Masters Theses

The Stalinist regime has long been considered an enigmatic political entity in the annals of history. Scholars have attempted to understand the primary motivations of this regime. Some have focused entirely on its brutality and nature as a totalitarian system. This viewpoint has often resulted in the conclusion that the regime served almost entirely for the purpose of satisfying Stalin’s megalomaniacal desires. This viewpoint often purports that the regime’s ideology of Marxism-Leninism was a secondary feature of the regime, which used it simply as a tool to bend at will in order to justify its autocratic desires. This thesis will contradict elements of that claim. While the Stalinist regime was certainly brutal and totalitarian in nature, its core Marxist-Leninist principles were by no means a secondary feature of its rule. Furthermore, these principles, far from acting as a malleable tool to justify any action, acted as a set of guidelines and restrictions. The regime could, at times, be flexible with some of these boundaries, but by no means could it outright neglect or contradict them. From this system emerged the overarching dynamic of the regime: self-preservation and ideological legitimacy. This the core insecurities and polices of the regime in both the 1930s and the Second World War as the regime sought to keep this volatile dynamic in balance at all times.

The Russian Revolution and formation of the Soviet Union yielded an unprecedented period of ideological, experimental artistic production. Art was esteemed as a method of proliferating monumental propaganda which could educate the Soviet masses about revolutionary ideology and industrial life. A core tenant of this artistic production was illustrated books for children, as well as animated films. Children’s media provided an efficient mechanism to bridge education, entertainment, and nationalism into an individual quotidian artistic product. A considerable portion of this media was created by female artists, who utilized children’s media as a way to generate aesthetic content which corresponded with Soviet values and gendered obligations of labor. Digital methodologies provide a way to explore the relationship between children’s media and gendered artistic labor, with this project placing a critical emphasis on the manifestation of political and social identity in book illustrations. In this project, I used a Princeton dataset of Soviet books published between 1917 and 1939 to examine publication patterns in books illustrated by women. My project posits that digital visualizations can represent the relationship between artist gender and image content, while also modeling broader trends within the Princeton archive.

This thesis examines how Chinese Buddhist institutions from mainland China and Taiwan construct, communicate, and adapt their religious visions within the American context, particularly through practices that engage questions of identity, belonging, and soft power. Drawing on two years of multi-sited ethnographic fieldwork at Fawang Temple in Manhattan, the NYU Buddhist Club, and the Chung Tai Zen Center of Houston, it explores how these institutions articulate and embody their ideals—and how those ideals are negotiated, reinterpreted, or at times undermined through encounters with complex local realities. These realities involve multiple agents who continuously co-produce Buddhism through emotional labor, informal teaching, improvisation, and micro-level decision-making. At the same time, local communities, spatial constraints, and broader sociocultural conditions are not mere backdrops to these transformations but active forces shaping the forms of Buddhism practiced and presented in the American religious landscape. Building on those discussions of lived religion, this thesis examines what “soft power through Buddhism” looks like in practice—how it is enacted, acquires meaning, and evolves through everyday religious life. While scholars such as Ashiwa and Wank argue that the Chinese state mobilizes Buddhism as a form of religious soft power, my fieldwork demonstrates that such influence must be actively enacted through affect, moral vision, and institutional practice rather than assumed from policy discourse. Ultimately, the question is not who speaks for Buddhism abroad, but whose Buddhism people are willing to follow.

