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Publication Graphene-Based Nanomaterials for Advancing Biosensing and Biocontrol(2024-09) Fan, XiaoThe development of techniques for detecting and regulating biomolecules and cells is crucial in clinical diagnostics and biological research. Elevated by significant advancements in materials science, electronics, and optics, the methodologies for detecting and modulating biomolecules and cells have achieved remarkable enhancements in sensitivity, specificity and reliability. However, combining all the necessary properties for electrode materials—including high transparency, high conductivity, biocompatibility, chemical stability, low impedance, and low cost— into a single material system remains a challenge for achieving high-performance biosensing and biocontrol. By synthesizing graphene-based nanomaterials with exceptional properties and applying them to interface with biological systems, this dissertation addresses this challenge and demonstrates advancements in biological sensing and control. For protein analysis, I utilize monolayer graphene microelectrodes in microfluidic devices for electrokinetic focusing and sensing of proteins. The electrolysis stability of graphene electrodes is >103× improved compared to typical microfabricated inert-metal microelectrodes. The reliable pH gradient between a pair of biased graphene microelectrodes enables the separation and concentration of specific proteins into narrow band (~100 micrometers) within minutes. The high optical transparency of graphene allows for label-free detection of the proteins at same processing position with sensitivity ~100× higher than those of the state-of-the-art label-free sensors. For cell action potential measurement, I synthesized whisker-like multiwalled carbon nanotubes on monolayer graphene surface via chemical vapor deposition using nanoparticle catalysts. The carbon nanotubes and substrate graphene share the same fermi level, and the hybrid material retains electrical mobility comparable to that of bare graphene. The carbon-nanotube structures enhance capacitive and resistive by 80× and 7×, respectively, serving as the primary transducing pathway and improving the signal-to-noise ratio for detecting extracellular cardiomyocytic action potentials by 2.5×. Furthermore, the enhancement of electric field at the carbon-nanotube structures enables low-bias (~4 V) nano-electroporation and the recording of intracellular action potentials. Future research in this area includes utilizing isoelectric focusing to analyze viruses and bacteria in our devices, and developing controllable capture and release systems to detect target molecules. Additionally, we aim to measure intracellular action potentials of neurons and investigate gene delivery to cancer cells using our CNT-graphene-based devices.Publication Impact of Fish Oil Intake and Hyperthermia Therapy on Metabolic Health(2024-09) Fan, RongAging is a major contributor to decreased metabolic rate, underscoring the need to develop effective strategies to combat this decline. Interventions that combine lifestyle adjustments with dietary strategies could be particularly effective in reducing the risks of metabolic dysfunction. Hyperthermia/heat treatment (HT) is a therapeutic practice that has been demonstrated to provide a variety of metabolic benefits. Fish oil (FO) is a potent dietary intervention that promotes metabolic health. However, whether HT could promote metabolic health by combating aging-associated metabolic slowdown and the combinational effect of FO and HT have not yet been evaluated. The first aim was to investigate the impact of HT on aging-associated metabolic dysfunction and to determine the underlying molecular mechanisms, including potential associations with gut microbiota. Next, we also aimed to unravel the synergistic effect of HT and FO supplementation on aging-related obesity and metabolic dysfunction in both aged female mice and ovariectomized (OVX) mice. Our overarching hypothesis was that HT and FO synergistically improve metabolic health by promoting energy expenditure and improving insulin sensitivity and inflammation response in aging and menopause. Our findings indicate that daily HT at 40-41℃ for 30 min showed no tissue damage and significantly reduced lactate dehydrogenase (LDH) levels in older females, indicating a decline in aging-mediated tissue damage. HT effectively countered weight gain induced by a high-fat diet in both aged female and ovariectomized mice. Furthermore, HT demonstrated significant improvements in 1) insulin sensitivity and insulin signaling in inguinal white adipose tissue (iWAT), 2) reduced lipid accumulation in the liver and brown fat, and 3) increased fatty acid beta-oxidation in the liver and iWAT. An increase in the expression of transient receptor potential vanilloid 1 (TRPV1) and genes associated with Ca2+/ATP-pump on the plasma membrane and endoplasmic reticulum (ER) suggests that HT triggers ATP-consuming futile calcium cycling. These findings were confirmed in human brown adipocytes. HT alone notably lowered core body temperature (~0.5℃) across all diets, leading to a reduced Firmicutes to Bacteroidetes ratio and significant changes in gut microbiome diversity and composition. Additionally, microbiota genera Tuzzerella, Defluviitaleaceae_UCG-011, Alistipes, and Enterorhabdus were significantly correlated with liver, brown adipose tissue weights, and core body temperature. The combination of HT and FO showed a more substantial improvement in metabolic health and insulin sensitivity. Additionally, FO supplementation significantly increased the abundance of [Eubacterium]_coprostanoligenes_group, a genus known for reducing cholesterol absorption and associated with lower plasma lipids and body weight. HT and FO intake correlated with a decrease in Alistipes, which are usually present with obesity and inflammation conditions. In the OVX mice, Colidextribacter and Muribaculaceae showed increased abundance in the HT group compared to the CON group. FO combined with HT increased the abundance of the microbial genera [Eubacterium]_coprostanoligenes_group, Bacteroides, and Incertae_Sedis, which negatively correlated with core body temperature. HT, FO, or the