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Evaluating pregnancy termination rates for fetal chromosome and single gene disorders
No full textThe ability to detect genetic abnormalities prenatally has expanded in recent years to include a variety of diagnoses, including aneuploidy, copy number variants (CNVs), and single-gene disorders. The purpose of this study was to report on pregnancy termination rates following an abnormal prenatal diagnosis and to determine which factors may influence this decision. We conducted a retrospective chart review of 332 pregnancies diagnosed with a genetic abnormality from 2012-2023 and collected the type of prenatal diagnosis in addition to a variety of other factors. Data analysis consisted of multivariate logistic regression comparing each variable to the outcome of elective termination. In this study, the overall termination rate was 61.45%. Three variables remained strong predictors of elective termination: type of prenatal diagnosis, paternal race and/or ethnicity, and gestational age at diagnosis. This study adds to the literature on pregnancy termination rates following an abnormal prenatal diagnosis. Additionally, this expands our understanding of what other factors may influence the decision to terminate an affected pregnancy.M.S.Includes bibliographical reference
Genetic counseling toolkit for Vietnamese community outreach
No full textBackground. Genetic counseling and genetic testing can inform individuals of appropriate medical management for hereditary cancer predisposition syndromes, yet many underserved populations experience barriers to genetic services. The Vietnamese American community experiences disparities due to lack of physician referrals and culturally-sensitive educational materials. Culturally-tailored outreach programs can help overcome these barriers to increase awareness and uptake rates of genetic counseling for targeted populations. This project seeks to identify themes to inform the development of a successful outreach program for Vietnamese Americans and an outreach toolkit for cancer genetic counseling in the Vietnamese community.
Methods. A literature review was performed to learn how to develop an outreach toolkit for the Vietnamese community. Themes were extracted from the content of the articles pertaining to Vietnamese cultural concerns, methods for outreach, and culturally sensitive educational materials. A toolkit of five educational documents was developed based on these themes. This toolkit was sent out via an online anonymous survey to healthcare professionals for content feedback. Revisions were made based on feedback, and documents intended for a Vietnamese-literate audience were sent to a third party to be professionally translated.
Results. Seven major themes emerged from the literature review regarding considerations for outreach in the Vietnamese community, including: concerns of financial cost, limited language proficiency and health literacy, limitations with understanding the purpose of genetic services/preventive medicine, stigma associated with cancer/illness, value of community/family, strongly trusting recommendations from physicians, and the value of lay health workers. Feedback was obtained from six healthcare professionals and was overall positive with most suggestions focused on improving conciseness and cultural sensitivity of the content.
Discussion. A cancer genetic counseling outreach toolkit for the Vietnamese American population was developed that incorporated key cultural themes based on literature. More research is needed in the future regarding the toolkit’s effectiveness in this community.M.S.Includes bibliographical reference
Magical acts: stage magic, desire, and the experience of subjectivity
No full textMy dissertation examines the figures of the modern stage magician and the spiritual medium across the 20th and 21st century to discuss how they perform and unsettle theatrical spectatorship. I draw from anthropology, performance studies, and critical studies to connect these figures to modern constructions of selfhood, often against historically raced, class, and gendered cultural others. If magic, broadly speaking, generated the theoretical limits of Western civilization, what Randall Styers calls “the unthought of modernity,” then magic on stage encourages the spectator to reflect on one’s engagement with theatrical aesthetics as modern subjects. Magic’s performance of selfhood is an enduring and evolving project, and one that has been largely neglected in theater history and performance studies. My intervention shows how magic performances construct and manage desiring audiences and discipline their expectations of how to interact with the unknown. I show that performance magic should be considered a serious object of inquiry and that it can help scholars frame historical and contemporary spectatorship, aesthetic consumption, and identification.Ph.D.Includes bibliographical reference
