Time-Resolved Cryo-EM Studies on Translation and Cryo-EM Studies on Membrane Proteins

Fu, Ziao Columbia University ProQuest Dissertations & These 2019 해외박사(DDOD)

소속기관이 구독 중이 아닌 경우 오후 4시부터 익일 오전 9시까지 원문보기가 가능합니다.

Single-particle reconstruction technique is one of the major approaches to studying ribosome structure and membrane proteins. In this thesis, I report the use of time-resolved cryo-EM technique to study the structure of short-lived ribosome complexes and conventional cryo-EM technique to study the structure of ribosome complexes and membrane proteins. The thesis consists three parts. The first part is the development of time-resolved cryo-EM technique. I document the protocol for how to capture short-lived states of the molecules with time-resolved cryo-EM technique using microfluidic chip. Working closely with Dr. Lin's lab at Columbia University Engineering Department, I designed and tested a well-controlled and effective microspraying-plunging method to prepare cryo-grids. I demonstrated the performance of this device by a 3-A reconstruction from about 4000 particles collected on grids sprayed with apoferritin suspension. The second part is the application of time-resolved cryo-EM technique for studying short-lived ribosome complexes in bacteria translation processes on the time-scale of 10-1000 ms. I document three applications on bacterial translation processes. The initiation project is collaborated with Dr. Gonzalez's lab at Chemistry Department, Columbia University. The termination and recycling projects are collaborated with Dr. Ehrenberg's lab at Department of Cell and Molecular Biology, Uppsala University. I captured and solved short-lived ribosome intermediates complexes in these processes. The results demonstrate the power of time-resolved cryo-EM to determine how a time-ordered series of conformational changes contribute to the mechanism and regulation of one of the most fundamental processes in biology. The last part is the application of conventional cryo-EM technique to study ribosome complexes and membrane proteins. This part includes five collaboration projects. Human GABA(B) receptor project is the collaboration with Dr. Fan at Department of Pharmacology, Columbia University. Cyclic nucleotide-gated (CNG) channels project is the collaboration with Dr. Yang at Department of Biological Sciences, Columbia University. The cryo-EM study of Ybit-70S ribosome complex and Cystic fibrosis transmembrane conductance regulator (CFTR) project are the collaboration with Dr. Hunt at Department of Biological Sciences, Columbia University. The cryo-EM study of native lipid bilayer in membrane protein transporter is the collaboration with Dr. Hendrickson at Department of Biochemistry and Molecular Biophysics, Columbia University and Dr. Guo at Department of Medicinal Chemistry, Virginia Commonwealth University.

Politics by Other Means: Economic Expertise, Power, and Global Development Finance Reform

Bhatt, Jigar D Columbia University ProQuest Dissertations & These 2018 해외박사(DDOD)

소속기관이 구독 중이 아닌 경우 오후 4시부터 익일 오전 9시까지 원문보기가 가능합니다.

This dissertation investigates how economic expertise influences development governance by examining how state economists establish methods for decision-making in global development finance. It contributes to debates over expert power by taking. State economists' efforts to establish three paradigmatic development economic methods in particular---governance indicators, growth diagnostics, and randomized controlled trials---and these methods' effects on power relations, decision-making. This dissertation's focus on economists' political work and methods has implications for planning practice because it opens up new political possibilities. Rather than treating state expertise and public participation as antagonistic, zero-sum c.

Dynamic Pricing and Demand Shaping: Theory and Applications in Online Assortments, Ride Sharing and Smart Grids

Wang, Shuangyu Columbia University ProQuest Dissertations & These 2019 해외박사(DDOD)

소속기관이 구독 중이 아닌 경우 오후 4시부터 익일 오전 9시까지 원문보기가 가능합니다.