combination of HT and FO, did not have a similar effect in OVX mice compared to the aged female mice, suggesting a potential effect of the absence of estrogen on the microbiota. Overall, the findings of this dissertation demonstrate that HT and FO supplementation, independently and in combination, significantly enhance metabolic health by improving insulin sensitivity, promoting thermogenic energy expenditure, and modulating gut microbiota diversity and composition. The combinational effects of HT and FO are more potent in aged female mice compared to the OVX mouse model of menopause.Publication Controlling Reactivity and Triggerability Using Intramolecular and Ad Hoc Electrostatic Interactions(2024-09) Das, RitamElectrostatic interactions play a vital role in natural design principles. An extraordinary amount of impact of such interactions also can be observed in evolutionary biology. The profound impact of these interactive forces underscores their pivotal role, yet there remains ample scope to develop our grasp of the bases that regulate and manipulate these interactions. Enriched intellectual capacity regarding electrostatic interactions will enable their more sophisticated and effective application across diverse platforms, unlocking new avenues and innovations. This dissertation reviews charge-based interactions at the molecular level and presents three perspectives on their fundamental and practical applications. The dissertation focuses on three key aspects i) studying intramolecular electrostatic interactions in tertiary amine-based zwitterionic structures, showing how these interactions affect reaction kinetics and nanostructure formation ii) developing hybrid lipid-polymer nanoparticles for RNA delivery using a ‘de-cationizable’ non-viral design, highlighting the separate roles of encapsulation and intracellular trafficking in optimizing delivery vectors. It also creates a unique opportunity to impose targeted delivery capabilities for selective treatment of excruciating diseases like triple-negative breast cancer, using a two-factor authentication approach for enhanced selectivity and efficacy. iii) Additionally, the dissertation explores improving electroporation in T-cells with anionic polymers attached to targeting antibodies, aimed at enhancing targeted cell therapies. Finally, this thesis summarizes these findings and discusses prospects, emphasizing the multifaceted roles of electrostatic interactions in biomedical research.Publication Critical Minerals and the Green Transition(2024-09) Das, DebamanyuOne major issue in the global green transition—i.e. in advancing a viable global climate stabilization path—is the massive increase in demand for electric vehicles (EVs). The growing demand for EVs in turn, generates a commensurate demand increase for the minerals needed to operate the batteries that power EVs. These minerals critical for the operation of EV batteries include lithium, cobalt, and nickel. This dissertation examines a range of questions resulting from the ongoing huge expansion in the global demand for these three critical minerals. The first chapter builds from the International Energy Agency’s (IEA) framework to estimate the requirements for lithium, cobalt, and nickel used in electric vehicle batteries in the IEA’s Net Zero Emissions by 2050 scenario. According to my analysis, demand for these minerals will far outstrip the estimates of supply under current industry conditions, thereby creating a demand-supply gap for these minerals. The chapter reviews alternative approaches to closing this gap. The second chapter explores the factors that have enabled China to dominate at present the global production and supply chain of critical minerals. I argue that the most basic explanation is that China developed effective industrial policies from the 1980s onward to create capacity for supplying the global economy with EVs and the batteries that power them. Among other resources, I draw here on Chinese government documents and data on state funding for innovation. Using mergers and acquisitions data, I also document various ways through which Chinese corporations have secured critical mineral supply chains. The third chapter documents the impact of critical mineral mining on a selected set of mineral-rich economies, in particular, Chile, Indonesia, and Congo. I utilize data on social conflicts that have resulted from mining operations in these economies to understand the impact of mining on conditions for mine workers and communities. I also explore ways through which state ownership and distribution of resources can provide net benefits to local communities. Such benefits do not result when mining operations are controlled by private multinational corporations along with governments that align themselves primarily with the interests of the multinationals.Publication Dynamically-Driven Allosteric and Specific Inhibition of Sika Virus Protease(2024-09) Cruz, KristalleDue to the lack of effective vaccines and antivirals, flaviviruses continue to pose a significant threat to public health. The Dengue virus is now a leading cause of hospitalization among children in developing countries while Zika virus outbreak resulted in severe congenital abnormalities. Most drug development research for flaviviruses targets the viral protease due to its crucial role in virus maturation. This dissertation presents the discovery of an allosteric inhibitor, MH1, which selectively binds to the Zika virus protease (ZVP). Our combined biochemistry and structural biology approach demonstrated that the dynamic C-terminal region of the NS2B of ZVP dictates the selectivity and efficacy of MH1. Our data suggested that MH1 disrupts the interaction between the C-terminal residue of NS2B and NS3pro, resulting in protease inhibition while selectivity stems from the differences in the dynamic properties of the NS2B of ZVP and Dengue virus protease (DVP). We believe that we are the first to report that the dynamics of the NS2B can influence the selectivity of an allosteric inhibitor. This discovery opens a new avenue that may be exploited to overcome selectivity issues that some allosteric inhibitors encounter. It is always of interest to develop a broad-spectrum antiviral to address future