Matching Items (283)
Description
This thesis focuses on the erotic depictions of Lucretia and Susanna in Renaissance art. Both noted for displaying exemplary chastity, Lucretia and Susanna gained popularity as Christian and secular role models for women in the late Middle Ages and Renaissance. My examination of the heroines addresses the seductive portrayal of these women in painting, which seemingly contradicts the essence of their celebrity. The images specifically analyzed in this thesis include: Lucas Cranach the Elder's Lucretia from 1525, Lucretia from 1533, and Venus from 1532 as well as Tintoretto's Susanna and the Elders and Annibale Carracci's Susanna and the Elders. The scope of my thesis includes both textual and visual analyses of the myths/figures and the disparity that arises between them. Employing Lucretia and Susanna as examples, my aim is to demonstrate a subtle subversion occurring within images of powerful women that ultimately strips them of their power.
ContributorsWilliamson, Jennifer Marie (Author) / Schleif, Corine (Thesis director) / Geschwind, Rachel (Committee member) / Pratt, Rebekah (Committee member) / Barrett, The Honors College (Contributor) / School of Social Transformation (Contributor) / School of Human Evolution and Social Change (Contributor) / School of Art (Contributor)
Created2013-05
Description
Science fiction themed video games, specifically Role Playing Games (RPGs) like Deus Ex: Human Revolution (DX:HR), that focus on an emerging technology, contain features that help to better inform anticipatory governance. In a game like DX:HR, players vicariously experience human-enhancement technology and its societal effects through their in-game character. Acting as the character, the player explores the topic of human-enhancement technology in various ways, including dialogue with non-player characters (NPCs) and decisions that directly affect the game's world. Because Deus Ex: Human Revolution and games similar to it, allow players to explore and think about the technology itself, the stances on it, and its potential societal effects, they facilitate the anticipatory governance process. In this paper I postulate a theory of anticipatory gaming, which asserts that video games inform the anticipatory governance process for an emerging technology. To demonstrate this theory I examine the parts of the anticipatory governance process and demonstrate RPG's ability to inform it, through a case study of Deus Ex: Human Revolution.
ContributorsShedd, Jesse Bernard (Author) / Wetmore, Jameson (Thesis director) / Fisher, Erik (Committee member) / McKnight, John Carter (Committee member) / Barrett, The Honors College (Contributor) / School of Human Evolution and Social Change (Contributor)
Created2013-05
Description
Surgery as a profession requires significant training to improve both clinical decision making and psychomotor proficiency. In the medical knowledge domain, tools have been developed, validated, and accepted for evaluation of surgeons' competencies. However, assessment of the psychomotor skills still relies on the Halstedian model of apprenticeship, wherein surgeons are observed during residency for judgment of their skills. Although the value of this method of skills assessment cannot be ignored, novel methodologies of objective skills assessment need to be designed, developed, and evaluated that augment the traditional approach. Several sensor-based systems have been developed to measure a user's skill quantitatively, but use of sensors could interfere with skill execution and thus limit the potential for evaluating real-life surgery. However, having a method to judge skills automatically in real-life conditions should be the ultimate goal, since only with such features that a system would be widely adopted. This research proposes a novel video-based approach for observing surgeons' hand and surgical tool movements in minimally invasive surgical training exercises as well as during laparoscopic surgery. Because our system does not require surgeons to wear special sensors, it has the distinct advantage over alternatives of offering skills assessment in both learning and real-life environments. The system automatically detects major skill-measuring features from surgical task videos using a computing system composed of a series of computer vision algorithms and provides on-screen real-time performance feedback for more efficient skill learning. Finally, the machine-learning approach is used to develop an observer-independent composite scoring model through objective and quantitative measurement of surgical skills. To increase effectiveness and usability of the developed system, it is integrated with a cloud-based tool, which automatically assesses surgical videos upload to the cloud.
ContributorsIslam, Gazi (Author) / Li, Baoxin (Thesis advisor) / Liang, Jianming (Thesis advisor) / Dinu, Valentin (Committee member) / Greenes, Robert (Committee member) / Smith, Marshall (Committee member) / Kahol, Kanav (Committee member) / Patel, Vimla L. (Committee member) / Arizona State University (Publisher)
Created2013
Description
This dissertation investigates the condition of skeletal muscle insulin resistance using bioinformatics and computational biology approaches. Drawing from several studies and numerous data sources, I have attempted to uncover molecular mechanisms at multiple levels. From the detailed atomistic simulations of a single protein, to datamining approaches applied at the systems biology level, I provide new targets to explore for the research community. Furthermore I present a new online web resource that unifies various bioinformatics databases to enable discovery of relevant features in 3D protein structures.