This dissertation consists of three papers in revenue management: on-line assortment optimization with reusable resources, spatial distribution of surge price under incentive compatible assignment for drivers and optimal price rebates for demand response under power flow constraints. In Chapter 2, we study an on-line assortment optimization problem of substitutable products with fixed reusable capacities. At any time, a potential user with her preference model (possibly adversarially chosen) arrives to the selling platform and the platform offers a subset of products from the available set of products to the user. The user selects a product with probability given by her preference model, uses it for a random duration, which is distributed according to a distribution that only depends on the product selected, and generates revenue to the seller. The revenue contribution depends on the product selected and the actual usage time of this user. The goal of the seller is to find a policy for determining the assortment offered to each arrival to maximize the expected cumulative revenue over a time horizon. We find that a simple myopic policy offering the available assortment that maximizes the expected revenue from a single user at her arrival time provides a good approximation for the problem. In particular, we show that the myopic policy is 1/2-competitive, i.e., the expected cumulative revenue of the myopic policy is at least 1/2 times the expected cumulative revenue of an optimal clairvoyant policy that has full information about the adversarially chosen user sequence, including their preference models and arrival epochs. The proof is based on partitioning the expected revenue of optimal clairvoyant policy into two parts and a coupling argument that allows us to bound the two parts in terms of the expected revenue of the myopic policy. In Chapter 3, we study the surge pricing problem on a ride sharing platform when there is a demand shock to the traffic network. The goal of the platform is to maximize the revenue by setting the prices over the network and the assignments between drivers and riders. In particular, we model the city as a continuous two dimensional network with exogenous arrivals of baseline riders, available drivers and demand shocks. We consider the demand shock only exists in a short time scale, so the rider chooses to request the ride or not depending on their willingness to pay and the price quoted to them, and the driver accepts any price to provide service. Since drivers can see the price distribution on driver app, they only accept the assignment from the locations that are incentive compatible for them. Thus, the price change at one location may affect the operations over the network and the platform must consider the incentive of drivers when assigning them. We develop a model for this surge pricing problem and show the structural properties of an optimal solution. Once the prices at the location with demand shock is determined, we can determine the optimal prices on other part of the network. Then, the optimal assignments between riders and drivers can be determined analytically. The surge pricing problem reduces to one that only depends on the price at the location with demand shock. We then extend our model by including strategic behavior of riders, using throughput as objective, dealing with multiple demand shocks, un-constraining the price and considering movement time. We also conduct numerical experiments to study the properties of the model which can not be explored analytically. In Chapter 4, we study the demand response problem of computing price rebates to offer to the customers to reduce the consumption in the presence of power flow constraints and transmission losses on the distribution grid. In particular, we employ alternating current power flow model for the power flow constraints with transmission loss. However, the demand response problem with alternating current power flow constraints is known as a non-convex problem, which is in-tractable to solve. To overcome this, we apply a semi-definite relaxation of alternating current power flow model to obtain a convex approximation for the problem. At the same time, to handle the uncertainty in the power reduction of customers, we use sample average to approach the expected cost and linear injection approximation to estimate the impact of uncertainty in the power reduction. Based on these relaxations and approximations, we propose an efficient iterative heuristic to solve the near-optimal offer price under alternating current power flow constraints and transmission losses. We conduct a substantial amount of numerical tests on our heuristic and compare its performance with other popular models. (Abstract shortened by ProQuest.).

The Veins of the Earth: Property, Environment, and Cosmology in Nanbu County, 1865-1942

Brown, Tristan G Columbia University ProQuest Dissertations & These 2017 해외박사(DDOD)

소속기관이 구독 중이 아닌 경우 오후 4시부터 익일 오전 9시까지 원문보기가 가능합니다.

During the Qing Dynasty (1644-1912) in Nanbu County, land was not only measured in quantitative dimensions, but also assessed through cosmological principles. These understandings of land often framed property claims while shaping rural geographies in the county under study. Drawing on 700 cases from the Nanbu Archive, this dissertation makes two related claims. First, in the mountainous periphery of Northern Sichuan, situated knowledge of land pervaded contracts, genealogies, stone inscriptions, and official handbooks. This information, composed of vernacular place-names, localized land boundaries, expressions of patrimonial merit and status, and cosmological dimensions of property, was often immediately understandable only to the members of a lineage or community, but could be interpreted by the state if needed. One type of situated information was geomantic information, which regularly entered the magistrate's court. Local officials engaged this information in legal practice and took geomantic claims or documentation into consideration during litigation. Sites holding great geomantic significance, such as ancient trees, graves, and temples, were often identified by locals as the landmarks or borders of private estates, market towns, or the county itself; these understandings were regularly woven into the administrative documents of the state. During the Qing, such interpretations were even extended to a local shrine of a Muslim (Qadiri) saint. Through routine engagement with these interpretations of the earth throughout the increasing landed commercialization of the nineteenth and early twentieth centuries --- in processing lawsuits, the Nanbu yamen (state administrative office) ordered landscapes concerning geomancy to be officially illustrated more than any other genre of claim --- the Qing state legitimated highly situated knowledge of the land within the local property regime while upholding geomantic information as a binding mechanism for the regulation of common lands and resource access. The dissertation's second point is that, while it is well-known that the early decades of the twentieth century saw increased state penetration into local society across China, Nanbu maintained a remarkable degree of continuity with its imperial heritage. Land surveyors working in the early twentieth century struggled to extract structured knowledge of land from the layered territorialities of the county's terrains that had persisted from the Qing. This process was highly negotiated and often interpretive, rather than based on precise statistical surveying or the clear directives of a hegemonic state. Through exploring the legal, environmental, and religious dimensions of a single county's terrains in the late imperial period, this study identifies situated geomantic information as one of the key arenas for the projection of --- and limitations on --- state power in the county in relation to the property system. The dissertation also provides the first English-language history of Nanbu, a county with a remarkably complete administrative and legal archive from 1656 to 1951.

