VictorJuiz/thesis huggingface dataset:
At home in the margins [electronic resource] : Vasily Rozanov, autobiography and alterity

In analyzing the works of Vasily Rozanov (1856-1919), this dissertation departs from the critical tendency to separate Rozanov's journalistic and philosophical works from his more famous autobiographical "trilogy": "Solitaria" (1911), "Fallen Leaves, Basketful I" (1913), and "Fallen Leaves, Basketful II" (1915). Addressing Rozanov's early writings, such as "In the Land of the Unclear and Undecided" (1901) and "The Family Question in Russia" (1903), as well as his problematic texts, such as "The Tactile and Olfactory Relation of Jews to Blood" (1914), in concert with his "Fallen Leaves" trilogy, the author points out the constancy, if not always in Rozanov's ideas, then in his performative self-presentation, which focused on the I's alterability and the autobiographer's interaction with figures of alterity. According to this reading, Rozanov emerges as part of a number of important 20th century trends that emphasize literary performance, the intersection of the body and the text, and the interaction of self and other. Rozanov's philosophical interest in physical intimacy and the body and his theoretical concern with the textual interrelations of self and other shape this dissertation's organization: Chapter 1 focuses on autobiography and the body and Chapter 2 considers the autobiographer's interactions with others' texts. Each section also counterposes Rozanov with other writers, such as his idol, Fyodor Dostoevsky, and literary theorists, such as Viktor Shklovsky, Mikhail Bakhtin, and Jacques Derrida. In this author's view, Rozanov not only influences Bakhtin, whose concept of the grotesque, carnival body is shockingly Rozanovian, but many aspects of his texts also emerge as a parallel to the writings of performative theorists like Derrida.

Keywords: Slavic Languages and Literatures.
Advisor: Greenleaf Monika
Freidin Gregory advisor. Thesis advisor
Safran Gabriella
Atomistic simulations of interfacial defect structures of nanoscale solid oxide electrolytes [electronic resource]

A Hybrid Monte Carlo - Molecular Dynamics algorithm was developed to sample the equilibrium distributions of point defects near the (100) surface and two types of pure tilt grain boundaries ([sigma]5(310)/[001] and [sigma]13(510)/[001]) in nanoscale yttria-stabilized zirconia and gadolinia-doped ceria. The simulations predict the first large-scale equilibrium distributions of dopant cations and oxygen vacancies near the three types of interfaces where both kinds display considerable amounts of segregation. The results are compared with various experimental observations, which are qualitatively consistent with the theoretical predictions. The simulation results offer new findings that were not accessible by experiments such as elemental distributions on the atomic scale, the effects of pressure and doping level on dopant segregation, and the effect of defect segregation on the ionic diffusivity. The simulations also reveal the strong dependence of defect segregation on the microscopic structure of the interface. Dopant segregation is triggered by the high concentration of oxygen vacancies at the interface due to lower formation energies and elastic strain due to size misfit between host and dopant cations, but the final distribution profiles are largely determined by the interactions between point defects. The newly proposed segregation mechanism sheds light on the understanding of equilibrium defect structures in these ionic oxides.

Keywords: Mechanical Engineering.
Advisor: Cai Wei
Prinz F. B. primary advisor. Thesis advisor
Reed Evan J. primary advisor. Thesis advisor
Attitude and rate estimation for remote tumbling targets using line scan range measurements [electronic resource]