Fairness in recommender systems
No full textAs one of the most pervasive applications of machine learning, recommender systems are playing an important role on assisting human decision making, which gives rise to essential concerns regarding the fairness of such systems. Research on fair machine learning has previously mainly focused on classification and ranking tasks. Although recommendation algorithm can usually be considered as a type of ranking algorithm, the fairness concerns in recommender systems are more complicated and should be extended to multiple stakeholders. In specific, different from only concerning item exposure fairness in ranking problem, we should also attach importance to the fairness demands of users in recommender systems. In this dissertation, we explore how to consider fairness requirements in the application of recommendation systems, and propose four works aiming to enhance user-side fairness in recommendation. The proposed works study fairness in recommendation from diverse and progressive perspectives. Experiments show that our fairness-aware methods can help enhance the fairness of recommender algorithms in various application scenarios.Ph.D.Includes bibliographical reference
Vitamin D binding protein: its role in vitamin D dysregulation and postsurgical outcomes
No full textVitamin D binding protein (DBP) is the major carrier for circulating vitamin D and plays an important role in regulating circulating total and free vitamin D metabolites. Since the concentration of DBP and its affinity to vitamin D is varied by different physiological and clinical conditions, only measuring total 25-hydroxyvitamin D (25OHD) may not accurately reflect functional vitamin D status. In addition, DBP is a potential prognostic indicator of clinical outcomes since it has other important functions beyond that as vitamin D carrier, including its role in actin scavenging and inflammation after tissue injury. It is hypothesized that circulating DBP is altered in patients with low vitamin D status and affects the concentration of total and free vitamin D metabolites and can explain postsurgical outcomes. The goal of this research, using two populations, one with primary hyperparathyroidism (PHPT) and the other with hip fracture, was to evaluate if DBP concentration and affinity are altered and determine whether they influence the total and free fraction of vitamin D metabolites and inflammation. In addition, another aim of this research was to examine underlying mechanisms related to DBP and determine whether circulating concentrations affect mortality and mobility in patients with hip fractures.
In a prospective study, we measured circulating free 25OHD levels in patients with PHPT and healthy controls (n=40/group). Circulating PTH was about 2.7 times higher and 25OHD was about 20% lower in patients with PHPT than controls. Total DBP was also lower (p < 0.05) in patients with PHPT, but not calculated or measured free 25OHD. In contrast, free fractions of serum 1,25(OH)2D were higher in patients than controls. In a subsequent study with larger population, blood samples were measured in a total of 70 patients before parathyroidectomy (PTX) and were measured again in a subset (n=28) after 3 months. In this second study of patients with PHPT, who also had low serum DBP and total 25OHD, serum interleukin-6 (IL-6) and monocyte chemoattractant protein-1 (MCP-1) were higher compared to controls (p < 0.01). The concentration of DBP was inversely correlated with intact parathyroid hormone (PTH) and IL-6 (p < 0.01), but not with other cytokines. Serum PTH and calcium reduced to the normal range by surgery. After PTX, total and free 25OHD and DBP levels were increased while concentrations of certain cytokines (IL-6 and MCP-1) decreased (p < 0.05) and not others such as C-reactive protein (CRP). In a prospective study to further examine DBP, we conducted a secondary analysis of 260 patients with hip fractures; mobility was assessed at 30 and 60 days and mortality at 60 days after repair surgery. Biochemical markers were measured before, and 2 to 4 days after surgery. Tissue injury markers were measured in 100 randomly selected patients and controls. Among all patients, the highest DBP tertile had greater mobility at 30 and 60 days and reduced mortality (P < 0.05) compared with the lowest tertile. Circulating DBP and gelsolin were lower, and IL-6, CRP, and F-actin were higher (P < 0.01) in patients compared to controls and worsened (P < 0.01) after surgery. Both IL-6 and CRP were inversely associated with DBP (P < 0.01).