Toward a Robust and Universal Crowd Labeling Framework

Khattak, Faiza Khan Columbia University ProQuest Dissertations & These 2017 해외박사(DDOD)

소속기관이 구독 중이 아닌 경우 오후 4시부터 익일 오전 9시까지 원문보기가 가능합니다.

The advent of fast and economical computers with large electronic storage has led to a large volume of data, most of which is unlabeled. While computers provide expeditious, accurate and low-cost computation, they still lag behind in many tasks that require human intelligence such as labeling medical images, videos or text. Consequently, current research focuses on a combination of computer accuracy and human intelligence to complete labeling task. In most cases labeling needs to be done by domain experts, however, because of the variability in expertise, experience, and intelligence of human beings, experts can be scarce. As an alternative to using domain experts, help is sought from non-experts, also known as Crowd, to complete tasks that cannot be readily automated. Since crowd labelers are non-expert, multiple labels per instance are acquired for quality purposes. The final label is obtained by combining these multiple labels. It is very common that the ground truth, instance difficulty, and the labeler ability are unknown entities. Therefore, the aggregation task becomes a "chicken and egg" problem to start with. Despite the fact that much research using machine learning and statistical techniques has been conducted in this area, many questions remain unresolved, these include: (a) What are the best ways to evaluate labelers? (b) It is common to use expert-labeled instances (ground truth) to evaluate labeler ability. The question is, what should be the cardinality of the set of expert-labeled instances to have an accurate evaluation? (c) Which factors other than labeler expertise can affect the labeling accuracy? (d) Is there any optimal way to combine multiple labels to get the best labeling accuracy? (e) Should the labels provided by oppositional/malicious labelers be discarded and blocked? Or is there a way to use the "information" provided by oppositional/malicious labelers? (f) How can labelers and instances be evaluated if the ground truth is not known with certitude?. In the first part of this thesis, we propose a method called Expert Label Injected Crowd Estimation (ELICE) and extend it to different versions and variants. ELICE is based on a frequentist approach for estimating the underlying parameters. The first version of ELICE estimates the parameters using the accuracy of crowd labelers on expert-labeled instances. The multiple labels for each instance are combined using weighted majority voting. These weights are the scores of labeler reliability on any given instance, which are obtained by inputting the parameters in the logistic function. In the second version of ELICE, we introduce entropy as a way to estimate the uncertainty of labeling. This provides an advantage of differentiating between good, random and oppositional/malicious labelers. The aggregation of labels for ELICE version 2 flips the label provided by the oppositional/malicious labeler thus utilizing the information that is generally discarded by other labeling methodologies. Both versions of ELICE have a cluster-based variant in which rather than making a random choice of instances from the whole dataset, clusters of data are first formed using any clustering approach. Then an equal number of instances from each cluster are chosen randomly to get expert-labels. Besides taking advantage of expert-labeled instances, the third version of ELICE, incorporates pairwise/circular comparison of labelers to labelers and instances to instances. The idea here is to improve accuracy by using the crowd labels, which unlike expert-labels, are available for the whole dataset and may provide a more comprehensive view of the labeler ability and instance difficulty. This is especially helpful for the case when the domain experts do not agree on one label and ground truth is not known for certain. Therefore, incorporating more information beyond expert labels can provide better results. We test the performance of ELICE on simulated labels as well as real labels obtained from Amazon Mechanical Turk. Results show that ELICE is effective as compared to state-of-the-art methods. Next, we also present a theoretical framework to estimate the number of expert-labeled instances needed to achieve certain labeling accuracy. Experiments are presented to demonstrate the utility of the theoretical bound. In the second part of this thesis, we present Crowd Labeling Using Bayesian Statistics (CLUBS), a new approach for crowd labeling to estimate labeler and instance parameters along with label aggregation. Our approach is inspired by Item Response Theory (IRT). We introduce new parameters and refine the existing IRT parameters to fit the crowd labeling scenario. The main challenge is that unlike IRT, in the crowd labeling case, the ground truth is not known and has to be estimated based on the parameters. In the last part of the thesis, we present past and contemporary research related to crowd labeling. We conclude with future of crowd labeling and further research directions. (Abstract shortened by ProQuest.).