The work in this thesis enables the estimation of orientation and angular rates for tumbling targets using scanning range measurements. This general estimation problem is a vital part of enabling autonomous rendezvous for spacecraft. The primary focus of this work was to consider cases where data smearing is a problem. Data smearing occurs when scanning range measurements are taken from a continuously moving target. If the raw data are aggregated into a point cloud without motion correction, they no longer represent the target geometry accurately. The estimation framework presented considers individual, sequential measurements as opposed to aggregating range data into point clouds. This paradigm shift addresses the problem of data smearing in a general and robust way by applying a recursive estimation framework that inherently accounts for noise in the motion correction. This algorithm relies on knowledge of the target's shape, e.g. a CAD model, and general equations of motion. The estimator is fed solely by measurements from the ranging sensor. The estimation process is decomposed into an acquisition phase and a tracking phase, and filters are constructed for each. Specifically, a particle filter is developed for use in the acquisition phase and an extended Kalman filter is utilized for the tracking phase. The design and implementation of an experimental platform are also discussed. This platform can rotate a model through an arbitrary, specified trajectory while maintaining unoccluded visibility of the target for observation by external sensors. Details of the hardware, software, sensing, and closed loop control architecture are included. Both simulation and experimental results are presented which verify the successful performance of the proposed algorithms in the presence of realistic sensor noise and modeling uncertainty. The hardware experiments employ a continuously rotating target, which results in data smearing, and consider a limiting case where the sensor has only a line scan pattern.

Keywords: Aeronautics and Astronautics
Advisor: Rock Stephen M. primary advisor. Thesis advisor
Close Sigrid
Enge Per advisor. Thesis advisor
Augmented self-regulation [electronic resource]

Research in interactive technology most often enables humans to enact more, better, or new behaviors or to gain greater or more efficient insight into our environment. This dissertation develops the notion that technology can also help us develop greater self-awareness. Self-awareness, made tangible and observable by physiological self- regulatory processes, rests at the core of the human experience by supporting comprehension, actions, and intentions in the world around us. Without it, our health and behavior are victims of demands from our sociocultural environments or of flippant or self-defeating patterns of thoughts. This dissertation explores and evaluates methods of using wearable sensors and interactive feedback to augment human self-regulation, specifically respiratory self- regulation, primarily during information work but also in mobile contexts. This is a potentially powerful means of not only influencing health and behavior but also developing an inner sense of wellness independent of one's physiological, cognitive, or affective state. The over-arching contribution of this dissertation is to demonstrate the view that computers will have a more direct and pervasive impact on human psychophysiology than is currently practiced. Rather than strictly adapting to human physiological and affective state, future machines will explicitly induce changes in psychophysiological state to amplify their user's innate self-regulatory ability and skill. In this way, machines of the future will help humans be 'more human' rather than simply adding or enhancing existing human abilities.

Keywords: Education.
Advisor: Obradović Jelena (Education professor) primary advisor. Thesis advisor
Pea Roy D. primary advisor. Thesis advisor
Heer Jeffrey Michael advisor. Thesis advisor
Autism mutations in ProSAP2/Shank3 disrupt zinc-dependent dynamics and transsynaptic signaling [electronic resource]

Autism spectrum disorders (ASDs) are a pervasive set of neurodevelopmental disorders that are characterized by deficits in social interaction and communication. ASDs are diagnosed in 1 out of 88 children and are more common in males. ASDs are thought to be highly heritable and a wide variety of genetic mutations have been identified, including mutations in several synaptic proteins. This dissertation research explores convergent synaptic mechanisms underlying ASDs, specifically exploring several aspects of synaptic biology that are disrupted by autism-associated mutations in the ProSAP/Shank family of postsynaptic scaffolding proteins, focusing primarily on one family member, ProSAP2/Shank3, for which the genetic data is strongest. Data collected for this thesis demonstrate that ProSAP/Shank proteins act within dendritic spines to coordinate pre- and postsynaptic changes in synaptic function by regulating the activation of Neurexin-Neuroligin signaling complexes. Intriguingly, autism mutations in ProSAP2/Shank3 were found to disrupt this transsynaptic signaling, thereby functionally linking several synaptic proteins implicated in ASDs. Mechanistic experiments revealed that ProSAP2/Shank3 activation and scaffold stability within postsynaptic densities (PSDs) are zinc-sensitive and that zinc supplementation can reactivate ProSAP2/Shank3 carrying an ASD mutations, partially or fully rescuing transsynaptic signaling. Importantly, zinc deficiencies are linked to mental retardation and thus may be a risk factor for autism by contributing to synaptic dysfunction within neuronal networks.

