VictorJuiz/thesis huggingface dataset:
Using optogenetics and advanced genetic techniques to study the nervous system

Clinical and research efforts have focused on promoting functional recovery after stroke. Brain stimulation strategies are particularly promising because they allow direct manipulation of the target area’s excitability. However, elucidating the cell type and mechanisms mediating recovery has been difficult because existing stimulation techniques non-specifically target all cell types near the stimulated site. To circumvent these barriers, we used optogenetics to selectively activate neurons that express channelrhodopsin (ChR2) and demonstrated that selective neuronal stimulations in the ipsilesional primary motor cortex (iM1) can promote functional recovery. Stroke mice that received repeated neuronal stimulations exhibited significant improvement in cerebral blood flow and the neurovascular coupling response, as well as increased expression of activity-dependent neurotrophins in the contralesional cortex, including brain-derived neurotrophic factor (BDNF), nerve growth factor (NGF) and neurotrophin 3 (NTF3). Western analysis also indicated that stimulated mice exhibited a significant increase in the expression of the plasticity-associated marker GAP43. Moreover, iM1 neuronal stimulations promoted functional recovery, as stimulated stroke mice showed faster weight gain and performed significantly better in sensory-motor behavior tests. Interestingly, stimulation in normal mice did not alter motor behavior or neurotrophin expression, suggesting that the pro-recovery effect of selective neuronal stimulations is dependent on the post-stroke environment. These results demonstrate that stimulation of neurons in the stroke hemisphere is sufficient to promote recovery.
Microtubule polarity plays an instructive role in protein trafficking and is highly conserved across species. The study of microtubule polarity in neurons is particularly interesting because the minus-end is known to be free-floating rather than embedded in a microtubule-organizing center. Previous works indicate that intrinsic cues like microtubule-binding proteins either selectively transport or selectively stabilize microtubules in neuronal processes. However, this study suggests that extrinsic cues like morphogen gradients may also play a critical role. In particular, we show that the UNC-6/Netrin signaling pathway, as well as the WNTs signaling pathway, are important in regulating the microtubule polarity of the sensory neurons in the tail of the worm. We propose that UNC-6 acts via the UNC-40 receptor to regulate UNC-73, while EGL-20 and LIN-44 (members of the WNTs family of proteins) act redundantly to activate UNC-73 via the LIN-17 receptor. UNC-73 then activates downstream genes that function to establish microtubule polarity. Thus, it is the bi-directionality of morphogen gradients that encode information about microtubule polarity.

Keywords:  Department of Biology
optogenetics
microtubule polarity
brain
neurons
mice
C. elegans
biology
developmental neurobiology
stroke
neurosurgery
Thesis
Advisor: Shen Kang
Luo Liqun
The vacuum Einstein constraint equations on manifolds with ends of cylindrical type [electronic resource]

This dissertation concerns the vacuum Einstein constraint equations on manifolds possessing end regions which are asymptotically periodic, including the special case where the ends are conformally asymptotically cylindrical. We will first apply the conformal method to construct a large class of vacuum initial data on any such manifold with positive Yamabe invariant, and then extend these existence results to manifolds which may also have asymptotically Euclidean ends. We will also show that, in the conformally asymptotically cylindrical case, any solution to the constraints one obtains via the conformal method which preserves the end geometry must have a unique asymptotic limit. Finally, we describe two different approaches to gluing generic asymptotically periodic initial data sets end-to-end, thereby allowing us to construct a large family of initial data sets with ``long neck'' regions.

Keywords: Mathematics.
Advisor: Mazzeo Rafe primary advisor. Thesis advisor
Schoen Richard (Richard M.) advisor. Thesis advisor
Vasy András advisor. Thesis advisor
Valid inference after data snooping [electronic resource]

This dissertation consists of three unrelated parts: - Only Part I is related to the title of this thesis, Valid inference after data snooping. It provides a unified framework for understanding the flurry of recent work in post-selection inference, unifying the three goals of estimation, testing, and confidence intervals. I have attempted to provide a clean exposition of the motivation, theoretical results, and algorithms. - Part II is a collection of two published IEEE conference papers relating to statistics and audio signal processing. Both papers study low-rank models of audio spectrograms. - Part III describes the design of OHMS, an online homework system I designed and developed with Naftali Harris. This will hopefully be useful to people wishing to use and improve upon our open-source system. Details on how to obtain our code can be found in the Appendix.

