Prison as Seen by Convict Criminologists

Most criminologists tend to base their view of prison on ideological assumptions gathered from secondary sources, with at best limited entry to the prison world. They nearly always get it wrong, as they systematically exclude the perspectives and real life experiences of their human subjects. These academic researchers have contributed to poor public policy that promotes the violent repression of prisoners in the USA and other countries. In response, Convict Criminologists are ex‐convicts working as criminology and criminal justice professors, along with “non‐con” associates, that insist that as a means for societies to develop humane, effective, and cost efficient prisons, we must develop ways to incorporate the voice of prisoners in our theorizing about, policy recommendations for, and management of the prison

Using Whole-Genome Sequence Data to Predict Quantitative Trait Phenotypes in Drosophila melanogaster

Predicting organismal phenotypes from genotype data is important for plant and animal breeding, medicine, and evolutionary biology. Genomic-based phenotype prediction has been applied for single-nucleotide polymorphism (SNP) genotyping platforms, but not using complete genome sequences. Here, we report genomic prediction for starvation stress resistance and startle response in Drosophila melanogaster, using ∼2.5 million SNPs determined by sequencing the Drosophila Genetic Reference Panel population of inbred lines. We constructed a genomic relationship matrix from the SNP data and used it in a genomic best linear unbiased prediction (GBLUP) model. We assessed predictive ability as the correlation between predicted genetic values and observed phenotypes by cross-validation, and found a predictive ability of 0.239±0.008 (0.230±0.012) for starvation resistance (startle response). The predictive ability of BayesB, a Bayesian method with internal SNP selection, was not greater than GBLUP. Selection of the 5% SNPs with either the highest absolute effect or variance explained did not improve predictive ability. Predictive ability decreased only when fewer than 150,000 SNPs were used to construct the genomic relationship matrix. We hypothesize that predictive power in this population stems from the SNP–based modeling of the subtle relationship structure caused by long-range linkage disequilibrium and not from population structure or SNPs in linkage disequilibrium with causal variants. We discuss the implications of these results for genomic prediction in other organisms

Using Whole-Genome Sequence Data to Predict Quantitative Trait Phenotypes in Drosophila melanogaster

Predicting organismal phenotypes from genotype data is important for plant and animal breeding, medicine, and evolutionary biology. Genomic-based phenotype prediction has been applied for single-nucleotide polymorphism (SNP) genotyping platforms, but not using complete genome sequences. Here, we report genomic prediction for starvation stress resistance and startle response in Drosophila melanogaster, using ∼2.5 million SNPs determined by sequencing the Drosophila Genetic Reference Panel population of inbred lines. We constructed a genomic relationship matrix from the SNP data and used it in a genomic best linear unbiased prediction (GBLUP) model. We assessed predictive ability as the correlation between predicted genetic values and observed phenotypes by cross-validation, and found a predictive ability of 0.239±0.008 (0.230±0.012) for starvation resistance (startle response). The predictive ability of BayesB, a Bayesian method with internal SNP selection, was not greater than GBLUP. Selection of the 5% SNPs with either the highest absolute effect or variance explained did not improve predictive ability. Predictive ability decreased only when fewer than 150,000 SNPs were used to construct the genomic relationship matrix. We hypothesize that predictive power in this population stems from the SNP–based modeling of the subtle relationship structure caused by long-range linkage disequilibrium and not from population structure or SNPs in linkage disequilibrium with causal variants. We discuss the implications of these results for genomic prediction in other organisms

The Sloan Digital Sky Survey Quasar Catalog V. Seventh Data Release

We present the fifth edition of the Sloan Digital Sky Survey (SDSS) Quasar Catalog, which is based upon the SDSS Seventh Data Release. The catalog, which contains 105,783 spectroscopically confirmed quasars, represents the conclusion of the SDSS-I and SDSS-II quasar survey. The catalog consists of the SDSS objects that have luminosities larger than M_i = -22.0 (in a cosmology with H_0 = 70 km/s/Mpc Omega_M = 0.3, and Omega_Lambda = 0.7) have at least one emission line with FWHM larger than 1000 km/s or have interesting/complex absorption features, are fainter than i > 15.0 and have highly reliable redshifts. The catalog covers an area of 9380 deg^2. The quasar redshifts range from 0.065 to 5.46, with a median value of 1.49; the catalog includes 1248 quasars at redshifts greater than four, of which 56 are at redshifts greater than five. The catalog contains 9210 quasars with i < 18; slightly over half of the entries have i< 19. For each object the catalog presents positions accurate to better than 0.1" rms per coordinate, five-band (ugriz) CCD-based photometry with typical accuracy of 0.03 mag, and information on the morphology and selection method. The catalog also contains radio, near-infrared, and X-ray emission properties of the quasars, when available, from other large-area surveys. The calibrated digital spectra cover the wavelength region 3800-9200 Ang. at a spectral resolution R = 2000 the spectra can be retrieved from the SDSS public database using the information provided in the catalog. Over 96% of the objects in the catalog were discovered by the SDSS. We also include a supplemental list of an additional 207 quasars with SDSS spectra whose archive photometric information is incomplete.Comment: Accepted, to appear in AJ, 7 figures, electronic version of Table 2 is available, see http://www.sdss.org/dr7/products/value_added/qsocat_dr7.htm

