3,731 research outputs found

    Effects of injury and nutrition on sediment reworking by Clymenella torquata (Annelida: Polychaeta)

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    Marine infaunas influence sediment chemistry, nutrient cycling, and microbial communities as they burrow, feed, defecate, and irrigate their tubes and burrows. Nonlethal tissue loss to predators or other disturbances is frequently observed in macrofaunal communities, and previous research has reported significant effects of onetime injury on animal activity. In this study, we examined the effects of injury and nutrient enrichment on sediment reworking rates of a common deposit-feeding polychaete, Clymenella torquata. Individual worms in cores were monitored in a recirculating seawater system, and their defecation and sediment mixing monitored under several experimental conditions. Worms held in control (unenriched) sediment or in homogeneously diatom-enriched sediment were injured on days 0 and 7 in a 21 d experiment. Worms held in control sediment or sediment with high surface diatom enrichment were observed in a 7 d experiment following repeated injury. Posterior segments were ablated for the injury treatments, and injury and nutrient supply treatments were crossed in all experiments. Repeated injury significantly decreased surface activities and defecation, and injured worms transported significantly less surface sediment to depth than intact worms. Microalgal enrichment at the sediment surface correlated with an increase in bioturbation; intact worms in surfaceenriched sediments were more active and more likely to hoe surface sediments to depth as evidenced by vertical profiles. These findings help explain how infaunal activities are modified by injury and food availability and can be used to improve models of bioturbation to further elucidate complex benthic community dynamics

    Rubidium abundances in the globular clusters NGC 6752, NGC 1904 and NGC 104 (47 Tuc)

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    Large star-to-star variations of the abundances of proton-capture elements, such as Na and O, in globular clusters (GCs) are interpreted as the effect of internal pollution resulting from the presence of multiple stellar populations. To better constrain this scenario we investigate the abundance distribution of the heavy element rubidium (Rb) in NGC 6752, NGC 1904, and NGC 104 (47 Tuc). Combining the results from our sample with those in the literature, we found that Rb exhibits no star-to-star variations, regardless the cluster metallicity, with the possible intriguing, though very uncertain, exception of the metal-rich bulge cluster NGC 6388. If no star-to-star variations will be confirmed for all GCs, it implies that the stellar source of the proton-capture element variations must not have produced significant amounts of Rb. This element is observed to be enhanced at extremely high levels in intermediate-mass AGB (IM-AGB) stars in the Magellanic Clouds (i.e., at a metallicity similar to 47 Tuc and NGC 6388). This may present a challenge to this popular candidate polluter, unless the mass range of the observed IM-AGB stars does not participate in the formation of the second-generation stars in GCs. A number of possible solutions are available to resolve this conundrum, also given that the Magellanic Clouds observations are very uncertain and may need to be revised. The fast rotating massive stars scenario would not face this potential problem as the slow mechanical winds of these stars during their main-sequence phase do not carry any Rb enhancements; however, these candidates face even bigger issues such as the production of Li and the close over-imposition with core-collapse supernova timescales. Observations of Sr, Rb, and Zr in metal-rich clusters such as NGC 6388 and NGC 6441 are sorely needed to clarify the situation.Comment: Accepted for publication in The Astrophysical Journa

    Lost to Follow-up: A Study Exploring Barriers to Care at UNC Women’s Hospital Dysplasia Clinic

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    Management of Cervical Intraepithelial Neoplasia (CIN) includes a long time course of surveillance in which many women are “lost to follow-up.” Inadequate management of early dysplastic changes that may progress to CIN contributes to an increased likelihood of mortality from invasive cervical cancer in the state of North Carolina. The aim of this qualitative study is to understand women’s knowledge and perceptions of cervical dysplasia in order to tailor counseling for improved follow-up. Thirteen women with varying levels of cytological abnormalities from pap smear screening were interviewed prior to their colposcopy appointment at a referral hospital. In addition to recalling significant anxiety and fear about the possibility of cancer, women exhibited an unexpected lack of knowledge about cervical dysplasia and human papilloma virus (HPV) despite counseling at previous clinics. Financial and cost barriers were less significant to seeking care than understanding of prognosis. This study reveals an opportunity for better pre-testing and pre-screening counseling about the causal role of HPV and the potential disease course following cytological abnormalities to increase women’s likelihood of referral follow-up.Master of Science in Public Healt

    Classical Guitar Ensemble

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    Kennesaw State University School of Music presents Classical Guitar Ensemble.https://digitalcommons.kennesaw.edu/musicprograms/1400/thumbnail.jp

    The GAN that Warped: Semantic Attribute Editing with Unpaired Data

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    Deep neural networks have recently been used to edit images with great success, in particular for faces. However, they are often limited to only being able to work at a restricted range of resolutions. Many methods are so flexible that face edits can often result in an unwanted loss of identity. This work proposes to learn how to perform semantic image edits through the application of smooth warp fields. Previous approaches that attempted to use warping for semantic edits required paired data, i.e. example images of the same subject with different semantic attributes. In contrast, we employ recent advances in Generative Adversarial Networks that allow our model to be trained with unpaired data. We demonstrate face editing at very high resolutions (4k images) with a single forward pass of a deep network at a lower resolution. We also show that our edits are substantially better at preserving the subject's identity
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