Reducing the amount of error and introduced data variability increases the accuracy of Western blot results. In this study, different methods of normalization for loading differences and data alignment were explored with respect to their impact on Western blot results. GAPDH was compared to the LI-COR Revert total protein stain as a loading control. The impact of normalizing data to a control condition, which is commonly done to align Western blot data distributed over several immunoblots, was also investigated. Specifically, this study addressed whether normalization to a small subset of distinct controls on each immunoblot increases pooled data variability compared to a larger set of controls. Protein expression data for NOX-2 and SOD-2 from a study investigating the protective role of the bradykinin type 1 receptor in angiotensin-II induced left ventricle remodeling were used to address these questions but are also discussed in the context of the original study. The comparison of GAPDH and Revert total protein stain as a loading control was done by assessing their correlation and comparing how they affected protein expression results. Additionally, the impact of treatment on GAPDH was investigated. To assess how normalization to different combinations of controls influences data variability, protein data were normalized to the average of 5 controls, the average of 2 controls, or an average vehicle and the results by treatment were compared. The results of this study demonstrated that GAPDH expression is not affected by angiotensin-II or bradykinin type 1 receptor antagonist R-954 and is a less sensitive loading control compared to Revert total protein stain. Normalization to the average of 5 controls tended to reduce pooled data variability compared to 2 controls. Lastly, the results of this study provided preliminary evidence that R-954 does not alter the expression of NOX-2 or SOD-2 to an expression profile that would be expected to explain the protection it confers against Ang-II induced left ventricle remodeling.

The Electoral College, the current electoral system in the U.S., operates on a Winner-Take-All or First Past the Post (FPTP) principle, where the candidate with the most votes wins. Despite the Electoral College being the current system, it is problematic. According to Lani Guinier in Tyranny of the Majority, “the winner-take-all principle invariably wastes some votes” (121). This means that the majority group gets all of the power in an election while the votes of the minority groups are completely wasted and hold little to no significance. Additionally, FPTP systems reinforce a two-party system in which neither candidate could satisfy the majority of the electorate’s needs and issues, yet forces them to choose between the two dominant parties. Moreover, voting for a third party candidate only hurts the voter since it takes votes away from the party they might otherwise support and gives the victory to the party they prefer the least, ensuring that the two party system is inescapable. Therefore, a winner-take-all system does not provide the electorate with fair or proportional representation and creates voter disenfranchisement: it offers them very few choices that appeal to their needs and forces them to choose a candidate they dislike. There are, however, alternative voting systems that remedy these issues, such as a Ranked voting system, in which voters can rank their candidate choices in the order they prefer them, or a Proportional voting system, in which a political party acquires a number of seats based on the proportion of votes they receive from the voter base. Given these alternatives, we will implement a software simulation of one of these systems to demonstrate how they work in contrast to FPTP systems, and therefore provide evidence of how these alternative systems could work in practice and in place of the current electoral system.

System and software verification is a vital component in the development and reliability of cyber-physical systems - especially in critical domains where the margin of error is minimal. In the case of autonomous driving systems (ADS), the vision perception subsystem is a necessity to ensure correct maneuvering of the environment and identification of objects. The challenge posed in perception systems involves verifying the accuracy and rigidity of detections. The use of Spatio-Temporal Perception Logic (STPL) enables the user to express requirements for the perception system to verify, validate, and ensure its behavior; however, a drawback to STPL involves its accessibility. It is limited to individuals with an expert or higher-level knowledge of temporal and spatial logics, and the formal-written requirements become quite verbose with more restrictions imposed. In this thesis, I propose a domain-specific language (DSL) catered to Spatio-Temporal Perception Logic to enable non-expert users the ability to capture requirements for perception subsystems while reducing the necessity to have an experienced background in said logic. The domain-specific language for the Spatio-Temporal Perception Logic is built upon the formal language with two abstractions. The main abstraction captures simple programming statements that are translated to a lower-level STPL expression accepted by the testing monitor. The STPL DSL provides a seamless interface to writing formal expressions while maintaining the power and expressiveness of STPL. These translated equivalent expressions are capable of directing a standard for perception systems to ensure the safety and reduce the risks involved in ill-formed detections.

This thesis identifies and explains two main problems students face during their internships. The first problem relates to feeling bored at internships due to the simplicity of projects or lack of work. From the interviews conducted, several strategies to avoid this boredom were created, including having employers design education plans for interns to further their knowledge in programs such as excel during their downtime. The second problem with internships discovered focuses on the gap between what is taught in schools versus what is expected of interns in practice. This thesis identifies several opportunities for improvement in education and strategies on how to handle feeling overwhelmed on intern projects due to lack of knowledge.

The market for searching for food online is exploding. According to one expert at Google, “there are over 1 billion restaurant searches on Google every month” (Kelso, 2020). To capture this market and ride the general digital trend of internet personalization (as evidenced by Google search results, ads, YouTube and social media algorithms, etc), we created Munch to be an algorithm meant to help people find food they’ll love. <br/><br/>Munch offers the ability to search for food by restaurant or even as specific as a menu item (ex: search for the best Pad Thai). The best part? It is customized to your preferences based on a quiz you take when you open the app and from that point continuously learns from your behavior.<br/><br/>This thesis documents the journey of the team who founded Munch, what progress we made and the reasoning behind our decisions, where this idea fits in a competitive marketplace, how much it could be worth, branding, and our recommendations for a successful app in the future.