Spectroscopic Target Selection in the Sloan Digital Sky Survey: The Quasar Sample

We describe the algorithm for selecting quasar candidates for optical spectroscopy in the Sloan Digital Sky Survey. Quasar candidates are selected via their non-stellar colors in "ugriz" broad-band photometry, and by matching unresolved sources to the FIRST radio catalogs. The automated algorithm is sensitive to quasars at all redshifts lower than z=5.8. Extended sources are also targeted as low-redshift quasar candidates in order to investigate the evolution of Active Galactic Nuclei (AGN) at the faint end of the luminosity function. Nearly 95% of previously known quasars are recovered (based on 1540 quasars in 446 square degrees). The overall completeness, estimated from simulated quasars, is expected to be over 90%, whereas the overall efficiency (quasars:quasar candidates) is better than 65%. The selection algorithm targets ultraviolet excess quasars to i^*=19.1 and higher-redshift (z>3) quasars to i^*=20.2, yielding approximately 18 candidates per square degree. In addition to selecting ``normal'' quasars, the design of the algorithm makes it sensitive to atypical AGN such as Broad Absorption Line quasars and heavily reddened quasars.Comment: 62 pages, 15 figures (8 color), 8 tables. Accepted by AJ. For a version with higher quality color figures, see http://archive.stsci.edu/sdss/quasartarget/RichardsGT_qsotarget.preprint.p

Lewy Body Dementia Association\u27s Research Centers of Excellence Program: Inaugural Meeting Proceedings.

The first Lewy Body Dementia Association (LBDA) Research Centers of Excellence (RCOE) Investigator\u27s meeting was held on December 14, 2017, in New Orleans. The program was established to increase patient access to clinical experts on Lewy body dementia (LBD), which includes dementia with Lewy bodies (DLB) and Parkinson\u27s disease dementia (PDD), and to create a clinical trials-ready network. Four working groups (WG) were created to pursue the LBDA RCOE aims: (1) increase access to high-quality clinical care, (2) increase access to support for people living with LBD and their caregivers, (3) increase knowledge of LBD among medical and allied (or other) professionals, and (4) create infrastructure for a clinical trials-ready network as well as resources to advance the study of new therapeutics

Colors of 2625 Quasars at 0<z<5 Measured in the Sloan Digital Sky Survey Photometric System

We present an empirical investigation of the colors of quasars in the Sloan Digital Sky Survey (SDSS) photometric system. The sample studied includes 2625 quasars with SDSS photometry. The quasars are distributed in a 2.5 degree wide stripe centered on the Celestial Equator covering $\sim529$ square degrees. Positions and SDSS magnitudes are given for the 898 quasars known prior to SDSS spectroscopic commissioning. New SDSS quasars represent an increase of over 200% in the number of known quasars in this area of the sky. The ensemble average of the observed colors of quasars in the SDSS passbands are well represented by a power-law continuum with $\alpha_{\nu} = -0.5$ ($f_{\nu} \propto \nu^{\alpha}$). However, the contributions of the $3000 {\rm \AA}$ bump and other strong emission lines have a significant effect upon the colors. The color-redshift relation exhibits considerable structure, which may be of use in determining photometric redshifts for quasars. The range of colors can be accounted for by a range in the optical spectral index with a distribution $\alpha_{\nu}=-0.5\pm0.65$ (95% confidence), but there is a red tail in the distribution. This tail may be a sign of internal reddening. Finally, we show that there is a continuum of properties between quasars and Seyfert galaxies and we test the validity of the traditional division between the two classes of AGN.Comment: 66 pages, 15 figures (3 color), accepted by A