Keywords: Neurosciences.
Advisor: Garner Craig primary advisor. Thesis advisor
Clandinin Thomas R. (Thomas Robert)
Hallmayer Joachim advisor. Thesis advisor
Reimer Richard J. advisor. Thesis advisor
Shatz Carla J. advisor. Thesis advisor
Automated look-ahead schedule generation and optimization for the finishing phase of complex construction projects [electronic resource]

In the project this dissertation describes, I have developed an integrated approach to quickly generate accurate and close-to-optimum LASs in the finishing phase of complex construction projects. In the finishing phase of such projects, project planners, site engineers, and construction engineers struggle to use look-ahead schedules (LASs) to effectively organize and allocate limited project resources such as crews and spaces on a daily basis for three main reasons. First, the LASs created are error-prone because site engineers and project planners need to consider constraints including precedence constraints, spatial and crew availabilities, and engineering constraints, such as zone and blocking constraints; second, the LAS generation process is time-consuming, even with the help of the existing commercial tools; and third, there is no way to tell whether the LASs created are the best means by which to achieve specific project goals, such as shortest construction duration and lowest construction cost. The approach I have developed builds on two theoretical foundations: automated schedule generation and project schedule optimization. This approach consists of an automated LAS generation (ALASG) method and an optimization method based on a genetic algorithm (GA). The ALASG method can quickly generate one accurate LAS. The ALASG method is composed of an information model that integrates the project data sources at the appropriate level of detail to facilitate the formation of operations and the accommodation of constraints, and an LAS generation process model that sequences operations without violating any constraints. The GA-based optimization method interacts with the ALASG method to quickly discover nearly optimum LASs. I have also developed a prototype based on this approach. The results from the use of this prototype in student and engineer design charrettes and from comparison studies provide evidence for the power of this approach in rapidly generating accurate and close-to-optimum LASs. Because of this unique capability, I claim the ALASG method as a contribution to the field of automated schedule generation and the GA-based method as a contribution to the field of project schedule optimization. This research lays the foundation for tools that can guide project planners, site engineers, and construction managers to effectively and efficiently conduct work assignments by (1) eliminating work conflict and rework, (2) always looking towards optimum project goals, and (3) quickly adjusting project actions according to the most up-to-date project status.

Advisor: Fischer Martin
Ge Dongdong advisor. Thesis advisor
Levitt Raymond E. advisor. Thesis advisor
Automatic hole-cutting in overset grids using the X-rays approach [electronic resource]

Overset grids resolve complicated geometries by creating high quality structured grids that are independently built for each component. This simplifies the process of grid generation, but domain connectivity must be performed so that adjacent grids share information. Currently available domain connectivity tools tend to be computationally expensive or require extensive user input. The X-rays approach is a robust and computationally efficient method, but it requires considerable user input and iteration. Shortcomings of the current X-rays method are explored to automate and improve the algorithm. Significant user time is saved by identifying and eliminating the manual bottlenecks of the X-rays approach. In addition, automation of the hole boundary adjustment helps to improve the accuracy of the solution. It is now possible to solve relative motion problems with significantly less user inputs, considerably reducing the design cycle time in engineering CFD analysis.

Keywords: Mechanical Engineering
Advisor: Leifer Larry J. primary advisor. Thesis advisor
Alonso Juan José
Beach David W.
Chan William
Steinert Ralf
Bayesian analysis for reversible time series with applications to molecular dynamics simulation [electronic resource]

A host of sequential models in probability and statistics are characterized by time reversibility, from Markov chain Monte Carlo samplers to queueing networks. In physics, this property arises naturally from Hamiltonian mechanics. Molecular dynamics simulations are computer experiments which approximate classical mechanics in a system of interacting particles; in consequence, they are frequently reversible. Recent technical progress has made it possible to investigate the dynamics of biological macromolecules in silico using molecular dynamics simulations. An active area of research within this field is concerned with modeling the output of a simulation stochastically. This dissertation deals with the problem of incorporating knowledge of reversibility into the estimation and testing of stochastic models. We define a range of Bayesian inference algorithms, which are motivated by specific problems in the analysis of molecular dynamics simulations.

