The research presented in this Honors Thesis provides development in machine learning models which predict future states of a system with unknown dynamics, based on observations of the system. Two case studies are presented for (1) a non-conservative pendulum and (2) a differential game dictating a two-car uncontrolled intersection scenario. In the paper we investigate how learning architectures can be manipulated for problem specific geometry. The result of this research provides that these problem specific models are valuable for accurate learning and predicting the dynamics of physics systems.<br/><br/>In order to properly model the physics of a real pendulum, modifications were made to a prior architecture which was sufficient in modeling an ideal pendulum. The necessary modifications to the previous network [13] were problem specific and not transferrable to all other non-conservative physics scenarios. The modified architecture successfully models real pendulum dynamics. This case study provides a basis for future research in augmenting the symplectic gradient of a Hamiltonian energy function to provide a generalized, non-conservative physics model.<br/><br/>A problem specific architecture was also utilized to create an accurate model for the two-car intersection case. The Costate Network proved to be an improvement from the previously used Value Network [17]. Note that this comparison is applied lightly due to slight implementation differences. The development of the Costate Network provides a basis for using characteristics to decompose functions and create a simplified learning problem.<br/><br/>This paper is successful in creating new opportunities to develop physics models, in which the sample cases should be used as a guide for modeling other real and pseudo physics. Although the focused models in this paper are not generalizable, it is important to note that these cases provide direction for future research.

High-entropy alloys possessing mechanical, chemical, and electrical properties that far exceed those of conventional alloys have the potential to make a significant impact on many areas of engineering. Identifying element combinations and configurations to form these alloys, however, is a difficult, time-consuming, computationally intensive task. Machine learning has revolutionized many different fields due to its ability to generalize well to different problems and produce computationally efficient, accurate predictions regarding the system of interest. In this thesis, we demonstrate the effectiveness of machine learning models applied to toy cases representative of simplified physics that are relevant to high-entropy alloy simulation. We show these models are effective at learning nonlinear dynamics for single and multi-particle cases and that more work is needed to accurately represent complex cases in which the system dynamics are chaotic. This thesis serves as a demonstration of the potential benefits of machine learning applied to high-entropy alloy simulations to generate fast, accurate predictions of nonlinear dynamics.

Exploration of a mouse model (C57BL/6J) capable of demonstrating behavioral changes after adolescent social isolation that are consistent with prior findings may prove beneficial in later research. This study examined 2 proposed long-term effects of isolated housing (one mouse/cage), when compared to group housing (two mice/cage) during adolescence. Mice were placed in their respective housing conditions after weaning (PND 21) and remained in those conditions until PND 60. The same cohorts were used in both phases of the experiment. Phase 1 sought to confirm previous findings that showed increases in ethanol intake after adolescent social isolation using a 2-bottle preference Drinking-in-the-Dark (DID) design over a 4-day period (PND 64-PND 67.). Phase 2 sought to elucidate the effects present after adolescent social isolation, as measured using response inhibition capabilities demonstrated during fixed-minimum interval (FMI) trials (PND 81-PND 111). Findings in phase 1 of the experiment were non-significant, save a strong tendency for female mice in both housing conditions to drink more as a proportion of their bodyweight (g/kg). However, a trend of lower bodyweight in single housed mice did exist, which does suggest that detrimental stress was applied via the used of adolescent isolation in that housing condition. Findings in phase 2 showed little effect of adolescent social isolation on mean inter-response time (IRT) at any criterion used (FMI-0, FMI-4, FMI-6). Evaluation of mean interquartile range (IQR) of IRTs showed a significantly greater amount of variation in IRT responses within single housed mice at the highest criterion (FMI-6), and a trend in the same direction when FMI-4 and FMI-6 were tested concurrently. Taken as a whole, the findings of this experiment suggest that the effect of adolescent social isolation on ethanol intake is far less robust than the effect of sex and may be difficult to replicate in a low-power study. Additionally, adolescent social isolation may interfere with the ability of mice to show consistent accuracy during FMI tasks or a delay in recognition of FMI criterion change.

Since the inception of what is now known as the Behavioral Analysis Unit (BAU) at the Federal Bureau of Investigation (FBI) in the 1970s, criminal profiling has become an increasingly prevalent entity in both forensic science and the popular imagination. The fundamental idea of which profiling is premised – behavior as a reflection of personality – has been the subject of a great deal of misunderstanding, with professionals and nonprofessionals alike questioning whether profiling represents an art or a science and what its function in forensic science should be. To provide a more thorough understanding of criminal profiling’s capabilities and its efficacy as a law enforcement tool, this thesis will examine the application of criminal profiling to investigations, various court rulings concerning profiling’s admissibility, and the role that popular media plays in the perception and function of the practice. It will also discuss how future research and regulatory advancements may strengthen criminal profiling’s scientific merit and legitimacy.

This thesis explores the potential for software to act as an educational experience for engineers who are learning system dynamics and controls. The specific focus is a spring-mass-damper system. First, a brief introduction of the spring-mass-damper system is given, followed by a review of the background and prior work concerning this topic. Then, the methodology and main approaches of the system are explained, as well as a more technical overview of the program. Lastly, a conclusion and discussion of potential future work is covered. The project was found to be useful by several engineers who tested it. While there is still plenty of functionality to add, it is a promising first attempt at teaching engineers through software development.