outbreaks and resistance mutations that commonly occurs in viruses.Publication Resource Management for Edge AI(2024-09) Liang, QianlinWith the proliferation of IoT devices and the continuous advancement of AI al- gorithms, edge AI, which represents the synergy of edge computing and artificial intelligence, has garnered increasing attention from both academia and industry. By pushing AI frontier to the edge ecosystem which is closer to users, edge AI provides substantial benefits such as low-latency inference, reduced network bandwidth us- age, and enhanced user privacy. However, deploying compute-intensive AI models on resource-constrained edge platforms presents substantial challenges to resource man- agement, which plays a key role in realizing the benefits and ensuring the success of edge systems. It is imperative to efficiently schedule and share the heterogeneous and limited edge resources, including emerging specialized AI accelerators such as GPUs and TPUs, to adapt to the dynamic edge workloads and satisfy their low-latency requirements. Additionally, energy, particularly for battery-powered edge devices, must be considered as a scarce resource, necessitating efficient operation to support the long-term execution of workloads. This thesis addresses pivotal challenges of resource management in Edge AI. By optimizing resource and energy efficiency for AI applications within the constraints of edge computing environments, this thesis aims to enhance hardware utilization, reduce costs, and improve application performance and reliability.Publication Linguistic Racism and Racialization on Social Media. The Case of (Mock) Kichwa(2024-09) Narváez Burbano, María DanielaThis dissertation examines the phenomenon of Mock Kichwa in memes shared on social media in Ecuador, focusing on how these memes contribute to racism and reflect enduring colonial raciolinguistic ideologies. Ecuador is a multilingual society where Spanish is the dominant language, and Kichwa is the most widely spoken Indigenous language in the Highlands. Due to centuries of contact between Spanish and Kichwa, there exists a continuum of Ecuadorian Andean Spanish (EAS) varieties, some of which are stigmatized and mocked, particularly by the white-mestizo population. This study investigates the linguistic and semiotic strategies used in these memes, exploring how both Indigenous and non-Indigenous people perceive them, while highlighting Ecuador's distinct sociopolitical dynamics and racial constructs, such as mestizaje and indigeneity, which shape these perceptions. Building on the concept of Mock Spanish (Hill, 1995) and raciolinguistic ideologies (Rosa and Flores, 2017), which link seemingly "innocent" or humorous practices to underlying beliefs about language, race, and class, this research extends these frameworks to the context of Latin America. By analyzing a corpus of 50 memes collected between 2020 and 2024, and incorporating ethnographic data from questionnaires and focus groups, this dissertation reveals that Mock Kichwa relies heavily on stigmatized linguistic features of EAS. These features include vowel neutralization, the representation of /ʃ/ as "sh" instead of "ll," the assibilation of the rhotic sounds /r/ and /ɾ/, the use of Kichwa words with negative connotations in EAS, and the hyper-use of EAS morphosyntactic features. The study employs diverse community-based and decolonial methodologies, such as multimodal semiotic analysis, Critical Discourse Analysis, and focus groups, to understand how language and race are co-constructed in these digital spaces and subsequently experienced in other contexts. Memes are analyzed as "semiotic packages" that combine linguistic and non-linguistic elements, serving as key indexes of social meaning. By utilizing the concept of "indexicality," this dissertation moves beyond a focus solely on mock languages, instead reflecting the diverse indexing practices that characterize the construction of Mock Kichwa and, more importantly, the underlying language ideologies that perpetuate social inequity. The findings highlight how Mock Kichwa in social media memes perpetuates social hierarchies and racist ideologies, continuing the marginalization of Indigenous communities. These memes are not merely playful or humorous; they serve as tools of power and control that reinforce existing social structures. This dissertation also underscores the ongoing resistance and contestation by Indigenous peoples, who continuously challenge racism and colonial legacies, leading to unique forms of resistance and language revitalization.Publication Essays on Social Reproduction, Distribution, and the Political Economy of Paid and Unpaid Work in Selected Latin American Countries(2024-09) Maqueira Linares, AnamaryThis dissertation comprises three essays that contribute to the social reproduction literature by using it as a framework to analyze Global South and “in transition” contexts while inquiring on the role of the state in shaping and directly contributing to social reproduction processes. Chapter 1 uses time-use data to explore the relationship between institutional and non-parental childcare provision on maternal unpaid time use in Ecuador. Results suggest that institutional and kinship childcare presents a complementary relationship for mothers’ active unpaid care time, while female kinship is associated with significant reductions in maternal time regarding supervisory childcare and housework. The size of the effects suggests that out-of-home childcare is associated with greater reductions for mothers with no co-resident adult female kin. Chapter 2, co-authored with Katherine Moos, proposes an accounting framework for understanding the distributional role of household production, employment, remittances, and government social transfers in the social reproduction of the Cuban people, and provide a snapshot for 2016. Our findings demonstrate that households were viii the largest contributors to social reproduction in Cuba. Our empirical exercise reveals how the actual distributional arrangements underlying Cuban social reproduction differ from the official commitments and goals of the Cuban Revolution. The relative contributions in 2016 signal several potentially unsustainable self-reinforcing