110 research outputs found

    Pluralism as a Bias Mitigation Strategy

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    An agnostic pluralist approaches inquiry with the assumption that it is possible for more than one account of the phenomenon in question to be correct. A monist approaches inquiry with the assumption that only one account of the phenomenon in question is correct. The purpose of my paper is to support the claim that agnostic pluralists are less susceptible to a sort of bias that I call dialectical bias than monists

    On deductivism : a critical survey of deductivism in informal logic

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    The aim of this thesis is to understand and critically evaluate deductivism as a theory of inferential sufficiency in informal logic. I distinguish three different types of deductivism: strong normative deductivism, weak normative deductivism, and reconstructive deductivism. I also discuss some potential justificatory strategies that might be invoked in an attempt to justify strong normative deductivism and reconstructive deductivism. I apply this categorization scheme to develop an interpretation of Leo Groarke\u27s version of reconstructive deductivism. I then evaluate some of the criticisms of deductivism raised in the informal logic literature. I focus in particular on the criticisms of Ralph Johnson and Trudy Govier. I follow up this evaluation by raising some problems for the justificatory strategies used to support deductivism. I also show how these problems apply to Groarke\u27s reconstructive deductivism

    Commentary On \u27Acts of Ostension\u27

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    The HST/ACS Coma Cluster Survey. II. Data Description and Source Catalogs

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    The Coma cluster was the target of a HST-ACS Treasury program designed for deep imaging in the F475W and F814W passbands. Although our survey was interrupted by the ACS instrument failure in 2007, the partially completed survey still covers ~50% of the core high-density region in Coma. Observations were performed for 25 fields that extend over a wide range of cluster-centric radii (~1.75 Mpc) with a total coverage area of 274 arcmin^2. The majority of the fields are located near the core region of Coma (19/25 pointings) with six additional fields in the south-west region of the cluster. In this paper we present reprocessed images and SExtractor source catalogs for our survey fields, including a detailed description of the methodology used for object detection and photometry, the subtraction of bright galaxies to measure faint underlying objects, and the use of simulations to assess the photometric accuracy and completeness of our catalogs. We also use simulations to perform aperture corrections for the SExtractor Kron magnitudes based only on the measured source flux and half-light radius. We have performed photometry for ~73,000 unique objects; one-half of our detections are brighter than the 10-sigma point-source detection limit at F814W=25.8 mag (AB). The slight majority of objects (60%) are unresolved or only marginally resolved by ACS. We estimate that Coma members are 5-10% of all source detections, which consist of a large population of unresolved objects (primarily GCs but also UCDs) and a wide variety of extended galaxies from a cD galaxy to dwarf LSB galaxies. The red sequence of Coma member galaxies has a constant slope and dispersion across 9 magnitudes (-21<M_F814W<-13). The initial data release for the HST-ACS Coma Treasury program was made available to the public in 2008 August. The images and catalogs described in this study relate to our second data release.Comment: Accepted for publication in ApJS. A high-resolution version is available at http://archdev.stsci.edu/pub/hlsp/coma/release2/PaperII.pd

    Airships: A New Horizon for Science

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    The "Airships: A New Horizon for Science" study at the Keck Institute for Space Studies investigated the potential of a variety of airships currently operable or under development to serve as observatories and science instrumentation platforms for a range of space, atmospheric, and Earth science. The participants represent a diverse cross-section of the aerospace sector, NASA, and academia. Over the last two decades, there has been wide interest in developing a high altitude, stratospheric lighter-than-air (LTA) airship that could maneuver and remain in a desired geographic position (i.e., "station-keeping") for weeks, months or even years. Our study found considerable scientific value in both low altitude (< 40 kft) and high altitude (> 60 kft) airships across a wide spectrum of space, atmospheric, and Earth science programs. Over the course of the study period, we identified stratospheric tethered aerostats as a viable alternative to airships where station-keeping was valued over maneuverability. By opening up the sky and Earth's stratospheric horizon in affordable ways with long-term flexibility, airships allow us to push technology and science forward in a project-rich environment that complements existing space observatories as well as aircraft and high-altitude balloon missions.Comment: This low resolution version of the report is 8.6 MB. For the high resolution version see: http://kiss.caltech.edu/study/airship

    Novel Associations between Common Breast Cancer Susceptibility Variants and Risk-Predicting Mammographic Density Measures.

