Culture and Psychiatric Evaluation: Operationalizing Cultural Formulation for DSM-5

The Outline for Cultural Formulation (OCF) introduced with DSM-IV provided a framework for clinicians to organize cultural information relevant to diagnostic assessment and treatment planning. However, use of the OCF has been inconsistent, raising questions about the need for guidance on implementation, training, and application in diverse settings. To address this need, DSM-5 introduced a cultural formulation interview (CFI) that operationalizes the process of data collection for the OCF. The CFI includes patient and informant versions and 12 supplementary modules addressing specific domains of the OCF. This article summarizes the literature reviews and analyses of experience with the OCF conducted by the DSM-5 Cross-Cultural Issues Subgroup (DCCIS) that informed the development of the CFI. We review the history and contents of the DSM-IV OCF, its use in training programs, and previous attempts to render it operational through questionnaires, protocols, and semi-structured interview formats. Results of research based on the OCF are discussed. For each domain of the OCF, we summarize findings from the DCCIS that led to content revision and operationalization in the CFI. The conclusion discusses training and implementation issues essential to service delivery

The PAU Survey: Photometric redshifts using transfer learning from simulations

In this paper we introduce the \textsc{Deepz} deep learning photometric redshift (photo-$z$) code. As a test case, we apply the code to the PAU survey (PAUS) data in the COSMOS field. \textsc{Deepz} reduces the $\sigma_{68}$ scatter statistic by 50\% at $i_{\rm AB}=22.5$ compared to existing algorithms. This improvement is achieved through various methods, including transfer learning from simulations where the training set consists of simulations as well as observations, which reduces the need for training data. The redshift probability distribution is estimated with a mixture density network (MDN), which produces accurate redshift distributions. Our code includes an autoencoder to reduce noise and extract features from the galaxy SEDs. It also benefits from combining multiple networks, which lowers the photo-$z$ scatter by 10 percent. Furthermore, training with randomly constructed coadded fluxes adds information about individual exposures, reducing the impact of photometric outliers. In addition to opening up the route for higher redshift precision with narrow bands, these machine learning techniques can also be valuable for broad-band surveys.Comment: Accepted versio

1873-1874, End of a Century?: Time and Space in Valera's Pepita Jiménez, Ros de Olano's Jornadas de retorno, and Alarcón's El sombrero de tres picos and La Alpujarra

This article argues for the existence of a literature of the first Spanish Republic in the early 1870s. Valera's Pepita Jimenez makes sense in relation to this literature, rather than in comparison with 'Realism'. The literature of the first republic is distinguished by two facets: an ongoing dialogue with Ros de Olano's experiments in simultaneous compression and extension of form; and a belief that the nineteenth-century revolutionary spirit of the age has reached a critical end point, and needs reinvention that leads to Restoration politics

The Physics of the Accelerating Universe Survey: narrow-band image photometry

PAUCam is an innovative optical narrow-band imager mounted at the William Herschel Telescope built for the Physics of the Accelerating Universe Survey (PAUS). Its set of 40 filters results in images that are complex to calibrate, with specific instrumental signatures that cannot be processed with traditional data reduction techniques. In this paper, we present two pipelines developed by the PAUS data management team with the objective of producing science-ready catalogues from the uncalibrated raw images. The NIGHTLY pipeline takes care of entire image processing, with bespoke algorithms for photometric calibration and scatter-light correction. The Multi-Epoch and Multi-Band Analysis pipeline performs forced photometry over a reference catalogue to optimize the photometric redshift (photo-z) performance. We verify against spectroscopic observations that the current approach delivers an inter-band photometric calibration of 0.8 per cent across the 40 narrow-band set. The large volume of data produced every night and the rapid survey strategy feedback constraints require operating both pipelines in the Port d’Informació Cientifica data centre with intense parallelization. While alternative algorithms for further improvements in photo-z performance are under investigation, the image calibration and photometry presented in this work already enable state-of-the-art photo-z down to iAB = 23.0

The PAU Survey: Narrow-band image photometry

PAUCam is an innovative optical narrow-band imager mounted at the William Herschel Telescope built for the Physics of the Accelerating Universe Survey (PAUS). Its set of 40 filters results in images that are complex to calibrate, with specific instrumental signatures that cannot be processed with traditional data reduction techniques. In this paper we present two pipelines developed by the PAUS data management team with the objective of producing science-ready catalogues from the uncalibrated raw images. The Nightly pipeline takes care of all image processing, with bespoke algorithms for photometric calibration and scatter-light correction. The Multi-Epoch and Multi-Band Analysis (MEMBA) pipeline performs forced photometry over a reference catalogue to optimize the photometric redshift performance. We verify against spectroscopic observations that the current approach delivers an inter-band photometric calibration of 0.8% across the 40 narrow-band set. The large volume of data produced every night and the rapid survey strategy feedback constraints require operating both pipelines in the Port d'Informaci\'o Cientifica data centre with intense parallelization. While alternative algorithms for further improvements in photo-z performance are under investigation, the image calibration and photometry presented in this work already enable state-of-the-art photometric redshifts down to iAB=23.0.Comment: 32 pages, 26 figures, MNRAS in pres

