The chemical composition of a regular halo globular cluster: NGC 5897

We report for the first time on the chemical composition of the halo cluster NGC 5897 (R=12.5 kpc), based on chemical abundance ratios for 27 alpha-, iron-peak, and neutron-capture elements in seven red giants. From our high-resolution, high signal-to-noise spectra obtained with the Magellan/MIKE spectrograph, we find a mean iron abundance from the neutral species of [Fe/H] = -2.04 +/- 0.01 (stat.) +/- 0.15 (sys.), which is more metal-poor than implied by previous photometric and low-resolution spectroscopic studies. NGC 5897 is alpha-enhanced (to 0.34 +/- 0.01 dex) and shows Fe-peak element ratios typical of other (metal-poor) halo globular clusters (GCs) with no overall, significant abundance spreads in iron nor in any other heavy element. Like other GCs, NGC 5897 shows a clear Na-O anti-correlation, where we find a prominent primordial population of stars with enhanced O abundances and ~Solar Na/Fe ratios, while two stars are Na-rich, providing chemical proof of the presence of multiple populations in this cluster. Comparison of the heavy element abundances with the Solar-scaled values and the metal poor GC M15 from the literature confirms that NGC 5897 has experienced only little contribution from s-process nucleosynthesis. One star of the first generation stands out in that it shows very low La and Eu abundances. Overall, NGC 5897 is a well-behaved GC showing archetypical correlations and element-patterns, with little room for surprises in our data. We suggest that its lower metallicity could explain the unusually long periods of RR Lyr that were found in NGC 5897.Comment: 13 pages, 8 figures, accepted for publication in Astronomy & Astrophysic

A comprehensive chemical abundance study of the outer halo globular cluster M 75

Context: M 75 is a relatively young Globular Cluster (GC) found at 15 kpc from the Galactic centre at the transition region between the inner and outer Milky Way halos. Aims: Our aims are to perform a comprehensive abundance study of a variety of chemical elements in this GC such as to investigate its chemical enrichment history in terms of early star formation, and to search for any multiple populations. Methods: We have obtained high resolution spectroscopy with the MIKE instrument at the Magellan telescope for 16 red giant stars. Their membership within the GC is confirmed from radial velocity measurements. Our chemical abundance analysis is performed via equivalent width measurements and spectral synthesis, assuming local thermodynamic equilibrium (LTE). Results: We present the first comprehensive abundance study of M 75 to date. The cluster is metal-rich ([Fe/H]=-1.16+/-0.02 dex, [alpha/Fe]=+0.30+/-0.02 dex), and shows a marginal spread in [Fe/H] of 0.07 dex, typical of most GCs of similar luminosity. A moderately extended O-Na anticorrelation is clearly visible, likely showing three generations of stars, formed on a short timescale. Additionally the two most Na-rich stars are also Ba-enhanced by 0.4 and 0.6 dex, respectively, indicative of pollution by lower mass (M ~ 4-5 M_Sun) Asymptotic Giant Branch (AGB) stars. The overall n-capture element pattern is compatible with predominant r-process enrichment, which is rarely the case in GCs of such a high metallicity.Comment: 15 pages, 11 figures, 7 tables, accepted for publication in A&

The Influence of In-School Time (IST) and Out-of-School Time (OST) Learning Experiences on Aviation Career Entry

Increased demand for aviation has created a skill and workforce gap. An understanding of how to increase this potential workforce is vital to ensure the ongoing success and sustainability of the commercial aviation industry. This research explores science, technology, engineering, and math (STEM) programs as a potential avenue for increasing the available aviation workforce. Specifically, it explores how STEM programs and their associated learning experiences influence career entry. Utilizing a mixed methodology approach, this research retrospectively explored the self-reported effect of out-of-school time (OST) and in-school time (IST) STEM experiences on aviation career development. Through interviews, a survey instrument was developed and validated that allowed for an assessment of the impact of STEM experiences on career interest. Through data analysis, specific major factors were extracted. The results were analyzed and assessed in the context of the existing aviation and career development literature. Data analysis revealed that STEM participation type impacted both the professional interaction and career knowledge constructs. Those participants who were involved in both an OST and IST STEM program had higher mean professional v interaction and career knowledge scores compared to those individuals that only participated in an IST STEM program. Individually examining each variable revealed key findings related to mentor interaction, career focus, and career confidence. The results are discussed in the context of the existing literature and social cognitive career theory (SCCT). In particular, the career focus and career confidence findings, related to the SCCT concept of self-efficacy, suggests that OST STEM education is more impactful upon aviation career self-efficacy than IST STEM education. Recommendations are made for future aviation and non-aviation STEM programs