Keywords: Structural Biology.
Advisor: Pande Vijay primary advisor. Thesis advisor
Andersen Hans
Diaconis Persi advisor. Thesis advisor
Bayesian assembly of reads from high throughput sequencing [electronic resource]

The high-throughput sequencing revolution allows us to take millions of noisy short reads from the DNA in a sample, essentially taking a snapshot of the genomic material in the sample. To recover the true genomes, these reads are assembled by algorithms exploiting their high coverage and overlap. I focus on two scenarios for sequence assembly. The first is de novo assembly, where the reads come from an unknown and diverse population of genomes. The second is variant assembly, where the reads come from short but clonally related genomes, only slightly mutated from each other. In both cases I use the same principled Bayesian approach to design an algorithm that uncovers the composition of the genomic sequences that produced the reads. I will demonstrate the algorithms' performance on real data taken from various metagenomic environments, as well as the immune system B cells. On that latter dataset, collected from 10 organ donors each providing 4 tissue samples, the results show evidence of clone migration between tissues and provide new insights on the organization of the immune system.

Advisor: Koller Daphne primary advisor. Thesis advisor
Batzoglou Serafim advisor. Thesis advisor
Fire Andrew Zachary advisor. Thesis advisor
Behavior modeling in smart environments using camera networks [electronic resource]

The goal of smart environments is to support people in their daily life by being sensitive and responsive to their presence and activities. The key challenges in achieving such a vision are the ability to robustly extract useful information from the sensors, and to utilize the extracted data to generate and reinforce a model representing the user's pattern of behavior so adaptive, personalized or even predictive responses can be provided. In the first part of the dissertation, we discuss how information about people in an environment can be obtained using a network of cameras. We propose efficient visual processing algorithms to track multiple people in real-time, to determine their pose and to estimate their head orientation. A discriminative classifier is trained to detect interactions between occupants of a space based on their locations and head orientations. We also describe methods to fuse information at different levels in a multi-camera scenario. In the second part of the dissertation, we discuss how behavior models can be constructed from observations obtained by cameras or other sensors. We propose a probabilistic model that takes into account the inherent hierarchical structure of human activities, as well as contextual information related to the user or the environment. Our model also allows for variations in the duration of different activities, and considers the uncertainty of the measurements reported by the sensors. To evaluate our visual processing algorithms and illustrate the benefits of our proposed behavior modeling approach, we study three use cases. In the first use case, we study the daily routine of an office worker, and derive the user's pattern of work. In the second use case, our proposed method is applied to a smart home to adaptively optimize energy consumption and user comfort by learning user preferences and habits. Finally, we consider a scenario where the built-in webcam on a personal computer is used to analyze the user's posture and gaze while working on the computer. Personalized ergonomic recommendations tailored to the user's behavior pattern are then provided. Experimental results are presented in each of the use cases to demonstrate the performance of our proposed methods.

Keywords: Electrical Engineering
Advisor: Meng Teresa H. primary advisor. Thesis advisor
Aghajan Hamid K.
El Gamal Abbas A. advisor. Thesis advisor
Behind a veil of smoke [electronic resource] : big tobacco and the hidden world of research and development at Philip Morris, 1950-1985

In 1952, the largest manufacturer of cigarettes, Philip Morris, founded a Department of Research and Development (R& D) that would ultimately elevate the company to its dominating role in the tobacco landscape. As revealed through internal industry documents available online and released through litigation, this study highlights both the role of scientific research in a controversial industry, and the role of individual researchers in the unbridled growth of Big Tobacco during the second half of the twentieth century. Despite extensive research, industry results were rarely published and never without extensive scrutiny by industry executives and lawyers. This scientific silence is in stark contrast to the industry's public stance of denying the health hazards of smoking. The extent to which the tobacco men understood the hazards of their products—and the specific details of several research projects on the dangers of smoking—are discussed. The history of the Department of Research at Philip Morris demonstrates that just as public concern was growing that smoking might be dangerous, the tobacco industry was actively pursuing research proving the very thing they were trying to convince the public was a non-issue: that smoking is harmful.

