VictorJuiz/thesis huggingface dataset:
Tribulation and Repair: Islamic Humanitarianism after the Syrian War

This dissertation is an ethnography of refuge, religion, and repair in the aftermath of violence and dispossession. Based in fifteen months of fieldwork with refugees and aid workers in Jordan and Canada, it considers the field of “Islamic humanitarianism” writ large in the wake of the Syrian civil war. I include under that name Quranic pedagogy and cultural translation, dramatic reenactments and poetic elegies, furniture drives and legal paperwork. What unites these heterogeneous elements is not a set of principles or theological doctrine, far less the institutional divisions of the international humanitarian regime, but their engagement by those compelled to act after the Syrian war. The forms of such action are modulated by my interlocutors’ inhabiting the tradition of Islam. Their struggle to inherit the sensibilities of this tradition is what articulates their practices of care./nPart One (The Grammar of Tribulation) ethnographically follows diverse figures of tribulation in conversation with four primary interlocutors, each of whom is engaged in projects of communal repair. They each understand the displacements of the war as a divine trial marking an existential corruption. The interlude lingers with the life of one man who lives at the Jordan-Syria border. Once an imam in Daraa, at the mosque celebrated as the birthplace of the Syrian revolution, then tortured and hunted by the Syrian regime, he now serves as steward of an orphanage funded by an Islamic charity. His practices of memory and of witness emerge in the hiatus between tribulation and repair. Part Two (Poetics of Repair) turns more directly to the sites of Islamic humanitarianism, albeit with a view not to empirically cataloging its transnational sector but to surveying some of its themes: solidarity (community in question); translation (universal vs. particular humanitarianisms); representation (the ambiguous power of images); and pedagogy (inheriting Islamic sensibilities). The dissertation is framed by two ethnographic sections that focus on the shifting temporal horizons—ruin and hope, despair and disclosure—afforded my interlocutors through their inhabitation of the Islamic tradition in the time of the war.

Advisor: Hirschkind, Charles
Tuning Cooperative Interactions in Redox-Active Metal-Organic Frameworks for Gas Adsorption

The discovery of permanent porosity in metal–organic frameworks has ushered in many developments towards the application of these materials for gas separations and storage. The work in this dissertation describes efforts to design and target redox-active metal–organic frameworks for gas separations and storage, such as O2 adsorption, O2/N2 separations, and NO adsorption. The usage of structural characterization, in particular by powder X-ray diffraction, to better understand adsorption in metal–organic frameworks is highlighted.

Advisor: Long, Jeffrey R
Is the Musical Disabled?

While there have been many studies of musical theater’s affinity to various marginalized cultural identities, such as gay or Jewish ones, there is less scholarly discussion of the genre’s relationship specifically to disability cultures and identities. In this dissertation I examine three oft-discussed aspects of musicals – gayness, Jewishness, and duality – each through the lens of disability, to reveal disability’s significance to the genre. Casting discrimination, the ubiquity of ableist tropes, and the over-categorizing of the visibly impaired body all contribute to the detrimental shortage of disabled performers and disability perspectives in productions of mainstream musicals. Casting more disabled talent in mainstream musicals, especially in “regular” roles, promotes disability justice, deepens the truth and reach of such productions, and transforms the musical genre as a whole to be more in resonance with itself.

Advisor: Chen, Mel Y
De Kosnik, Abigail
Evergreening At-Risk

Brand-name pharmaceutical manufacturers leverage patent protection, regulatory loopholes, and the atypical economics of the prescription drug market to strengthen and prolong market exclusivity for their products. These phenomena, commonly known as “evergreening,” are among the most pressing and unsolved public policy challenges on the national agenda. With far-reaching implications on public health, social justice, and innovation policy, the evergreening epidemic has captured growing attention from Congress, the president, the judiciary, regulatory authorities, and the general public. Irrespective of nationwide uproar, the concept of evergreening remains surprisingly misunderstood and grossly undertreated. This article fills these gaps. First, this article defines evergreening—thus far a confused and obscure concept—as a problem of skewed overpatenting incentives. It explains how brand-name manufacturers leverage follow-on “improvement” patents to strengthen and prolong market exclusivity for existing drugs. In light of this leverage, brand-name manufacturers’ incentives to pursue improvement patents far exceed the social value of such improvements. Then, inspired by generic manufacturers’ “at-risk” market launches, this article proposes an original remedial approach to scale back brand-name manufacturers’ overpatenting incentives. When generic manufacturers venture into the drug market to compete with a branded drug that is still under patent protection, they expect to earn generous duopoly profits alongside brand-name manufacturers. At the same time, however, they also risk losing these profits if an infringement lawsuit materializes against them and the challenged patents are proved valid and infringed. Mirroring this logic, this article proposes that brand-name manufacturers be required to evergreen at risk. Thus, brand-name manufacturers making monopoly profits by enforcing follow-on patents that prolong market exclusivity for existing drugs, would also expect to lose these additional profits if the challenged patents are subsequently proved invalid. Instead, these wrongly obtained monopoly profits would be vested with the first generic manufacturer to successfully invalidate the patent and open the market to price-reducing competition. This approach aligns the divergent interests of brand-name and generic manufacturers with the social interest—enforcing follow-on patents that are likely to cover nontrivial improvements while invalidating those patents that are likely to cover trivial improvements.