Interleukin 6 Dependence of Anti-DNA Antibody Production: Evidence for Two Pathways of Autoantibody Formation in Pristane-induced Lupus

Pristane induces a lupus-like syndrome in nonautoimmune mice characterized by the development of glomerulonephritis and lupus-associated autoantibodies. This is accompanied by overproduction of interleukin (IL)-6, a cytokine linked with autoimmune phenomena. The goal of this study was to evaluate the role of IL-6 in autoantibody production in pristane-induced lupus. BALB/cAn IL-6–deficient (−/−) and –intact (+/+) mice were treated with pristane or phosphate-buffered saline, and autoantibody production was evaluated. Pristane induced high levels of immunoglobulin (Ig)G anti-single-stranded DNA, –double-stranded (ds)DNA, and -chromatin antibodies in IL-6+/+, but not IL-6−/− mice by enzyme-linked immunosorbent assay. High titer IgG anti-dsDNA antibodies also were detected in sera from +/+, but not −/−, mice by Crithidia luciliae kinetoplast staining. The onset of IgG anti-dsDNA antibody production in +/+ mice occurred >5 mo after pristane treatment, well after the onset of nephritis, suggesting that these antibodies are not directly responsible for inducing renal disease. In contrast to anti-DNA, the frequencies of anti-nRNP/Sm and anti-Su antibodies were similar in pristane-treated IL-6−/− and IL-6+/+ mice. However, levels were higher in the +/+ group. These results suggest that IgG anti-DNA and chromatin antibodies in pristane-treated mice are strictly IL-6 dependent, whereas induction of anti-nRNP/Sm and Su autoantibodies is IL-6 independent. The IL-6 dependence of anti-DNA, but not anti-nRNP/Sm, may have implications for understanding the patterns of autoantibody production in lupus. Anti-DNA antibodies are produced transiently, mainly during periods of disease activity, whereas anti-nRNP/Sm antibody levels are relatively insensitive to disease activity. This may reflect the differential IL-6 dependence of the two responses

