Japan and the Ancient Western Classics: The Role of Divine Intervention in Greek Roman and Japanese Literature

This thesis explores the reasons for divine intervention in Greek, Roman, and Japanese literature and how it impacts the cultures and traditions of ancient Greece,Rome, and Japan. In the first chapter, I discuss the main motivations of divine intervention in human affairs in Homer’s Iliad. In the second chapter, I examine the lack of divine intervention in Lucan’s Bellum Civile and the changing attitudes toward the role of divinities. In the third chapter, I examine divine intervention in both the ancient mythology and contemporary folklore of Japan, and ask whether or not we can find its impact on traditional values incorporated in the country’s culture. I selected these three areas because divinities play a crucial role in the literature of all three civilizations. For ancient Greece and Rome, the epic genre taught values and traditions that many took seriously. For Japan, its mythology is considered history and important to the nation’s identity. I conclude this thesis with a comparison of all three civilizations and the meaning of divine intervention in literature as a general concept

Processing and Microstructural Characterization of Silicon Carbide, Silicon Nitride, and Tungsten Carbide Fibers

This research focuses on developing polymer-derived ceramic fibers. The spun micro/nanofibers were sintered into silicon carbide/silicon nitride and tungsten carbide respectively. The relationship between processing, fiber microstructure, morphology, and purity is investigated by scanning electron microscopy, Fourier transform infrared spectroscopy, energy-dispersive X-ray spectroscopy, and thermogravimetric analysis. Dynamic Mechanical Analysis was used to test the reinforcement capabilities of tungsten carbide fibers. EDS identified a near-perfect 1:1 Si-C ratio in silicon carbide fibers sintered between 1200 °C -1400 °C, Silicon carbide was confirmed by FTIR between 1000 °C – 1400 °C. Silicon Nitride peaks were noted in FTIR between 1200 °C – 1400 °C. Tungsten carbide nanofibers were confirmed by SEM, EDS, and FTIR for sintering temperatures 800 °C – 1000 °C. DMA results show an increase in mechanical properties as fiber wt % increases in the polymer-ceramic composites made

Changes of Winter Severity in Arkansas during 1901-2100

The objective of this study was to quantify the winter severity in a way that was reproduceable and easy to understand. The Accumulated Winter Severity Seasonal Index (AWSSI) was chosen for this reason and was used to quantify winter severity by season across the state of Arkansas. The variables that go into the AWSSI calculation are maximum daily temperature, minimum daily temperature, daily snowfall, and daily snow depth. When the snowfall and snow depth were missing, they can be estimated using daily temperature and precipitation. Then the estimated snowfall and snow depth can be subsequently used to quantify the winter severity. The AWSSI calculated this way is named as (Precipitation Accumulated Winter Severity Seasonal Index) pAWSSI. Our evaluations suggested that pAWSSI can reasonably reproduce the temporal variation of AWSSI. Due to scarce snowfall and snow depth data in Arkansas, this study used the pAWSSI to examine the spatial and temporal variations of winter severity in Arkansas from 1901-2012 based on observations and from 2012- 2100 based on multiple climate model simulations. The long-term averaged pAWSSI suggested more harsher winter in the north and northwest Arkansas. The state averaged AWSSI suggest notable interannual variability. The most severe winters occurred in late 1970s and earlier 1980s, likely due to several severe snow storms in these years. There is an overall weak downward trend before middle 1970s, followed by notable decreasing AWSSI scores, suggesting less harsher winters in recent decades. However, the start, end, and length of winter season in AR show weak spatial and temporal variations. The temporal variations in pAWSSI are largely controlled by winter temperature. There was less snowfall in warm winters and hence smaller pAWSSI. The decreasing pAWSSI (less cold winter) is associated with warming temperature, especially in the recent several decades. The temporal variations of pAWSSI are also influenced by large-scale atmospheric and oceanic indices. On interannual time scale, the winters with higher pAWSSI scores are usually associated with negative North Atlantic Oscillation (NAO) phases. The milder winters during 1990s and 2000s are associated with positive NAO phases. The pAWSSI is also significantly correlated with Pacific Decadal Oscillation (PDO) during 1948-2012. However, the link between PDO and pAWSSI weakened during recent two decades, suggested that the impacts of PDO on winter severity in Arkansas may change on decadal time scales. The daily temperature and precipitation from 20 CMIP5 models under the RCP8.5 scenario were also used to evaluate the winter severity in AR in the future. The pAWSSI for individual models was calculated. The ensemble mean pAWSSI of the 20 CMIP5 models show similar long-term averaged and trend as that based on observations during 1950-2012, suggesting that the models did a reasonable job in simulating the temporal variations of pAWSSI. The models projected accelerating decreasing trend in pAWSSI from 2006-2100, suggesting that the projected climate changes can cause pronounced decrease in winter severity. Compared to the present-day condition, the pAWSSI in Arkansas may decrease 65-75% by the end of this century

