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Big Data For Microorganisms: Computational Approaches Leveraging Large-Scale Microbial Transcriptomic Compendia
Get PDFGenome-wide transcriptomics data captures the molecular state of microorganisms – the expression patterns of genes in response to some condition or stimuli. With advancements in high-throughput sequencing technologies, there are thousands of microbial transcription profiles publicly available. Consequently, this data has been collected and integrated to form transcriptomic compendia, which are collections of diverse gene expression experiments. These compendia were found to be a valuable resource for studying systems level biology and hypothesis generation. We describe the construction, benefits and challenges in creating microbial transcriptomic compendia in Chapter 1. One challenge for compendia, which integrates across many different experiments, is batch effects, which are technical sources of variability that can disrupt the detection of underlying biological signals of interest. In Chapter 2, we use a generative neural network to simulate gene expression compendia with varying amounts of technical variability and assess the ability to detect the underlying biological structure in the data after noise was added and then after batch correction was applied. We define a set of principles for how batch correction should be used in the context of these large-scale compendia. In Chapter 3 and 4 we introduce computational approaches to use compendia to improve the analysis of individual experiments and analysis of genomic patterns respectively. In Chapter 3, we develop a portable framework to distinguish between common and context specific transcriptional signals using a compendium to autogenerate a null set of expression changes. This approach allows researchers to put gene expression changes from their individual experiment of interest into the context of existing compendia of experiments. In Chapter 4 we develop an approach to examine the effect of different Pseudomonas aeruginosa genomes, using two dominant strain types, on transcriptional profiles in order to understand how traits manifest. This genome-wide approach reveals a more complete picture of how different genomes affect expression, which mediates different traits present. Overall, these compendia provide a valuable resource that computational tools can leverage to extract patterns and inform research directions
Study Of Nash Equilibria In Blockchain Voting Systems
Get PDFIn the first part of this thesis we analyze the three most common blockchain committeesselection strategies: lottery, single-vote and approval voting, where voters can “approve” of any number of candidates. We first show that all these mechanisms converge to optimality exponentially quickly as the size of the committee grows. Approval-voting requires that even honest voters act strategically, we characterize different approval voting strategies and we show that although finding the optimal approval voting strategy is extremely complex, almost any approval voting strategy outperforms the single-vote mechanism enforced on the majority of blockchains. In the second part, we investigate a blockchain governance model where a group of n voters must choose between two collective alternatives. As opposed to the usual voting system (one person – one vote), we propose a voting system where each agent buys votes in favor of their preferred alternative, paying the m-th root of the number of votes purchased. Its novelty relies on allowing voters to express the intensity of their preferences in a simple manner. We provide a rigorous comparison of the utilitarian welfare between Regular Voting (m = 1) and Quadratic Voting (m = 2). We present closed form equilibrium solutions to the 2 voters and 3 voters games. In addition to characterizing the nature of equilibria, one of our main result demonstrates that the normalized utilitarian welfare of the mechanisms tends to one as the population size becomes large
Functional Brain Network Development: Shifting Boundaries & Environmental Influences
No full textIn this work, we take a network science approach to studying large-scale intrinsic brain networks during three important periods of development. In the first study, we employ sophisticated acquisition and analysis tools to investigate functional network development in children between the ages of 4 and 10 (n = 92). We demonstrate that age is positively associated with network segregation at multiple spatial scales, and that associations between age and functional connectivity are most pronounced in visual and medial prefrontal cortex, at two ends of a gradient from perceptual, externally-oriented cortex to abstract, internally-oriented cortex. In the second study, we uncover the community structure of cortex in children aged 9 to 11 years (n = 670). We show that children have similar community structure to adults in early-developing sensory and motor communities, but differences emerge in association areas. Children have more cortical territory in the limbic community, which is involved in emotion processing, than adults. Regions in association cortex interact more flexibly across communities, perhaps reflecting cortical boundaries that are not yet solidified, and uncertainty is highest for cingulo-opercular areas involved in flexible deployment of cognitive control. In the third study, we map the associations between neighborhood SES and functional brain networks in a sample of children between the ages of 8 and 22 years (n = 1012). We characterize network topology using a local measure of network segregation known as the clustering coefficient and find that it accounts for a greater degree of SES-associated variance than mesoscale segregation captured by modularity. High- SES youth show stronger positive associations between age and segregation than low-SES youth, and this effect was most pronounced for regions in the limbic, somatomotor, and ventral attention systems. Collectively, our results provide new insights into how changes in cortical organization give rise to changes in the mind as children grow up, and how variation in the neighborhood environment might in turn affect brain development
No Such Thing as a Free Lunch? A Three Part Analysis of Free School Meal Programs Under the Community Eligibility Provision
No full textTraditional federal school meals help mitigate food insecurity among students (Hinrichs, 2010) but do not fully eliminate it. The Community Eligibility Provision (CEP) is a federal attempt to expand access to school meals in areas of targeted need. Schools that opt into CEP offer meals at no cost to all students regardless of individual need, thus replacing free and reduced-price meal applications. However, by virtue of the funding design, schools with lower levels of documented poverty are financially disincentivized from participating in CEP and despite promising benefits, many of these schools do not take up the program. Importantly, even though these schools demonstrate “lower” need, their needs may still be persistent and severe as qualification standards may under-diagnose poverty, especially in specific communities. I conduct a three-part analysis of CEP. Part one is a systematic review of existing CEP literature. CEP has shown promise in initial research to benefit students with positive outcomes on student participation in meal programs, improved nutrition quality, improved test scores, and improved attendance and taken cumulatively, indicate a reduction in anti-poverty stigma. In part two, I conduct a novel analysis of schools that opt into CEP before subsequently opting out. I find that students miss more school when CEP is taken away, an effect driven largely by students who are economically disadvantaged. In part three, I analyze the economic implications of policy proposals that expand or contract CEP. Results indicate that CEP could be expanded to provide access to nearly 20 million more students with a net federal school meal expenditure change of between 11-15.3%. Taken together, CEP is a program that benefits economically disadvantaged students in spite of a sliding scale finance schedule that disadvantages schools. Policy changes that would improve this sliding scale feature are reasonably feasible and would impact millions of economically disadvantaged students. These analyses are timely, given recent interest in the expansion of CEP and have the potential to contribute to important conversations on the future of federal school meal policy