dynamics that undermine efforts to achieve gender and racial equality on the Island. Chapter 3 asks how the economic and social reform processes of the post-2010s Cuba have redistributed the costs of social reproduction among the State, the market, and the family, particularly regarding the caring of dependents. I examine the transformations in unpaid and paid work, government benefits, and remittances using legal and policy changes and their implementation. Results demonstrate that the reproductive bargain in post-2010s Cuba has explicitly changed, acquiring a transnational dimension. The analysis shows that the reform policies have shifted the responsibilities of social reproduction more onto households and that increasing commodification of social reproduction processes has occurred, with adverse consequences for women. De-statization processes have followed as a combination of direct withdrawal of the government’s role as a social provider and less state presence in other socio-economic affairs.Publication Developing Digital Biomarkers of Early Childhood Mental Health using Multimodal Sensor Data(2024-09) Kalanadhabhatta, ManasaPediatric mental health is a growing concern around the world, with mental, emotional, and behavioral disorders affecting children's social-emotional development and increasing the risk of adverse behavioral outcomes later in life. However, diagnosing mental health disorders in early childhood remains challenging. Caregivers are often unable to accurately identify signs of problematic behavior, and many lack access to specialized screening services. Digital biomarkers from passively sensed signals collected using smartphones and wearable devices have shown remarkable promise for mental health screening at scale. Nevertheless, such digital mental health tools are yet to make a significant mark in pediatric settings. While this may partly be driven by caregivers' perspectives toward such tools, the fact that children rarely tend to be independent users of mobile and wearable devices is also a key deterrent to developing scalable digital biomarkers of mental health in younger populations. In this thesis, I attempt to bridge this pediatric mental health diagnosis gap by developing novel digital tools that enable screening for problem behaviors in a convenient and scalable manner. These screening tools leverage multimodal signals that can be recorded using ubiquitous devices in the home while children are engaged in brief, clinically validated play-based interactions. I establish the technical feasibility of developing machine learning models to detect interaction-based biomarkers of attention-deficit/hyperactivity, disruptive behavior, and other externalizing disorders using behavioral (audio, video) and physiological (heart rate, electrodermal activity) signals. I incorporate these biomarkers into three new home-based assessments that can be realized using off-the-shelf mobile and wearable devices to predict not just behavioral symptoms but also their neurophysiological underpinnings, thus providing richer insight into the trajectories of early problem behaviors. To facilitate the integration of these next-generation screening tools into existing mental healthcare ecosystems, I further outline design recommendations for such tools by distilling findings from stakeholder studies involving parents and child mental health practitioners. This work thus sets the stage for ubiquitous technologies that can obtain rich, multidimensional data in the wild and enable screening for early childhood mental health concerns at scale.Publication Stored Multiword Representations and their Usage during Chinese Reading(2024-09) Huang, Kuan-JungWhat are the building blocks of language stored in memory and how are they utilized in linguistic tasks? It has been proposed that meaningful strings of all lengths—morphemes, words, and sequences of multiple words—can be stored, with the last kind playing a crucial role in language processing. This dissertation investigates the existence of stored multiword representations and their usage in Chinese reading. Stored multiword representations are operationalized by using two words that frequently co-occur and comparing them with those that do not. Morphosyntactic structure is also manipulated, with the main comparison between noun-noun and verb-object sequences. Two tasks are used to study visual recognition of multiword sequences: (1) a rapid masked visual presentation without sentence context probes how many words in a string can be simultaneously recognized and whether this limit is modulated by the co-occurrence frequency of the two words in the string; (2) a naturalistic sentence reading task with a gaze-contingent boundary change paradigm probes how far/deep Chinese ix readers process downstream text not yet directly fixated (i.e., parafoveal processing) and whether this limit is modulated by the co-occurrence frequency of the two words in the downstream string. The results show that co-occurrence frequency facilitates rapid visual recognition without sentence context, making parallel recognition of the two embedded words possible. This is the case for both noun-noun and verb-object sequences. In sentence reading, however, co-occurrence frequency influences online processing differently for strings of different structures. It facilitates processing extremely early on for noun-noun sequences: readers process Characters n+3 and n+4 in the parafovea beyond the visuo-orthographical level, while no such evidence is found for verb-object sequences. However, relatively late foveal processing does appear to be facilitated by co-occurrence frequency, for both kinds. Based on the findings, I argue that while language users are highly sensitive to statistical regularities of word sequences of various structures, this possibly yields only familiarity with the surface multiword forms and ease of on-the-fly composition of the two embedded words for verb-object sequences. Compound nouns on the other hand may be lexically stored to have direct form-meaning mapping via frequent exposure, hence the additional early facilitation observed. Future models of Chinese reading must incorporate mechanisms to explain the current data: (1) extremely fast