Keywords: Statistics.
Advisor: Smith Julius O. (Julius Orion) primary advisor. Thesis advisor
Taylor Jonathan
Walther Guenther advisor. Thesis advisor
The visible college [electronic resource] : how social network analysis informs our understanding of knowledge production and exchange in the university

This dissertation uses social network analytical techniques to illuminate questions of central interest to higher education scholars. In it, I investigate the role that the university, as a formal organization, plays in knowledge creation, with particular focus on interdisciplinary research, asking how interdisciplinary research centers shape the lives of faculty and the organizational form of the university. The first chapter reviews the existing literature applying social network analysis in higher education, and then maps the network of co-citations among papers in this domain, providing a picture of where links are strongest and where gaps remain. Chapters 2 and 3 examine the interplay between the network of collaborative relations among faculty members and the organizational form of the university, touching on questions of university governance, faculty productivity, and knowledge creation. These chapters examine how interdisciplinary centers bring colleagues together in new collaborations, how they position faculty members within the social structure of the university, and whether they influence the content of the work scholars produce. Social network analysis (SNA), I argue, provides unique traction on these issues. Through this dissertation, I explore the potential of SNA methods to deepen our understanding of higher education, of knowledge production and exchange, and of the university as a formal organization.

Keywords: Education.
Advisor: McFarland Daniel (Daniel A.) primary advisor. Thesis advisor
Parigi Paolo
Willinsky John
Visual learning with weakly labeled video [electronic resource]

With the rising popularity of Internet photo and video sharing sites like Flickr, Instagram, and YouTube, there is a large amount of visual data uploaded to the Internet on a daily basis. In addition to pixels, these images and videos are often tagged with the visual concepts and activities they contain, leading to a natural source of weakly labeled visual data, in which we aren't told where within the images and videos these concepts or activities occur. By developing methods that can effectively utilize weakly labeled visual data for tasks that have traditionally required clean data with laborious annotations, we can take advantage of the abundance and diversity of visual data on the Internet. In the first part of this thesis, we consider the problem of complex event recognition in weakly labeled video. In weakly labeled videos, it is often the case that the complex events we are interested in are not temporally localized, and the videos contain varying amounts of contextual or unrelated segments. In addition, the complex events themselves often vary significantly in the actions they consist of, as well as the sequences in which they occur. To address this, we formulate a flexible, discriminative model that is able to learn the latent temporal structure of complex events from weakly labeled videos, resulting in a better understanding of the complex events and improved recognition performance. The second part of this thesis tackles the problem of object localization in weakly labeled video. Towards this end, we focus on several aspects of the object localization problem. First, using object detectors trained from images, we formulate a method for adapting these detectors to work well in video data by discovering and adapting them to examples automatically extracted from weakly labeled videos. Then, we explore separately the use of large amounts of negative and positive weakly labeled visual data for object localization. With only negative weakly labeled videos that do not contain a particular visual concept, we show how a very simple metric allows us to perform distributed object segmentation in potentially noisy, weakly labeled videos. With only positive weakly labeled images and videos that share a common visual concept, we show how we can leverage correspondence information between images and videos to identify and detect the common object. Lastly, we consider the problem of learning temporal embeddings from weakly labeled video. Using the implicit weak label that videos are sequences of temporally and semantically coherent images, we learn temporal embeddings for frames of video by associating frames with the temporal context that they appear in. These embeddings are able to capture semantic context, which results in better performance for a wide variety of standard tasks in video.

Advisor: Koller Daphne primary advisor. Thesis advisor
Li Fei Fei
Savarese Silvio advisor. Thesis advisor
Visual scene perception in the human brain [electronic resource] : connections to memory, categorization, and social cognition

The human visual system faces a monumental data processing challenge: using about a pound of slow, inexact biological processors, it must analyze the barrage of constantly-shifting light patterns hitting the eye and quickly extract a stable, high-level model of the environment around us. Almost every piece of this process is mysterious: exactly what information is being gleaned from the visual signal, how this information is represented, and how this processing is implemented in neural circuits. Despite the superiority of silicon computers for most big-data processing, our emulations of the human visual system are still rudimentary, and can capture only basic information from visual images such as which objects are present. In this work, I describe a number of projects toward understanding higher-level processing of visual scenes. The first examines the neural basis of understanding human-object interactions, showing how an emergent property of a scene (created by the interaction of two scene parts) can activate representations in social cognition regions. The second investigates how scenes are categorized, arguing that one of the fundamental features encoded about a scene is the type of actions which could be performed in that environment. Finally, I present a large body of work on how scene processing interacts with long-term memory systems. These chapters describe several novel types of mathematical models for measuring connections between brain regions, and end with a new organizing proposal for scene perception regions.

