Exploring the SDSS Dataset with Linked Scatter Plots: I. EMP, CEMP, and CV Stars

We present the results of a search for extremely metal-poor (EMP), carbon-enhanced metal-poor (CEMP), and cataclysmic variable (CV) stars using a new exploration tool based on linked scatter plots (LSPs). Our approach is especially designed to work with very large spectrum data sets such as the SDSS, LAMOST, RAVE, and Gaia data sets, and it can be applied to stellar, galaxy, and quasar spectra. As a demonstration, we conduct our search using the SDSS DR10 data set. We first created a 3326-dimensional phase space containing nearly 2 billion measures of the strengths of over 1600 spectral features in 569,738 SDSS stars. These measures capture essentially all the stellar atomic and molecular species visible at the resolution of SDSS spectra. We show how LSPs can be used to quickly isolate and examine interesting portions of this phase space. To illustrate, we use LSPs coupled with cuts in selected portions of phase space to extract EMP stars, CEMP stars, and CV stars. We present identifications for 59 previously unrecognized candidate EMP stars and 11 previously unrecognized candidate CEMP stars. We also call attention to 2 candidate He~II emission CV stars found by the LSP approach that have not yet been discussed in the literature.Comment: Accepted by the Astrophysical Journal Supplement (February 2017

Clinical predictors of therapeutic response to antipsychotics in schizophrenia

The search for clinical outcome predictors for schizophrenia is as old as the field of psychiatry. However, despite a wealth of large, longitudinal studies into prognostic factors, only very few clinically useful outcome predictors have been identified. The goal of future treatment is to either affect modifiable risk factors, or use nonmodifiable factors to parse patients into therapeutically meaningful subgroups. Most clinical outcome predictors are nonspecific and/or nonmodifiable. Nonmodifiable predictors for poor odds of remission include male sex, younger age at disease onset, poor premorbid adjustment, and severe baseline psychopathology. Modifiable risk factors for poor therapeutic outcomes that clinicians can act upon include longer duration of untreated illness, nonadherence to antipsychotics, comorbidities (especially substance-use disorders), lack of early antipsychotic response, and lack of improvement with non-clozapine antipsychotics, predicting clozapine response. It is hoped that this limited capacity for prediction will improve as pathophysiological understanding increases and/or new treatments for specific aspects of schizophrenia become available

Extending the Implicit Association Test (IAT): Assessing Consumer Attitudes Based on Multi-Dimensional Implicit Associations

Background: The authors present a procedural extension of the popular Implicit Association Test (IAT; [1]) that allows for indirect measurement of attitudes on multiple dimensions (e.g., safe–unsafe; young–old; innovative–conventional, etc.) rather than on a single evaluative dimension only (e.g., good–bad). Methodology/Principal Findings: In two within-subjects studies, attitudes toward three automobile brands were measured on six attribute dimensions. Emphasis was placed on evaluating the methodological appropriateness of the new procedure, providing strong evidence for its reliability, validity, and sensitivity. Conclusions/Significance: This new procedure yields detailed information on the multifaceted nature of brand associations that can add up to a more abstract overall attitude. Just as the IAT, its multi-dimensional extension/application (dubbed md-IAT) is suited for reliably measuring attitudes consumers may not be consciously aware of, able to express, or willing to share with the researcher [2,3].Product Innovation ManagementIndustrial Design Engineerin

Eigenvalues and Eigenvalue Sensitivities of a Beam Supported by Viscoelastic Solids

The eigenvalues and the first and second-order eigenvalue sensitivities of a uniform Euler-Bernoulli beam supported by the standard linear solid model for viscoelastic solids are studied in detail. A method is proposed that yields the approximate eigenvalues and allows the formulation of a frequency equation that can be used to obtain approximate eigenvalue sensitivities. The eigenvalue sensitivities are further exploited to solve for the perturbed eigenvalues due to system modifications, using both a first-and secondorder Taylor series expansion. The proposed method is easy to formulate, systematic to apply, and simple to code. Numerical experiments consisting of various beams supported by a single or multiple viscoelastic solids validated the proposed scheme and showed that the approximate eigenvalues and their sensitivities closely track the exact results

