16,464 research outputs found
Hydrogen in Type Ic Supernovae?
By definition, a Type Ic supernova (SN Ic) does not have conspicuous lines of
hydrogen or helium in its optical spectrum. SNe Ic usually are modelled in
terms of the gravitational collapse of bare carbon-oxygen cores. We consider
the possibility that the spectra of ordinary (SN 1994I-like) SNe Ic have been
misinterpreted, and that SNe Ic eject hydrogen. An absorption feature usually
attributed to a blend of Si II 6355 and C II 6580 may be produced by H-alpha.
If SN 1994I-like SNe Ic eject hydrogen, the possibility that hypernova (SN
1998bw-like) SNe Ic, some of which are associated with gamma-ray bursts, also
eject hydrogen should be considered. The implications of hydrogen for SN Ic
progenitors and explosion models are briefly discussed.Comment: Accepted by PASP. Several significant changes including one
additional figur
Are you a researcher as well as a medical illustrator?
When we list the areas of practice for medical illustrators we always include research, but how involved in research are we? The aim of this activity is to encourage your professional development not just as a medical illustrator but your involvement with research whether that is undertaking your own research, undertaking evidence based practice (1) , working as part of a research team, advising researchers on the value of medical illustration or supporting a student undertaking a research project for their degree or post-graduate qualification
The clinical relevance and newsworthiness of NIHR HTA-funded research: a cohort study
ObjectiveTo assess the clinical relevance and newsworthiness of the UK National Institute for Health Research (NIHR) Health Technology Assessment (HTA) Programme funded reports.Study designRetrospective cohort study.SettingThe cohort included 311 NIHR HTA Programme funded reports publishing in HTA in the period 1 January 2007–31 December 2012. The McMaster Online Rating of Evidence (MORE) system independently identified the clinical relevance and newsworthiness of NIHR HTA publications and non-NIHR HTA publications. The MORE system involves over 4000 physicians rating publications on a scale of relevance (the extent to which articles are relevant to practice) and a scale of newsworthiness (the extent to which articles contain news or something clinicians are unlikely to know).Main outcome measuresThe proportion of reports published in HTA meeting MORE inclusion criteria and mean average relevance and newsworthiness ratings were calculated and compared with publications from the same studies publishing outside HTA and non-NIHR HTA funded publications.Results286/311 (92.0%) of NIHR HTA reports were assessed by MORE, of which 192 (67.1%) passed MORE criteria. The average clinical relevance rating for NIHR HTA reports was 5.48, statistically higher than the 5.32 rating for non-NIHR HTA publications (mean difference=0.16, 95% CI 0.04 to 0.29, p=0.01). Average newsworthiness ratings were similar between NIHR HTA reports and non-NIHR HTA publications (4.75 and 4.70, respectively; mean difference=0.05, 95% CI ?0.18 to 0.07, p=0.402). NIHR HTA-funded original research reports were statistically higher for newsworthiness than reviews (5.05 compared with 4.64) (mean difference=0.41, 95% CI 0.18 to 0.64, p=0.001).ConclusionsFunding research of clinical relevance is important in maximising the value of research investment. The NIHR HTA Programme is successful in funding projects that generate outputs of clinical relevance
mixtools: An R Package for Analyzing Mixture Models
The mixtools package for R provides a set of functions for analyzing a variety of finite mixture models. These functions include both traditional methods, such as EM algorithms for univariate and multivariate normal mixtures, and newer methods that reflect some recent research in finite mixture models. In the latter category, mixtools provides algorithms for estimating parameters in a wide range of different mixture-of-regression contexts, in multinomial mixtures such as those arising from discretizing continuous multivariate data, in nonparametric situations where the multivariate component densities are completely unspecified, and in semiparametric situations such as a univariate location mixture of symmetric but otherwise unspecified densities. Many of the algorithms of the mixtools package are EM algorithms or are based on EM-like ideas, so this article includes an overview of EM algorithms for finite mixture models.
ECONOMICALLY OPTIMAL NITROGEN FERTILIZATION FOR YIELD AND PROTEIN IN HARD RED SPRING WHEAT
This analysis determines profit maximizing N fertilization levels of hard red spring wheat (HRSW) for various wheat prices, N prices, and protein-based HRSW price premium/discount (P/D) structures for south eastern Washington data. Fertilizer response data consisting of rates of N fertilization (lb/ac), grain yield (bu/ac), and grain protein (%) were used to statistically estimate regression relationships that predicted yield and protein in response to N. All predicted net return maximizing N, protein, and yield levels were within the data range. Increasing P/D incentives for protein increased optimal N, the expected economic result. At the high P/D structures, the P/D structure dominated N and wheat prices in determining optimal N application levels. Overall, net return-maximizing yields varied only modestly with changes in both N and wheat price in this data set. However, in all scenarios, as P/D incentives increased, net return maximizing N levels were beyond the level that resulted in maximum yield. At the two lowest P/D structures, which provided the lowest reward for protein, it was most profitable to fertilize for slightly less than 14% expected protein. These results indicate that it is not always profitable to use 14% protein as an N fertilization goal. Abbreviations: CT, conventional tillage; HRSW, hard red spring wheat; HRWW, hard red winter wheat; N, nitrogen; NO3, nitrate; NT, No Tillage; P/D, premium/discount; SWSW, soft white spring wheat; SWW, soft white wheat.Crop Production/Industries,
Hinode/Extreme-Ultraviolet Imaging Spectrometer Observations of the Temperature Structure of the Quiet Corona
We present a Differential Emission Measure (DEM) analysis of the quiet solar
corona on disk using data obtained by the Extreme-ultraviolet Imaging
Spectrometer (EIS) on {\it Hinode}. We show that the expected quiet Sun DEM
distribution can be recovered from judiciously selected lines, and that their
average intensities can be reproduced to within 30%. We present a subset of
these selected lines spanning the temperature range T = 5.6 to 6.4 K
that can be used to derive the DEM distribution reliably. The subset can be
used without the need for extensive measurements and the observed intensities
can be reproduced to within the estimated uncertainty in the pre-launch
calibration of EIS. Furthermore, using this subset, we also demonstrate that
the quiet coronal DEM distribution can be recovered on size scales down to the
spatial resolution of the instrument (1 pixels). The subset will therefore
be useful for studies of small-scale spatial inhomogeneities in the coronal
temperature structure, for example, in addition to studies requiring multiple
DEM derivations in space or time. We apply the subset to 45 quiet Sun datasets
taken in the period 2007 January to April, and show that although the absolute
magnitude of the coronal DEM may scale with the amount of released energy, the
shape of the distribution is very similar up to at least T 6.2 K
in all cases. This result is consistent with the view that the {\it shape} of
the quiet Sun DEM is mainly a function of the radiating and conducting
properties of the plasma and is fairly insensitive to the location and rate of
energy deposition. This {\it universal} DEM may be sensitive to other factors
such as loop geometry, flows, and the heating mechanism, but if so they cannot
vary significantly from quiet Sun region to region.Comment: Version accepted by ApJ and published in ApJ 705. Abridged abstrac
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