Advisor: Li Fei Fei
Beck Diane (Neuroscientist) advisor. Thesis advisor
Liang Percy advisor. Thesis advisor
Visual word recognition with large-scale image retrieval [electronic resource]

OCR techniques that were developed for scanned high-resolution images suffer from poor text recognition accuracy on camera images. In this dissertation, we cast text recognition as a word patch retrieval problem. By comparing visual text queries against a database of labeled word images, we demonstrate a text recognition system that achieves significantly improved performance on camera images. Robust visual text features are the foundation for optimal word patch retrieval. We introduce Text Aggregated Gradients (TAG), a visual text descriptor discriminatively learned using easily obtainable training data. At the query stage, query words can be accurately recognized via Approximate Nearest Neighbor search. In the interest of system scalability to a large number of fonts, a font recognition method is developed to facilitate fast query retrieval. We show that by employing a Bayesian network, surprisingly good font recognition accuracy can be achieved via probabilistic inference. A compact database is highly desirable for our large-scale word patch retrieval. To eliminate inter-font redundancies from the database, we perform feature aggregation within groups of similar fonts. Using Canonical Correlation Analysis, our database can be compressed by a factor of 5x without any loss of word retrieval accuracy.

Keywords: Electrical Engineering.
Advisor: Girod Bernd primary advisor. Thesis advisor
Guibas Leonidas J. advisor. Thesis advisor
Pauly John (John M.) advisor. Thesis advisor
A wall of many heights [electronic resource] : the uneven enforcement of the Canadian-United States border

This dissertation examines the creation, demarcation, and enforcement of the Canadian-United States border from the American Revolution until 1924. Although diplomats often viewed the division between national spaces as a clean and uniform line, the Canadian-United States border is better understood as a series of interlocking, uneven, and inconsistent walls. Federal administrators created national border policy, but local agents dictated the practical impacts this policy could have. Inconsistent policy decisions ensured that the border closed at different times in different regions and created an uneven set of impositions on borderland communities. As a result, federal border policy cannot be understood by looking at a single racial, ethnic, or tribal group. Europeans, Chinese, African Americans, Cree, Sioux, Nez Perce, Métis, Stó:lō, Haida, Ojibwe, and Iroquois all experienced the impacts of border closure in different ways and to different extents.

Keywords: History.
Advisor: White Richard
Camarillo Albert advisor. Thesis advisor
Snipp C. Matthew advisor. Thesis advisor
The wandering sage [electronic resource] : Zhi Dun's (314-366) life and thought in multiple contexts

This dissertation explores the life and philosophy of the Chinese Buddhist monk-scholar Zhi Dun (314--366). Zhi Dun was a leading Buddhist figure who represented "gentry" Buddhism in South China in the Six Dynasties era (220--589). He was a celebrity who had broad social relationships with notables of his time; he was one of the most prominent representative figures of his time. Zhi Dun's philosophy combined Buddhist and indigenous Chinese thought, including Daoism and Confucianism. Despite Zhi Dun's contribution to the development of early Chinese Buddhism by propagating Buddhist teaching, his life and thought have received much less attention from scholars than those of contemporary eminent monks such as Dao'an (312--385), who represented Buddhism in North China at the time. Above all, Zhi Dun's Buddhism, which was strongly influenced by native traditions of thought, has often been understood as reflecting an immature stage of early Chinese Buddhism in the Six Dynasties era, when the Chinese people attempted to understand Buddhism through the lens of indigenous thought. This dissertation reassesses Zhi Dun and his Buddhism by examining his life and philosophy in multiple contexts and backgrounds of his time, including socio-political, intellectual, and cultural contexts/backgrounds. I assume that Zhi Dun's Buddhism, as well as early Chinese Buddhism more generally, cannot be understood apart from the various contexts of the era. Research on Zhi Dun's life and thought illuminates not only early Chinese Buddhism but also the Six Dynasties era, in which Buddhism played a significant role in developing the cultural and intellectual history of the era.

Keywords: Religious Studies.
Advisor: Bielefeldt Carl primary advisor. Thesis advisor
Kieschnick John
Yearley Lee H. advisor. Thesis advisor
A wavefront coded light field microscope [electronic resource]