Overall, our data support that the concentration and affinity of DBP is reduced by high PTH or hip fracture, and results in dysregulation of vitamin D metabolites. Thus, low vitamin D status is more complicated than the simple clinical definition of low total 25OHD. Only certain cytokines, MCP-1 and IL-6, are upregulated by PTH and that in turn may contribute to the reduction in DBP concentrations. PTX surgery not only decreases PTH, but also may affect clinical outcomes by decreasing IL-6 and MCP-1. In addition, the results from patients with hip fracture provide new evidence that higher DBP concentrations are associated with better postsurgical outcomes. This may due to the importance of DBP in actin scavenging system and its association with inflammation after tissue injury. The role of DBP as an acute phase reactant to tissue injury and clinical outcomes should be addressed in future studies.Ph.D.Includes bibliographical reference
Hypergeometric sheaves, Weil representations, and finite general linear groups
No full textAbhyankar’s conjecture, proved by Raynaud, Harbater and Pop, characterizes the finite quotient groups of the étale fundamental group of affine algebraic groups over algebraically closed fields of positive characteristic. Katz, Rojas-León and Tiep, in their recent series of papers, realized many of these groups as monodromy groups of certain “easy to remember” local systems over the affine line A1 and the multiplicative group Gm. On Gm, they used the hypergeometric sheaves to realize these groups. Furthermore, they classified the finite groups that can be possibly realized by irreducible hypergeometric sheaves.
In this dissertation, we give the complete solution of this problem for the hypergeometric sheaves and almost quasisimple groups with the unique nonabelian composition factor PSL(n,q) with n ≥ 3. Specifically, we fully generalize a construction of Katz and Tiep, and prove that there is no other irreducible hypergeometric sheaf with such geometric monodromy group. This includes several results about the irreducible Weil representations of GL(n,q). We also present analogous results on the Weil representations of GU(n,q), which is likely to be needed in the classification of the hypergeometric sheaves in the case of PSU(n,q).Ph.D.Includes bibliographical reference
Colonizing the landscape: memory, ritual, and perceptions of place in seventeenth-century Maine
No full textThis dissertation analyzes the landscape history of English colonization in seventeenth-century Maine. Engaging with recent social historical scholarship on the early modern English landscape and the analyses of English colonization in New England explicated by Allan Greer, Lisa Brooks, Emerson Baker, and William Cronon, this dissertation draws on a rich archive of seventeenth-century Maine land deeds and related legal documents, the York Deeds.
As the majority of seventeenth-century English colonists in Maine were not fully literate, colonial claims to land in Maine were not exclusively made within textual frameworks. Rather, while text was certainly an important tool in this style of early modern colonization, it was integrally supported by non-textual rituals involving the use of the spoken word, meaningful material items, and the memorialization of monuments in the landscape. Thus, the authority of a land deed derived not only from its text, but also from its words spoken aloud and retained in oral memory, the materiality of its form (paper, ink, seals, and objects symbolic of the conveyed land), and sites of memory in the landscape. These landscape monuments took on a wide range of forms and usually functioned as “bound marks,” delineating the extent of a colonist’s claimed tract of land. Seventeenth-century Maine was manifestly not colonized by the pen, but rather by the environmental changes and military actions undertaken by its English inhabitants. But, as physical proofs of enduring English inhabitation, landscape monuments worked in tandem with the authority of written text, oral memories, and the physical materials of the law to justify the righteousness of English colonization in Maine on both a micro scale (the individual colonial landholding) and a macro scale (the entirety of Maine as English space).
