Dissertation Defense Announcements

Sexually transmitted infections (STIs) affect an estimated 347 million people worldwide. These diseases can potentially incur significant long-term negative health outcomes, including lifetime treatment regimens, cancer, or infertility. Outcome severity, clinical manifestations, and acquisition rates show a sexually dimorphic variability, with women experiencing a higher disease burden than men. While the exact mechanism for this disparity is unknown, it is likely due to a combination of biological and social influences disproportionately affecting the sexes. This study investigates some of these gendered variables, particularly those involving birth control and sexual healthcare, and their relationship with STI acquisition. Data analysis using the National Health and Nutritional Examination Survey, and a cross-sectional sexual health survey disseminated to college women concluded that women in the United States follow the classic gendered trend with higher rates of STIs. Our cross-sectional sexual health survey included information from 522 sexually active women. We found significant associations regarding a positive self-reported STI history with sexual partner number and inconsistent screening frequency. We also found associations between women who do use some form of hormonal contraceptive with condom use, STI screening frequency, and age. Free-response questions also gave us qualitative insight regarding comfort with sexual health physicians, feelings regarding positive STI diagnosis, and physician’s approach toward their positive STI history. This study addressed several variables associated with women's sexual health care and outcomes and was able to identify several risk factors that may influence the gendered disparity we see in STI prevalence.

Additive manufacturing (AM), particularly laser powder bed fusion (LPBF), is of great interest to the aerospace community as it can be used to manufacture parts with complex internal and external geometries. This is in contrast to conventional manufacturing methods that limit the complexity of part designs. Of particular interest are the manufacture of parts with cooling channels consisting of complex surface topographies designed to improve thermal performance of the channels. While conventional machining can reduce the roughness of external surfaces, most surface treatment processes cannot be applied to internal channels, especially when the dimensions are a millimeter or submillimeter scale. Additive manufacturing offers an alternative that has the potential to overcome this limitation.
For a successful industrial adoption of AM for parts requiring complex cooling channels, an understanding of the relationship between the as-built surface finish and heat transfer is needed. In LPBF, there are numerous build parameters, such as part orientation during the build, that affect the final part surface topography and hence heat transfer. The classic literature on the impact of surface roughness on heat transfer (Moody's diagram) uses a simplified treatment of surface roughness, while powder bed fusion processes generate complex surfaces with strong anisotropic features, spatter, and surface and subsurface defects, all of which may affect heat transfer and fluid flow.
The primary focus of this work is to study the effects of AM roughness characteristics (build orientations, density of spatter deposits and their sizes, amplitudes/wavelengths, etc.) on heat transfer from the corresponding AM surfaces and pressure drop across cooling channels. Both numerical and experimental investigations are carried out for this purpose. Computational Fluid Dynamics (CFD) models for mini-channels using StarCCM+ (a commercial CFD code) were developed by acquiring the roughness data from real AM surfaces with various roughness parameters. To explore the correlation between sand-grain modeled roughness and AM surface roughness with 90° build orientation, CFD simulations for the entire system model (experimental setup) were employed. Further, CFD modeling of mini-channels with different wavy surfaces helped in determining the suitable dimensions for the mini-channel experimental set-up and the range of Reynolds numbers necessary for carrying out relevant experiments. Based on CFD findings, an exchangeable experimental setup was developed and on the basis of roughness characterizations, the AM parts with three critical orientations (0°, 45°, and 90°) were fabricated and then machined to the required shape and size to fit into the set-up. In addition, an Inconel part with a smooth surface has been machined from a forged Inconel-625 circular bar to serve as the baseline control condition.
Both CFD and experimental results were compared for different Reynolds numbers. The experimental results validated the CFD findings. Significant differences in the Nusselt numbers and pressure drops were observed across the different AM surfaces, with the surface with 90° build orientation performing best in terms of heat transfer. Based on these results, further investigation on the effects of 90° weld tracked surfaces in a circular form was also carried out. For this exploration, two aluminum (Al-6061) channels - one with a smooth surface and the other with internal threads serving as artificial waviness, similar to an AM surface with a 90° build orientation to the fluid flow direction - were conventionally manufactured and both CFD and experimental investigations were carried out for different mass flow rates. Both CFD and experimental results show that the artificial waviness (structured surfaces) has a significant impact on heat transfer and leads to a high cooling efficiency with a Nusselt number approximately 3x larger for various flow conditions compared to the smooth channel. However, the intentional structured surface also leads to larger pressure drops and may require extra pumping power, depending upon the application.

ABSTRACT

Reexamining Intra Team Conflict: A Dyadic Perspective

Conflict is seen as an emergent process when looking at the construct of the team as a whole. Researchers have investigated the interpersonal dynamics that contribute to intrateam conflict. According to researchers, intrateam conflict may be the result of conflict that arises from interactions between members of the team on a dyadic level. The dyadic perspective works under the assumption that conflicts can arise between individual members of a team. Researchers have focused on the perspective of the team rather than the dyadic perspective. In fact, many previous studies have concentrated on conflict and the causes of conflict within the team. However, more recently, there have been studies that lend support to the idea that dyadic conflict is one of the primary sources of conflict within teams. There is a possibility that various members of the same team will experience varying degrees of conflict with the other members of the team. It is possible that members of the team will perceive an increase in the amount of conflict between one another. This research contributed to the perception of generalized and dyadic reciprocity among the members of the team. The Social Relations Model (SRM) round robin design will be utilized in the execution of this study, which will take place in a real-world environment. This study will address the dyadic relationship between team members by using this design. It will rate the team members individually as well as the team as a whole, and it will report on each individual team member. In addition, the survey will include information on demographics, questions to assess dyadic task and relationship conflict, as well as questions regarding Jehn and Mannix's research on team level conflict. The results will be analyzed using the TripleR package in R statistical analysis software.

Keywords: Dyadic conflict, Conflict, Team level construct, Social Relations Model

This dissertation explores the potential of natural language models, including large language models, to extract causal relations from medical texts, specifically from Clinical Practice Guidelines. The outcomes of causality extraction from Clinical Practice Guidelines on gestational diabetes are presented, marking a first in the field. We also release, the first of its kind, an annotated corpus of causal statements in the Clinical Practice Guidelines.
We address the challenge of classifying causal sentences with a small amount of annotated data at the inter-sentence level by treating it as a cross-domain transfer learning problem. Obtaining these classified sentences is the first step in extracting causality. Furthermore, we delve into the importance of modal verbs and the degree of influence from cause to effect. We show the capability of three models (BERT, DistilBERT, and BioBERT) to identify the degree of influence in the text.
Lastly, we tackle the challenge of sparse annotated data for the causality extraction from Clinical Practice Guidelines by, again, using transfer learning. We investigate the correlation between data similarity and the efficacy of transfer learning. We also investigate a zero-shot and few-shot approach to cross-domain transfer learning and quantify the link between data similarity and success rates. With the cross-domain few-shot transfer learning, we achieve an F1-score of 81%, which suggests transfer learning as a possible solution to address the limited availability of annotated data.