Light field microscopy is a high-speed computational imaging method, which enables reconstruction of a 3-dimensional volume from a light field image. Unlike standard imaging systems, the light field microscope uses a microlens array to capture both spatial and angular information about the incoming light in a single image, from which a volume can be reconstructed computationally. Among volumetric imaging methods in microscopy, light field microscopy is unique in that it allows imaging large volumes, spanning hundreds of microns in depth, at a speed limited only by the camera frame rate. Due to this unique advantage it has recently been adapted to in vivo imaging of neural activity, enabling biologists a glimpse into an organism's brain while in action. Despite its advantages, the light field microscope still suffers from a major limitation - its lateral spatial resolution is not uniform across depth. Some depths, particularly at the center of the imaged volume, where the microscope is focused at, show very low resolution which hinders its use in applications. This non-uniform resolution stems from the way the light field microscope samples the volume: at the center of the volume samples are angularly discriminative but spatially redundant, hence for isotropically absorptive or emissive volumes, they cannot support high resolution reconstructions. We present a method that, for such isotropic volumes, significantly improves the resolution profile of the light field microscope across depth and enables accurate control over it, thereby overcoming the limitations of traditional light field design. The key to our approach is using a technique called wavefront coding to control properties of the point spread function of the microscope. By including phase masks in the optical path we a create a wavefront coded light field microscope that samples the 3-dimensional volume more uniformly than the standard light field microscope, solving the low resolution problem at the center of the imaged volume and improving the resolution at its borders. We derive an extended optical model for the wavefront coded light field microscope and propose design guidelines and a performance metric which we use to choose adequate parameters for good phase masks. To validate our approach, we show simulated data and experimental resolution measurements, and demonstrate the wavefront coded light field microscope's utility for biological applications.

Keywords: Electrical Engineering.
Advisor: Levoy Marc primary advisor. Thesis advisor
Dror Ron
Horowitz Mark
Wavelength demultiplexing using multilayer structures with frustrated total internal reflection [electronic resource]

Wavelength division multiplexing (WDM) has been the primary technique used to increase fiber channel capacity to keep up with the increasing information demands of modern society. WDM enables one to multiply existing channel capacity without having to install new fibers. The increased channel capacity is usually accompanied by the need to use more complex (more expensive) transmitters and receivers; this complexity has currently limited WDM primarily to long-haul optical networks. With optical links replacing electrical links at shorter length-scales all the way down to the chip level (silicon photonics), the need for compact, energy efficient devices for WDM arises. Conventional devices used for WDM either require long path lengths (e.g. arrayed waveguide gratings) or rely on resonators (microring-based devices) that require on-chip tuning, which can be highly energy-intensive. In this thesis, we discuss the design of multilayer structures that employ frustrated total internal reflection (frustrated TIR) to successfully demultiplex wavelengths in the telecommunication bands without relying on long paths or resonances. The devices are designed using materials compatible with the CMOS platform, which is essential for large scale integration. We believe frustrated TIR-based devices can serve as a viable alternative to conventional resonator-based approaches and open up a new design space for silicon photonics.

Keywords: Electrical Engineering.
Advisor: Miller D. A. B. primary advisor. Thesis advisor
Fan Shanhui
Vuckovic Jelena advisor. Thesis advisor
Waves and turbulence in aquatic canopies [electronic resource]

For this dissertation, three major topics were explored, each related to submerged aquatic canopies exposed to waves. The first topic was the dynamics of flexible vegetation, specifically how models of wave attenuation can account for flexibility of submerged plant communities. A model for dynamic simulation of a single flexible element exposed to waves was developed and validated through laboratory experiments. The model demonstrated that, despite the presence of chaotic motion, most of the attenuation of mean energy occurs when the element is nearly stationary and has a predictable orientation. Based on this result, an algebraic model with a simple set of parameters was developed for predicting wave attenuation by flexible vegetation. The second topic was the modeling of velocity profiles in wave-driven flows over canopies. High resolution canopy flow measurements were used to determine the hierarchy of momentum budget terms, to test parameterizations for terms in the momentum and turbulent kinetic energy budgets, and to validate a simple 1-D model for predicting velocity profiles. The Reynolds stress was found to be less important in the momentum budget for wave driven flows than previously thought, indicating that relatively simple models can be effective at predicting velocity profiles. The 1-D model developed in this study was designed to be straightforward to implement either in experimental studies of canopy flows or in large scale numerical models. The third topic was the small-scale horizontal variability of the flow within a wave-exposed canopy. An innovative experimental approach was used to fully resolve the in-canopy flow. The resulting data was used to evaluate the possibility of leveraging the self-similarity of element wakes to account for small-scale variability. This approach was found to be effective under certain conditions. When the flow was nearly quasi-steady and 2-D, the behavior was found to be approximately self-similar. In addition some flow statistics were better characterized by self-similarity than others. The results of this study may act as guidelines for how to approach the development of parameterizations for small-scale variability based on self-similarity in future studies.

Keywords: Civil and Environmental Engineering.
Advisor: Koseff Jeffrey Russell primary advisor. Thesis advisor
Fong Derek advisor. Thesis advisor
Fringer Oliver B. (Oliver Bartlett) advisor. Thesis advisor