Advisor: Menell, Peter S.
Coded Illumination for Multidimensional Quantitative Phase Microscopy

Phase contrast microscopy reveals transparent objects under optical microscopes, and has been widely used for biomedical imaging. Combining specially-designed optics and computational post-processing of the raw acquisitions, quantitative phase imaging (QPI) can convert qualitative phase contrast into physical quantities, such as optical phase delay or refractive index (RI) of the object. A common way to achieve QPI is by creating interference between the scattered light from the object and a reference wave, using coherent illumination. However, the method suffers from low resolution and strong speckle noise, and it is difficult to implement interferometry in off-the-shelf microscopes. In this work, we develop QPI methods for commercial microscopes, with coded illumination. Using a programmable light source (e.g. an LED array) that generates partially coherent illumination, many multidimensional QPI techniques can be implemented on a commercially-available microscope without the drawbacks mentioned above. First, differential phase contrast (DPC) microscopy using wavelength-multiplexing is presented, which achieves real-time QPI up to the incoherent resolution limit. Second, quantitative phase and system aberrations are simultaneously encoded in the measurements by alternating between spatially coherent and spatially partial coherent illumination. Absorption and phase of the object, as well as the spatially varying aberrations, can then be resolved computationally. Third, a through-focus DPC microscopy is proposed in order to extend QPI to 3D. The 3D RI of the object is recovered after performing a 3D deconvolution. Finally, most of the existing 3D QPI methods, including 3D DPC, work under the weakly scattering assumption. Hence, they fail to reconstruct accurate RI when multiply scattered light dominates in the captured data. To mitigate artifacts and obtain accurate information of multiple-scattering objects, a new light scattering model is introduced along with an algorithm that solves the non-linear phase retrieval problem. The multiple-scattering model outperforms the traditional weakly scattering models while requiring similar computation cost. As a result, high resolution Giga-voxel 3D phase imaging with multiple-scattering objects is achieved.

Advisor: Waller, Laura
Metastability of Zero Range Processes

This dissertation is about the metastability of a condensed zero range process on a fixed finite set. Most of the time, nearly all particles of this zero range process are at one single site. The site of condensate asymptotically behaves as a Markov chain. This is proven for the reversible case, for the totally asymmetric case, and for the non-reversible case using the martingale approach which requires precise estimates of capacities. We prove the metastability of zero range processes on a fixed finite set with an approach using solutions of Poisson equations. By this approach, we circumvent precise estimates of capacities and prove the metastability for both reversible and non-reversible cases.

Advisor: Rezakhanlou, Fraydoun
Efficient Deep Neural Networks

The success of deep neural networks (DNNs) is attributable to three factors: increased compute capacity, more complex models, and more data. These factors, however, are not always present, especially for edge applications such as autonomous driving, augmented reality, and internet-of-things. Training DNNs requires a large amount of data, which is difficult to obtain. Edge devices such as mobile phones have limited compute capacity, and therefore, require specialized and efficient DNNs. However, due to the enormous design space and prohibitive training costs, designing efficient DNNs for different target devices is challenging. So the question is, with limited data, compute capacity, and model complexity, can we still successfully apply deep neural networks?/nThis dissertation focuses on the above problems and improving the efficiency of deep neural networks at four levels. Model efficiency: we designed neural networks for various computer vision tasks and achieved more than 10x faster speed and lower energy. Data efficiency: we developed an advanced tool that enables 6.2x faster annotation of a LiDAR point cloud. We also leveraged domain adaptation to utilize simulated data, bypassing the need for real data. Hardware efficiency: we co-designed neural networks and hardware accelerators and achieved 11.6x faster inference. Design efficiency: the process of finding the optimal neural networks is time-consuming. Our automated neural architecture search algorithms discovered, using 421x lower computational cost than previous search methods, models with state-of-the-art accuracy and efficiency.