ContributorsMielke, Clinton (Author) / Mandarino, Lawrence (Committee member) / LaBaer, Joshua (Committee member) / Magee, D. Mitchell (Committee member) / Dinu, Valentin (Committee member) / Willis, Wayne (Committee member) / Arizona State University (Publisher)
Created2013
Description
The living world we inhabit and observe is extraordinarily complex. From the perspective of a person analyzing data about the living world, complexity is most commonly encountered in two forms: 1) in the sheer size of the datasets that must be analyzed and the physical number of mathematical computations necessary to obtain an answer and 2) in the underlying structure of the data, which does not conform to classical normal theory statistical assumptions and includes clustering and unobserved latent constructs. Until recently, the methods and tools necessary to effectively address the complexity of biomedical data were not ordinarily available. The utility of four methods--High Performance Computing, Monte Carlo Simulations, Multi-Level Modeling and Structural Equation Modeling--designed to help make sense of complex biomedical data are presented here.
ContributorsBrown, Justin Reed (Author) / Dinu, Valentin (Thesis advisor) / Johnson, William (Committee member) / Petitti, Diana (Committee member) / Arizona State University (Publisher)
Created2012
Description
Critical care environments are complex in nature. Fluctuating team dynamics and the plethora of technology and equipment create unforeseen demands on clinicians. Such environments become chaotic very quickly due to the chronic exposure to unpredictable clusters of events. In order to cope with this complexity, clinicians tend to develop ad-hoc adaptations to function in an effective manner. It is these adaptations or "deviations" from expected behaviors that provide insight into the processes that shape the overall behavior of the complex system. The research described in this manuscript examines the cognitive basis of clinicians' adaptive mechanisms and presents a methodology for studying the same. Examining interactions in complex systems is difficult due to the disassociation between the nature of the environment and the tools available to analyze underlying processes. In this work, the use of a mixed methodology framework to study trauma critical care, a complex environment, is presented. The hybrid framework supplements existing methods of data collection (qualitative observations) with quantitative methods (use of electronic tags) to capture activities in the complex system. Quantitative models of activities (using Hidden Markov Modeling) and theoretical models of deviations were developed to support this mixed methodology framework. The quantitative activity models developed were tested with a set of fifteen simulated activities that represent workflow in trauma care. A mean recognition rate of 87.5% was obtained in automatically recognizing activities. Theoretical models, on the other hand, were developed using field observations of 30 trauma cases. The analysis of the classification schema (with substantial inter-rater reliability) and 161 deviations identified shows that expertise and role played by the clinician in the trauma team influences the nature of deviations made (p<0.01). The results shows that while expert clinicians deviate to innovate, deviations of novices often result in errors. Experts' flexibility and adaptiveness allow their deviations to generate innovative ideas, in particular when dynamic adjustments are required in complex situations. The findings suggest that while adherence to protocols and standards is important for novice practitioners to reduce medical errors and ensure patient safety, there is strong need for training novices in coping with complex situations as well.
ContributorsVankipuram, Mithra (Author) / Greenes, Robert A (Thesis advisor) / Patel, Vimla L. (Thesis advisor) / Petitti, Diana B. (Committee member) / Dinu, Valentin (Committee member) / Smith, Marshall L. (Committee member) / Arizona State University (Publisher)
Created2012
Description
This work involved the analysis of a public health system, and the design, development and deployment of enterprise informatics architecture, and sustainable community methods to address problems with the current public health system. Specifically, assessment of the Nationally Notifiable Disease Surveillance System (NNDSS) was instrumental in forming the design of the current implementation at the Southern Nevada Health District (SNHD). The result of the system deployment at SNHD was considered as a basis for projecting the practical application and benefits of an enterprise architecture. This approach has resulted in a sustainable platform to enhance the practice of public health by improving the quality and timeliness of data, effectiveness of an investigation, and reporting across the continuum.