Dark Energy Survey year 1 results: galaxy sample for BAO measurement

FINEP - FINANCIADORA DE ESTUDOS E PROJETOSFAPERJ - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DO RIO DE JANEIROCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOMCTIC - MINISTÉRIO DA CIÊNCIA, TECNOLOGIA, INOVAÇÕES E COMUNICAÇÕESWe define and characterize a sample of 1.3million galaxies extracted from the first year of Dark Energy Survey data, optimized to measure baryon acoustic oscillations (BAO) in the presence of significant redshift uncertainties. The sample is dominated by luminous red galaxies located at redshifts z greater than or similar to 0.6. We define the exact selection using colour and magnitude cuts that balance the need of high number densities and small photometric redshift uncertainties, using the corresponding forecasted BAO distance error as a figure-of-merit in the process. The typical photo z uncertainty varies from 2.3 per cent to 3.6 per cent (in units of 1+z) from z = 0.6 to 1, with number densities from 200 to 130 galaxies per deg(2) in tomographic bins of width Delta z = 0.1. Next, we summarize the validation of the photometric redshift estimation. We characterize and mitigate observational systematics including stellar contamination and show that the clustering on large scales is robust in front of those contaminants. We show that the clustering signal in the autocorrelations and cross-correlations is generally consistent with theoretical models, which serve as an additional test of the redshift distributions.482228072822FINEP - FINANCIADORA DE ESTUDOS E PROJETOSFAPERJ - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DO RIO DE JANEIROCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOMCTIC - MINISTÉRIO DA CIÊNCIA, TECNOLOGIA, INOVAÇÕES E COMUNICAÇÕESFINEP - FINANCIADORA DE ESTUDOS E PROJETOSFAPERJ - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DO RIO DE JANEIROCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOMCTIC - MINISTÉRIO DA CIÊNCIA, TECNOLOGIA, INOVAÇÕES E COMUNICAÇÕESSem informaçãoSem informaçãoSem informaçãoSem informaçãoMC acknowledges support from the Spanish Ramon y Cajal MICINN program. MC and EG have been partially funded by AYA2015-71825. AJR is grateful for support from the Ohio State University Center for Cosmology and AstroParticle Physics. KCC acknowledges the support from the Spanish Ministerio de Economia y Competitividad grant ESP2013-48274-C3-1-P and the Juan de la Cierva fellowship. This work has used CosmoHub, see Carretero et al. (2017). CosmoHub has been developed by the Port d'Informacio Cientifica (PIC), maintained through a collaboration of the Institut de Fisica d'Altes Energies (IFAE) and the Centro de Investigaciones Energeticas, Medioambientales y Tecnologicas (CIEMAT) and was partially funded by the 'Plan Estatal de Investigacion Cientfica y Tecnica y de Innovacion' program of the Spanish government. Funding for the DES Projects has been provided by the U.S. Department of Energy, the U.S. National Science Foundation, the Ministry of Science and Education of Spain, the Science and Technology Facilities Council of the United Kingdom, the Higher Education Funding Council for England, the National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign, the Kavli Institute of Cosmological Physics at the University of Chicago, the Center for Cosmology and Astro-Particle Physics at the Ohio State University, the Mitchell Institute for Fundamental Physics and Astronomy at Texas A&M University, (0:funding-source) FINEP - FINANCIADORA DE ESTUDOS E PROJETOS (0: funding-source), Fundacao Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro, Conselho Nacional de Desenvolvimento Cientifico e Tecnologico and the Ministerio da Ciencia, Tecnologia e Inovacao, the Deutsche Forschungsgemeinschaft, and the Collaborating Institutions in the DES. The Collaborating Institutions are Argonne National Laboratory, the University of California at Santa Cruz, the University of Cambridge, Centro de Investigaciones Energeticas, Medioambientales y Tecnologicas-Madrid, the University of Chicago, University College London, the DES-Brazil Consortium, the University of Edinburgh, the Eidgenossische Technische Hochschule (ETH) Zurich, Fermi National Accelerator Laboratory, the University of Illinois at Urbana-Champaign, the Institut de Ciencies de l'Espai (IEEC/CSIC), the Institut de Fisica d'Altes Energies, Lawrence Berkeley National Laboratory, the Ludwig-Maximilians Universitat Munchen and the associated Excellence Cluster Universe, the University of Michigan, the National Optical Astronomy Observatory, the University of Nottingham, The Ohio State University, the University of Pennsylvania, the University of Portsmouth, SLAC National Accelerator Laboratory, Stanford University, the University of Sussex, Texas A&M University, and the OzDES Membership Consortium. The DESDM is supported by the National Science Foundation under Grant Numbers AST-1138766 and AST-1536171. The DES participants from Spanish institutions are partially supported by MINECO under grants AYA2015-71825, ESP2015-66861, FPA2015-68048, SEV-2016-0588, SEV-2016-0597, and MDM-2015-0509, some of which include ERDF funds from the European Union. IFAE is partially funded by the CERCA program of the Generalitat de Catalunya. Research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Program (FP7/2007-2013) including ERC grant agreements 240672, 291329, and 306478. We acknowledge support from the Australian Research Council Centre of Excellence for All-sky Astrophysics (CAASTRO), through project number CE110001020. This manuscript has been authored by Fermi Research Alliance, LLC under Contract No. DE-AC02-07CH11359 with the U.S. Department of Energy, Office of Science, and Office of High Energy Physics. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes

Dark energy survey year 1 results: Redshift distributions of the weak-lensing source galaxies

We describe the derivation and validation of redshift distribution estimates and their uncertainties for the populations of galaxies used as weak-lensing sources in the Dark Energy Survey (DES) Year 1 cosmological analyses. The Bayesian Photometric Redshift (BPZ) code is used to assign galaxies to four redshift bins between z ≈ 0.2 and ≈1.3, and to produce initial estimates of the lensing-weighted redshift distributions nPZi(z) ∝ dni/dz for members of bin i. Accurate determination of cosmological parameters depends critically on knowledge of ni, but is insensitive to bin assignments or redshift errors for individual galaxies. The cosmological analyses allow for shifts ni (z) = nPZi(z - Δzi) to correct themean redshift of ni(z) for biases in nPZi. The Δzi are constrained by comparison of independently estimated 30-band photometric redshifts of galaxies in the Cosmic Evolution Survey (COSMOS) field to BPZ estimates made from the DES griz fluxes, for a sample matched in fluxes, pre-seeing size, and lensing weight to the DES weak-lensing sources. In companion papers, the Δzi of the three lowest redshift bins are further constrained by the angular clustering of the source galaxies around red galaxies with secure photometric redshifts at 0.15 < z < 0.9. This paper details the BPZ and COSMOS procedures, and demonstrates that the cosmological inference is insensitive to details of the ni(z) beyond the choice of Δzi. The clustering and COSMOS validation methods produce consistent estimates of Δzi in the bins where both can be applied, with combined uncertainties of σΔzi = 0.015, 0.013, 0.011, and 0.022 in the four bins. Repeating the photo-z procedure instead using the Directional Neighbourhood Fitting algorithm, or using the ni(z) estimated from the matched sample in COSMOS, yields no discernible difference in cosmological inferences