56 research outputs found

    Multivariate Analyses of Spatiotemporal Water Quality Patterns of Back Bay, Virginia

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    An investigation employing multivariate statistical techniques was conducted to determine major spatiotemporal patterns in water quality in Back Bay, Virginia. Water quality data collected by the Virginia Water Control Board (VWCB) over the past two decades and recent data collected by the Department of Game and Inland Fisheries and the Back Bay Restoration Foundation were consolidated for statistical analysis. Unfortunately, lack of continuity in sampling regimes prevented the use of many of the site/date/variable combinations in the statistical analyses. Nonetheless, a number of water quality patterns were characterized. Long-term trends could be evaluated for a relatively few parameters (NO2, NH3, TKN, conductivity, DO, and pH) for which an adequate data base existed. Trend analysis of a 16-year data base for Hell Point Creek indicated a significant decrease in ammonia concentrations (-0.011 mg 1-1 yr-1) , possibly related to changes in land use activities in the region. The TKN concentrations in the Bay almost doubled between the 1970\u27s and 1980\u27s (from 1.14 mg/1 to 1.97 mg/1). Indicators of eutrophication such as high daytime dissolved oxygen and pH measurements qualitatively appeared to decrease between 1970\u27s and 1980\u27s throughout the Bay, but lack of spatial and/or temporal continuity in the data sets prevented direct statistical comparisons. Distinct seasonal patterns were characterized: summer conditions were characterized by high temperatures but lower suspended solids load and nutrient concentrations, while the converse was true for winter months. Spring and fall collection periods were intermediate in these characteristics but displayed elevated volatile suspended solids and depressed phosphorus concentrations, possibly due to seasonal phytoplankton blooms. Overall spatial patterns indicated the tributary creeks appeared to be source areas for elevated nitrogen and phosphorus based nutrients, while the main Bay was characterized by a high organic-rich suspended solids load. The tributary of greatest concern was Nawney Creek, which displayed elevated nutrient concentrations and appeared to influence water quality in the proximate Bay region. In summary, two major problems appear to be associated with water quality conditions in Back Bay: elevated levels of nitrogen and phosphorus based nutrient in the tributary creeks and a high suspended solids load of organic-rich particles in the Bay. The full ecological significance of these conditions cannot be determined by the present study. However, consistent and comprehensive monitoring of water quality conditions, such as has been implemented in recent years, should permit observation of long-term trends in environmental conditions in various portions of the Bay. Only in this way can the success of any management or restoration actions be judged

    The James Webb Space Telescope Mission: Optical Telescope Element Design, Development, and Performance

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    The James Webb Space Telescope (JWST) is a large, infrared space telescope that has recently started its science program which will enable breakthroughs in astrophysics and planetary science. Notably, JWST will provide the very first observations of the earliest luminous objects in the Universe and start a new era of exoplanet atmospheric characterization. This transformative science is enabled by a 6.6 m telescope that is passively cooled with a 5-layer sunshield. The primary mirror is comprised of 18 controllable, low areal density hexagonal segments, that were aligned and phased relative to each other in orbit using innovative image-based wavefront sensing and control algorithms. This revolutionary telescope took more than two decades to develop with a widely distributed team across engineering disciplines. We present an overview of the telescope requirements, architecture, development, superb on-orbit performance, and lessons learned. JWST successfully demonstrates a segmented aperture space telescope and establishes a path to building even larger space telescopes.Comment: accepted by PASP for JWST Overview Special Issue; 34 pages, 25 figure

    Analysis of shared heritability in common disorders of the brain

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    ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

    Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

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    Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyper-activity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.Peer reviewe

    Search for single production of vector-like quarks decaying into Wb in pp collisions at s=8\sqrt{s} = 8 TeV with the ATLAS detector

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    Measurements of top-quark pair differential cross-sections in the eμe\mu channel in pppp collisions at s=13\sqrt{s} = 13 TeV using the ATLAS detector

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    Measurement of the W boson polarisation in ttˉt\bar{t} events from pp collisions at s\sqrt{s} = 8 TeV in the lepton + jets channel with ATLAS

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    Charged-particle distributions at low transverse momentum in s=13\sqrt{s} = 13 TeV pppp interactions measured with the ATLAS detector at the LHC

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    Measurement of the bbb\overline{b} dijet cross section in pp collisions at s=7\sqrt{s} = 7 TeV with the ATLAS detector

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