The Regulation of Mitochondrial Complex I Biogenesis in Drosophila Flight Muscles

Mitochondrial Complex I (CI) is composed of 44 distinct subunits that are assembled with eight Fe- S clusters and a single flavin mononucleotide. Mitochondria is highly enriched in the flight muscles of Drosophila melanogaster, however the assembly mechanism of Drosophila CI has not been described. We report that the mechanism of CI biogenesis in Drosophila flight muscles proceeds via the formation of ~315- , ~550-, and ~815 kDa CI assembly intermediates. Additionally, we define specific roles for several CI subunits in the assembly process. In particular, we show that dNDUFS5 is required for converting the ~700 kDa transient CI assembly intermediate into the ~815 kDa assembly intermediate, by stabilizing or promoting the incorporation of dNDUFA10 into the complex. Our findings highlight the potential values of Drosophila as a suitable model organism and resource to study the CI biogenesis in vivo, and to address questions relevant to CI biogenesis in humans. CI biogenesis is regulated by transient interactors known as CI assembly factors (CIAFs). To date, about half of CI disorders are attributed to the mutations in the CI subunits and the known CIAFs. The cause for the other half remains to be discovered, warranting the investigation for additional regulators of CI biogenesis such as novel CIAFs. To identify novel regulators, we cataloged interactors of a core subunit, NDUFS3, knocked each one down by RNAi in the Drosophila flight muscle, and analyzed its effect in the stability of CI by blue-native PAGE. We identified the Drosophila Fragile X Mental Retardation protein (dFMRP) to destabilize the holoenzyme of CI and cause it to misassemble. Therefore, we report dFMRP as a novel regulator of CI biogenesis, and demonstrate the utilization of Drosophila as an effective model system to uncover the mysteries of CI biogenesis

In vitro screening of the effect of three glucosinolate derived nitriles on soil-borne fungi

Glucosinolates are allelochemicals present in all plants of the order Capparales that are hydrolysed by endogenous enzymes (myrosinases) forming a variety of compounds with biological activity. ‘Biofumigation’ is the term used to describe the effect of these compounds on soil-borne pathogens and it has normally been attributed to isothiocyanates. At acidic pH and in the presence of redox co-factors such as glutathione, glucosinolate hydrolysis yields also nitriles, which are more hydrophilic and stable than isothiocyanates. Three nitriles (allyl-, benzyl- and phenethyl cyanide) were tested against soil borne fungi of economic importance: Aphanomyces euteiches var. pisi, Gaeumannomyces graminis var. tritici and Verticillium dahliae. The nitriles were initially tested at 1 mM and four additional concentrations were further tested in order to determine LD50. At 1 mM, allyl cyanide showed in all cases less than 10% inhibition and it did not inhibit fungi growth at higher concentrations. LD50 of benzyl cyanide was 2.5 mM for Verticillium and Aphanomyces, whereas it was as low as 0.5 mM for Gaeumannomyces. LD50 of phenyl ethyl cyanide was 2.5 mM for Verticillium, 1.4 mM Gaeumannomyces and 1.25 mM Aphanomyces. Although nitriles are generally less toxic than ITCs, their role in biofumigation should not be disregarded

A Senior Flute Recital

https://dc.ewu.edu/music_performances/1690/thumbnail.jp

Practical Hidden Voice Attacks against Speech and Speaker Recognition Systems

Voice Processing Systems (VPSes), now widely deployed, have been made significantly more accurate through the application of recent advances in machine learning. However, adversarial machine learning has similarly advanced and has been used to demonstrate that VPSes are vulnerable to the injection of hidden commands - audio obscured by noise that is correctly recognized by a VPS but not by human beings. Such attacks, though, are often highly dependent on white-box knowledge of a specific machine learning model and limited to specific microphones and speakers, making their use across different acoustic hardware platforms (and thus their practicality) limited. In this paper, we break these dependencies and make hidden command attacks more practical through model-agnostic (blackbox) attacks, which exploit knowledge of the signal processing algorithms commonly used by VPSes to generate the data fed into machine learning systems. Specifically, we exploit the fact that multiple source audio samples have similar feature vectors when transformed by acoustic feature extraction algorithms (e.g., FFTs). We develop four classes of perturbations that create unintelligible audio and test them against 12 machine learning models, including 7 proprietary models (e.g., Google Speech API, Bing Speech API, IBM Speech API, Azure Speaker API, etc), and demonstrate successful attacks against all targets. Moreover, we successfully use our maliciously generated audio samples in multiple hardware configurations, demonstrating effectiveness across both models and real systems. In so doing, we demonstrate that domain-specific knowledge of audio signal processing represents a practical means of generating successful hidden voice command attacks