Fluorine Abundances in the Large Magellanic Cloud and Omega Centauri: Evidence for Neutrino Nucleosynthesis?

The behavior of fluorine with metallicity has not yet been probed in any stellar population. In this work, we present the first fluorine abundances measured outside of the Milky Way from a sample of red giants in the Large Magellanic Cloud (LMC), as well the Galactic globular cluster Omega Centauri. The fluorine abundances are derived from vibration-rotation transitions of HF using infrared spectra obtained with the Phoenix spectrograph on the Gemini South 8.1m telescope. It is found that the abundance ratio of F/O declines as the oxygen abundance decreases. The values of F/O are especially low in the two Omega Cen giants; this very low value of F/O probably indicates that 19F synthesis in asymptotic giant branch (AGB) stars is not the dominant source of fluorine in stellar populations. The observed decline in F/O with lower O abundances is in qualitative agreement with what is expected if 19F is produced via H- and He-burning sequences in very massive stars, with this fluorine then ejected in high mass-loss rate Wolf-Rayet winds. A quantitative comparison of observations with this process awaits results from more detailed chemical evolution models incorporating the yields from Wolf-Rayet winds. Perhaps of more significance is the quantitative agreement between the Galactic and LMC results with predictions from models in which 19F is produced from neutrino nucleosynthesis during core collpase in supernovae of Type II. The very low values of F/O in Omega Cen are also in agreement with neutrino nucleosynthesis models if the ``peculiar'' star formation history of Omega Cen, with 2-4 distinct episodes of star formation, is considered.Comment: 19 pages, 2 tables, 4 figures. In press to the Astronomical Journa

Fluorine Abundance Variations in Red Giants of the Globular Cluster M4 and Early-Cluster Chemical Pollution

We present fluorine abundances in seven red-giant members of the globular cluster M4 (NGC 6121). These abundances were derived from the HF (1--0) R9 line at 2.3357 microns in high-resolution infrared spectra obtained with the Phoenix spectrograph on Gemini-South. Many abundances in the target stars have been studied previously, so that their overall abundance distributions are well-mapped. The abundance of fluorine is found to vary by more than a factor of 6, with the F-19 variations being correlated with the already established oxygen variations, and anti-correlated with the sodium and aluminium variations. In this paper we thus add fluorine to the list of elements known to vary in globular cluster stars, and this provides further evidence that H-burning is the root cause of the chemical inhomegeneities. The fact that F-19 is found to decrease in the M4 stars, as the signature of H-burning appears, indicates that the polluting stars must have masses greater than about 3.5 solar masses, as less massive stars than this should produce, not destroy, fluorine.Comment: Astrophysical Journal, accepted and in-pres

Infrared Spectroscopy of Symbiotic Stars. IV. V2116 Ophiuchi/GX 1+4, The Neutron Star Symbiotic

We have computed, based on 17 infrared radial velocities, the first set of orbital elements for the M giant in the symbiotic binary V2116 Ophiuchi. The giant's companion is a neutron star, the bright X-ray source GX 1+4. We find an orbital period of 1161 days by far the longest of any known X-ray binary. The orbit has a modest eccentricity of 0.10 with an orbital circularization time of less than 10^6 years. The large mass function of the orbit significantly restricts the mass of the M giant. Adopting a neutron-star mass of 1.35M(Sun), the maximum mass of the M giant is 1.22M(Sun), making it the less massive star. Derived abundances indicate a slightly subsolar metallicity. Carbon and nitrogen are in the expected ratio resulting from the red-giant first dredge-up phase. The lack of O-17 suggests that the M-giant has a mass less than 1.3M(Sun), consistent with our maximum mass. The red giant radius is 103R(Sun), much smaller than the estimated Roche lobe radius. Thus, the mass loss of the red giant is via a stellar wind. Although the M giant companion to the neutron star has a mass similar to the late-type star in low-mass X-ray binaries, its near-solar abundances and apparent runaway velocity are not fully consistent with the properties of this class of stars.Comment: In press to The Astrophysical Journal (10 April 2006 issue). 23 page

Red supergiants as potential Type IIn supernova progenitors: Spatially resolved 4.6 micron CO emission around VY CMa and Betelgeuse

