Programming is quickly becoming as ubiquitous a tool as general mathematics. The technology field is progressing at an exponential rate and driving this constantly evolving field forward requires competent software developers. Elementary and high school educational facilities do not currently express the importance of the computer science field. Computer science is not a required course in high school and nearly impossible to find at a middle school level. This lack of exposure to the field at a young age handicaps aspiring developers by not providing them with a foundation to build on when seeking a degree. This paper revolves around the development of a virtual world that encompasses principles of programming in a video game structure. The use of a virtual world-based game was chosen under the hypothesis that embedding programming instruction into a game through problem-based learning is more likely to engage young students than more traditional forms of instruction. Unlike the traditional method of instruction, a virtual world allows us to "deceive" the player into learning concepts by implicitly educating them through fun gameplay mechanics. In order to make our video game robust and self-sufficient, we have developed a predictive recursive descent parser that will validate any user-generated solutions to pre-defined logical platforming puzzles. Programming topics taught with these problems range from binary numbers to while and for loops.

Valley Fever, also known as coccidioidomycosis, is a respiratory disease that affects 10,000 people annually, primarily in Arizona and California. Due to a lack of gene annotation, diagnosis and treatment of Valley Fever is severely limited. In turn, gene annotation efforts are also hampered by incomplete genome sequencing. We intend to use proteogenomic analysis to reannotate the Coccidioides posadasii str. Silveira genome from protein-level data. Protein samples extracted from both phases of Silveira were fragmented into peptides, sequenced, and compared against databases of known and predicted proteins sequences, as well as a de novo six-frame translation of the genome. 288 unique peptides were located that did not match a known Silveira annotation, and of those 169 were associated with another Coccidioides strain. Additionally, 17 peptides were found at the boundary of, or outside of, the current gene annotation comprising four distinct clusters. For one of these clusters, we were able to calculate a lower bound and an estimate for the size of the gap between two Silveira contigs using the Coccidioides immitis RS transcript associated with that cluster's peptides \u2014 these predictions were consistent with the current annotation's scaffold structure. Three peptides were associated with an actively translated transposon, and a putative active site was located within an intact LTR retrotransposon. We note that gene annotation is necessarily hindered by the quality and level of detail in prior genome sequencing efforts, and recommend that future studies involving reannotation include additional sequencing as well as gene annotation via proteogenomics or other methods.

Learning to program is no easy task, and many students experience their first programming during their university education. Unfortunately, programming classes have a large number of students enrolled, so it is nearly impossible for professors to associate with the students at an individual level and provide the personal attention each student needs. This project aims to provide professors with a tool to quickly respond to the current understanding of the students. This web-based application gives professors the control to quickly ask Java programming questions, and the ability to see the aggregate data on how many of the students have successfully completed the assigned questions. With this system, the students are provided with extra programming practice in a controlled environment, and if there is an error in their program, the system will provide feedback describing what the error means and what steps the student can take to fix it.

The objective of this creative project was to gain experience in digital modeling, animation, coding, shader development and implementation, model integration techniques, and application of gaming principles and design through developing a professional educational game. The team collaborated with Glendale Community College (GCC) to produce an interactive product intended to supplement educational instructions regarding nutrition. The educational game developed, "Nutribots" features the player acting as a nutrition based nanobot sent to the small intestine to help the body. Throughout the game the player will be asked nutrition based questions to test their knowledge of proteins, carbohydrates, and lipids. If the player is unable to answer the question, they must use game mechanics to progress and receive the information as a reward. The level is completed as soon as the question is answered correctly. If the player answers the questions incorrectly twenty times within the entirety of the game, the team loses faith in the player, and the player must reset from title screen. This is to limit guessing and to make sure the player retains the information through repetition once it is demonstrated that they do not know the answers. The team was split into two different groups for the development of this game. The first part of the team developed models, animations, and textures using Autodesk Maya 2016 and Marvelous Designer. The second part of the team developed code and shaders, and implemented products from the first team using Unity and Visual Studio. Once a prototype of the game was developed, it was show-cased amongst peers to gain feedback. Upon receiving feedback, the team implemented the desired changes accordingly. Development for this project began on November 2015 and ended on April 2017. Special thanks to Laura Avila Department Chair and Jennifer Nolz from Glendale Community College Technology and Consumer Sciences, Food and Nutrition Department.

This study observes two fanfiction speech communities, Danny Phantom and Detective Conan. The members of these communities write stories based upon the canon within these two animated cartoons and interact with one another through reviews, author's notes, and story summaries. Using the speech community model, this community's unique practices and communicative repertoire will be identified and analyzed. Both of these fandoms show similarities with the overarching general fanfiction speech community, but they also possess key differences that define them as their own separate community. Fan jargon is used frequently in author's notes, reviews, and summaries to indicate fan expertise and membership within the fandom as well as exclude newcomers from understanding the information. This jargon remains largely the same across languages, and using it properly is important to being considered a true fan. Furthermore, many stories share similar elements that are not present within the source material, indicating that the fandoms possess a shared communicative repertoire. Review practices also show strong cultural norms that demand that reviewers offer praise and encouragement to the writers. Most criticism is phrased extremely kindly to avoid breaking cultural norms. Those who do not follow these cultural norms are shunned by the community, and required to apologize to maintain proper fan membership. Fan hierarchy is also examined, including the ways that big name fans and reviewers exert centripetal and centrifugal forces upon the language, simultaneously pushing it towards standardization and variation. Authors also use many face saving techniques to demonstrate their own lack of knowledge within the community, especially if they are new or inexperienced. The members of these communities share a deep cultural connection that is strengthened by their practices and repertoires.