access to frequently co-occurring strings’ orthography, which suggests that a single decomposition route alone is likely insufficient; (2) distinctive processing patterns throughout the time course between noun-noun and verb-object sequences, which points toward structural/semantic composition in addition to utilization of word statistics and contextual probability.Publication Mapping Modernisms:Translation and Travel in Twentieth Century Indo-Persian Letters(2024-09) Noor, HabibMapping Modernisms offers a study of three writers: Miraji (1912-1949), N.M. Rashed (1911-1975), and Sadegh Hedayat (1903-1951). It highlights the role that each played in defining an emerging modernist mode in prose and poetry in Urdu and Persian literature during the mid-twentieth century in India, Iran, and beyond. I focus on the twin acts of travel and translation as crucial elements of their literary practice. In chapter one, which serves as an extended introduction, I activate an interdisciplinary methodology to the study of their works, drawing from literary history, orientalism, translation studies, and theories of global modernism and critical cosmopolitanism. This dissertation advocates an approach to comparative study that considers both the works and networks that enable encounters between literary agents from the Global South, uncovering shared literary lineages and alternative geographic imaginaries. In chapter two, I contextualize N. M. Rashed’s collection of poetry titled A Stranger in Iran within the discourse of critical cosmopolitanism, and trace a contrarian, anti-imperialist poetics. This chapter closely examines poems that, among others, were written in and about Tehran during the second world war. These poems dramatize the crisis of a weakening “Asian” identity as a viable counter to Western imperialism. In chapter three, I closely examine Miraji’s literary commentaries and translations to build a case for translation as both a constituent aspect of modernist writing in Urdu, and a subversive challenge to the existing norms of literary canonization during the colonial era. In chapter four, I analyze the Persian writer Sadegh Hedayat’s novella The Blind Owl (1936), written in Bombay, India, to evaluate the role occupied by India as a symbolic construct and uncanny Other in the narrator’s world. All three writers offer a conception of “the world” in their work that exposes the instability of both national borders and the identities contained within them.Publication Hormonal Control in Mammary Development and Uterine Health: Insights from Cell Lines and Animal Models(2024-09) Goral, CerenMammary gland development is a complex physiological process regulated by a delicate balance of hormonal signals, among which estrogens play a pivotal role. Estrogens, primarily estradiol, mediate their effects through binding to estrogen receptors (ERs), notably ERα (ESR1) and ERβ (ESR2). These receptors are transcription factors that, upon activation, regulate the expression of genes involved in cell proliferation, differentiation, and apoptosis. The differential roles of ERα and ERβ in mammary tissue are critical for normal development and are implicated in the pathogenesis of breast cancer. The objectives of this research are to evaluate the endogenous and exogenous activation of ERα and ERβ receptors in various cellular contexts. This involves a detailed examination of the transactivation capacities of ESR1 and ESR2 in different cell lines by assessing the responses of ERα and ERβ to estrogenic compounds. Furthermore, the study characterizes the estrogen-induced responses in Esr2 knock-out mice, backcrossed onto a BALB/c background. This analysis sheds light on the role of ERβ in mammary gland development and tumorigenesis, as well as its influence on metabolism, providing a comprehensive understanding of its systemic effects. Additionally, the research explores the control of the estrus cycle and uterine disease treatment in equids. It examines the systemic effects of intrauterine device (IUD) placement in mares and investigates the efficacy of copper-banded IUDs in promoting bacterial clearance and preventing uterine diseases. This aspect aims to enhance reproductive health management in equids, addressing the control of the estrus cycle and the treatment and prevention of uterine conditions. Overall, these objectives are designed to provide a holistic view of estrogen receptor functions in both mammary gland and reproductive health, contributing to advancements in human medicine and animal husbandry.Publication Engineered Polymer-Based Nanomaterials for the Treatment of Biofilm-Associated Infections(2024-09) Nabawy, AhmedBiofilm-associated infections present a clinical challenge, with biofilms protecting resident bacteria from host immune response and therapeutic agents. Severe biofilm infections annually afflict 300 million people worldwide, with treatment costing $25B in the US alone.Clinical treatment of refractory chronic wound infections combines surgical removal of infected tissues with long-term antibiotic therapy. Debridement is an invasive process and use of antibiotics selects for drug resistance, further increasing therapeutic challenges with chronic wound infections. Polymeric nanomaterials provide a promising opportunity to effectively address bacterial and biofilm infections.Polymers can be engineered to combat biofilm infections by tuning their morphological and physicochemical properties, including size, shape, and surface chemistry. In this dissertation, I demonstrate polymer-based strategies for the treatment of biofilm-associated infections, with a focus on wound biofilms. In the initial studies, we leveraged poly(oxanorborneneimide)-based biodegradable polymeric nanoemulsion to deliver plant-derived essential oil, including carvacrol, that can penetrate and eliminate bacterial biofilms. Next, we build upon this nanoemulsion platform and encapsulate two hydrophobic antimicrobial agents (eugenol and triclosan) into this nanoemulsion for synergistic treatment of wound biofilms. Notably, this combination nanoemulsion mitigates resistance development of antimicrobial triclosan and clears 99% of bacterial load in severe wound biofilm infections in mice. In a related system, I developed