We present high-resolution 4.6micron CO spectra of the circumstellar environments of two RSGs that are potential SN progenitors: Betelgeuse and VY CMa. Around Betelgeuse, 12CO emission within 3arcsec follows a mildly clumpy but otherwise spherical shell, smaller than its 55arcsec shell in KI lambda7699. In stark contrast, 4.6micron CO emission around VY CMa is coincident with bright KI in its clumpy asymmetric reflection nebula, within 5arcsec of the star. Our CO data reveal redshifted features not seen in KI spectra of VY CMa, indicating a more isotropic distribution of gas punctuated by randomly distributed asymmetric clumps. The relative CO and KI distribution in Betelgeuse arises from ionization effects within a steady wind, whereas in VY CMa, KI is emitted from skins of CO cloudlets resulting from episodic mass ejections 500--1000 yr ago. In both cases, CO and KI trace potential pre-SN circumstellar matter: we conclude that an extreme RSG like VY CMa might produce a Type IIn event like SN1988Z if it were to explode in its current state, but Betelgeuse will not. VY CMa demonstrates that LBVs are not necessarily the only progenitors of SNe IIn, but it underscores the requirement that SNe IIn suffer enhanced episodic mass loss shortly before exploding.Comment: 16 pages, AJ accepte

Silver-assisted development and imaging of fingermarks on non-porous and porous surfaces

This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ This author accepted manuscript is made available following 24 month embargo from date of publication (Aug 2017) in accordance with the publisher’s archiving policyIn order to deal with the range of surfaces encountered in crime scenes and items associated with crimes, forensic fingermark examiners must have access to a range of latent mark enhancement techniques, each compatible with a particular type of surface. Consequently, the development of techniques with universal or even wide-ranging surface compatibility would be valuable to law enforcement. Herein, we describe a one-step silver sputtering method for the enhancement of latent fingermarks on plastic, glass, paper and metal substrates. This method allows for the ridge pattern to be captured for human identification purposes and, more importantly, for the downstream mass spectrometric imaging of the fingermark in order to display the spatial distribution of common endogenous and exogenous substances such as illicit drug

Modules, networks and systems medicine for understanding disease and aiding diagnosis

Many common diseases, such as asthma, diabetes or obesity, involve altered interactions between thousands of genes. High-throughput techniques (omics) allow identification of such genes and their products, but functional understanding is a formidable challenge. Network-based analyses of omics data have identified modules of disease-associated genes that have been used to obtain both a systems level and a molecular understanding of disease mechanisms. For example, in allergy a module was used to find a novel candidate gene that was validated by functional and clinical studies. Such analyses play important roles in systems medicine. This is an emerging discipline that aims to gain a translational understanding of the complex mechanisms underlying common diseases. In this review, we will explain and provide examples of how network-based analyses of omics data, in combination with functional and clinical studies, are aiding our understanding of disease, as well as helping to prioritize diagnostic markers or therapeutic candidate genes. Such analyses involve significant problems and limitations, which will be discussed. We also highlight the steps needed for clinical implementation

Abolition of male sexual behaviors in mice lacking estrogen receptors alpha and beta (alpha beta ERKO)

Male mice with a knockout of the estrogen receptor (ER)-α gene, a ligand-activated transcription factor, showed reduced levels of intromissions and no ejaculations whereas simple mounting behavior was not affected. In contrast, all components of sexual behaviors were intact in male mice lacking the novel ER-β gene. Here we measure the extent of phenotype in mice that lack both ER-α and ER-β genes (αβERKO). αβERKO male mice did not show any components of sexual behaviors, including simple mounting behavior. Nor did they show ultrasonic vocalizations during behavioral tests with receptive female mice. On the other hand, reduced aggressive behaviors of αβERKO mice mimicked those of single knockout mice of ER-α gene (αERKO). They showed reduced levels of lunge and bite aggression, but rarely showed offensive attacks. Thus, either one of the ERs is sufficient for the expression of simple mounting in male mice, indicating a redundancy in function. Offensive attacks, on the other hand, depend specifically on the ER-α gene. Different patterns of natural behaviors require different patterns of functions by ER genes

Born to learn: The inspiration, progress, and future of evolved plastic artificial neural networks

Biological plastic neural networks are systems of extraordinary computational capabilities shaped by evolution, development, and lifetime learning. The interplay of these elements leads to the emergence of adaptive behavior and intelligence. Inspired by such intricate natural phenomena, Evolved Plastic Artificial Neural Networks (EPANNs) use simulated evolution in-silico to breed plastic neural networks with a large variety of dynamics, architectures, and plasticity rules: these artificial systems are composed of inputs, outputs, and plastic components that change in response to experiences in an environment. These systems may autonomously discover novel adaptive algorithms, and lead to hypotheses on the emergence of biological adaptation. EPANNs have seen considerable progress over the last two decades. Current scientific and technological advances in artificial neural networks are now setting the conditions for radically new approaches and results. In particular, the limitations of hand-designed networks could be overcome by more flexible and innovative solutions. This paper brings together a variety of inspiring ideas that define the field of EPANNs. The main methods and results are reviewed. Finally, new opportunities and developments are presented