Glioblastoma (GB) is one of the deadliest cancers and the most common form of adult primary brain tumors. SGEF (ARHGEF26) has been previously shown to be overexpressed in GB tumors, play a role in cell invasion/migration, and increase temozolomide (TMZ) resistance.[3] It was hypothesized parental LN229 cell lines with SGEF knockdown (LN229-SGEFi) will show decreased metabolism in the MTS assay and decreased colony formation in a colony formation assay compared to parental LN229 cells after challenging the two cell lines with TMZ. For WB and co-immunoprecipitation (co-IP), parental LN229 cells with endogenous SGEF and BRCA were expected to interact and stain in the BRCA1:IP WB. LN229-SGEFi cells were expected to show very little SGEF precipitated due to shRNA targeted knockdown of SGEF. In conditions with mutations in the BRCA1 binding site (LN229-SGEFi + AdBRCAm/AdDM), SGEF expression was expected to decrease compared to parental LN229 or LN229-SGEFi cells reconstituted with WT SGEF (LN229-SGEFi + AdWT). LN229 infected with AdSGEF with a mutated nuclear localization signal (LN229-SGEFi + AdNLS12m) were expected to show BRCA and SGEF interaction since whole cell lysates were used for the co-IP. MTS data showed no significant differences in metabolism between the two cell lines at all three time points (3, 5, and 7 days). Western blot analysis was successful at imaging both SGEF and BRCA1 protein bands from whole cell lysate. The CFA showed no significant difference between cell lines after being challenged with 500uM TMZ. The co-IP immunoblot showed staining for BRCA1 and SGEF for all lysate samples, including unexpected lysates such as LN229-SGEFi, LN229-SGEFi + AdBRCAm, and LN229-SGEFi + AdDM. These results suggested either an indirect protein interaction between BRCA1 and SGEF, an additional BRCA binding site not included in the consensus, or possible detection of the translocated SGEF in knockdown cells lines since shRNA cannot enter the nucleus. Further optimization of CO-IP protocol, MTS assay, and CFA will be needed to characterize the SGEF/BRCA1 interaction and its role in cell survival.

Abortion is one of the most polarizing moral issues in our society today. This issue divides the country into two separate groups: Pro-choice or Pro-life. Our thesis analyzes published reviewed articles, media articles, policy papers, and perspective, opinion, and commentary pieces to discuss the ethical implications of selective abortion, specifically sex-selective abortion and genetic-selective abortion. Our thesis provides an overview of selective abortion, explores women’s bodily autonomy in the U.S., addresses the complexities of both sex-selective and genetic-selective abortion, and finally evaluates the U.S.’s regulation of selective abortion. Through these topics, we were able to determine the implications selective abortion has on the disabled community and how selective abortion is being used to ban abortion overall in the U.S.

Water quality and accessibility can impact most aspects of life such as hygiene, medicine,<br/>thermal comfort, sewage disposal, and health, to name a few. Rising concerns related to the<br/>quality of drinking water in the United States caused by municipal water utility failures such as<br/>in Texas or in Michigan has led to an inquiry into the root cause of how a supply-chain for a<br/>basic necessity such as water can run into issues. After initial research and investigation, one<br/>hypothesis for this was the nature of how recyclable materials in a linear economy eventually run<br/>into production or storage problems as exhaustible resources (or space) become less accessible<br/>over time. To remedy this issue, LifeGear360 is introduced to allow individual users the liberty<br/>to treat their water directly if needed, while also remaining in a circular economy for the<br/>lifecycle of the product. As a backpack with water treatment capabilities, natural plant fibers are<br/>used to ensure a renewable cycle of production while also redefining the traditional<br/>“plastic-taste” characteristics many people associate with water pouches to a smoother, cleaner<br/>taste. Engineering, sustainability, and business and public service practice have been used in an<br/>interdisciplinary way to prepare this product for its intended use such as in school, for travel, and<br/>for the outdoors. According to the collected outreach, many indicated that they feel as though<br/>there is a need for a product that allows for the feeling of water security which can include<br/>carrying any personal belongings as well. Marketing strategies such as logo creating and online<br/>outreach continually influence product design, up until production would take place following<br/>the finalized design.

Curiosity has been linked with many benefits, including increased overall well-being (Lydon-Staley et al., 2020) and greater academic achievement (Gottfried et al., 2016). The value that children place on learning new things and exploring novel ideas is unrivaled by older individuals. However, little research has been conducted to examine how parents may be able to help foster their children’s curiosity in a way that teaches them how to effectively search for and synthesize information. This paper aims to determine how parents’ language during a storybook task is related to their children’s strategy to collect rewards during a search game. Preliminary results suggest that parents may be able to encourage more effective search by asking more close-ended questions. These findings provide insight into how parents and guardians may be able to encourage their children to become better adept at searching for information by taking in clues about their environment and modifying their behavior to maximize their efforts.