Experimental and Numerical Investigations into Fundamental Mechanisms Controlling Particle Transport in Saturated Porous Media

Liu, Po-Chieh Columbia University ProQuest Dissertations & These 2016 해외박사(DDOD)

소속기관이 구독 중이 아닌 경우 오후 4시부터 익일 오전 9시까지 원문보기가 가능합니다.

This dissertation presents the results of a series of experimental and numerical studies designed to advance knowledge of the fundamental mechanisms controlling colloidal particle transport in saturated porous media. That colloidal particles facilitate contaminant transport in porous media, or act as contaminant sources, is well known, and also widely recognized as important to environmental and health issues around the world. Many prior and ongoing studies are aimed at understanding particle transport and deposition behavior in saturated porous media, and these studies have generated a broad range of knowledge regarding particle fate and transport mechanisms. However, the prediction of particle transport behavior still remains challenging, not least because the particle transport processes themselves still include many unknown factors. The goal of the work reported in this dissertation, was to advance understanding of the influence of varying flow velocity conditions, flow direction, particle size and mixed particle populations on particle transport processes. In order to meet this goal, a new numerical model for particle transport was developed, and standard laboratory column test protocols were modified to enable the imposition of varying flow conditions during a test, as well as visualization of particle concentrations within the interior of a column. In addition, and in collaboration with other researchers, numerical modeling work was also undertaken to provide insight into the processes governing particle transport at an instrumented field site. (Abstract shortened by ProQuest.).

Three Essays on the Economics of Higher Education

Xia, Xing Columbia University ProQuest Dissertations & These 2016 해외박사(DDOD)

소속기관이 구독 중이 아닌 경우 오후 4시부터 익일 오전 9시까지 원문보기가 가능합니다.

As the primary transmitter of advanced skills and incubators of new knowledge, colleges and universities play a crucial role in modern economies. In the U.S., the higher education sector consists of a diverse set of institutions. Public, private non-profit, and private for- profit organizations coexist in this market. Although large research universities constitute what we usually think of as higher education institutions, the vast majority of colleges and universities do not follow the model of the research university. Some are two-year institutions with Associate's degrees as their highest degree offering. Some are Baccalaureate institutions offering undergraduate education only. Some are Master's universities who offer some graduate instruction but do not engage in research as much as research universities do. Unlike traditional firms that rely on sales revenue to cover their costs, many colleges and universities rely on external funding from the government and private donors. Like other non-profit institutions, many of them have large amounts of endowment funds that general investment income to support the institution. Given the diversity of organizations in this sector, how well do conventional economic theory describe their behavior? Do non-profit and for-profit institutions face the same incentives? How does the profit status affect the behavior of the university? What is the role of endowments in higher education finance? How does the performance of the endowment affect the real operations of the university? Are instructions at two-year and four-year colleges of similar quality? Is it wise for some students to start in two-year colleges and transfer to a four-year college rather than starting in a four-year college directly? These are the questions I attempt to answer in this dissertation. Chapter 1 investigates whether for-profit and public community colleges respond differently to increases in demand for occupational education. I exploit a regulatory change, which broadened the scope of practice for dental assistants (DAs) and led to significant in- creases in DAs' wages and employment. In response to this change, for-profit universities substantially expanded their DA programs, whereas most community college DA programs maintained their existing size. Moreover, community colleges that charged a high premium for the DA program expanded their DA programs, whereas those that did not charge a premium downsized their DA programs. These results are consistent with a for-profit sector that maximizes profits and a public sector that sets capacity to balance its budget. Chapter 2 studies how universities responded to the large and negative financial shocks to their endowments induced by the Great Recession. Exploiting variations across universities in the relative size of their investment losses during the Great Recession, I found sharp contrasts among Doctoral, Master's, and Baccalaureate Universities both in how they responded to the endowment shocks and in how their students fared after the Great Recession. In response to large, negative endowment shocks, Doctoral Universities cut down on instructional expenses and reduced faculty and staff of all types; Baccalaureate Colleges cut down on administrative and supportive expenses and reduced non-tenure-track instructors and staff; Master's Universities reduced research expenses and size of the tenure-track faculty. Meanwhile, Doctoral Universities cut student financial aid and admitted fewer low-income and Hispanic students. Master's and Baccalaureate institutions also admitted fewer low- income students. Most notably, the negative endowment shocks led to significant reductions in student persistence and graduation rates at Doctoral and Master's Universities, while having no such effects on Baccalaureate Colleges. As the tuition and living expenses of four-year colleges continue to rise, spending the first two years of college at a community college and transferring to a four-year college has become a more cost-effective way to obtain a university degree. In Chapter 3, a joint paper with Zach Brown, we examine the labor market outcomes of transfer students relative to students who attend a four-year institution directly in the United States. We find a large negative effect on wages driven by selection on unobservables. Instrumental variable estimates using data from the National Education Longitudinal Study imply a 27% reduction in wages from attending a two-year college conditional on eventually attending a four-year institution. This is true regardless of whether we control for four-year college quality. Since students who obtain a bachelor's degree have no reason to reveal their transfer status to employers, this is evidence that college quality has important implications for labor market returns independent of signaling effects. We also find some evidence that the negative effect of transferring is largest for women as well as students at the lowest and highest ends of the ability distribution.