But no matter how ardently seventeenth-century colonists believed in the righteousness of their colonization, they had to contend with the reality of the militarily potent presence in Maine of Native Wabanakis. Indeed, Maine’s lucrative fur trade, a key component of the colony’s economy, depended on Wabanaki participation. Accordingly, it is no surprise that Maine’s colonists contracted a significant number of deeds with Wabanakis during the seventeenth century. These Anglo-Wabanaki deeds reveal the attempted creation of syncretic Anglo-Wabanaki landscapes in the period roughly between 1640 and 1688. Wabanakis were not deceived or misled by the early modern English legal system, but rather were able to creatively adapt to it and use it for their own advantage. During this era of early colonization, Wabanaki military and economic power could not be ignored by colonists, and both Natives and newcomers were often willing to work together for what they perceived as their mutual benefit. But with the spread of King Philip’s War from southern New England to Maine in the fall of 1675, the resulting nearly eight-decade era of Anglo-Wabanaki warfare forever poisoned relations between Natives and English colonists. Emerging victorious by 1678, Wabanakis dictated the terms of a peace treaty (the Treaty of Casco) that recognized Native sovereignty in Maine, thereby formalizing what pre-war Anglo-Wabanaki deeds had established de facto. But most colonists refused to abide by these terms, and after the conclusion of the Second Anglo-Wabanaki War (King William’s War) in 1697, both Wabanakis and English colonists had come to permanently disavow attempts to create or maintain shared Anglo-Wabanaki landscapes.Ph.D.Includes bibliographical reference
Enhancing robotic vision through excitatory-inhibitory recurrent memory networks: facial recognition and recall
No full textRobotic vision, characterized by the necessity for real-time processing of complex, dynamic data in ever-changing environments, confronts significant challenges with traditional computational paradigms. Deep learning algorithms, while powerful, often rely on static conditions and extensive, homogenous datasets, limitations that are impractical in real-world scenarios. Addressing these challenges, previous work introduces a neuromorphic oculomotor controller integrated into a biomimetic robotic head prototype, inspired by neurological studies that elucidate the unified circuitry behind saccade and smooth pursuit eye movements. In this work, we present an innovative approach that leverages excitatory-inhibitory recurrent memory networks for facial recognition and recall, enhancing robotic vision beyond conventional methodologies. Building upon this foundation, our study extends the capabilities of neuromorphic systems through the development and integration of an Excitatory-Inhibitory Recurrent Memory Networks (EIR-MN) model. This model further enhances the biomimetic aspects of our robotic head prototype by introducing a mechanism for facial recognition, even in noisy environments. The EIR-MN model showcases resilience to environmental noise through its dynamic temporal processing capabilities. Its architecture, designed to reflect the intricacies of neural processing found in the human brain, leverages spike-based encoding to achieve high levels of accuracy in facial recognition tasks. This model not only complements the previously developed oculomotor controller by adding visual processing abilities but also underscores the potential of neuromorphic computing to emulate complex cognitive functions without the need for extensive training datasets. The controller is unique in its utilization of spikes for encoding and processing information among models of biological neurons, and its architecture mimics brain anatomy, enabling operation without specific training. The EIR-MN model will be running on top of this previous work. This advancement aligns with ComBra Lab's vision of developing neuro-mimetic "bottom-up" computational models of brain networks that harness natural intelligence for robotic control. Our contributions extend the robustness of the robot in target detection, particularly in facial recognition tasks, broadening the spectrum of applications and marking a significant step forward in the pursuit of biologically inspired, efficient robotic vision systems. This work not only enhances robotic capabilities in complex environments but also offers insights into the potential convergence of neuroscience, robotics, and artificial intelligence.M.S.Includes bibliographical reference
It’s not magic!: instructional practices that cultivate positive mathematics identity in middle school Black girls
No full textAs a racially and gendered organizational space (Hottinger, 2016, Martin, 2007), mathematics education in the United States places African American girls as "outsiders” to mathematics learning and knowledge production (Gholson & Martin, 2014). We need to comprehend the mathematics and pedagogical communications Black girls are receiving and how these messages affect their development in order to construct supportive classroom environments for these and students. A technique to evaluate and explain how mathematics education serves as an exclusionary gatekeeper to STEM disciplines is traditional mathematical logics (Battey & Marshall, 2024). This three-paper dissertation first looks at how mathematics has been used as a tool to further Western imperialism and perpetuated antiBlackness in schools, then uses Joseph's Black Feminist Mathematics Pedagogies (2021) theoretical framework to directly challenge these traditional mathematics logics and shed light on the teaching strategies and relational interactions (Battey, 2013) that create safe spaces for Black girls to cultivate strong positive mathematics identities. Chapter 3 focuses on two teachers who navigated the structural constraints of a Title I school district to look for ways to open up access and opportunities and enriched learning experiences for their Black girl students. Although they reinforced several traditional math logics, these teachers still believed in their students’ ability and provided words of affirmation and humor that encouraged Black girls in their classrooms. In chapter 4, a very successful STEM teacher delivered rigorous and engaging real-world lessons and created a sense of community that encouraged Black girl students, while disrupting several traditional mathematics logics. Both schools served as case-studies to understand the affordances and constraints of enacting BlackFMP pedagogical approaches in traditional public middle school settings. This work contributes to Black Girlhood Studies and Mathematics Education by foregrounding how teachers' instructional practices and intentions help cultivate positive mathematics identities for middle school Black girls.Ph.D.Includes bibliographical reference
Data-driven optimization solutions for in-situ monitoring, prognostics, and optimization in production systems: addressing randomness from micro to macro levels
No full textEnsuring optimal production performance is crucial for achieving high-quality products, meeting customer demands, and maximizing profitability. However, unpredictable events and inherent randomness can lead to variations in the system, thereby affecting system performance. This randomness exists at each level of the system, from a single machine to a manufacturing system composed of machines and extending to the supply chain, resulting in performance fluctuations. Recently, advanced sensing technologies have provided opportunities to leverage rich sensing data for in-situ monitoring, leading to more accurate prediction and better decision-making. The applicability of data-driven optimization approaches in production systems, however, is limited by the lack of understanding from both engineering and data aspects due to the inherent randomness and complex nature. This dissertation proposes data-driven optimization solutions integrated with domain knowledge for in-situ monitoring, prognostics, and optimization, addressing randomness in production systems at each critical link, from the micro to the macro level of scope.