an antimicrobial nanoemulsion composed of all nature-derived materials. This nanoemulsion uses gelatin as a scaffold and carvacrol (from oregano oil) as the active antimicrobial phytochemical. Crosslinking of the gelatin scaffold using riboflavin (vitamin B2) led to a formation of a stable nanoemulsion with excellent antifungal activities against C. albicans biofilms. In a following study, I have leveraged this all-natural gelatin nanoemulsion to encapsulate transition metal catalysts (TMCs) for bioorthogonal catalysis in biofilms. This emulsion nanocatalyst can efficiently penetrate biofilms and eradicate mature bacterial biofilms through bioorthogonal activation of a pro-antibiotic, providing a highly biocompatible platform for antimicrobial therapeutics. The last parts of this dissertation focus on developing polymers with inherently antimicrobial activity for topical applications in wound biofilms. Our strategies include 1) integration of antimicrobial poly(oxanorborneneimide)-based polymer into hydrogel materials, 2) development of cationic conjugated polymers for simultaneous biofilm imaging and therapy. In summary, Polymer nanotherapeutics offer a promising alternative to antibiotics, alleviating challenges faced in the post-antibiotic era.Publication Self-Assembly of Linear and Bottlebrush Copolymers: Bulk and Thin Films Studies(2024-09) Hu, MingqiuMoore’s law predicts that the areal density of transistors in semiconductor devices doubles every two years. The self-assembly of copolymers have emerged as a promising alternative to yield sub-10 features on Silicon substrates. In this work, we presented a solid-state hydrolysis strategy, where a hydrophobic-hydrophobic copolymer was hydrolyzed into a hydrophilic-hydrophobic copolymer in spin-coated thin films. The solid-state hydrolysis bypassed the poor solubility of high-chi copolymers. We introduced photoacid generators into the spin-coated copolymer films so that the solid-state hydrolysis can be achieved through exposure to UV light, aligning the self-assembly closer to currently used photolithography approaches in industry. To assist characterization of film thickness and X-ray scattering analysis, we developed an open-source Python package allowing X-ray scattering and specular reflectivity to be measured at the same areal detector. The orientation of the self-assembled patterns in thin films needs to be carefully controlled because only vertical orientation is suitable for pattern transfer into substrate through sequential etching. We developed a depth-sensitive characterization method using grazing-incidence small-angle neutron scattering. We identified that the horizontal patterns persist through the entire film while the vertical patterns only exist near the polymer-air and polymer-substrate interfaces and get randomized in depths away from the interfaces. Promoting vertical orientation of the self-assembled patterns is essential for pattern transfer. We developed block copolymers with low-surface-area junctions that assemble into vertical lamellae in spin-coated thin films. The self-assembly occurred on unmodified Silicon substrates without any surface modification or external field. Moving on from linear copolymers to bottlebrush copolymers, we first summarized recent progress on the architectural effect on polymer self-assembly in a review article. It is commonly believed that bottlebrush copolymers self-assemble more rapidly than their linear analogs due to the absence of entanglements. However, we found that high-chi bottlebrush copolymers are trapped in meta-stable poorly ordered status unlike their linear analogs, which evolve into better lateral order after thermal annealing. For low-chi bottlebrush copolymers, we highlighted the conformation of the molecular backbone in the self-assembled lamellar morphologies. Bottlebrush copolymers at lower grafting densities have the backbone looping back and forth between the two sidechain domains.Publication Developing a Bone Metastasis Model in Immunocompetent Mice(2024-09) Giles, ConnorCancer is a burdensome and challenging disease. Existing treatments, including chemotherapy and radiotherapy, are effective in reducing primary tumor burden. However, metastatic growths in distant organs can emerge years later, which may be lethal. Breast cancer, especially, is prone to seeding dormant metastases throughout the body. Furthermore, there is a growing body of evidence suggesting that these treatments may actually promote metastatic resurgence. Successful, long-term treatment of breast cancer depends on understanding the process by which dormant, disseminated tumor cells reawaken and become proliferative once more. A major barrier to developing such understanding is the lack of breast cancer models capable of recapitulating this phenomenon. Often, host organisms perish from primary tumor burden before dormant breast cancer cells can reawaken. To address this need, novel breast cancer models were developed to recapitulate the dormant cancer niche. An implantable, microporous, polyacrylamide scaffold developed by the Lee lab were implanted subcutaneously into PyMT-MMTV mice which spontaneously generate breast tumors. Implanted scaffolds captured circulating breast tumor cells. Implanted scaffolds were serially transplanted into tumor-free mice to avoid primary tumor induced morbidity. Immunohistochemistry (IHC) was used to confirmed capture of DTC’s. Captured tumor cells remained dormant for up to 24 weeks in vivo following transplantation. To investigate implications of inflammation, scaffolds were intentionally disrupted via biopsy punch following serial transplantation. Disrupted scaffolds were capable of developing overt metastasis, and showed a higher population of cancer cells, linking ECM remodeling to metastatic relapse, and suggesting that disruptive treatment modalities may carry metastatic risk. Lastly, biomaterial platforms were created to more accurately model the bone environment to support future breast to bone metastasis modeling. Demineralized trabecular bone scaffolds were seeded with bone marrow cells and implanted subcutaneously in mice. The trabecular pore space was filled with polyacrylamide in order to attract circulating tumor cells to this bone