Review of: Carl F. Cranor, Regulating Toxic Substances

Review of: Carl F. Cranor, Regulating Toxic Substances (Oxford University Press 1993). Acknowledgments, appendices, bibliography, figures, foreword by The Honorable George E. Brown, Jr., index, notes, tables. LC 91-47046; ISBN 0-19- 507436-X. [272 pp. Cloth $45.00. 200 Madison Avenue, New York NY 10016.

Spectra and Light Curves of Failed Supernovae

Astronomers have proposed a number of mechanisms to produce supernova explosions. Although many of these mechanisms are now not considered primary engines behind supernovae, they do produce transients that will be observed by upcoming ground-based surveys and NASA satellites. Here we present the first radiation-hydrodynamics calculations of the spectra and light curves from three of these "failed" supernovae: supernovae with considerable fallback, accretion induced collapse of white dwarfs, and energetic helium flashes (also known as type .Ia supernovae).Comment: 33 pages, 14 figure

The Los Alamos Supernova Light Curve Project: Computational Methods

We have entered the era of explosive transient astronomy, in which upcoming real-time surveys like the Large Synoptic Survey Telescope (LSST), the Palomar Transient Factory (PTF) and Panoramic Survey Telescope and Rapid Response System (Pan-STARRS) will detect supernovae in unprecedented numbers. Future telescopes such as the James Webb Space Telescope may discover supernovae from the earliest stars in the universe and reveal their masses. The observational signatures of these astrophysical transients are the key to unveiling their central engines, the environments in which they occur, and to what precision they will pinpoint cosmic acceleration and the nature of dark energy. We present a new method for modeling supernova light curves and spectra with the radiation hydrodynamics code RAGE coupled with detailed monochromatic opacities in the SPECTRUM code. We include a suite of tests that demonstrate how the improved physics is indispensable to modeling shock breakout and light curves.Comment: 18 pages, 19 figures, published in ApJ Supplement

Reconstructing Single Field Inflationary Actions From CMBR Data

This paper describes a general program for deriving the action of single field inflation models with nonstandard kinetic energy terms using CMBR power spectrum data. This method assumes that an action depends on a set of undetermined functions, each of which is a function of either the inflaton wave function or its time derivative. The scalar, tensor and non-gaussianity of the curvature perturbation spectrum are used to derive a set of reconstruction equations whose solution set can specify up to three of the undetermined functions. The method is then used to find the undetermined functions in various types of actions assuming power law type scalar and tensor spectra. In actions that contain only two unknown functions, the third reconstruction equation implies a consistency relation between the non-gaussianty, sound speed and slow roll parameters. In particular we focus on reconstructing a generalized DBI action with an unknown potential and warp factor. We find that for realistic scalar and tensor spectra, the reconstructed warp factor and potential are very similar to the theoretically derived result. Furthermore, physical consistency of the reconstructed warp factor and potential imposes strict constraints on the scalar and tensor spectral indices.Comment: 33 pages, 3 figures: v3 - References adde

Science and Ideology in Economic, Political, and Social Thought

This paper has two sources: One is my own research in three broad areas: business cycles, economic measurement and social choice. In all of these fields I attempted to apply the basic precepts of the scientific method as it is understood in the natural sciences. I found that my effort at using natural science methods in economics was met with little understanding and often considerable hostility. I found economics to be driven less by common sense and empirical evidence, then by various ideologies that exhibited either a political or a methodological bias, or both. This brings me to the second source: Several books have appeared recently that describe in historical terms the ideological forces that have shaped either the direct areas in which I worked, or a broader background. These books taught me that the ideological forces in the social sciences are even stronger than I imagined on the basis of my own experiences. The scientific method is the antipode to ideology. I feel that the scientific work that I have done on specific, long standing and fundamental problems in economics and political science have given me additional insights into the destructive role of ideology beyond the history of thought orientation of the works I will be discussing

Multisite Comparison of MRI Defacing Software Across Multiple Cohorts

With improvements to both scan quality and facial recognition software, there is an increased risk of participants being identified by a 3D render of their structural neuroimaging scans, even when all other personal information has been removed. To prevent this, facial features should be removed before data are shared or openly released, but while there are several publicly available software algorithms to do this, there has been no comprehensive review of their accuracy within the general population. To address this, we tested multiple algorithms on 300 scans from three neuroscience research projects, funded in part by the Ontario Brain Institute, to cover a wide range of ages (3–85 years) and multiple patient cohorts. While skull stripping is more thorough at removing identifiable features, we focused mainly on defacing software, as skull stripping also removes potentially useful information, which may be required for future analyses. We tested six publicly available algorithms (afni_refacer, deepdefacer, mri_deface, mridefacer, pydeface, quickshear), with one skull stripper (FreeSurfer) included for comparison. Accuracy was measured through a pass/fail system with two criteria; one, that all facial features had been removed and two, that no brain tissue was removed in the process. A subset of defaced scans were also run through several preprocessing pipelines to ensure that none of the algorithms would alter the resulting outputs. We found that the success rates varied strongly between defacers, with afni_refacer (89%) and pydeface (83%) having the highest rates, overall. In both cases, the primary source of failure came from a single dataset that the defacer appeared to struggle with - the youngest cohort (3–20 years) for afni_refacer and the oldest (44–85 years) for pydeface, demonstrating that defacer performance not only depends on the data provided, but that this effect varies between algorithms. While there were some very minor differences between the preprocessing results for defaced and original scans, none of these were significant and were within the range of variation between using different NIfTI converters, or using raw DICOM files