ContributorsKriseman, Jeffrey Michael (Author) / Dinu, Valentin (Thesis advisor) / Greenes, Robert (Committee member) / Johnson, William (Committee member) / Arizona State University (Publisher)
Created2012
Description
Immunosignaturing is a technology that allows the humoral immune response to be observed through the binding of antibodies to random sequence peptides. The immunosignaturing microarray is based on complex mixtures of antibodies binding to arrays of random sequence peptides in a multiplexed fashion. There are computational and statistical challenges to the analysis of immunosignaturing data. The overall aim of my dissertation is to develop novel computational and statistical methods for immunosignaturing data to access its potential for diagnostics and drug discovery. Firstly, I discovered that a classification algorithm Naive Bayes which leverages the biological independence of the probes on our array in such a way as to gather more information outperforms other classification algorithms due to speed and accuracy. Secondly, using this classifier, I then tested the specificity and sensitivity of immunosignaturing platform for its ability to resolve four different diseases (pancreatic cancer, pancreatitis, type 2 diabetes and panIN) that target the same organ (pancreas). These diseases were separated with >90% specificity from controls and from each other. Thirdly, I observed that the immunosignature of type 2 diabetes and cardiovascular complications are unique, consistent, and reproducible and can be separated by 100% accuracy from controls. But when these two complications arise in the same person, the resultant immunosignature is quite different in that of individuals with only one disease. I developed a method to trace back from informative random peptides in disease signatures to the potential antigen(s). Hence, I built a decipher system to trace random peptides in type 1 diabetes immunosignature to known antigens. Immunosignaturing, unlike the ELISA, has the ability to not only detect the presence of response but also absence of response during a disease. I observed, not only higher but also lower peptides intensities can be mapped to antigens in type 1 diabetes. To study immunosignaturing potential for population diagnostics, I studied effect of age, gender and geographical location on immunosignaturing data. For its potential to be a health monitoring technology, I proposed a single metric Coefficient of Variation that has shown potential to change significantly when a person enters a disease state.
ContributorsKukreja, Muskan (Author) / Johnston, Stephen Albert (Thesis advisor) / Stafford, Phillip (Committee member) / Dinu, Valentin (Committee member) / Arizona State University (Publisher)
Created2012
Description
This paper studies the change in social diversity and interaction space from the Classic to Postclassic periods in the Mimbres Valley and East Mimbres Area. Between the Classic and Postclassic periods the Mimbres region of the American Southwest exhibits an increase in diversity of ceramic wares. Previous research suggests that increased diversity of ceramics indicates a more diverse community, which could pose challenges to local social interaction (Nelson et al. 2011). I am interested in whether the architecture of plazas, focal points of communities' social structures, change in response to the growing social diversity. To examine this, I quantify the diversity of painted ceramics at Classic and Postclassic villages as well as the extent of the enclosure of plazas. I find that there is a definite shift towards greater plaza enclosure between the Classic and Postclassic periods. I conclude this paper with a discussion of possible interpretations of this trend regarding the social reactions of Mimbres communities to the changes which reshaped the region between the Classic and Postclassic periods.
ContributorsHarkness, Rebecca Jean (Author) / Nelson, Margaret (Thesis director) / Hegmon, Michelle (Committee member) / Barrett, The Honors College (Contributor) / School of Human Evolution and Social Change (Contributor) / School of Historical, Philosophical and Religious Studies (Contributor)
Created2015-05
Description
Background: Both puberty and diets composed of high levels of saturated fats have been shown to result in central adiposity, fasting hyperinsulinemia, insulin resistance and impaired glucose tolerance. While a significantly insulinogenic phenotypic change occurs in these two incidences, glucose homeostasis does not appear to be affected. Methods: Male, Sprague-dawley rats were fed diets consisting of CHOW or low fat (LF), High Fat Diet and High Fat Diet (HFD) with supplementary Canola Oil (Monounsaturated fat). These rats were given these diets at 4-5 weeks old and given intraperitoneal and oral glucose tolerance tests(IPGTT; OGTT) at 4 and 8 weeks to further understand glucose and insulin behavior under different treatments. (IPGTT: LF-n=14, HFD-n=16, HFD+CAN-n=12; OGTT: LF-n=8, HFD-n=8, HFD+CAN-n=6). Results: When comparing LF fed rats at 8 weeks with 4 week glucose challenge test, area under the curve (AUC) of glucose was 1.2 that of 4 weeks. At 8 weeks, HFD fed rats AUCg was much greater than LF fed rats under both IPGTT and OGTT. When supplemented with Canola oil, HFD fed rats AUC returned to LF data range. Despite the alleviating glucose homeostasis affects of Canola oil the AUC of insulin curve, which was elevated by HFD, remained high. Conclusion: HFD in maturing rats elevates fasting insulin levels, increases insulin resistance and lowers glucose homeostasis. When given a monounsaturated fatty acid (MUFA) supplement fasting hyperinsulinemia, and late hyperinsulinemia still occur though glucose homeostasis is regained. For OGTT HFD also induced late hyper c-peptide levels and compared to LF and HFD+CAN, a higher c-peptide level over time.
ContributorsRay, Tyler John (Author) / Caplan, Michael (Thesis director) / Herman, Richard (Committee member) / Towner, Kali (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor) / W. P. Carey School of Business (Contributor) / School of Human Evolution and Social Change (Contributor)
Created2015-05