The development of targeted cancer therapies is a critical area of research, as conventional treatments often have severe side effects and limited efficacy against drug-resistant tumors. One promising strategy involves reactivating the body’s natural process of programmed cell death called apoptosis. Often, cancer cells suppress these apoptotic pathways to survive, therefore, it represents a promising target for therapeutic intervention. This study aimed to investigate the effectiveness of a novel pro-siRNA technology for silencing key anti-apoptotic genes in different human carcinoma cell lines. We evaluated the effects of silencing JUP, HMGB1, and FASN in HeLa, Huh7, and Caco2 cells. Using RT-qPCR, we confirmed the knockdown of the target genes at the mRNA level. Additionally, chemically synthesized siRNAs were employed as comparators to validate the efficacy of the pro-siRNA constructs. Knockdown of JUP and HMGB1 in Caco2 cells unexpectedly conferred significant resistance to TNF-α-induced apoptosis, reducing relative caspase activity by approximately by 53.6% and 53.1% respectively, in both cases compared to siNC controls. However, in both HeLa and Huh7 cells, the silencing of these genes did not significantly alter the cell's response to the death ligands. These results demonstrate the potential of pro-siRNA technology as a cost-effective and scalable approach for targeted cancer therapy, while also highlighting the cellular heterogeneity and complex survival mechanisms that must be considered in future research and clinical translation.

Background: This study investigates the role of resilience and its interplay with caregiver burden and quality of life (QoL) among family caregivers of individuals with mental illness. The research combines a systematic review of global studies with an empirical case study conducted in Kunshan, China. Objectives: The study aims to (1) Assess resilience levels among caregivers and their associations with sociodemographic and caregiving factors. (2) Examine the relationships between resilience, caregiver burden, and QoL, with a focus on potential mediating mechanisms. Methods: The systematic review included 18 cross-sectional studies, synthesizing global evidence on the relationships between resilience, caregiver burden, and QoL. The case study involved 40 caregivers at a psychiatric rehabilitation station in Kunshan, China, using the Brief Resilience Scale (BRS), Zarit Burden Interview (ZBI-12), and a single-item QoL measure. Results: The systematic review found consistent negative correlations between resilience and burden, and positive associations between resilience and QoL. In the case study, 85% of caregivers exhibited moderate resilience, and 82.5% reported high to severe burden. Resilience significantly predicted lower burden, but did not directly predict QoL. Mediation analysis revealed that caregiver burden fully mediated the resilience-QoL relationship. Conclusions: This study underscores resilience as a key protective factor in caregiving, highlighting its indirect effect on QoL through burden reduction. The findings stress the need for culturally tailored interventions to strengthen caregiver resilience, particularly in non-Western contexts like China.

Ralstonia solanacearum is a highly destructive soil-borne plant pathogen that poses a serious threat to global agricultural production due to its wide host range, high genetic diversity, and strong environmental adaptability. Despite extensive research on its pathogenicity and classification, the evolutionary dynamics across different hosts and regions and the identification of conserved protein targets for sustainable control remain insufficiently understood. In this study, we analyzed 208 Ralstonia solanacearum genomes using pan-genome analysis to characterize core, shell, and cloud gene clusters, revealing an open pan-genome structure and significant genomic variability. Functional enrichment analyses (GO and KEGG) of core genes highlighted conserved metabolic and biosynthetic pathways, which were further explored to identify potential receptor proteins. Using AlphaFold structural predictions, P2Rank binding site prediction, and AutoDock Vina molecular docking, we evaluated the binding affinities of selected key proteins with plant-derived and synthetic antimicrobial compounds. The results provide insights into the evolutionary patterns, host adaptation mechanisms, and potential pesticide targets of R. solanacearum, contributing to a deeper understanding of its control strategies. This study demonstrates the value of integrating comparative genomics and computational approaches for pathogen management and offers a basis for developing more targeted and sustainable disease control measures.Keywords: Ralstonia solanacearum; pan-genome analysis; core genes; functional enrichment; AlphaFold; P2Rank; molecular docking; host adaptation; evolutionary dynamics; pesticide targets

This thesis focuses on optimizing and applying the importance sampling algorithm for context-dependent evolutionary models. First, we use variational inference to update the parameters of the independent-site model as proposal distribution to optimize the importance sampling algorithm. Then, we try blockwise importance sampling algorithm to optimize the importance sampling algorithm. Finally we apply the importance sampling algorithm to estimate unknown parameters given the start and end sequences over a specified time interval.