Voracious villains or hungry heroes? : depictions of food critics in popular media

There are copious types of visual media that viewers presently consume as entertainment. These various mediums showcase depictions that influence people's perceptions of both individuals and entire careers. In journalism studies, scholars look at these visual depictions in film, television, graphic novels, and others to categorize how journalism works and how journalists interact with the world. Depictions too often focus on hard news and mainline journalism at the expense of subfields such as food criticism. This study responds to a call to action to look into media beyond film, while carving out its own path and establishing that food critics are understudied. From non-journalistic beginnings, food criticism entered the fold of lifestyle journalism. In popular fictional visual media across time, close textual analysis of the depiction of food critics shows unique and shared themes, tropes, and story arcs specific to food critics, including: violence and anonymity. Depictions of food critics were homogenous regardless of the medium and were shown primarily as older white men with similar dress, attitude, and ethics. These depictions were overwhelmingly negative with few showing food critics doing their job well in a positive light. This thesis combats the neglect of depictions of food critics in journalistic study, as well as showcases the characterizations of food critics that separates them from other journalists and critics.Dr. Ryan J. Thomas, Thesis Supervisor.Includes bibliographical references (pages 99-103)

Demyansk 1941-1943 : a microscopic view of the German-Soviet conflict

Well over ten million men served in the Axis armies during the war, and over 70 percent of these troops fought on the Eastern Front. Each soldier has/had a personal story to tell - their fighting units are all worthy of mention and every battle they fought in should be appraised. It has been the habit of English-speaking historians studying the Second World War to concentrate almost exclusively on the European Theater of operations. The events on the Eastern Front, with the exception of the battles of Leningrad, Stalingrad, and perhaps Kursk, are practically ignored. This study, however, will analyze a previously little known yet significant campaign of the Soviet-German war of 1941-1945 - the experiences of a portion of Army Group North in and around Demyansk from December 1941 through February 1943. It is the aim of this analysis to help fill the void in the study of individual battles and operations on the Eastern Front. It is hoped that the work will assist English-speaking historians in the discovery of the individual engagements and operations that were fought there. The information shall be presented in a topical fashion that closely adheres to the chronological order of events. The research is based largely on primary source material, including captured German war documents and personal narratives obtained from the Bundesarchiv in Freiburg, from the National Archives in Washington, D.C., and from interviews with veterans of the campaign

Multiplication-based analog motion detection chip

Novel use of an analog motion detection circuit is presented. The circuit, developed by Tanner and Mead, computes motion by dividing the time derivative of intensity by its spatial derivative; the four-quadrant division is realized with a multiplier within a negative feedback loop. The authors have opened the loop and characterized the circuit as a multiplication-based motion detector, in which the output is the product of the temporal and spatial derivatives of intensity, for various light levels and various moving patterns. An application to the time-to- contact computation is presented

Hyperprofile-based Computation Offloading for Mobile Edge Networks

In recent studies, researchers have developed various computation offloading frameworks for bringing cloud services closer to the user via edge networks. Specifically, an edge device needs to offload computationally intensive tasks because of energy and processing constraints. These constraints present the challenge of identifying which edge nodes should receive tasks to reduce overall resource consumption. We propose a unique solution to this problem which incorporates elements from Knowledge-Defined Networking (KDN) to make intelligent predictions about offloading costs based on historical data. Each server instance can be represented in a multidimensional feature space where each dimension corresponds to a predicted metric. We compute features for a "hyperprofile" and position nodes based on the predicted costs of offloading a particular task. We then perform a k-Nearest Neighbor (kNN) query within the hyperprofile to select nodes for offloading computation. This paper formalizes our hyperprofile-based solution and explores the viability of using machine learning (ML) techniques to predict metrics useful for computation offloading. We also investigate the effects of using different distance metrics for the queries. Our results show various network metrics can be modeled accurately with regression, and there are circumstances where kNN queries using Euclidean distance as opposed to rectilinear distance is more favorable.Comment: 5 pages, NSF REU Site publicatio

Patron Driven Acquisitions: Integrating Print Books with eBooks

pg.26 and 28, vol.24 no.6 of ALA's Midwinter issu