are sufficiently strongly correlatedComment: 4 pages, 1 figure, ICM 2009 conference proceedings (to appear in Journal of Physics: Conference Series

Development of helical seal for high temperature /2000 degrees F/ application

Helical seal is used to seal bolted flange joints in a high temperature environment. The seal design incorporates a new cross-sectional shape, a metal strip with a slight radius, and the use of premolded asbestos. It provides equal load distribution under compression loads, allows for minimum loss and recovery values, and increases the temperature range

The invisible power of fairness. How machine learning shapes democracy

Many machine learning systems make extensive use of large amounts of data regarding human behaviors. Several researchers have found various discriminatory practices related to the use of human-related machine learning systems, for example in the field of criminal justice, credit scoring and advertising. Fair machine learning is therefore emerging as a new field of study to mitigate biases that are inadvertently incorporated into algorithms. Data scientists and computer engineers are making various efforts to provide definitions of fairness. In this paper, we provide an overview of the most widespread definitions of fairness in the field of machine learning, arguing that the ideas highlighting each formalization are closely related to different ideas of justice and to different interpretations of democracy embedded in our culture. This work intends to analyze the definitions of fairness that have been proposed to date to interpret the underlying criteria and to relate them to different ideas of democracy.Comment: 12 pages, 1 figure, preprint version, submitted to The 32nd Canadian Conference on Artificial Intelligence that will take place in Kingston, Ontario, May 28 to May 31, 201

Synthetic aperture radar target simulator

A simulator for simulating the radar return, or echo, from a target seen by a SAR antenna mounted on a platform moving with respect to the target is described. It includes a first-in first-out memory which has digital information clocked in at a rate related to the frequency of a transmitted radar signal and digital information clocked out with a fixed delay defining range between the SAR and the simulated target, and at a rate related to the frequency of the return signal. An RF input signal having a frequency similar to that utilized by a synthetic aperture array radar is mixed with a local oscillator signal to provide a first baseband signal having a frequency considerably lower than that of the RF input signal

Signature of antiferromagnetic long-range order in the optical spectrum of strongly correlated electron systems

We show how the onset of a non-Slater antiferromagnetic ordering in a correlated material can be detected by optical spectroscopy. Using dynamical mean-field theory we identify two distinctive features: The antiferromagnetic ordering is associated with an enhanced spectral weight above the optical gap, and well separated spin-polaron peaks emerge in the optical spectrum. Both features are indeed observed in LaSrMnO_4 [G\"ossling et al., Phys. Rev. B 77, 035109 (2008)]Comment: 11 pages, 9 figure

Efficient simulation of Bayesian logistic regression models

In this paper we highlight a data augmentation approach to inference in the Bayesian logistic regression model. We demonstrate that the resulting conditional likelihood of the regression coefficients is multivariate normal, equivalent to a standard Bayesian linear regression, which allows for efficient simulation using a block Gibbs sampler. We illustrate that the method is particularly suited to problems in covariate set uncertainty and random effects models

External calibration of SIR-B imagery with area-extended and point targets

Data-takes on two ascending orbits of the Shuttle Imaging Radar-B (SIR-B) over an agricultural test site in west-central Illinois were used to establish end-to-end transfer functions for conversion of the digital numbers on the 8-bit image to values of the radar backscattering coefficient sigma sup 0 (sq m/sq. m) in dB. The transfer function for each data-take was defined by the SIR-B response to an array of six calibrated point targets of known radar cross-section (transponders) and to a large number of area-extended targets also with known radar cross-section as measured by externally calibrated, truck-mounted scatterometers. The radar cross-section of each transponder at the SIR-B center frequency was measured on an antenna range as a function of local angle of incidence. Two truck-mounted scatterometers observed 20 to 80 agricultural fields daily at 1.6 GHz with HH polarization and at azimuth viewing angles and incidence angles equivalent to those of the SIR-B. The form of the transfer function is completely defined by the SIR-B receiver and the incoherent averaging procedure incorporated into production of the standard SIR-B image product