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    Mammographic density measures adjusted for age and body mass index (BMI) are heritable predictors of breast cancer risk, but few mammographic density-associated genetic variants have been identified. Using data for 10,727 women from two international consortia, we estimated associations between 77 common breast cancer susceptibility variants and absolute dense area, percent dense area and absolute nondense area adjusted for study, age, and BMI using mixed linear modeling. We found strong support for established associations between rs10995190 (in the region of ZNF365), rs2046210 (ESR1), and rs3817198 (LSP1) and adjusted absolute and percent dense areas (all P < 10(-5)). Of 41 recently discovered breast cancer susceptibility variants, associations were found between rs1432679 (EBF1), rs17817449 (MIR1972-2: FTO), rs12710696 (2p24.1), and rs3757318 (ESR1) and adjusted absolute and percent dense areas, respectively. There were associations between rs6001930 (MKL1) and both adjusted absolute dense and nondense areas, and between rs17356907 (NTN4) and adjusted absolute nondense area. Trends in all but two associations were consistent with those for breast cancer risk. Results suggested that 18% of breast cancer susceptibility variants were associated with at least one mammographic density measure. Genetic variants at multiple loci were associated with both breast cancer risk and the mammographic density measures. Further understanding of the underlying mechanisms at these loci could help identify etiologic pathways implicated in how mammographic density predicts breast cancer risk.ABCFS: The Australian Breast Cancer Family Registry (ABCFR; 1992-1995) was supported by the Australian NHMRC, the New South Wales Cancer Council, and the Victorian Health Promotion Foundation (Australia), and by grant UM1CA164920 from the USA National Cancer Institute. The Genetic Epidemiology Laboratory at the University of Melbourne has also received generous support from Mr B. Hovey and Dr and Mrs R.W. Brown to whom we are most grateful. The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Breast Cancer Susceptibility Variants and Mammographic Density 5 Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the USA Government or the BCFR. BBCC: This study was funded in part by the ELAN-Program of the University Hospital Erlangen; Katharina Heusinger was funded by the ELAN program of the University Hospital Erlangen. BBCC was supported in part by the ELAN program of the Medical Faculty, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg. EPIC-Norfolk: This study was funded by research programme grant funding from Cancer Research UK and the Medical Research Council with additional support from the Stroke Association, British Heart Foundation, Department of Health, Research into Ageing and Academy of Medical Sciences. MCBCS: This study was supported by Public Health Service Grants P50 CA 116201, R01 CA 128931, R01 CA 128931-S01, R01 CA 122340, CCSG P30 CA15083, from the National Cancer Institute, National Institutes of Health, and Department of Health and Human Services. MCCS: Melissa C. Southey is a National Health and Medical Research Council Senior Research Fellow and a Victorian Breast Cancer Research Consortium Group Leader. The study was supported by the Cancer Council of Victoria and by the Victorian Breast Cancer Research Consortium. MEC: National Cancer Institute: R37CA054281, R01CA063464, R01CA085265, R25CA090956, R01CA132839. MMHS: This work was supported by grants from the National Cancer Institute, National Institutes of Health, and Department of Health and Human Services. (R01 CA128931, R01 CA 128931-S01, R01 CA97396, P50 CA116201, and Cancer Center Support Grant P30 CA15083). Breast Cancer Susceptibility Variants and Mammographic Density 6 NBCS: This study has been supported with grants from Norwegian Research Council (#183621/S10 and #175240/S10), The Norwegian Cancer Society (PK80108002, PK60287003), and The Radium Hospital Foundation as well as S-02036 from South Eastern Norway Regional Health Authority. NHS: This study was supported by Public Health Service Grants CA131332, CA087969, CA089393, CA049449, CA98233, CA128931, CA 116201, CA 122340 from the National Cancer Institute, National Institutes of Health, Department of Health and Human Services. OOA study was supported by CA122822 and X01 HG005954 from the NIH; Breast Cancer Research Fund; Elizabeth C. Crosby Research Award, Gladys E. Davis Endowed Fund, and the Office of the Vice President for Research at the University of Michigan. Genotyping services for the OOA study were provided by the Center for Inherited Disease Research (CIDR), which is fully funded through a federal contract from the National Institutes of Health to The Johns Hopkins University, contract number HHSN268200782096. OFBCR: This work was supported by grant UM1 CA164920 from the USA National Cancer Institute. The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the USA Government or the BCFR. SASBAC: The SASBAC study was supported by Märit and Hans Rausing’s Initiative against Breast Cancer, National Institutes of Health, Susan Komen Foundation and Agency for Science, Technology and Research of Singapore (A*STAR). Breast Cancer Susceptibility Variants and Mammographic Density 7 SIBS: SIBS was supported by program grant C1287/A10118 and project grants from Cancer Research UK (grant numbers C1287/8459). COGS grant: Collaborative Oncological Gene-environment Study (COGS) that enabled the genotyping for this study. Funding for the BCAC component is provided by grants from the EU FP7 programme (COGS) and from Cancer Research UK. Funding for the iCOGS infrastructure came from: the European Community's Seventh Framework Programme under grant agreement n° 223175 (HEALTH-F2-2009-223175) (COGS), Cancer Research UK (C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692), the National Institutes of Health (CA128978) and Post- Cancer GWAS initiative (1U19 CA148537, 1U19 CA148065 and 1U19 CA148112 - the GAMEON initiative), the Department of Defence (W81XWH-10-1-0341), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer, Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund.This is the author accepted manuscript. The final version is available via American Association for Cancer Research at http://cancerres.aacrjournals.org/content/early/2015/04/10/0008-5472.CAN-14-2012.abstract

