Washington University Medical Center
Washington University St. Louis: Open ScholarshipNot a member yet
26344 research outputs found
Sort by
The Psychology of Sharing Experiences
No full textFrom dinners with family to parties with friends, consumers frequently spend time with and share experiences with other people. Sharing consumption with other people can uniquely shape people’s decisions and experiences, often in ways that differ from when individuals are on their own. In my research, I examine what kinds of experiences consumers like to share with other people, and how being the one who organizes gatherings for other people influences consumers’ decisions and experiences during shared consumption. In Chapter One, “When Sharing Experiences with Others, People Prefer Novel Experiences,” I examine how the social context of an experience, in particular whether someone has a companion during the experience, influences their preferences for new experiences. Consumers are often drawn to familiar and tried-and-true options, but there is also value in trying new things. I show that people prefer novel experiences when they will share them with other people versus have them alone. Doing something with someone else, as opposed to by oneself, reduces the feelings of awkwardness—that is, the perceived discomfort from not knowing what to do—associated with trying something new, and leads people to prefer novel options over familiar ones. This preference for novelty is amplified when the option is new to the self but familiar to the consumption partner, such that the consumption partner can serve as a guide when navigating new experiences, and is strongest when consumers are going to share the experience with someone they are particularly close to. This research suggests that being with others can encourage individuals to step outside their comfort zones and open doors to new experiences. Chapter One examines how simply being in the company of someone else can influence consumers’ choices in shared experiences. In the other two chapters, I examine the decision-making processes, experiences, and psychology of those who organize social gatherings where these shared experiences happen: hosts. Consumers commonly host parties and other gatherings for family and friends, yet little is known about how hosting uniquely shapes the choices consumers make for such shared consumption experiences. In Chapter Two, “Hosting Leads People to Make Self-Reflective Choices for Shared Consumption,” I examine how hosts make decisions for the parties and other gatherings that they organize. Although one might expect hosts to prioritize guests’ preferences, I find that hosts more strongly prefer options that feel like “them”—that is, options that reflect their personal tastes and preferences rather than their guests’—compared to someone making the same choice for a gathering but not in the role of host. This tendency is driven by hosts’ greater sense of ownership over a gathering, and a stronger desire to share something about themselves with the other people at the event. The findings shed light on hosting as a unique decision making context and provide insight into how the party industry can appeal to hosts. In Chapter Three, “Hosts Feel Like They Miss Out on Their Own Gatherings,” I examine how taking on the role of the host of a gathering can interfere with the host’s ability to take full advantage of the shared experiences they set out to create. Despite how integral hosts are to parties, they feel more like they “miss out” during a get-together than do their guests. This happens because hosts’ feelings of responsibility over their gatherings lead them to divide their attention more than guests, rather than simply because hosts spend less time with the other people at the gathering or because they know more people there and thus have more to miss out on. I show that sharing hosting responsibility with a co-host does not free up attention or reduce the feeling one has missed out, but dividing responsibility by delegating elements to someone else can make hosts feel less attentionally divided, less like they miss out, and more interested in hosting again. This research illuminates how social roles and their attentional requirements shape shared experiences and reveals how to help people feel more connected to others. The presence of others makes our lives richer and fuller. Overall, my dissertation contributes to our understanding of how sharing experiences with others, whether by merely having a companion or by being in charge of organizing social gatherings, uniquely impacts consumer experiences and decisions. The findings offer implications for consumers seeking more meaningful and connecting shared experiences, as well as for marketers aiming to promote products and services that are meant to be enjoyed with others
Data Registration Techniques for Optical Functional Brain Mapping
No full textOptical functional brain mapping presents a versatile, portable, and cost-effective alternative to conventional functional imaging techniques such as functional magnetic resonance imaging (fMRI). However, optical imaging does not inherently capture anatomical details and relies on existing structural imaging to generate accurate brain maps. By employing head models that incorporate participant-specific anatomy, imaging array placement, and the optical properties of underlying tissues, optical functional brain mapping can achieve results comparable to those of fMRI. Despite advances in registration techniques, the creation of atlas-derived yet participant-specific head models remains a significant challenge. My research endeavors to develop innovative registration and analysis pipelines for optical functional brain mapping by (1) estimating participant-specific scalp morphology using three-dimensional (3D) scanning, photogrammetry, and an atlas, (2) localizing imaging array placement in 3D from two-dimensional (2D) images, and (3) establishing and validating an alternative analysis and registration method for longitudinal optical functional brain mapping studies. The focus is on developing scalable algorithms that are independent of imaging array design, computationally efficient, and applicable in low-resource environments. This work aims to establish accurate registration in the absence of participant-specific structural imaging and promote the development of simplified pipelines for more widespread use