Safe Programming over Distributed Streams
No full textThe sheer scale of today\u27s data processing needs has led to a new paradigm of software systems centered around requirements for high-throughput, distributed, low-latency computation.Despite their widespread adoption, existing solutions have yet to provide a programming model with safe semantics -- and they disagree on basic design choices, in particular with their approach to parallelism. As a result, naive programmers are easily led to introduce correctness and performance bugs. This work proposes a reliable programming model for modern distributed stream processing, founded in a type system for partially ordered data streams. On top of the core type system, we propose language abstractions for working with streams -- mechanisms to build stream operators with (1) type-safe compositionality, (2) deterministic distribution, (3) run-time testing, and (4) static performance bounds. Our thesis is that viewing streams as partially ordered conveniently exposes parallelism without compromising safety or determinism. The ideas contained in this work are implemented in a series of open source software projects, including the Flumina, DiffStream, and Data Transducers libraries
Hyperscale Data Processing with Network-Centric Designs
No full textToday’s largest data processing workloads are hosted in cloud data centers. Due to unprecedented data growth and the end of Moore’s Law, these workloads have ballooned to the hyperscale level, encompassing billions to trillions of data items and hundreds to thousands of machines per query. Enabling and expanding with these workloads are highly scalable data center networks that connect up to hundreds of thousands of networked servers. These massive scales fundamentally challenge the designs of both data processing systems and data center networks, and the classic layered designs are no longer sustainable. Rather than optimize these massive layers in silos, we build systems across them with principled network-centric designs. In current networks, we redesign data processing systems with network-awareness to minimize the cost of moving data in the network. In future networks, we propose new interfaces and services that the cloud infrastructure offers to applications and codesign data processing systems to achieve optimal query processing performance. To transform the network to future designs, we facilitate network innovation at scale. This dissertation presents a line of systems work that covers all three directions. It first discusses GraphRex, a network-aware system that combines classic database and systems techniques to push the performance of massive graph queries in current data centers. It then introduces data processing in disaggregated data centers, a promising new cloud proposal. It details TELEPORT, a compute pushdown feature that eliminates data processing performance bottlenecks in disaggregated data centers, and Redy, which provides high-performance caches using remote disaggregated memory. Finally, it presents MimicNet, a fine-grained simulation framework that evaluates network proposals at datacenter scale with machine learning approximation. These systems demonstrate that our ideas in network-centric designs achieve orders of magnitude higher efficiency compared to the state of the art at hyperscale
Bringing Down the House: Gambling, Speculation and the Making of the Small Investor in Colonial India, 1867-1943
No full textMy dissertation uses the history of gambling and speculation to narrate the growth of commodity exchanges and markets that emerged in colonial India during the early twentieth century and the clientele they attracted. My project intervenes in a number of major existing debates in the histories of law and governmentality, finance and political economy and ‘vernacular’ knowledge and networks of circulation in South Asia. Existing works in these fields have tended to depict state engagements with practices such as ‘commodity speculation’ and ‘gambling’ within a framework of ‘colonial governmentality’, ‘market rationality’ and the ‘legal standardization’ of market behavior. By closely following the anti-gaming laws of the late nineteenth and early twentieth centuries, this dissertation moves beyond the regulative ideals of colonial policing and interrogates the actual operations of colonial laws, their anxieties and the inconsistent categories they generated. In the process, I historicize the shifting definitions regarding native gambling, which passed through multiple regimes of legal classifications during this period. I show how the practice of gambling, which earlier corresponded to precise legal definitions became undefined when commercial actors and native business communities became its major practitioners. Additionally, the project reveals the impact of extra-legal, normative discourses that transformed the once criminalized ‘petty gambler’ into the ‘useful’ ‘small investor’. While the histories of twentieth century Indian capitalism have focused largely on the contributions of large business houses and post-colonial state planning, my dissertation accounts for the tactics that helped liberate petty capital away from ‘savings’ and redirected them towards risky speculation. I do so by showing how the prognostic literature of astro-meteorological weather manuals that predicted the chances of rainfall, reoriented themselves to predict the future prices of commodities like cotton, jute and grain. In doing so, they were able to turn a section of working class gamblers off the ‘rain betting’ houses of Calcutta, Delhi and Bombay and onto options and derivative markets in commodities
Penn Library\u27s LJS 416 - [Regulations for mills and bakeries]. (Video Orientation)
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Organizations as Agents for Well-Being: How an Organizational Orientation to “Do Good” Could Lead to Flourishing
Get PDFIt has been proposed that flourishing individuals enable flourishing organizations which leads to a flourishing world. However, is it also possible that by focusing on building a flourishing world a reciprocal elevation of organizational flourishing and individual flourishing can occur? This paper discusses well-being, the progression of research regarding organizational orientation to do good, and mirror flourishing. The amplification effect of virtuousness, along with the heliotropic effect, provide support to the theorized concept of mirror flourishing. In addition, this paper proposes a study design using appreciative inquiry to conduct interviews to better understand how an organization’s orientation to do good impacts employee flourishing
Kinegami: Algorithmic Design of Compliant Kinematic Chains From Tubular Origami
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