environment and crushed bone powder in order to promote mineralization in-vivo. These results suggest that an implantable based model will be an enabling tool to study the progression of dormant niches and the effect of treatment on the development of these niches. Isolating the dormant niche in this manner will yield unique opportunities to develop treatments that specifically target dormant cancer.Publication Reciprocal Effects of Parent Emotion Socialization and Child Emotion Expression During Dyadic Interactions(2024-09) Gair, ShannonEmotion socialization plays an important role in children’s socio-emotional and behavioral development. Understanding the short-term bidirectional effects of parents’ and children’s emotion-related behavior within dyadic interactions—as well as individual differences in these process—is important for understanding how long-term maladaptive patterns of emotion socialization practices are maintained through short-term social learning processes. Participants included 261 (141 boys; 120 girls) 3-year-old children and their caregivers who took part in a 3-year longitudinal study. Results support the notion that emotion socialization processes are dynamic, with parents and children influencing one another’s emotional responses within their dyadic interactions. Further, past parent emotion socialization and child emotion expression changed subsequent concurrent relations between parent and child behavior, suggesting that past parent and child behavior changes the way dyads respond to one another in the future. Parent and child effects varied across parent and child gender and psychopathology, indicating that there are individual differences in the ways that parents and children respond to one another emotionally. Lastly, these early patterns of parent and child effects differed for children with high levels of psychopathology 3 years later, suggesting that early maladaptive patterns of parent-child interaction may lay the groundwork for future psychopathology. These findings suggest that long-term maladaptive patterns of emotion socialization may be maintained through short-term social learning processes and offer intervention targets for clinicians working with families with psychopathology.Publication Investigation into the Sintering Phenomena of Ultra-High Molecular Weight Polyethylene (UHMWPE)(2024-09) Zhou, YingThis dissertation investigates the sintering of Ultra-High-Molecular-Weight Polyethylene (UHMWPE) using in-situ techniques. Despite its widespread use, the manufacturing process of UHMWPE is not fully understood. Specifically, the short processing time under moderate pressure contradicts analytical models predicting particle coalescence and interfacial strength buildup, given its low surface energy and high viscosity. This research represents one of the first systematic studies dedicated to qualitatively identifying the macroscopic volume change during the overall sintering process of nascent UHMWPE powder. The goal is to monitor and reveal deformation during the manufacturing process, ultimately for a better understanding of the structure-process-property relationships of UHMWPE. The study begins with pressure-free sintering of UHMWPE nascent powder to investigate the influence of compaction pressure on the subsequent deformation of the sintering stage. Without pressure during sintering, significant expansion is observed during heating through the α-relaxation and melting. This large expansion impedes the porosity removal during isothermal sintering, therefore leading to high porosity remaining in the sintered UHMWPE and insufficient properties for applications. Since pressure is essential for porosity removal, a customized pressure sintering apparatus are developed, providing in-situ density evolution. Specifically, five distinct processes are identified including: (1) room temperature compaction; (2) subsequent densification through the α-relaxation, (3) enthalpy-driven melt explosion via crystal melting; (4) entropy-driven melt explosion due to non-equilibrium melt; (5) recrystallization under pressure. Thus, this in-situ density is applied to study varying external processing parameters and molecular architecture. The mechanical properties of sintered UHMWPE are evaluated, focusing on impact behaviors and using fracture mechanics to compare crack resistance under severe conditions. Both metallocene-catalyzed- and Ziegler-Natta-catalyzed- UHMWPE exhibit ductile fracture behaviors with significant plastic deformation, evidenced by fibrils observed through microscopy. Additionally, higher molecular weight reduces diffusion, leading to weak interface and the formation of grain boundaries. Finally, the blends of UHMWPE-HDPE is studied aiming to enhance the processibility. Interesting results are observed with a mass concentration of 20% UHMWPE in the blends. Preliminary results indicate that 20% UHMWPE can enhance load transfer ability while maintaining higher crystallinity.Publication Leveraging Explanations for Information Retrieval Systems under Data Scarcity(2024-09) Yu, PuxuanThe importance of explanations in the advance of information retrieval (IR) systems is on the rise. On one hand, this is driven by the increasing complexity of IR systems and the demand for transparency and interpretability from users; on the other hand, explanations can inherently improve the effectiveness of IR systems without necessarily being displayed to users. However, the scarcity of data poses significant challenges in developing these explanations, as acquiring high-quality explanations for relevance judgments is prohibitively expensive yet crucial for training neural network-based IR models and explanation generation models. To overcome these challenges, we utilize open-domain knowledge and generative language models to facilitate the generation of user-oriented explanations for various IR tasks limited by data availability. We start by introducing a novel model-agnostic task for search result explanations that emphasizes context-aware summaries, detailing each document's relevance to the query and other documents. To address this task, we design a novel Transformer-based encoder-decoder architecture. Next, we develop an inherently explainable IR model specifically