Empirically Assessing Students\u27 Perceptions of the Importance of Student Characteristic

After at least four years of college, do students seeking entry-Ievel IS employment realize that employers consider many variables when making the hiring decision? Many employers look at GPA, but other variables, such as the business skills, ability to work with others, energy, drive, and enthusiasm, and analytical skills, are also important. This study empirically assesses students\u27 perceptions of the importance of seven student characteristics in the hiring process. Subjects included 51 undergraduate and 28 graduate students. The methodology employs analysis that facilitates the examination of all seven characteristics simultaneously. Results show that the two most important variables were communication skills and the ability to work with others. While all seven variables were important, students perceived GPA to be the least important of the seven. Demographic variables such as gender and major had no effect on the results

Preliminary Design of JML: A Behavioral Interface Specification Language for Java

JML is a behavioral interface specification language tailored to Java(TM). Besides pre- and postconditions, it also allows assertions to be intermixed with Java code; these aid verification and debugging. JML is designed to be used by working software engineers; to do this it follows Eiffel in using Java expressions in assertions. JML combines this idea from Eiffel with the model-based approach to specifications, typified by VDM and Larch, which results in greater expressiveness. Other expressiveness advantages over Eiffel include quantifiers, specification-only variables, and frame conditions. This paper discusses the goals of JML, the overall approach, and describes the basic features of the language through examples. It is intended for readers who have some familiarity with both Java and behavioral specification using pre- and postconditions

Course Specifications for New Introductory Courses: Computer Science 227X and 228X

Computer Science 227X introduces first-year students to programming using Scheme. Computer Science 228X is an introduction to data structures in C++. Both courses attempt to teach principles through extensive practice in programming. This document specifies the course\u27s general objectives and gives an overview of what would be taught

101 Dothideomycetes genomes: A test case for predicting lifestyles and emergence of pathogens.

Dothideomycetes is the largest class of kingdom Fungi and comprises an incredible diversity of lifestyles, many of which have evolved multiple times. Plant pathogens represent a major ecological niche of the class Dothideomycetes and they are known to infect most major food crops and feedstocks for biomass and biofuel production. Studying the ecology and evolution of Dothideomycetes has significant implications for our fundamental understanding of fungal evolution, their adaptation to stress and host specificity, and practical implications with regard to the effects of climate change and on the food, feed, and livestock elements of the agro-economy. In this study, we present the first large-scale, whole-genome comparison of 101 Dothideomycetes introducing 55 newly sequenced species. The availability of whole-genome data produced a high-confidence phylogeny leading to reclassification of 25 organisms, provided a clearer picture of the relationships among the various families, and indicated that pathogenicity evolved multiple times within this class. We also identified gene family expansions and contractions across the Dothideomycetes phylogeny linked to ecological niches providing insights into genome evolution and adaptation across this group. Using machine-learning methods we classified fungi into lifestyle classes with >95 % accuracy and identified a small number of gene families that positively correlated with these distinctions. This can become a valuable tool for genome-based prediction of species lifestyle, especially for rarely seen and poorly studied species

Multi-Messenger Gravitational Wave Searches with Pulsar Timing Arrays: Application to 3C66B Using the NANOGrav 11-year Data Set

When galaxies merge, the supermassive black holes in their centers may form binaries and, during the process of merger, emit low-frequency gravitational radiation in the process. In this paper we consider the galaxy 3C66B, which was used as the target of the first multi-messenger search for gravitational waves. Due to the observed periodicities present in the photometric and astrometric data of the source of the source, it has been theorized to contain a supermassive black hole binary. Its apparent 1.05-year orbital period would place the gravitational wave emission directly in the pulsar timing band. Since the first pulsar timing array study of 3C66B, revised models of the source have been published, and timing array sensitivities and techniques have improved dramatically. With these advances, we further constrain the chirp mass of the potential supermassive black hole binary in 3C66B to less than $(1.65\pm0.02) \times 10^9~{M_\odot}$ using data from the NANOGrav 11-year data set. This upper limit provides a factor of 1.6 improvement over previous limits, and a factor of 4.3 over the first search done. Nevertheless, the most recent orbital model for the source is still consistent with our limit from pulsar timing array data. In addition, we are able to quantify the improvement made by the inclusion of source properties gleaned from electromagnetic data to `blind' pulsar timing array searches. With these methods, it is apparent that it is not necessary to obtain exact a priori knowledge of the period of a binary to gain meaningful astrophysical inferences.Comment: 14 pages, 6 figures. Accepted by Ap