"Army of One" to "Army Strong" : visual media and U.S. Army recruitment during Bush"s "War on Terror"

From Bush’s September 20, 2001 “War on Terror” speech to Congress to President-Elect Barack Obama’s acceptance speech on November 4, 2008, the U.S. Army produced visual recruitment material that addressed the concerns of falling enlistment numbers—due to the prolonged and difficult war in Iraq—with quickly-evolving and compelling rhetorical appeals: from the introduction of an “Army of One” (2001) to “Army Strong” (2006); from messages focused on education and individual identity to high-energy adventure and simulated combat scenarios, distributed through everything from printed posters and music videos to first-person tactical-shooter video games. These highly polished, professional visual appeals introduced to the American public during a time of an unpopular war fought by volunteers provide rich subject matter for research and analysis. This dissertation takes a multidisciplinary approach to the visual media utilized as part of the Army’s recruitment efforts during the War on Terror, focusing on American myths—as defined by Barthes—and how these myths are both revealed and reinforced through design across media platforms. Placing each selection in its historical context, this dissertation analyzes how printed materials changed as the War on Terror continued. It examines the television ad that introduced “Army Strong” to the American public, considering how the combination of moving image, text, and music structure the message and the way we receive it. This dissertation also analyzes the video game America’s Army, focusing on how the interaction of the human player and the computer-generated player combine to enhance the persuasive qualities of the recruitment message. Each chapter discusses how the design of the particular medium facilitates engagement/interactivity of the viewer. The conclusion considers what recruitment material produced during this time period suggests about the persuasive strategies of different media and how they create distinct relationships with their spectators. It also addresses how theoretical frameworks and critical concepts used by a variety of disciplines can be combined to analyze recruitment media utilizing a Selber inspired three literacy framework (functional, critical, rhetorical) and how this framework can contribute to the multimodal classroom by allowing instructors and students to do a comparative analysis of multiple forms of visual media with similar content.

Genetic association studies under the population stratification, family pedigree and application to genome-wide association studies

This dissertation has three separate parts: the first part deals with the general pedigree association testing incorporating continuous covariates; the second part deals with the association tests under population stratification using the conditional likelihood tests; the third part deals with the genome-wide association studies based on the real rheumatoid arthritis (RA) disease data sets from Genetic Analysis Workshop 16 (GAW16) problem 1. Many statistical tests are developed to test the linkage and association using either case-control status or phenotype covariates for family data structure, separately. Those univariate analyses might not use all the information coming from the family members in practical studies. On the other hand, the human complex disease do not have a clear inheritance pattern, there might exist the gene interactions or act independently. In part I, the new proposed approach MPDT is focused on how to use both the case control information as well as the phenotype covariates. This approach can be applied to detect multiple marker effects. Based on the two existing popular statistics in family studies for case-control and quantitative traits respectively, the new approach could be used in the simple family structure data set as well as general pedigree structure. The combined statistics are calculated using the two statistics; A permutation procedure is applied for assessing the p-value with adjustment from the Bonferroni for the multiple markers. We use simulation studies to evaluate the type I error rates and the powers of the proposed approach. Our results show that the combined test using both case-control information and phenotype covariates not only has the correct type I error rates but also is more powerful than the other existing methods. For multiple marker interactions, our proposed method is also very powerful. Selective genotyping is an economical strategy in detecting and mapping quantitative trait loci in the genetic dissection of complex disease. When the samples arise from different ethnic groups or an admixture population, all the existing selective genotyping methods may result in spurious association due to different ancestry distributions. The problem can be more serious when the sample size is large, a general requirement to obtain sufficient power to detect modest genetic effects for most complex traits. In part II, I describe a useful strategy in selective genotyping while population stratification is present. Our procedure used a principal component based approach to eliminate any effect of population stratification. The paper evaluates the performance of our procedure using both simulated data from an early study data sets and also the HapMap data sets in a variety of population admixture models generated from empirical data. There are one binary trait and two continuous traits in the rheumatoid arthritis dataset of Problem 1 in the Genetic Analysis Workshop 16 (GAW16): RA status, AntiCCP and IgM. To allow multiple traits, we suggest a set of SNP-level F statistics by the concept of multiple-correlation to measure the genetic association between multiple trait values and SNP-specific genotypic scores and obtain their null distributions. Hereby, we perform 6 genome-wide association analyses using the novel one- and two-stage approaches which are based on single, double and triple traits. Incorporating all these 6 analyses, we successfully validate the SNPs which have been identified to be responsible for rheumatoid arthritis in the literature and detect more disease susceptibility SNPs for follow-up studies in the future. Except for chromosome 13 and 18, each of the others is found to harbour susceptible genetic regions for rheumatoid arthritis or related diseases, i.e., lupus erythematosus. This topic is discussed in part III.