AbstractBackground: The maternal continuum of care (CoC), including antenatal care (ANC), facility-based delivery, and postnatal care (PNC), is essential for improving maternal and newborn outcomes. In Cambodia, while service coverage has improved over the past two decades, significant gaps remain in the completion of the full continuum of care (CoC), especially among disadvantaged groups. This study assessed trends in CoC coverage, identified socio-demographic determinants of service utilization, and examined gaps by urban and non-urban residence and socioeconomic class across survey years from 2000 to 2022. Methods: This study used repeated cross-sectional data from five rounds of the Cambodia Demographic and Health Survey (DHS), covering 2000 to 2022. Descriptive statistics were used to examine trends in the utilization of ANC, facility-based delivery, PNC, and optimal CoC, Disparity analyses were conducted to evaluate service utilization gaps between urban–rural and wealth subgroups. Multivariable logistic regression models were applied to identify factors associated with service completion, using both single-year (2021–2022) and pooled-year (2010–2022) datasets. Results: Utilization of maternity care improved significantly between 2000 and 2022. The proportion of women receiving ≥4 ANC visits increased from 6.72% to 82.23%, facility-based delivery from 5.79% to 96.54% and optimal CoC rose from 1.6% in 2000 to a peak of 68.9% in 2014, before declining to 46.3% in 2021. However, disparities by educational level and household wealth remained persistent across all services. For example, in 2021, 56.59% of women from the richest households had optimal CoC, comparing to only 30.83% from the poorest group. While urban–rural gaps have narrowed, women with higher socioeconomic status—including higher education, greater household wealth, and health insurance coverage—were significantly more likely to receive optimal ANC and CoC. Wealth-related disparities remained persistent across these services. The notably low PNC proportion in 2021–2022 contributed to the decline in full CoC coverage, underscoring the postnatal stage as a crucial point of dropout within the continuum. Insurance coverage was also a significant predictor of optimal CoC. In 2021–2022, 53.7% of insured women completed the full CoC, compared to 44.3% of uninsured women, highlighting the advantage associated with insurance coverage. Logistic regression analysis also showed that lower parity, older maternal age, and formal employment were significantly associated with higher odds of optimal CoC. Conclusions: Despite significant progress since the year 2000, inequities in utilization of maternity care persisted by socio-economic factors. The results underscore the need for more targeted strategies to support underserved populations, particularly women with low education, income and with no insurance. Future policies should prioritize improving postnatal care uptake and addressing structural barriers to achieving full continuum of maternal care.

Background: Given the growing relevance of post-retirement employment, the lack of significant within-individual health changes following re-employment underscores the importance of controlling for unobserved heterogeneity and cautions against over- interpreting simple associations. Research Aims: This study investigates the bidirectional relationship between health and re-employment among older adults, examining how baseline health predicts re-employment and how re-employment, in turn, affects subsequent health outcomes. Methods: Data were drawn from the Transitions in Health, Employment, Social Engagement and Inter-generational Transfers in Singapore (THE SIGNS) Study, a nationally representative longitudinal survey of adults aged over 60 (N = 2,266). Logistic regression assessed baseline health predictors of re-employment; OLS, ordinal logistic, and first-difference models examined 2019 health outcomes. Results: Baseline self-rated health (OR for excellent vs. poor = 0.689, 95% CI: –0.609 to 1.987), cognitive function (OR= 0.023, 95% CI: –0.227 to 0.273), and depressive symptoms (OR = 0.007, 95% CI: –0.007 to 0.091) were not significantly associated with re-employment in 2019. Re-employment, in turn, was linked to lower odds of better self- rated health when modeled as an ordinal outcome (OR = 0.357, 95% CI: –0.016 to 0.730), but showed a small positive association when health was treated as a continuous variable (β = 0.157, 95% CI: 0.002 to 0.312), indicating model-dependent sensitivity. A marginally positive association was observed for cognitive function (β = 0.107, 95% CI: –0.017 to 0.231), while no significant was found for depressive symptoms (β = –0.034, 95% CI: –0.334 to 0.265). These associations were not replicated in first-difference models, though effect directions remained consistent. Conclusions: Re-employment showed limited health selection effects and modest, model-sensitive associations with later-life health, underscoring the complexity of work-health dynamics in aging populations.Keywords: Aging, Re-employment, Self-rated health, Cognition, Depression, Singapore