At the single-machine level, the quality of a part is one of the most concerned metrics. In order to achieve desired quality, it is necessary to develop methods that facilitate in-situ process monitoring and quality prediction. However, the deployment of data-driven approaches necessitates substantial datasets for training, posing challenges in real manufacturing scenarios with limited defect data, insufficient historical data, and frequently changing process settings. To mitigate the issue of imbalanced data, a novel data augmentation approach integrating deep convolutional generative adversarial networks (DCGAN) with physics-informed constraints is proposed. To address the issue of insufficient historical data due to process changes, a process-informed transfer learning method is proposed to leverage the strength of pre-trained deep learning models for quality prediction, allowing them to be reused on similar tasks with minimal additional training. To address the issue of changing process settings, a new quality prediction method based on continual learning is proposed so that the method can adapt to the dynamic nature of the production system without forgetting previous ones. The proposed methods are demonstrated in process monitoring and quality prediction in laser-based manufacturing.
The performance of an individual machine is critical to the throughput of an entire manufacturing system, which is one of the primary metrics at the system level. Therefore, it is essential to investigate the interdependence among machines and understand how they affect the system’s overall performance. Moreover, the randomness in machine status, such as machine breakdown, poses challenges to throughput prediction. To address this challenge, this research proposes a machine learning-based hierarchical model to characterize between-machine relationship, identify machine condition and analyze root cause. The effectiveness of this approach is demonstrated in the context of automotive manufacturing by leveraging rich sensor data from each machine on the production floor.
Manufacturing system is one of the fundamental components in delivering high-quality products to end customers. At the supply chain’s scope, traditional methods have focused on maximizing profit and minimizing the cost. Advances in data collection offer opportunities to access real-time data from different regions. This introduces new concerns about resource accessibility that linked with fairness, inclusion, and equity. These new concerns are further coupled with uncertainty in supply/demand. The presence of uncertainties such as stochastic supply/demand and system disruptions can make it challenge to ensure optimization model parameters. Therefore, it is essential to develop solutions for decision-making that prioritize system resilience. To address this challenge, this research proposes an approach that combines stochastic optimization and simulation. The effectiveness of this approach is demonstrated in the context of a food supply chain, where the approach initially solves for stochastic demand and supply and further explores solutions for system disruption under emergency scenarios.
This research aims to offer a comprehensive investigation to the analysis of complex systems, specifically, addressing randomness at each critical link in production systems. By incorporating advanced sensing technologies and domain knowledge, these solutions enable in-situ production performance monitoring, prognostics, and optimization. This research contributes to enhancing quality prediction, production performance, and supply chain resilience, ultimately ensuring the efficient delivery of high-quality products to customers. The methodology can be generalized to applications in production systems and other systems with sensing capabilities and prediction needs, but grapple with challenges of insufficient data, systems variation, and accessibility concerns.Ph.D.Includes bibliographical reference