Face-space: A unifying concept in face recognition research

The concept of a multidimensional psychological space, in which faces can be represented according to their perceived properties, is fundamental to the modern theorist in face processing. Yet the idea was not clearly expressed until 1991. The background that led to the development of face-space is explained, and its continuing influence on theories of face processing is discussed. Research that has explored the properties of the face-space and sought to understand caricature, including facial adaptation paradigms, is reviewed. Face-space as a theoretical framework for understanding the effect of ethnicity and the development of face recognition is evaluated. Finally, two applications of face-space in the forensic setting are discussed. From initially being presented as a model to explain distinctiveness, inversion, and the effect of ethnicity, face-space has become a central pillar in many aspects of face processing. It is currently being developed to help us understand adaptation effects with faces. While being in principle a simple concept, face-space has shaped, and continues to shape, our understanding of face perception

Overcoming the risk of inaction from emissions uncertainty in smallholder agriculture

The potential for improving productivity and increasing the resilience of smallholder agriculture, while also contributing to climate change mitigation, has recently received considerable political attention (Beddington et al 2012). Financial support for improving smallholder agriculture could come from performance-based funding including sale of carbon credits or certified commodities, payments for ecosystem services, and nationally appropriate mitigation action (NAMA) budgets, as well as more traditional sources of development and environment finance. Monitoring the greenhouse gas fluxes associated with changes to agricultural practice is needed for performance-based mitigation funding, and efforts are underway to develop tools to quantify mitigation achieved and assess trade-offs and synergies between mitigation and other livelihood and environmental priorities (Olander 2012)

Early Galactic Evolution of Carbon, Nitrogen and Oxygen

We present results on carbon, nitrogen, and oxygen abundances for a sample of unevolved metal-poor stars with metallicities in the range -0.3< [Fe/H]< -3. Oxygen abundances derived from different indicators are compared showing consistently that in the range 0.3 >[Fe/H]>-3.0, the [O/Fe] ratio increases from approximately 0 to 1. We find a good agreement between abundances based on the forbidden line, the OH and IR triplet lines when gravities based on Hipparcos} parallaxes are considered for the sample stars. Gravities derived from LTE ionization balance in metal-poor stars with [Fe/H]< -1 are likely too low, and could be responsible for an underestimation of the oxygen abundances derived using the [OI] line. [C/Fe] and [N/Fe] ratios appear to be constant, independently of metallicity, in the same range. However, they show larger scatter than oxygen at a given metallicity, which could reflect the larger variety of stellar production sites for these other elements.Comment: 10 pages, 3 figures, To appear in the proceedings of the conference "The Chemical Evolution of The Milky Way: Stars versus Clusters", eds. F. Matteucci and F. Giovannelli, Vulcano, Italy, September 20-24 199

Spectral Irradiance Calibration in the Infrared

We present five new absolutely calibrated continuous stellar spectra constructed as far as possible from spectral fragments observed from the ground, the Kuiper Airborne Observatory (KAO), and the IRAS Low Resolution Spectrometer. These stars-alpha Boo, gamma Dra, alpha Cet, gamma Cru, and mu UMa-augment our six, published, absolutely calibrated spectra of K and early-M giants. All spectra have a common calibration pedigree. A revised composite for alpha Boo has been constructed from higher quality spectral fragments than our previously published one. The spectrum of gamma Dra was created in direct response to the needs of instruments aboard the Infrared Space Observatory (ISO); this star's location near the north ecliptic pole renders it highly visible throughout the mission. We compare all our low-resolution composite spectra with Kurucz model atmospheres and find good agreement in shape, with the obvious exception of the SiO fundamental, still lacking in current grids of model atmospheres. The CO fundamental seems slightly too deep in these models, but this could reflect our use of generic models with solar metal abundances rather than models specific to the metallicities of the individual stars. Angular diameters derived from these spectra and models are in excellent agreement with the best observed diameters. The ratio of our adopted Sirius and Vega models is vindicated by spectral observations. We compare IRAS fluxes predicted from our cool stellar spectra with those observed and conclude that, at 12 and 25 microns, flux densities measured by IRAS should be revised downwards by about 4.1% and 5.7%, respectively, for consistency with our absolute calibration. We have provided extrapolated continuum versions of these spectra to 300 microns, in direct support of ISO (PHT and LWS instruments). These spectra are consistent with IRAS flux densities at 60 and 100 microns