Characterization of Atmospheric Particles and Gases Based on Mass Spectrometry
No full textThe atmosphere is composed of gases and particles, some of which are recognized as air pollutants owing to their detrimental impact on human health. Beyond their health effects, air pollutants also influence atmospheric reactivity and global radiative forcing. Chemicals such as volatile organic compounds (VOCs) play an important role in the formation and evolution of air pollutants in both particulate and gaseous phases. The characterization of atmospheric particles and gases necessitates sophisticated analytical techniques capable of resolving complex mixtures across wide concentration ranges. Mass spectrometry (MS) is among the most widely used and informative methods and has revolutionized the field of atmospheric chemistry by providing detailed, high-resolution, molecular-level information. This dissertation focuses on the characterization and implications of atmospheric particles and gases as well as the methodological development based on mass spectrometry techniques. Specifically, this work examines brown carbon (BrC) and VOCs as the targets in the particulate phase and gaseous phase, in Chapter 2 and Chapter 3, respectively, and develops an offline aerosol mass spectrometry (AMS) technique in Chapter 4. Atmospheric brown carbon (BrC) from wildfires is a key component of light-absorbing carbon that significantly contributes to global radiative forcing, but its atmospheric evolution and lifetime remain poorly understood. In Chapter 2, the evolution of BrC is investigated by synthesizing data from one laboratory campaign and three aircraft campaigns spanning diverse spatial scales across North America. A method to parameterize the emission ratios of BrC and other species using inert tracers such as acetonitrile (CH3CN) and hydrogen cyanide (HCN) commonly measured by chemical ionization mass spectrometry (CIMS) across campaigns has been developed to estimate the initial conditions for evaluating plume evolution. The BrC evolution is then characterized as a function of hydroxyl radical (OH) exposure. VOCs are key contributors to air pollution and human exposure to toxic chemicals. Their spatial and temporal variability, diverse sources, and chemical complexity present significant challenges for exposure assessment and air quality management. Chapter 3 presents the deployment and application of the Multichannel Organics In-situ enviRonmental Analyzer (MOIRA)a mobile, high-resolution gas chromatography-mass spectrometry (GC-MS) system developed for dynamic, speciated VOC measurements. MOIRA was deployed during the Neighborhood-Scale Assessment of Volatile Organic Compounds in Air (NAVOCA) campaign across a range of indoor and outdoor environments in Louisville, Kentucky. Key findings demonstrate MOIRA’s ability to capture VOC data in multiple different environments. The study underscores the importance of microenvironmental context in VOC exposure and supports the development of routine indoor-outdoor monitoring strategies. Together, these studies demonstrate the value of MS technology in advancing atmospheric chemistry and air quality research. The methodologies and findings presented contribute to improved climate modeling, instrumentation, exposure assessment, and the design of effective environmental health interventions. The High-Resolution Time-of-Flight Aerosol Mass Spectrometry (HR-TOF-AMS) instrument is a widely utilized instrument that enables the quantitative analysis of non-refractory inorganic and organic aerosol species. Chapter 4 presents the development, evaluation, and optimization of an offline AMS technique aimed at chemically characterizing aerosol samples collected on filters by leveraging the capability of HR-TOF-AMS. This technique addresses logistical and financial barriers to widespread AMS deployment, thereby extending the temporal and spatial coverage of aerosol chemical analysis, particularly in underrepresented regions and during non-summer seasons. The study also highlights the potential of the offline AMS technique to be integrated into the Surface Particulate Matter Network (SPARTAN), a global aerosol monitoring initiative. The findings underscore the technique’s value in enhancing long-term, multi-site aerosol studies and support its broader application in atmospheric chemistry, air quality assessment, public health, and climate research
Resilient Safe Control of Autonomous Systems