Animals encounter information from different resources simultaneously, integrating input from multiple sensory systems before responding behaviorally. When different cues interact with one another, they may enhance, diminish, or have no impact on their responses. In this project, we test how the presence of chemical cues affect the perception of visual cues. Zebrafish (Danio rerio) often use both chemical cues and visual cues to communicate with shoal mates, to assess predation risk, and to locate food. For example, zebrafish rely on both olfactory cues and visual cues for kin recognition, and they frequently use both chemical and visual cues to search for and to capture prey. In zebrafish, the terminal nerve (TN) constitutes the olfacto-visual centrifugal pathway and connects the olfactory bulb with the retina, thus allowing olfactory perception also to activate visual receptors. Past studies have found that the presence of an olfactory cue can modulate visual sensitivity in zebrafish through the terminal nerve pathway. Alternatively, given that zebrafish are highly social, the presence of social chemical cues may distract individuals from responding to other visual cues, such as food and predator visual cues. Foraging and predator chemical cues, including chemical food cues and alarm cues, may also distract individuals from responding to non-essential visual cues. Here, we test whether the response to a visual cue either increases or decreases when presented in concert with alanine, an amino acid that represents the olfactory cues of zebrafish prey. We found that the presence of chemical cues did not affect whether zebrafish responded to visual cues, but that the fish took longer to respond to visual cues when chemical cues were also present. These findings suggest that different aspects of behavior could be affected by the interaction between sensory modalities. We also found that this impact of delayed response was significant only when the visual cue<br/>was weak compared to the strength of the chemical cue, suggesting that the salience of interacting cues may also have an influence on determining the outcomes of the interactions. Overall, the interactive effects of chemicals on an animal’s response to visual cues may also have wide-ranging impacts on behavior including foraging, mating, and evading predators, and the interaction of cues may affect different aspects of the same behavior.

Humans use emotions to communicate social cues to our peers on a daily basis. Are we able to identify context from facial expressions and match them to specific scenarios? This experiment found that people can effectively distinguish negative and positive emotions from each other from a short description. However, further research is needed to find out whether humans can learn to perceive emotions only from contextual explanations.

Locusts are generalist herbivores meaning that they are able to consume a variety of plants. Because of their broad diet, and ability to respond rapidly to a favorable environment with giant swarms of voracious insects, they are dangerous pests. Their potential impacts on humans increase dramatically when individuals switch from their solitarious phase to their gregarious phase where they congregate and begin marching and eventually swarming together. These swarms, often billions strong, can consume the vegetation of enormous swaths of land and can travel hundreds of kilometers in a single day producing a complex threat to food security. To better understand the biology of these important pests we explored the gut microbiome of the South American locust (Schistocerca cancellata). We hypothesized generally that the gut microbiome in this species would be critically important as has been shown in many other species. We extracted and homogenized entire guts from male S. cancellata, and then extracted gut microbiome genomic DNA. Genomic DNA was then confirmed on a gel. The initial extractions were of poor quality for sequencing, but subsequent extractions performed by collaborators during troubleshooting at Southern Illinois University Edwardsville proved more useful and were used for PCR. This resulted in the detections of the following bacterial genera in the gut of S. cancellata: Enterobacter, Enterococcus, Serratia, Pseudomonas, Actinobacter, and Weisella. With this data, we are able to speculate about the physiological roles that they hold within the locust gut generating hypotheses for further testing. Understanding the microbial composition of this species’ gut may help us better understand the locust in general in an effort to more sustainably manage them.

CubeSats can encounter a myriad of difficulties in space like cosmic rays, temperature<br/>issues, and loss of control. By creating better, more reliable software, these problems can be<br/>mitigated and increase the chance of success for the mission. This research sets out to answer the<br/>question: how do we create reliable flight software for CubeSats? by providing a concentrated<br/>list of the best flight software development practices. The CubeSat used in this research is the<br/>Deployable Optical Receiver Aperture (DORA) CubeSat, which is a 3U CubeSat that seeks to<br/>demonstrate optical communication data rates of 1 Gbps over long distances. We present an<br/>analysis over many of the flight software development practices currently in use in the industry,<br/>from industry leads NASA, and identify three key flight software development areas of focus:<br/>memory, concurrency, and error handling. Within each of these areas, the best practices were<br/>defined for how to approach the area. These practices were also developed using experience<br/>from the creation of flight software for the DORA CubeSat in order to drive the design and<br/>testing of the system. We analyze DORA’s effectiveness in the three areas of focus, as well as<br/>discuss how following the best practices identified helped to create a more reliable flight<br/>software system for the DORA CubeSat.

Over 40% of adults in the United States are considered obese. Obesity is known to cause abnormal metabolic effects and lead to other negative health consequences. Interestingly, differences in metabolism and contractile performance between obese and healthy weight individuals are associated with differences in skeletal muscle fiber type composition between these groups. Each fiber type is characterized by unique metabolic and contractile properties, which are largely determined by the myosin heavy chain isoform (MHC) or isoform combination that the fiber expresses. In previous studies, SDS-PAGE single fiber analysis has been utilized as a method to determine MHC isoform distribution and single fiber type distribution in skeletal muscle. Herein, a methodological approach to analyze MHC isoform and fiber type distribution in skeletal muscle was fine-tuned for use in human and rodent studies. In the future, this revised methodology will be implemented to evaluate the effects of obesity and exercise on the phenotypic fiber type composition of skeletal muscle.