Keywords: History
Advisor: Proctor Robert
Campbell James T.
Kennedy David M.
Biochemical, electrical, and optogenetic control of human pluripotent stem cell-derived cardiomyocytes [electronic resource]

Cardiovascular disease affects more than 70 million Americans and is the number one cause of mortality in the United States. Because the regenerative capacity of cardiac tissue is limited, human pluripotent stem cells (hPSC) have emerged as a potential source for cellular-based therapies. However, for these therapies to be effective, sufficient amounts of differentiated cells must be produced, these cells must be identified and sorted, and, upon implantation, arrhythmias must be avoided. In this dissertation, I describe the biochemical control of hPSC for their directed differentiation into cardiomyocytes, electrical control for electrophysiology-based cell sorting, and optogenetic control for temporal synchronization. For future therapy, the in vivo application of optical stimulation could allow immediate, precise, and specific synchronization of efficiently derived and purified hPSC-CM with patient cardiac rates and rhythms. This, in turn, would significantly reduce the chance of arrhythmias arising from implanted hPSC-CM, and, therefore, contribute towards establishing a safe and effective cell-based therapy.

Keywords: Bioengineering.
Advisor: Zarins Christopher K. primary advisor. Thesis advisor
Quake Stephen Ronald advisor. Thesis advisor
Wu Joseph Ching-Ming
Yock Paul G. advisor. Thesis advisor
Biofilm formation and its interaction with surfactants and solvents [electronic resource] : a physico-biological approach

Bacteria tend to aggregate on surfaces and form biofilms that are characterized by an extracellular polymeric matrix consisting of proteins and polysaccharides. The unique structure of biofilms prevents bacteria from harsh environmental conditions so they can survive in a broad range of conditions. While this ability is beneficial to the bacteria's survival, biofilms are implicated in most infectious diseases such as catheter infections, cystic fibrosis, endocarditis, and urinary tract infections. Successful treatments of these diseases require thorough understanding of the biochemical and physico-chemical properties of biofilms that relate to function. In this thesis, we combined conventional biofilm research methods with interfacial science techniques including interfacial rheometry and tensiometry to study air-liquid interface biofilm (pellicle) formation by uropathogenic E. coli, which produces an amyloid-fiber called "curli" to develop a biofilm network. We analyzed the bacteria cell growth, adhesion ability, and curli expression, and relate them to the interfacial viscoelasticity during biofilm formation. Our results showed that over-expressed curli content leads to more robust biofilms with higher tenacity. Nonionic surfactant-biofilm interaction was also studied, and the results showed that biofilm formation was very sensitive to surfactant concentration. Below the critical micelle concentration (CMC), the surface was dominated by bacteria-degradable proteins from the nutrient broth, and pellicle formation was observed with delayed inception at increasing surfactant concentration. Above the CMC, the surface was dominated by surfactants, and biofilm formation was inhibited. Our studies demonstrated a unique approach to comprehensively examine air-liquid interface biofilm formation and investigated the influence of curli content and surfactants on amyloid-integrated biofilm formation. The application of this approach is extensible to studies of amyloid-integrated biofilm formation among other microorganisms as well as interactions of surfactant-protein and surfactant-polymer at air-liquid and oil-liquid interfaces.

Keywords: Chemical Engineering
Advisor: Fuller Gerald G.
Cegelski Lynette advisor. Thesis advisor
Dunn Alexander Robert advisor. Thesis advisor
Swartz James R. advisor. Thesis advisor