No full textAsimov\u27s Three Laws of Robotics famously outlined fundamental safety principles governing human-robot interaction. This foundational concept of safety is paramount for today\u27s autonomous systems, such as robots, which possess inherent cyber-physical properties. With the increasingly widespread application of autonomous systems in real-world environments, the challenges facing research on formal safety verification have grown even more significant. However, end-to-end verification of such complex, integrated systems remains an open and formidable challenge due to their high dimensionality, nonlinearity, and the use of learning-based components. This thesis approaches this challenge by pursuing verifiably safe autonomy from two complementary directions: (i) safe control of learning-enabled systems providing formal guarantees and (ii) resilient safe control that maintains formal safety guarantees under extreme scenarios such as sensor faults and cyber-physical attacks. The first half of this dissertation presents the formal verification of autonomous systems that integrate learning-enabled components. It starts with the safety verification of neural control barrier functions (NCBF) employing Rectified Linear Unit (ReLU) activation functions. By leveraging a generalization of Nagumo\u27s theorem, we propose exact safety conditions for deterministic systems. To manage computational complexity, we enhance the efficiency of verification and synthesis using a VNN-based (Verification of Neural Networks) search algorithm and a neural breadth-first search algorithm. We further propose the synthesis and verification of safe control for stochastic systems. The second half of this dissertation broadens the scope of end-to-end verification by explicitly accounting for imperfections and perturbations. We first proposed Fault-Tolerant Stochastic CBFs and NCBFs to provide safety guarantees for autonomous systems under state estimation error caused by low-dimensional sensor faults and attacks. We then investigate the unique challenges posed by Light Detection And Ranging (LiDAR) perception attacks. We propose a fault detection, identification, and isolation mechanism for 2D and 3D LiDAR and provide safe control under attacks
Data-Driven Discovery and Evaluation of Brain Models Using Data From Magnetic Resonance Elastography and Tagged Magnetic Resonance Imaging
No full textTraumatic brain injury (TBI) has been the focus of multidisciplinary research for decades due to its significant impact and high incidence rate. Computational models, simulations of TBI, and in vivo human brain imaging methods such as magnetic resonance elastography (MRE) and tagged magnetic resonance imaging (tagged MRI) are powerful tools to understand the mechanisms of TBI, from the loading and kinematics to strain fields experienced by brain tissue to its complex pathology. Remaining challenges include: 1) assumptions and approximations in models and simulations; 2) limited model evaluations; 3) low-amplitude (linear-regime) deformations in experiments; 4) the effect of noise on experimental strain calculations; and 5) the high dimensionality of brain deformation fields, making them computationally expensive to simulate and analyze. These difficulties compromise our understanding of TBI, raise questions concerning the biofidelity of simulations, and limit the generalizability of in vivo experiments to real-world TBI scenarios. Two main objectives are pursued in this thesis: 1) developing a quantitative comparison framework that can provide objective scores for the degree of similarity (or discrepancy) across measured and simulated human brain deformation; and 2) discovering the governing equations of human brain and reducing the dimensionality of brain deformation by revealing the dominant coherent patterns. To achieve the first aim, we introduced a framework that integrates nonlinear registration with image-based reconstruction of the finite element mesh and developed new correlation metrics that enable local and global comparisons across multiple simulations and experiments. The second aim was accomplished by designing a novel data-driven algorithm, time-augmented, space-contracted dynamic mode decomposition (TASC-DMD), and combining it with sparse identification of nonlinear dynamics (SINDy) to discover reduced-order models (ROMs) and governing equations describing the dynamics of 45 in vivo human brain tagged MRI subjects. Additionally, we showed that TASC-DMD is a universal dimensionality reduction technique that outperforms other popular DMD methods in modeling spatiotemporal data and capturing the correct underlying physics from quantum mechanics to fluid flows
Leveraging Ownership: Comparative Analysis of Old North and Pruitt-Igoe
No full textThis paper compares the failed top-down development of St. Louis\u27 Pruitt-Igoe with the community-based efforts of the Old North neighborhood
Safe Sex in the Age of Big Tech Feminism
Get PDFLawmakers and technology companies are regulating online sexuality in the name of feminism. Whereas libertarian ideals dominated early debates about internet governance, “safety” became a rallying cry to regulate online activity in the age of Big Tech. As these regulatory paradigms now clash once again, one trend remains: legislators across the political spectrum and companies around the world are devising interventions that purportedly keep people—and especially women—safe from the risks of online sexuality. Through law and technology, they are targeting everything from privacy invasions to unwanted messages to sexual deepfakes. We call this regulatory and ideological trend Big Tech feminism.This Article interrogates the feminist strands animating Big Tech feminism. Overall, regulators are favoring prudish and punitive measures to promote sexual safety, repurposing concerns about sex harms to control and penalize harmless sexual activity. Big Tech feminism is hardly novel in this regard. Rather, it is a contemporary example of how some feminists align with power elites to develop systems of sex regulation at the expense of sexual autonomy.This Article offers an alternative regulatory agenda grounded in queer and critical feminist theory. It decenters punishment of wrongdoers and focuses on the social determinants of safety. Safety is best served by structuring sexual life more fairly and empowering everyone to shape the norms and terms of online sexuality. The interventions advanced here would allow people to navigate sexual risks and pleasures more autonomously and, thus, more safely. In this tumultuous moment for governing online activity, we reimagine safety to renew the emancipatory potential of a feminist agenda
