104 research outputs found
W49A North - Global or Local or No Collapse?
We attempt to fit observations with 5" resolution of the J=2-1 transition of
CS in the directions of H II regions A, B, and G of W49A North as well as
observations with 20" resolution of the J=2-1, 3-2, 5-4, and 7-6 transitions in
the directions of H II regions A and G by using radiative transfer
calculations. These calculations predict the intensity profiles resulting from
several spherical clouds along the line of sight. We consider three models:
global collapse of a very large (5 pc radius) cloud, localized collapse from
smaller (1 pc) clouds around individual H II regions, and multiple, static
clouds. For all three models we can find combinations of parameters that
reproduce the CS profiles reasonably well provided that the component clouds
have a core-envelope structure with a temperature gradient. Cores with high
temperature and high molecular hydrogen density are needed to match the higher
transitions (e.g. J=7-6) observed towards A and G. The lower temperature, low
density gas needed to create the inverse P-Cygni profile seen in the CS J=2-1
line (with 5" beam) towards H II region G arises from different components in
the 3 models. The infalling envelope of cloud G plus cloud B creates the
absorption in global collapse, cloud B is responsible in local collapse, and a
separate cloud, G', is needed in the case of many static clouds. The exact
nature of the velocity field in the envelopes for the case of local collapse is
not important as long as it is in the range of 1 to 5 km/s for a turbulent
velocity of about 6 km/s. High resolution observations of the J=1-0 and 5-4
transitions of CS and C34S may distinguish between these three models. Modeling
existing observations of HCO+ and C18O does not allow one to distinguish
between the three models but does indicate the existence of a bipolar outflow.Comment: 42 pages, 27 figures, accepted for publication in the ApJS August
2004, v153 issu
FUSE observations of HD 5980: The wind structure of the eruptor
HD 5980 is a unique system containing one massive star (star A) that is
apparently entering the luminous blue variable phase, and an eclipsing
companion (star B) that may have already evolved beyond this phase to become a
Wolf-Rayet star. In this paper we present the results from FUSE observations
obtained in 1999, 2000, and 2002 and one far-UV observation obtained by
ORFEUS/BEFS in 1993 shortly before the first eruption of HD 5980. The eight
phase-resolved spectra obtained by FUSE in 2002 are analyzed in the context of
a wind-eclipse model. This analysis shows that the wind of the eruptor obeyed a
very fast velocity law in 2002, which is consistent with the line-driving
mechanism. Large amplitude line-profile variations on the orbital period are
shown to be due to the eclipse of star B by the wind of star A, although the
eclipse due to gas flowing in the direction of star B is absent. This can only
be explained if the wind of star A is not spherically symmetric, or if the
eclipsed line radiation is "filled-in" by emission originating from somewhere
else in the system, e.g., in the wind-wind collision region. Except for a
slightly lower wind speed, the ORFEUS/BEFS spectrum is very similar to the
spectrum obtained by FUSE at the same orbital phase: there is no indication of
the impending eruption. However, the trend for decreasing wind velocity
suggests the occurrence of the "bi-stability" mechanism, which in turn implies
that the restructuring of the circumbinary environment caused by the transition
from "fast, rarefied wind" to "slow, dense wind" was observed as the eruptive
event. The underlying mechanism responsible for the long-term decrease in wind
velocity that precipitated this change remains an open issue.Comment: 19 pages, 13 figure
Potential climatic transitions with profound impact on Europe
We discuss potential transitions of six climatic subsystems with large-scale impact on Europe, sometimes denoted as tipping elements. These are the ice sheets on Greenland and West Antarctica, the Atlantic thermohaline circulation, Arctic sea ice, Alpine glaciers and northern hemisphere stratospheric ozone. Each system is represented by co-authors actively publishing in the corresponding field. For each subsystem we summarize the mechanism of a potential transition in a warmer climate along with its impact on Europe and assess the likelihood for such a transition based on published scientific literature. As a summary, the ‘tipping’ potential for each system is provided as a function of global mean temperature increase which required some subjective interpretation of scientific facts by the authors and should be considered as a snapshot of our current understanding. <br/
Publisher Correction:Discovery of rare variants associated with blood pressure regulation through meta-analysis of 1.3 million individuals (Nature Genetics, (2020), 52, 12, (1314-1332), 10.1038/s41588-020-00713-x)
In the version of this article originally published, the e-mail address of corresponding author Patricia B. Munroe was incorrect. The error has been corrected in the HTML and PDF versions of the article
A Framework For Detecting Noncoding Rare-Variant associations of Large-Scale Whole-Genome Sequencing Studies
Large-scale whole-genome sequencing studies have enabled analysis of noncoding rare-variant (RV) associations with complex human diseases and traits. Variant-set analysis is a powerful approach to study RV association. However, existing methods have limited ability in analyzing the noncoding genome. We propose a computationally efficient and robust noncoding RV association detection framework, STAARpipeline, to automatically annotate a whole-genome sequencing study and perform flexible noncoding RV association analysis, including gene-centric analysis and fixed window-based and dynamic window-based non-gene-centric analysis by incorporating variant functional annotations. In gene-centric analysis, STAARpipeline uses STAAR to group noncoding variants based on functional categories of genes and incorporate multiple functional annotations. In non-gene-centric analysis, STAARpipeline uses SCANG-STAAR to incorporate dynamic window sizes and multiple functional annotations. We apply STAARpipeline to identify noncoding RV sets associated with four lipid traits in 21,015 discovery samples from the Trans-Omics for Precision Medicine (TOPMed) program and replicate several of them in an additional 9,123 toPMed samples. We also analyze five non-lipid toPMed traits
Rare and low-frequency coding variants alter human adult height
Height is a highly heritable, classic polygenic trait with ~700 common associated variants identified so far through genome - wide association studies . Here , we report 83 height - associated coding variants with lower minor allele frequenc ies ( range of 0.1 - 4.8% ) and effects of up to 2 16 cm /allele ( e.g. in IHH , STC2 , AR and CRISPLD2 ) , >10 times the average effect of common variants . In functional follow - up studies, rare height - increasing alleles of STC2 (+1 - 2 cm/allele) compromise d proteolytic inhibition of PAPP - A and increased cleavage of IGFBP - 4 in vitro , resulting in higher bioavailability of insulin - like growth factors . The se 83 height - associated variants overlap genes mutated in monogenic growth disorders and highlight new biological candidates ( e.g. ADAMTS3, IL11RA, NOX4 ) and pathways ( e.g . proteoglycan/ glycosaminoglycan synthesis ) involved in growth . Our results demonstrate that sufficiently large sample sizes can uncover rare and low - frequency variants of moderate to large effect associated with polygenic human phenotypes , and that these variants implicate relevant genes and pathways
Non-Gaussian Lineshapes and Dynamics of Time-Resolved Linear and Nonlinear (Correlation) Spectra
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An Empirical Study of Infrasonic Propagation
Observations of atmospheric nuclear tests carried out at the Nevada Test Site from 1951 to 1958 provided data for an empirical investigation of how infrasonic signals are propagated to distances of about 250 km. Those observations and the analysis documented in this report involved signal amplitudes and average velocities and included three classes of signals: stratospheric, thermospheric, and tropospheric/surface. The authors' analysis showed that stratospheric winds have a dominant effect upon stratospheric signal amplitudes. The report outlines a method for normalizing stratospheric signal amplitudes for the effects of upper atmospheric winds and presents equations for predicting or normalizing amplitude and average velocity for the three types of signals
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