117 research outputs found
The Theory of Brown Dwarfs and Extrasolar Giant Planets
Straddling the traditional realms of the planets and the stars, objects below
the edge of the main sequence have such unique properties, and are being
discovered in such quantities, that one can rightly claim that a new field at
the interface of planetary science and and astronomy is being born. In this
review, we explore the essential elements of the theory of brown dwarfs and
giant planets, as well as of the new spectroscopic classes L and T. To this
end, we describe their evolution, spectra, atmospheric compositions, chemistry,
physics, and nuclear phases and explain the basic systematics of
substellar-mass objects across three orders of magnitude in both mass and age
and a factor of 30 in effective temperature. Moreover, we discuss the
distinctive features of those extrasolar giant planets that are irradiated by a
central primary, in particular their reflection spectra, albedos, and transits.
Aspects of the latest theory of Jupiter and Saturn are also presented.
Throughout, we highlight the effects of condensates, clouds, molecular
abundances, and molecular/atomic opacities in brown dwarf and giant planet
atmospheres and summarize the resulting spectral diagnostics. Where possible,
the theory is put in its current observational context.Comment: 67 pages (including 36 figures), RMP RevTeX LaTeX, accepted for
publication in the Reviews of Modern Physics. 30 figures are color. Most of
the figures are in GIF format to reduce the overall size. The full version
with figures can also be found at:
http://jupiter.as.arizona.edu/~burrows/papers/rm
The Psychological Science Acceleratorâs COVID-19 rapid-response dataset
In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data
The Psychological Science Acceleratorâs COVID-19 rapid-response dataset
In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data
Urinary benzene as a biomarker of exposure among occupationally exposed and unexposed subjects
Urinary benzene (UB) was investigated as a biomarker of exposure among benzene-exposed workers and unexposed subjects in Shanghai, China. Measurements were performed via headspace solid phase microextraction of 0.5 ml of urine specimens followed by gas chromatography-mass spectrometry. This assay is simple and more sensitive than other methods (detection limit 0.016 microg benzene/l urine). The median daily benzene exposure was 31 p.p.m. (range 1.65-329 p.p.m.). When subjects were divided into controls (n = 41), those exposed to 31 p.p.m. benzene (n = 20), the median UB levels were 0.069, 4.95 and 46.1 microg/l, respectively (Spearman r = 0.879, P < 0.0001). A linear relationship was observed between the logarithm of UB and the logarithm of benzene exposure in exposed subjects according to the following equation: ln(UB, microg/l) = 0.196 + 0.709 ln (exposure, p.p.m.) (r = 0.717, P < 0.0001). Considering all subjects, linear relationships were also observed between the logarithm of UB and the corresponding logarithms of four urinary metabolites of benzene, namely t,t-muconic acid (r = 0.938, P < 0.0001), phenol (r = 0.826, P < 0.0001), catechol (r = 0.812, P < 0.0001) and hydroquinone (r = 0.898, P: < 0.0001). Ratios of individual metabolite levels to total metabolites versus UB provide evidence of competitive inhibition of CYP450 enzymes leading to increased production of phenol and catechol at the expense of hydroquinone and muconic acid. Among control subjects UB was readily detected with a mean level of 0.145 microg/l (range 0.027-2.06 microg/l), compared with 5.63 microg/l (range 0.837-26.38 microg/l) in workers exposed to benzene below 10 p.p.m. (P < 0.0001). This suggests that UB is a good biomarker for exposure to low levels of benzene
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