Transient Receptor Potential Melastatin 8 (TRPM8) is a non-selective cation channel notable as a primary cold sensor in humans. It is also involved in a variety of (patho)physiological events including pain sensation, chronic cough, diabetes, obesity, and cancer. TRPM8 is modulated by a variety of stimuli including pH, temperature, cooling agents, voltage, lipid, and other proteins. However, the molecular mechanism underlining its function has not yet clear raising the need for isolated proteins to be well-characterized. Over 20 years, E. coli has been a heterologous expression system of interest due to its low cost and high yield. However, the lack of post-translational modifications and chaperone may cause a misfolding or affect protein function. Mammalian expression system addresses these drawbacks and is a good candidate for the functional study of complex human protein. Here I describe my research in optimizing the transfection, expression, and purification of the human TRPM8 from adherent Human Embryonic Kidney (HEK293) cells which can be used for small-scale studies including, but not limited to, planar lipid bilayer electrophysiology.

Methane (CH4) is very important in the environment as it is a greenhouse gas and important for the degradation of organic matter. During the last 200 years the atmospheric concentration of CH4 has tripled. Methanogens are methane-producing microbes from the Archaea domain that complete the final step in breaking down organic matter to generate methane through a process called methanogenesis. They contribute to about 74% of the CH4 present on the Earth's atmosphere, producing 1 billion tons of methane annually. The purpose of this work is to generate a preliminary metabolic reconstruction model of two methanogens: Methanoregula boonei 6A8 and Methanosphaerula palustris E1-9c. M. boonei and M. palustris are part of the Methanomicrobiales order and perform hydrogenotrophic methanogenesis, which means that they reduce CO2 to CH4 by using H2 as their major electron donor. Metabolic models are frameworks for understanding a cell as a system and they provide the means to assess the changes in gene regulation in response in various environmental and physiological constraints. The Pathway-Tools software v16 was used to generate these draft models. The models were manually curated using literature searches, the KEGG database and homology methods with the Methanosarcina acetivorans strain, the closest methanogen strain with a nearly complete metabolic reconstruction. These preliminary models attempt to complete the pathways required for amino acid biosynthesis, methanogenesis, and major cofactors related to methanogenesis. The M. boonei reconstruction currently includes 99 pathways and has 82% of its reactions completed, while the M. palustris reconstruction includes 102 pathways and has 89% of its reactions completed.

Speech recognition in games is rarely seen. This work presents a project, a 2D computer game named "The Emblems" which utilizes speech recognition as input. The game itself is a two person strategy game whose goal is to defeat the opposing player's army. This report focuses on the speech-recognition aspect of the project. The players interact on a turn-by-turn basis by speaking commands into the computer's microphone. When the computer recognizes a command, it will respond accordingly by having the player's unit perform an action on screen.

Bots tamper with social media networks by artificially inflating the popularity of certain topics. In this paper, we define what a bot is, we detail different motivations for bots, we describe previous work in bot detection and observation, and then we perform bot detection of our own. For our bot detection, we are interested in bots on Twitter that tweet Arabic extremist-like phrases. A testing dataset is collected using the honeypot method, and five different heuristics are measured for their effectiveness in detecting bots. The model underperformed, but we have laid the ground-work for a vastly untapped focus on bot detection: extremist ideal diffusion through bots.

The objective of this project concentrates on the game Defense of the Ancients 2 (Dota 2). In this game, players are constantly striving to improve their skills, which are fueled by the competitive nature of the game. The design influences the community to engage in this interaction as they play the game cooperatively. This thesis illustrates the importance of player interaction in influencing design as well as how imperative design is in affecting player interaction. These two concepts are not separate, but are deeply entwined. Every action performed within a game has to interact with some element of design. Both determine how games become defined as competitive, casual, or creative. Game designers can benefit from this study as it reinforces the basics of developing a game for players to interact with. However, it is impossible to predict exactly how players will react to a designed element. Designers should remember to tailor the game towards their audience, but also react and change the game depending on how players are using the elements of design. In addition, players should continue to push the boundaries of games to help designers adapt their product to their audience. If there is not constant communication between players and designers, games will not be tailored appropriately. Pushing the limits of a game benefits the players as well as the designers to make a more complete game. Designers do not solely create a game for the players. Rather, players design the game for themselves. Keywords: game design, player interaction, affinity space, emergent behavior, Dota 2