Growing global energy demands coupled with the detrimental environmental impacts of fossil fuel combustion highlight an urgent need to develop sustainable energy technologies. Electrochemical water splitting stands as a promising approach to convert renewable energy sources to hydrogen, a clean and carbon free energy carrier, for applications and energy transportation. However, the process requires efficient, durable, and cost-effective electrocatalysts that are still being developed. Non-precious metal nitrides have recently garnered significant attention due to their excellent catalytic properties, low cost, and high stability. This thesis focuses on several important aspects related to this catalyst family. Chapter 1 discusses recent advancements and fundamental methodologies in electrocatalyst research relevant to water splitting applications. Chapter 2 describes the system involving the development of nitridated NiMoO4 nanoneedles as a catalyst for the hydrogen evolution reaction (HER). The optimized material shows strong HER performance in alkaline solution, with low overpotentials, favorable Tafel slopes, and stable long-term operation. Notably, the catalyst reaches a high current density of 350 mA/cm² at an overpotential of only -10 mV, showing its potential for practical hydrogen production. Chapter 3 focuses on Co3Mo3N nanoparticles used as a photo-thermal electrocatalyst for the oxygen evolution reaction (OER) and its improved performance under both light and heat. Electrochemical testing shows that Co3Mo3N catalyst has a significant photo-thermal enhancement in OER. For example, under 2 watts of blue light, it achieves a 150% increase in current density at an overpotential of 0.34 V. The outstanding effect of photo-thermal enhancement of the catalyst indicates its potential in light-assisted water-splitting technologies. Overall, this research supports the development of affordable, high-performance catalytic materials for clean energy applications.

Extreme heat events have become increasingly frequent with global climate change, posing significant threats to maternal and fetal health. Although epidemiological studies have suggested associations between maternal heat exposure during pregnancy and adverse birth outcomes, direct experimental evidence on how heat exposure leads to fetal growth restriction (FGR) and the underlying mechanisms is still lacking.This study used a mouse model to explore the impact pathway of maternal heat exposure leading to FGR with a focus on the placenta. Female CD1 mice were divided into a room temperature group (25°C) and a heat exposure group (40°C, 50% humidity, 2 hours daily throughout pregnancy). Placenta and fetal samples were collected, and weights were recorded at key gestational stages at embryonic day 7.5 (E7.5), E10.5, E13.5, E16.5, and E18.5. Maternal heat exposure significantly decreased placental efficiency and fetal weight at E13.5 and E16.5, and lower birth weight on postnatal day 1 (PND1) (p<0.05) compared to the control group. Using photoacoustic imaging technology (PAM), we dynamically monitored placental blood oxygen saturation (sO₂), blood perfusion, and vessel diameter before and after heating (40°C, 30 minutes). The results showed that heat exposure significantly reduced placental blood oxygen saturation, blood perfusion, and vessel diameter across all gestational stages. The study recapitulated well-established adverse birth outcomes associated with maternal heat exposure, including fetal growth restriction and low birth weight, validating the model’s translational relevance. Our study further revealed an underlying mechanism of this association through placental hypoxia. These findings highlight the importance of incorporating heat exposure risks into maternal health management and advancing climate-adaptive strategies in clinical and public health settings.