Advisor: Keutzer, Kurt W
Development of Genetically Targeted Voltage Sensitive Dyes

Comprehensively mapping and recording the electrical inputs and outputs of multiple neurons simultaneously with cellular spatial resolution and millisecond time resolution remains an outstanding challenge in the field of neurobiology. Development of fluorescence indicators for direct visualization of membrane potential changes offers a powerful method for probing voltage dynamics in neurons with unprecedented spatial and temporal resolution. Despite the promise of voltage imaging, key challenges of speed, sensitivity, brightness, and localization remain. The Miller lab has developed a new class of small molecules dyes, VoltageFluors (VF), that rely on photoinduced electron transfer (PeT) and display voltage-sensitive fluorescence due to modulation of the rate of PeT within the VF scaffold by the transmembrane electric field. This approach allows for fast, sensitive and non-invasive recording of neuronal activity in cultured mammalian neurons and in ex vivo tissue slices in single trials. One major limitation of small-molecule dye imaging is the inability to target the dye to specific cells of interest, which significantly erodes signal to noise and cellular resolution. To solve this problem, we have worked to combine VF dyes with a genetically encoded component to enable high-contrast imaging in defined neurons. We first attempted a fluorogenic approach, in which the parent VF dye is chemically modified to be minimally fluorescent and non-voltage-sensitive and must be enzymatically activated prior to imaging. We designed a couple of dyes which can only be activated by a cell-surface pig liver esterase (PLE) and observed enhanced contrast in both HEK cells and cultured neurons with good sensitivity. We have also shown that our genetically targeted voltage dyes outperform purely genetically encoded voltage indicators. In addition, we are exploring other enzyme/substrate pair for fluorogenic activation purpose. The second approach is covalent labeling of voltage sensitive dye to cells of interest using a cell-surface HaloTag enzyme. We have successfully demonstrated selective membrane staining in mouse brain slices and live animal using this strategy. Current efforts focus on applying this method for targeted voltage imaging in live animals to probe specific neuroscience questions.

Advisor: Miller, Evan W
Placing the preinitiation complex at the promoter

Transcription is the process of copying the genetic code and producing functional intermediates or readable instructions. The transcription of protein coding genes produces messenger RNA which the cell uses to synthesize proteins that carry out various functions. In this way the process of transcription initiation is a major determinant of cell fate as it controls which genes will be transcribed./nThe main subject of this thesis will look at how human TFIID binds the core promoter and subsequently aids in the assembly of the transcription preinitiation complex. Early work on TFIID had shown that the complex binds the promoter at two distinct sites, a large region downstream of the transcription start site and a smaller region upstream. Subsequent studies found several conserved sequences within the core promoter such as the TATA-box, downstream promoter element, initiator and motif ten element. Structural studies of TFIID have revealed that the complex adopts a trilobed structure that undergoes a dramatic rearrangement upon promoter binding. Through these works and others, a great deal about the function of TFIID has been revealed, however the underlying mechanism by which TFIID binds the promoter and subsequently recruits RNA polymerase II remained missing. This thesis attempts to address these last two questions./nUsing a combination of biochemical reconstitution, chemical crosslinking mass spectrometry, and electron microscopy I have been able to determine the complete architecture of TFIID and how it loads TBP onto the promoter. The structure of TFIID contains an asymmetric dimer at its core that forms a scaffold which the rest of the complex assembles upon. It was also found that TFIID initially binds the downstream promoter, and then subsequently rearranges to load TBP onto the TATA-box with the help of TFIIA. From this model we can begin to rationalize how TFIID integrates information from histone marks on the downstream +1 nucleosome and upstream activators./nWhile working with TFIID and other samples a common issue has been preferred sample orientation on the grid. This issue has led to artefacts in the reconstruction due to missing information. To overcome this issue, I have developed a reliable method to coat gold foil EM grids with graphene oxide. These grids can be used to collect tilted images which can produce high resolution isotropic reconstructions as they do not suffer large amounts of drift.

Advisor: Nogales, Eva
Structure, Dynamics, and Information Flow Across Brain States

A key challenge in neuroscience is to synthesize our understanding of neural structure, dynamics, and information processing in both health and disease. While substantial progress has been made toward such a synthesis at the microscopic scale of single neurons and their connections, signicant work remains to be done at the macroscopic scale of interacting brain regions. While the eld has successfully mapped the macroscale connections bridging cortical columns and regions, and has also systematically described basic features of macroscale cortical electrodynamics across perceptual, cognitive, and brain states, neuroscientists still currently lack a mathematically-specic understanding of how these macroscale networks and electrodynamics underpin large-scale neural computation and communication. Toward the end of advancing our mathematical understanding of this relationship between large-scale brain networks, dynamics, and information ow, we here present: a tool for quantifying, in bits, how much information is integrated across large-scale brain networks; a tool for tracking the presence and degree of chaos in neural electrodynamics; and evidence that macroscale cortical circuits optimize their information-carrying capacity during conscious states by operating near edge-of-chaos criticality.