Pattern Mining and Concept Discovery for Multimodal Content Analysis

Li, Hongzhi Columbia University ProQuest Dissertations & These 2016 해외박사(DDOD)

소속기관이 구독 중이 아닌 경우 오후 4시부터 익일 오전 9시까지 원문보기가 가능합니다.

With recent advances in computer vision, researchers have been able to demonstrate impressive performance at near-human-level capabilities in difficult tasks such as image recognition. For example, for images taken under typical conditions, computer vision systems now have the ability to recognize if a dog, cat, or car appears in an image. These advances are made possible by utilizing the massive volume of image datasets and label annotations, which include category labels and sometimes bounding boxes around the objects of interest within the image. However, one major limitation of the current solutions is that when users apply recognition models to new domains, users need to manually define the target classes and label the training data in order to prepare labeled annotations required for the process of training the recognition models. Manually identifying the target classes and constructing the concept ontology for a new domain are time-consuming tasks, as they require the users to be familiar with the content of the image collection, and the manual process of defining target classes is difficult to scale up to generate a large number of classes. In addition, there has been significant interest in developing knowledge bases to improve content analysis and information retrieval. Knowledge base is an object model (ontology) with classes, subclasses, attributes, instances, and relations among them. The knowledge base generation problem is to identify the (sub)classes and their structured relations for a given domain of interest. Similar to ontology construction, Knowledge base is usually generated by human experts manually, and it is usually a time-consuming and difficult task. Thus, it is important and necessary to find a way to explore the semantic concepts and their structural relations that are important for a target data collection or domain of interest, so that we can construct an ontology or knowledge base for visual data or multimodal content automatically or semi-automatically. Visual patterns are the discriminative and representative image content found in objects or local image regions seen in an image collection. Visual patterns can also be used to summarize the major visual concepts in an image collection. Therefore, automatic discovery of visual patterns can help users understand the content and structure of a data collection and in turn help users construct the ontology and knowledge base mentioned earlier. In this dissertation, we aim to answer the following question: given a new target domain and associated data corpora, how do we rapidly discover nameable content patterns that are semantically coherent, visually consistent, and can be automatically named with semantic concepts related to the events of interest in the target domains? We will develop pattern discovery methods that focus on visual content as well as multimodal data including text and visual. (Abstract shortened by ProQuest.).

Examining Vaping’s Possible Unintended Consequences on Cannabis Initiation and the Initiation of Other Substances

Perlmutter, Alexander S Columbia University ProQuest Dissertations & These 2023 해외박사(DDOD)

소속기관이 구독 중이 아닌 경우 오후 4시부터 익일 오전 9시까지 원문보기가 가능합니다.