Introduction: Caregiver-child interactions are vital for the cognitive, emotional, and social communicative development of young children. In low- and middle-income countries (LMIC), and other settings with inadequate health resources to cater for autistic individuals, caregiver-mediated interventions have shown potential to address the vast unmet needs of those who need autism care. Over the last decade, there has been a significant increase in research output on the use of caregiver-mediated interventions in autism care, however, there is little knowledge to whether caregiver and child characteristics affects the caregivers’ use of intervention strategies during caregiver-child interactions. With this existing research gap, it is imperative to study the association of the caregiver and child characteristics with the caregiver’s use of strategies to support the social communication abilities of their young autistic children in a LMIC. Study Aim: Determine the association between caregiver and child characteristics with the caregiver’s use of strategies to support the social communication development of their young autistic children. Methods: This is a sub-study of the parent study, Autism Caregiver Coaching in Africa (ACACIA), conducted in the Centre for Autism Research in Africa (CARA) at the University of Cape Town, South Africa. This sub-study utilized an exploratory, cross-sectional design. At study enrollment, baseline data of the caregiver-child dyads was obtained, and a 6-minute video of the caregiver and child interaction was recorded and coded using the Parent-Early Start Denver Model fidelity scale (P-ESDM). The measures included participant sociodemographic questionnaire, Caregiver Strain Questionnaire, Autism Observational Diagnostic Schedule – 2nd Edition (ADOS-2), and P-ESDM scale. A sociodemographic risk score was conceptually developed for data analysis. Scatterplots, and linear regression analyses were used to determine the association between four explanatory variables of interest (sociodemographic data, Caregiver Strain, ADOS-2 comparison score, Sociodemographic Risk Score), and the outcome variable (P-ESDM total fidelity score). Unadjusted analyses included a single explanatory variable, adjusted included all four variables of interest. Results: 41 participants caregiver-child dyads enrolled into the study, and 39 caregiver-child dyads had all the baseline data available. Among the 41 caregivers, the mean age was 38.8 years, and most (35/41, 85.4%) were females. For the 41 children, the median age at study enrolment was 59 months, and most (35/41, 85.4%) were males. There was no evidence of an association between caregiver strain and fidelity or between the sociodemographic risk score and fidelity. However, there was an indication of a negative association with child age at enrollment (Adjusted: 0.31 units per month; 95% CI: 0.03, 0.6) and a negative association with autism severity (Adjusted: 3.1 units per 1-unit increase in severity score 95% CI: 1.2, 5.1) in unadjusted and adjusted analyses. Conclusion: The result showed that prior to initiation of caregiver-coaching interventions in ACACIA study, there was no evidence that the sociodemographic risk score and caregiver strain affects the caregiver’s use of strategies. Instead, the significant factors were the autism-related behaviors and the child’s age at enrollment, of which both factors have a negative association with caregiver’s use of strategies at baseline. As caregiver-mediated interventions emerge as a crucial tool for addressing the unmet needs of autism care in LMIC and other low-resource settings, understanding and leveraging the factors that influence caregivers’ use of strategies is essential in supporting the social communication development of autistic children.

The regulated degradation of Auxin Response Factors (ARFs) is central to the dynamic control of auxin signaling, a hormone pathway critical for plant development. However, the specific degron sequences that signal ARF proteins for degradation remain poorly defined. This thesis focuses on identifying the degron region within ARF2, a transcriptional repressor and key regulator of auxin responses in Arabidopsis thaliana.To localize the degron, the ARF2 gene was divided into 28 overlapping segments, each cloned into a dual-fluorescence vector containing mNeonGreen and mScarlet. These constructs were transformed into protoplasts (plant cells with a dissolved cell wall), and fluorescence ratios were analyzed to infer degradation activity. Due to inconclusive results from the segmented approach, a second strategy was employed that split ARF2 into three functional regions: the DNA-binding domain (DBD), the intrinsically disordered middle region (MR), and the PB1 domain. Fluorescence assays were used to compare stability across these larger domains, supported by colony PCR and sequencing for construct validation. Results indicated region-specific differences in degradation likelihood and demonstrated that the protoplast assay system is sensitive to degradation-dependent fluorescence changes. These findings lay a methodological foundation for more refined biochemical and genetic studies. Future work could apply targeted mutagenesis, hormone treatments, and protein-interaction analyses to test hypotheses about signal-induced degron exposure, interaction-based stabilization, and post-translational modification. This study establishes a tractable system for probing the post-translational regulation of ARFs and proposes a framework for continued investigation into the molecular logic of auxin signaling.