    Measurements of the leptonic branching fractions of the τ\tau

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    Data collected with the DELPHI detector from 1993 to 1995 combined with previous DELPHI results for data from 1991 and 1992 yield the branching fractions B({\tau \rightarrow \mbox{\rm e} \nu \bar{\nu}}) = (17.877 \pm 0.109_{stat} \pm 0.110_{sys} )\% and B(τμννˉ)=(17.325±0.095stat±0.077sys)%B({\tau \rightarrow \mu \nu \bar{\nu}}) = (17.325 \pm 0.095_{stat} \pm 0.077_{sys} )\%

    Search for scalar fermions and long-lived scalar leptons at centre-of-mass energies of 130 GeV to 172 GeV

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    Data taken by DELPHI during the 1995 and 1996 LEP runs have been used to search for the supersymmetric partners of electron, muon and tau leptons and of top and bottom quarks. The observations are in agreement with standard model predictions. Limits are set on sfermion masses. Searches for long lived scalar leptons from low scale supersymmetry breaking models exclude stau masses below 55~GeV/c2^2 at the 95\% confidence level, irrespective of the gravitino mass

    Measurement of the gluon fragmentation function and a comparison of the scaling violation in gluon and quark jets

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    Global, regional, and national levels of maternal mortality, 1990-2015 : a systematic analysis for the Global Burden of Disease Study 2015

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    Background In transitioning from the Millennium Development Goal to the Sustainable Development Goal era, it is imperative to comprehensively assess progress toward reducing maternal mortality to identify areas of success, remaining challenges, and frame policy discussions. We aimed to quantify maternal mortality throughout the world by underlying cause and age from 1990 to 2015. Methods We estimated maternal mortality at the global, regional, and national levels from 1990 to 2015 for ages 10-54 years by systematically compiling and processing all available data sources from 186 of 195 countries and territories, 11 of which were analysed at the subnational level. We quantified eight underlying causes of maternal death and four timing categories, improving estimation methods since GBD 2013 for adult all-cause mortality, HIV-related maternal mortality, and late maternal death. Secondary analyses then allowed systematic examination of drivers of trends, including the relation between maternal mortality and coverage of specific reproductive health-care services as well as assessment of observed versus expected maternal mortality as a function of Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Findings Only ten countries achieved MDG 5, but 122 of 195 countries have already met SDG 3.1. Geographical disparities widened between 1990 and 2015 and, in 2015, 24 countries still had a maternal mortality ratio greater than 400. The proportion of all maternal deaths occurring in the bottom two SDI quintiles, where haemorrhage is the dominant cause of maternal death, increased from roughly 68% in 1990 to more than 80% in 2015. The middle SDI quintile improved the most from 1990 to 2015, but also has the most complicated causal profile. Maternal mortality in the highest SDI quintile is mostly due to other direct maternal disorders, indirect maternal disorders, and abortion, ectopic pregnancy, and/or miscarriage. Historical patterns suggest achievement of SDG 3.1 will require 91% coverage of one antenatal care visit, 78% of four antenatal care visits, 81% of in-facility delivery, and 87% of skilled birth attendance. Interpretation Several challenges to improving reproductive health lie ahead in the SDG era. Countries should establish or renew systems for collection and timely dissemination of health data; expand coverage and improve quality of family planning services, including access to contraception and safe abortion to address high adolescent fertility; invest in improving health system capacity, including coverage of routine reproductive health care and of more advanced obstetric care-including EmOC; adapt health systems and data collection systems to monitor and reverse the increase in indirect, other direct, and late maternal deaths, especially in high SDI locations; and examine their own performance with respect to their SDI level, using that information to formulate strategies to improve performance and ensure optimum reproductive health of their population.Peer reviewe
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