Advisor: D'Esposito, Mark
Optical Studies of Electron-Phonon Interactions in Two-Dimensional and One-Dimensional Materials

Reduced-dimensionality nanostructures have long attracted interest in the physics and materials science communities. Zero-dimensional structures such as quantum dots, one-dimensional structures such as carbon nanotubes, and two-dimensional materials such as graphene and transition metal dichalcogenides have all exhibited unique properties as a result of their dimensionality and quantum confinement. Optical spectroscopy has proven to be a versatile tool to study and characterize these materials. Linear optical measurements such as absorption and photoluminescence, scattering measurements such as Raman spectroscopy, nonlinear measurements such as higher harmonic generation, and ultrafast time-resolved measurements have all provided extensive information about the electronic and optical properties and dynamics of nanomaterials./nMany nanomaterials possess strong electron-phonon coupling, which can affect their optical and electronic properties. Here, we employ various optical spectroscopies to investigate electron-phonon interactions in nanomaterials. First, we study the coupling between the electronic valley degree of freedom and Raman scattering in monolayer MoS2, a semiconducting transition metal dichalcogenide. We find that the valley optical selection rules on exciton resonances can affect Raman scattering by modifying the Raman selection rules expected from the symmetry of the material. Second, we study exciton-phonon coupling in semiconducting carbon nanotubes by performing optical Stark spectroscopy. We observe a strong phonon-mediated optical Stark effect in the nanotubes, which enables us to quantify the interactions between phonon-dressed states and exciton states. These studies show that optical spectroscopy is an effective tool to probe electron-phonon interactions in reduced-dimensionality materials.

Advisor: Wang, Feng
Molecular and Cellular Mechanisms of Pain and Itch in the Mammalian Peripheral Nervous System

Two main questions drove my PhD research: 1) what are the molecules in the peripheral nervous system that are important for touch, pain, and itch; and 2) how do different cell types in the periphery (namely immune cells, skin cells, and neurons) interact in chronic pain and itch. To address the first question, I mined several transcriptomic datasets from our lab and others, and uncovered the sphingosine 1-phosphate (S1P) signaling pathway as a candidate mediator of somatosensation. I uncovered an essential role for endogenous, baseline levels of S1P and S1P Receptor 3 (S1PR3) signaling in setting mechanical pain thresholds. I demonstrated that S1PR3 modulates activity KCNQ2/3 potassium channels in mechanical pain neurons to increase neuronal excitability. This study was the first to identify a molecule selectively required for baseline mechanical pain sensation. In addition to this necessary role for S1P in setting mechanical pain thresholds, I found that elevated levels of S1P, observed in inflammatory itch and pain disorders, triggers nociceptor activation and itch/pain behaviors in mice. Using a variety of genetic, physiological, pharmacological, and behavioral approaches, I showed that elevated S1P evokes itch and pain in a dose-dependent manner via two distinct molecular pathways dependent upon Transient Receptor Potential (TRP) ion channels in discrete subsets of itch- and pain-sensing somatosensory neurons. This study revealed a detailed molecular understanding of how a single ligand/receptor can engage in distinct pain and itch signaling pathways in the periphery. Moreover, using an engineered S1P molecule containing an azobenzene photoswitch, I showed that S1P-dependent nociceptor activation and pain hypersensitivity behaviors could be rapidly activated and inactivated with light./nWith respect to the second research question, I sought to unravel the complex molecular and cellular pathways underlying the development of chronic itch in atopic dermatitis (eczema). Using RNA-seq of tissues at key time points in a mouse model of chronic itch, I identified molecules and cells associated with the development of atopic dermatitis in skin, spinal cord, and somatosensory ganglia. These data implicate neutrophils in the pathogenesis of atopic dermatitis. Antibody-mediated depletion of neutrophils significantly attenuated itch-evoked scratching behaviors in our mouse model of chronic itch. Neutrophils were also required for induction of several key hallmarks of chronic itch, including inflammatory cytokines, skin hyperinnervation, itch signaling molecules, and activity-induced genes and markers of neuropathic itch. Finally, I demonstrated that induction of CXCL10, a chemokine and ligand of the CXCR3 receptor that promotes itch via activation of sensory neurons, is neutrophil-dependent. Moreover, CXCR3 antagonism attenuated chronic itch across multiple time points of the model. Taken together, these findings show that neutrophils promote the transition from acute to chronic itch via induction of CXCL10/CXCR3 signaling.

Advisor: Bautista, Diana