Electronic nicotine delivery systems emerged during the 2010s as a novel way to consume (i.e., vape) nicotine. Public health authorities became concerned that vaping could cause nicotine-naive youth to begin using tobacco products and that a new generation of youth could become tobacco-dependent. Though millions of youth have vaped, authorities’ fears about a new generation of youth tobacco dependence has not materialized. A more recent concern is nicotine vaping’s potential effects on cannabis use and the use of other substances. An increase in cannabis use among some adolescent groups and young adults could be because of nicotine vaping’s rise. Additionally, cannabis can be vaped, so transitioning from nicotine vaping to cannabis vaping may be easier than transitioning from nicotine vaping to other forms of cannabis use. Furthermore, nicotine product use was historically associated with later use of cannabis and other substances; this trend may be renewed with the advent of nicotine vaping. To date, most studies on the associations between nicotine vaping and cannabis/other substance use are cross-sectional, so more longitudinal evidence is needed. If evidence suggests that nicotine vaping does affect the use of cannabis and other substances, specifying a mechanism would help with developing potential interventions and with testing the validity of total effects. The overarching goal of this dissertation is to advance evidence of nicotine vaping’s potential harmful effects on youth and young adults, which could be used to support interventions aimed at reducing the burden of nicotine vaping’s outcomes. First, I conducted a systematic review in which I examined the extent to which confounding, measurement errors, and loss to follow-up could alternatively explain reported longitudinal effects of nicotine vaping on cannabis use or other substance use. I also identified studies that tested effect modification and mediation. This systematic review revealed that nicotine vaping likely increases the risk of subsequent cannabis use and other substance use for up to 24 months. It also revealed that some studies evaluated effect measure modification, while no study assessed mechanisms. These observations suggest that future studies should assess long-term effects on initiation and evaluate potential mechanisms. Second, I evaluated whether nicotine vaping affected the initiation of cannabis and other substances over a six-year period among adolescents as they age into adulthood. Results suggested that nicotine vaping had harmful effects on both outcomes over the six-year period. I also found evidence that nicotine vaping’s harmful effects in later years appeared stronger than in earlier years; the absence of age effects suggest the absence of cohort effects. Furthermore, I found that effects appeared stronger among individuals who had a history of non-vaping tobacco product use than among individuals without a history of non-vaping tobacco product use, suggesting that tobacco use is key to nicotine vaping’s harms Finally, I evaluated possible mechanisms of the effects based on a theory that I developed from prior empirical literature and behavioral theory. I posited that nicotine vaping caused deviant peer affiliation, which caused conduct problems and subsequently, the outcomes. I found no evidence that three conduct problems (considered together) were mechanisms of the effects. Future studies of mechanisms can reveal potential intervention targets, lead to studies of other potential mechanisms, and help test the validity of total effects. This dissertation achieved its goal of advancing evidence that nicotine vaping may harm youth and young adults. Public health bodies tasked with addressing potential public health concerns about nicotine vaping products should consider evidence from this dissertation.

Elements of Innovators' Fame: Social Structure, Identity and Creativity

Banerjee, Mitali Columbia University ProQuest Dissertations & These 2017 해외박사(DDOD)

소속기관이 구독 중이 아닌 경우 오후 4시부터 익일 오전 9시까지 원문보기가 가능합니다.

What makes an innovator famous? This is the principal question of this dissertation. I examine three potential drivers of the innovators' fame -- their social structure, creativity and identity. My empirical context is the early 20th century abstract artists in 1910-25. The period represents a paradigmatic shift in the history of modern art, the emergence of the abstract art movement. In chapter 2, I operationalize social structure by an innovator's local peer network. I find that an innovator with structurally and compositionally diverse local network is likely to be more famous than the one with a homogenous local network. I find no statistical evidence for creativity as a link between social structure and fame. Instead, the evidence suggests that an innovator's creative identity and access to promotional opportunities are the key drivers of her fame. In Chapter 3, I find that the creativity identity resulting from an innovator's creative trajectory can lead to obscurity despite early fame and acclaim. The drastic change in the nature of a producer's output can dilute her identity and cost her niche. In combination with her peer network characteristics, these dynamics can mean obscurity even for talented and prolific innovators. In chapter 4, I undertake a large-scale analysis of the relationship between creativity and fame. Using a novel computational measure for the novelty of the artists' works, I explore how their creativity and fame evolve over 1905-2000 in five markets. I find no statistical evidence for a positive relationship between creativity and fame; in fact, the statistical evidence is in favor of a negative relationship between creativity and fame through several time periods. The results suggest that creativity (measured by expert or machines) is not a driver of fame. In effect, it further supports the conclusions of chapter 2 and 3.