This study evaluates the geological suitability of the subsurface geology of the Durham Triassic sub-basin at Duke University for the implementation of an Aquifer Thermal Energy Storage system. The proposed project would capture excess electricity-driven heat produced by chiller plants on Duke's campus during the summer. This heat would be transferred to a water source using a heat exchanger, and the heated water would then be pumped underground for storage until winter. During the winter, the stored hot water would be pumped back up and used as a supplemental heat source for campus buildings which are currently heated by CO2 producing natural gas. To assess ATES potential, cores drilled from a 202-meter (666-foot) borehole on Duke's central campus drill site were analyzed. In addition, we collected hand samples from nearby outcrops in the Durham sub-basin and created rock thin sections to determine mineralogy and sediment characteristics including grain size and porosity. We found sequences of sandstone layers in the core that were 1-5 meters thick. We also found a range of porosities from outcrop hand samples (median porosity 8.2% ±5.9%). Preliminary pumping tests suggest low flow rate (~0.03-10 gallons per minute) could impede ATES potential in the Durham sub-basin. By understanding the geological characteristics of the site, we can better understand what it would take to tailor and optimize the design and operation of the ATES system for maximum energy storage. The project will study Durham sub-basin geology to determine suitability for a proof-of-concept ATES system to facilitate targeted deployment across the Durham region for communities in need.

AbstractObjective To develop a 3D-printed phantom that accurately replicates patient-specific anatomical geometry, tissue textures, and attenuation characteristics derived from CT scans, thereby enabling precise lung tissue properties simulation for radiological medical imaging applications. Materials and Methods A streamlined workflow was developed to convert DICOM-format CT images into printer-executable G-code, eliminating conventional segmentation and intermediate file formats (e.g., STL). Using fused deposition modeling (FDM) with a 0.2-mm nozzle and polylactic acid (PLA) filament, the algorithm dynamically adjusts nozzle speed (5–50 mm/s) and extrusion rates to control line width (0.1–1 mm), thereby managing voxel density and replicating Hounsfield Unit (HU) values (-900 to 100 HU). Validation experiments used patient-specific lung CT data, and phantom accuracy was assessed through geometric measurements and HU value comparisons between printed models and original patient scans. Results The printed phantoms demonstrated a linear correlation (R² > 0.95) between designed fill rates and measured HU values, achieving submillimeter geometric accuracy in replicating lung vasculature and parenchymal structures. Manual measurements of 10 regions of interest (ROIs) revealed less than 5% deviation in dimensional fidelity, while HU distributions in phantom scans matched patient data within clinically acceptable margins (±50 HU). The method successfully simulated heterogeneous tissue textures, with printer parameters allowing for precise control over density gradients critical for radiometric applications. Conclusions This study introduces a breakthrough in patient-specific phantom fabrication, providing a rapid and cost-effective solution for validating CT-based techniques without exposure to ionizing radiation. The direct DICOM-to-G-code workflow ensures high anatomical and radiological fidelity and has applications in radiotherapy dosimetry, imaging protocol optimization, and medical training. Future research will expand to include multi-material printing and dynamic motion simulation to improve physiological realism.

This study is motivated by the increasing need to mitigate storm-induced urban flooding, particularly in highly developed environments near floodplains or humid coastal regions, where climate change has intensified extreme rainfall events. The study explores a top-down approach to stormwater drainage system design, contrasting with the conventional bottom-up implementation commonly seen in urban planning.Two drainage pipe network layouts are evaluated within the Storm Water Management Model (SWMM) under identical storm conditions: one with a 4:1 inlet-to-outlet ratio per junction (shorter total flow path) and another with a 2:1 inlet-to-outlet ratio per junction (longer flow path with intermediate layer of pipes). Performance is compared based on runoff-outflow delay and internal system storage volume, using a controlled study area with consistent input parameters. To improve simulation accuracy, additional pipe flow networks replicating overland flow paths are incorporated, ensuring the full water movement process is represented—from surface accumulation to final discharge. Findings indicate that reducing in-system flow path length minimally impacts outflow delay, whereas shortening overland flow paths by increasing drainage inlets significantly improves performance. Results also suggest that dynamic storage volume does not correlate with discharge flow rate, indicating potential for increasing internal storage through intermediate pipe layers and extended conduit paths without negatively affecting system efficiency.