designed to provide diversified reranking of retrieved documents. This model is pre-trained on open-domain data using explanation tasks, achieving state-of-the-art results in search result diversification with minimal domain-specific data. Additionally, we explore how natural language explanations can enhance the capabilities of generative language models to augment IR datasets through synthetic query generation, achieved by automatically identifying similarities and differences between document pairs. Finally, we utilize zero-shot generative language models to directly elicit natural language explanations of relevance between search queries and candidate documents, providing crucial auxiliary information for the calibration of neural ranking models and thus enhancing their ability to generate meaningful scores.Publication Nonparametric Inference using Shape Constraints and Bias Correction(2024-09) Wu, YujianIn the first chapter, we study the problem of nonparametric inference for a hazard ratio function under the constraint of monotonicity. The ratio of the hazard functions of two populations or two strata of a single population plays an important role in time-to-event analysis. Cox regression is commonly used to estimate the hazard ratio under the assumption that it is constant in time, which is known as the proportional hazards assumption. However, this assumption is often violated in practice, and when it is violated, the parameter estimated by Cox regression is difficult to interpret. The hazard ratio can be estimated in a nonparametric manner using smoothing, but smoothing-based estimators are sensitive to the selection of tuning parameters, and it is often difficult to perform valid inference with such estimators. In some cases, it is known that the hazard ratio function is monotone. In this chapter, we demonstrate that monotonicity of the hazard ratio function defines an invariant stochastic order, and we study the properties of this order. Furthermore, we introduce an estimator of the hazard ratio function under a monotonicity constraint. We demonstrate that our estimator converges in distribution to a mean-zero limit, and we use this result to construct asymptotically valid confidence intervals. Finally, we conduct numerical studies to assess the finite-sample behavior of our estimator, and we use our methods to estimate the hazard ratio of progression-free survival in pulmonary adenocarcinoma patients treated with gefitinib or carboplatin-paclitaxel. In the second chapter, we explore a novel nonparametric inference approach for a debiased kernel density estimator. Kernel density estimation is one of the most popular nonparametric methods for estimating probability density functions. However, it is well-known that kernel density estimators are biased. The robust bias correction approach proposed by Calonico et al. (2018) can effectively reduce this bias, leading to substantial improvements in confidence interval coverage. However, bias correction can result in negative density estimates. In this section, we propose bias correction and inference for kernel density estimators on the log density scale, which ensures positive density estimates wherever the original kernel density estimator is positive. We demonstrate our estimator is within oP(n−1) of the bias corrected estimator of Calonico et al. (2018), and that the t-statistic constructed with the logarithm-transformed estimator exhibits higher coverage accuracy compared to the t-statistic for the bias corrected estimator. Finally, we use an Edgeworth expansion of our estimator to demonstrate that the proposed approach yields the same rate of coverage error as that of Calonico et al. (2018). We conduct numerical studies illustrating the practical performance of our methods compared to ordinary and bias-corrected kernel density estimators. In the third chapter, we consider improving the monotonicity-constrained nonparametric inference with debiased kernel smoothing. The property of monotonicity plays an important role when dealing with survival data or regression relationships, and it is desired to have one estimator that is both monotone and smooth. However, monotonicity-constrained estimators can suffer from issues such as significant boundary bias, slower convergence rates, and lack of smoothness. Simply combining a monotone estimator with kernel smoothing can exacerbate these problems, leading to increased bias, loss of smoothness, and loss of monotonicity. In this section, our new method projects a debiased local linear regression estimator onto a monotonicity-constrained spline smoother. This resulting estimator adheres to shape constraints, ensures smoothness, achieves uniform consistency, reduces bias, and maintains a satisfactory rate of convergence. In the numerical study, we use bootstrap to demonstrate the superior performance of our estimator compared to the local linear estimator.Publication Tackling Omitted and Not-Reached Items in Low-Stakes Assessment: A Model-Based Approach(2024-09) Wang, Kelsey DongweiIn low-stakes assessment, there is often a substantive amount of missing data observed from omitted and not-reached items. Missing item responses are often MNAR and lead to biased parameter estimates if not handled properly. This study evaluated and compared the accuracy of parameter estimates between classical approaches and model-based approaches. The study contains an empirical data analysis and a simulation study. For the empirical data analysis, a subset of data from PISA 2018 reading portion of test was selected. Item responses from nine countries were calibrated using traditional approaches and two of the model-based approaches and subsequently compared. It was found that person parameter estimates of the model-based approach are the closest to the model scoring omits as wrong and not-reached as administered. The item parameter estimates from the model-based approaches coincided with the estimates from the model currently adopted by the program for most countries. For the simulation study, it was found that scoring both omitted and not-reached items as not-presented was sufficient to retrieve unbiased parameter estimates in most conditions, even when the rate of missing item responses was extreme.