The LAIR at East Texas A&M
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Mayo Memorial Monument
No full textA color photograph of the north face of the Mayo Memorial Monument.https://lair.etamu.edu/scua-univ-photos-browse-all/1391/thumbnail.jp
Journalism Building and William L. Mayo Statue
No full textA color photograph showing the west face of the Journalism Building and the William L. Mayo Statue.https://lair.etamu.edu/scua-univ-photos-browse-all/1387/thumbnail.jp
Phase II Residence Hall Main Entrance
No full textA color photograph of the northeast corner of Phase II Residence Hall, showing one of the main entrances.https://lair.etamu.edu/scua-univ-photos-browse-all/1377/thumbnail.jp
Nursing and Health Sciences Building Outdoor Seating
No full textA color photograph showing outdoor seating located on the north side of the Nursing and Health Sciences Building. Pictured in the background, from left to right, are Charles S. Garvin Lake, the Performing Arts Center, and the Keith D. McFarland Science Building.https://lair.etamu.edu/scua-univ-photos-browse-all/1366/thumbnail.jp
Faye and Tildon Heritage Garden North Entrance
No full textA color photograph showing the ETSTC Arch and the north entrance to the Faye and Tildon Heritage Garden.https://lair.etamu.edu/scua-univ-photos-browse-all/1384/thumbnail.jp
Bill Martin Jr. Portrait, Reverse
No full textThe reverse side of a black and white photograph. The top of the image includes a red photographers stamp.https://lair.etamu.edu/scua-martin-photos/1005/thumbnail.jp
Character Strengths and Virtues: A Global Citizenship Perspective
No full textAn individual’s life context (i.e., normative environment) and knowledge about the world (i.e., global awareness) predict one’s connection with the global citizen identity. One’s degree of identification with global citizens has been shown to consistently predict prosocial outcomes. Similarly, the character strengths and virtues classification consists of many overlapping prosocial concepts that tap into the outcomes of perceiving oneself as a global citizen, based on human similarities and interconnection. The purpose of the current study was to examine whether both concepts are correlated, as well as the virtues as predictors of the model of antecedents and outcomes of global citizenship identification. All of the variables assessed were positively correlated, with exception of courage (with social0 justice and environmentalism) and temperance (with social justice). Previously documented global citizenship identification relationships were consistent. Wisdom and humanity were found to significantly predict aspects of the model of antecedents and outcomes of global citizenship identification
A Hedonic Analysis of Cattle Prices in Nicaragua
No full textGrowing at an annual rate of 3.7%, the Latin American livestock sector has surpassed the average global livestock growth rate of 2.1% and has become the leading region for beef and poultry exports worldwide (Food and Agriculture Organization [FAO], 2020a). In this investigation, a case study of cattle prices in Nicaragua, the leading meat-producing country in Central America, is conducted. Nicaragua’s cattle production is non-intensive and exhibited a growth rate of 24% between 2017 and 2018 (Nicaraguan Central Bank [NCB], 2018). Using data on futures on feeder cattle prices from the Chicago Mercantile Exchange Group (CME) supplemented with data on 2,520 sales transactions from 99 auctions from 2017 to 2018 from the Nicaraguan Cattle Auction (NCA), this study conducts a hedonic price analysis for cattle auctioned in Nicaragua. While in a previous study, we used cash price as the independent variable, following Trapp and Eilrich (1991), we used a basis approach in the present study to further improve the regression model. A basis model has been found to be a better risk management tool as variations between cash prices and futures prices are reduced. In particular, the study empirically identifies factors affecting price differentials for cattle. The estimation results show that weight, lot size, and sex are among statistically significant factors impacting cattle auction prices. The results of the study are of importance to buyers and sellers of cattle in their decision-making process and help them understand information from the futures market to predict price differences and reduce price risk and uncertainty
Pulsating White Dwarfs in the Open Star Cluster M67
No full textWhite dwarfs are some of the most versatile tools in the universe. Their ages can provide a lower limit to the age of the universe, and their masses and structure can inform us about the inner workings of the stars they came from. Asteroseismic studies of pulsating white dwarfs have greatly increased our knowledge about the masses of the atmospheric layers, which are crucial to determine the cooling rate of white dwarfs. Knowing the cooling rate will tell us much about the age of the white dwarf and in turn, the age of the universe. In this study, we present the first time-series photometry of pulsating white dwarf candidates in the open star cluster Messier 67. By looking at an ensemble of white dwarfs in an old, open cluster such as Messier 67, we can begin to constrain which properties of stars affect the thicknesses of the atmospheric layers. Standard stellar evolutionary theory suggests the atmospheric structure of each white dwarf in the sample should be identical, as they came from nearly identical progenitor stars; this prediction has yet to be tested. This sample of spectroscopically confirmed white dwarfs comes from a previous study of the white dwarf population in Messier 67. Six hours of time-series photometry are analyzed for pulsation-driven luminosity changes. We find one definite pulsator that is not a cluster member and evidence of variability in three additional white dwarfs that are cluster members. If these additional white dwarfs can be confirmed to be variable, then they can be subject to the time-intensive follow-up observations necessary to search for differences in their atmospheric structures
Early Network Attack Identification
No full textEarly attack identification is critical to secure the network exposed to various cyber-attack risks in modern times. Anomaly detection is also an important task, but devising a relevant strategy against the malicious event may be limited due to lacking attack information. For early attack identification, the main challenges are (1) imbalanced class data, (2) limited availability network datasets for early identification, and (3) determining variables to improve performance. To deal with these challenges, this research will explore early-identification of attacks with the following two angles: (1) Deep learning models including ANN, RNN; (2) Data augmentation for balanced data. Based on the analysis of the result of the experiments, this study will develop a deep learning model for early attack identification for validation purposes