Energy drink consumption has become increasingly popular in Cambodia since theintroduction of Red Bull in 1997. High in caffeine and sugar, energy drinks are often marketed as energy boosters but are associated with various health risks, including cardiovascular diseases, neurological disorders, and metabolic issues such as diabetes. While existing studies have primarily focused on the health impacts of energy drinks in developed countries, there is a lack of qualitative research exploring the socio-cultural and economic factors influencing energy drink consumption in developing countries like Cambodia. This study is a qualitative study using in- depth interviews and observations to collect data. The result demonstrates that numerous factors shape their energy drink consumption behavior, including social norms, peer influence, economic factors, and accessibility. Simultaneously, some of them have attempted to reduce or stop energy drink consumption, aligning with the health action process, with emphasis on the transition from intention to action in health behavior. This finding innovatively bridges the gap between energy drink consumption and diabetes from polybasic aspects and provides solid evidence for policy making in the realm of global health in Cambodia

Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, with non-invasive imaging playing a crucial role in its diagnosis and management. However, optimizing these imaging technologies to improve patient outcomes remains a challenge. Virtual imaging trials (VITs) provide a powerful alternative to traditional clinical studies by using computational phantoms, virtual patients that can be imaged with simulated scanners, to systematically evaluate imaging technologies. The 4D extended Cardiac-Torso (XCAT) phantom series is one of the most widely used computational phantoms, providing anatomically detailed whole-body models with cardiac and respiratory motion. Despite their utility, the current XCAT cardiac models are limited in their ability to represent population variability and physiologically informed motion. The existing models are derived from gated 4D CT data of only two healthy individuals (one male, one female), restricting their ability to capture diverse anatomical and functional variations. Furthermore, abnormal cardiac motion is introduced manually, lacking a physiological basis and reducing realism and scalability. To address these limitations, this work explores techniques to develop a new series of 4D beating heart models derived from multiple sets of 4D cardiac-gated CT data. By segmenting and analyzing patient-specific cardiac motion, we first investigate an image-based method to construct a population of anatomically variable heart models that better reflect real-world variability, comparing the motion patterns to values reported in the literature. To further enhance realism, we explore a workflow for generating controlled variations in both normal and abnormal cardiac motion using finite element (FE) simulations. This approach integrates patient-specific electrophysiology and morphological parameters, allowing for the generation of physiologically informed cardiac motion models. These enhanced models can be integrated into whole-body XCAT phantoms to provide a novel population of virtual subjects with realistic anatomical and functional variability. The models can provide a valuable tool for virtual imaging trials, enabling the evaluation of emerging cardiac imaging technologies on a representative range of patient anatomies and motion patterns.

The post-COVID inflationary surge and subsequent disinflation have generated significant debate regarding their causes and policy implications. This paper assesses the drivers of inflation from the onset of the COVID-19 pandemic through the subsequent disinflation, with a particular focus on the sharp decline in inflation from June to July 2022. Using the Consumer Price Index (CPI), this analysis evaluates six primary explanations for inflationary trends: energy price shocks, supply chain disruptions, firm pricing power, wages and worker bargaining power, inflation expectations, and government stimulus.

A Rolling-Window Granger Causality model is employed to assess the temporal relationships between inflation and key economic indicators, allowing for a structural break in the data coinciding with initial stay-at-home orders. This approach identifies real personal expenditures, and the labor leverage ratio as significant contributors to the initial inflationary surge, while over-water shipping costs and the Federal Funds Rate exhibits a delayed relationship with disinflation. A time-interaction linear model is further applied to test the impact of identified economic events on inflation trends, revealing a lack of support for the common narrative that corporate profits, consumer income, or government transfers significantly drove inflation.

The findings suggest that inflation was largely driven by real economic shifts rather than speculative price-setting behavior, and that Federal Reserve policy may not have been the primary driver of disinflation. These results highlight the need for a more nuanced approach to assessing the causes of inflation and the efforts to mitigate it.