Consider Steven Cryos’ words, “When disaster strikes, the time to prepare has passed.” Witnessing domestic water insecurity in events such as Hurricane Katrina, the instability in Flint, Michigan, and most recently the winter storms affecting millions across Texas, we decided to take action. The period between a water supply’s disruption and restoration is filled with anxiety, uncertainty, and distress -- particularly since there is no clear indication of when, exactly, restoration comes. It is for this reason that Water Works now exists. As a team of students from diverse backgrounds, what started as an honors project with the Founders Lab at Arizona State University became the seed that will continue to mature into an economically sustainable business model supporting the optimistic visions and tenants of humanitarianism. By having conversations with community members, conducting market research, competing for funding and fostering progress amid the COVID-19 pandemic, our team’s problem-solving traverses the disciplines. The purpose of this paper is to educate our readers about a unique solution to emerging issues of water insecurity that are nested across and within systems who could benefit from the introduction of a personal water reclamation system, showcase our team’s entrepreneurial journey, and propose future directions that will this once pedagogical exercise to continue fulfilling its mission: To heal, to hydrate and to help bring safe water to everyone.

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.

In this creative thesis project I use digital “scrolleytelling” (an interactive scroll-based storytelling) to investigate diversity & inclusion at big tech companies. I wanted to know why diversity numbers were flatlining at Facebook, Apple, Amazon, Microsoft and Google, and took a data journalism approach to explore the relationship between what corporations were saying versus what they were doing. Finally, I critiqued diversity and inclusion by giving examples of how the current way we are addressing D&I is not fixing the problem.

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.