In Search of Extreme Extragalactic Energy: A catalog of TeV-emitting BL Lac candidates from eROSITA and WISE
Get PDFActive galactic nuclei (AGN) are supermassive black holes that reside at galactic centers and are actively accreting matter. In approximately 10% of cases, AGN produce relativistic jets: collimated streams of particles that travel for thousands of light years and have been detected at TeV energies by ground-based gamma-ray observatories. However, the mechanisms that accelerate particles beyond the TeV scale are largely unknown. Currently, only 56 objects are confirmed to accelerate particles to these extreme energies. Here we provide a selection of over 150 sources that exhibit infrared (IR) and X-ray emission profiles similar to those of the 56 TeV sources. In performing this selection, we develop new constraints on the IR and X-ray emissions of TeV-emitting sources using data from the WISE ALLSKY (WISEA) catalog and the eROSITA-DE Data Release 1. We compare our candidates to existing catalogs interested in selecting TeV-emitting AGN and find a selection of 35 previously unidentified candidate sources for extreme particle emission. Within this selection 32 of these sources are not detected by Fermi-LAT as gamma-ray sources, despite exhibiting IR and X-ray emission profiles characteristic of TeV sources. With further study, these 32 sources will motivate a correlation between the X-ray and TeV emissions of AGN. TeV observations of the candidates proposed in our work will unveil new constraints on the emissions of relativistic jets. With improved constraints, better theoretical models of particle acceleration within relativistic jets can be developed and our understanding of galactic/black hole evolution and structure formation in the universe can be refined
Studies in Algebraic Cycles: Hodge Theory of Degenerations, Regulators, and Cluster Varieties
Get PDFThis dissertation brings together results in Hodge theory and the theory of cluster varieties. The second chapter, based on a paper written in collaboration with Devin Akman and Matt Kerr, uses admissible normal functions to establish the first finiteness result for zero-dimensional components of the Hodge locus. The third chapter, based on joint work with Matt Kerr, shows that weak polar- ized relations constrain possible adjacencies of mixed Hodge structures across boundary strata in geometric compactifications. The fourth chapter gives a geometric construction of a 6-dimensional cluster variety with a disconnected mutation graph, as discovered by Yan Zhou. These three chap- ters employ different techniques, but they are tied together by the common threads of algebraic cycles and the Hodge theory of degenerations
Focused ultrasound-enhanced agent transport in the brain
No full textBlood-brain barrier (BBB) is a crucial neurovascular unit that maintains the homeostasis of the central nervous system but also poses a significant challenge for brain disease treatment and diagnosis. Focused ultrasound combined with microbubbles (FUSMB) has emerged as a promising technique for noninvasive, localized, transient and safe BBB opening, thereby enhancing both drug delivery for treatment and biomarker detection for diagnosis of brain diseases. Extensive research has demonstrated the potential of FUSMB-enhanced drug delivery to various brain diseases. The conventional treatment for diffuse intrinsic pontine glioma (DIPG) remains challenging due to the often-intact BBB, making FUSMB a strong candidate for DIPG drug delivery. In parallel, FUSMB-enhanced biomarker release for brain disease diagnosis has progressed rapidly, yet few studies have explored its broader applications such as gene therapy monitoring in the brain. Reporter genes used in gene delivery can serve as measurable biomarkers released by FUSMB, offering a safer alternative to radioactive tracers in nuclear imaging. Despite advances in applications, the biophysical mechanism of how FUSMB enhances agent transport remains unclear. Neither drug delivery outcomes in brain nor biomarker levels in plasma reveal the biophysical process during FUSMB treatment. Real-time capture of the FUSMB-enhanced agent transport is needed to better elucidate the mechanisms. My dissertation aims to leverage the FUSMB-enhanced agent transport for brainstem drug delivery and gene therapy monitoring, followed by biophysical mechanism study on the microscopic level. The research is divided into three specific aims. The first aim optimized the FUS sonication patterns, microbubble administration methods and FUS pressures for FUSMB treatment at the mouse brainstem. The optimized strategy achieved efficient, homogenous, and safe large volume drug delivery at the brainstem, providing guidance for future development of FUSMB treatment in DIPG. The second aim evaluated the capability of FUSMB to release biomarkers for monitoring gene delivery in the brain. Released biomarkers showed dependency on FUS pressure, enhancement on multiple molecular levels, and spatial concordance with the true expression in the targeted region, demonstrating FUSMB as a promising tool for gene delivery monitoring. The third aim investigated real-time interaction between FUSMB and agent transport in the mouse brain using in vivo two-photon microscopy. FUSMB induced vessel deformation at the affected vasculature, which was found to be highly correlated with the enhanced agent transport. This indicated that FUSMB-induced vessel deformation plays an important role in regulating the agent transport, providing valuable insights into the underlying mechanism. In conclusion, my thesis optimized FUSMB-enhanced brainstem drug delivery, characterized FUSMB-enhanced gene-therapy reporter release, and investigated real-time microscopic bioeffects, laying foundation to broaden applications and understand the mechanisms underlying FUSMB-enhanced agent transport in the brain